Barrier systems for environmental contaminant containment and treatment

BARRIERSYSTEMS for

ENVIRONMENTALCONTAMINANTCONTAINMENTand TREATMENT

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BARRIERSYSTEMS for

ENVIRONMENTALCONTAMINANTCONTAINMENTand TREATMENT

Edited by

Calvin C. Chien • Hilary I. InyangLorne G. Everett

Published in 2006 byCRC PressTaylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300Boca Raton, FL 33487-2742

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Barrier systems for environmental contaminant containment and treatment / contributing editors, Calvin C. Chien, Hilary I. Inyang, Lorne G. Everett ; prepared under the auspices of U.S. Department of Energy, U.S. Environmental Protection Agency, DuPont.

p. cm.Includes bibliographical references and index.ISBN 0-8493-4040-3 (alk. paper)1. In situ remediation. 2. Sealing (Technology) I. Chien, Calvin C. II. Inyang, Hilary I. III. Everett,

Lorne G. IV. United States. Dept. of Energy. V. United States. Environmental Protection Agency. VI. E.I. du Pont de Nemours & Company.

TD192.8.B375 2005628.5--dc22 2005047215

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4040_Discl.fm Page 1 Monday, September 26, 2005 11:08 AM

Contributing Editors

Calvin C. Chien, Ph.D., P.E.

DuPont FellowDuPontWilmington, Delaware

Hilary I. Inyang, Ph.D.

Duke Energy Distinguished Professor and Director,Global Institute for Energy and Environmental SystemsUniversity of North Carolina, Charlotte, North Carolina

Lorne G. Everett, Ph.D., D.Sc.

PresidentL. Everett and Associates, LLCSanta Barbara, California

Prepared under the auspices ofU.S. Department of EnergyU.S. Environmental Protection AgencyDuPont

With contributions by renowned experts on waste containment and waste treat-ment science and technology

2005

Technical Review Board

David E. Daniel, Ph.D., Overall Book Reviewer

University of IllinoisUrbana-Champaign, Illinois

Skip Chamberlain

U.S. Department of EnergyWashington, DC

Calvin C. Chien, Ph.D., P.E.

DuPontWilmington, Delaware

Annette M. Gatchett

U.S. Environmental Protection AgencyWashington, DC

Hilary I. Inyang, Ph.D.

University of North CarolinaCharlotte, North Carolina

Lorne G. Everett, Ph.D., D.Sc.

L. Everett and Associates, LLCSanta Barbara, California

Brent E. Sleep, Ph.D.

University of TorontoToronto, Ontario, Canada

Craig H. Benson, Ph.D., P.E.

University of WisconsinMadison, Wisconsin

Ernest L. Majer, Ph.D.

Lawrence Berkeley LaboratoryBerkeley, California

David J. Borns, Ph.D.

Sandia National LaboratoriesAlbuquerque, New Mexico

Special Contributors

Jada M. Kanak, Special Technical Assistant


Kathy O. Adams, Contract Technical Writer


Introduction

Significant advances in subsurface containment technology occurred in the 1990s,both with the improvement of the technology and the broader acceptance andapplications as a measure for environmental remediation. Since 1995, the U.S.Department of Energy (USDOE), U.S. Environmental Protection Agency (USEPA),and DuPont have collaborated on a series of organized efforts to advance thistechnology. In that year, these collaborators sponsored an international expertworkshop that led to the publication of the first major book on containmenttechnology. Two international conferences were held by the same three partnersin 1997 and 2001, with individuals from all over the world attending.

Although subsurface containment technologies are becoming increasinglyacceptable and popular in the environmental remediation field, questionsremained on the prediction and verification of long-term barrier performance andthis subject began to gain interest from the public, government agencies, and theU.S. Congress. With funding provided by USDOE, an executive committee, con-sisting of Skip Chamberlain (Chairperson, USDOE), Calvin C. Chien (DuPont),and Annette M. Gatchett (USEPA), was formed in October 2001 to plan andorganize an expert workshop. Sixty invited international experts participated. Themeeting was held between June 30 and July 2, 2002 in Baltimore, Maryland, andconsisted of five discussion panels — three on prediction and two on verification.Each panel was led by a panel leader and a co-leader to address particulartechnical topics in a designated area. A designated graduate fellow, a graduatestudent whose research was related to these topics, recorded detailed notes forthe panel discussions. The graduate fellow group was coordinated and supervisedby Jada M. Kanak (DuPont). Each panel leader, assisted by the co-leader, wasresponsible for writing a chapter for this book, using the information generatedfrom the panel discussions and the detailed notes recorded by the graduatefellows. The prediction chapters were reviewed and edited by Hilary I. Inyang, andLorne G. Everett reviewed and edited the verification chapters. Calvin Chien hadthe responsibility for planning, coordinating, and editing the book, ensuring con-sistency and completeness, and resolving differences in opinions. Skip Chamberlainprovided technical input and crucial support in working with experts from thenational laboratories on critical issues during the preparation of the book. David E.Daniel (University of Illinois) conducted an initial review of the first draft andprovided high-level comments, which were useful in performing subsequentrevisions. Dr. Daniel also wrote the preface for the book, which provides anoutstanding introduction of containment technology history and book structure.Relevant new information that became available during the period of preparation

and editing was identified, evaluated, and added to the book to ensure that theinformation is as up-to-date as possible.

In addition to organizing and leading the graduate fellow group, Jada Kanakalso served as a special technical assistant for book preparation. Her detailed andpatient efforts in reviewing and checking all of the references, figures, and tablescontributed greatly to the quality of this book. Ms. Kathy O. Adams, a long-timeDuPont in-house contract technical writer, was responsible for ensuring the gram-matical accuracy of the book, and did an excellent job polishing the final draft.The team from Florida State University, consisting of Norbert Barszczewski,Sheryl A. Grossman, Loreen Y. Kollar, J. Michael Kuperberg, and Laymon L.Gray, were responsible for the workshop planning and contributed greatly to thesuccess of the meeting.

Preface

The containment of buried waste, contaminated soil or groundwater, refers to

in situ

(in place) management of contaminants in the subsurface. Containment isachieved with individual barriers or control technologies that, together, providea system of engineered control. Containment is potentially applicable to anycircumstance in which contaminants exist in the subsurface (e.g., uncontrolledlandfills or dumps, chemical spills or leaks, pond or lagoon contaminant seepage)and can provide a safe and highly cost-effective mechanism for environmentalcontrol. Containment is accomplished using physical, hydraulic, or chemicalbarriers that prevent or control the outward migration of contaminants.

Containment has come full circle as an acceptable environmental controltechnology over the past 30 years. Prior to the 1980s, containment was virtuallythe only technology available for managing subsurface contamination. Althoughsome wastes were exhumed and treated, more often than not, if the pollutionproblem was recognized at all, the problem was managed via containment. Duringthe 1980s, new environmental regulations emphasized treatment rather than con-tainment. Research and development during this time dramatically expanded theportfolio of options available for treating or destroying contaminants at pollutedsites. Technologies such as vapor extraction, oxidation, bioremediation, surfactantflushing, and heat-induced treatment became viable, though often expensive,treatment alternatives.

In the 1990s, a dose of reality swung the pendulum back toward containment.It became apparent that it was not technically feasible to return contaminatedsites to pristine condition. Further, as a nation, the United States came to realizethat it could not afford, nor did it need, the most sophisticated treatment technol-ogy available to manage pollution problems at every site effectively and safely.In addition, further research clearly showed that the subsurface has advantagesin addressing contamination problems — natural processes such as adsorptionand biodegradation can serve to contain or degrade contaminants. For certainmaterials such as radioactive wastes, it became apparent that the exposure risksassociated with exhuming contaminants might be far greater than risks associatedwith managing the wastes

in situ

with containment. Thus, for many reasons,interest in containment was revived in the 1990s. Today, containment thrives asa viable environmental management technology, and is often the preferred choicefor protecting human health and the environment.

But a price was paid for putting containment “on hold” during the 1980s,when emphasis was placed on developing sophisticated treatment technologies:little research and development on containment technologies was achieved during

this time. As interest shifted back toward containment in the 1990s, the industryfound itself relying largely on pre-1980s technology. Fortunately, in the past10 years, important advances have occurred in several areas of containment, mostnotably in the area of permeable reactive barriers, which transform containmentbarriers into a passive treatment installation.

In the early 1990s, the need to define the state of the art for containment wasunderstood by three visionary organizations: DuPont, the U.S. EnvironmentalProtection Agency, and the U.S. Department of Energy. The DuPont CorporateRemediation Group (CRG) initiated the trio’s first collaborative effort in 1992.Experts from four nations experts were invited by DuPont to work with a teamat the State University of New York at Buffalo to conduct a comprehensive reviewof the containment technology, the technology gaps, and future direction. Theproduct of the work, a 1993 internal report, was published in 1995 by John Wiley &Sons, New York, titled

Barrier Containment Technologies for EnvironmentalRemediation Applications

, and edited by Ralph R. Rumer and Michael E. Ryan.The principal chapters of the book focused on vertical barriers (walls), bottombarriers (floors), and surface barriers (caps). The three organizations joined againand organized an expert workshop on containment technology in 1995, inviting115 international experts. The book,

Assessment of Barrier Containment Technol-ogies: A Comprehensive Treatment for Environmental Remediation Applications

,was edited by Ralph R. Rumer and James K. Mitchell and was published thenext year.

With the rapidly increasing use of barrier technology in remediation, the needfor better understanding, prediction, and monitoring of the performance of bar-riers emerged. The trio organized another expert workshop on the topic in 2002,which led to the development of this book. The workshop planning committeeinvited many of the world’s most knowledgeable researchers and practitioners todiscuss the current state of the art and debate the appropriate applications anddirections for containment. The participants then went home and collectivelycreated this book from their knowledge and exchanges. This book is essentiallya diary of those discussions and assessments, recast into the form of an easilyreadable, comprehensive book that is rich with discussion and references toliterature, as well as further detail on specific topics of interest. The first twochapters address prediction issues, Chapters 3 and 4 address monitoring tech-niques, and Chapter 5 addresses the largely undeveloped field of verification. Thediscussions in the first four chapters address caps, vertical walls, and permeablereactive barriers.

Chapter 1, “Damage and System Performance Prediction,” sets the stage forhow contaminants can get into the subsurface. This is an important chapter,because one cannot understand how to contain something unless one knows howthe contaminants got into the subsurface in the first place, and how they mightspread and threaten the environment without containment. This chapter not onlydescribes pathways, but also introduces the essential concept of risk. No controltechnology is without risk. Ultimately, a low risk of adverse environmental impact

should be maintained in a way that uses resources as wisely as possible. Chapter 1draws from concepts in reliability of structures, and couples barrier structuralfailure to functional failure. Relevant quantitative frameworks are presented foruse in assessing the long-term performance of containment systems.

Chapter 2, “Modeling of Fluid Transport through Barriers,” addresses thebasis for predicting the transport of water and contaminants through barriercomponents. This chapter focuses on modeling the inflow of moisture to theburied waste (e.g., caps), or modeling the release of contaminants throughsubsurface barriers. Fluid transport rate prediction is essential to the designprocess, because predictions can be integrated into the overall containment systemperformance assessment scheme presented in Chapter 1. Chapter 2 providesdetails on the current state of the art for performance prediction, but also clearlydelineates the limitations in modeling specific situations.

Chapter 3, “Material Stability and Applications,” addresses the materials usedin barriers, defining the properties of barrier materials and exploring how mate-rials perform in the field. The materials used for barriers include a myriad ofnatural and man-made materials, such as natural soil, stones and cobbles, imper-meable plastic lining materials, man-made filter fabrics, and chemical agentsdesigned to sorb or degrade contaminants that might come in contact with thematerial. Factors such as clogging, deterioration, or alteration of physical, chem-ical, or hydraulic properties are explored, not only to define what is known aboutthese materials, but also to provide a learned and balance sense of what is notknown.

Chapter 4, “Airborne and Surface Geophysical Method Verification,” providesa thorough description of the application of geophysical methods to subsurfacebarriers. Geophysical methods have been used widely to assist in identifyingpotential mineral resources deep within the subsurface, and in more recent years,in the shallow environment, to help with identifying contaminant plumes andother anomalies. When applied to subsurface barriers, geophysical methods arechallenged beyond their traditional role of identifying gross features that mightwarrant more detailed exploration (e.g., via a borehole), toward identifying moresubtle features, such as a leak in a subsurface barrier. The techniques describedin this chapter include both near- and far-field devices, spanning equipmentdeployed in aircraft flying above a site to devices placed on the ground surfacethat probe the subsurface directly with electromagnetic or other sources of energy.The first half of this chapter describes the technologies that are available, and thesecond half addresses their applications to various types of barriers.

The subject of Chapter 5, “Subsurface Barrier Verification,” tackles perhapsthe most challenging aspect of waste containment technology, i.e., validation offield performance. Traditionally, monitoring has consisted of sampling of ground-water or soil gas from wells. Although sampling soil, water, and air can provideinformation about the general performance of a system, it does not provide imme-diate, specific information about how a particular barrier component is meetingits design goals. Further, there is little to motivate stakeholders to spend money

for performance verification, unless required for compliance with regulations.This chapter provides a comprehensive review of sensors and examples of howsensors can be used to document system performance, addressing the basicquestions: where, what, how, and what-if? Ultimately, the performance verifica-tion scheme should be linked to the performance prediction process. It is perhapsthis linkage that is our most important end point, and one that requires morework, particularly in terms of assessing reliability and risk associated with theuse of waste containment as a technique for managing waste in the subsurface.The two well-known case studies in the United States that are presented in thischapter provide particular value to this need.

That which is buried in the subsurface, out of sight and out of mind, is thatwhich in some respects is the most challenging. Nature has placed geologicmaterials in the subsurface in rather unpredictable and unknowable locations,with properties that are difficult to discern. Individual barriers are constructed inmore controlled and documented ways, but still with considerable uncertainty inactual characteristics. Systems comprised of multiple barriers enjoy considerableredundancy and tend not to rely on any single component for success. Scientistsand engineers strive to understand, predict, design, and verify safe containmentschemes, both in terms of individual barriers and more complex containmentsystems. This book provides a comprehensive report on the science and technol-ogy of waste containment, with a balanced presentation of what is and is notknown. Subsurface containment will continue to be a widely used environmentalcontrol technology in the years ahead. This book will provide a valuable reference,helping to chart the way to successfully managing many contaminated sites.

David E. Daniel

University of IllinoisUrbana, Illinois

Editors

Calvin C. Chien

is a DuPont Fellow, one of only 13 individuals serving in thiscapacity in DuPont. He has been working in the area of groundwater investigationand remediation since 1975. Since 1991, he has been responsible for evaluatingand developing transport modeling and containment technologies. As such,Dr. Chien has played a leading role in improving the understanding of contain-ment technology for use in environmental remediation. He orchestrated the FirstInternational Expert Workshop (1995) and the publication (based on the work-shop) of the first comprehensive containment book:

Assessment of Barrier Con-tainment Technologies: A Comprehensive Treatment for Environmental Remedi-ation Applications

(1996)

.

In 1997, he spearheaded another effort to advance thetechnology: the First International Containment Technology Conference. Throughthese efforts, he has been recognized as a leading contributor to improving thescience of containment technology as well as its acceptance at the regulatorylevel. He has authored and co-authored many technical papers for peer-reviewedjournals and books. Currently, Dr. Chien provides technical environmental sup-port and oversight for existing and new DuPont operations in the Asia-Pacificregion. His contributions in the region led the Chinese Ministry of Science andTechnology to invite him to evaluate candidates for the 2005 State Natural ScienceAward of the People’s Republic of China. This award is the most prestigiousaward for scientists and engineers in China.

Hilary I. Inyang

is the Duke Energy Distinguished Professor of EnvironmentalEngineering and Science, Professor of Earth Science (GIEES), and Director ofthe Global Institute for Energy and Environmental Systems at the University ofNorth Carolina–Charlotte. From 1997 to 2001, he was the Chair of the Environ-mental Engineering Committee of the U.S. Environmental Protection AgencyScience Advisory Board, and also served on the Effluent Guidelines Committeeof the National Council for Environmental Policy and Technology. He hasauthored and co-authored more than 170 research articles, book chapters, federaldesign manuals, and the textbook

Geoenvironmental Engineering: Principles andApplications

published by Marcel Dekker (ISBN: 0-8247-0045-7). Dr. Inyang isan associate editor and editorial board member of 17 refereed international jour-nals, and contributing editor of three books, including the

United Nations Ency-clopedia of Life Support Systems

(Environmental Monitoring Section). He hasserved on more than 85 international, national, and state science/engineeringpanels and committees. Since 1995, he has co-chaired several international con-ferences on waste management and related topics, and given more than 100 invited

speeches and presentations on a variety of technical and policy issues at institu-tions and agencies globally. Professor Inyang holds a Ph.D. with a double majorin Geotechnical Engineering and Materials, and a minor in Mineral Resourcesfrom Iowa State University, Ames; a M.S. and B.S. in Civil Engineering fromNorth Dakota State University, Fargo; and a B.Sc. (Honors) in Geology from theUniversity of Calabar, Nigeria. His research has been sponsored by several agen-cies and corporations. Dr. Inyang’s research accomplishments and contributionsto geoenvironmental science and engineering have been rewarded with honorsby various national and international agencies among which are Fellow of theGeological Society of London; 2001 Swiss Forum Fellow selection by the Amer-ican Association for the Advancement of Science; 1991 Chancellor’s Medal forDistinguished Public Service awarded by the University of Massachusetts Lowell;and the 1992/93 Eisenhower Fellowship of the World Affairs Council to com-memorate the international achievements of the late U.S. President Dwight Eisen-hower. In 1999, Prof. Inyang was appointed to Concurrent Professorship ofNanjing University, China and subsequently selected as an Honorary Professorof the China University of Mining and Technology, Jiangsu, China. He is thePresident of the International Society of Environmental Geotechnology (ISEG)and the Global Alliance for Disaster Reduction (GADR).

Lorne G. Everett

is the 6th Chancellor of Lakehead University in Canada,President of L. Everett and Associates LLC, Santa Barbara, a Research Professorin the Bren School of Environmental Science & Management at UCSB (LevelVII), and Past Director of the University of California Vadose Zone MonitoringLaboratory. The University of California describes full professor Level VII as“reserved for scholars of great distinction.” He has a Ph.D. in Hydrology fromthe University of Arizona in Tucson, and is a member of the Russian Academyof Natural Sciences. In 1996, he received a Doctor of Science Degree (HonorisCausa) from Lakehead University in Canada for Distinguished Achievement inHydrology. In 1997, he received the Ivan A. Johnston Award for OutstandingContributions to hydrogeology. In 1999, he received the Kapitsa Gold Medal —the highest award given by the Russian Academy for original contributions toscience. In 2000, he received the Medal of Excellence from the U.S. Navy, andthe Award of Merit, the highest award given by American Standards and TestingMaterials (ASTM) International. In 2002, he received the C.V. Theis Award, thehighest award given by the American Institute of Hydrology (AIH) for majorcontributions to groundwater hydrology. In 2003, he received the CanadianGolden Jubilee Medal for “Significant Contributions to Canada.” He is an inter-nationally recognized expert who has conducted extensive research on subsurfacecharacterization and remediation. Dr. Everett has published over 150 technicalpapers, holds several patents, developed 11 national ASTM vadose zone moni-toring standards, and authored several books, including

Vadose Zone Monitoringfor Hazardous Waste Sites

and

Subsurface Migration of Hazardous Waste

. Hisbook, entitled

Handbook of Vadose Zone Characterization and Monitoring,

is a

best seller. His book

Groundwater Monitoring

was endorsed by the U.S. Envi-ronmental Protection Agency as establishing “the state-of-the-art used by industrytoday,” and is recommended by the World Health Organization for all developingcountries.

Table Of Contents

Chapter 1

Damage and System Performance Prediction.................................1

Hilary I. Inyang and Steven J. Piet

1.1 Overview......................................................................................................11.2 Long-Term Performance Analysis Framework...........................................7

1.2.1 Concepts and Analytical Framework ..............................................81.2.2 Types of Performance Prediction Approaches..............................11

1.2.2.1 Empirical Prediction Approaches ..................................111.2.2.2 Semi-Empirical Prediction Approaches.........................121.2.2.3 Less Empirical (Theoretical) Modeling Approach........14

1.3 Relationship of Structural Failure to Functional Failure..........................151.3.1 Economic or Pseudo-Economic Criteria.......................................181.3.2 Regulatory Criteria ........................................................................191.3.3 Prescriptive Design Criteria ..........................................................191.3.4 Risk Criteria...................................................................................201.3.5 Demonstrating Compliance: The Safety Case Concept ...............221.3.6 Mixed Criteria ...............................................................................231.3.7 Qualitative and Indexing Analyses................................................23

1.4 Quantification of Long-Term Damage Scenarios, Events, and Mechanisms ...............................................................................................241.4.1 Categories of Degradation Mechanisms .......................................24

1.4.1.1 Slow Physico-Chemical and Biological Processes........241.4.1.2 Intrusive Events..............................................................291.4.1.3 Transient Events .............................................................301.4.1.4 Cyclical Stressing Mechanisms .....................................32

1.4.2 Quantitative Linkage of Contaminant Release Source Terms to Risk Assessment and Compliance Limits ................................37

1.4.3 Frameworks for Assessment of Event Consequences and Connectivities Among Causes of Failure......................................421.4.3.1 Fault Trees......................................................................421.4.3.2 Event Trees.....................................................................42

1.4.4 Estimation of Long-Term Failure Probabilities ............................421.4.4.1 System Failure Probability.............................................431.4.4.2 Component Failure Probability......................................441.4.4.3 Random Resistance ........................................................471.4.4.4 Simplifications of Theory ..............................................481.4.4.5 The Multi-Dimensional Case.........................................51

1.4.5 Component and System Failure in Containing Contaminants .....531.4.6 Relating Probable Contaminant Concentrations to Risks ............54

1.5 Use of Barrier Damage and Performance Models for Temporal Scaling of Monitoring and Maintenance Needs .......................................591.5.1 Updating ........................................................................................591.5.2 Effect of Updating on System Management.................................60

1.6 Life-Cycle Decision Approach and Management.....................................61References ...........................................................................................................62

Chapter 2

Modeling of Fluid Transport through Barriers .............................71

Brent E. Sleep, Charles D. Shackelford, and Jack C. Parker

2.1 Overview....................................................................................................712.2 Caps ...........................................................................................................72

2.2.1 Features, Events, and Processes Affecting Performance of Caps ...............................................................................................722.2.1.1 Hydrologic Cycle ...........................................................722.2.1.2 Layers and Features .......................................................74

2.2.2 Current State of Practice for Modeling Performance of Caps.....752.2.2.1 Water Balance Method...................................................752.2.2.2 HELP..............................................................................812.2.2.3 UNSAT-H .......................................................................822.2.2.4 SoilCover........................................................................822.2.2.5 HYDRUS-2D .................................................................832.2.2.6 VADOSE/W ...................................................................842.2.2.7 TOUGH2 ........................................................................842.2.2.8 FEHM.............................................................................852.2.2.9 RAECOM.......................................................................85

2.2.3 Modeling Limitations and Research Needs for Caps...................862.2.3.1 Role of Modeling ...........................................................862.2.3.2 Data Needs .....................................................................862.2.3.3 Code Quality Assurance and Quality Control...............872.2.3.4 Verification, Validation, and Calibration........................88

2.2.4 Unresolved Modeling Challenges .................................................892.2.4.1 Time-Varying Material Properties and Processes..........892.2.4.2 Infiltration at Arid Sites .................................................902.2.4.3 Role of Heterogeneities .................................................90

2.3 PRBs ..........................................................................................................902.3.1 Features, Events, and Processes Affecting Performance of

PRBs ..............................................................................................912.3.1.1 Groundwater Hydraulics ................................................912.3.1.2 Geochemical Processes ..................................................922.3.1.3 Reaction Kinetics ...........................................................98

2.3.2 Impacts on Downgradient Biodegradation Processes...................982.3.2.1 Enhancement of Geochemical Conditions Conducive

to Anaerobic Biodegradation .........................................982.3.2.2 Overall Contaminant Concentration Reduction ............99

2.3.2.3 Production of Hydrogen.................................................992.3.2.4 Electron Donor Production ..........................................1002.3.2.5 Direct Addition of Dissolved Organic Carbon............100

2.3.3 PRB System Dynamics ...............................................................1012.3.4 Geochemical Modeling ...............................................................104

2.3.4.1 Speciation Modeling ....................................................1052.3.4.2 Reaction Path Modeling...............................................1062.3.4.3 Reactive Transport Modeling.......................................1072.3.4.4 Inverse Modeling..........................................................108

2.3.5 Modeling Limitations and Research Needs of PRBs.................1092.4 Walls and Floors......................................................................................110

2.4.1 Vertical Barriers...........................................................................1102.4.2 Horizontal Barriers ......................................................................1102.4.3 Current State of Practice for Modeling Performance of Walls

and Floors ....................................................................................1112.4.4 Contaminant Transport Processes ...............................................112

2.4.4.1 Aqueous-Phase Transport ............................................1122.4.4.2 Coupled Solute Transport ............................................1172.4.4.3 Modeling Water Flow through Barriers.......................1192.4.4.4 Analytical Models ........................................................120

2.4.5 Modeling Limitations and Research Needs of Walls and Floors ...........................................................................................1232.4.5.1 Input Parameters and Measurement Accuracy ............1232.4.5.2 Time-Varying Properties and Processes ......................1252.4.5.3 Influence of Coupled Solute Transport........................1252.4.5.4 Membrane Behavior in Clay Soils ..............................126

2.5 Complicating Factors...............................................................................1282.5.1 Constant Seepage Velocity Assumption......................................1282.5.2 Constant Volumetric Water Content Assumption .......................1282.5.3 Anion Exclusion and Effective Porosity.....................................1292.5.4 Nonlinear Sorption ......................................................................1292.5.5 Rate-Dependent Sorption ............................................................1302.5.6 Anion Exchange ..........................................................................1302.5.7 Complexation...............................................................................1312.5.8 Organic Contaminant Biodegradation.........................................1312.5.9 Temperature Effects.....................................................................132

References .........................................................................................................132

Chapter 3

Material Stability and Applications ............................................143

Craig H. Benson and Stephan F. Dwyer

3.1 Overview..................................................................................................1433.1.1 The Role of Barrier Material Mineralogy and Mix

Composition on Performance......................................................1443.1.2 Approaches to Material Evaluation and Selection .....................1473.1.3 Geosynthetics and their Durability in Barrier Systems..............149

3.2 Material Performance Factors in Caps....................................................1533.2.1 Material Performance Factors in Composite Barriers ................1553.2.2 Material Performance Factors in Water Balance Designs..........1603.2.3 Coupling of Vegetation and Material Performance Factors .......163

3.3 Material Performance Factors in PRBs ..................................................1673.3.1 Approach to Selection of PRB Materials ...................................1683.3.2 Evaluation of Field Performance Using Pilot Testing................1703.3.3 Effects of Hydraulic Considerations on Reactive Material

Performance.................................................................................1723.3.4 Structural Stability Factors in Performance................................1783.3.5 Material Durability Factors .........................................................183

3.3.5.1 Effect of Mineral Precipitation on Porosity and Hydraulic Conductivity ................................................185

3.3.5.2 Effect of Mineral Precipitation on Reactivity .............1863.3.6 Applications of Geochemical Models in Reaction Tracking .....187

3.4 Material Performance Factors in Cutoff Walls .......................................1913.4.1

In Situ

Hydraulic Conductivity ...................................................1933.4.2 Design Configuration ..................................................................1963.4.3 Geosynthetics in Vertical Cutoff Walls .......................................1983.4.4 Permeant Interaction Effects .......................................................199

References .........................................................................................................201

Chapter 4

Airborne and Surface Geophysical Method Verification............209

Ernest L. Majer

4.1 Geophysical Method Application and Use .............................................2094.1.1 Characterization and Geophysics ................................................2104.1.2 Performance Monitoring and Geophysics ..................................2124.1.3 Geophysical Methods for Site Characterization and

Monitoring of Subsurface Processes...........................................2144.1.3.1 Seismic .........................................................................2144.1.3.2 Electrical and Electromagnetic ....................................2144.1.3.3 Natural Field and Magnetic .........................................2154.1.3.4 Remote Sensing............................................................216

4.2 Specific Methods .....................................................................................2164.2.1 Seismic Methods .........................................................................216

4.2.1.1 Conventional and Advanced Ray and Waveform Tomography..................................................................220

4.2.1.2 Guided/Channel Waves ................................................2214.2.1.3 Scattered and Reflected Energy ...................................2214.2.1.4 Cross-Well/VSP/Single Well Imaging .........................2224.2.1.5 Summary ......................................................................224

4.2.2 Electrical and Electromagnetic Methods ....................................2244.2.3 Natural Field and Magnetic Methods .........................................2274.2.4 Airborne Geophysical Methods ..................................................228

4.2.5 State-of-the-Practice Remote Sensing Methods .........................2314.2.5.1 Aerial Photography ......................................................2324.2.5.2 Multi-Spectral Scanners ...............................................2324.2.5.3 Thermal Scanners.........................................................233

4.2.6 State-of-the-Art Remote Sensing Technologies..........................2334.2.6.1 Hyperspectral Imaging Sensors ...................................2344.2.6.2 LIDAR Systems ...........................................................2354.2.6.3 Laser-Induced Fluorescence (LIF)...............................2364.2.6.4 Radar Systems..............................................................2374.2.6.5 Fused Sensor Systems/Data Streams...........................238

4.3 PRBs ........................................................................................................2394.3.1 Requirements, Site Characterization, Design Verification,

and Monitoring ............................................................................2394.3.1.1 Site Characterization ....................................................2404.3.1.2 PRB Construction Verification.....................................2414.3.1.3 Short-Term Monitoring ................................................2424.3.1.4 Long-Term Monitoring ................................................242

4.3.2 Case Histories..............................................................................2434.3.2.1 Electrical Imaging of PRB Construction and

Installation (Kansas City, Missouri) ............................2434.3.2.2 Cross-Hole GPR Investigations (Massachusetts

Military Reservation, Massachusetts) ..........................2454.4 Vertical Barriers.......................................................................................246

4.4.1 Requirements, Site Characterization, Design Verification, and Monitoring ............................................................................2494.4.1.1 Design...........................................................................2494.4.1.2 Installation/Verification ................................................2494.4.1.3 Short-Term Monitoring ................................................2544.4.1.4 Long-Term Monitoring ................................................254

4.4.2 Case Studies ................................................................................2544.4.2.1 Cross-Hole GPR...........................................................2554.4.2.2 Seismic .........................................................................2594.4.2.3 ERT...............................................................................260

4.5 Caps and Covers......................................................................................2614.5.1 Requirements, Site Characterization, Design Verification,

and Monitoring ............................................................................2624.5.2 Case Histories..............................................................................263

4.5.2.1 EMI and GPR...............................................................2634.5.2.2 Apparent Conductivity Maps.......................................2674.5.2.3 Electromagnetic Radar for Monitoring Moisture

Content .........................................................................2694.5.2.4 Aerial Photography ......................................................2724.5.2.5 Multi-Spectral Scanners ...............................................2734.5.2.6 Thermal Scanners.........................................................2734.6.2.7 HIS Imagery .................................................................274

4.6 Summary..................................................................................................2744.6.1 Primary Needs for Advancement ................................................275

4.6.1.1 Integration ....................................................................2754.6.1.2 Processing and Interpretation.......................................2754.6.1.3 Code Development.......................................................2764.6.1.4 Instrumentation.............................................................276

4.6.2 Future Developments...................................................................276References .........................................................................................................278

Chapter 5

Subsurface Barrier Verification ...................................................287

David J. Borns, Carol Eddy-Dilek, John D. Koutsandreas, and Lorne G. Everett

5.1 Overview..................................................................................................2875.2 Goals ........................................................................................................2885.3 Verification Monitoring ...........................................................................289

5.3.1 Methods .......................................................................................2925.3.1.1 Moisture Change Monitoring Methods .......................2925.3.1.2 Moisture Sampling Methods........................................2945.3.1.3 Vadose Zone Monitoring Considerations ....................295

5.4 Verification System Design .....................................................................2965.5 Moving from State of the Practice to State of the Art ...........................297

5.5.1 System Approach.........................................................................2985.5.1.1 Links to Modeling and Prediction ...............................2985.5.1.2 Optimization.................................................................2995.5.1.3 Decision and Uncertainty Analysis..............................299

5.5.2 Smart Structures ..........................................................................3005.5.2.1 Long-Term, Post-Closure Radiation Monitoring

Systems (LPRMS)........................................................3025.5.2.2 Environmental Systems Management, Analysis, and

Reporting (E-SMART™) Network..............................3045.5.2.3 Direct Push Technologies ............................................3055.5.2.4 Nanotechnology Sensors..............................................307

5.5.3 Advanced Environmental Monitoring System (AEMS).............3075.5.4 A New DOE Barrier Design Code .............................................308

5.6 Drivers for Implementation of New Approaches....................................3095.6.1 Costs ............................................................................................3095.6.2 Enabling Desired End States.......................................................309

5.7 Covers ......................................................................................................3105.7.1 Moving from State of the Practice to State of the Art ...............310

5.7.1.1 Methods ........................................................................3105.7.1.2 Verification Measurement Systems..............................3115.7.1.3 Barrier Cap Monitoring ...............................................311

5.7.2 Case History: Mixed Waste Landfill ...........................................3125.7.2.1 Cover Infiltration Monitoring ......................................3135.7.2.2 Neutron Moisture Monitoring......................................313

5.7.2.3 Fiber Optics Distributed Temperature Moisture Monitoring....................................................................314

5.7.2.4 Shallow Vadose Zone Moisture Monitoring................3145.7.3 Case History: Fernald On-Site Disposal Facility .......................3155.7.4 Verification Needs .......................................................................318

5.7.4.1 Optimization and Trend Analysis ................................3195.7.4.2 Sensors and Other Hardware .......................................320

5.8 PRBS........................................................................................................3215.8.1 Regulatory Framework ................................................................3245.8.2 Moving from State of the Practice to State of the Art ...............325

5.8.2.1 Flow Characterization and Monitoring........................3255.8.2.2 Verification of Geochemical Gradients and Zones......327

5.8.3 Case History: Subsurface Monitoring.........................................3295.8.4 Verification Needs .......................................................................329

5.8.4.1 Spatial and Temporal Flow Monitoring Considerations ..............................................................330

5.8.4.2 Geochemical and Hydrological Process Monitoring Considerations ..............................................................331

5.8.4.3 Acoustic Wave Devices................................................3315.9 Walls and Floors......................................................................................332

5.9.1 Moving from State of the Practice to State of the Art ...............3375.9.1.1 Neutron Well Logging .................................................3375.9.1.2 Perfluorocarbon Tracer (PFT) Monitoring/

Verification ...................................................................3385.9.2 Case History: Colloidal Silica Demonstration............................3415.9.3 Case History: Barrier Monitoring at the Environmental

Restoration Disposal Facility (ERDF) ........................................3435.9.3.1 Study Conclusions........................................................3455.9.3.2 Study Recommendations..............................................345

5.9.4 Verification Needs .......................................................................3465.9.4.1 Adequacy of the Containment Region ........................3475.9.4.2 Long-Term Performance of the Containment .............347

5.10 Conclusions..............................................................................................348References .........................................................................................................349

Appendix A

Workshop Panels .........................................................................353

Panel 1 Prediction: Materials Stability and Application.................................353Panel 2 Prediction: Barrier Performance Prediction.......................................353Panel 3 Prediction: Damage and System Performance Prediction.................354Panel 4 Verification: Airborne and Surface/Geophysical Methods ................355Panel 5 Verification: Subsurface-Based Methods ...........................................355

Index..................................................................................................................357

1

1

Damage and System Performance Prediction

Prepared by*

Hilary I. Inyang

University of North Carolina at Charlotte, Charlotte, North Carolina

Steven J. Piet

Idaho National Engineering and Environmental Laboratory, Idaho Falls, Idaho

1.1 OVERVIEW

Long-term hazardous waste containment using physical barriers such as capsdemands the estimation of system reliability, system deterioration rate, and con-sequences of system failure. The use of a systematic approach and a set of sequentialanalytical steps, such as those included in Figure 1.1, enables opportunities forsystem improvement to be identified. Barrier systems for buried waste or migratingcontaminants are subjected to various physical, physico-chemical, and biologicalphenomena. The synergistic action of these phenomena ultimately damages bar-rier systems and produces or enlarges flow channels through which pollutantscan escape. The observation that the degradation of constructed facilities increaseswith service life is not unique to containment systems: deterioration characterizesall constructed facilities, from roadways to pyramids. Current uncertainties per-tain to the establishment of reasonably valid deterioration rates for various barrierdesigns, waste types, management systems, climatic and geohydrologic environ-ments, site stability, and barrier construction materials for time frames that rangefrom hundreds to thousands of years.

The diversity of waste types and desirable service lives for facilities undervarious regulatory programs are summarized in Tables 1.1 and 1.2, respectively.

* With contributions by James H. Clarke, Vanderbilt University, Nashville, Tennessee; John B.Gladden, Westinghouse Savannah River Company, Aiken, South Carolina; Horace K. Moo-Young,Villanova University, Villanova, Pennsylvania; Priyantha W. Jayawickrama, Texas Tech University,Lubbock, Texas; W. Barnes Johnson, U.S. Environmental Protection Agency, Washington, DC; RobertE. Melchers, University of Newcastle, Callaghan, NSW, Australia; Mark L. Mercer, U.S. Environ-mental Protection Agency, Washington, DC; V. Rajaram, Black and Veatch Corporation, OverlandPark, Kansas; and, Paul R. Wachsmuth, University of North Carolina at Charlotte, Charlotte, NorthCarolina.

2

Barrier Systems for Environmental Contaminant Containment & Treatment

Estimation of the long-term deterioration pattern of barriers is necessary toimprove the reliability of estimates of long-term contaminant release source termsfor input into human health and ecological risk assessments, as well as facilitymonitoring and maintenance planning. Monitoring of barrier performance pro-vides useful but inadequate data for performance predictions, because of limitedfield experience with barriers of various configurations in many environments,and because epochal events such as floods and earthquakes produce transienteffects that cause deviations from performance patterns.

The majority of quantitative methods that are currently used to estimate long-term barrier performance have time-invariant material characteristics andload/fluid application rates. The use of these fate and transport models, most of

FIGURE 1.1

Flow chart for risk-based decision making. (From Stewart, M.G. andMelchers, R.E., 1997.

Probabilistic Risk Assessment of Engineering Systems

, Chapman &Hall, London. With permission.)

Define Contextsocial, individual, organizational,

political, technological

Define System

Hazard Scenario Analysis • what can go wrong? • how can it happen? • what controls exist?

Estimate Probability(of occurrence of

consequences)

Estimate Consequences (magnitude)

Define Risk Scenarios Sensitivity Analysis

Risk Assessment compare risks against criteria

Risk Treatment • avoidance • reduction • transfer • acceptance

Monitor and

Review


3

TABLE 1.1Types of Hazardous Materials

Type

Typically Found

in Nature?

Importance of Chemical Form

to ToxicityDoes Hazard

Decay Naturally?

Do We Know How to

Destroy Hazard?

Radioactive isotopes

Yes

a

Can affect the level of exposure to the hazard by altering the ingestion or inhalation uptake of isotopes

Natural decay is fixed for each isotope

Negligible prospects for

in situ

destruction or treatment

Ex situ

treatment may be practical to separate long-lived isotopes from short-lived isotopes

Toxic organic compounds

b

No Affects ingestion and inhalation uptake

Decay generally slow (years, decades) and often dependent on specific chemical environment, e.g., trichloroethylene

In situ

decay may be deliberately enhanced by microbes

Determines toxicity level

Ex situ

destruction generally possible, but the associated risks and costs of transportation and destruction are high

Toxic metals Yes, although sometimes not in the more hazardous chemical forms

Can affect ingestion or inhalation uptake

Metals won’t decay, but the chemical form may naturally change into less toxic forms

Destruction is not practical

Generally affects toxicity

In situ

alteration of chemical form can sometimes be enhanced by microorganisms

4


which are based on one-dimensional differential equations, for describing contam-inant advection-dispersion has simplified barrier performance analyses but doesnot address long-term barrier system performance adequately. As the performance

TABLE 1.1 (continued)Types of Hazardous Materials

Type

Typically Found

in Nature?

Importance of Chemical Form

to ToxicityDoes Hazard

Decay Naturally?

Do We Know How to

Destroy Hazard?

Toxic metals

Ex situ

destruction generally possible, but with associated risks and costs during transportation and destruction

a

However, the specific radioactive isotopes are typically are not the specific isotopes found innature.

b

There are also some toxic compounds that are neither organic nor metals, e.g., asbestos.

Source:

INEEL (2000). Environmental Laboratory Report INEEL/EXT-2000-01094; Piet et al.(2001). INEEL technical report INEEL/EXT-2001-01485.

TABLE 1.2Time frames for Waste Containment Performance under Various U.S. Regulatory Programs

Time Frame Regulatory Program

10,000 years Nuclear Regulatory Commission and EPA regulations for high-level and transuranic waste (10 CFR 60, 10 CFR 63, 40 CFR 191, 40 CFR 197)

1000 years EPA regulations for near-surface uranium and thorium mill tailings (40 CFR192) and DOE policy for new land burial (DOE M 435.1)

500 years NRC regulations for near-surface burial of low-level waste (10CFR61)30 years Baseline EPA RCRA time period for near-surface burial chemical hazards

(40 CFR264); EPA can increase or decrease this value for each caseIndefinite Baseline EPA CERCLA time period for residual hazards (CERCLA requires a

5-year review to ensure the remedy is still protective of human health and the environment and is still performing as predicted)


5

analyses time frames extend from one or two decades to hundreds of years,changes in barrier material characteristics; cyclic changes, waning, or growth ofstressing events; and possible exhaustion of initially present parent contaminantsand/or generation of daughter contaminants combine to decrease the reliabilityof contaminant release estimates.

Long-term performance modeling of waste containment systems and individ-ual barriers within such systems require identifying possible damage mechanismsand assessing the system resistance in all possible ways in which the systemmight fail. Various techniques have been developed in practice (in differentindustries) and, hence, with different names, including the following:

•

Preliminary hazard analysis (PHA) (nuclear industry)

•

Walk-down analysis consisting of on-site visual inspection, particularlyof pipe work (nuclear industry)

•

Failure modes and effects analysis (FMEA), which uses generic termsas prompts (various applications)

•

Failure modes, effects, and criticality analysis (FMECA), which alsoassesses criticality of consequences

•

Hazard and operability studies (HAZOP), which uses guide words asprompts (primarily chemical industry)

•

Incident data banks, which contain data such as accident data and near-miss data

For the range of barrier applications available now and in the future, there isa need for improved capacity to predict containment barrier damage and systemperformance. Damage and system performance models must be:

•

Responsive to the needs of a diverse set of decision makers(i.e., designers of new barriers, managers of barriers in service, regu-lators, funding agencies, and the public)

•

Integrative of the most important mechanisms of failure (i.e., bothspatially uniform degradation and localized degradation; both contin-uously acting and discrete in time)

•

Comprehensive with regard to the range of performance measuresrelevant to a given barrier design that solves a particular problem at aparticular location

•

Stochastic to allow evaluation of the sensitivities of parameter uncer-tainties compared to performance measures

•

Probabilistic in consideration of failure scenarios and mechanisms thatmay or may not occur during the service life

•

Validated by data to the extent practical

•

Adaptive to new information obtained during barrier service

6


•

Informative regarding barrier degradation to guide barrier surveillanceand maintenance, justification for reduction of surveillance and main-tenance, barrier lifetime extension while in service, and future barrierdesigns

•

Graded in its implementation according to the severity and longevityof the associated risks (barriers with lower severity or shorter durationhazards do not need all of the above)

Attempts to provide satisfactory system performance demands that one ormore criteria be available against which to measure system performance. Thesetting or derivation of performance criteria is a problem with a fascinating andcomplex history, much of it based originally on issues associated with the nuclearindustry. This history includes some deep philosophical questions, including“Who is to bear what level of risk, who is to benefit from risk-taking, and whois to pay? Where should the line be drawn between risks that are to be managedby the state and those that are to be managed by individuals, groups, or corpo-rations? Who evaluates success or failure in risk management and how? Whodecides what should be the desired trade-off between different risks?” (Hoodet al., 1992). The decisions about these matters are influenced by judgments aboutthe following (Stewart and Melchers, 1997):

•

Anticipation of system failure and resilience against unexpected catas-trophe

•

Assumptions used to compute a numerical estimate of system risks• Size of uncertainties in estimating system risks• Organizational vulnerabilities to system failure• Cost of risk reduction• Size and composition of groups involved in decision-making processes• Aggregation of individual preferences (i.e., distribution of benefits and

risks)• Counter-risks (i.e., alternatives may have other societal risks)

Psychological aspects, such as risk perception and risk aversion, social andcultural preferences, as well as political processes and risk communication alsoplay a part. The term “failure” can mean a variety of structural conditions or lackof capacity to meet expected performance functions when it is applied to con-tainment systems. Structural failure of a system component or the entire systemshould be differentiated from functional system failure as described by Inyang(1994) and Inyang et al. (1995). Structural failure of a containment system maynot necessarily lead to immediate functional failure because the former is oftenindexed in terms of parameters that define the stability and hydraulic character-istics of the containment system, whereas functional failure is assessed in termsof the risk of environmental and human exposure to contaminants that may bereleased from the system. More broadly, for a given initial hazard inventory, the

Damage and System Performance Prediction 7

exposure generally depends on the five factors listed below and illustrated inFigure 1.2. Eventually, hazard either decays (with some half-life) or escapes.

1. Hazardous half-life2. Mobilization rate/year (e.g., leaching, diffusion in the absence of a

barrier)3. Time at which barrier begins to degrade4. Barrier degradation rate/year5. Transport time of escaped materials between barrier and recipients

Factors 2, 3, and 4 control when and how fast the hazard escapes. Factor 5 controlshow much time (with additional hazard decay) will elapse before the escapedhazard impacts human health and the environment. With reference to the rangeof time horizons in various regulations, there is no systematic connection betweenthe hazard timescales and regulatory timescales that are summarized in Table 1.2.Different regulations were established at different times by different legislationin response to different issues. Thus, the appropriate framework for predictingbarrier system performance is not always clear: the time frames can differ greatlyand the appropriate assumptions on how long to monitor and manage the barriersystem can also differ.

1.2 LONG-TERM PERFORMANCE ANALYSIS FRAMEWORK

It is necessary to formulate a long-term performance analysis framework that enablesthe consideration of factors that are significant for a given class of containmentsystems. The failure states of the constructed system in terms of both structuralfailure and functional failure need to be defined. Also, the performance assessment

FIGURE 1.2 Simplistic illustration of processes that influence exposure to individuals.

Hazard halflife

Hazard inventory

Escaping inventory

Time barrier starts to degrade Rate barrier degrades per year

Rates inventory mobilizes per year

Delay time in transportthrough environmental media Exposed individuals

8 Barrier Systems for Environmental Contaminant Containment & Treatment

framework should incorporate nodes to which pre-failure performance modelscan be linked.

1.2.1 CONCEPTS AND ANALYTICAL FRAMEWORK

Several concepts and analytical frameworks have been proposed for use in assess-ing the long-term performance of containment systems. The concepts pertain tothe performance pattern of containment systems during service lives and post-closure time frames that can range from 30 years to thousands of years. The focusof the analyses is the formulation and use of performance prediction models thatare capable of determining contaminant release rates as a function of estimated,measured, or designed magnitudes of containment system design parameters,waste characteristics, stressing events and processes, and site/hydrological con-ditions. The factors that need to be considered are numerous, as exemplified bythe case of a near-surface barrier illustrated in Figure 1.3.

Several attempts have been made to establish the expected general pattern ofbarrier performance over long service lives. Figure 1.4a shows the containmentsystem performance model that is implicit to current practice. The facility isassumed to provide a constant level of service, or to be structurally sound untilexternal monitoring data indicate the release of contaminants at unacceptable

FIGURE 1.3 An illustration of the interaction among various processes and parametersthat influence the long-term performance of near-surface containment systems.

Plugging and surface tension

Output: Contaminant flow to the vadose zone

Surface ecology(especially

evapo-transpiration

barriers)

Interfacialecology

(especiallycapillarybarriers)

Waste zone

Hydrology(including

micropores,capillaries)

Structure

Natural boundary conditions (weather, climate, biota)

Engineered boundary conditions (design, maintenance, repair)

Plants Dimensions, materials

configuration

Temperature

Precipitation

Plant/animal intrusion

Soil type and thickness

Erosion

Subsidence

Compaction

Wind/water erosion

Biochemical changes?

Ecological

Water


concentrations. Figure 1.4b shows a more realistic performance pattern in whichthe performance degrades gradually during the immediate post-implementationperiod and then decays abruptly. After abrupt decay, the performance decreasesmuch more gradually in a period that is characterized by large uncertainties. Thereader should note that system damage vs. time plots have configurations thatare the reverse of those of system performance (or effectiveness) vs. time plots.Thus, Figure 1.5 shows an increase in the risk of containment system failure withtime. It should be noted that although the system deterioration pattern may berepresented by a smooth curve, the performance pattern of a particular componentof the containment system could exhibit temporal fluctuations in response totransient stressing mechanisms, the passage of contaminant fronts, and mainte-nance activity. In developing the conceptual framework for estimating the long-term performance pattern of containment systems, Inyang (1994) identified thevarious stages illustrated in Figure 1.6. Curve 1 shows the barrier degrading viacontinuous deterioration mechanisms. The branching to Curve 2 shows a barriersuffering from a discrete (in time) negative perturbation, such as a flood or anearthquake. The branching to Curve 3 reflects a barrier being upgraded orrepaired. In the illustration, following Curve 1, the containment system effective-ness decays from an initial level of Eto, to a minimum acceptable level of Etr attime, tr. Etr corresponds to the functional performance level that is typically

FIGURE 1.4 Conceptual pattern of long-term performance of containment systems(a) abrupt failure pattern implicit to current practice (b) gradual degradation pattern thatis more realistic.

CurrentMethodology

Perfo

rman

ce

RealisticPerformance

Perfo

rman

ce

Uncertain howto managebarriers &resistance tonew materialsand designs

Design Life

Detect only after failure(leakage through barrier)

Time

Uncertainlong-term

performance

(a)

Time(b)


specified by regulators or other authorities. If the facility is repaired at a time,tm, the effectiveness can abruptly increase to Etm so that an improved performance(described by Curve 3) results. Essentially, repairs postpone the attainment of Etr

FIGURE 1.5 Conceptual degradation-time function of a containment system. (Illustratedby Melchers, R.E., 2001. Reliability Engineering and System Safety, 71(2), 201–208. Withpermission.)

FIGURE 1.6 A conceptual long-term deterioration pattern and maintenance scheme forwaste containment system. (From Inyang, H.I., 1994. Proceedings of the First InternationalCongress on Environmental Geotechnics, Calgary, Canada, pp. 273–278. With permission.)

Risk

of f

ailu

re

Particular structuredeterioration

Acceptable risk level

Expected deterioration

Time (age of structure)

Syst

em eff

ectiv

enes

s, E

(frac

tion)

Eto

Etm

E1

E2

Etg

Etr

to

Time, t (years)

Curve 1

Curve 3

Curve 2

tg t2 tm tr


by slowing down the deterioration of the repaired component(s) and, hence, thesystem. The system can also degrade abruptly, as at tg, such that its effectivenessfalls to Etg and system performance follows Curve 2 to failure at t2 (much soonerthan would result from the regular deterioration pattern).

1.2.2 TYPES OF PERFORMANCE PREDICTION APPROACHES

In order to serve practical purposes, performance patterns need to be quantified,requiring the development of rating systems and models. Approaches to perfor-mance prediction can be categorized as empirical, semi-empirical, and less empirical(theoretical modeling).

1.2.2.1 Empirical Prediction Approaches

Empirical prediction approaches involve the extrapolation of current knowledgeof system behavior and/or similar system behavior to long-term system behavior.Such knowledge can also be acquired through accelerated testing in intensifiedenvironments. Another example of an empirical approach is performance index-ing. In most cases, indexing criteria do not explicitly include time functions withperformance factors. Table 1.3 shows the ratings of single components and com-posite configurations of barriers (Piet et al., 2001). In general, the scores on

TABLE 1.3Overall Benefit of Each Barrier Configuration of Cover/Liner Materials

Design Alternate Description

Overall Benefit

Estimated Cost (dollars/ft2)

Benefit/Cost Ratio

Ranking in Group

One-Barrier LayerA CCL 36 0.70 51 3B GM 64 0.70 91 1C GCL 46 0.70 66 2

Two-Barrier LayerD GM/CCL 58 1.40 41 2E GM/GCL 66 1.40 47 1

Three-Barrier LayerF GM/CCL/GM 71 2.10 34 2G GM/GCL/GM 77 2.10 37 1

CCL, single compacted clay liner; GM, single geomembrane; GCL, single geosynthetic clay liner;GM/CCL, two-component composite; GM/GCL, two-component composite; GM/CCL/GM,three-component composite liner; GM/GCL/GM, three-component composite liner.

Source: Adapted with modification from Koerner, R.M. and Daniel, D.E. (1992). Civil Engi-neering, pp. 55–57.


overall benefit or utility of a particular design increase with the number ofcomponents.

Inyang and Tomassoni (1992) indexed the long-term performance pattern ofwaste covers for use in regulatory impact analysis. The scores are presented inTable 1.4. The reader should note that these scores are general indices and arenot precise estimates of the performance of the components scored. Otherresearchers exemplified by Hagemeister et al. (1996) developed detailed perfor-mance indexing systems that incorporate ratings of barrier components, contam-inant transport pathway factors, and human exposure potential.

1.2.2.2 Semi-Empirical Prediction Approaches

These approaches involve the use of semi-empirical models to estimate thedamage time functions or deterioration pattern of containment systems or specificcontainment system components. Using adaptations from product reliability anal-yses, a parameter that is generically referred to as the “failure rate” is used toquantitatively describe the effectiveness or reliability of a barrier or containmentsystem with time. The magnitude of the failure rate is the significant determinantof the barrier degradation rate in the absence of transient events. It is tempting

TABLE 1.4Estimated Long-Term Effectiveness of Selected Waste Containment Measures

Effectiveness, Et (%)

Indexing Time Increments (t years)

t0 t10 t30 t100

Clay cap 80 75 60 20 (85a)Synthetic cap 90 85 75 15 (90b)Clay plus synthetic cap 95 92 80 35 (98c)RCRA C composite liner system 98 95 85 60Clay liner 70 60 40 5Synthetic liner 85 75 35 0HDPE wall 65 60 50 25 (65d)Slurry wall 70 60 20 (70e) 0

a Assumes addition of new clay cap at 100 years.b Assumes addition of new synthetic cap at 100 years.c Assumes addition of new composite clay and synthetic cap at 100 years.d Assumes addition of new HDPE at 100 years.e Assumes addition of new slurry wall at 30 years.

Source: Inyang, H.I. and Tomassoni, G. (1992). Indexing of long-termeffectiveness of waste containment systems for a regulatory impact analysis.A technical guidance document. Office of Solid Waste, U.S. EnvironmentalProtection Agency, Washington, DC.


to erroneously assume that failure rates for containment systems are constant. Inpractice, the failure rates of most engineered systems are not constant with time.Generally,

(1.1)

where λ(t) is the time-variable failure rate of the containment system; λ0 is theinitial failure rate of the containment system; β is an exponent that describes thevariation (usually decay) of the failure rate with time, t. Equation (1.1) representsthe general exponential form of the decay equation. The linear and Weibull formsof the equation are presented below as Equations (1.2) and (1.3), respectively.The parameters are as defined for Equation (1.1). The time parameter, t0, is thetime corresponding to the origin of the initial failure, λ0.

(1.2)

(1.3)

For Equations (1.1) through (1.3), the value of the constant β determines theshape of the failure rate function. The failure rate is increasing with time if β > 0,it is constant if β = 0, and it is decreasing if β < 0. For more information, thereader is referred to Wolford et al. (1992), who used this approach to estimatethe aging pattern of nuclear power plant equipment. Such techniques have alreadybeen successful in extending the license of 10 United States nuclear power plantsby 20 years. Inyang (1994) observed that the Weibull format of failure analysisprovides the curve geometries that match the expected deterioration pattern ofmost containment systems and proposed the use of Equation (1.4) with shapeparameters ranging from 2 to 5. The use of Equation (1.4) enables long-termperformance to be addressed within the context of system reliability.

(1.4)

where Rt is the reliability of the containment system at a future time of reference,t is the future time of reference, and n is the scale or normalization parameterthat corresponds to the time duration at which the failure probability is 0.632.Generally, the larger the magnitude of β, the greater the deterioration rate.

Considering that there is a complimentary relationship between the probabil-ity of failure, Pt, and reliability, Rt, of a component or system as indicated byEquation (1.5), initial values of reliability can be established.

λ λ β( ) exp( )t t= 0 �

λ λ β( ) ( )t t= +0 1 �

λ λβ

( )tt

t=

⎛

⎝⎜⎞

⎠⎟0

0

Rt t

nt = −−⎛

⎝⎜⎞

⎠⎟

⎡

⎣

⎢⎢

⎤

⎦

⎥⎥

exp 0

β


(1.5)

The damage functions for each system component can be generated fromcurrent knowledge, testing, and extrapolations, and can be used to determine theprobability that barrier characteristics will meet specified standards at specifiedfuture times.

1.2.2.3 Less Empirical (Theoretical) Modeling Approach

This approach involves modeling the stresses, deterioration processes, wastetransformations and release, barrier material durability, and flaw evolution for abarrier component or system. In this approach, the failure probabilities of systemcomponents and the system itself are modeled. Interactions among various param-eters that promote or negate effects are considered. Considering that variousstressors and their impacts have different probabilities of occurrence within dif-ferent timescales, the challenge of deciphering the interactions among parametersis quite great. Therefore, an innovation within this modeling approach is the useof modeling frameworks that enable the incorporation of various models and theestablishment of dynamic linkages among them. This technique is nested in thesubdiscipline of system dynamics.

System dynamics is the study of dynamic feedback systems using computermodeling and simulation (Forrester, 1961). Unlike other scientists, who study theworld by breaking it up into smaller and smaller pieces, system dynamicists lookat things as a whole. The central concept of system dynamics is understandinghow all objects in a system interact with one another. Visualization of the systemis one of the assets of this modeling technique. However, beneath the visualexterior is a series of differential equations that define the behavior of the systemover time. An example of software that can be used in this modeling exercise isStella Research (Stella, 2001). The calculations are performed using numericalintegration. Although the interface makes the modeling look superficial andalmost trivial, a sophisticated mathematical engine performs the calculations.Using this modeling technique, it is possible to model complicated systems. Athorough understanding of the structure of these complex systems can lead to anexplanation of their performance, both over time and in response to internal andexternal perturbations. By understanding the underlying system structure, predic-tions can be made relative to how the system will react to change. Systemdynamics models are descriptive in nature. The elements in the models mustcorrespond to actual entities in the real world. The decision rules in the modelsmust conform to actual practice and real-world phenomena. A new project at theIdaho National Engineering and Environmental Laboratory (INEEL) is addressingbarrier degradation dynamics (Piet and Breckenridge, 2002). One component ofthe effort is the use of relatively simple but flexible system dynamics models toexplore possible interactions of processes. These models provide a tool to exploreuncertainties in scenarios and mechanisms, whereas more sophisticated modelsare tools for exploring sensitivities to parameter uncertainties.

R Pt t= −1


To illustrate the necessity of addressing interactions among various parame-ters, the effects of the burrowing of covers by animals on evapo-transpiration areconsidered. During the summer months, more water is lost from plots with animalburrows than from plots where no animal burrows are present. During the wintermonths, both the plots with animal burrows and the control plots gain water. Inaddition, water does not infiltrate below approximately 1 meter (m), even thoughburrow depths always exceed approximately 1.2 m. The lack of significant waterinfiltration at depth and the overall water loss in the lysimeter plots are occurringdespite the following worst-case conditions:

• No vegetative cover (no water loss through transpiration)• No water run off (all precipitation is contained)• Burrow densities in lysimeters greater than those in natural settings• Extreme rainfall events applied frequently (i.e., three 100-year storm

events in three months)• Animals burrowing deeper in the lysimeters than in natural settings

As part of the conclusion of the study described in the precedingparagraph, the investigators noted that “the overall water loss fromsoils with small-small burrows appears to be enhanced by a com-bination of soil turnover and subsequent drying, ventilation effectsfrom open burrows, and high ambient temperatures” (Gee and Ward,1997). Thus, in this case, animal intrusion had a net positive effect.Indeed, earlier work shows that soils were more dry beneath burrowsthan elsewhere (Cadwell et al., 1989; Link et al., 1995). Link et al.(1995) report that the increased moisture in burrows facilitatedvegetation response that increased plant transpiration as plants tookadvantage of the moisture and sent roots to use it, leading to dryzones under the burrows. Indeed, Link et al. (1995) note that “eco-logically, it is expected that a local abundance of a limiting resource,in this case moisture, would be rapidly and therefore depleted.”

1.3 RELATIONSHIP OF STRUCTURAL FAILURE TO FUNCTIONAL FAILURE

In real-world situations, defining satisfactory system performance can be difficult.It is a vector with many components, governed by different criteria, and drivenby different and perhaps interacting processes. These processes may not be wellunderstood and, hence, can be represented analytically only with considerableuncertainty. This situation is not too different from that in other spheres anddisciplines.

It is usual in risk analysis to consider the consequences of failure, hence therecent focus of performance assessments has been on readily measurable barriercharacteristics (e.g., barrier permeability) with limited focus on various combi-nations of outflows and inflows. Because the system properties and processes areuncertain, failure consequences can be described only with uncertainty. Moreover,


the consequences usually are the critical outcome(s) of the system because thelarger community seldom has particular interest in the structural system itself.

The foregoing discussion leads to the need to examine the performance factorsnecessary to evaluate containment systems. These factors are divided into thefollowing two categories:

• Total system (parameters that define functional performance)• Concentration of hazardous materials in surface/aquifer water• Exposure to humans (e.g., water, air, intrusion pathways)• Risk to humans• Risk to ecologies

• Barrier and barrier subsystems (parameters that define structural per-formance)• Resistance to human intrusion• Water flux through barrier• Gas flux through barrier• Hazardous material flux through barrier• Measures of individual degradation mechanisms (e.g., erosion,

subsidence)

The satisfaction of both functional and structural design functions of thecomposite containment system requires that the various system components meetspecific design functions that contribute to overall system performance. Thevariability in the combination of various containment system components impliesthat long-term performance under a given set of applied stresses will also bedifferent. Inyang (1999) suggested the following nonexclusive criteria as indicesof containment system and component performance:

• Ability of the system to reduce the concentrations of aqueous phasecontaminants to acceptable levels through one or more contaminantattenuation processes (e.g., sorption, precipitation)

• Ability of the system to reduce the volume of contaminants that isreleased into protected media to acceptable levels

• Ability of the system to reduce the leaching of bound contaminantsfrom stabilized media to acceptable levels

• Ability of near-surface system components to attenuate radiation tonondamaging levels

Often, the locations at which measurements of contaminant volumes orrelease rates will be obtained are specified in documents that are used to establishthe compliance of a component or system at specified time intervals. As anexample, in Table 1.5, Ho et al. (2002a) summarized the design performanceobjectives for the Monticello Mill Tailings Repository in which performancestandards are specified in terms of specific quantities of contaminants that mustnot be exceeded.


TABLE 1.5Summary of Performance Objectives Applicable to the Monticello Mill Tailings Repository

Media StandardPoint of

CompliancePeriod of

Compliance Regulation

All pathways <100 mrem/year Effective Dose Equivalent from all routine DOE activities

To a member of the public

Not defined DOE Order 5400.5 II 1.a

Atmosphere <10 mrem/year Effective Dose Equivalent, excluding Rn

To a member of the public

Not defined 40 CFR 61.92

Atmosphere Average flux of Rn-222 <20 pCi/m2/s or (see next row)

In air above landfill, averaged over entire landfill

1000 years if reasonably achievable and, in any case, for at least 200 years

40 CFR 192.02(a) and 40 CFR 192(b)(1)

Atmosphere Annual average concentration of Rn-222 in air <0.5 pCi/L

At or above any location outside the landfill


40 CFR 192.02(a) and 40 CFR 192(b)(2)

Groundwater Arsenic <0.05 mg/La,b

Chromium <0.05 mg/La,b

Lead <0.05 mg/La,b

Molybdenum <0.01 mg/La,b

Selenium <0.01 mg/La,b

Combined Ra-226 and Ra-228 <5 pCi/La,b

Combined U-234 and U-238 <30 pCi/La,b,c

Gross alpha-particle activity, excluding Rn and U <15 pCi/La,b

Intersection of vertical plane with uppermost aquifer at downgradient limit of disposal area plus area taken by dike or other waste barrier


40 CFR 192.02(a) and 40 CFR 192.02(c)(4), and Table 1 to Subpart A of 40 CFR 192

Groundwater Beta particles, and photons made from manmade radionuclides <4 mrem/year

In community water supply systems



1.3.1 ECONOMIC OR PSEUDO-ECONOMIC CRITERIA

Economic evaluation has the advantage (and disadvantage) of forcing all partiesto evaluate their objectives in monetary terms. Pseudo-economic criteria, such asutility analysis, require a similar approach but in terms of a different unit ofmeasurement. In principle, the maximum expected net present value criterion canbe stated as follows:

(1.6)

where k is the alternative or system configuration being considered, i is the stateof the system (e.g., normal operation, one or other mode of system failure), pi isthe probability of occurrence for each such state of nature, M is the number ofsuch states, j is the attribute, N is the number of attributes, and Xji represents thevarious costs or benefits associated with each state. There are some very signif-icant problems associated with determining the Xji, and these are well known incost-benefit analysis literature (Layard, 1972; Dasgupta, 1993). Usually, the opti-mal decision is considered to be the maximization of the value of Equation (1.6),which then provides the possible decisions required. Typically, this translates intodesired (maximum) values for the probabilities, pi. These values are obtainablethrough risk analysis, as are some of the values of Xji (where these are conse-quences). In practice, the optimization of Equation (1.6) can be constrained byregulatory requirements (Stewart and Melchers, 1997).

TABLE 1.5 (continued)Summary of Performance Objectives Applicable to the Monticello Mill Tailings Repository

Media StandardPoint of

CompliancePeriod of

Compliance Regulation

Compacted soil layer in cover

Water percolationd <1 × 107 cm/s

Hydraulic conductivity of compacted soil layer in cover


a If background is below this level.b An alternative concentration limit may be established under 40 CFR 192.02 (c)(ii)(A).c Where secular equilibrium is obtained, this criterion will be satisfied by a concentration of 0.044milligrams per liter. For conditions of other than secular equilibrium, a corresponding value may bederived and applied, based on the measured site-specific ratio of the two isotopes of uranium.d A unit gradient flow is assumed to equate percolation to hydraulic conductivity.

max EV p Xk i

i

M

ji

j

N

=⎛

⎝⎜⎜

⎞

⎠⎟⎟

= =∑ ∑

1 1


1.3.2 REGULATORY CRITERIA

Typically, regulatory criteria are developed by public authorities acting broadlyon behalf of the public and mandated by government. Generally, regulatoryauthorities develop general safety goals and set specific safety standards, monitorsystem performance, and prosecute if specified safety standards are violated.There are a number of possible measurement units available, including expectednumber of deaths, injuries or cost equivalents, short- and long-term expectedhealth implications, and various environmental criteria. None constitutes a com-pletely satisfactory accounting for the possible impact of a hazardous situation.However, alternatives are difficult to find or suggest. In a sense, all should beseen as convenient surrogates for much more complex accounting schemes; theassociated issues are, ultimately, the same as those for economic decision criteria.Table 1.6 shows an example of a typical set of safety targets for hazardousindustries where neighboring land usage may be affected. Regulatory standardenforcement can cause resentment and an adversarial situation that is not condu-cive to the operator or licensee committing to risk control and appropriate riskmanagement. Enforcement also requires periodic inspection of the facility byregulatory personnel.

1.3.3 PRESCRIPTIVE DESIGN CRITERIA

The easiest approach, and perhaps the most used approach, is to show compliancewith existing regulations and their prescriptive instructions for design. Thisapproach, strictly speaking, does not determine performance in the sense of per-formance measures noted above, but only shows that regulatory instructions fordesign have been met. This is often adequate, because the prevailing knowledgebase is often used to establish conservative limits for design and performanceparameters. However, the literature contains examples of barriers not meeting theobjectives of the Resource Conservation and Recovery Act (RCRA) to protecthuman health, while being consistent with RCRA design guidance. Thus, for future

TABLE 1.6Typical Safety Targets for Land Use Analysis

Land UseIndividual Fatality Risk

(××××10–6 per year)

Hospitals, schools, child-care facilities, old age housing 0.5Residential, hotels, motels, holiday resorts 1Commercial (including retail centers, offices and entertainment centers) 5Sporting complexes and active open space 10Industrial 50

Source: Stewart, M.G. and Melchers, R.E. (1997). Probabilistic Risk Assessment of EngineeringSystems, Chapman & Hall, London.


barriers, it cannot be simply assumed that meeting RCRA design guidance willprovide the protection that regulations and the public desire if the hazards, location,or design approach vary significantly from demonstrated RCRA design guidance.

1.3.4 RISK CRITERIA

A more complete and systematic approach to developing long-term performancestandards is to estimate risk to human health and the environment by consideringpossible exposure pathways, estimating the total exposure, and then (if needed)converting to risk. This task can be performed with varying degrees of sophisti-cation depending on the situation. The most common approach is deterministic.Under the deterministic approach, a range of standard release and pathway sce-narios is constructed by the analyst, then doses are calculated under the assump-tion that the scenarios will occur without consideration of the likelihood of thescenarios. This approach is characteristically conservative, worst case, and tendsto overestimate dose exposures to the receptors (Moore et al., 2001). An exampleis the use of a hydrological code, e.g., HELP, to estimate water movement througha barrier, then estimate exposure to the nearest population, convert to risk (ifneeded), and compare to exposure/risk requirements — all without includingprobabilities in any of the stages of analysis.

For more complex, longer hazard, and/or higher hazard situations, probabi-listic approaches have been used. “A probabilistic approach to scenarios takesthe likelihood of occurrence into account, allowing a mechanism to differentiatebetween site characteristics and accessibility” (Moore et al., 2001). Where uncer-tainties in key variables are significant, stochastic approaches are used to estimateuncertainties and sensitivities. The uncertainties in key parameters are estimatedand then propagated through the analysis of relevant scenarios to determine theresulting uncertainty in the relevant performance measures. The term “probabi-listic” is sometimes used for such analyses because one is dealing with proba-bilities of a variable having a certain value. However, the term can be used as adescriptor of the approach of analyzing the probabilities of different scenarios(as used in the nuclear industry and other industries). A stochastic approach canbe combined with either deterministic sets of scenarios or probabilistic sets ofscenarios. For example, the United States Nuclear Regulatory Commission(USNRC) has established a set of regulatory guidelines for decommissioningsites (leaving residual hazards protected by barriers) that use stochastic parametervariations to estimate parameter uncertainties (Meyer and Gee, 1999; Meyer andTaira, 2001; Meyer and Orr, 2002).

A recent powerful method of stochastic barrier analyses was performed forthe Mill Tailings Repository in Utah (Ho et al., 2001a,b, 2002a,b). The FRAMESshell with HELP was used to estimate the cumulative probability distribution forthe following four performance measures:

• Peak Ra-226 dose• Peak Ra-226 concentration in aquifer


• Water transport through cover• Radio-gas transport through cover

The exposure scenarios were deterministic. The stochastic analyses allowed forthe estimation of the chance that a given performance measure would be exceededand the relative contribution of different variables to the total uncertainty wascovered. Figure 1.7 provides information on the cumulative probability distributionfor the peak Ra-226 dose that was determined in this analysis. The figure showsthat there is 100% probability that the dose will be below the 100 mrem/year(1 mSv/year) limit. In this example, there is a 50% probability that the dose willbe below 10–12 mrem/year (which is the value of a femto-Sv/year in internationaldose units). The approaches described above can be applied in either a static ordynamic manner. In static analyses, the probability of the occurrence of thescenarios; the boundary conditions; the mechanisms; the state of the barrier; and,hence, the failure rates are considered constant with time. In dynamic analyses, oneor more of the parameters is considered to vary with time. Realistically, no barrieranalysis is totally static because the boundary conditions of precipitation almostalways vary over a year (or several years). Construction quality assurance/qualitycontrol (QA/QC) is often the key issue at the beginning of service life, but several

FIGURE 1.7 A typical risk-consequence matrix. (From Stewart, M.G. and Melchers R.E.,1997. Probabilistic Risk Assessment of Engineering Systems, Chapman & Hall, London.With permission.)

Likelihood

Consequences

Almost certain(5)

Likely(4)

Moderate(3)

Unlikely(2)

Rare(1)

Insignificant(1)

Minor(2)

Moderate(3)

Major(4)

Catastrophic(5)

High risk

Significant risk

Moderate risk

Low risk


combinations of factors become the overriding issue during long service lives.Indeed, the United States Environmental Protection Agency (USEPA) found QA/QCproblems at several barriers studied in 1998 (USEPA, 1998). The challenge is toestimate the state of the system toward its end of life. For illustration, considerthe section ABCD through a conceptualized model of a cover system (Figure 1.8).The barrier AB is a cap composed of a number of layers of different permeabilities(and other properties) and may include a man-made membrane. It may be assumedthat the properties of this latter subsystem are reasonably well known. On theother hand, it may be that CD represents a natural barrier with permeability andother properties that are known only with considerable uncertainties.

1.3.5 DEMONSTRATING COMPLIANCE: THE SAFETY CASE CONCEPT

A safety case consists of a document describing how the regulatory safety goalshave been met. Such a document is reviewed or audited by the regulatory authorityto ensure the following:

• The study deals in sufficient depth with the facility under discussion(completeness requirement).

• Appropriate event probabilities and consequences have been considered.• Compliance to the relevant regulations has been achieved and

documented.

An important advantage is that the onus of proof is put on the licensee oroperator. Safety cases are used extensively in the off-shore, chemical and petro-chemical industries, particularly in Europe, and are similar to the demonstration

FIGURE 1.8 Schematic cap containment system showing potential fluxes and someinfluences.

ContaminantDifferentialsettlements

Flux Q1(t)Environmentalinfluences E1

Barrier layersresistance R2(t)

Barrier layersresistance R1(t)

A B

CD

Flux Q2(t)Environmentalinfluences E2


of compliance for operational activities or environmental impact assessments fornew systems adopted internationally.

1.3.6 MIXED CRITERIA

A mixed economic and regulatory framework for decisions is the so-calledALARP (as low as reasonably practical) or the ALARA (as low as reasonablyattainable) approach. Although terms such as “low,” “reasonably,” “possible,” and“attainable” are highly subjective and difficult to define, ALARP has been widelyadopted (e.g., USNRC, off-shore industry members). The concept is sketched inFigure 1.9, and an overview is provided by Stewart and Melchers (1997).

1.3.7 QUALITATIVE AND INDEXING ANALYSES

This is the simplest level approach. Numbers are not used in qualitative analysis,only subjective assessments, perhaps obtained from interaction between riskanalysts and operators. The results can then be put into a risk-consequence matrix.This approach is easy to use and useful for nontechnical audiences. However, itis difficult to use with quantitative approaches to risk assessment. The rankingscannot be converted to numbers, as the outcome can be meaningless and incon-sistent. An example of a qualitative risk-consequence matrix is shown in Figure1.7. The indexing approach involves assigning ratings that usually are not ana-lytically derived, but represent performance assessments conducted on the basis

FIGURE 1.9 ALARP concept. (From Stewart, M.G. and Melchers R.E., 1997. Probabi-listic Risk Assessment of Engineering Systems, Chapman & Hall, London. With permission.)

Unacceptable region-risks cannot be justified (except in extraordinary circumstances)

ALARP region-risk reduction isimpractical or costs are disproportionateto benefits gained

Acceptable region-ensure risks remain in this region

Negligible risk


of experience with such systems or subjective estimates of performance proba-bilities. This approach was used by Einarsson and Rausand (1998) in rating thesurvivability of an industrial system that was subjected to a number of stressors.

1.4 QUANTIFICATION OF LONG-TERM DAMAGE SCENARIOS, EVENTS, AND MECHANISMS

Establishing the quantitative relationship between containment system or com-ponent reliability and design has been targeted by many researchers, among whichare Gilbert and Tang (1995), Hartley (1988), Bogardi et al. (1989), and Shackel-ford (1992). The limitations of current performance assessment models fall intoone or more of the following categories:

• Description of only statistical reliability of sample test data for initialfacility design

• Use of time-invariant barrier material characteristics and contaminantloading/stress levels to develop long-term performance estimates

• Repetition of stress tests to a few cycles corresponding to short servicelives relative to the service lives of real facilities

1.4.1 CATEGORIES OF DEGRADATION MECHANISMS

The potential for damage of containment systems under applied stress is deter-mined by the interactions among three categories of factors that can change inmagnitude with time: location factors, design and operational factors, and wastecharacteristics. While some damage phenomena occur continuously, others aretransient and can cause instantaneous damage if the resistance of the system orits components is exceeded by the applied stresses.

1.4.1.1 Slow Physico-Chemical and Biological Processes

Among the physico-chemical processes that can damage barriers are barrierflocculation at low depth of burial; chemical attack and photo-aging of geotextiles,slurry settlement, dissolution; and freeze-thaw action (Chamberlain and Gow,1978; Fernandez and Quigley, 1991; Fleming and Inyang, 1995; Elias et al., 1997;Daniels et al., 1999, 2001). Liu and Gilbert (2002) identified seepage-induced fluidpressure as a potential damage mechanism for landfill cover slopes. Figure 1.10shows experimental results obtained by Fernandez and Quigley (1991) on theeffects of permeant viscosity and effective stress on the hydraulic conductivityof compacted clays with mineralogies simulative of clay barriers.

Generally, the spatial scale at which physico-chemical and biological pro-cesses degrade barrier systems is microscopic, at least initially. However, mani-festations such as visible flaws, increased flow of fluids through the barrier, and/ora reduction in barrier strength can eventually result. Chen et al. (2000) investigatedthe effects of organic fluid contamination on the compressibility of kaolinite. The


dielectric constant of the liquids was used as an index of physico-chemicalaggressiveness. The results indicate that the kaolinite compressive indexdecreased from 2.8 at a dielectric constant of 1.9 for heptane, to 0.75 at a dielectricconstant of 24 for ethanol. The compressive index was 2.06 for distilled water(which has a dielectric constant of about 80), but decreased slightly for formamide,

FIGURE 1.10 Hydraulic conductivity of water-compacted clay permeated with municipalsolid waste leachate–ethanol mixtures subsequent to prestressing water-wet clay at variouslevels of vertical effective stress. (From Fernandez, F. and Quigley, R.M., 1991. CanadianGeotechnical Journal, 28, 338–398. With permission.)

Hyd

raul

ic co

nduc

tivity

, k (c

m/s

)

10−5

10−6

10−7

10−8

10−9

Water compactedσ′vo = 0 kpaReference k (water)Final k for permeant

Water only

Viscositycontrol

Double layercontrol

0 50% Ethanol in the permeant

% Domestic waste leachate100 50 0

100H

ydra

ulic

cond

uctiv

ity, k

(cm

/s)

10−5

10−6

10−7

10−8

10−9


Water onlyViscositycontrol



100

Hyd

raul

ic co

nduc

tivity

, k (c

m/s

)

10−5

10−6

10−7

10−8

10−9


Water onlyViscositycontrol



100

% Domestic waste leachate

Hyd

raul

ic co

nduc

tivity

, k (c

m/s

)

10−6

10−7

10−8

10−9

10−10


Water only

Viscositycontrol


100 50 0

100

H−C−C−OHH− H−

H

−

H

−

(Ethanol)є = 32

(a) (b)

(c) (d)


which has a dielectric constant of 110. The authors computed the attractive forcesfor kaolinite in the various organic fluids using the Lifshitz theory and found thatthe attractive force variation agreed with the compressibility results qualitatively.The reader should note that, as discussed in Chapter 3, barrier components rarelycomprise only a single mineral. They are usually composite mixtures such thatmineralogy, particle size distribution, and mix proportions determine their reac-tivity with permeants of a given chemistry under prevailing environmental con-ditions (Inyang et al., 1998a). As nontraditional barrier materials (e.g., paper millsludges) are used more frequently, it is essential to consider physico-chemicalinteractions in barrier design and long-term performance assessment (Moo-Youngand Zimmie, 1997).

Physico-chemical interactions that can affect barrier performance are notlimited to particulate barrier materials. Geosynthetics are known to degrade underattack by permeants with which they are not chemically compatible (Lord andKoerner, 1984). Indeed, as explained by Elias et al. (1997), the potential degra-dation of geosynthetics during service depends on the mineralogy of the fibersthat comprise them, permeant chemistry, environmental exposure conditions, andthe intensity of the stresses to which they are subjected. Indeed, tensile strengthreduction factors for geosynthetics aging ranging from 1.15 to 2 are recom-mended. Test results and semi-empirical analytical approaches for evaluating thetime-dependent mechanical response of high-density polyethylene geomem-branes (HDPE) were presented by Merry and Bray (1997). Regardless of the typeof physico-chemical and biological mechanisms that are known to degrade barriermaterials, transport rates at the microscopic level are likely to be affected. Quan-titative methods that are suitable for use in estimating transport rates of fluidsthrough barriers at the scale in which these processes are significant were describedby Lake and Rowe (2000), Bai and Inyang (1999), and Inyang et al. (2000a,b).These processes should be differentiated from the largely physical mechanismsof fluid flow through large fissures such as cracks, macropores, and inter-liftbreaks in compacted soils, as well as defects in geomembranes. Jayawickramaand Lytton (1992) presented quantitative relationships for estimating flow throughmacropores, while Giroud (1997) comprehensively treated liquid migrationthrough defects in composite liners that comprise geomembranes with defects.In particular, concrete covers such as those used to contain contaminants atbrownfield sites as described by Inyang et al. (1998b) are susceptible to cracking.A number of investigators have presented conceptual frameworks and quantitativemodels for estimating liquid flow rates through cracked systems (Bernabe, 1995;Bai et al., 1996, 1997, 2000a). With appropriate boundary conditions and materialcharacterization, these methods can be used for damaged barrier performanceassessment. Additional discussion of transport mechanisms and models that applyto barriers at various scales is presented in Chapter 2.

Another class of slow processes that impact the exposed surface of barriersis vegetation succession. The process of ecological succession on the exposedcap of a containment system is important for several reasons. First, without activeintervention, the species complex representing the “climax” community is the


one that will ultimately occur on the capping system. While the forces of naturalreplacement can be managed, there are forces that require active intervention(i.e., expenditure of maintenance energy) to change or arrest the natural trajectorytoward the successional equilibrium. The bare soil cap, or cap planted withvegetation in most cases, represents a nonequilibrium condition. As vegetationcolonizes the cap and changes over time, it produces significant changes in thesoil conditions relative to the initial soil conditions. In addition to the changesnoted above, root systems penetrate the soil structure, altering hydraulic propertiesby creating preferential flow paths through the soil and adding organic matter tothe soil matrix. The death and decay of above-ground plant material depositorganic matter on the soil surface, thereby altering the evaporative properties ofthe soil. The increased organic content of the soil and development of preferentialflow paths increases the moisture retention capacity of the soils of the cap system.Similarly, the development of a mulch or litter layer on the soil surface retardsrun off, increases water infiltration rates, and decreases evaporation from the soilsurface.

The timing of successional sequences can vary dramatically, but the attain-ment of the local climax condition takes a long period of time. Smith et al. (1997)reported that in areas near Oak Ridge, Tennessee, the progression from old fieldgrassland to a shrub vegetation stage is expected to take 10 to 25 years, whilethe continued development to a mature forest takes on the order of 65 to 150years. Processes in a Colorado subalpine forest can take 200 to 300 years toachieve the expected spruce-fir forest cover, and the rate of the processes issignificantly influenced by such factors as soil nutrients, aspect (e.g., north orsouth facing slope), and rock cover in the terrain (Donnegan and Rebertus, 1998).Succession in nutrient-poor sand dune communities is similarly slow, with earlysuccessional species being lost within 100 years, while plant species were stillbeing replaced after over 300 years. Rates of change in the plant communitiestend to be most rapid in the earlier stages of the successional sequence.

One highly significant effect of vegetation is the alteration of the waterbalance. Plants mine water and nutrients from the soil to support photosynthesisand growth. Thus, the plant root systems pump water from the soil to the atmo-sphere throughout the growing season. With this property in mind, much workhas been performed in arid and semi-arid climates with water balance or evapo-transpiration caps (DOE, 2000). In this approach, the function of the vegetationis not only to hold the surface soil in place against wind and water erosion, butalso to maintain the water balance of the cap. Surface soil layers are designedby depth and texture to hold the annual input of moisture in the soil matrix, whilethe plants extract the moisture through the growing season, resulting in little orno deep penetration of moisture to the drainage layer. Furthermore, by seedingthese capping systems with the native climax vegetation, the successionalsequence is jump-started, likely minimizing potential surprises as the cappingsystems mature.

The penetration of root systems into the subsurface is also an issue of concern.Plant roots penetrate a soil matrix in search of water and represent a powerful


force. Initial studies of plant root systems on capping systems were largely drivenby concerns about root penetration into buried wastes. Many cases are docu-mented of plant root systems penetrating into buried waste and transportinghazardous material to the surface (Arthur, 1982; Arthur and Markham, 1983).Recent capping system designs have included low permeability clay barriersbetween the vegetated topsoil and the buried waste. Studies have shown that plantroots can penetrate into, if not through, clay barriers. Particularly susceptible topenetration are barriers constructed of clays such as bentonite which have sig-nificant shrink-swell properties as moisture conditions change. Drying of previ-ously hydrated clays of this type leads to cracking and permits points of entryfor plant roots (Nyhan, 1989). One need only witness the ability of plants toestablish in asphalt cracks and concrete pavements with the subsequent deterio-ration of those materials to understand that initial penetration into such claybarriers leads to further deterioration and potential localized movement of waterthrough the barrier into the buried waste. This poses the following two problems.

(i) Potential mobilization of contaminants to the surface through plantuptake — Because plant roots do not absorb some elements, a significant factorin this consideration is the nature of the waste that is buried. Root penetrationinto buried wastes at the Uranium Mill Tailings Remedial Action (UMTRA) sitein Burrell, Pennsylvania, was deemed not to be a significant issue because theplants were not mobilizing the buried uranium mill tailing waste to an extent thatresulted in significant human or ecological risks (UMTRA, 1992). Radioisotopessuch as cesium and strontium, which are analogs for the biologically essentialelements potassium and calcium, have significant remobilization potential if theyare biologically available in the buried wastes. Another type of slow process thataffects the long-term performance of containment systems is global warming becauseof its impacts on regional hydrology and the response of vegetation, soils, andtemperature conditions to expected patterns. It should be noted that large-scale,long-duration events such as global warming may not directly affect containmentsystem performance at initially discernable scales, but may cause significantchanges in environmental conditions that, in turn, impact long-term performance.Uncertainties in the estimates of the impact of large-scale, long-duration phe-nomena such as global warming translate to uncertainties in their impacts onfuture containment system performance. Generally, a possible worse climate forthe barrier should be estimated using climate change modeling and/or examiningthe geological and fossil record. Then, the resulting effects can be estimated bymodeling how the ecosystem would respond to the new climate and/or examiningnatural analogs. The natural analogs can be from the site in question, or can becurrent ecology from a location that approximates the hypothetical new climate.Ho et al. (2002b) used this approach to compare estimates of cumulative probabilitydistributions of a radon-226 dose from a shallow alluvial aquifer (Figure 1.11).

“Natural and archeological analogs exist for ecological change, pedogenesis (soildevelopment), and climate change. Effects of ecological change are inferred by mea-suring water balance parameters in plant communities representing chronosequences


of responses to climate shifts and secondary disturbances (e.g., fire). Pedogeniceffects are inferred from measurements of key physical and hydraulic soil propertiesin natural and archaeological soil profiles that are considered analogous to futurestates of engineered soils. Analogs of local responses to future global climate changeexist as proxy ecological records of similar paleoclimates” (Waugh, 2001).

Indeed, the “present” and hypothetical “future” climate cases by Waugh (2002)were the basis for the two cases by Ho et al. (2002b) in Figure 1.11. In that study,the future climate case was wetter, and the overall performance was calculatedto be worse, but still acceptable.

(ii) Induction of water movement into buried waste — The second andlikely more significant issue associated with root penetration through the imper-meable layers is the induction of water movement into the buried waste. Depend-ing on the magnitude of the water flow and the type of barrier systems below thewaste, this type of failure can result in waste mobilization downward into thevadose zone and potentially to the water table, resulting in a contamination eventthat requires remedial action.

1.4.1.2 Intrusive Events

Just as plants grow on the caps with the root systems seeking water, variousanimal species also invade capping systems with the primary objective of seekingfood or shelter. Both invertebrate and vertebrate species have been documentedto invade waste isolation systems, resulting in the mobilization of buried mate-rials. Bowerman and Redente (1998), Suter et al. (1993), and Smith et al. (1997)summarized experiences of animal intrusion into buried waste. Studies at HanfordWashington and Idaho National Environmental and Engineering Laboratory

FIGURE 1.11 A schematic illustration of landfill deformation due to seismic activity. (FromInyang, H.I., 1992. Journal of Environmental Systems, 21(3), 223–235. With permission.)

Deformed leachatecollection pipe

Drainage layer

Leachatecollection pipe

Clay liner

Landfill surface


(INEEL) in the U.S. documented excavation by harvester ants to depths of 2 to4 m below the ground surface through types of cover materials ranging fromtopsoil to gravel. Studies at a variety of primarily arid and semi-arid sites inWashington, Idaho, New Mexico, and Colorado documented intrusion into cap-ping systems by pocket mice, deer mice, kangaroo rats, pocket gophers, prairiedogs, and ground squirrels. These excavations represented invasions through awide variety of cover systems with penetrations at least to 1 m and probablysignificantly deeper; because in one case animals assimilated radionuclides buriedunder 2.4 m of soil cover. These breaches of cover integrity can be complimentedby slower migration of fines under overburden loads into the pore spaces ofdrainage layers as mathematically modeled by Bai et al. (2000b).

Larger animals are also capable of invading burial sites, primarily in searchof food, but sometimes in search of shelter. Foxes, coyotes, badgers, and otherpredators excavate the tunnels of prey species such as mice and gophers. In thesoutheastern region of the United States, the spread of armadillos represents thethreat of disruption of surface cover systems as they search for insect prey. As isthe case of plants, these organisms are part of the surrounding landscape andsignificant (sometimes excessive) maintenance activities are required to eliminatethem or minimize the effects of their activity once the capping system is con-structed. Given the long expected requirements for cap integrity, high maintenancecosts are not a desirable characteristic for a capping system, as they represent asubstantial mortgage cost that can and should be avoided.

1.4.1.3 Transient Events

Transient events can cause catastrophic damage to containment systems. Amongsuch events are seismic shaking, landslides, and volcanic activity. Inyang (1992)has described the damage potential of near-surface containment systems by seis-mic activity. Figure 1.12 shows a schematic illustration of the potential damagesto landfill components by an earthquake. Excessive ground shaking can causeliquefaction-induced differential settlement of barrier layers, destruction ofimpoundment walls by hydrodynamic forces, interface failures in geomem-brane/soil systems, and sand boiling through liner systems. Several investigatorshave analyzed and documented the impacts of seismic activity on containmentsystems and components (Matasovic et al., 1995; Daneshjoo and Hushmand,1999; Kavazanjian and Matasovic, 2001). The distribution of such events in timeand space is highly variable, owing to the differences in the characteristics ofbedrock and soil cover, as well as the intensity of geodynamic activities. Thus,the potential for containment system damage by transient events varies consid-erably from one region to another. Figure 1.13 shows the regions of the conter-minous United States with greater than 90% probability that acceleration inbedrock will exceed 0.1 g in 250 years. For regulatory purposes, this level of bedrockacceleration is generally considered to be the minimum level required to causedamage to buried and/or embedded facilities when soil cover amplification factors


FIGURE 1.12 Regions in the conterminous United States with greater than 90% proba-bility that the acceleration in bedrock will exceed 0.1 g in 250 years.

FIGURE 1.13 Cumulative probability distribution for peak cumulative dose for Ra-226and its progeny from the shallow alluvial aquifer for present and future conditions. The“present” and “future” curves reflect the present and a hypothetical future climate. (FromHo, C.K. et al., 2002b. Spectrum 2002, Reno, Nevada, August 2002. With permission.)

Cum

ulat

ive p

roba

bilit

y

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.01.0E + 041.0E + 011.0E − 021.0E − 051.0E − 081.0E − 111.0E − 141.0E − 171.0E − 201.0E − 23

Present

Future

100

mre

m/y

r (D

OE

orde

r 540

0.5

|| 1.

a)

Peak cumulative dose (mrem/yr)


are applied. A comprehensive listing of stressing factors and their effects on thelong-term performance of containment systems is presented in Table 1.7.

1.4.1.4 Cyclical Stressing Mechanisms

Several loading mechanisms of barrier systems are repetitive in nature(e.g., freeze-thaw and wet-dry cycling of cover systems). A barrier component orsystem that does not fail at constant loading or imposition of a single-load cyclecan still be damaged by repetitive loads of a single magnitude. The potential andmagnitude of future containment system damage do not depend exclusively onthe level and number of repetitions of stress and intensity of physico-chemicaland biological phenomena. In general, three categories of interactive factors arerecognized: location factors, design and operational factors, and waste factors.A conservatively designed system is likely to resist the same level of stress betterthan a poorly designed system. Furthermore, a well-constructed and maintainedsystem should perform better under stresses that are imposed. Various types ofsystems and barriers exhibit different levels of susceptibilities when exposed todifferent modes of physical stress and other damage processes. Table 1.8 showsa matrix of which stressors are relevant for which barrier systems. Each modelsystem has characteristic materials. The matrix includes the natural subsurfacefor comparison; note that the natural subsurface is isolated from many stressorsthat have impacts on near-surface, engineered barriers. Not shown in the table isan assessment of how important a stressor may be, or when a stressor may beimportant. These aspects must be considered for individual barrier designs atspecific locations (e.g., freeze-thaw cycles can be critical in northern climatesand irrelevant in southern climates).

In particular, freeze-thaw effects on the texture and hydraulic conductivity ofclay barrier materials in cold regions have been intensively investigated. Cham-berlain and Ayorinde (1991) summarized the results of tests performed by manyinvestigators, largely in the laboratory. A set of tests conducted on compactedclays from four facilities produced results that exhibit permeability increases upto three orders of magnitude for 14 freeze-thaw cycles, after which furtherincreases were negligible. In their investigation of the Waite Amulet failings soilcover system near Rouyn-Noranda in Quebec, Canada, Mohamed et al. (1993)found a 23-fold increase in cover permeability due to three freeze-thaw cycles.Experimental results suggest that the initial moisture content, soil particle sizedistribution, and mineralogy play a significant role in determining the magnitudeof increase in soil permeability in response to freeze-thaw cycles (Benoit, 1973).Indeed, for some of the soil cores tested, freezing and thawing caused a decreasein hydraulic conductivity (e.g., soil consisting predominantly of relatively largeaggregates such as 1.0 to 2.0 mm in diameter). To cover scale effects, evaluationsof freeze-thaw effects have also been made at meso-scale and field scale (Millerand Lee, 1992). In their studies, Benson et al. (1995) instrumented a test pad ofcompact clay and performed hydraulic conductivity tests before and after winterseason on block samples retrieved from the field. The results indicated that up


TABLE 1.7How Stressors May Generate Effects on Near-Surface Barriers

Stressor Mechanical EffectsPhysicochemical and Biochemical Effects

Water (rainfall/snowmelt, surface water)

Hydrostatic headErosion (run off, surface water, movement of materials within barriers, localized depressions pooling water)

Ice expansion/contraction

Wet-dry cyclesCorrosionLeachingWater influences plant, animal,

microbial behaviorWater transports contaminantsSurface water brings seeds → plant ecology

Water brings microbes → microbial ecology

Temperature changes Differential thermal expansionFreeze-thawDesiccationIce expansion/contraction

Influences bio-chemical reaction ratesClimate changes impact biota

Wind Mechanical loading of surfaceMovement of objectsErosion of exposed surfaceDelayering (lifting layers)

Bring seeds → plant ecologyBring microbes → microbial ecologyAdd soil → change plant growing conditions → change/hurt/help vegetation

Mechanical loads (seismic, vibration, subsidence, impacting objects)

PuncturingMechanical loadingSettling of fines into coarse layers

N/A

Plants Macro-porosity developmentEvapo-transpiration

Uptake contaminated material and bring to surface

Impact animal ecology (food supply)Impact microbial ecology (e.g., nutrient profiles)

Evapo-transpirationAnimals Macro-porosity

InfiltrationErosion (of excavated material)Digging and exposure of buried material

Impact plant community/speciesImpact microbial ecology (e.g., nutrient profiles)

Microbes Plugging of capillaries Bio-corrosionBio-leachingChange surface tension, e.g., in pores and capillaries

Change PRB biochemistrySoil formation → change plant biota → change animal biota


to 10 freeze-thaw cycles occurred in the season and that the hydraulic conductivityof the samples increased by factors ranging from 50 to 300. More recently, efforthas been made as exemplified by Daniels et al. (2001) to develop quantitativeschemes for interrelating field- and laboratory-based freeze-thaw permeabilitymeasurements and improving the resistance of barriers to freeze-thaw throughsoil stabilizer amendments. In some cases, soil strength can improve at theexpense of low hydraulic conductivity (Daniels et al., 1999).

TABLE 1.7 (continued)How Stressors May Generate Effects on Near-Surface Barriers

Stressor Mechanical EffectsPhysicochemical and Biochemical Effects

Radiation (UV, ionizing)

N/A Material property degradation

Waste Chemical attack Material property degradation

TABLE 1.8Relevant Stressors for Various Barrier Systems

Relevant Stressors Eart

hen

Cap

Con

cret

e C

ap

Top

of G

rout

ed/

Ento

mbe

d St

ruct

ure

Evap

orat

ion

Pond

Lin

er

Line

r at

Bot

tom

of

Was

te Z

ones

Bot

tom

of

Gro

uted

/En

tom

bed

Stru

ctur

e

Vad

ose

Zon

e It

self

(fat

e an

d tr

ansp

ort,

no

t ba

rrie

r pe

r se

)

Water (hydrostatic head, erosion) X X XWater (wet-dry cycles) X X X X XCorrosion/other chemical attack X X X X X XTemperature changes, e.g., freeze-thaw cycles X X X X X XWind erosion X XImposed mechanical stress (subsidence, seismic, structural loads)

X X X X X X

Impacting objects, e.g., construction/operations activities, people and animals walking

X

Plant and/or animal intrusion X X XBiocorrosion X X XOther microbial impacts, e.g., plugging capillaries X XUltraviolet radiation XIonizing radiation XContaminant leachate interaction X X X X


Other cyclical degradation mechanisms of barrier systems include wet-drycycling and desiccation in response to temperature and relative humidity profilesthat can alternate but remain predominantly at high temperature and low humiditylevels during most of the year. At the fundamental level, the swelling potentialof clays has been investigated by many researchers, among whom are Blackmoreand Miller (1961) and Dasog et al. (1988). From a practical standpoint, theinclusion of granular soils (sands and silts) in barrier mixtures and their compac-tion generally decrease shrink-swell potential.

Several investigators have developed empirical methods for analyzing therelationships between the residual strength of structures and the number of loadcycles. Schaff and Davidson (1997) developed Equation (1.7) to describe thepattern of the Weibull scale parameter in terms of the residual strength of com-ponents of structures under fatigue loading:

(1.7)

where Rn is the residual strength scale parameter after n cycles of loading, Ro isthe static strength scale parameter, Sp is the peak stress magnitude of the constant-amplitude loading, N is the scale parameter for the fatigue life distribution, andv is the strength degradation parameter. Equation (1.7) describes the exponentialline shown in Figure 1.14. The reader should note that the strength measured fora particular cycle is observed as a distribution of magnitudes. Thus, the linerepresents the connection of points defined by the specified statistical confidencelevel of strength data for each loading cycle. Kachanov (1986) developed Equa-tion (1.8) for describing damage accumulation in materials and systems as a resultof load repetition:

(1.8)

In Equation (1.8), D is the damage variable, S is the amplitude range of therepeated stress, n is the number of cycles, C > 0 and m ≥ 1 are material constants.In the case of containment systems, D could be fracture intensity or macroporos-ity. In the field, load repetitions are not designed but observed, implying thatobserved data or their estimates need to be fitted to time functions for use inperformance prediction equations.

Quantitative techniques that are based on time-series analysis are useful inefforts to describe the loading pattern of containment systems in the field. Khaliland Moraes (1997) developed a simple method of time-series analysis that isbased on the linear least squares spectral analysis (LLSSA). For a given set ofloading frequencies, the best-fit sinusoidal equation is found for observed data.

R R R Sn

Nn o o p

v

= − −( ) ⎡⎣⎢

⎤

⎦⎥

∂∂

=−

⎛

⎝⎜⎞

⎠⎟D

nC

S

D

mΔ

1


The power of each frequency is taken as the square of the amplitude of the fit.In this method, the function described by Equation (1.9) is fitted to a time seriesfor each frequency. By using the LLSSA, the parameters A and B can be foundthrough Equations (1.10), (1.11), and (1.12).

(1.9)

(1.10)

(1.11)

(1.12)

In the equations, Σ is the variance, γ is the parameter of interest, and t is thetime. The error on each of the two parameters A and B can be estimated usingEquations (1.13) and (1.14), respectively. Then, the total error of the power canbe expressed as in Equation (1.15).

FIGURE 1.14 Strength distributions associated with a residual strength Weibull relation-ship with number of loading cycles on materials. (From Schaff, J.R. and Davidson, B.D.,1997. Composite Materials: Fatigue and Fracture (Sixth Volume). ASTM STP 1285, pp.179–200. With permission.)

Resid

ual s

tren

gth,

R (n

)

Peak

Static strength

Residual strength relation

Failed portionof distribution

Stress

γ γ ω ωi avg i iA t B t− = • + •cos sin

A t t t t ti i i i i i i= − ∑∑∑1 2

Δγ ω ω γ ω ω ωcos sin sin cos sin∑∑⎡⎣⎢ ⎤

⎦⎥

B t t t t ti i i i i i i= − ∑∑∑1 2

Δγ ω ω γ ω ω ωsin cos cos cos sin∑∑⎡⎣⎢ ⎤

⎦⎥

Δ = − ( )∑∑∑cos sin cos sin2 22

ω ω ω ωt t t ii i i i


(1.13)

(1.14)

(1.15)

The phase of the periodicity, Ø, and its error, σØ, can be estimated usingEquations (1.16) and (1.17).

(1.16)

(1.17)

With these parameters, the best-fit sinusoidal equation can be developed fordata that fluctuate in cycles over time. Khalil and Moraes (1997) applied thismethod to a different type of problem: determination of the concentration vs.time function for methane in ice cores during the past 160,000 years (Figure 1.15).

1.4.2 QUANTITATIVE LINKAGE OF CONTAMINANT RELEASE SOURCE TERMS TO RISK ASSESSMENT AND COMPLIANCE LIMITS

Risk assessments of containment facilities require estimating the level of hazardposed by a containment system to human health and the environment. Theestimation of risks to human health and the environment is at the posterior endof the analyses. At the anterior end, there is the step in which estimates of theprobable quantities of contaminants that will be released from the facilities aremade. Such analysis is typical at the source term assessment stage illustrated inFigure 1.16 by the USNRC (2000) as adapted from Kozak et al. (1990). Theoverall framework for relating containment system performance (operationallydefined in terms of source term concentrations) to human health and ecologicalrisk assessment are illustrated in Figure 1.17 as developed by Nazarali et al.(1998). System failure can be defined in terms of the exceedence of a given

σγ γ ω

A

fit it

N2

2 2

2=

−( )−( )∑sin

Δ

σγ γ ω

B

fit it

N2

2 2

2=

−( )−( )∑cos

Δ

σ σ σP A BA B2 2 2 2 24= +( )

Ø

/

/=

− >

− − < >

−

−

−

−

tan ( )

tan ( ) ,

tan (

1

1

1

0

0 0

B A A

B A A Bπ

BB A A B/ ) ,+ < <

⎧

⎨⎪

⎩⎪ π 0 0

σσ σ

φ =+

⎛

⎝⎜⎞

⎠⎟−

+

⎛

⎝⎜⎞

⎠⎟B

A B

A

A BA B

2 2

2

2 2

2


probability of release of specific quantities of target contaminants in the future.Such a quantity can be specified on the basis of the known or assumed humanhealth and environmental risks associated with exposures to the target contami-nants at contaminant levels above the specified values. As shown in Figure 1.18,releases of a specific contaminant from a containment system over a given intervaloccur as a distribution. Several uncertainties plague efforts to make preciseestimates of the probability of release of specific quantities of contaminants forselected future time frames. Gallegos et al. (1998) identified the following sourcesof uncertainty in long-term performance predictions of containment systems:

• Uncertainty in the likelihood of occurrence of future events• Uncertainty in conceptual and analytical models that describe events

and processes• Uncertainty in parameter values

The establishment of the compliance of a containment system with selectedperformance criteria is characterized by the uncertainties stated above. Indeed,one of the utilities of system dynamics approaches described by Siu (1994) isthat possible interactions among various performance factors can be addressed,and uncertainties can be reduced by using the evolving knowledge base.

FIGURE 1.15 Methane concentration vs. time experimentally measured on ice cores.(From Khalil, M.A.K. and Moraes, F.P., 1995. Journal of the Air and Waste ManagementAssociation, 45, 62–74. With permission.)

Conc

entr

atio

n (p

pbv)

700

600

500

400

300

20016012080

Kiloyears before present400


Two common types of probabilistic analyses can be used in assessing con-tainment system performance. Quantified risk analysis (QRA) gives all elementperformances and all probability estimates as numerical point estimates. Thereis no estimate of the uncertainty in the result(s). QRA is widely employed in the

FIGURE 1.16 Conceptual model showing processes to be considered in an LLW perfor-mance assessment. (USNRC, 2000. A performance assessment methodology for low-levelradioactive waste disposal facilities. Recommendations of NRC’s Performance AssessmentWorking Group. NUREG-1573. United States Nuclear Regulatory Commission, Office ofNuclear Material Safety and Safeguards, Washington, DC; modified from Kozak, M.W.et al., 1990. U.S. Nuclear Regulatory Commission, NUREG/CR-5532, Washington, DC.)

Infiltration

Container breach

Engineeredbarrier

performance

Air transport

Vadose-zonetransport

Source term detail

Waste from leach

Facility release

UnsaturatedVadose-zone

flow

Engineered barrier performance

Source term

Vadose-zonetransport

Saturated-zone transport

Saturated-zone flow

Surface-water transport

Pathways and dosimetry

Dose to human

Air transport


FIG

UR

E 1.

17R

isk

calc

ulat

ion flo

w c

hart

. (Fr

om N

azar

ali,

A.M

. et a

l., 1

998.

Pro

ceed

ings

of

Topi

cal M

eeti

ng o

n R

isk-

Bas

ed P

erfo

rman

ceA

sses

smen

t an

d D

ecis

ion

Mak

ing,

Ric

hlan

d/Pa

sco,

Was

hing

ton,

Apr

il 5–

8, p

p. 1

43–1

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ith p

erm

issi

on.)

Risk

Risk

Gen

eric

plan

t

Gre

at b

asin

pock

et m

ouse

Coyo

te

Red-

taile

dha

wk

Resid

entia

lex

posu

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ioun

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Indu

stria

lex

posu

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it ris

k

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icul

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lex

posu

re sc

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it ris

k

Recr

eatio

nal

expo

sure

scen

ario

unit

risk

Ecol

ogic

al

Hum

anhe

alth

Tran

spor

ted

unit

conc

entr

atio

nt =

40

year

s

Tran

spor

ted

unit

conc

entr

atio

nt =

100

year

s

Tran

spor

ted

unit

conc

entr

atio

nt =

140

year

s

Tran

spor

ted

unit

conc

entr

atio

nt =

10,

000

year

s

Sour

ceco

ncen

trai

ont =

0

Sour

ceTr

ansp

ort

Expo

sure

Risk


chemical and petrochemical industries. Probabilistic risk analysis (PRA) is moreadvanced than QRA and has element performances treated as random variables.Occurrence rates also can be given as random variables. PRA is the method ofchoice in the nuclear industry. Although more complex, more explicitness isrequired in the analysis and outcome uncertainty is recognized. Both methodsuse essentially the same tools but more refined data and analysis is used in the

FIGURE 1.18 Probabilistic approach for treating model parameter uncertainty in an LLWperformance assessment. (From USNRC, 2000. A performance assessment methodologyfor low-level radioactive waste disposal facilities. Recommendations of NRC’s Perfor-mance Assessment Working Group. NUREG-1573. United States Nuclear RegulatoryCommission, Office of Nuclear Material Safety and Safeguards, Washington, DC.)

f(x) f(y) f(z)x y

Estimate distributions of valuesfor parameters x, y, and z

Input distributions into model

Produce distribution of model results

Compare with dose limits

Freq

uenc

yFr

eque

ncy

Dose = g(x, y, z)

z

Dose

Dose limit

a

Dosea = Probability of dose limit being exceeded


case of PRA. Estimates of performance (i.e., failure or success) probabilities ofcomponents need to be made. For a composite containment system that comprisesmany components, the following sequential steps can be taken:

1. Disassemble the system into components.2. Analyze the system (e.g., series, parallel, compound).3. Consider the technology and understand each component.4. Predict future performance of each component (with uncertainty).5. Reassemble the components and their future behaviors.6. Assess critical components vs. system behaviors.7. Develop future expected system performance vs. time (or a surrogate).8. Estimate system uncertainty vs. time.

1.4.3 FRAMEWORKS FOR ASSESSMENT OF EVENT CONSEQUENCES AND CONNECTIVITIES AMONG CAUSES OF FAILURE

Two important assessment systems aid in the analysis of long-term performancecharacteristics of multi-component facilities and systems: fault trees and eventtrees.

1.4.3.1 Fault Trees

The connectivity of failure causes is often represented by a fault tree (Figure1.19). A fault tree describes the chain of events leading to system failure and isused extensively for estimating the reliability of mechanical systems such asrockets and aircraft. Fault trees form the basis for quantitative estimation of failureprobabilities in systems with simple pass-fail components, using point estimatesof the probability of occurrence for each failure event. They are less suited toreliability analysis for systems that are likely to fail mainly because of stochasticprocesses. However, Cepic and Mavko (2002) discussed the use of the dynamicfault tree method to analyze the performance of multi-component systems.

1.4.3.2 Event Trees

The consequences arising from component failure usually can be represented byan event tree (Figure 1.20). Again, usually point estimates of the probability ofoccurrence of each event in the event tree are used to predict outcome probabilitiesfor each of the various outcomes.

1.4.4 ESTIMATION OF LONG-TERM FAILURE PROBABILITIES

The use of system failure probabilities as the target of computational steps providesan opportunity for estimating the reliability of containment systems and theirdecay or improvement with time. It should be noted that the relationship betweenreliability and failure probability is complementary as expressed in Equation(1.18). The sum of system reliability, Rss, and the system failure probability, Fss,


must be unity. Because the objective is to track the variability in barrier perfor-mance with time, both Rss and Fss can be considered to be time functions.

(1.18)

1.4.4.1 System Failure Probability

The composite containment system illustrated in Figure 1.8 can be subjected toa number of loads (i.e., structural and chemical), with a resulting condition inwhich contaminants have greater potential to travel through its barrier system.Any of the component barriers can have subcomponents, but in order for thebarrier to fail functionally, the contaminant must penetrate all layers. Hence, ina simplified case, and as discussed by Stewart and Melchers (1997), the barriercan be considered as a system with n parallel components, with system failureFss requiring failure Fi (i = 1, …, n) of each component barrier. Both structurallyand functionally, the configuration barrier system components may be such thatsome components are arranged in parallel mode, series mode, or a combinationof both (i.e., compound mode). For a parallel system of components, Equation(1.19) represents the relationship between the failure of components and that ofthe system:

FIGURE 1.19 A typical fault tree for a waste containment system.

Contaminant release volume/rate exceed

design value

Liner systemdamage

Loss of cover system effectiveness

Cover clay fails to contain

infiltration

Drainage layer clogs

Vegetative cover develops

infiltration channels

R Fss ss= −1


(1.19)

When there are multiple failure paths perhaps through multiple barriers (Figure 1.8),failure of the whole or a significant part of the whole system, Fs, may be broughtabout by failure of one or more of the subsystems, Fssj:

(1.20)

where the component terms Fssj refer to any failure path and may be defined byEquation (1.19) in the case of a failure path having to cross through a barrierwith multiple layers. Note also that Equations (1.19) and (1.20) define the failuredomain for the system (Stewart and Melchers, 1997).

1.4.4.2 Component Failure Probability

Theoretically, for a multi-component system, the system failure probability cannotbe estimated precisely without computation of the failure probabilities of eachof the system components. For the containment system illustrated in Figure 1.8,if contaminant flux is selected as the performance factor, the probability of failure(exceedence of a specified flux within a specified time interval) can be modeledas a random process on a barrier parameter, Q(t), because the several factors

FIGURE 1.20 A typical event tree for a waste containment system.

Liner systemdamage

Drainagelayer clogs

Vegetative layerdevelops large

infiltration channels

Cover clayfails to contains

contaminant

Contaminant releasevolume and rateexceed design value

Contaminant releasevolume and rate do notexceed design value

Contaminant releasevolume and rateexceed design value



Yes

No

Yes

No

Yes

No

Yes

No

Consequences

F F F Fss = ∩ ∩ ∩1 2 3 etc.

F F F Fs ss ss ss= ∪ ∪ ∪1 2 3 etc.


presented in Table 1.8 have highly uncertain magnitudes. When one layer in abarrier is subject to only one flux, the flux will be a function of time. Becausethe flux is a complex process that is not well defined as a function of environ-mental influences (e.g., rainfall, temperature, water table fluctuations, groundmovements, earthquakes), it is appropriate to model it as a random process,Q(t) (Figure 1.21). This is approach is not uncommon in other applications suchas water resource projects.

Also shown in Figure 1.21, a barrier parameter, R, must not have a valuegreater than r, where r is a deterministic quantity that represents the resistanceoffered by the containment system barrier layer(s) to the permeation of the fluxQ(t) through it. Failure is defined by the upcrossing event Q(t) > r.

Of particular interest is the time, t1, to the first occurrence of a failure event(i.e., the first exceedence event). This time should be long for safe containmentsystems, and can be estimated readily if the exact trace of fluctuating loading isknown. However, because the loading is a stochastic process, the first exceedenceevent will be a random variable. Its estimation is a central matter in reliabilitytheory and is further discussed by Inyang (1994), Inyang et al. (1995), andMelchers (1999). Following the analysis by Stewart and Melchers (1997), twoprobability density functions are shown to the left of Figure 1.21. The main one,instantaneous distribution, refers to all possible values of the load (flux). Thepoint where the resistance, R = r, cuts across it has a small (shaded) part of theprobability density function above it. This is the probability that Q(t) > r. Evi-dently, the shaded zone (i.e., the probability of failure) will be smaller for highervalues of resistance, r. Also, the time to the first exceedence event is expected toincrease with r, indicating the importance of the resistance level.

FIGURE 1.21 Realization of a continuous random process showing time to firstexceedence. (From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction,2nd ed., Wiley, Chichester. With permission.)

Extreme value distribution

Instantaneous distribution

Realization of load

First exceedence time t Time t

1

Load Q

Barrier R = r

Upcrossing event Q > r


The other probability density function is an extreme value distribution thatrefers to the distribution of peaks (e.g., the maximum value recorded in any oneyear, month, or other time period). The reader is referred to standard textbookson probability for deeper treatment of extreme values distributions. More gener-ally, more than one flux can act on a given barrier or layer with the loadingdescribed by a vector process, Q(t). The details are not of concern here, exceptto note that the problem becomes an outcrossing of two processes: a continuousprocess and a pulse process (Figure 1.22). Also, the resistance becomes anenvelope in the space of Q(t). The first exceedence time is now the time wheneither the load process or the combined action of the two processes outcrossesthe envelope of capacity (i.e., the combined process or any individually crossesfrom the safe domain to the failure domain). Figure 1.9 shows a particularrealization of the load process.

The probability that the system fails in a given time period (0, tL ) (e.g., thedesign life) can be stated as the probability that the system will fail when it isfirst loaded, denoted pf (0, tL ), and the probability that it will fail subsequentlygiven that it has not failed earlier. This can be expressed as follows:

(1.21)

where v is the outcrossing rate. The expression is approximate because the second[ ] term is based on the assumption that failure events are rare and that suchevents therefore can be represented by the Poisson distribution, which leads tothe expression shown.

If the random load processes are assumed to continue indefinitely and havea stationary statistical nature (e.g., in the simplest case, the means and variances

FIGURE 1.22 Envelope of resistance showing a realization of the vector load processand an outcrossing by one load component.

Load 1

Load 2

Time t

Envelope of resistance

Outcrossing event

P t P t P t vtf f L f L( ) ( , ) [ ( , )][ exp( )]≈ + − − −0 1 0 1


do not change with time), then the rate at which they cross out of the safe domain(i.e., the outcrossing rate) can be estimated from the following:

(1.22)

where X = X(t) is a vector process and ( )+ denotes the positive component only.The term E(Xn�X = x) = xn = n(t) · x(t) > 0 represents the outward normalcomponent of the vector process at the domain boundary. Note that the integralextends over the safe domain, which is the complement of Equations (1.19) and(1.20).

The result (Equation (1.21) is valid only for rare outcrossings like those thatmight be associated with failure due to extremely rare, high-load events. Theresult can be extended (i) to allow for gradual deterioration of structural strengthwith time with the result that pf(0, tL) and v become time dependent, and(ii) approximately for situations with outcrossings which are not rare.

Approaches to evaluating expressions pf(0, tL) and v for the expected life and,hence, the reliability of the system are available through Monte Carlo simulationand further simplifications of the problem. However, in both cases, Equations(1.21) and (1.22) must allow for the resistance R = R(t) to be a random variableas a function of time or a slow stochastic process (Stewart and Melchers, 1997).

1.4.4.3 Random Resistance

In practice, the actual resistance R = R(t) will not be known precisely. Moreover,it will vary from point to point across the barrier, suggesting that actual resistanceshould be expressed as R = R(x,y,t) and modeled as a random field (Vanmarcke,1983). However, this represents a difficult problem. Consider first the case of asingle point in (x,y) space. Then R = R(x,y,t) becomes R = R(t) and could bemodeled as a random variable, expressed through a probability density function(e.g., as in Figure 1.23). It follows that the line R = r shown in Figure 1.21 isjust one realization of many possible outcomes.

Usually, the resistance is made up of a number of components or is theoutcome of a calculation procedure involving several variables. These, too, canbe uncertain and may be expressed as random variables or processes. The mod-eling of R = R(t), therefore, can be complex. The issues involved can be illustratedwith a simple example. Consider a random variable, S, that is a function of twoothers, M and A, given by:

(1.23)

The probability density function fs(s) of S can be estimated from the correspondingprobability density functions for M and A using Equation (1.23). In general, this

v E X f x dxn X= =⎛

⎝⎜⎞

⎠⎟•

+

∫ X xsafedomain

( )

S MA=


will require numerical integration and, in the case of complex functional rela-tionships, Monte Carlo simulation. However, a simpler but approximate approachis to calculate only the first two moments of S using standard expressions, asfollows:

(1.24)

(1.25)

where V = σ/μ is the coefficient of variation. Here, μs is the mean (i.e., the expectedvalue) and σ2

s is the variance. The latter is a first estimate of the degree ofuncertainty associated with S. Extending this approach to a function that is morecomplex than Equation (1.23) leads directly to the so-called error propagation(or second moment) techniques already used in the environmental modeling arena,and earlier in the general system reliability evaluations (Shakshuki et al., 2002).Although these techniques are sometimes termed risk or reliability techniques,they are strictly techniques for estimating uncertainty involved in the algorithm.

For the case of a random field, R = R(x,y,t), two approaches are possible.One is to use random field theory to represent R = R(x,y,t) and to apply MonteCarlo simulation in (x,y) space to estimate the outcrossing rate (Vanmarke, 1983).This is a major computational task for realistic problems. A simpler approach isto estimate the probabilistic properties of the weakest failure path using extremevalue theory. The problem then reverts to the case described above, but now withminimum resistance for a given barrier area, Rmin = Rmin(t), with the associatedprobability density function (Melchers, 1999).

1.4.4.4 Simplifications of Theory

The theory sketched above can be simplified using a small number of assumptions.The main outcome is that the formulation does not address time explicitly.

FIGURE 1.23 Schematic probability density function of resistance.

Probability

Meanresistance

Resistance

μ μ μS M A= +

V V VS M A2 2 2≈ +


Although this implies significant limitations, the approach has been appliedsuccessfully to other problems. The first assumption is that resistance remainsconstant with time, at least for reasonably long periods of time. A step-wiseapproximation could allow for deterioration provided the stationarity remainsvalid. The second assumption is that the load processes are stationary, that is,their statistical properties do not change with time. As a result, the outcrossingrate, v, is constant with time, meaning that the probability of failure for any givenperiod of time is constant. When only one load is primarily of interest, the aboveassumptions allow that load to be represented by only its probability densityfunction. This represents a significant computational simplification. When mul-tiple loads act, usually one load dominates a particular failure scenario, allowingthe loadings to be combined into load combinations that show the dominance ofone load or high correlation between the dominant loads (such that they can berepresented by the one random variable). Finally, under the above assumptions,the initial failure probability pf(0, tL) of Equation (1.21) can be subsumed into therandom variable representation.

Consider now the case with just one load. Let this be the extreme value duringthe lifetime, with associated extreme value distribution fQ( ) (in this case for themaxima). Evidently, the maximum load is applied only once and the probabilityof failure is, thus, directly related to the probability distribution of the maximumload as follows:

Failure: (1.26)

in the event that the maximum load is applied or

(1.27)

where Z is the safety margin. It follows that the probability of failure is:

(1.28)

Allowing also for random strength with associated probability density, fR(r),Equation (1.28) becomes:

(1.29)

where FR( ) is the cumulative distribution function for R. It is given by:

(1.30)

r Q<

Z r Q= − < 0

p r Q Z f x dxf Q

r

= < = =

∞

∫Prob( Prob( < 0) ) ( )

p R Q F x f x dxf R Q= < =−∞

∞

∫Prob( ) ( ) ( )

F r R r f x dxR R

r

( ) ( ) ( )= < =−∞∫Prob


Equation (1.29) is known as a convolution integral and can be interpretedloosely as follows. Under the integral, the first term, given by Equation (1.30),denotes the probability of failure given that the actual load has the value Q = x.The second term is the probability that the load takes the value Q = x. This isthen integrated over all possible values of x, a dummy variable. In general, it isdifficult to solve Equation (1.29) in closed form. As seen below, an importantexception is when R and Q are each represented by a normal distribution or, moregenerally, are completely described only by their means and variances. Equation(1.29) could also have been written as follows:

(1.31)

where G( ) is known as the limit state (or performance) function, and X = (R,Q)denotes the random vector of loads and resistances in general. Expression G(X) <0 represents the condition that the bar will fail and was noted earlier.

Then, Equation (1.30) can be extended to the case where several performancefunctions (e.g., Equations (1.19) and (1.20)) are met. Equation (1.20), for exam-ple, becomes the following, with X collecting all of the random variables in theproblem:

(1.32)

where fx( ) is the joint density function of the random variables, X. The solutionof Equation (1.32) is not a simple matter. One option is to use Monte Carlosimulation to perform the integration. However, in its elementary form, thismethod is highly inefficient. An alternative is to linearize the boundary ∪

iGi(X) =

0 of the region of integration (i.e., a first-order approximation) and simplify theform of Equation (1.32) to each random variable being represented only by itsfirst two moments. These two simplifications allow the problem of integration tobe bypassed altogether, because simple rules can be used for the addition ofrandom variables represented by their first and second moments (i.e., mean andvariance). For obvious reasons, this approach is called the first-order secondmoment (FOSM) method. Because of its simplicity, it is widely used.

In the FOSM method, the mean and standard deviation of the safety margin(Figure 1.24) are, from probability theory rules:

(1.33)

(1.34)

with, as before, failure denoted by Z < 0 and survival by Z ≥ 0 (Figure 1.24).Hence, the probability of failure becomes:

p R Q Z G Xf = < = < = <Prob Prob Prob( ) ( ) [ ( ) ]0 0

pf f x dxx

G xi

i

=∪ <∫∫… ( )( ) 0

μ μ μZ R Q= −

σ σ σZ R Q2 2 2= +


(1.35)

where Φ( ) is the standard normal distribution function with zero mean and unitstandard deviation or variance. It is extensively tabulated in statistics texts, atleast for higher probability levels. For low values of probability, more detailedtables are required (Melchers, 1999).

The parameter β is known as the safety or reliability index. Evidently,β = μZ /σZ and measures, in the space of the safety margin (Figure 1.24), thedistance from the mean of the safety margin to the failure condition in terms ofthe uncertainty, σZ, of the safety margin. Evidently, a greater β implies a lowerprobability of failure and vice versa (Melchers, 1999).

1.4.4.5 The Multi-Dimensional Case

The above concepts carry over directly to problems involving multiple resistanceparameters and multiple loads, but not load processes. For load processes, time-dependent theory must be used. It is conventional to transform all of the loadsto the standard normal space Y (with zero mean, unit variance). The limit statefunction, which must be linear, is transformed also to g(y) = 0 about the (as yetunknown) design point, y*. Where there is dependence between the variables orwhere they are not normal, the Nataf, Rosenblatt, or some other transformationis required (Melchers, 1999).

Figure 1.25 is a sketch of the problem in two-dimensional y space, showingcontours of the hill described by the joint probability density function, fY (y), ofall the transformed random variables, Y. The probability of failure, pf, is represented

FIGURE 1.24 Probability of failure and safety index. (From Melchers, R.E., 1999. Struc-tural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

Z < 0Failure

Z > 0Safety

fZ(z)

pf

0

βσz

zμz

σz

p R Q ZfZ

Z

= − < = < =−⎛

⎝⎜⎞

⎠⎟= −(Prob Prob( ) ( )0 0

0Φ Φ

μσ

β))


by the volume under this hill in the failure region, i.e., the region for which g(y)< 0. As before, rather than address pf directly, it is convenient to work with thesafety index, β. The central statement of the FOSM problem then becomes:

(1.36)

where yi represents the coordinates of any point on the limit state surface, g(y) =0. This is an optimization problem and can be solved using any appropriateminimization algorithms.

Figure 1.26 shows the same situation with m (i.e., multiple) limit states. Inthe case of a series system, series bounds can be used to collect together theprobabilities estimated separately using Equation (1.36) for individual limit states.There are several such series bounds, the simplest (and least accurate) being:

FIGURE 1.25 Space of standard normal variables and linearized limit state function.(From Melchers, R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley,Chichester. With permission.)

Failure domain

g(y) = 0 Non-linear

g(y) = 0 Linearized

Contours of fy (y)

y10

y2

y*ν Safe domain

β

β = =⎛

⎝⎜⎜

⎞

⎠⎟⎟

=∑min( · ) miny y yT

i

i

n

1 2 2

1


(1.37)

with pf system denoting the probability of failure for the structural system with mlimit state functions. Bounds are available also for the intersections of two ormore limit state functions (Melchers, 1999).

1.4.5 COMPONENT AND SYSTEM FAILURE IN CONTAINING CONTAMINANTS

The proper reliability estimation of a system such as in Figure 1.8 is a significanttask, recognizing the complex relationships governing the inputs and environ-mental effects. Reliability estimates are heavily dependent on the information inthe tails of probability distributions, implying that a good understanding of theinput and output processes exists and that they can be modeled appropriately.Although simplified models can be used, their use affects the quality of theoutcomes from a reliability analysis. Other alternatives are characterized by somedeficiencies: simpler methods of safety or risk assessment, modeling and infor-mation about stochastic processes, and probabilistic variables that hide these

FIGURE 1.26 Series system representation in standard normal space. (From Melchers,R.E., 1999. Structural Reliability Analysis and Prediction, 2nd ed., Wiley, Chichester. Withpermission.)

g1(y) = 0linearized

g1(y) = 0

g2(y) = 0

g3(y) = 0

Contoursof fy(y) = 0

Safe domain

y1

y1*

y2Failuredomain

Df

0β1 β3

β2

maxi

m

fi f system fi

i

m

fi

i

p p p p=

= =

( ) ≤ ≤ − −( ) ≈∏11 1

1 1mm

∑


difficulties by ignoring the uncertainties. Their application can lead to a falsesense of security in future performance estimates.

It follows that the simplifications introduced above in reliability theory alsoshould be used with care. As indicated, each requires significant assumptionsabout the system behavior. Thus, when predicting the long-term reliability ofcontainment systems, the time-variant approach is the most appropriate.

The incompleteness of data and probabilistic models need not, however, bean insurmountable obstacle in the application of reliability theory. As discussedbriefly below, experience gained in-service through monitoring and observationcan be used to refine understanding of the system and characteristics of theprocesses involved. The tools to monitor and observe are Bayesian updating andsystem dynamics analysis, both of which are increasingly recognized as powerfultools in geoenvironmental engineering.

A second and equally important aspect of the Bayesian method is the use ofsubjective probabilities in reliability analysis and elsewhere. The probabilitydistributions and the stochastic process representations in the exposition abovewere assumed to be completely known. Classic statistical literature assumes thatthese can be inferred from observation of sufficient experiments, as in the use ofmonitoring data. The issue of modeling vs. monitoring with respect to contain-ment system performance assessment has drawn attention from many researchersand practicing personnel. Inyang (2003) provided an assessment of the generalutility of monitoring and modeling in environmental assessments. Following theissues discussed by Melchers (1999), it is not surprising that engineers and someapplied scientists have taken a more pragmatic approach and assumed that evennonfrequent subjective information obtained from less formal observation andexperience can be applied in probability theory and, hence, reliability theory.Subjective information can, as Bayes implied, be used as prior information andrefined as more data become available (see below). This is an important pointwith respect to applying probabilistic methods for the long-term performanceanalysis of waste containment systems. In essence, there is convergence in utilitybetween probabilistic analysis and the use of monitoring data, but monitoringdata alone are insufficient as the bases for predictions and system management.

1.4.6 RELATING PROBABLE CONTAMINANT CONCENTRATIONS TO RISKS

Within the regulatory context, the effectiveness of a waste management system(of which a containment system is a part) is most commonly appreciated in termsof ecological and human health risks. Therefore, it is necessary to establish therelationship between the failure probabilities of the containment system andhuman health and ecological risks. Risk assessments require the input of con-taminant source terms. As a simple illustration, Reddi and Inyang (2000) devel-oped Equation (1.38) to estimate the source term for a containment system thatreleases contaminants into the vadose zone. This equation is presented in con-junction with Figure 1.27.


(1.38)

where Co is the source term concentration per unit width of the plume forcontaminant fate and transport modeling (M/L2), q is the contaminant flow rateper unit width in the vadose zone (L2/T), Ca is contaminant concentration in thevadose zone (M/L3), d is the width of the saturated zone (L), Vh is the plumevelocity (L/T), and b is the plume thickness (L). Obviously, parameters Ca andq are determined mostly by containment system performance.

Deterministic equations that express the flow rate and quantities of contam-inants through the components of a containment system (such as those presentedin Chapter 2) can be used to estimate the magnitude of these parameters. Withrespect to the probabilistic analysis presented below, Ca and q can be computedas quantities with specified probabilities of occurrence for use in source termestimates in ecological and human health risk assessments.

If the failure is specified in terms of the maximum allowable magnitudes ofCa, q, and even Co, then the probability of exceeding the specified magnitude ofany of these three parameters can be used to determine failure. In the latter case,if the probability of exceedence of a given magnitude is high enough (value to

FIGURE 1.27 An illustration of the influence of barrier damage on contaminant sourceterm for fate and transport modeling and risk assessments. (From Reddi, L.N. and Inyang,H.I., 2000. Geoenvironmental Engineering, Principles and Applications, 1st ed., MarcelDekker, New York. With permission.)

Surfaceimpoundment

Liner

Unsaturatedgeomedia

Saturatedgeomedia b

Bedrock

d

q, Ca

Leachate plumeVh, Co

Water table

Long term flowchannels α Dt

Ground surface

CC qd

V boa

h

=


be specified), then the system would be considered to have failed. Typically,contaminant migration models (i.e., fate and transport models) contain Co insteadof Ca, thus eliminating the essential parameters that would enable a more completeappreciation of the decay, growth, or constancy of the source term with extendedtime. In some cases where the source (e.g., the impoundment in Figure 1.27) hasbeen eliminated, focus on Co instead of Ca may be justified.

The parameters Ca and Co can be quantitatively linked to exposure assessmentequations that are usually incorporated into quantitative human health and eco-logical risk assessment frameworks. An example of such a framework is the totalrisk integrated methodology (TRIM) described by USEPA (1999) and illustratedin Figure 1.28. The exposure-event function is an expression of the micro-environmental exposure of an individual or cohort to a contaminant in an exposuremedium during a time step, t. As shown in Equation (1.39), the exposure eventfunction is the product of exposure concentration and exposure duration. It shouldbe noted that Equation (1.39) contains the parameter Cm, which relates to Ca andCo of Equation (1.38). Essentially, the critical utility of contaminant subsurfacefate and transport models is to establish the quantitative linkage between Ca, Co,and Cm. Usually, Ca and Co > Cm due to travel path attenuation factors, except for

FIGURE 1.28 An exposure-event simulation framework for the TRIM. (From USEPA,1999. Technical Support Document EPA-453/D-99-001. Research Triangle Park, NorthCarolina, pp. 4.1–6.8.)

Ambient media concentrationsCi, air (t) Ci, water (t) Ci, soil (t) etc.

Time step Averagingtime

Time scalematching

Uncertaintyvariability

Exposure-event function

Inter media transferIFT (j, s –> m, k, t)

Contact mediumAir

WaterFoodSoiletc

Ambientzone

MicroenvironmentActivity

Time

Cm (i, k, l, t) ETz, m (i, k, l, t) Ez, m (t)


unusual situations in which the contaminants accumulate at the sink where Cm ismeasured.

The fate processes and transport rates of each contaminant that is released atinitial but time-variable concentration, Ca, into the surrounding geomedia areaffected by the homogeneity, isotropy, and continuity of the geomedium. In somecases, as modeled by Inyang et al. (2000a), the released contaminant can betransported away quickly because of the high permeability or high diffusioncoefficient of the contaminant in the geomedium. This transport would set up ahigh concentration gradient between the barrier and the bounding surface of thegeomedium such that faster rates of contaminant release into the geomediumwould result within the limits of the contaminant concentration for the contain-ment system.

As discussed by Rowe and Fraser (1995), an impact assessment of the wastedisposal facilities that comprise barrier systems is characterized by several uncer-tainties, some of which derive from hydrogeological factors. Upon release froma containment system into the subsurface, the transport of a contaminant to anenvironmental sink can be retarded or accelerated by physico-chemical processesand travel path hydrogeology. At adequate concentration and favorable pH-Ehcondition, substances can precipitate out of pore solution, thereby blocking somepores and retarding contaminant transport to a sink. Shu et al. (2000) provideda phenomenological and quantitative description of pore plugging processes thatcan result from mineral substance precipitation. Furthermore, Mazurek et al.(1996) experimentally investigated and confirmed redox front entrapment in clayshales that resulted from contrasting solubilities of reduced and oxidized species.Coupled with mineral sorption on pore walls and co-precipitation of secondarymineral phases that were produced, the contaminant was immobilized in the clayshale. In fractured systems, contaminants can travel at high rates relative to valuescomputed for an intact medium. In some cases, the contaminants can travel ascolloids at relatively fast rates from source to sink (Roy and Dzombak, 1997).Several investigators have developed and demonstrated techniques for character-izing textural characteristics of geomedia (Malone et al., 1986; Shi et al., 1999a,b).The characterization of fluid flow channels in geomedia is not always possibleat the application scale of transport models such as those analyzed by Hathorn(1993) and Inyang et al. (2000b).

For a given contaminant concentration at the sink or exposure point, exposureis not time-invariant. McCurdy (1994) illustrated the fluctuations in human expo-sure that define the exposure profile with some measures of exposure or potentialdose to an individual or cohort (Figure 1.29). The utility of this assessment isthat it is possible to estimate different exposure magnitudes for different exposureprofiles to contaminants released into media. The implication is that in order tospecify a human exposure (and hence risk) level as a design requirement forwaste containment system, an exposure profile may need to be specified. Realhealth risks are affected by the exposure profile. For the same contaminantconcentration in the medium proximal to the waste containment system, a widerange of human health risk estimates can result.


(1.39)

where Ez,m is the exposure experienced by person, z, from exposure medium, m,during time step, t, given that person z is in exposure district i in microenvironmentk conducting activity i during that time step t. For example, the exposure in airmight be measured in units of mg-h/m3. Note that the exposure time does notneed to be a whole time step; Cm is the concentration in exposure medium, m(e.g., air, water, soil), in exposure district, i, in microenvironment, k, associatedwith activity, l, during time step, t. The units of measurement for air might bemg/m3, while the units of measurement for food might be mg/kg; ETz,m is theexposure duration of individual or cohort, z, to exposure medium, m, in exposuredistrict, i, in microenvironment, k, conducting activity, l, during time step, t; z isthe individual or cohort; m is the exposure medium contacted (i.e., air, water,food); i is the exposure district; k is the microenvironment in which the exposureoccurs (e.g., indoors at home, in a vehicle, indoors at work); and l is the activity

FIGURE 1.29 An example of an exposure or a potential dose profile and associatedmeasures, where B is the integrated exposure from time t = a to t = b; p is the time betweenpeaks over x; and R is the respites between exceedences of x. (From USEPA, 1999. TRIMTechnical Support Document EPA-453/D-99-001. Research Triangle Park, North Carolina,pp. 4.1–6.8; adapted from McCurdy, T.R., 1994. In McKee, D.J. (Ed.), TroposphericOzone: Human Health and Agricultural Impacts, Lewis, Ann Arbor, MI, pp. 85–127. Withpermission.)

Conc

entr

atio

n C(t)

x

ci

P

B

R

Time t = a t = bti–1 ti

Δti

E C i k l t ET i k l tz m m z m, ,( , , , ) ( , , , )=


code that describes what the individual is doing at the time of exposure(e.g., resting, working, preparing food, cleaning, eating).

1.5 USE OF BARRIER DAMAGE AND PERFORMANCE MODELS FOR TEMPORAL SCALING OF MONITORING AND MAINTENANCE NEEDS

Monitoring the state of the system provides some level of information about itsoperation. For the most beneficial results, objectives should be set and the designof a monitoring program should be addressed prior to system construction. Systemmonitoring also requires an understanding of the manner in which results mightbe used in a system reliability context, as described in this section. It should benoted, however, that the implementation of monitoring technologies and actualinterpretation of the monitoring observations require appropriate expertise andare described in detail in Chapters 4 and 5. Monitoring approaches and technol-ogies were also analyzed by Inyang et al. (1995).

1.5.1 UPDATING

The facility risk analysis involves assumptions about the probability distributionsfor random variables, including means (expected values) and variations about themean. Monitoring can provide data to allow these initial assumptions to bemodified. The standard procedure in probability theory is to use the Bayes the-orem because it allows incorporation of experimental observations in an existingprobability density function, so-called Bayesian updating. This method can allowfor imperfections in the data obtained from monitoring (e.g., known uncertaintiesintroduced by instruments).

The concept can be illustrated quite simply (Figure 1.30). Consider someresistance property, R, which might, for example, represent some characteristicpermeability. Let represent the original (a priori) partial differential equa-tion of R. New data collected from monitoring usually will not fit wholly in theoriginal partial differential equation. Let fv( ) represent the new data, here takenfor simplicity as a continuous partial differential equation. Both are shown onFigure 1.30, together with the updated (posteriori) pdf

It should be clear that if the data have a lot of scatter [i.e., if fv( ) has a largevariance], the data do not contain much useful information and do little to help inrefining the original partial differential equation. Conversely, if the data have verylittle scatter, it is highly informative and will have a significant influence. Simi-larly, if there is little understanding of the variable being considered, its a prioridistribution, fR′ ( ), is highly uncertain and can be said to be noninformative. Theposteriori distribution will then be considerably influenced by the additional data.

Typically, the new evidence is monitoring data, which can be represented asa likelihood function, L (E/λ). This likelihood function is the conditional proba-bility of observing the set of observation outcomes, E, given that the value of theparameter about which there is uncertainty (e.g., the mean of a random variable)

′′fR (�)

′′fR (�).


is λ. According to Bayes theorem, the posterior probability distribution is thengiven by:

(1.40)

For example, if the observation data are the number of particular values above agiven level during a given time interval or as a proportion of all readings, thenthe likelihood function is described by the Poisson distribution and is given by:

(1.41)

Typical prior, likelihood, and posterior distributions are available in standardtexts. The posterior distribution is usually highly dependent on the selection ofthe prior distribution. Hence, care in selecting the original probability distributionsis reflected in subsequent analysis, even after updating using observations.

1.5.2 EFFECT OF UPDATING ON SYSTEM MANAGEMENT

Updating provides a better estimate of the random variables that influence thebehavior of the system and, hence, the predicted probabilities of failure that should

FIGURE 1.30 Known (a priori) pdf for resistance fR′(r) as modified by new informationfV ( ) and modified (posteriori) pdf fR″( ). (From Melchers, R.E., 1999. Structural ReliabilityAnalysis and Prediction, 2nd ed., Wiley, Chichester. With permission.)

Posterior f ''R

Prio f 'R

Likelihood fV

ff L E

f L E d

"'

'

( | )

( | )

λλ λ

λ λ λ

( )=( )

( )∞

∫0

L ET T

nL L

n

( | )exp

!λ

λ λ=

−( ) −( )


enable the risk assessment to be updated as more appropriate monitoring infor-mation becomes available. A simple example is sketched in Figure 1.31, whichindicates the improved life expectancy of a system as a result of favorableobservations leading to an improved estimate of system reliability, shown at theinspection time point.

1.6 LIFE-CYCLE DECISION APPROACH AND MANAGEMENT

It is desirable to optimize the management of containment systems over time.Examples might include minimizing the total expected costs, minimizing envi-ronmental impact, or reducing the likelihood of regulatory breaches and fines toa minimum. With this approach, the possibility exists to optimize the timesbetween discrete monitoring or the intensity of monitoring, if continuous, withrespect to the desired objective (Figure 1.32).

When contamination is left on-site in engineered containment systems, mea-sures must be taken to ensure that humans and the environment will continue tobe protected from harmful exposures. Monitoring, maintenance, institutional con-trols, and other stewardship activities may be needed for very long periods oftime (hundreds to thousands of years), depending on the times over which thecontaminants retain their hazardous characteristics. A report by the NationalAcademies (National Research Council, 2000) suggests that all engineered con-tainment systems, if left unattended, will eventually “fall” and recommendsplanning for fallibility.

An ability to forecast system performance is needed for a number of reasons,not the least of which is the need to have a better understanding of the actualstewardship requirements associated with containment systems. This knowledge

FIGURE 1.31 Schematic variation of reliability showing effect of an observation at“inspection time point.”

Time

ReliabilityDesign reliability

Acceptable reliability

Inspectiontime point


can then be factored into remedial technology evaluation and remediation deci-sion-making. Analytical forecasting tools that enable quantification of the likeli-hoods of events that could lead to failure, their potential consequences, and theassociated response costs are needed so that more informed decisions can bemade concerning the resources that will be needed and more effective stewardshipplanning can occur (Clarke et al., 2002; DOE, 2002). To achieve this requiresthe prediction of future environmental conditions and corresponding systemresponses. Here, the use of natural analogue models is emerging as a valuabletool (Waugh et al., 1994).

Although there is a lack of performance data that can enable predictionverification at this point in time, the use of probabilistic approaches and scenarioanalyses can be helpful in determining the sensitivity of containment systems tospecific events (Sanchez et al., 2002). With time, the ability to predict futureperformance to a reasonable period (a few decades) will increase as the knowledgebase increases. Improvement will occur through a combination of analyticalmodels, natural analogs, and performance monitoring.

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71

2 Modeling of Fluid Transport through Barriers

Prepared by*

Brent E. SleepUniversity of Toronto, Toronto, Canada

Charles D. ShackelfordColorado State University, Fort Collins, Colorado

Jack C. ParkerOak Ridge National Laboratory, Oak Ridge, Tennessee

2.1 OVERVIEW

As understanding of the mechanisms of contaminant transport through barriersystems improves, the design of containment systems is moving from a prescrip-tive approach to a performance design approach. It is expected that reliance onmodels for predictive-based design will increase in the future, as the need forpredicting long-term barrier system performance increases. This chapter detailsthe mechanisms and models for predicting the performance of components ofpassive barriers such as caps, permeable reactive barriers (PRBs), and walls andfloors. The relevant regulatory drivers and current state of practice are summa-rized, and research needs are identified. Chapter 1 dealt with system performancemodeling while this chapter focuses on the performance of components thatconstitute containment systems.

* With contributions by Calvin C. Chien, DuPont, Wilmington, Delaware; Thomas O. Early, OakRidge National Laboratory, Oak Ridge, Tennessee; Clifford K. Ho, Sandia National Laboratories,Albuquerque, New Mexico; Richard C. Landis, DuPont, Wilmington, Delaware; Alyssa Lanier,University of Wisconsin, Madison, Wisconsin; Michael A. Malusis, GeoTrans, Inc., Westminster,Colorado; Mario Manassero, Politecnico I, Torino, Italy; Greg P. Newman, Geo-Slope InternationalLtd., Calgary, Canada; Robert W. Puls, U.S. Environmental Protection Agency, Ada, Oklahoma;Terrence M. Sullivan, Brookhaven National Laboratory, Upton, New York


2.2 CAPS

2.2.1 FEATURES, EVENTS, AND PROCESSES AFFECTING PERFORMANCE OF CAPS

Covers and caps are engineered structures that must perform within a largerdynamic natural system and, as such, must be designed with consideration ofnatural system influences. Understanding these physical processes and applyingappropriate numerical analyses to these processes can help the engineer to buildan appropriate overall system that will perform with the desired objective. Theprimary processes acting on a cap are described in the subsections below.

2.2.1.1 Hydrologic Cycle

The purpose of a cap is usually to minimize water infiltration into underlyingwaste, and sometimes to minimize gas transport to the atmosphere. As shown inFigure 2.1, water originates as precipitation that falls on the cap. Depending onthe cap slope, cap soil properties, cap moisture conditions, and the duration andmagnitude of precipitation, ponding and water run off can occur. Water that doesnot run off of the cap is either stored in depressions in the cap surface, or infiltratedinto the surface layer of the cap. Water infiltrating into the surface layer of thecap is subject to evapo-transpiration. Rates of evapo-transpiration depend onsurface vegetation, soil properties, surface temperatures, soil and air relativehumidities, and net solar radiation. The remainder of the precipitation not trans-formed to run off or evapo-transpiration remains as storage in the cap, or, if thestorage capacity of the cap is exceeded, the water percolates through the cap.

Contaminant vapors can migrate through caps by advection or diffusion.Advection rates depend on gas-phase permeabilities and pressure gradients acrossthe cap. Variations in barometric pressures can increase contaminant vapor advec-tion to the atmosphere. Vapor diffusion is driven by the gas-phase concentrationgradient existing across the cap. Diffusion coefficients depend on soil porosityand water content, as well as contaminant molecular weight. It is often assumedthat diffusion at the ground surface occurs across a stagnant surface boundarylayer the depth of which depends on surface topography, vegetation, and windconditions (Thibodeaux, 1981).

Water percolation and contaminant transport through the cap can also bealtered by human or biointrusion into the cap and other natural events, leadingto disparities between probable current and future percolation rates as shown inFigure 2.2. Animal burrows or other passageways through the cap can acceleratethe migration of water or contaminant vapors through the system. Natural eventssuch as earthquakes, tornadoes, floods, and melting snow can also be disruptiveto the cap. Although a great deal of uncertainty is associated with these eventsand processes as discussed in Chapter 1, their potential impact and consequencecan be significant and should therefore be considered.

Modeling of Fluid Transport through Barriers 73

FIGURE 2.1 Features, events, and processes associated with a long-term cap.

FIGURE 2.2 Cumulative probability distribution of water percolation reaching the milltailings for present and future conditions. (From Ho, C.K. et al., 2001. Sandia NationalLaboratory Report SAND2001-3032; October.)

Climate

Transpiration Precipitation

Run-on

Run-off

Gas release

Evaporation

Storage

Lateral drainage

Waste

Percolation/leaching

Human intrusion/ bio-intrusion

10−13 10−12 10−11 10−10 10−9 10−8 10−7 10−60

20

40

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100

Present

Future

Percolation Flux through Cover (cm/s)

Cum

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2.2.1.2 Layers and Features

In very rare cases, a cap comprises a single soil layer over waste material.Typically however, a cap is the unique combination of soils placed in layers ontop of each other and in certain order that create the desired effect. This sectionbriefly outlines the general performance objective of each potential cap layer.

• Ground surface layer — The top few inches of any surface soil mayneed to be treated as a unique soil region since, due to desiccation anddrying effects, this zone generally has a much higher hydraulic con-ductivity than the soil a few inches below surface. This zone is espe-cially important to include when simulating infiltration through coversystems using numerical models.

• Vegetation layers — It is common to include a vegetation growthlayer that may or may not be part of another cover layer. In manycases, the vegetation can be a key to cap performance, but based onthe analysis presented in Section 1.4.1, this should not be assumed.According to energy balance accounting, the sum of actual evaporationand transpiration are always less than the potential evaporation. Thismeans that for near-surface processes, the availability of water limitsevapo-transpiration, and water that is not transpired through vegetationis removed through evaporation. In other words, if vegetation were notpresent, actual evaporation would remove a similar amount of water.The transpiration process becomes important when it is necessary todraw water from deeper beneath the surface, particularly when actualevaporation has significantly diminished at the surface due to dryingof soils. Vegetation is also critical for stability purposes on slopedcovers, as well as erosion control.

• Capillary break layers — These layers are generally created withcoarse materials next to fine materials because, at a common negativewater pressure, two different soils have different water contents. Cap-illary breaks can be used in caps for various purposes. When placedbeneath a compacted layer, the capillary break limits percolationthrough the compacted material. When placed above a compacted layer,the capillary break limits the evaporative drying of the compacted layer,because water cannot readily be drawn up in its liquid phase throughthe coarser capillary break layer when it is dry. For this type of coverdesign, a model that includes coupled vapor flow should be used toassess the impact of vapor flux on barrier layer drying in the event thatupward liquid phase flow has shut down.

• Barrier layers — Barrier layers are generally made of well-com-pacted, low-permeability fine-grained soils. A barrier layer should notbe placed directly at the surface, or it will be subjected to effects suchas extreme drying, desiccation, and freeze-thaw. It is common to place


a barrier layer over a coarser layer to create a capillary break effect,and then place it beneath a vegetation growth layer. It is not desiredto have the root zone of the plant species extend into the barrier layerwhere damage can occur. While long-term barrier layer performanceis unknown and cannot be predicted with precision, the use of dense,well-graded materials for these layers has shown the best resistance tolong-term performance deterioration (Wilson, 2002).

• Storage layers — These layers are generally made of loose well gradedmaterials such that the hydraulic conductivity is sufficient to allowwater to infiltrate and subsequently be drawn back out by evaporationand/or roots. The thickness of a storage layer becomes a critical ques-tion in its functionality. The cover must be thick enough to keep near-surface wetting and drying processes from interacting with the waste,and to withstand long-term erosion. If the cover is to limit gas fluxesas well, there must be a zone of continual near-saturation within thislayer over time and over prolonged dry periods; either that, or thestorage layer must protect a deeper near-saturation barrier layer. Long-term storage layer performance can be affected by coarse materialbreakdown, which can result in permeability loss.

2.2.2 CURRENT STATE OF PRACTICE FOR MODELING PERFORMANCE OF CAPS

Water movement through soils can be thought of as a three-component systemconsisting of the soil-atmosphere interface, the near-surface unsaturated zone,and the deeper saturated zone. In the past, groundwater modeling has primarilyfocused on the saturated zone, which creates a discontinuity in the natural systembecause the unsaturated zone and the soil-atmosphere interface are not repre-sented. Advances in unsaturated soil technology during the past decade have ledto the development of routine modeling techniques for saturated and unsaturatedsoil systems. However, modeling techniques for the third component, involvingthe detailed evaluation of the flux boundary condition imposed by the atmosphere,are not routinely available. This section discusses some of the available codesthat can be used for the predictive modeling of processes associated with capperformance. A summary of the codes considered, and some of the key featuresand solution techniques are provided in Tables 2.1 and 2.2. Table 2.1 lists severaldifferent available software tools and their main solution processes, as well asfeature overviews and source availability. Table 2.2 lists the individual program’ssolution options and features that are built into the various codes.

2.2.2.1 Water Balance Method

The estimation of the amount of water infiltrating through a cap is essentially theestimation of the water balance for the cap. The net percolation through the cap isthe remainder from precipitation after run off, surface storage, evapo-transpiration,


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and soil storage are considered. The first method used for water balance calcu-lations was developed by Thornthwaite and Mather (1957). This method was usedby Fenn et al. (1975) to analyze leachate generation at municipal solid wastelandfills.

Typically, the water balance method is based on monthly climatic variables.The monthly infiltration, I (cm), into a cover is given by:

I = P – R (2.1)

where P is precipitation (cm) and R is surface run off (cm). Surface storage wasnot considered by Fenn et al. (1975). Run off is calculated from precipitationusing a run off coefficient, C:

R = C P (2.2)

Fenn et al. (1975) provided values of C for different soil types and slopes, withvalues ranging from 0.05 for sand with less than a 2% slope, to 0.35 for a steeplysloped (>7%) clay layer.

Thornthwaite and Mather (1957) also provided tables for determining poten-tial evapo-transpiration (PET) as a function of mean temperature, heat index, andhours of sunlight. When PET exceeds infiltration, moisture storage in the cap isexpected to decrease unless the cap was already dry. PET cannot exceed the waterstored in the cap plus the infiltration for the month. When infiltration exceedsPET, evapo-transpiration is equal to PET, and excess infiltration increases themoisture storage in the cap to field capacity. Excess infiltration above the fieldcapacity of the cap percolates through the cap.

2.2.2.2 HELP

The hydrologic evaluation of landfill performance (HELP) model was developedby the United States Army Engineer Waterways Experimentation Station for theUnited States Environmental Protection Agency (USEPA) in 1984. The currentversion of the model, Version 3, was released in 1993.

The HELP model is essentially a water balance model that includes subsur-face water routing. It simulates both model cap and liner behavior in a landfillsystem. The model is referred to as a quasi-two-dimensional model, as it simulatesvertical flow in barrier and waste layers (assuming unit hydraulic gradient), andhorizontal flow in drainage layers (using an analytical solution of the Boussinesqequation). Calculations are performed on a daily basis, and changes in soilmoisture and surface storage are tracked (Peyton and Schroeder, 1993). The HELPmodel considers both rain and snow infiltration and accounts for interception byvegetation, surface evaporation, and surface storage.

Evapo-transpiration is modeled based on a square root of time calculationand the energy available for evaporation. The type and stage of vegetative growthis also considered in evapo-transpiration calculation.


2.2.2.3 UNSAT-H

UNSAT-H (WinUNSAT-H) is a model for calculating water and heat flow inunsaturated media. The model was developed at Pacific Northwest NationalLaboratory in Richland, Washington, to assess the water dynamics of near-surface, waste disposal sites. The code is primarily used to predict deep drainageas a function of environmental conditions such as climate, soil type, and vegeta-tion. UNSAT-H is a one-dimensional model that simulates the dynamics processesof infiltration, drainage, redistribution, surface evaporation, and uptake of waterfrom soil by plants. It uses a finite-difference approximation to solve the one-dimensional vertical form of Richards’ equation, which governs unsaturatedmoisture movement. UNSAT-H was designed for use in water balance studiesand has capabilities to estimate evaporation resulting from meteorological surfaceconditions and plant transpiration.

The parameters required for each material type are saturated hydraulic con-ductivity, volumetric moisture content at saturation, irreducible moisture content,air entry head, and inverse pore size distribution index.

2.2.2.4 SoilCover

SoilCover is a soil-atmosphere flux model that links the subsurface saturated/unsaturated groundwater system and the atmosphere above the soil in an attemptto represent the soil-atmosphere continuum. It is a one-dimensional finite elementpackage that models transient conditions. The model uses a physically-basedmethod for predicting the exchange of water and energy between the atmosphereand a soil surface. The theory is based on the well-known principles of Darcy’sand Fick’s Laws that describe the transport of liquid water and water vapor andFourier’s Law that describes conductive heat flow in the soil profile below thesoil-atmosphere boundary. SoilCover predicts the evaporative flux from a saturatedor an unsaturated soil surface on the basis of atmospheric conditions, vegetationcover, and soil properties and conditions. The Penman–Wilson formulation isused to compute the actual rate of evaporation from the soil-atmosphere boundary,which is critical to modeling of evapo-transpirative caps (Wilson, 1990; Wilsonet al., 1994).

The primary features and modeling capabilities of SoilCover are as follows:

• Specification of detailed climate data, including minimum and maxi-mum air temperature, net radiation, minimum and maximum relativehumidity, and wind speed

• Specification of reduced climate data, including air temperature, rela-tive humidity, and potential evaporation (wind speed is optional)

• Multi-layered soil profiles• Optional specification of an internal liquid source/sink node• Optional specification of oxygen diffusion coefficients for monitoring

oxygen flux and the concentration between soil surface and seconduser-specified node


• User-defined or SoilCover-predicted thermal and hydraulic soil prop-erty functions

• Internal adaptive time stepping scheme for daily simulations• Relative convergence criteria for suction and temperature applied at

every node• Output data files providing daily profiles of volumetric and gravimetric

water content, degree of saturation, matrix suction, total head, temper-ature, ice content, hydraulic conductivity, oxygen concentration, andvapor pressure

• Daily reporting of potential evaporation, surface flux, base flux, totalevaporation, total run off, root flux, user-selected internal node fluxand user selectable on-screen graphics during program execution show-ing continuous daily or cumulative fluxes in chart and table formatplus daily updates of temperature and degree of saturation profiles

The program user interface occurs in Microsoft Excel™ using dialogue boxesand custom menus, and the solver is a 32-bit Fortran executable file.

2.2.2.5 HYDRUS-2D

HYDRUS-2D can be used to simulate two-dimensional water flow, heat transport,and the movement of solutes involved in consecutive first-order decay reactionsin variably saturated soils. HYDRUS-2D uses the Richards’ equation for simu-lating variably saturated flow and Fickian-based convection-dispersion equationsfor heat and solute transport. The water flow equation incorporates a sink termto account for water uptake by plant roots. The heat transport equations considertransport due to conduction and convection with flowing water. The solute trans-port equations consider convective-dispersive transport in the liquid phase, aswell as diffusion in the gaseous phase. The transport equations also includeprovisions for nonlinear nonequilibrium reactions between the solid and liquidphases, linear equilibrium reactions between the liquid and gaseous phases, zero-order production, and two first-order degradation reactions: one independent ofother solutes and one that provides coupling between solutes involved in thesequential first-order decay reactions.

The user interface includes data pre-processing and graphical presentation ofthe output results in the Microsoft Windows 95, 98, and NT environments. Datapre-processing involves specification of a flow region of arbitrary continuousshape by means of lines, arcs and splines, discretization of domain boundaries,and subsequent automatic generation of an unstructured finite element mesh. Analternative structured mesh for relatively simple transport domains defined byfour boundary lines can also be considered. Graphical presentation of the outputresults consists of simple two-dimensional x–y graphs, contour and spectral maps,velocity vectors, as well as animation of both contour and spectral maps. Graphsalong any cross sections or boundaries can be readily obtained. A small catalogof soil hydraulic properties is also part of the interface.


2.2.2.6 VADOSE/W

VADOSE/W is a commercially developed two-dimensional finite element codethat accounts for precipitation; evaporation; snow accumulation/melt/run off;groundwater seepage; freeze-thaw; ground vapor flow; actual transpiration fromplants; and gas diffusion, dissociation, and decay. It solves the same primary heatand mass differential equations as the SoilCover model except in two dimensions.The gas diffusion equation is solved at the completion of each time step oncewater contents and temperatures are known throughout the domain.

VADOSE/W uses the Penman–Wilson method (Wilson, 1990; Wilson et al.,1994) method for computing actual evaporation at the soil surface such that actualevaporation is computed as a varying function of potential evaporation dependenton soil pore water pressure and temperature conditions and independent of soiltype and drying history. The fully coupled heat and mass equations with vaporflow in VADOSE/W permit the necessary parameters at the soil surface to beavailable for use in the Penman–Wilson method. VADOSE/W is currently theonly numerical two-dimensional cap design model capable of calculating actualevaporation based on first-principle physical relationships, not empirical formu-lations that are developed for unique soil types, soil moisture conditions, orclimate parameters.

VADOSE/W can be used wherever accurate surface boundary conditions arerequired. Typical applications include designing single or multi-layered soil cov-ers over mine waste and municipal landfill disposal sites; obtaining climate-controlled soil pore pressures on natural slopes or man-made covered slopes foruse in stability analysis; and determining infiltration and evaporation as well asplant transpiration from agricultural irrigation projects.

VADOSE/W comes with a built-in soil property database as well as full-yeardetailed climate data for over 40 sites worldwide. Climate data can be easilyscaled to suite specific conditions or the user can input specific climate data.

2.2.2.7 TOUGH2

Transport of unsaturated groundwater and heat (TOUGH2) is a multi-dimensionalnumerical simulator that simulates the transport of air, water, and heat in porousand fractured media (Pruess, 1991). Mass and energy balances for air, water, andheat are solved simultaneously in TOUGH2 using the integrated finite differencemethod. The integrated finite difference formulation of TOUGH2 allows for theconstruction of nonuniform elements that can be used to represent irregulardomains. The development of this code was originally motivated by problemsinvolving heat-driven flow, although this code is now used in a wide range ofproblems involving unsaturated flow. For example, Ho and Webb (1998) usedTOUGH2 to simulate the effects of heterogeneities on capillary barrier perfor-mance in landfill caps. A multi-phase approach was used to describe the move-ment of gaseous and liquid phases, their transport of latent and sensible heat, andphase transitions between liquid and vapor. Water vapor and air, which generally


constitute the gas phase, are tracked and simulated separately. Liquid- and gas-eous-phase flow can occur under pressure, viscous, and gravity forces accordingto Darcy’s Law, and interference between the phases is represented throughrelative permeability functions.

A number of variations of the TOUGH2 code have been developed to includeadditional capabilities of modeling additional species, modeling fluctuating atmo-spheric boundary conditions, and inverse modeling. The model parameters, initialconditions, and boundary conditions are typically entered into the code throughtext entry into a file that is read by the code. Post-processing within TOUGH2 islimited and is typically performed by third-party software. The source code forTOUGH2, written in standard FORTRAN77, is available from the United StatesDepartment of Energy (USDOE) Office of Scientific and Technical InformationEnergy Science and Technology Software Center in Oak Ridge, Tennessee.

2.2.2.8 FEHM

Finite element heat and mass (FEHM) is a numerical simulation code for sub-surface transport processes (Zyvoloski et al., 1997). It models three-dimensional(3-D), time-dependent, multi-phase, multi-component, nonisothermal, reactiveflow through porous and fractured media. It can represent complex 3-D geologicmedia and structures and their effects on subsurface flow and transport. FEHMuses a finite-element formulation to solve the governing equations of heat andmass transport. Simulation of additional species (e.g., organics, radionuclides)can be performed simultaneously with the solution of heat, air, and water trans-port. In addition, a particle-tracking module is also included that provides a morecomputationally efficient procedure to the solution of contaminant transport.Millions of particles can be simulated that represent the effects of advection,diffusion, dispersion, and fracture-matrix interactions on transport.

The entry of model parameters, boundary conditions, and initial conditionsinto FEHM is performed through the creation of text files that are read by thecode. FEHM does not perform any direct post-processing of the data for visual-ization, but the user has the option to output the data in formats that can be readby third-party software. FEHM can be obtained free of charge in the United Statesfor most applications via the web site http://ees-www.lanl.gov/EES5/fehm/.

2.2.2.9 RAECOM

Radiation attenuation effectiveness and cover optimization with moisture effects(RAECOM) is a code that simulates steady, one-dimensional radon gas diffusionthrough a multi-layer cover (Rogers et al., 1984). Material properties, dimensions,and diffusion coefficients can vary among the different layers, and activity andemanation coefficients can be specified. An online calculator that provides thesame functional calculations as RAECOM is provided at the following web site:http://www.antenna.nl/wise/uranium/ctc.html.


2.2.3 MODELING LIMITATIONS AND RESEARCH NEEDS FOR CAPS

There are many limitations to modeling the performance of caps, including dataneeds; lack of quality assurance and control of models and model usage; and lackof verification, validation, and calibration. This section discusses these limitationsand the associated research needs, as well as the role of modeling in designingcaps.

2.2.3.1 Role of Modeling

There is often a misperception of what a model can and cannot do. It is criticalto get all stakeholders to understand and agree on the objectives of using themodel. Many believe that if the predictions arise from a sophisticated computercode that incorporates the fundamental physics as it is currently understood, theanswer must be correct. In fact, at best, the model output is a scientificallydefensible, although not necessarily accurate, prediction of system behavior. Thisbelief in modeling leads to the development and use of more sophisticated modelsthat advance the state of the science, but do not necessarily provide more defen-sible predictions.

In modeling cover system performance, the objective is to provide a measureof the ability of the cover to prevent water infiltration to the waste zone over longperiods of time (i.e., tens of years to hundreds of years). It is not possible toprecisely predict infiltration over long time periods due to the large number ofuncontrolled variables (e.g., weather conditions, burrowing animals, root growth),heterogeneities in the physical properties of the system, and lack of preciseunderstanding of the flow physics (e.g., hysteresis effects and soil characteristiccurves are empirical relationships based on data). Therefore, the modelingapproach should aim to demonstrate that the cover system limits infiltration toan acceptable level over a range of potential conditions. This lends itself naturally,although not exclusively, to probabilistic modeling.

2.2.3.2 Data Needs

The data required for modeling cap behavior depends on the model being used.The simplest models such as the water balance method of Thornthwaite andMather (1957) and Fenn et al. (1975) require monthly climatic data such asprecipitation, mean temperature, heat index, and hours of sunlight. Soil types andcap slopes are also required to allow estimation of run off.

More comprehensive water balance models such as the HELP model allowfor more complex cap configurations and, thus, require specification of the dif-ferent cap layers. The HELP model also simulates the surface processes in greaterdetail and therefore requires additional climatic data and soil properties. Theclimate data input to the HELP model include daily precipitation, daily meantemperature, daily solar evaporation, maximum leaf area index, growing season,and evaporative zone depth (Peyton and Schroeder, 1993). The soil properties


required include porosity, field capacity, wilting point, hydraulic conductivity,and the United States Soil Conservation Society curve number for the surfacelayer. The HELP model contains a list of default soil properties, and a databaseof climate data for a large number of North American cities (Peyton andSchroeder, 1993).

Other more rigorous models such as UNSAT-H, HYDRUS-2D, andVADOSE/W simulate unsaturated water flow by solving Richards’ equation.Simulation of unsaturated water flow with Richards’ equation requires parameterspecification of the soil characteristic curves for hydraulic conductivity and mois-ture content as a function of suction pressure, typically represented by empiricalrelationships such as those developed by van Genuchten (1980) or Fredlund andXing (1994). These parameters are required for each unique soil layer in the coversystem. Saturated hydraulic conductivity and porosity are also required for eachmaterial. Other parameters, such as the air entry pressure head, residual saturationvalue, vertical and horizontal saturated conductivity, and anisotropy parametersmay be required depending on the model.

Some of the models (i.e., TOUGH2, FEHM, VADOSE/W, HYDRUS-2D) alsosolve the heat transport equation to track evaporation and water vapor transport.Therefore, these models require additional information regarding soil propertiesrelated to heat transport for the gas and liquid phase. Parameters that are typicallyneeded include thermal conductivity, specific heat capacity, latent heat of vapor-ization, surface tension, and parameters that describe the interactions betweengas and liquids under flowing conditions (e.g., relative permeability).

2.2.3.3 Code Quality Assurance and Quality Control

Numerical models are nothing more than tools that solve mathematical equationsthat cannot be solved with conventional techniques. Typical geotechnical com-puter models have thousands of lines of code; it is easy to inadvertently introducemistakes that can cause unpredictable behavior. When source code is made avail-able to end users to change and compile, unique versions of the code that onlysolve specific problems commonly result, and the original verification of theoriginal model may not apply to the slightly changed version. For this reason,regulatory authorities should consider developing a standard set of benchmarktests that model developers can use to verify and validate their codes. If smallchanges to the code are made, all benchmark tests must be resolved to ensurethat no undesirable errors have been introduced. Benchmark testing would includesolving some simple steady-state and transient seepage examples using fixedmaterial properties where known solutions for the equation exist to validate thenumerical solution of the code under the most basic conditions. More advancedbenchmark tests should be available where individual theoretical components ofthe models could be tested in isolation from other factors (e.g., actual evaporationcan be computed and compared against rigorously controlled laboratory experi-ments). All input data, including material properties, would be listed in the


benchmark test documentation as would the required results. If the new modelcannot perform the basic benchmark tests, it is not acceptable for use in fielddesign.

A final point to consider is the establishment of a group of individuals whocan assemble the benchmark tests and can review and update the tests as newand more advanced physics are introduced.

2.2.3.4 Verification, Validation, and Calibration

The verification, validation, and calibration of numerical models are key compo-nents in the modeling process and are often the most poorly implemented andmisunderstood.

The key questions to ask when looking at models are what equations arebeing solved, what assumptions have been applied to the equations, and how arethe equations being solved? For example, just because a model computes evap-oration does not mean that it does so based on sound physical relationships orthat, if it is based on sound physics, the equations are solved properly. After amodel user has an understanding of the theory and physics incorporated into anumerical code, they should satisfy themselves that the numerical solution forthat set of equations is correct. This is the verification stage of the modelingprocess and is usually carried out by the model developer. Verification has nothingto do with site data and everything to do with correct solution of the mathematics.Verification and validation go together; where verification addresses solutiontechniques and validation is the process of obtaining confidence that the modelapplies to real situations represented by the theoretical formulations applied inthe model. Validation tests if the model theories actually apply to specific realobservations — whether they are laboratory experiments or field studies.

It is absolutely critical to validate a model based on known closed-formsolutions, known physical observations, and laboratory tests where all parameterscan be controlled and adjusted individually. Models cannot be validated usingfield data alone because there is no direct control over or monitoring of all majormodel parameters. For example, if a model is validated using site data whereprecipitation, run off, change in water storage, and bottom drain fluxes are mea-sured but actual surface evaporation and transpiration are not measured, then thesource of discrepancies between measured and computed results cannot be deter-mined. There could be error in the model estimate of evaporation, or there couldbe error in the field measurement of particular parameters. The most appropriateuse for field data in modeling is calibration of a previously validated model.

Calibration of a model involves making small adjustments to measured orpredicted model input parameters to obtain better matches between measured andcomputed results data at more than one instance in time. In the ideal case, oncea model is calibrated for a site, it will give reliable results for the same site ifexternal parameters at that site change. For example, if precipitation is doubledor halved, the change in soil responses can be predicted using a calibrated modelfor that site only. The problem with calibration is that it only works if the model


physics truly represent the real physical processes in the ground. If the model isrigorous enough and calibrated properly, then all physical processes measured inthe ground and predicted by the model should match. Calibration of nonrigorousmodels such as HELP must be interpreted with caution because, in many cases,the calibration can be achieved by adjusting only a single model parameter. Whenthis is done, the predicted and measured data only match for a single instance intime. There is no guarantee that the adjustments made to the model to fit measureddata represent the true physical properties in the field. It may be possible tocalibrate HELP to match measured percolation data, but it is very unlikely thatparameters such as the temperature, water pressure, water stored in the soil, andthe root depth match field conditions at the same instance or at some other instancein time.

2.2.4 UNRESOLVED MODELING CHALLENGES

There are many challenges facing model developer users. These challengesinclude the difficulties in modeling systems with time-varying properties andprocesses, the problems encountered in modeling infiltration at arid sites, and therole of heterogeneities in modeling.

2.2.4.1 Time-Varying Material Properties and Processes

A major challenge facing modelers of cap performance is the time-varying natureof climate, vegetation, and soil properties. All models of cap performance requireextensive climatic data, including precipitation, temperature, and solar radiationto determine infiltration and evapo-transpiration. Although historic data are avail-able for many locations, methods for estimating extreme values of these variablesare not well developed.

Physical deterioration of caps is commonplace, as they are easily impactedby surface and climate processes. Changes in vegetation have an effect on runoff generation and evapo-transpiration. Establishment of shrubs and trees on capscan lead to cap penetration by roots, creating high conductivity pathways for waterinfiltration. Similarly, burrowing animals can create high conductivity conduitsthrough a cap. Erosion and subsidence can seriously impact cap performance.The cracking of clay layers in caps due to freeze-thaw cycles or desiccation(e.g., Albrecht and Benson, 2001) can significantly increase the effective hydrau-lic conductivity of caps, leading to greatly increased water infiltration or vaporescape. Albrecht and Benson (2001) found that clay hydraulic conductivitiesincreased by factors as high as 500 upon desiccation. Subsequent resaturationdid not lead to complete healing of dessication-induced cracks. Although capmodeling can predict soil moisture levels in the cap, reliable models for changesin cap hydraulic properties due to dessication or freeze-thaw have not beendeveloped.

Many caps are expected to provide environmental protection for decades orcenturies. Studies of cap stability and soil and geomembrane property stability


over these long periods of time have not been conducted. In addition, accuratepredictions of long-term climate changes and the occurrence and impact ofextreme events (e.g., earthquakes, floods, hurricanes, tornadoes) are not possible.

2.2.4.2 Infiltration at Arid Sites

Arid sites are characterized by levels of precipitation that are almost balanced byloss mechanisms such as evaporation, transpiration, and run off. For water balancemodels, the recharge is estimated by subtracting the losses from the predictedproduction. Thus, small errors in either estimate can lead to large errors inrecharge estimates.

A second issue at arid sites is that evapo-transpiration models used in thewater balance models for disposal cells that are sparsely vegetated are not accurateand tend to overpredict evapo-transpiration and underpredict recharge. The useof physically based evapo-transpiration models (e.g., SoilCover, VADOSE/W)that are formulated to shut down actual evaporation as ground surfaces dry greatlyimproves infiltration estimates at arid sites.

2.2.4.3 Role of Heterogeneities

The most commonly used models for estimating flow through cover systemsassume uniform hydraulic and thermal properties for each layer of the coversystem. In practice, local heterogeneities are likely to be responsible for a largeportion of the flow through cover systems. The heterogeneities can arise naturallydue to improper construction (e.g., leaks at seams, improper compaction) orevolve in time (Section 2.3.5.1).

Currently, the capability to predict the occurrence of local heterogeneitiesand their impact on flow does not exist. For example, desiccation cracking isknown to occur in clay barriers and leads to increased flow. However, the capa-bility to predict crack formation; the density of cracks; the changes in hydraulicconductivity that occur due to cracking and subsequently rewetting; and, moreimportantly, the change in flow through the layer does not exist.

For field performance, localized failure will often control infiltration throughthe cover system. This leads to the need to develop procedures to adequatelyrepresent these local failures using gross average properties for the layers.

2.3 PRBS

In recent years, PRBs have evolved from the realm of an experimental method-ology to standard practice for containment and treatment of a variety of contam-inants in groundwater. Like any remedial technology, the decision to use PRBsis conditioned by the characteristics of the natural system, target contaminants,and treatment objectives. More than 60 sites have implemented this technologyin the last few years to treat chlorinated solvents, fuel hydrocarbons, and variousinorganic contaminants in groundwater. As with any technology used to treat or


extract contaminants in the subsurface, successful implementation is contingenton effective site characterization, design, and construction. Recent studies onlong-term PRB performance at a number of sites emphasize the following keyissues for successful use of PRBs:

• Performing adequate site characterization on the scale of thePRB — Site characterization approaches, typical of Resource Conser-vation and Recovery Act (RCRA) facility investigations (RFIs), are notadequate. Performing additional localized characterization of theplume distribution in three spatial dimensions and with time, under-standing the local hydrogeology, and knowing the site geochemistry isrequired.

• Understanding site hydrology to achieve successful implementation— PRBs must be located correctly to intercept the plume because oncelocated in the subsurface, they cannot be moved. It is therefore imper-ative that the PRB captures the plume at the present time and in thefuture allowing for variations in flow direction, velocity, and concen-trations of contaminants over time.

• Developing contingency plans for failure to meet design objectives —It is surprising that site owners and regulators often fail to explicitlydevelop contingency plans. Contingency plan development requiresspecification of design criteria and performance objectives and deter-mination of what constitutes a failure in order to clearly trigger con-tingency plan activation.

2.3.1 FEATURES, EVENTS, AND PROCESSES AFFECTING PERFORMANCE OF PRBS

Design of PRBs requires consideration of groundwater hydraulics, geochemicalprocesses, and reaction kinetics and the interaction between these processes.

2.3.1.1 Groundwater Hydraulics

As with any groundwater remediation technology, an understanding of the direc-tion and rate of groundwater flow spatially and temporally is critically importantfor successful design. Groundwater hydraulics are particularly crucial for PRBsbecause the treatment system is immovable and passive yet must intercept thecontaminant plume for effective treatment.

Groundwater flow is well understood, and groundwater modeling is a maturetechnology (e.g., Bear and Verruijt, 1987; Anderson and Woessner, 1992). Manycomputer models are available in the public and commercial domains that canbe utilized to perform quantitative predictions of transient 3-D groundwater flowgiven appropriate input. The key difficulty in modeling groundwater hydraulicsis that critical variables that control groundwater flow typically exhibit a highdegree of variability spatially and temporally. These variables are difficult to


characterize with precision and sufficient resolution given physical and budgetaryconstraints.

To assess PRB system performance, information is needed on groundwatervelocities through and near the planned PRB. On the simplest level, these valuescan be estimated from observed hydraulic gradients and measured or estimatedhydraulic conductivities. Alternatively, groundwater velocities can be determinedwith a numerical groundwater flow model based on estimated hydraulic propertydistributions and hydrologic boundary conditions (i.e., water levels and/or fluxeson model boundaries and recharge and extraction rates), which can vary tempo-rally. In many cases, it is important to consider the effects of temporal changesin flow direction and velocity due to variations in recharge, pumping of adjacentwells, or other disturbances. It is not uncommon to observe changes in flowdirection on the order of 30˚ or more over time due to transient boundaryconditions. Furthermore, the PRB permeability itself can change markedly overtime in some situations (e.g., due to biological fouling or chemical precipitationin or near the PRB), which can substantially impact the hydraulic regime.

Understanding site stratigraphy and lithology is crucial to understanding andpredicting groundwater hydraulics. If a low permeability layer exists at the site,the PRB can be keyed into this layer. If one does not exist, then a hanging walldesign can be employed, but uncertainty regarding plume capture may increase.If the site has low permeability layers through which the PRB must be constructed,care must be taken during construction to avoid smearing of such layers, whichcould impact hydraulic contact between the formation and reactive media. Athorough understanding of site stratigraphy is important when choosing a partic-ular construction method. For example, the use of sheet piling to construct areactive gate may not be a good choice where low permeability layers existbecause of smearing potential.

2.3.1.2 Geochemical Processes

The nature and extent of geochemical processes occurring within a PRB to alarge degree determine the long-term treatment performance of the barrier. Thedetails of these processes are site specific and associated with chemical, physical,and biological factors such as the following:

• Reactive media type (e.g., zero-valent iron (ZVI), other metals, zeolite,organic materials)

• Influent groundwater chemistry (e.g., pH; amounts of cations, anions,and target contaminants)

• Microbiological environment within and around the PRB• Physical conditions (e.g., temperature)• The 3-D characteristics of groundwater flow within and near the PRB

There are several good sources that provide information about pilot and full-scale PRB installations worldwide. Although new PRBs continue to be deployed,


summaries provided by the Air Force Research Laboratory (AFRL, 2000) andon the Remediation Technologies Development Forum (RTDF) web site(http://www.rtdf.org/public/permbarr/prbsumms/) identify more than 50 PRBsthat have been installed. Of these, the vast majority (approximately 85%) useZVI as the reactive medium. Other types of reactive media that have been inves-tigated include other metallic materials (Gillham and O’Hannesin, 1992; Korteet al., 1995; Muftikian et al., 1995; Orth and McKenzie, 1995; Bostick et al.,1996; Hayes and Marcus, 1997), zeolite (Bowman et al., 2001; Rabideau andVan Benschoten, 2002), various organic materials (Benner et al., 1997), apatite(Conca et al., 2000; Fuller et al., 2002), and sodium dithionite injected as asolution (Fruchter et al., 1997). The AFRL (2000) summarizes different PRBmedia that have been investigated. The AFRL (2000) and the RTDF web site alsodocument the range of contaminants that are being treated by PRBs. Chlorinatedsolvents such as trichloroethylene (TCE) and perchloroethylene (PCE) are thedominant target contaminants, but others include metals and radionuclides[e.g., Cr(VI), U(VI), Tc(VII)], other inorganics (e.g., NO3

–, SO42–), and other

organics (e.g., pesticides, toluene).Because of the dominance of ZVI as a reactive medium in PRBs, the following

discussion focuses exclusively on geochemical processes occurring within it. ZVIfunctions as a redox medium and treats contaminants by chemical reduction. Atthe same time, the iron is sacrificially oxidized progressively from Fe(0) to Fe2+

and, finally, Fe3+. The oxidized species of iron potentially can react with othercomponents in the groundwater to precipitate a variety of amorphous and crys-talline phases as described below. Table 2.3 lists secondary phases that reportedlyhave been formed by reactions occurring in ZVI PRBs.

The reaction of groundwater with ZVI causes several major compositionalchanges that drive the formation of these reaction products. ZVI begins to dissolveaccording to the following reactions:

2Fe0 + 2H2O + O2 (aq) = 2Fe2+ + 4OH–

Fe0 + 2H2O = Fe2+ + H2 (aq) + 2OH–

The first reaction involves the scavenging of dissolved oxygen by ZVI and isknown to be a fast reaction because column and field studies show the completeabsence of dissolved oxygen within a few centimeters of the influent face of aPRB. The second reaction prevails once the oxygen is gone and is slower. Bothreactions result in a significant decrease in redox potential and a dramatic rise inpH, both of which are observed in typical ZVI PRBs. The magnitude of changein pH depends on the detailed chemistry of the influent groundwater, its bufferingcapacity, and the rate of groundwater flow through the barrier. For example, highalkalinity groundwater is more resistant to a change in pH. However, the largeavailable mass of ZVI in PRBs tends to overwhelm any redox buffering capacityof the groundwater.


The oxidation of ZVI (and associated decrease in groundwater redox poten-tial) and the dramatic pH rise are the two principal factors that result in theformation of new solid phases, many of which are iron bearing (Table 2.3). Someof these phases that contain either Fe2+ (e.g., amorphous ferrous oxyhydroxides,FeS, FeCO3) or mixed Fe2+ and Fe3+ (e.g., Fe3O4, green rust) also are effectivereducing agents for metals, radionuclides, and organics in groundwater. Conse-quently, the formation of these reduced iron phases does not necessarily signifi-cantly diminish the reactivity of the barrier media. However, not all phases formedin a PRB are iron-bearing. For example, the increase in pH can also lead toprecipitation of various carbonate minerals (e.g., calcite, aragonite) if the influentwater has sufficient amounts of dissolved alkalinity and calcium. The mix of solidphases formed and their order of precipitation depend on influent groundwaterchemistry, the complex interplay of changing redox potential and pH in the systemas ZVI dissolves, reaction rates, factors affecting the nucleation of phases, andgroundwater flow rate. The ability to predict these reactions and estimate theirimpact on PRB performance is discussed in Section 2.4.4.

One concern associated with secondary mineral formation in PRBs is thatthese phases passivate the ZVI media, decreasing its reactivity and ability to treatcontaminated groundwater. Farrell et al. (2000) reported an example of ZVIpassivation with results of long-term column experiments in which they observedan over six-fold decrease in the reactivity of ZVI to TCE in the two-year experiment.

TABLE 2.3Examples of Precipitated Minerals Found in Fe(0) Field-Installed PRBs and Column Studies

Mineral Precipitate Group Minerals

Iron oxides and oxyhydroxides Goethite (α-FeOOH)Akaganeite (β-FeOOH)Lepidocrocite (γ-FeOOH)(Maghemite (Fe2O3))Magnetite (Fe3O4)Amorphous iron oxyhydroxides

Iron sulfides Mackinawite (Fe9S8)Amorphous ferrous sulfide (FeS)

Carbonates Aragonite (CaCO3, orthorhombic)Calcite (CaCO3, hexagonal)Siderite (FeCO3)

Green Rusts GR-I (CO32–) (Fe4

2+Fe23+(OH)12)(CO3⋅2H2O)

GR-I (Cl–) (Fe32+Fe3+(OH)8Cl)

GR-II (SO42–) (Fe4

2+Fe23+(OH)12)(SO4⋅2H2O)

Source: Liang, L., Sullivan, A.B., West, O.R., Kamolpornwijit, W. and Moline,G.R., 2003. Predicting the precipitation of mineral phases in permeable reactivebarriers. Environ. Eng. Sciences. Vol 20(6): p. 635.


The authors found that the degree of passivation was related to the adheringability of secondary minerals and not the overall mass of these phases formed.

A number of PRBs have been cored and the media examined to understandthe formation of secondary minerals (e.g., Puls et al., 1999a; Vogan et al., 1999;Phillips et al., 2000; Roh et al., 2000). Typically, cores are obtained by angledrilling through the vertical influent face of the barrier to provide a cross sectionextending into the PRB interior, capturing the precipitation that is expected to bethe most significant at the sediment–ZVI interface. Analytical methods such asX-ray diffraction (XRD) and scanning electron microscopy (SEM) typically areused to examine the solid phases that have formed. Table 2.4 illustrates differencesin groundwater chemistry and resultant secondary minerals observed in PRBs atthe Canadian Forces Base Borden in Ontario, Canada (O’Hannesin and Gillham,1998) and the USDOE Y-12 plant in Oak Ridge, Tennessee (Phillips et al., 2000).The low dissolved solids groundwater at the Borden site has resulted in littleformation of new solid phases over a period of four years, and most precipitation

TABLE 2.4Groundwater Chemistry of Two Different PRB Sites and the Secondary Phases Observed in Each

Chemical Constituent

Concentration (mg/L)

Canadian Forces Base Borden USDOE Y-12 Plant

Na 4 8.9K 0.4 3.6Ca 55 361Mg 4 20.5Total Fe <0.5 0.02Cl 3 55SO4 5–10 47SiO2 Not available 3.8NO3 Not available 904Alkalinity (as CaCO3) 158 220pH (unitless) 7.9 6.8Eh (mV) 300 Not availableDissolved oxygen 2.5-5 Not available

Secondary minerals observed:

Traces of iron oxides CaCO3 (aragonite)CaCO3 Fe2(OH)2CO3

FeCO3 FeCO3

(After four years of operation; no cementation; mineralization confined to within several millimeters of influent face of the PRB)

GoethiteMaghemiteAmorphous iron oxideGreen rustMackinawite (Iron media cemented extensively at influent face)


appears to be restricted to a very thin zone at the influent face of the PRB. Incontrast, the highly mineralized water from the Y-12 plant resulted in much moreextensive formation of secondary phases, illustrated by the cementation of reac-tive media (Figure 2.3). The presence of NO3

– at high concentrations in the Y-12plant groundwater is an important factor in determining the degree of reactionoccurring in this PRB because NO3

– is readily reduced to NH3 as iron is oxidizedand, therefore, is very corrosive to ZVI.

In terms of groundwater treatment, the geochemical reactions between ZVIand the target contaminants are of primary importance within PRBs. Currently,most PRBs are deployed to treat groundwater contaminated with chlorinatedsolvents such as TCE, PCE, and their daughter products. A discussion of severalpossible degradation reaction pathways for TCE is provided in AFRL (2000). Thefollowing reaction illustrates the overall reductive dechlorination process for TCE:

3Fe0 + C2HCl3 + 3H+ = 3Fe2+ + C2H4 + 3Cl–

As noted in AFRL (2000), there may be a number of reaction pathwaysresulting in a variety of potential intermediates, but experimental and field studiesindicate that the net reaction is one of iron oxidation coupled with reductivedechlorination, leading to the production of dissolved ethene (and ethane) andchloride.

FIGURE 2.3 Section of cemented core from a PRB at the USDOE Y-12 plant in OakRidge, Tennessee.

9 1 0 1 1 1 22 F8

0 2 1 2 2 2 3 2 4 2 5 2 6 2


PRBs with ZVI also can be used to treat groundwater contaminated withsome redox-sensitive toxic metals. For example, dissolved species such as hexava-lent chromium, pertechnetate, and uranyl ions are known to react with ZVI.Examples that conceptually illustrate these reactions are as follows:

Fe0 + 6H+ + CrO42– = Fe3+ + Cr(OH)2

+ + 2H2O

Fe0 +4H+ + TcO4– = Fe3+ + TcO2 + 2H2O

2Fe0 + 3UO22+ = 2Fe3+ + 3UO2

The reduction of these metals tends to make them less soluble and less mobilethan the oxidized forms. Because these contaminants generally are present insuch low concentrations in groundwater, it has not been possible to identifyspecific solid phases where they are located within PRBs. For example, Phillipset al. (2000) did not observe uranium-bearing phases at the Y-12 PRB. However,Fiedor et al. (1998), and Gu et al. (1998, 2002a) were able to confirm that U(VI)readily reduced to U(IV) in laboratory experiments with ZVI. Gu et al. (1998)also confirmed that precipitation, not sorption, was the overwhelmingly dominantprocess for immobilizing uranium. For the PRB in Elizabeth City, North Carolina,Puls et al. (1999b) report that the chromate contaminant in groundwater wasreduced to the chromic (Cr3+) form in an insoluble mixed Cr–Fe hydroxide,although that assumption is based on the sharp decrease in chromium concentra-tions within the PRB rather than characterization of specific chromium-bearingphases. Based on their work at this PRB, Mayer et al. (2001) also assert thatchromic hydroxide is the likely Cr(III)-bearing phase formed. There is no doubtthat ZVI reduces these metals, but whether they are immobilized in the form ofa separate reduced solid state, sorbed in phases such as iron oxyhydroxides, co-precipitated with other metals, or a combination of all of these processes has notbeen thoroughly studied.

The final geochemical process deserving consideration is related to the poten-tial for contaminant remobilization from an aging PRB. For contaminants suchas metals and radionuclides where sorption and/or precipitation associated withreduction is the dominant process occurring, the contaminants can be releasedeventually through ion exchange, desorption, reoxidation, or colloidal transport.Beyond recognition of these possibilities, little formal study of this potential hasbeen performed. Of more immediate concern, however, is that some regulatoryagencies may insist on eventual excavation and removal of reactive media whenprecipitation and/or sorption are the dominant processes of contaminant seques-tration. Currently, there is no information concerning the risk associated eitherwith leaving the PRB in the ground or excavating it. Considering the cost asso-ciated with excavating, transporting, and disposing of spent reactive media, thisdeserves further investigation.


2.3.1.3 Reaction Kinetics

Reaction kinetics must be considered for chemical reactions occurring withinPRBs. From a design perspective, the target contaminants (and any toxic daughterproducts) must have adequate residence time within the barrier to react sufficientlyso that effluent concentrations meet design expectations at the downgradient pointof compliance (POC). Typical values of half-lives for common organic contam-inants with commercial iron tend to range from less than one to approximately50 hours, depending on the contaminant and the source of iron used. Tabulatedsummaries of measured half-lives for many compounds are given by Gillham(1996) and AFRL (2000); however, in the design phase of a PRB, site-specifichalf-lives of target contaminants usually are determined experimentally.

Residence times are also partially dependent on the architecture of the ground-water flow system within the PRB. Flow heterogeneities (e.g., preferential path-ways) generally exist and can permit target contaminants to migrate through thePRB more rapidly than designed, resulting in inadequate concentration reduction.In addition, ZVI corrosion reactions and precipitation of secondary phases withina PRB can lead to progressive clogging of the media, resulting in localized flowdiversion. Tracer tests have been conducted at several PRBs and illustrate theheterogeneous nature of groundwater flow that exists (e.g., Battelle, 1998).Although the impacts of heterogeneities on groundwater flow and contaminantresidence times in PRBs have received only limited attention, Benner et al. (2001)modeled heterogeneous aquifer-barrier systems and provided some insights onhow the effects on preferential pathways and residence time can be minimized.

2.3.2 IMPACTS ON DOWNGRADIENT BIODEGRADATION PROCESSES

At many sites, the rate of natural biodegradation is not sufficient to meet remedialgoals, and intervention is required in the form of additional treatment to accelerateor enhance the degradation rate. ZVI treatment and natural biodegradation arecompatible treatment processes for many chlorinated solvents. Both are reductiveprocesses that follow first-order reaction kinetics, and both involve the generationof partially dechlorinated daughter products with reaction rates that are typicallyslower than those of the parent compound. Under appropriate circumstances, thetwo treatment processes may be synergistic in that the ZVI treatment can enhanceor accelerate downgradient biodegradation rates by creating geochemical condi-tions more suitable to anaerobic bacterial metabolism. A variety of mechanismsmay be operative that stimulate biological processes.

2.3.2.1 Enhancement of Geochemical Conditions Conducive to Anaerobic Biodegradation

ZVI PRBs remove any dissolved oxygen or nitrates present in the upgradientgroundwater. The removal of these inorganic electron acceptors lowers the oxi-dation/reduction potential of the groundwater, creating more favorable conditions


for reductive biological processes. In addition, many of the organisms involvedin chlorinated solvent biodegradation are obligate anaerobes that cannot survivein the presence of oxygen.

2.3.2.2 Overall Contaminant Concentration Reduction

In cases where a PRB does not achieve complete treatment of the parent com-pounds or reaction daughter products, partial treatment reduces the total loadingof chlorinated contaminants in the downgradient aquifer. Such incomplete treat-ment can be helpful to the downgradient biological processes in a number of ways.In aquifers that are electron donor limited, the PRB can bring down the concen-tration of chlorinated solvents to a point where they can be fully dechlorinatedby the available electron donor supply.

Some chlorinated compounds are known to inhibit reductive dechlorinationprocesses when present above a threshold concentration. An example of this isthe observed inhibitory effect of chloroform (CF) on the reductive dechlorination ofchlorinated ethenes (Maymo-Gatell et al., 2001). This effect has been observed atCF concentrations above a few parts per million. 1,1,1-trichloroethane (1,1,1-TCA)and carbon tetrachloride have also been observed to inhibit methanogenesis andthe dechlorination of chloroethenes, although not a severely as CF (Adamson andParkin, 2000). The PRB can create more favorable conditions for dechlorinationby reducing the concentration of such compounds to below the level where theyare inhibitory.

A third beneficial effect of incomplete treatment is that the effects of competingelectron acceptors can be reduced or eliminated. When mixtures of chlorinatedsolvents are present in groundwater, the dechlorinating bacteria preferentially usethe electron acceptors that yield the most energy for their metabolism. Themetabolic energy available from a given half-reaction is expressed as the Gibbsfree energy of reaction, in units of kilojoules per mole. The greater the Gibbs freeenergy available from dechlorinating a given compound, the more likely it is thatthe dechlorinating bacteria will preferentially use that compound as an electronacceptor. This effect can be significant in plumes with mixtures of differentchlorinated compounds.

2.3.2.3 Production of Hydrogen

Hydrogen gas is produced in PRBs as a product of ZVI corrosion. Hydrogenserves as the ultimate electron donor in the biological reductive dechlorinationof chlorinated solvents and is known to stimulate reductive biological processes.The production of hydrogen may explain the “halo” of enhanced biologicalactivity observed in the immediate vicinity of ZVI PRBs, both upgradient anddowngradient (Gu et al., 2002b). The presence of dissolved hydrogen understrongly reducing conditions can stimulate methanogenesis, as well as biologicalreduction of chlorinated ethenes. Although the produced hydrogen is not expectedto persist far downgradient of the PRB, the enhanced biological activity in this


hydrogen-rich zone can have effects that extend further. Dechlorinating organisms,notably Dehalococcoides ethenogenes, are known to be mobile in groundwatersystems and can be carried downgradient with the groundwater flow (Ellis et al.,2000). As such, the hydrogen-rich zone immediately downgradient of the PRBcan act as a robust source of dechlorinating organisms for the downgradientplume. However, increased microbial activity can result in PRB biofouling(Gu et al., 2002b).

2.3.2.4 Electron Donor Production

The ZVI reaction products from chlorinated solvent treatment include fully andpartially dechlorinated simple organic compounds that can serve as electrondonors for downgradient biological dechlorination processes. Examples includethe production of formate from carbon tetrachloride and ethene from PCE andTCE. Similarly, the treatment of 1,1,1-TCA with ZVI yields a significant amountof ethane, with lesser amounts of ethene, cis-2-butene, and 2-butyne (Fennellyand Roberts, 1998).

Typically, the daughter products of chlorinated solvents treated with ZVI arepartially dechlorinated and therefore less highly oxidized than the parent com-pound. Some of these partially reduced daughter products can be used as electrondonors in downgradient biodegradation processes, particularly in aquifers thatare not strongly reduced. An example is the conversion of carbon tetrachlorideto dichloromethane (DCM) in a PRB. DCM is known to biodegrade rapidly underboth aerobic and anaerobic conditions. Under aerobic conditions, DCM can bebiologically oxidized to carbon dioxide and hydrochloric acid. Under anaerobicconditions, DCM can be converted to acetate by fermentation (Freedman andGossett, 1991). The generated acetate can then serve as an electron donor. Otherexamples of partially dechlorinated compounds that can serve as electron donorsare cis-1,2-dichloroethylene (cis-1,2-DCE) and vinyl chloride, the daughter prod-ucts of PCE and TCE (Bradley and Chapelle, 2000), and 1,1-DCE, the daughterproduct of 1,1,1-TCA. In aerobic aquifers, the biological transformation of fullychlorinated compounds such as PCE or carbon tetrachloride does not occur. Undersuch conditions, a PRB can convert these compounds into lesser chlorinatedspecies, which subsequently can be biologically oxidized.

2.3.2.5 Direct Addition of Dissolved Organic Carbon

The addition of organic carbon to an aquifer can significantly accelerate reductivebiodegradation processes by providing a ready supply of an electron donor. In somecases, the introduction of organic carbon to the aquifer may be the sole purposeof the PRB and no other reactive media is involved. Such applications are referredto as biobarriers or bio-walls and involve the emplacement of a slow release sourceof organic carbon such as compost or vegetable oil. It is a matter of discussionwhether such treatment should be considered a permeable barrier technology orwhether it should be considered purely in the context of bioremediation.


More commonly, the introduction of dissolved organic carbon can be anancillary effect from ZVI emplacement, as in the case of biopolymer trenchingor guar-based injection methods such as hydraulic fracturing or jetting. Whentrenching is used as the construction method for a PRB, a high-density biode-gradable slurry is often used to hold the trench open during excavation andemplacement of the reactive media. Typically, the slurry-filled trench is filledwith the granular iron or sand/iron mixture from the bottom up using a tremie.After the reactive media is emplaced, the biopolymer slurry is typically brokenwith an enzyme that converts it into simple soluble sugars. Complete breakingof the slurry is essential to ensure that the completed PRB will have the desiredpermeability. The resultant simple sugars are then dissolved in the groundwaterand carried downgradient in the PRB effluent.

Guar is used to suspend the granular iron during injection-based PRBemplacement methods such as jetting and hydraulic fracturing. Guar is a highlysoluble food-grade starch which, when chemically cross-linked, forms a highlyviscous gel. This viscous gel serves as a carrier fluid for the iron during the jettingor fracturing process. As in the case of biopolymer slurry trenching, a breakerenzyme is added to the gel/iron slurry as it is injected into the subsurface, resultingin the transformation of the cross-linked slurry into simple soluble sugars.

Dissolved organic carbon introduced as a by-product of PRB construction istransient and completely consumed after a period of time. This period of time,however, may last as long as a few years depending on site-specific conditionssuch as groundwater velocity and the amount of biological activity. During thisperiod, the introduced organic carbon can significantly impact downgradientgroundwater quality, particularly during the transition period from pre-PRB con-ditions to the new post-PRB steady-state. In fact, the organic carbon can shortenthe period of time necessary to reach steady-state by accelerating biodegradationand consequently accelerating the rate of desorption in the downgradient aquifer.

2.3.3 PRB SYSTEM DYNAMICS

After a PRB is installed, treated groundwater begins to displace untreated ground-water in the downgradient aquifer. Notwithstanding this influx of treated water,contaminants continue to be present in the downgradient aquifer for some timeafter PRB installation, largely due to the slow desorption of contaminants fromthe aquifer solids. This desorption occurs as the downgradient aquifer transitionsinto a new equilibrium with the treated PRB effluent. Eventually, the reservoirof sorbed contaminants is depleted and downgradient contaminant concentrationsare no longer replenished by the dissolution of sorbed contaminants. This processcan take several years, depending on site-specific factors such as aquifer grainsize, fraction of organic carbon (FOC), groundwater velocity, and initial contam-inant concentrations.

The rate of desorption is a function of the relative amounts of the compoundin the dissolved phase and the sorbed phase. Like dissolution, the rate of desorp-tion is largely driven by the concentration gradient. Desorption rate can be


modeled using the Langmuir isotherm and is often represented as a graph ofdissolved phase concentration vs. time. In groundwater systems, time is equivalentto the number of pore volumes of clean water that have passed through the aquifermaterial. A typical desorption curve is shown in Figure 2.4.

Sorbed phase contaminants are largely unavailable for biodegradation. Ascontaminants desorb from aquifer solids and re-enter the dissolved phase, theybecome available to dechlorinating organisms in the downgradient aquifer. Bio-degradation can accelerate the desorption process by suppressing contaminantconcentrations in the dissolved phase. Downgradient biodegradation processescan be accelerated by the presence of organic carbon from PRB construction andother processes discussed later.

Both the desorption of parent compounds and the subsequent biodegradationof these compounds into fully or partially dechlorinated daughter compoundsimpacts downgradient groundwater quality until steady-state is reached. Datafrom groundwater monitoring during this transient period can be confusing andcan lead to erroneous conclusions about the performance of the PRB itself. Forexample, the persistent presence of parent compounds such as TCE or PCE dueto desorption in the downgradient aquifer can be interpreted as breakthrough orleakage of these compounds through the PRB because of faulty construction suchas PRB holes or gaps. Similarly, the presence of cis-1,2-DCE or vinyl chlorideresulting from partial biodegradation of desorbed PCE or TCE can be incorrectlyinterpreted as daughter products in the PRB effluent resulting from insufficientresidence time in the reactive treatment zone. It is therefore useful to model these

FIGURE 2.4 Representative desorption curve.

Theoretical Desorption Curve

Time

Nor

mal

ized

Con

cent

ratio

n

0.8

1

0.2

0.6

0.4

0


processes to develop an estimate of the amount of time needed for the aquifer toreach steady-state at a given distance downgradient of the PRB.

Figure 2.5 shows a conceptual model of a treatment train consisting of a PRBin combination with natural biodegradation processes at steady-state. The con-centration of the target constituent (vertical axis) is shown vs. distance in thedowngradient direction (horizontal axis). C0 represents the initial concentrationin the upgradient area, which decreases in the downgradient direction at theintrinsic rate of natural biodegradation at the site. This intrinsic rate can be slowor negligible at sites where additional treatment has been deemed warranted. Ct isthe target concentration that needs to be achieved prior to reaching the downgra-dient POC. It is not necessary to design the PRB to achieve Ct at the downgradientedge of the PRB, if space is available downgradient of the PRB for biodegradationto further reduce the concentration prior to reaching the POC. Cd is the PRBdesign concentration selected to achieve the target concentration at the POC,taking downgradient biodegradation into account.

Consider the case of a treatment train consisting of ZVI treatment in a PRBfollowed by natural biological degradation for treatment of a carbon tetrachlorideplume. When treated by ZVI, carbon tetrachloride can be completely transformedinto the fully dechlorinated end products carbon monoxide and formate, with apartial yield of trichloromethane (TCM) (approximately 40% on a molar basis).The generated TCM can then be completely transformed into a mixture of fullydechlorinated end products and DCM, which is not further treated by the ZVI.The end result of this reaction series is the complete transformation of carbontetrachloride and TCM, with production of DCM in the amount of approximately

FIGURE 2.5 Conceptual model of chlorinated solvent treatment using a PRB coupledwith natural biodegradation.

Compliance point Permeable

barrier

Design basis

Co

Cd

Ct


20% of the parent carbon tetrachloride on a molar basis. Biodegradation can bean effective means of treating the generated DCM daughter product, therebyachieving complete dechlorination of the parent carbon tetrachloride to nonchlo-rinated end products prior to reaching the POC. DCM is known to be rapidlybiodegradable under a variety of environmental conditions, both aerobic andanaerobic (Cox et al., 1998).

In addition to carbon tetrachloride, the design approach shown conceptuallyin Figure 2.5 can be used to optimize the design of PRB remedies for otherchlorinated solvents where daughter products are generated that can be fullytransformed in the presence of ZVI, but at a slower rate than the parent com-pounds. The slower reaction rates of the daughter products necessitate a longerresidence time in the reactive iron zone to achieve full dechlorination, resultingin a thicker PRB and correspondingly greater cost. Examples of such compoundsinclude PCE and TCE. In the case of PCE and TCE, the daughter compoundscis-1,2-DCE and vinyl chloride are generated as part of the ZVI-driven degrada-tion reactions. Both of these compounds have slower reaction rates than the parentPCE or TCE. The generated vinyl chloride and cis-1,2-DCE can be fully dechlo-rinated in a ZVI PRB given a sufficient thickness of iron and correspondingresidence time. However, significant cost savings can be realized by using theavailable aquifer space downgradient of the PRB as a natural bioreactor to degraderesidual cis-1,2-DCE and vinyl chloride rather than increasing PRB thickness.This approach is only practicable at sites where the biodegradation rates of thesedaughter compounds is sufficiently rapid and where sufficient space and residencetime is available downgradient of the PRB prior to reaching the POC.

2.3.4 GEOCHEMICAL MODELING

The discussion in the previous section illustrates that a variety of chemicalreactions occur when groundwater, with a complex mix of cations, anions, andcontaminants, passes through a ZVI PRB. One method for evaluating these typesof reactions and predicting their effects is through the use of geochemical models.There are several different kinds of geochemical models that can be applied toPRBs. Speciation models evaluate the state of thermodynamic equilibrium ofgroundwater in a static, closed system. Reaction path models add to speciationmodeling the capability of considering the step-wise reaction of the water witha medium such as ZVI. These models progressively compensate for groundwaterthat becomes oversaturated with respect to specified phases by allowing them toprecipitate to maintain a state of chemical equilibrium. Redissolution of an earlyformed phase also is possible if the changing groundwater composition leads toundersaturation. Coupled flow, transport, and reactive transport models potentiallydevelop a more realistic picture of reaction processes in dynamic systems byincorporating groundwater flow, solute transport (by advection, dispersion, anddiffusion), and reaction kinetics into the modeling. Inverse or mass balancemodeling differs from other types of geochemical models in that it does notinvolve thermodynamic considerations, but rather attempts to link two related


groundwater compositions by the dissolution and/or precipitation of phases froma user-specified list of candidate phases.

There are several general resources that discuss geochemical modeling indetail (Bethke, 1996; Paschke and van der Heijde, 1996; Zhu and Anderson,2002). Those individuals interested in the chemical, mathematical, and numericalmethods behind geochemical models and information about the limitations of thethermodynamic databases commonly used should consult these sources. In addi-tion, these sources provide listings and references to many of the most commongeochemical models in use today. AFRL (2000), Yabusaki et al. (2001), and Mayeret al. (2001) are examples of studies that focus on geochemical modeling asapplied to PRBs with ZVI as the reactive medium. The specific examples in thefollowing discussion are largely summarized from these and several additionalsources.

2.3.4.1 Speciation Modeling

Speciation models utilize the composition of groundwater (e.g., concentrationsof dissolved species, pH, redox state) and temperature as input data to examinea large number of chemical reactions that potentially interrelate the chemicalconstituents of the water. These models use the law of mass action to relate thevarious chemical species; identify the state of saturation of mineral phases; anddetermine the distribution of dissolved constituents among several different spe-cies (e.g., Ca2+, CaHCO3

+), including conversion of redox-sensitive species tomore stable forms consistent with the redox state of the system (e.g., NO3

– toNH3). At the heart of speciation models is a database containing the thermo-dynamic properties for elements, ions in solution, solid phases, and gases fromwhich the state of groundwater equilibrium is computed. Speciation models alsoincorporate corrections for the effects of ionic activity and temperature.

The saturation state of a specific phase in groundwater is determined by thesaturation index (SI), which is defined by the relationship:

SI = log (IAP/K)

where K is the equilibrium constant of the reaction controlling formation of thephase and IAP is the ion activity product for the reaction (i.e., using the actualactivities of the reaction species in groundwater). A state of equilibrium for thephase in the system is defined by SI = 0; SI > 0 indicates oversaturation and SI < 0defines a condition of undersaturation.

In general, speciation models predict some mineral phases will be oversatu-rated in groundwater; however, many of these phases will never be found pre-cipitating from the water. Slow kinetics is one reason. Likewise, some dissolvedions are known to inhibit the precipitation of certain phases, and this phenomenonis not captured by geochemical models. Therefore, natural groundwaters fre-quently are in meta-stable equilibrium with respect to some phases. For example,


clay minerals nearly always have SI >> 0, even when similar clays are found assecondary minerals in the host rock.

Phases that are known to form slowly, but are found to precipitate nonethelesscomplicate matters further. For example, the abiotic reduction of SO4

2– to S2–

(with subsequent precipitation of sulfide phases) involves the transfer of eightelectrons and is slow. Typically, such reactions are considered unlikely duringspeciation modeling. However, at the Portsmouth gaseous diffusion plant in Ohio,FeS was discovered in an ex situ, flow-through groundwater treatment canisterfilled with ZVI. Investigation determined that the FeS resulted from microbial-catalyzed reduction of SO4

2– to S2– followed by precipitation of the phase. There-fore, the potential for microbial processes should not be ignored during modeling.

MINTEQA2 (Allison et al., 1991), EQ3/EQ6 (Wolery, 1992), and PHREEQC(Parkhurst and Appelo, 1999) are examples of the many geochemical models thatcan perform equilibrium speciation calculations for groundwaters and evaluatethe saturation state for a large number of phases.

AFRL (2000) contains an example of speciation modeling applied to a ZVIPRB at Naval Air Station (NAS) Moffett Field in Mountain View, California.Groundwater samples were collected from monitoring wells placed in locationsupgradient of, within, and downgradient of the PRB. Using PHREEQC, it waspossible to evaluate the changing saturation state of a variety of selected mineralphases for groundwater at different positions within the barrier system. Forexample, upgradient groundwater at this site is observed to be close to equilibriumwith respect to calcite (or aragonite). However, within the PRB near the upgra-dient side, calcite becomes oversaturated and then becomes sharply undersatu-rated within the PRB further in the downgradient direction. A reasonable inter-pretation is that, as the water becomes oversaturated in calcite in the first fewfeet of the PRB, the phase precipitates. Further downgradient of the PRB, chang-ing groundwater composition (e.g., decreasing concentrations of Ca2+ and alka-linity) result in undersaturated conditions for the phase. Analogous relationshipsare observed for other phases. This modeling supports the general observationthat most precipitation occurs near the sediment-PRB interface. Speciation mod-eling is a qualitative and indirect method for evaluating the reactions that canoccur within a PRB. A more direct (and quantitative) approach is through reactionpath modeling.

2.3.4.2 Reaction Path Modeling

The next level of complexity for geochemical models is reaction path modelingin which groundwater is permitted to react with (i.e., dissolve) a small amountof the host media (i.e., ZVI), the resultant equilibrium state of the groundwateris determined, and oversaturated phases are permitted to precipitate to achieve amore stable state of equilibrium. An early formed phase can redissolve at a laterpoint if the groundwater becomes undersaturated because of other reactions thatoccur and because the phase has not become isolated from the water. Carriedthrough many reaction steps, it can be examined how the groundwater chemically


evolves and what phases (and their amounts) precipitate or redissolve at eachstep. Computing the masses of different phases both dissolving and precipitatingwithin PRBs as a function of reaction progress can yield estimates of the rate ofpore space in-filling, an important consideration in predicting the lifetime of abarrier. In an effort to match what is observed in the PRB, reaction path modelspermit the user to suppress the precipitation of phases that are not observed toform due to extremely slow kinetics. Reaction kinetics can be incorporated intoreaction path modeling if sufficient information about reaction rate equations isavailable (Gunter et al., 2000). Examples of geochemical models that have theability to perform reaction path calculations include PHREEQC (Parkhurst andAppelo, 1999), EQ3/EQ6 (Wolery, 1992), and Geochemist’s Workbench (Bethke,1994).

Reaction path modeling has been applied to the PRB at NAS Moffett Fieldand is reported in AFRL (2000). In contrast to results from speciation modelingat the barrier described above, reaction path modeling is able to provide a vividconceptual picture of the complex interplay of the impacts of iron dissolution togroundwater chemistry (e.g., large, rapid increase in pH and decrease in redoxpotential) and associated onset of precipitation of new phases with increasingreaction progress (e.g., siderite, FeS2, aragonite and magnesite, followed byFe(OH)3 and green rust). In the case of aragonite, magnesite, and siderite, pro-gressive decreases in Ca2+, Mg2+, Fe2+, and alkalinity concentrations in the laterstages of reaction progress lead to eventual dissolution of these early formedphases. Sequential changes in the amounts of solid phases formed and dissolvedconstituents in groundwater can be graphically and quantitatively tracked. In thisexample, a small number of plausible phases were selected by the modeler toparticipate in the reactions; all others were suppressed. Clearly, the degree to whichthe model represents what happens in the PRB is dependent on this selectionprocess, although other factors are important as well.

Although reaction kinetics can be incorporated into reaction path modeling,it is not possible to develop a temporal and spatial picture of reactions occurringwithin a PRB without explicitly including flow and transport. The following sub-section examines this more advanced approach to geochemical modeling.

2.3.4.3 Reactive Transport Modeling

Reactive transport modeling is the most sophisticated form of geochemical mod-eling currently in use and incorporates groundwater flow, solute transport, andgeochemical reactions in a fully coupled modeling system. The primary advantageof coupled modeling is that there is an added degree of realism because theelement of time is explicitly included in the simulations. As a result, reactionkinetics can be incorporated into the modeling scheme and, in principle, thechanges in groundwater chemistry and phases precipitating can be seen as afunction of time (and space) as a packet of water passes through a PRB.

In general, the maturity of coupled codes is considerably greater than ourability to provide adequate characterization data to populate the models. Chemically,


not only are the thermodynamic data important, but kinetic relationships for thekey phases, and sorption relationships for important dissolved species are needed.In addition, hydraulic information from which the flow equations can be simulatedis required. The amount and variety of data needed to take full advantage of thecapabilities of modern coupled models is significant and probably not somethingto be expected for normal PRB design activities. However, when used as aresearch tool capable of capturing the important components of the site hydrologyand geochemistry through sensitivity analysis, this type of modeling can behelpful in determining what level of sophistication of modeling is really necessary.

PHREEQC (Parkhurst and Appelo, 1999), MIN3P (Mayer, 1999), OS3D(Steefel and Yabusaki, 1996), and the Geochemist’s Workbench (Bethke, 1994)are examples of coupled flow, transport, and geochemical models.

Continuing with the example provided by the PRB at NAS Moffett Field,Yabusaki et al. (2001) presented results of a reactive transport investigation usingthe OS3D modeling code (Steefel and Yabusaki, 1996). For this study, one-dimensional transport was used. As in the other modeling methods describedabove, a set of plausible phases was selected by determining if the phases wereundersaturated in the background groundwater and oversaturated in the PRB.Phases such as Fe(OH)3(am), Fe(OH)2(am), siderite, aragonite, and green rust wereincluded. Reaction rate equations were selected for the key reactions to be modeled.Hydraulic data was selected; dispersion and diffusion were ignored. Althoughnot without some problematic results, reactive transport modeling succeeded inproviding improved understanding of the inter-relationship between transport andreaction rates occurring in the field.

A second example of reactive transport modeling, applied to a ZVI PRB inElizabeth City, North Carolina, was illustrated by Mayer et al. (2001). In thisexample, Cr(VI) and TCE were the target contaminants. The modeling resultswere able to closely match the observed behavior of these contaminants withinthe barrier, as well as that of other groundwater chemistry parameters such aspH and various dissolved inorganic species. In addition, this modeling approachoffered the possibility of hypothesizing important processes associated with morecomplex reactions.

2.3.4.4 Inverse Modeling

All of the types of modeling discussed so far are examples of forward modeling.Inverse geochemical models use mass balance techniques to find a relationshipbetween two related groundwater compositions and the reactions that connectthem. These models can only be applied to a system (e.g., a PRB or flow-throughcolumn) where at least two groundwater samples are available, with the reason-able assumption that one groundwater directly evolved from the other. The useridentifies a list of plausible phases that can relate the two groundwater samples.The model then uses analytical methods to define all combinations of these phasesthat, when dissolved precipitate from the initial groundwater composition, or willyield the later stage groundwater. In general, solutions to inverse modeling are


nonunique and, being strictly a mass balance or mathematical operation, thermo-dynamics does not enter into the simulations. One application of this methodologythat might be used to help understand possible reactions in a future PRB is aflow-through column. Because it is not thermodynamically based, issues such asreaction kinetics, inhibitions, and microbial catalysis do not enter into the mod-eling. If the list of plausible phases is inclusive, the combinations of phases andamounts of them can be determined mathematically to account for changes ingroundwater chemistry. It is up to the user to determine which, if any, of theacceptable solutions is realistic.

NETPATH (Plummer et al., 1994) and PHREEQC (Parkhurst and Appelo,1999) are two models that perform mass balance modeling.

An example of an inverse modeling example based on data from the NASMoffett Field PRB is presented in AFRL (2000). In this example, compositionsof an upgradient groundwater and of a groundwater inside the PRB 0.5 feet fromthe upstream side of the PRB were selected for modeling. Eight plausible phaseswere selected. Only ZVI was allowed to dissolve; the other phases [Fe(OH)3,siderite, marcasite, brucite, aragonite, magnesite, and CH4] were only allowed toform. Using the mass balance capability of PHREEQC, four acceptable solutionsresulted that successfully related the two groundwater compositions. Based onfield observations at the PRB site, one of the models was rejected, but theremaining models were considered equally reasonable. In general, one mightimagine selecting the most probable model based on field observations of theidentity and amounts of precipitated phases. However, when the quantity ofsecondary phases is small, it is difficult to obtain an accurate estimate of theirabundance with standard solids characterization techniques. The relatively smallnumber of solid samples that reasonably can be collected and analyzed from aPRB further compounds this difficulty. Therefore, no selection among the threeremaining models was possible.

2.3.5 MODELING LIMITATIONS AND RESEARCH NEEDS OF PRBS

Geochemical modeling can be a powerful predictive tool when applied to PRBsystems. One major advantage of working with a ZVI barrier system in compar-ison to normal geologic systems is the inherent simplicity of the iron medium.In effect, a single simple phase is present (Fe) that has well characterized physical,chemical, and thermodynamic properties. However, as with any natural system(especially one with flowing groundwater), the simulation of multiple heteroge-neous reactions is not without complexities. Attempts to make such models morerealistic (temporally and spatially) have increased the burden on the modeler toobtain appropriate data. For example, reaction rate equations, sorption relation-ships, hydraulic properties, and microbially catalyzed reactions are some of thecomplications that can be important.

As noted above, the most sophisticated models used today are more maturethan our ability to supply required input data at an appropriate scale. The majorlimitations in modeling PRBs arise from inadequate knowledge of the processes


occurring in PRBs, especially as PRB materials age. In spite of these limitations,experience gained investigating and modeling existing PRBs improves the under-standing of key processes, helps refine the selection of plausible phases, and helpsfocus on the most sensitive parameters to quantify.

2.4 WALLS AND FLOORS

Both vertical and horizontal barriers can be used to mitigate the extent of sub-surface contaminant migration. The most common type of vertical barrier is theslurry cutoff wall, whereas horizontal barriers can include constructed engineeredbarriers (floors) and natural geologic formations such as aquitards and aquicludes.

2.4.1 VERTICAL BARRIERS

The three main types of cutoff walls used as vertical barriers for subsurfacecontainment of contaminated groundwater are soil–bentonite (SB) walls,cement–bentonite (CB) walls, and composite slurry walls (CSWs). SB cutoffwalls are constructed by displacing the bentonite slurry in an excavated trenchby backfilling with a mixture of the bentonite slurry and the excavated trenchspoils. CB cutoff walls are constructed using a mixture of cement and bentoniteslurry to maintain the stability of the excavated trench and then allowing themixture to set to form the cutoff wall. CSWs are constructed by inserting ageomembrane into the slurry along the centerline of the trench during construction.

In most applications involving the containment of contaminated groundwater,vertical cutoff walls are keyed into naturally occurring horizontal barriers formedby low-permeability geologic formations, such as aquitards or aquicludes, toimpede contaminant migration beneath the zone of contamination.

2.4.2 HORIZONTAL BARRIERS

In the case where a suitable aquitard or aquiclude is too deep, the constructionof a horizontal barrier beneath the zone of contamination may be required. Themore common options for horizontal barrier construction based on existing tech-nologies are permeation grouting and jet grouting. Permeation grouting involvesthe injection of a low viscosity slurry material into the ground through a seriesof overlapping injection wells. Construction of a basal barrier by permeationinjection requires the grout material to penetrate the soil completely and remainin place until solidification is complete. For jet grouting, a single fluid (grout),two fluids (grout/air), or three fluids (grout/air/water) are injected into the soilunder high pressure (over 300 atm) through a small orifice (1 to 2 mm diameter)to erode or cut the soil and simultaneously place and mix the grout, resulting ina homogeneous columnar mass (e.g., Kauschinger et al., 1992; Tausch, 1992).Jet grouting is feasible in virtually all soil conditions ranging from clays to gravels(Kauschinger et al., 1992).

The jet grouting technique can be used to form a horizontal barrier belowthe waste material by drilling on a regular grid pattern to form a system of


inter-penetrating grout discs. In this application, a borehole is driven to therequired depth, and a jet grout monitor is inserted. The monitor is fitted with ahigh-pressure jet-cutting nozzle and can be rotated to cut a disc-shaped hole atthe required depth. The monitor is raised during cutting to form a disc of therequired thickness. Jet grouting can also be used to form inclined barriers (Dwyeret al., 1997). The barrier in this case consists of two honeycombed rows ofinterconnected vertical and inclined Portland-based grout columns forming a V-shaped trough in which the contamination is located. The inside of the cementV-trough can be lined with a low viscosity, chemically resistant polymer to forma secondary barrier to contaminant movement. This approach offers the advantageof not having to drill through the contamination.

Another possible approach is to use horizontal directional drilling to form abarrier under the contamination (Sass et al., 1997). Although not yet practical,this technique potentially overcomes the shortcomings of vertical or inclineddrilling and has been successful in contamination detection (Katzman, 1996;Anon, 2000).

2.4.3 CURRENT STATE OF PRACTICE FOR MODELING PERFORMANCE OF WALLS AND FLOORS

Given the limitations of the prescriptive design approach, a performance-baseddesign approach may be more appropriate to ensure successful containment. Ina performance-based design, individual properties or elements of a containmentsystem are not prescribed. Instead, the design is based on demonstration that thecontainment system will meet the overall objective. For example, the overallobjective may be to maintain the concentration of a target pollutant at a levelbelow risk-based standards [e.g., drinking water maximum contaminant levels(MCLs)] at a downgradient POC (e.g., fence line, monitoring well) or point ofexposure (POE) (e.g., drinking water well). Predictive contaminant transportmodeling will be a critical component for demonstrating successful performancein this regard.

This chapter provides a comprehensive description of the current state of theart for prediction of the performance of vertical cutoff walls for waste contain-ment. The description is focused on applications in the saturated zone, withemphasis on performance of cutoff walls for containment of aqueous phasemiscible contaminants. However, given the recent interest in vadose zone walls,liquid- and gas-phase transport processes that govern the performance of vadosezone walls merit some consideration and are described in this chapter to providea foundation for future development of design criteria and/or transport modelsfor prediction of wall performance.

Either a component approach or a system approach may be adopted whenusing models to assess the effectiveness of containment barriers in terms ofmitigating the extent and/or impact of subsurface pollution. In the componentapproach, only the barrier is modeled. This approach allows for the use ofrelatively simple analytical models (e.g., Rabideau and Khandelwal, 1998a,b). In


the system approach, multiple components of the flow domain, such as a verticalcutoff wall located within an aquifer, are modeled as a system resulting in theneed to consider the effect of heterogeneous media. This approach generallyrequires the use of more complex semi-analytical or numerical models (e.g., finitedifference, finite element).

These two approaches differ primarily with respect to the point at which thecontaminant migration is evaluated, such as the POC or POE. The component oranalytical modeling approach is relatively simple to use, but is potentially con-servative in that the POC typically must be assumed to be located at the outerboundary of the barrier rather than at some other location downgradient of thecontainment location. As a result, the design based on a component analysis maybe too conservative and, therefore, ineffective in terms of cost.

In most cases, environmental regulations allow for a POC at some locationdowngradient of the containment facility (e.g., the interface between a confinedsite and the upper confining layer, a property boundary, some other location) suchthat the impact of contamination reaching the outer boundary of the barrier isnot the primary concern. In such cases, the system approach using either semi-analytical or numerical models may be more appropriate (i.e., less conservative)and, therefore, may result in more cost-effective designs. However, the systemsapproach generally requires more input data than the component approach, tend-ing to offset the difference in cost between the two approaches.

2.4.4 CONTAMINANT TRANSPORT PROCESSES

Most barriers employed in geoenvironmental applications are designed to providecontainment of dissolved contaminant plumes in groundwater. Thus, the discus-sion herein is limited to processes that govern the liquid-phase migration ofsolutes. The reader is referred to Bear (1972), Corey (1994), Pankow and Cherry(1996), and Charbeneau (2000) for information regarding the migration of immis-cible fluids.

2.4.4.1 Aqueous-Phase Transport

Aqueous-phase contaminant transport in porous media is controlled by a varietyof physical, chemical, and biological processes. The primary physical processesgoverning miscible contaminant transport are advection, diffusion, and dispersion.Diffusion tends to be the dominant transport process in relatively low flow ratesituations, such as those that occur through clay barriers (Rowe, 1987; Shackel-ford 1988, 1989). However, advection and dispersion dominate in relatively highflow rate situations, such as contaminant migration through coarse-grained aquifermaterials.

Processes such as adsorption, radioactive decay, precipitation, hydrolysis, andbiodegradation generally are considered attenuation processes in that contaminantmass is removed from the aqueous phase. However, in some cases, some of theseattenuation processes may not be effective in reducing the potential impact of


the contaminants. For example, the radioactive decay of the initial contaminantresults in by-products that also can represent a potential adverse environmentalimpact. Similarly, subsequent desorption of a previously adsorbed contaminantor dissolution of a previously precipitated contaminant can result in negativeenvironmental impacts.

Typically, only the physical processes of advection, diffusion, and dispersion,and the chemical processes of sorption and radioactive decay are included inpractical modeling applications. Although prototype models that include the morecomplicated chemical processes (e.g., oxidation/reduction, precipitation, hydrol-ysis, complexation, biodegradation) have been formulated, these models are con-sidered not yet suitable for routine use in practice (National Research Council,1990). Thus, the development contained herein pertains primarily to modelingadvection, dispersion, and/or diffusion with sorption and radioactive decay.

For applications involving subsurface containment barriers, aqueous-misciblesolute transport traditionally is described using the one-dimensional form of theadvective-dispersive transport equation, in which the total flux of a solute, J, isrepresented as the sum of advective, diffusive, and dispersive fluxes, or:

(2.3)

where Ja is advective flux, Jd is diffusive flux, Jm is mechanical dispersive flux,qh [= khih, where kh = hydraulic gradient] is hydraulic liquid flux, C is the soluteconcentration, θ is the volumetric water content, which is equal to the porosity(n) for saturated media, D* is the effective diffusion coefficient, Dm is the coef-ficient of mechanical dispersion, vS (= qh /θ) is seepage velocity, D is the hydro-dynamic dispersion coefficient, and x is the direction of transport. For one-dimensional transport, the hydrodynamic dispersion coefficient, D, can beexpressed as follows (Freeze and Cherry 1979, Shackelford 1993):

(2.4)

where αL is the longitudinal dispersivity of the porous medium in the directionof transport. For transport through low permeability cutoff walls, the seepagevelocity, vs, is often sufficiently low that mechanical dispersion is negligible.

The governing equation for transient solute transport through porous mediabased on conservation of mass within a representative elementary volume (REV)is as follows:

(2.5)

J J J J q C DC

xv C D

C

xa d m h S= + + = −∂∂

= −∂∂

θ θ θ*

D D D D vm L S= + = +* * α

∂∂

= −∇ ⋅ +( )θR C

tJ Sd


where Rd is the dimensionless retardation factor that accounts for instantaneous,linear, reversible adsorption of the solute to the solid phase, and S is a generalsource (>0)/sink (<0) term for other chemical and/or biological reactions. Forexample, first-order decay of a chemical species can be included through a sinkterm as follows (van Genuchten and Alves, 1982):

(2.6)

where Λ is a lumped decay constant [T–1] given as follows (Rabideau and Khan-delwal, 1998a):

(2.7)

where λw is the decay constant for first-order decay of contaminant in aqueoussolution, and λs is the decay constant for first-order decay of contaminant on thesolid phase. The value of Rd is equal to unity for a nonreactive solute (i.e., Rd = 1)and greater than unity for a reactive solute (i.e., Rd > 1). For linear sorption, theretardation factor is written as:

(2.8)

where ρd is the dry bulk density of the soil, and Kd is the distribution coefficientthat relates the change in adsorbed concentration of a solute to a change in theliquid-phase solute concentration at equilibrium. For organic contaminants, thedistribution coefficient commonly is related to the organic carbon partition coef-ficient, Koc, as follows:

(2.9)

where foc is the mass fraction of organic carbon in the soil. The lumped decayconstant assumes several reduced forms depending on special conditions. Forexample, for nonadsorbing solutes (i.e., Rd = 1) or solutes that undergo decayonly in the aqueous phase (i.e., λs = 0), Λ = λw, whereas for equal rates of decayin both the aqueous and solid phases (i.e., λw = λs = λ), Λ = λRd.

Based on the assumptions that the porous medium is homogeneous, isotropic,and rigid (nondeformable); the water is incompressible; and the liquid flux issteady (i.e., vs = constant), the combination of Equations (2.3) through (2.8)results in the following form of the advection-dispersion reaction equation(ADRE) governing one-dimensional aqueous miscible transport:

(2.10)

S C= −θΛ

Λ = + −λ λw s dR( )1

R Kdd

d= +1ρθ

K K fd oc oc= ⋅

RC

tD

C

xv

C

xCd S

∂∂

=∂

∂−

∂∂

−2

2Λ


Equation (2.10) is often presented in dimensionless form:

(2.11)

where:

(2.12)

where L is the barrier thickness.Solution and application of Equation (2.11) requires specification of initial

and boundary conditions. Consider conditions as illustrated in Figure 2.6, whichcan be viewed as a vertical cross section for a horizontal barrier or a plan viewof a vertical wall. A complete solution of transport in this system requires a two-dimensional (or 3-D) description. However, a very common approach is to onlyconsider one-dimensional contaminant transport through the barrier and to chooseboundary conditions that are an approximation of reality. These boundary con-ditions consist of entrance boundary conditions on the inside of the barrier andexit boundary conditions on the outside of the barrier.

The most common entrance boundary condition used is the first type, con-sisting of specification of a temporally constant concentration at the inlet (x = 0):

C (0,t) = C0 (2.13)

FIGURE 2.6 Boundary conditions for horizontal (vertical cross-section) or vertical barrier(plan view).

Entrance: C(0, t)

L Horizontal or verticalbarrier

Groundwater flow

Exit: C(L, t)

Contaminatedmaterial

∂∂

=∂

∂−

∂∂

−C

t

C

xPe

C

xC

**

*

*

**

* *2

2Λ

CC

Ct

tD

R Lx

x

LPe

v L

D

L

Dd

s* * * *; ; ; ;= = = = =0

2

2

ΛΛ


van Genuchten and Alves (1982) also give boundary conditions that represent anexponentially decaying entrance boundary concentration. Third-type boundaryconditions consist of specifying that the sum of the advective and dispersive fluxesaway from the boundary is constant, given by the product of temporally constantfluid velocity and contaminant concentration:

(2.14)

These boundary conditions are appropriate for advection-dominated transporttypical of laboratory columns, but can give inaccurate flux predictions for thelow flow conditions typical of low permeability barriers (Rabideau and Khandel-wal, 1998a). Rowe and Booker (1985a) gave a modified third-type boundarycondition that assumed finite initial mass in a completely mixed source zone anddecreasing source concentration due to transport into the barrier. This boundarycondition was also used by Rabideau and Khandelwal (1998b).

The most common outlet boundary conditions used for general modeling ofcontaminant transport are semi-infinite boundary conditions of first type:

(2.15)

or second type:

(2.16)

The use of a semi-infinite boundary condition implies no change in materialproperties and flow perpendicular to the barrier on the aquifer side of the barrier.However, in many cases such as groundwater flow beneath a liner or parallel toa vertical barrier, contaminants leaving the barrier are diluted, thus reducing theconcentration at the exit boundary and increasing the concentration gradient anddiffusive fluxes. In these cases, a semi-infinite exit boundary condition (of anytype) is not appropriate because contaminant fluxes through the barrier would beunderestimated.

If the flow rate in the aquifer is rapid relative to the contaminant flux acrossthe barrier, the contaminant concentration at the barrier-aquifer boundary canapproach zero and a first type boundary condition may be appropriate:

C(L,t) = 0 (2.17)

Rowe and Booker (1985a) gave boundary conditions that accounted for therate of contaminant removal at the barrier-aquifer interface as a function ofgroundwater velocity, diffusion coefficient, barrier width, and aquifer depth.Equation (2.17) represents a more conservative assumption as it maximizes flux.

vC vC t DC

t0 0 0= −∂∂

( , )

C t( , )∞ = 0

∂ ∞∂

=C t

x

( , )0


When transport is advection dominated, a second-type boundary condition issometimes applied at the barrier-aquifer interface. This application is not appro-priate for systems where diffusion is significant because it assumes that diffusionacross the boundary is negligible (Rabideau and Khandelwal, 1998a).

2.4.4.2 Coupled Solute Transport

Although solute transport analyses for engineered soil barriers of low hydraulicconductivity typically are based on advective-dispersive theory as describedabove, advective-dispersive transport theory represents a limiting case of the moregeneral coupled flux transport theory in that coupling terms (e.g., chemico-osmosis) are assumed to be negligible (e.g., Yeung, 1990; Shackelford, 1997).While advective-dispersive theory is considered acceptable for coarse-grainedsoils (e.g., aquifers), use of advective-dispersive transport theory for clay-richsoil barriers may not be appropriate. For example, results of several laboratorystudies have shown that some clay soils have the ability to act as membranes thatrestrict the transport of charged solutes (i.e., ions) (e.g., Kemper and Rollins,1966; Olsen, 1969; Kemper and Quirk, 1972; Fritz and Marine, 1983; Malusiset al., 2001; Malusis and Shackelford, 2002a). This solute restriction also resultsin chemico-osmosis, or the movement of liquid in response to a solute concen-tration gradient, but opposite to the direction of solute diffusion (Olsen, 1969;Mitchell et al., 1973; Olsen, 1985; Barbour, 1986; Barbour and Fredlund, 1989;Neuzil, 2000).

Several solute transport models that account for the presence of soil mem-brane behavior have been developed (Bresler, 1973; Greenberg et al., 1973;Barbour and Fredlund, 1989; Yeung, 1990; Yeung and Mitchell, 1993; Malusisand Shackelford, 2002b). In all of these models, membrane behavior is repre-sented by a chemico-osmotic efficiency coefficient, ω, or reflection coefficient,σ, that ranges from zero (ω = σ = 0) for nonmembranes to unity (ω = σ = 1) forideal membranes that completely restrict the passage of solutes (Staverman, 1952;Kemper and Rollins, 1966; Olsen et al., 1990; Keijzer et al., 1997). Clay soilsthat exhibit membrane behavior typically only partially restrict the passage ofsolutes (i.e., 0 < ω, σ < 1) and, therefore, are considered nonideal membranes.

In the absence of electrical current, the general expression for total coupledflux of a chemical species, j (neglecting mechanical dispersion), can be writtenas follows (Shackelford et al., 2001):

(2.18)

where Jha,j is the hyper-filtrated advective flux of solute j, Jπ,j is the chemico-osmotic counter-advective flux of solute j, Jd,j is the diffusive flux of solute j, andqπ is chemico-osmotic liquid flux. The hyper-filtrated advective mass flux repre-sents the traditional advective transport term that is reduced by a factor of (1 – ω)

J J J J q C q C nDC

xj ha j j d j h j jj= + + = − + −

∂

∂, , , ( ) *π πω1


due to the membrane behavior of the soil [i.e., Jha,j = (1 – ω)Ja,j]. In physicalterms, the factor (1 – ω) represents the process of hyper-filtration whereby solutesare filtered out of solution as the solvent passes through the membrane under anapplied hydraulic gradient. The chemico-osmotic counter-advective flux representsthe transport of solutes due to chemico-osmotic liquid flux opposite to the direc-tion of diffusion (i.e., from low solute concentration to high solute concentration).

The chemico-osmotic liquid flux, qπ, can be written as follows (Malusis andShackelford, 2002c):

(2.19)

where γw is the unit weight of water and π is chemico-osmotic pressure. For dilutechemical solutions, chemico-osmotic pressure, π, is related to solute concentra-tion in accordance with the van’t Hoff expression or (Tinoco et al., 1995):

(2.20)

where R is the universal gas constant [8.143 J/mol⋅K], T is the absolute temper-ature [K], N is the total number of solutes. Thus, the summation term accountsfor the concentrations of all chemical species in solution, including species j. Forexample, if a solution contains the cation and anion of a binary, fully dissociatingsalt (e.g., sodium chloride), the chemico-osmotic pressure can be expressed asfollows:

(2.21)

where Ca and Cc are the concentrations of the salt anion and the salt cation,respectively. Fritz (1986) notes that the van’t Hoff equation is valid for concen-trations up to 1.0 M for monovalent salts (e.g., sodium chloride, potassiumchloride).

For transient transport, the total coupled solute flux equation (Equation (2.18))is substituted into the continuity equation (Equation (2.3)) to yield the following:

(2.22)

where vπ is the chemico-osmotic seepage velocity that is related to the chemico-osmotic liquid flux, qπ , or

qK

xh

wπ

ωγ

π=

∂∂

π ==∑RT Ci

i

N

1

π = +RT C Ca c( )

RC

tv

C

xv

C

xC

vx

D

djj

Sj j

j

∂

∂= −

∂

∂−

∂

∂−

∂∂

+

∂

( )

�� *

ω ππ1

22

2

C

x

Dx

C

xCj j

∂+∂∂

∂

∂−

*θΛ


(2.23)

Equation (2.22) must be written separately for each chemical species insolution. The equations are nonlinear and require a numerical method (e.g., finitedifference, finite element) to solve for the concentration distribution of a solutewithin a cutoff wall at any point in time. In addition, because the transport of asolute is dependent on the presence of other solutes in the system based onEquation (2.20), an iterative solution method must be utilized in conjunction withthe following electro-neutrality constraint that must be satisfied at all points withinthe system:

(2.24)

where Ci is expressed in molar concentration and Zi is the ionic charge of solutei. Further information with regard to solution of the coupled solute transportequations is given by Malusis and Shackelford (2002c).

2.4.4.3 Modeling Water Flow through Barriers

The simplest approach to modeling water flow through barriers is to apply Darcy’sLaw, assuming one-dimensional, steady-state saturated flow. If the hydraulic headdifference across the barrier is known, this approach is straightforward and canbe applied to single- or multiple-layer barriers. In cases where head differencesmay not be known, a barrier is usually modeled as part of a larger system suchas a landfill or a subsurface system. For landfills, the most commonly used modelis the HELP model (Schroeder et al., 1994a,b). The HELP model is an integratedquasi- two-dimensional model that includes the cap processes discussed in Sec-tion 2.3.2, vertical flow through a waste layer, lateral flow through a drainagelayer, and vertical flow through a horizontal barrier layer that can include ageomembrane. The model predicts water buildup above the barrier layer to predictleakage rates through the barrier layers.

To predict leakage rates through vertical barriers installed in complex hydro-geologic settings, a variety of numerical models can be employed, withMODFLOW (McDonald and Harbaugh, 1988) being the most widely used.Particular attention must be given to grid discretization issues because barriersare often small in size in comparison to the total size of the system beingsimulated, and sharp hydraulic head gradients and changes in groundwater flowdirections can occur in the vicinity of the barrier.

When geomembranes are employed in horizontal and vertical barriers, fluidflow through defects may be the dominant mode of water flow and contaminant

vq K

gRT

C

xh

w

i

i

N

ππ

θωθ ρ

= =⎛

⎝⎜⎞

⎠⎟∂∂

=∑

1

C Zi i

i

N

==∑ 0

1


transport. Foose et al. (2001) used MODFLOW to examine several analyticalmodels (e.g., Giroud, 1992; Rowe, 1998) for leakage rates through compositeliners. They concluded that the existing analytical solutions had shortcomingsand provided a series of recommendations for modification of these solutions fora variety of different conditions.

2.4.4.4 Analytical Models

Shackelford (1988, 1989) identified three possible scenarios (Figure 2.7) for thedesign of low permeability walls based on a one-dimensional conceptualizationof the system: (a) pure diffusion; (b) diffusion with advection and (c) diffusionagainst advection. The pure diffusion scenario represents the limiting case. Dif-fusive transport generally is significant through relatively thin (≤ 1 m) barrierswith K ≤ 10–7 centimeters per second (cm/s) and dominant through thin barrierswith K ≤ 5 × 10–8 cm/s (Shackelford, 1988, 1989). The diffusion with advectionscenario occurs when water levels on the inside of the barrier exceed those onthe outside. The diffusion against advection scenario occurs when the water levelis drawn down on the containment side of the wall to induce inward flow andreduce the outward flux of contaminants.

A variety of analytical models can be applied to predict one-dimensionalcontaminant transport under the scenarios illustrated in Figure 2.6 and Figure 2.7.Selection of the appropriate model involves a choice of steady-state or transientconditions and the choice of the appropriate boundary conditions. Analyses canbe performed to evaluate contaminant concentrations on the aquifer side of the

FIGURE 2.7 Design scenarios for low permeability walls: (a) pure diffusion, (b) diffusionwith advection, (c) diffusion against advection. (From Shackelford, C.D., 1989. Geotech-nical Engineering 1989, TRB, NRC, National Academy Press, Washington, DC, pp.169–182; Manassero, M. and Shackelford, C.D., 1994. Rivista Italiana di Geotecnica,AGI, 28(1). With permission.)

Diffusion

(b)

Advection

Diffusion

(c)

Advection

+x +x +x

Diffusion

(a)

co c < co co c < co co c < co


barrier, or flux rates of contaminants through the barrier as a function of wallthickness; drawdown across the wall; and the associated pore water velocity,effective diffusion coefficient (influenced by soil type), and adsorption capacityof the wall.

Rubin and Rabideau (2000) illustrated the impact of the Peclet number onsteady-state fluxes through one-dimensional barriers with constant concentrationentrance boundary condition, fixed-zero concentration exit boundary condition,and no decay. For zero concentration at the barrier-aquifer interface, the flux rate,F, through the barrier is:

(2.25)

In dimensionless form this becomes:

(2.26)

The dimensional flux, F*, is thus the ratio of steady-state advective-dispersiveflux to steady-state dispersive flux alone.

When decay occurs as the contaminant is transported through the barrier, thedimensionless flux is given by (Rabideau and Khandelwal, 1998a):

(2.27)

For the case of no decay (Rubin and Rabideau, 2000), this simplifies to:

(2.28)

Consider a 1 m thick barrier with a hydraulic conductivity of 10–9 m/s, aporosity of 0.4, and an effective diffusion coefficient of 10–10 m2/s. Assumingnegligible mechanical dispersion gives a Pe number of 25Δh, where Δh is thehydraulic head difference across the barrier. The impact of Δh on flux is plottedin Figure 2.8 for three different values of the dimensionless decay constant. Theresults for zero hydraulic head gradient correspond to diffusive transport withvarying rates of decay. The figure illustrates the significance of advection anddecay on contaminant flux rates.

F v C DC

xs= −∂∂

⎛

⎝⎜⎞

⎠⎟θ

FFL

DCPeC

C

x* *

**

= = −∂∂θ 0

F

PePe

Pe

*

*

*

exp

sinh=

⎛

⎝⎜⎞

⎠⎟+

+( )2

4

2 4 2

2

2

Λ

Λ

FPe

Pe*

exp( )=

− −1


In the case of a decaying contaminant source (i.e., a finite source), designshould be based on a transient analysis. In many cases, the rate of increase offlux with time or the time to reach some critical concentration at the barrier-aquifer interface can be estimated, necessitating the use of a transient solution.A variety of solutions have been used for transient analysis of barriers. Many ofthese (Shackelford, 1989, 1990; Acar and Haider, 1990) are based on the OgataBanks solutions for transient, one-dimensional contaminant transport with type-one entrance boundary conditions, and type-one semi-infinite boundary conditions.Rabideau and Khandelwal (1998a) give transient solutions for the combinationof type-one entrance boundary condition and perfect flushing exit boundarycondition, as well as a variety of other boundary conditions. The combination ofa first-type entrance condition and flushing exit condition again resulted in themost conservative mass flux estimates at the exit end of the barrier. In comparison,estimated flux rates from a model based on a third-type entrance boundarycondition and a zero-gradient exit boundary condition were about a factor of 20lower.

When the impact of groundwater flow below a horizontal barrier or parallelto a vertical barrier is important, and the perfect flushing boundary condition isdeemed to be too conservative, models that simulate the aquifer adjacent to thebarrier (Figure 2.7) as a mixing zone can be used. Rowe and Booker (1985a)applied Equation (2.10) with a finite mass entrance condition to one-dimensionaltransport across the barrier layer. They assumed a completely mixed aquifer withknown depth and seepage velocity below the barrier and developed a Laplacetransform solution that was inverted using a numerical Laplace inversion routine.Manassero and Shackelford (1994) presented a steady-state solution for a similarconceptual model, but with a constant concentration entrance condition. Rabideauand Khandelwal (1998a) developed a transient model (with numerical Laplace

FIGURE 2.8 Steady-state flux across a barrier as a function of hydraulic head gradient.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10Hydraulic Head Gradient

Dim

ensio

nles

s Flu

x, F

*

No decayDecay constant = 5Decay constant = 10


transform inversion) similar to that of Rowe and Booker (1985a), and showedthat a range of mixing zone flow rates spanned behavior from the perfect flushingcondition to that of a semi-infinite boundary condition. Because transverse verticaldispersion coefficients can be quite small (on the order of molecular diffusion),definition of an appropriate mixing zone for use of one-dimensional solutions isan open question.

In the case where greater accuracy in predicting contaminant transportthrough barriers is desired, multi-dimensional models should be used. In thiscase, Rowe and Booker (1985b, 1986) developed Laplace transform solutions fortransport through a variety of barrier–aquifer configurations, including a systemwith four layers in descending order consisting of a clay layer, a sand layer, asecond clay layer, and a lower sand layer. However, as with the one-dimensionalanalytical and quasi-analytical models, transport in the sand layers was assumedto be one-dimensional and fully mixed vertically.

In many cases, horizontal and vertical barriers can include geomembranes.Inorganic contaminants have negligible diffusion rates through intact geomem-branes, while organic compounds diffuse readily through geomembranes (Fooseet al., 2001). Foose et al. (2001) developed simplified analytical solutions forsolute transport through composite liners incorporating a geomembrane and asoil layer. Modeling the transport of contaminants through CSWs that containgeomembranes is, however, complicated by the possibility of defects in thegeomembranes, particularly at joints. Estimating contaminant flux rates throughpoorly characterized defects in geomembranes is difficult, but necessary for arealistic prediction of contaminant flux rates into the environment. Foose et al.(2002) evaluated the impact of geomembrane defects on contaminant transportusing a finite difference numerical model and demonstrated the importance ofdefective joints on transport through composite geosynthetic clay liners.

2.4.5 MODELING LIMITATIONS AND RESEARCH NEEDS OF WALLS AND FLOORS

Limitations to modeling barrier performance include difficulties in determininginput parameters, dealing with measurement accuracy and uncertainty, and time-varying properties. Models are also limited with respect to their ability to simulatecoupled solute transport and membrane effects in clay soils.

2.4.5.1 Input Parameters and Measurement Accuracy

Given the importance of a reliable risk analysis and of correct barrier modeling,the importance of a reliable assessment of input parameters is apparent. In fact,sufficient attention is not always given to the evaluation of these parameters,particularly to low permeability materials. The accuracy of tests for low perme-ability materials and the appropriate interpretation procedures after tests arecomplete are fundamental in order to obtain reliable results.


As in the case of compacted clay soils, the basic parameters of CB and SBmixtures for slurry cutoff walls (SCOWs) refer to (1) hydraulic conductivity,(2) sorption and diffusion, and (3) compatibility. The main factors influencingthe hydraulic conductivity of CB mixtures are the solids content, curing time,confinement stress, and stress–strain behavior. For the common basic composi-tions of CB mixtures, the hydraulic conductivity can vary from 10–8 to 10–9 m/s(one order of magnitude change). The use of additives can lower these values byanother order of magnitude (De Paoli et al., 1991).

The confinement stress history is an important factor that influences thehydraulic conductivity of CB mixtures (Manassero et al., 1995). The confinementstress in reducing hydraulic conductivity is more effective if applied at short curingtimes, although after 50 days it is also possible to observe hydraulic conductivityreduction due to an increase of confinement effective pressure. For confiningstresses ranging from 0.1 to 10 MPa applied on 28 days cured samples, thehydraulic conductivity varies between 5 × 10–8 m/s to 5. × 10–10 m/s (Manasseroet al., 1995).

Stress–strain behavior can influence the in situ hydraulic conductivity ofSCOWs due to the possible stress and strain induced by surrounding groundmovements. The level of confinement stress can determine different kinds ofmixture behavior under deviatoric stress as observed by Manassero et al. (1995).The different kinds of mixture behavior are brittle-softening, brittle-hardening,ductile-softening, and ductile-hardening. The latter is the most favorable to keephydraulic conductivity low. On the basis of preliminary experimental results(Manassero et al., 1995) and to obtain satisfying stress–strain behavior, theminimum effective confinement stress provided to the CSW CB backfilling mix-ture should be higher than 0.8 qu with qu being the unconfined compressivestrength of the CB mixture.

Some information on physico-chemical interactions between CB mixtures andchemical compounds to be contained by a SCOW can be found in Ziegler et al.(1993), Gouvenot and Bouchelaghem (1993), Finsterwalder and Spirres (1990),Muller-Kirchenbauer et al. (1991), Jessberger (1994), and Mitchell et al. (1996).The diffusion parameters are fully comparable with the same parameters fromcompacted clay liners (CCLs) (on the order of 10–10 m2/s) even though the totalporosity of typical CB mixtures can be 2 to 10 times greater. From preliminaryexperimental results, the sorption capacity of CB mixtures seems to be rathereffective for some organic pollutants and for anions in solution (Fratalocchi etal., 1996). This is probably due to the alkaline environment in the pore space.However, further validation of these results is necessary.

As far as compatibility problems are concerned, the cement seems to play afundamental role because the basic role of the bentonite (i.e., to stabilize thecement suspension) is fully completed during the first curing phase. Observationsafter curing with a scanning electronic microscope have shown that the bentonitegrains are fully wrapped by hydrated cement that carries out the role of the solidstructure of the cured mixture. Both low hydraulic conductivity and high confiningstress tend to reduce the sensitivity of the mixtures to chemical attack, at least


in the short term. Jefferis (1992) and Tedd et al. (1993) showed that only strongacids and/or sulfates could cause problems for the CB mixtures in the long term.As far as the laboratory tests for compatibility assessment problems are concerned,further information is provided in Manassero et al. (1995). In terms of furtherdevelopment, more research is needed to evaluate the temperature effects anddesiccation problems, which can be particularly serious for SCOW mixtures.

The hydraulic conductivity of SB slurry trench cutoff walls can be less than10–9 m/s. The stress state in the SB backfill can have a strong influence on in-service hydraulic conductivity. Also, contaminated permeants can increase thehydraulic conductivity of barrier soil, but the effect is less significant when thesoil is under high confining pressure.

To measure the hydraulic conductivity, it is possible to perform laboratoryor in situ tests. The main difficulty in performing the laboratory tests is to obtainundisturbed samples. In fact, to bore into the wall after construction is difficultdue to the soft consistency of the backfill.

Large-scale pumping tests can be difficult to interpret due to the impact ofgravity drainage from porous soils as the groundwater level is lowered within thecontained area and the possibility of leakage through an underlying aquitard.

2.4.5.2 Time-Varying Properties and Processes

Properties of barrier materials often change in time as barrier materials age. Acomprehensive experimental study on the curing time effect and solids contentof CB mixtures was carried out by Fratalocchi (1996). The decrease in thehydraulic conductivity vs. time was fitted by an exponential equation of the type:

(2.29)

where K and Kr are the hydraulic conductivities at time, t and tr, respectively,and the exponent, α is the coefficient of reduction of the hydraulic conductivityin time. The α parameter for the best fitting functions has also been related tothe cement to water ratio. For other types of cement and/or bentonite, an inde-pendent determination of α is recommended (Manassero, 1996).

The reduction of SB SCOW hydraulic conductivity vs. time is generallyquicker than for CB mixtures. Due to the short drainage paths, most of theconsolidation process of an SB mixture occurs in a few months and, after thisperiod, the hydraulic conductivity reduction is negligible. On the other hand, anincrease of hydraulic conductivity in the long term can occur using compatibilityproblems with the pollutants to be contained.

2.4.5.3 Influence of Coupled Solute Transport

Vertical cutoff walls typically are designed to prevent or minimize the spread ofa miscible contaminant plume in a groundwater aquifer as shown schematically

K Kt

trr

=⎛

⎝⎜⎞

⎠⎟

−α


in Figure 2.7. In the absence of pumping, a hydraulic gradient is establishedacross the wall such that advective contaminant flux, Ja, typically occurs in thesame direction as the diffusive flux, Jd (i.e., positive advection) (Figure 2.7a). Asa result, breakthrough of the contaminant plume through the wall cannot beprevented without active pumping within the contaminant source area to reversethe hydraulic gradient such that the advective flux occurs opposite to the directionof diffusion (i.e., negative advection) (Figure 2.7b). In this case, contaminantbreakthrough can be prevented if the diffusive flux is greater than the opposingadvective flux.

If the soil within the wall exhibits membrane behavior (i.e., ω > 0), chemico-osmotic flux of liquid from low concentration to high concentration (i.e., fromthe receptor side to the source side of the wall) results in a counter-advectivecontaminant flux, Jπ, that opposes Jd regardless of the direction of the hydraulicgradient. The advective contaminant flux in response to the hydraulic gradient isreduced by the factor (1 – ω) due to hyper-filtration, as explained previously.Thus, membrane behavior within the cutoff wall provides additional protectionagainst contaminant breakthrough and can reduce the need for pump and treat toestablish a counter-advective hydraulic gradient. The coupled solute flux equation(Equation (2.22)) indicates that the significance of the potential benefit of mem-brane behavior depends on the magnitude of the chemico-osmotic efficiencycoefficient, ω, for the soil.

2.4.5.4 Membrane Behavior in Clay Soils

Membrane effects (e.g., hyper-filtration, chemico-osmosis) are attributed to elec-trostatic repulsion of charged solutes (ions) by the diffuse double layers ofadjacent clay particles that extend into the pore space (e.g., Hanshaw and Coplen,1973; Marine and Fritz, 1981; Fritz and Marine, 1983; Fritz, 1986; Keijzer et al.,1997). As stated previously, a soil membrane that completely restricts the trans-port of ions and, thus, exhibits a chemico-osmotic efficiency coefficient equal tounity (i.e., ω = 1) is considered an ideal membrane. In this case, the diffusivedouble layers of adjacent particles overlap in the pore space, leaving no free spacefor solute transport. However, values of ω for clay membranes typically fall withinthe range 0 < ω < 1 because the pores vary over a range of sizes relative to thethickness of the diffuse double layers such that not all of the pores are restrictive(Kemper and Rollins, 1966; Olsen, 1969; Bresler, 1973; Barbour, 1986; Barbourand Fredlund, 1989; Mitchell, 1993; Keijzer et al., 1997). Thus, the degree ofsolute restriction and the resulting value of ω is affected by a combination ofphysical and chemical factors, including the state of stress on the soil, the typesand amounts of clay minerals in the soil, and the types and concentrations of thesolutes (Kemper and Rollins, 1966; Bresler, 1973; Olsen et al., 1990; Mitchell,1993). In general, ω increases with an increase in stress (lower porosity), anincrease in the amount of high activity clay minerals, and a decrease in the valenceand concentration of the solute.


For example, consider the effects of salt concentration and ion valence illus-trated in Figure 2.9 (also see Kemper and Rollins, 1966). The results in Figure2.9 pertain to recent tests performed at Colorado State University on bentonite-based geosynthetic clay liner (GCL) specimens using potassium chloride solu-tions, as described by Malusis et al. (2001) and Malusis and Shackelford(2002a,c). The results illustrate that ω can vary over almost the entire range of0 < ω < 1. For a given porosity (n), values of ω increase with an increase in theaverage salt concentration across the soil and a decrease in valence (Ca2+ vs. Na+

or K+). Both of these trends are consistent with expected behavior, in that thethickness of the diffuse double layers of adjacent clay particles within the soilpores decreases as the ion concentration and cation valence in the pore waterincreases (e.g., Mitchell, 1993).

The results in Figure 2.9 suggest that membrane behavior can be significantin clay soils containing an appreciable amount of sodium bentonite. Sodiumbentonite often is the principal clay mineral in soil-based vertical cutoff walls forwaste containment due to the low hydraulic conductivity (e.g., ≤ 10–7 cm/s)typically required in these applications. Thus, consideration of membrane effects

FIGURE 2.9 Chemico-osmotic efficiency. (From Malusis, M.A. and Shackelford, C.D.,2002b. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 128(2),97–106. With permission.)

0.0

0.1

0.2

0.2

0.3

0.4

0.5

0.5

0.6

0.7

0.8

0.8

0.9

1.0

0.0001 0.001 0.01 0.1 1

n = 0.74

n = 0.78–0.80

n = 0.86

n = 0.80

n = 0.84

n = 0.91

n = 0.84

n = 0.84

Average Salt Concentration (M)

CsCl

NaCl

Closed Symbols: Malusis and Shackelford (2002 b)

Open Symbols: Kemper and Rollins (1966)

Crossed Symbols: Kemper and Quirk (1972)

KCl

NaCl

Chem

ico-

Osm

otic

Effi

cien

cy C

oeffi

cien

t, ω


may be warranted in predictive assessments of the waste containment perfor-mance of cutoff walls.

2.5 COMPLICATING FACTORS

Several factors can complicate the rather simplified modeling approach describedthus far. A brief discussion of some of these factors is provided here to indicatea sense of the potential problems associated with contaminant transport modelingin environmental geotechnics.

2.5.1 CONSTANT SEEPAGE VELOCITY ASSUMPTION

Shackelford (1997) has observed that a potentially significant limitation in theanalytical modeling approach for modeling contaminant migration using modelsbased on the ADRE is the assumption of a constant seepage velocity. The assump-tion of steady-state flow is unrealistic, particularly in relatively short-term situations.

A simplified analysis of the accuracy of the constant seepage velocity assump-tion for flow through a compacted clay liner was presented by Shackelford (1997).While admittedly limited in application, this analysis indicates that the constantseepage velocity assumption can lead to potentially unconservative results in thatthe depth of penetration of the contaminant front is underestimated in the shortterm. Thus, care should be exercised when using models based on solution to theADRE for modeling scenarios that do not maintain a constant seepage velocity.

2.5.2 CONSTANT VOLUMETRIC WATER CONTENT ASSUMPTION

Thus far, conditions in which the volumetric water content, θ, is constant (i.e.,θ ≠ f (t)) have been assumed. However, complications arise in the formulationwhen the conditions initially are unsaturated and θ is not maintained constant[i.e., θ = f (t)], as in the case of transient infiltration processes. In these cases,the time-dependent change in θ affects the magnitude of the seepage velocity[i.e., v = f (θ)] and the dispersion coefficient [i.e., D = f (θ)].

A number of investigators have studied diffusive transport through unsatur-ated soils, including sandy clay loam (Rowell et al., 1967), clay and loam (Porteret al., 1960), silt (Rowe and Badv, 1996a), sand (Lim et al., 1994; Rowe and Badv,1996b), and gravel (Conca and Wright, 1990; Rowe and Badv, 1996b; andBadv and Rowe, 1996). The diffusion coefficient for chloride has been shown todecrease with decreasing θ. In addition, Rowe and Badv (1996b) found that thefollowing relationship could be used to estimate the effective diffusion coefficientin unsaturated soil, Dθ

*.

(2.30)Dn

Dθθ θ

θ* min

min

*=−−

⎛

⎝⎜⎞

⎠⎟


where θmin = minimum volumetric water content at which there is no intercon-nected water through which diffusion can occur. For some soils, Rowe and Badv(1996b) found that θmin ≈ 0 such that Equation (2.30) reduces to:

(2.31)

Rowe and Badv (1996b) also experimentally and theoretically examinedadvective-diffusive transport through layered systems consisting of a near-satu-rated lower permanent liner over an unsaturated layer (including silt, fine sand,fine gravel, and 38-millimeter stone) and demonstrated that conventional theory(e.g., Rowe and Booker, 1987, 1994) could be used to obtain good predictionsof contaminant transport provided that allowance was made for the effect of θon D* through Equation (2.30). For low degrees of saturation, such as for stone,dispersion was found to be significant in the unsaturated zone for q ≥ 0.12 m/year,whereas diffusion was important for q = 0.017 m/year.

The modeling formulation presented thus far includes only liquid-solid par-titioning. The transport of volatile organic compounds (VOCs) also can lead togas-liquid partitioning. Gas-phase diffusion coefficients of VOCs typically are 104

to 105 times higher than the corresponding liquid-phase diffusion coefficients. Adetailed description of the influence of variably saturated conditions is beyondthe scope of this chapter; a comprehensive presentation on the subject is providedby Charbeneau and Daniel (1993).

2.5.3 ANION EXCLUSION AND EFFECTIVE POROSITY

In some clay soils, anion exclusion or negative adsorption results from the repul-sion of anions from the negatively charged surfaces of clay particles (e.g., Bohnet al., 1985). The exclusion of anions from the pores of clay soils during transportcontributes to an effective porosity effect in terms of anion migration. That is,not all of the pore space is available for contaminant migration. In such cases,the effective porosity effect is indicated by values of Rd < 1 for nonreactive tracers,typically anions, where the actual value for Rd equals the effective porosity ratio,ne /n, where ne is the effective porosity and n is the total porosity (Shackelford,1995a,b; Shackelford et al., 1997a,b). For example, Wierenga and van Genuchten(1989) attributed Rd values for Cl– of 0.78 to an effective porosity effect due toanion exclusion.

2.5.4 NONLINEAR SORPTION

In formulating the adsorption process, linear sorption was assumed. However, inmany practical applications, the contaminant concentrations are sufficiently highsuch that nonlinear adsorption isotherms result. In such cases, the partitioningbetween liquid and solid phases is a function of the pore water concentration. In

Dn

Dθθ* *=


the case of nonlinear adsorption, the standard form of the ADRE (Equation (2.10))is not strictly applicable, and more complex numerical procedures are required.

Approximate methods for utilizing analytical models with nonlinear adsorp-tion isotherms are given by Shackelford (1993) for column tests and by Manasseroet al. (1997) for diffusion tests. These approximate methods simplify the analysesconsiderably and tend to provide reasonably good indications of the extent ofcontaminant migration, particularly for cases where the advective flow rates arelow. However, the approximate methods can result in significant errors in esti-mating the distribution of contaminants.

2.5.5 RATE-DEPENDENT SORPTION

The local equilibrium assumption (LEA) for adsorption in the formulation of theretardation factor generally is valid when the reaction time between the adsorbate(contaminant) and the adsorbent (soil) is fast relative to the flow rate of the porewater. Khandelwal et al. (1998) examined the transport of organic solutes throughSB barrier materials and concluded that deviations from local equilibrium werenot likely significant. However, for relatively high flow rates that typically occurin coarse-grained systems such as aquifers, the LEA may not be strictly valid. Insuch cases, kinetic or rate-dependent (nonequilibrium) adsorption reactions maybe required. In general, incorporation of kinetic or rate-dependent reactions inthe governing transport equations requires a numerical solution, although thesemi-analytical finite-layer technique recently developed by Rabideau and Khan-delwal (1998b) may be used in some cases.

The existence of a rate-dependent adsorption process tends to result in lessadsorption than would be predicted based on the LEA. Thus, failure to recognizethe existence of rate-dependent adsorption can result in an underestimation ofthe actual extent of contaminant migration.

2.5.6 ANION EXCHANGE

Some soils possess the ability to adsorb anions as well as cations. In fact, anionexchange capacities (AEC) have been reported for some clay minerals as shownin Table 2.5. Thus, the common assumption that anions, such as Cl– and Br–, arenonreactive (i.e., Rd = 1) during transport may not be appropriate in all soils,particularly soils that contain appreciable amounts of the clay minerals withAEC > 0 as shown in Table 2.5. Measured adsorption of anions, principally Cl–

and Br–, has been reported recently on the basis of both laboratory studies(Shackelford and Redmond, 1995; Alshawabkeh and Acar, 1996) and field studies(Seaman et al., 1995).

Anion adsorption generally is attributed to a pH-dependent surface chargeassociated with exposed hydroxyls on the edges of clay minerals (layered sili-cates) and/or metal hydroxides (e.g., Fe2O3). In general, the exposed hydroxylscarry either a partial positive charge (–OHδ+) at low pH or a partial negativecharge (–OHδ–) at high pH that results in the ability to adsorb either anions or


cations, respectively. The partial charges on the exposed hydroxyls result fromincomplete charge balance with the interior structure of the mineral. The pH atwhich the net anion adsorption capacity equals the net cation adsorption capacityis referred to as the zero point of charge (ZPC) or the point of zero charge (PZC).Thus, anion adsorption is favored for pH < ZPC, whereas cation adsorption isfavored for pH > ZPC. However, as indicated by Shackelford and Redmond(1995), simultaneous adsorption of both anions and cations probably occursduring solute transport in soils that exhibit a pH-dependent surface charge.

2.5.7 COMPLEXATION

Analyses performed using models based on the ADRE typically neglect thepotential effects of complexation. For example, when a metal, M2+, is dissolvedin water, the metal may exist in several different forms or complexes, such asfree metal species, M2+, or as metal hydroxides such as MOH+ and M(OH)2.These three different complexes migrate at different rates due to the differencein charges and sizes associated with each species. For example, adsorption ofthese three species based on consideration of charge is expected to be favored inthe following order: M2+ > MOH+ > M(OH)2. However, in most simplifiedmodeling applications, the potential transport of complexed species is simplyignored and the transport is assumed to be associated with the principal free ionicform of the species (i.e., M2+). Thus, it is important to note that an evaluation ofthe contaminant transport of a given species may actually encompass the transportof several different complexed species that do not migrate at the same rate.

2.5.8 ORGANIC CONTAMINANT BIODEGRADATION

Certain organic contaminants can diffuse readily through both geomembranes(e.g., Britton et al., 1988; Saleem et al., 1989; Park and Nibras, 1993; Park et al.,1995; Rowe et al., 1995, 1996a) and clay (e.g., Rowe et al., 1995, 1997). Con-sideration of biodegradation is important for modeling the potential impact ofthese contaminants. Studies of biodegradation of VOCs in leachate are limited.

TABLE 2.5The Cation and Anion Exchange Capacities of Common Soil Minerals and Organic Matter

Soil Component CEC (cmol/kg) AEC (cmol/kg)

Illite (2:1) 10–40 1Smectite (2:1) 90–120 1Vermiculite (2:1) 100–150 1Kaolinite (1:1) 3–15 3–5Oxides/Hydroxides Below 5 5Organic matter 200–400 0


However, Rowe (1995) and Rowe et al. (1996b, 1997) showed that there can besubstantial degradation both within the landfill and in the soil. The rate of deg-radation can have a profound effect on the suitability of different liner systems(Rowe et al., 1996a).

2.5.9 TEMPERATURE EFFECTS

Although most of the transport parameters are functions of temperature, and asignificant amount of study has been devoted to freeze-thaw effects on the hydraulicconductivity of fine-grained soils, temperature effects generally are ignored inmodeling simulations that cover long-term effects. However, in some applications,temperature effects may not be negligible. For example, the large temperaturegradients typically found between landfills (approximately 60°C) and the sur-rounding soil (approximately 20°C) may require incorporation of heat transportto provide accurate predictions of mass transport. Therefore, the potential effectsof temperature should be recognized when extrapolating results over extendedperiods that involve significant temperature fluctuations.

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van Genuchten, M.Th. and Alves, W.J. (1982). Analytical solutions for the one-dimensionalconvective-dispersive solute transport equation. Technical Bulletin No. 1661,USDA, Washington, DC.

Vogan, J.L., Focht, R.M., Clark, D.K. and Graham, S.L. (1999). Performance evaluationof a permeable reactive barrier for remediation of dissolved chlorinated solventsin groundwater. Journal of Hazardous Materials, 68, 97–108.

Wierenga, P.J. and van Genuchten, M.Th. (1989). Solute transport through small and largeunsaturated soil columns. Ground Water, 27(1), 35–42.

Wilson, G.W. (1990). Soil evaporative fluxes for geotechnical engineering problems. Ph.DThesis, University of Saskatchewan, Saskatoon, Canada.

Wilson, G.W. (2002). Can apples be compared to cover systems. Waste Geotechnics, March.Wilson, G.W., Fredlund, D.G. and Barbour, S.L. (1994). Coupled soil-atmosphere mod-

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Yabusaki, S., Cantrell, K., Sass, B. and Steefel, C. (2001) Multicomponent reactive trans-port in an in situ zero-valent iron cell. Environmental Science and Technology,35, 1493–1503.

Yeung, A.T. (1990). Coupled flow equations for water, electricity and ionic contaminantsthrough clayey soils under hydraulic, electrical, and chemical gradients. Journalof Non-Equilibrium Thermodynamics, 15, 247–267.

Yeung, A.T. and Mitchell, J.K. (1993). Coupled fluid, electrical, and chemical flows insoil. Geotechnique, 43(1), 121–134.

Zhu, C. and Anderson, G. (2002) Environmental Applications of Geochemical Modeling,Cambridge University Press, Cambridge.

Ziegler, C., Pregl, O. and Lechner, P. (1993). Pollutant transport through sealing mediumin contaminated land and sanitary landfills. Proceedings of the 4th InternationalLandfill Symposium, Sardinia ’93, Vol. 2, S. Margherita di Pula, EnvironmentalSanitary Engineering Centre (CISA), Cagliari, Italy, pp. 1599–1612.

Zyvoloski, G.A., Robinson, B.A., Dash, Z.V. and Trease, L.L. (1997). Summary of Modelsand Methods for the FEHM Application — A Finite Element Heat- and Mass-Transfer Code, LA-13307-MS. Los Alamos National Laboratory, Los Alamos, NM.

143

3 Material Stability and Applications

Prepared by*

Craig H. BensonUniversity of Wisconsin at Madison, Madison, Wisconsin

Stephan F. DwyerSandia National Laboratories, Albuquerque, New Mexico

3.1 OVERVIEW

This chapter focuses on material properties and behavior for caps, cutoff walls,and permeable reactive barriers (PRBs), with an emphasis on understanding themechanisms and factors that affect their durability in full-scale systems. Infor-mation obtained from laboratory tests are analyzed in this context. The reader isreferred to the preceding book in the containment series, Assessment of BarrierContainment Technologies (Rumer and Mitchell, 1995), as well as Daniel (1993),Gavaskar et al. (1998), LaGrega et al. (2000), Blowes et al. (2000), Naftz et al.(2002), and Reddi and Inyang (2000) for detailed information on the generalcharacteristics of barrier materials mix design approaches and performance issues.In this chapter, the emphasis is on fundamental factors and laboratory and fieldobservations that relate to the long-term performance of materials used in con-structing various types of containment systems. The overall performance of thesesystems has been analyzed holistically using the systems approach in Chapter 1.Chapter 2 dealt with models of water and contaminant fate and transport throughcomponents of containment systems. It is herein recognized that material properties

* With contributions by David W. Blowes, University of Waterloo, Waterloo, Ontario, Canada; DavidA. Carson, U.S. Environmental Protection Agency, Nashville, Tennessee; Peter W. Deming, MueserRutledge Consulting Engineers, New York, New York; Jeffrey C. Evans, Bucknell University, Lewis-burg, Pennsylvania; Glendon W. Gee, Battelle Pacific Northwest National Laboratory, Richland,Washington; Hilary I. Inyang, University of North Carolina at Charlotte, Charlotte, North Carolina;Stephan A. Jefferis, University of Surrey, Surrey, United Kingdom; Mark R. Matsumoto, Universityof California at Riverside, California; Gustavo Borel Menezes, University of North Carolina atCharlotte, Charlotte, North Carolina; Stanley J. Morrison, Environmental Services Laboratory, GrandJunction, Colorado; Scott D. Warner, Geomatrix Consultants, Oakland, California; John A. Wilkens,DuPont, Wilmington, Delaware

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play a significant role in overall system performance. This chapter is divided intothree primary subsections, each of which addresses materials performance for aspecific type of containment structure.

3.1.1 THE ROLE OF BARRIER MATERIAL MINERALOGY AND MIX COMPOSITION ON PERFORMANCE

Earthen materials or geomaterials are the most frequently used materials incontainment system barrier construction. Generally, barrier mixes are compositesof particles of various sizes and minerologies. For barriers that are designed tominimize flow rates and retard contaminant solute transport through physico-chemical interactions, clays are commonly used in mixes with silts; sands; andamendments such as resins, activated carbon, slags, polymers, and ash. The claysare usually alumino-silicates native to the barrier material, or they may be addedto the barrier mix in cases where the natural clay content of the barrier materialis insufficient to provide the required mix characteristics. In other cases, barriermaterials are fabricated and used to provide specific functions. An example is ageomembrane that can be incorporated as a component into a containment structurefor fluid retention, separation of clay to minimize the chance of attack by aggres-sive permeants, and diversion of gas flow to desirable control points. Table 3.1provides a general listing of various characteristics of barriers that affect classesof phenomena that relate to the most significant barrier design objectives. Some of

TABLE 3.1Containment System Design Considerations and Material Characteristics that are Usually Evaluated in Bench-Scale Tests

Physico-Chemical Design Consideration Phenomena of Concern

Significant Barrier Material Properties

Reduction of contaminant release and transport

Advection Hydraulic conductivityDensityMoisture contentGradationPorosityCrack density

Diffusion PorosityDispersion TortuosityLeachability Crack density

Chemical compatibility Inadequate retardation DensityPhysical durability Chemical attack Mineralogy relative to

contaminant chemistry

Radiation transport Density, mass attenuation coefficient

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Material Stability and Applications 145

the barrier parameters such as hydraulic conductivity, porosity, and crack densityapply to compacted, cemented, and fabricated materials.

For granular barrier materials that may be compacted or cemented into barrierlayers, the component material mineralogy and specific surface area are keymaterial factors that, in combination with the emplacement density, control theinitial and long-term barrier material textures when exposed to physical stressesand chemical contact. Mineralogy controls the physico-chemical interactions(including the reactivity) of a barrier component with permeating fluids under agiven environmental condition. Under the most frequently encountered temper-ature, pressure, and pH–Eh conditions in the field, clays (comprising mostlyaluminosilicates) react with permeants much more aggressively than sands (com-prising mostly silica). Because of their mineralogy, the charged clay surfacespresent opportunities for the chemisorption of charged contaminants such asheavy metals as summarized by Inyang (1996) in Table 3.2.

For a barrier material that has favorable mineralogy (i.e., a mineralogy thatfavors its interaction with permeating fluids in reactions that remove soluteswithout degrading the barrier), the opportunity for its interaction with the per-meant is enhanced if its specific surface is high. The specific surface is the ratioof surface area to weight of a material, and it is inversely proportional to thegrain size of the material. For surface reactions like cation exchange and adsorp-tion that are prevalent in barriers, their role in increasing the contaminant distri-bution coefficients (i.e., cleaning the permeating fluid in terms of its entry vs.exit chemistries) increases as the specific surface of the component materialincreases, as reflected in results plotted by Milne-Home and Schwartz (1989)presented in Figure 3.1. Often, even when a specific barrier component exhibitsa desirable material characteristic, it may not be adequate with respect to anothercharacteristic. For example, a clay mineral such as sodium montmorillonite maybe sorptive enough for heavy metals but inadequate in terms of providing strengthagainst desiccation. Yet still, cost considerations usually preclude the use ofsingle-component barrier systems in waste containment. Essentially, most barriermaterials are composites, the proportions of which are designed to optimizeperformance characteristics at minimal cost. In the case illustrated in Figure 3.2,D’Appolonia (1980) evaluated the effects of fines (% minus #200 sieve) on thepermeability of soil-bentonite (SB) backfill candidate materials and found thatfor both plastic fines and nonplastic/low-plasticity fines, the permeabilitydecreased as the fines content increased. Permeability values for the plastic fineswere generally lower than those of the nonplastic/low-plasticity fines. Presumably,the plastic fines comprise more moisture-sensitive or expansive minerals than thenonplastic/low-plasticity fines. Figure 3.3 shows the effects of bentonite (mont-morillonite) content on the permeability of the SB backfill candidate materialmixes. A bentonite content of 3% (by dry weight) was adequate to reduce thepermeability values from 5 × 10–5 to 5 × 10–3 centimeters per second (cm/s) toabout 10–7 cm/s for well-graded coarse materials.

In another investigation that illustrates the optimization of mix compositionto obtain a favorable material characteristic, Ryan and Day (1986) evaluated the

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TABLE 3.2Sorption Characteristics of Soil Minerals and Chemical Additives for Hazardous and Radioactive Metals

Single Component

MaterialGeneral

PropertiesMetals Tested

Test Type

Test Conditions Results

Montmorillonite (Garcia-Miragaya and Page, 1976)

CEC = 94.8 meql/L; particle size <2 μm

Cd2+ Batch Initial pH range = 4.6–7.3

95%, 95%, and 90% of Cd2+ sorbed by Na-, Ca-, and K-montmorillonite, respectively

Montmorillonite from Texas (Puls and Bohn, 1988)

Ca — saturated

Cd2+, Zn2+, Ni2+

Batch Initial pH = 5.5, 6.5, 7.5

50% of metals were adsorbed at pH range of 4–5.81

Vermiculite (Ziper et al., 1988)

K — fixed, 500–1000 μm particle size, SSA = 22.5 m2/g

Cd2+ Batch Initial pH = 5.0, 10–9–10–5 M

0.9 moles of Cd2+ adsorbed per kg

Kaolinite (Puls and Bohn, 1988)

Fine particles Cd2+, Zn2+, Ni2+

Batch Initial pH = 5.5, 6.5, 7.5

Adsorption followed the order: Cd > Zn > Ni. 50% of metals were adsorbed within pH range 4.49–5.80

Kaolinite (Yong and Galvez-Cloutier, 1993)

LI = 61%, SSA = 24 m2/g; 84% below 2 μm

Pb2+ Batch Initial pH = 3.0. 4 g of Kaolinite in 40 mL of lead solutions

Maximum Pb2+ adsorption decreased at high pH due to precipitation

Goethite (iron oxide) (Coughlin and Stone, 1995)

SSA = 47.5 m2/g

Mn2+, Co2+, Ni2+, Cu2+, Pb2+

Batch Initial pH = 3–8. NaNO3 used to maintain selected ionic strength

Coordination chemistry of oxides affects adsorption. 50% of Cu2+, Pb2+, Co2+, Ni2+ removed at pH 4.5, 4.8, 6.3, 6.8, respectively

Goethite (iron oxide) (Kuo, 1996)

Zn2+, Cd2+, Ca2+

Batch Initial pH = 5.3–8.3. NaNO3 used to maintain selected ionic strength

Selectivity order: Zn2+ > Cd2+ > Ca2+

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permeability ranges of three mix compositions for a fly ash cement-slurry wall,the results of which are presented in Figure 3.4. Test results developed (Flemingand Inyang, 1995) for fly ash amended materials, which may, in some cases,exhibit cementation if the ash mineralogy is favorable or some cementing agentsare added, show that initial and longer term permeabilities of cemented barriermaterials can be significantly influenced by reactions among the mix components.Figure 3.5 shows the conceptual textural patterns proposed by Fleming and Inyang(1995) in a comparative study of the effects of class F (nonreactive) fly ash andclass C (reactive) fly ash amendment of barrier clay on changes in permeabilityunder freeze-thaw action. The patterns are similar, but the reactive fly ash exhibitsinitial and final permeabilities that are lower than those of the nonreactive ash.

3.1.2 APPROACHES TO MATERIAL EVALUATION AND SELECTION

Bench-scale tests provide the best opportunity to evaluate the fundamental char-acteristics of barrier materials. However, holistic assessments of a barrier systemperformance are most meaningfully performed through a combination of bench-scale testing and field quality assurance and monitoring tests. The bench-scaleapproach has been widely used to evaluate barrier material parameters in batch

TABLE 3.2 (continued)Sorption Characteristics of Soil Minerals and Chemical Additives for Hazardous and Radioactive Metals

Single Component

MaterialGeneral

PropertiesMetals Tested

Test Type

Test Conditions Results

Fly ash (Singer and Berkgaut, 1995)

Hydrothermally treated, CEC = 2.5–3 meq/g

Pb2+, Sr2+, Cu2+, Zn2+, Cd2+, Cs2+

Batch Initial pH = 5.0. Total concentration of competing ions = 0.1 N

Selectivity order: Pb2+ > Sr2+ > Cu2+ > Cd2+ > Zn2+ > Cs2+ at 25 mg/L lead concentration, absorbed Pb = 35 μg/g

Pyrolusite (MnO2) (Ajmal et al., 1995)

Crushed samples

Pb2+, Cd2+, Zn2+, Mg2+

Batch Washed and dried at 40°C; pH range of about 2–8

At pH = 6.5, 100% of initial 22.7 mg/L of Pb2+ was sorbed; other results show high sorption for Zn2+ and Cd2+ but low sorption for Mg2+

Source: Inyang, H.I. (1996). Sorption of inorganic chemical substances by geomaterials and additives,Report CEEST/001R-96, University of Massachusetts, Lowell, MA.

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systems, monoliths of scaled down dimensions, or columns of media. The lattercan be densely compacted, as in the case of earthen materials considered forfluid/contaminant transport barriers or loosely emplaced as in reactive columns.Most of the granular barrier material characteristics that are usually targeted aresummarized in Table 3.3. Not all of these tests need to be performed for all barriermaterials. Some tests, exemplified by porosimetry, are not usually performedbecause the influence of the pore size distribution measured is represented alongwith barrier material density and reactivity with specific contaminants in dataobtained from column tests for contaminant retardation coefficient estimation.The tests listed in Table 3.3 have designations that vary from one country toanother, although they are most standardized under the American Society for

FIGURE 3.1 Specific surface vs. bulk cation exchange capacity for various sedimentsand minerals. (From Milne-Home, W.A. and Schwartz, F.W., 1989. Proceedings of theConference on New Field Techniques for Quantifying the Physical and Chemical Proper-ties of Heterogeneous Aquifers, Dallas, Texas, pp. 77–98. With permission.)

Spec

ific s

urfa

ce (m

2 /g.)

1000

100

10

1

0.1 0.1 1

Bulk C.E.C. (meq/100 g)10 100

Montmorillonite

Illite

Kaolinite

ExplanationAmerican Petroleum InstituteReference clays (Patchett, 1975)Shales (Patchett, 1975)Milk River formationMome L’Enfer, Erin formationsBelly River formation (GENPAR 2)Sandstones

Discrete particle claysPore ilning claysPore bridging clays

1

123

1 1 1

1

2 2

2

2 2 3

3

3

3

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Testing Materials (ASTM) protocols. As evident in Section 3.2, fabricated mate-rials such as geomembranes are tested under protocols that are different fromthose of granular barrier materials. Fundamental tests are important because theycan provide data that are helpful in performing a general durability evaluation ofbarrier materials and understanding mechanisms that are determinants of theirdurability.

3.1.3 GEOSYNTHETICS AND THEIR DURABILITY IN BARRIER SYSTEMS

In general, the ability of barrier materials to retard fluid transport, resist chemicaland biological attack, and maintain structural integrity under externally imposedstresses depends on their composition, emplaced thickness, and the quality assur-ance practices implemented during construction. Early in the development ofcontainment system design configurations, earthen and cementitious barrier mate-rials were used almost exclusively. A more recent development, particularlywithin the past two decades, is an increase in the use of geosynthetic materialsto enhance containment system barrier layer performance. Both earthen andgeosynthetic barrier materials have advantages and disadvantages. Earthen bar-riers are most commonly clayey soils that are either compacted into layers as inlandfills and surface impoundments or emplaced as slurry backfill as in slurrycutoff walls. While they can retard contaminant transit through a variety ofprocesses (e.g., sorption, induced precipitation of dissolved substances withininter-particle pore spaces), significant variability and uncertainty can exist in the

FIGURE 3.2 Effects of fines content on the permeability of soil-bentonite backfill. (FromD’Appolonia, 1982. Proceedings of the 13th Annual Geotechnical Lecture Series, Phila-delphia Section, American Society of Civil Engineers, Philadelphia, PA. With permission.)

% M

inus

#20

0 sie

ve

80

70

60

50

40

30

20

10

0 10−4 10−5 10−6 10−7 10−8 10−9

Plastic fines

SB Backfill permeability, cm/sec

Nonplastic or lowplasticity fines

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spatial distribution of barrier transport parameters such as hydraulic conductivityand diffusion coefficient. Furthermore, under aggressive chemical environmentsand sustained desiccation processes, earthen barriers can develop enlarged flowchannels that allow contaminants in both the gaseous and liquid phases to travelthrough the barrier easily. Geosynthetic materials such as geomembranes have less

FIGURE 3.3 Effects of bentonite content on the permeability of SB backfill. (FromD’Appolonia, 1982. Proceedings of the 13th Annual Geotechnical Lecture Series, Phila-delphia Section, American Society of Civil Engineers, Philadelphia, PA. With permission.)

FIGURE 3.4 The effects of cement/water ratio and fly ash/cement ratio on the perme-abilities of slurry wall mixtures. (From Ryan, C.R. and Day, S.R., 1986. Proceedings ofthe 7th National Conference on Management of Uncontrolled Hazardous Waste Sites,Washington, DC. With permission.)

Perm

eabi

lity o

f SB

back

fill,

cm/s

ec.

10–2

10–3

10–4

10–5

10–6

10–7

10–8

10–9 0 1 2

% Bentonite by dry weight of SB backfill 3 4 5

Well-graded coarsegradations (30–70% + 20 sieve)w/10 to 25% nonplastic fines

Poorly graded silty sandw/30 to 50% nonplastic fines

Clayey silty sand w/30 to 50% fines

Mix 3

Mix 2

Mix 1

10–7 10–6

K, (cm/sec.)

C/W FA/CMix 1 0.20 0.00Mix 2 0.20 0.24Mix 3 0.25 0.60

10–5

Average(typ.)

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variability in the spatial distribution of transport parameter magnitudes becausethey are manufactured in tightly controlled processes. Furthermore, they are lesspermeable to fluids and offer the opportunity to minimize the overall designthickness of a barrier layer. On the other hand, punctures, poor joints, and internaldegradation can diminish their effectiveness as barrier layers. Giroud et al. (1992,1997) have developed quantitative methods for estimating liquid transport throughgeomembrane defects.

Geosynthetic barrier materials have been used as barrier layers that comple-ment the functions of earthen barrier layers. Many composite cover designs such

FIGURE 3.5 Effects of reactions among barrier constituents on the permeability of ash-modified clayey barrier soil subjected to freeze-thaw cycling. (From Fleming, L.N. andInyang, H.I., 1995. ASCE Journal of Materials in Civil Engineering, 7(3), 178–182. Withpermission.)

Before freezing

After freeze - thaw cycling

a. Class F fly ash-modified clay soil

c. Class F fly ash-modified clay soil

Perm

eabi

lity

b. Class C fly ash-modified clay soil

d. Class C fly ash-modified clay soil

Longitudinal fracture

Reactive ash particle Clay platelet

Reacted rim

Nonreactive ashparticle

PCA

POA PCB

0 tCB No. of freeze-thaw cycles or time

tCA

POB


as those consistent with the minimum design standards developed for theResource Conservation and Recovery Act (RCRA), comprise both soil barrierlayers and geosynthetic materials. Othman et al. (1997) have performed studiesof the performance of such barrier configurations in the field. The results indicatethat with adequate quality control, such systems can perform effectively, at leastwithin the few decades that they have been in service. Another composite barriersystem that typically produces desirably low hydraulic conductivities in barriersystems is the geosynthetic clay liner (GCL) that has been studied by manyresearchers (Estornell and Daniel, 1992; Rad et al., 1994; and Petrov et al., 1997).The GCL is gaining wider acceptance in the containment industry because of itscost effectiveness, relatively easy installation, and low barrier thickness. Instal-lation methods are summarized in Section 3.4.3.

Although test protocols, design methods, and quality assurance methods havebeen developed [Koerner and Daniel, 1997; Haxo, 1987; United States Environ-mental Protection Agency (USEPA), 1985], concerns about the long-term dura-bility of geosynthetic materials in barrier systems remain. This concern is drivenby the knowledge that all materials that are exposed to stressors degrade withtime. Such degradation in the long term is not limited to geosynthetic materials,but extends to emplaced earthen barrier materials as well. For geosynthetic

TABLE 3.3General Testing Approaches and Methods for Significant Characteristics of Batch and Compacted Barrier Materials

Dependent Property Test Method(s)

Soil TextureDensitya Direct measurementDispersivity Indeterminate; evaluate experimentallyGradation Sieve, hydrometer testsHydraulic conductivitya,b Permeameter testsMoisture content Drying testsPath length/tortuositya Indeterminate; evaluate experimentallyPlasticityb Atterberg limitsPore size distribution PorosimetryPorosity (effective)a Empirical methods, porosimetry

Soil CompositionChemical (elemental) composition Chemical tests (e.g., x-ray fluorescence)Mineralogy (crystallinity) Mineralogy tests (e.g., x-ray diffraction)

a Denotes a property dependent on compaction.b Denotes a property dependent on mineralogy.

Source: Adapted from Inyang, H.I. et al. (1998). Physico-Chemical Interactionsin Waste Containment Barriers, Encyclopedia of Environmental Analysis andRemediation, Vol. 2, Wiley, New York, pp. 1158–1165.

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materials that have been effectively installed, degradation mechanisms includeaging, chemical attack, and photo-oxidation. To assess the potential effectivenessof geosynthetic barriers in containment systems over 500 service time frames,Badu-Tweneboah et al. (1999) analyzed prospective effects of various degradationprocesses of a 1.5-millimeter (mm)-thick high-density polyethylene (HDPE)geomembrane that was installed within a landfill cover. They used data fromstudies performed on geomembranes and other polymeric materials to evaluatethe damage potential under sustained contact with aging agents such as oxygen,microorganisms, heat, ultraviolet radiation, and radioactivity, as well as flawdevelopment due to abrasion, thermal stresses, animal burrowing, and plant rootpenetration. The analysis led to the conclusion that up to 5% reduction in yieldstrain can occur per 25 years of service, resulting in an estimated yield strain ofzero if a liner deterioration pattern is assumed or 36% of the original yield strainin 500 years if a logarithmic deterioration pattern is assumed.

On the basis of their analysis, Badu-Tweneboah et al. (1999) estimated thatthe progressive stiffening of the geomembrane due to molecular rearrangementunder induced stresses in common containment system configurations wouldlikely result in stress cracking after 300 years of service. The challenge is torelate the damage potential to flaw sizes and numbers — a necessary step forestimating potential fluid transport rates through geosynthetic materials.

3.2 MATERIAL PERFORMANCE FACTORS IN CAPS

Caps or surface barriers in general are used to isolate buried wastes or contam-inated soils from the atmosphere and biota on the earth’s surface. To design aneffective cap, it is necessary to consider multiple objectives, including biotaintrusion (i.e., intrusion of plants, animals, and humans into the underlying wasteor contaminated soils), wind and water erosion, gas control, and percolation ofwater into underlying waste. The material performance criteria established foreach of these objectives depend on the type of waste to be contained and therisks imposed by the waste on the nearby environment. For example, stringentmix design criteria may need to be used for facilities containing long-lived andtoxic radioactive wastes, whereas less stringent criteria can be applied to facilitiescontaining largely inert construction and demolition wastes. The life span overwhich the cap must function is generally associated with the type of waste aswell (e.g., 1,000 years for radioactive wastes or 30 years for solid wastes). Inmost containment applications, however, there is no intent of ever exhuming thewaste. Thus, a cap must meet the performance criteria as long as the materialbeing contained poses a risk to the surrounding environment. In most cases, thismeans that caps need to be designed for perpetuity and that a plan be in place tomonitor and maintain the cap as needed.

Percolation from the base of the cap is the primary design criterion in mostcases. A capping approach that will meet a percolation criterion (e.g., <1 mm/year)is usually selected. Then, the materials and geometry (e.g., layering) are selectedand configured to meet the percolation criterion, as well as the other criteria

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(e.g., erosion, biota intrusion, gas control). Two general cap designs are used:resistive designs and water balance designs. Examples of resistive designs areshown in Figure 3.6; examples of water balance designs are shown in Figure 3.7.Resistive designs employ a barrier system with high hydraulic impedance to limitpercolation (Benson, 2001). The barrier system can consist of geomembranes,fine-grained earthen materials, asphalt layers, or combinations of these or similarmaterials. A drainage system is often used to limit the driving head on the barrierand ensure physical stability. The water balance approach employs the store andrelease principle to limit percolation to an acceptable amount (Benson, 2001).Materials are selected that have adequate capacity to store infiltrating water duringwet periods without appreciable percolation. Vegetation is used to remove thestored water and return it to the atmosphere so that the cover has the capacity tostore water during subsequent infiltration events.

The resistive and water balance design approaches are fundamentally different.The resistive design approach is predicated on constructing and maintaining asystem that blocks natural water movement. In contrast, the water balance approach

FIGURE 3.6 Profiles of caps relying on a resistive barrier: (a) Compacted clay barrierand (b) composite barrier.

Vegetated surface layer (150 mm)

Clay liner (>600 mm)

Clay liner (>600 mm)

(a)

(b)

Geomembrane Geocomposite drain



uses natural processes to limit natural water movement. The natural approach usedfor water balance covers is considered by some to be superior. The logic is thata system that works with nature (i.e., water balance cap) is believed to be lesslikely to fail over the long term than a system that works against nature(i.e., resistive cap). However, currently there is no direct evidence demonstratingthat one approach is superior, provided that the cap is designed and constructedproperly.

3.2.1 MATERIAL PERFORMANCE FACTORS IN COMPOSITE BARRIERS

Resistive designs generally employ engineered materials to provide the hydraulicimpedance needed to meet a percolation criterion. These materials include com-pacted natural clays, bentonites used alone in layers (e.g., as in a geosyntheticsclay liner) or mixed with other earthen materials (e.g., a compacted mixture ofsand and bentonite), polymeric sheets known as geomembranes, and asphalt andasphalt concrete layers (Koerner and Daniel, 1997). During the last decade, awealth of experience has accrued regarding the characteristics of these materialsand the elements that are required to reduce percolation to small amounts. Expe-rience has shown that systems that rely solely on an earthen barrier (i.e., compacted

FIGURE 3.7 Schematic water balance caps: (a) Monolithic cap design and (b) two-layercapillary barrier.

Finer-grained soil

Coarser-grained soil

Capillary break

(b)

Thick layer offiner-grained

soil

Waste

(a)


clay barrier or GCL) are prone to failure, even after short service lives, whereascomposite designs that combine a geomembrane underlain by an earthen barrierappear to function extremely well, at least for the relatively short experience record(<10 years) that currently exists (Benson, 2001, 2002). The performance of capsthat rely solely on a geomembrane or asphalt layer is largely unknown.

The following two examples illustrate how resistive designs that rely solelyon an earthen barrier can fail soon into their service lives. One is a cap employinga compacted clay barrier consisting of 460 mm of compacted clay placed oncompacted subgrade and overlain with 150 mm of topsoil vegetated with Bermudaand rye grasses. This type of cap is often the presumptive remedy (i.e., the defaultdesign) for sites in the United States Superfund program, as was the case for thecap described here. The other is a similar design, except a GCL was used insteadof a compacted clay barrier, and 600 mm of “protective cover soil” was placedbetween the GCL and the topsoil layer. The topsoil layer was vegetated withcrown vetch to minimize erosion.

The clay barrier was compacted in a manner that yielded a field hydraulicconductivity of 5 x 10–8 cm/s at the time of construction (the design criterion was10–7 cm/s). The cap was intended to transmit less than 30 mm/year of percolation.Concerns about long-term cap performance led to installation of a system formonitoring all components of the water balance (Benson, 2002; Roesler et al.,2002) and, most importantly, the percolation rate. Water balance data collectedfrom the cap since the time of construction are shown in Figure 3.8.

FIGURE 3.8 Water balance data for the clay cap.

0

500

1000

1500

2000

50

100

150

200

250

8/1/02

Surface runoff

Soil water storage

No rain

Drying soil

Wat

er ap

plie

d, e

vapo

tran

spira

tion,

su

rface

runo

ff, an

d pe

rcol

atio

n (m

m)

Soil-water storage (m

m)

Evapo-transpiration

Percolation

Applied water

4/1/00 8/1/00 12/1/00 4/1/01 8/1/01 12/1/01 4/1/02


Approximately 10 months after construction (September/October 2000), aperiod with little precipitation persisted for approximately six weeks. During thisperiod, the cap desiccated as evidenced by the monotonic decrease in soil-waterstorage during this period. Prior to this period, the cap transmitted percolation atrate of approximately 30 mm/year, which is consistent with the design criterion.Afterward, the percolation rate was approximately 500 mm/year (approximatelyone half of annual precipitation). Inspection of the clay barrier after it desiccatedshowed that the barrier contained desiccation cracks (Albright and Benson, 2002;Roesler et al., 2002) that served as preferential flow paths, causing the largepercolation rate increases that were measured and the stair-step character of thecumulative percolation record.

Concerns about the field performance of a cap that relies solely on a GCLalso led to percolation rate monitoring using two 10 m by 10 m lysimeters(Thorstad, 2002). The cumulative percolation recorded by the lysimeters is shownin Figure 3.9. Excessive percolation was first noticed during the spring thaws of1997. The GCL was exhumed in June 1997 and inspected to determine the causeof the excessive leakage rates. GCL thinning due to pressure applied by gravelin the lysimeter was the suspected cause of the high percolation rate, but noquantitative assessment of the failure mechanisms was made. A layer of sand wasadded to the lysimeter above the gravel as a cushion, a new GCL was installed,and the over-lying soil layers were replaced.

Percolation monitoring continued after the lysimeters were rebuilt in 1997.Approximately 15 months after reconstruction, the percolation rate became exces-sive again. Monitoring continued until October 1999, when one of the lysimeters(BL2) was exhumed to inspect the GCL. Monitoring of the other lysimeter (BL1)continued. Percolation recorded by lysimeter BL1 continued relatively steadilyand averaged 211 mm/year.

Inspection of the GCL exhumed from directly over lysimeter BL2 revealedthat the bentonite was dry and cracked. No thinning due to uneven pressure appliedby the underlying soil was observed. Hydraulic conductivity tests on samples ofthe GCL exhumed from inside and outside the lysimeter showed a saturatedhydraulic conductivity ranging between 1.4 × 10–6 cm/s and 1.0 × 10–4 cm/s oras much as 50,000 times the as-built hydraulic conductivity (2 × 10–9 cm/s).

Chemical analysis showed that the exchange complex of the bentonite wasdominated by calcium and magnesium, whereas sodium was originally the pre-dominant cation (Thorstad, 2002). The exchange of calcium and magnesium forsodium reduced the swell potential of the bentonite sufficiently so that cracksthat formed during drier periods could not swell shut during wetter periods. Asa result, the hydraulic conductivity of the GCL became unacceptably high.

When lysimeter BL2 was exhumed in October 1999, it was rebuilt using acomposite barrier consisting of a thin (0.5 mm) polyethylene geomembrane heatbonded to one side of the GCL. This barrier was installed with the geomembranedown, as recommended by the manufacturer. The overburden soils removed duringexhumation were replaced after the new GCL was installed. Very little percolationfrom the new GCL has been recorded during the two years of monitoring since


installation (2.4 mm/year on average), suggesting that the composite barrier isfar superior to the GCL alone.

Positive field performance of caps that employ a resistive design with acomposite barrier has been reported by others as well (Melchior, 1997; Dwyer,

FIGURE 3.9 Profile (a) and cumulative percolation record (b) for GCL cap.


Silty base layer (600 mm)

Protective layer (600 mm)

GCL

(a)

0

100

200

300

400

500

600

700

800

2000

Original BL1 Original BL2 Rebuild BL1 1st rebuild BL2 2nd rebuild BL2

Elapsed time (days)

1996

1997 1998

1strebuild

2ndrebuild

BL2

2001 2000

(b)

Cum

ulat

ive p

erco

latio

n (m

m)

1999

0 500 1000 1500


2001; Albright and Benson, 2002). Melchior (1997) reported percolation ratesbetween 0.8 and 3.0 mm/year for a cap in Germany employing composite barrierdesign. The barrier consisted of 600 mm of clay (saturated hydraulic conductivityless than 10–7 cm/s) overlain by a 1.5-mm-thick HDPE geomembrane, a sanddrainage layer 250 mm thick, and a vegetated topsoil layer 750 mm thick. Dwyer(2001) reported an annual percolation rate of 0.1 mm/year for a cap in semi-aridAlbuquerque, New Mexico, having a design similar to Melchior’s cap. Dwyer(2001) also reported a percolation rate of 1.8 mm/year for a similar cap inAlbuquerque employing a composite barrier with a GCL as the earthen component.

The USEPA’s Alternative Cover Assessment Program (ACAP) is also moni-toring the percolation rate from seven caps employing composite barrier layersconsisting of a geomembrane underlain by a GCL or compacted clay barrier(Albright and Benson, 2002; Roesler et al., 2002). Percolation rates from thesecaps are summarized in Table 3.4. The percolation rates generally are near zeroin semi-arid and arid climates, and less than 4 mm/year in humid climates. Thus,the composite barrier generally seems to be effective, largely because thegeomembrane is nearly impervious and the fine-grained soil beneath the geomem-brane provides impedance to flow at points where the geomembrane may containdefects.

The exception is the cap located in Monterey, California. This cap is located ina semi-arid environment, but is transmitting 18 mm/year of percolation (Table 3.4).The cover soil placed on the geomembrane for this cap consisted of soil from

TABLE 3.4Summary of Precipitation and Percolation Rates from Caps with Composite Barriers Monitored by ACAP

SiteDuration

(Days) Climate

Total Precipitation

(mm)Percolation (mm/year)

Altamont, CA 517 Arid 487 0.0 (0.0%)Apple Valley, CA 156 Arid 115 0.0 (0.0%)Marina, CA 684 Semi-arid 466 18.1 (3.9%)Boardman, OR 485 Semi-arid and seasonal 181 0.0 (0.0%)Polson, MT 847 Semi-arid and seasonal 744 0.2 (0.1%)Cedar Rapids, IA 381 Humid and seasonal 772 0.9 (0.1%)Omaha, NE 552 Humid and seasonal 719 3.7 (0.5%)

Percentage of precipitation in parentheses.

Source: Data from Albright, W. and Benson, C. (2002). Alternative Cover Assessment Program2002 Annual Report, Publication No. 41182, Desert Research Institute, Reno, NV; Roesler, A.et al. (2002). Field Hydrology and Model Predictions for Final Covers in the Alternative CoverAssessment Program — 2002, Geo-Engineering Report No. 02-08, University of Wisconsin,Madison, WI.


demolition projects and contained a variety of debris, including reinforcing barsand angular chunks of concrete. These materials may have caused puncturing ofthe geomembrane, which may be responsible for the higher percolation rates(Roesler et al., 2002). This example illustrates an important point: caps con-structed with suitable barrier materials can function poorly if other aspects of thedesign are not properly implemented.

Although the performance record for caps with composite resistive barriersis good, the record is short relative to the life span over which the caps areintended to function. Melchior’s study has the longest record (eight years).Dwyer’s record is four years, and the monitoring is continuing at ACAP sites. Ingeneral, composite barriers that have been exhumed appear to be in excellentcondition even after several years of service, including those barriers located inthe arid desert in southern California (Corser and Cranston, 1991; Melchior,1997). Additionally, several studies suggest that geomembranes should performadequately for hundreds of years, if not longer (Hsuan and Koerner, 1998; Clarke,2002; Rowe and Sargam, 2002). However, these predictions are primarily heu-ristic or based on ancillary measurements (e.g., depletion rate of anti-oxidants).The reality is that little hard data exist that can be used to make reliable predictionsregarding the life span of geomembranes in composite covers. Given the dearthof information on life expectancy, this is an area in need of research given thatcaps employing composite barriers are ubiquitous.

3.2.2 MATERIAL PERFORMANCE FACTORS IN WATER BALANCE DESIGNS

Water balance designs generally employ broadly graded finer-textured soilsbecause of their capacity to store significant amounts of water with little drainageand their ability to deform without cracking. Coarse-grained materials are alsoused to form capillary breaks that enhance storage in the finer layer or divertwater under unsaturated conditions. The coarse material can also be used toremove water from the barrier through advective drying (Albrecht and Benson,2002; Stormont et al., 1994). Caps that employ a single layer of fine-texturedsoil are generally referred to as monolithic barriers, whereas those with two ormore layers with contrasting particle size are referred to as capillary barriers(Figure 3.7).

The performance record for water balance designs generally is shorter thanthat associated with resistive designs, although a large effort has been underwayin North America during the last decade to collect field data on water balancecaps (Khire et al., 1997; Ward and Gee, 2000; Dwyer, 2001; Albright and Benson,2002). Perhaps the most notable monitoring program has been conducted at thesemi-arid Hanford site (south-central Washington) for a cap designed to limitpercolation to <0.5 mm/year. The cap is intended to have service life of 1000 yearswithout maintenance [United States Department of Energy (USDOE), 1999; Wardand Gee, 2000]. A full-scale test section of the cap was constructed in 1994 and


has been monitored under natural conditions and conditions that are extremelywet for the region.

Because a 1000-year life without maintenance was required, natural construc-tion materials that are known to have existed in place for thousands of years wereselected. The top-to-bottom profile consists of a 2-m-thick layer of vegetated silt-loam overlying layers of sand, gravel, basalt rock (riprap), and asphalt (Figure3.10). Each layer serves a distinct purpose. The silt-loam is for storing infiltration(600 mm of water can be stored in the silt loam before it will drain) and providesthe medium for establishing plants that are necessary for transpiration. The coarsermaterials placed directly below the fine soil layer create a capillary break thatenhances the storage capacity of the silt-loam. Placement of the silt-loam directlyover coarser materials also creates an environment that encourages plants andanimals to limit their natural biological activities to the near surface, therebyreducing biointrusion into the lower layers. The coarser materials also help deterinadvertent human intruders. The asphalt layer (asphalt concrete overlain by layerof fluid-applied asphalt) acts as a secondary barrier that employs a resistiveapproach to impede and divert water passing through the capillary break. A shruband grass cap was established on the cap in November 1994. Two sideslopeconfigurations, a clean fill gravel on a 10:1 slope and a basalt riprap on a 2:1slope, were also part of the overall design and testing.

FIGURE 3.10 Hanford cross section of Hanford cap showing (a) interactive water balanceprocesses, (b) gravel sideslope, and (c) basalt riprap sideslope.

Lateral drainge

Upper neutron probeaccess tube

Erosion- resistant

gravel admix

Runoff

Existing grade

(a)

(b)

1 10 1

50 1

2 1

50

Clean fill side slope (pit run gravel)

(c)

Basalt side slope

Verticaldrainage

Waste crib

Precipitation (P)

Evapo-transpiration

Neutron probe access tube

Upper silt w/admix 1.0 m

Lower silt 1.0 m Sand filter 0.15 m Gravel filter 0.3 m

Basalt rockRiprap 1.5 m

Drainage gravel 0.3 m min.

Composite asphalt (asphaltic concrete

coated w/fluid applied asphalt

0.15 m min.)

Top course 0.1 m min. Sandy soil

(structural) fill In situ soil


From November 1994 through October 1997, sections of the cap were sub-jected to an irrigation regime of three times the long-term average annual pre-cipitation, which included a simulated 1,000-year storm event (70 mm of water)during the last week of March for three years (1995 through 1997). Percolationdid not occur from the cap until the third year, and then only a small amount(less than 0.2 mm) was transmitted from one section subjected to the enhancedirrigation treatment. No drainage has occurred since then from this section orfrom any other portion of the cap. In fact, the percolation that was recorded hasbeen attributed to lateral flow from water diverted off an adjacent roadway ratherthan flow through the cap (USDOE, 1999).

Despite the large amount of water that was applied, all available stored soilwater was removed from the entire soil profile by late summer each year byevapo-transpiration (Figure 3.11), which maintained the water storage in the silt-loam layer well below the estimated drainage limit of 600 mm. If the silt-loamthickness was reduced from 2 m to 1.5 m, the storage data indicate that little orno percolation would be expected. However, if the silt-loam thickness was

FIGURE 3.11 Temporal variation in mean soil water storage in the silt-loam in theHanford cap. Monitoring was interrupted 1998–2000. Horizontal dashed lines representestimated storage limits for caps with silt-loam layers 2 m, 1.5 m, and 1.0 m thick. (FromUSDOE, 1999. 200-BP-1 Prototype Barrier Treatability Test Report. DOE/RL-99-11, U.S.Department of Energy, Richland, WA; Ward, A. and Gee, G., 2000. In Looney, B. andFalta, R. (Eds.), Vadose Zone Science and Technology Solutions, Battelle Press, Columbus,OH, pp. 1415–1423. With permission.)

9/30/1994 Date

0

100

200

300

400

500

600

700 Nonirrigated averageIrrigated average

2.0 m silt loam

1.5 m silt loam

1.0 m silt loam

Drainage under natural

conditions

Wat

er st

orag

e (m

m w

ater

)

9/30/20029/29/2000 9/30/1998 9/29/1996


reduced to 1 m, it appears that the cap would not perform well under extremelywet conditions.

The cap tested at Hanford represents perhaps the most sophisticated andredundant type of water balance design ever considered. The level of complexityassociated with the cap is needed for the radioactive wastes that it is designed toisolate. For many sites (e.g., municipal solid wastes, demolition debris, contam-inated soils), however, less sophisticated water balance caps are needed. Anassessment of more typical water balance caps is being conducted by ACAP undernatural climatic conditions (Bolen et al., 2001; Albright and Benson, 2002). Thecaps tested by ACAP are intended to meet a target percolation rate that rangesbetween 3 and 30 mm/year depending on the type of waste, the regulations inplace at each site, and the climate (semi-arid or arid vs. humid). Laboratorymeasurements of unsaturated and saturated soil properties were used in conjunc-tion with common methods accepted in practice to design each cap (Bolen et al.,2001). Typically, an unusually wet condition was used for the design calculations.

Percolation rates measured for the ACAP water balance caps as of April 2002are summarized in Table 3.5, along with the design percolation rates. Ninemonolithic barriers and five capillary barriers are being evaluated. The designcriterion is being achieved at eight of the 10 semi-arid sites, but at none of thehumid sites. The factors contributing to the higher than anticipated percolationrates are currently under evaluation, but the data do illustrate that water balancecaps do not necessarily perform as intended.

One key factor contributing to the higher than anticipated percolation ratesappears to be the influence of pedogenesis on hydraulic properties near thesurface. Samples are currently being collected from the surface of each test sectionas large undisturbed blocks to characterize the hydraulic property changes thathave occurred. A summary of the saturated hydraulic conductivity measurementsobtained to date is provided in Table 3.6. The saturated hydraulic conductivityhas increased due to factors such as desiccation and root penetration at three ofthe four sites for which tests have been conducted. At the fourth site, the hydraulicconductivity has remained about the same. Understanding how the hydraulicproperties change over time is critical to predicting how water balance caps willperform over the long term. Long-term performance prediction is an issue in needof research before water balance caps can be considered a long-term solution forcontainment. Another important issue probably contributing to higher than antici-pated percolation rates is scaling between hydraulic properties measured in thelaboratory and those operative in the field. Additional study of scaling issues andhow they can be incorporated in design is needed to understand long-term capperformance.

3.2.3 COUPLING OF VEGETATION AND MATERIAL PERFORMANCE FACTORS

Vegetation is not a cap material per se like soils and geosynthetics, but it is criticalto the long-term behavior of most caps, as discussed in detail in Chapter 1.


TAB

LE 3

.5D

esig

n an

d M

easu

red

Perc

olat

ion

Rat

es a

nd P

reci

pita

tion

Sum

mar

y fo

r W

ater

Bal

ance

Cap

s M

onit

ored

by

AC

AP

Site

Des

ign

Cri

teri

on

(mm

/yea

r)D

urat

ion

(Day

s)C

limat

eC

over

Typ

e

Tota

l Pr

ecip

itat

ion

(mm

)Pe

rcol

atio

n (m

m/y

ear)

Alta

mon

t, C

A3

517

Ari

dM

onol

ithic

bar

rier

487

1.0

(0.3

%)

App

le V

alle

y, C

A3

156

Ari

dM

onol

ithic

bar

rier

115

0.0

(0.0

%)

Mar

ina,

CA

368

4Se

mi-

arid

Cap

illar

y ba

rrie

r46

661

.8 (

13.3

%)

Sacr

amen

to,

CA

384

7Se

mi-

arid

and

sea

sona

lM

onol

ithic

bar

rier

108

0 m

m t

hick

744

48.4

(11

.1%

)M

onol

ithic

bar

rier

245

0 m

m t

hick

3.1

(0.7

%)

Pols

on,

MT

384

7Se

mi-

arid

and

sea

sona

lC

apill

ary

barr

ier

744

0.2

(0.1

%)

Hel

ena,

MT

390

5Se

mi-

arid

and

sea

sona

lM

onol

ithic

bar

rier

385

0.0

(0.0

%)

Boa

rdm

an,

OR

348

5Se

mi-

arid

and

sea

sona

lM

onol

ithic

bar

rier

122

0 m

m t

hick

181

0.0

(0.0

%)

348

5Se

mi-

arid

and

sea

sona

lM

onol

ithic

bar

rier

184

0 m

m t

hick

181

0.0

(0.0

%)

Mon

ticel

lo,

UT

360

7Se

mi-

arid

Cap

illar

y ba

rrie

r51

40.

0 (0

.0%

)A

lban

y, G

A30

722

Hum

idM

onol

ithic

bar

rier

with

tre

es19

8391

.3 (

7.2%

)C

edar

Rap

ids,

IA

338

1H

umid

and

sea

sona

lM

onol

ithic

bar

rier

with

tre

es77

214

3.1

(15.

6%)

Om

aha,

NE

355

2H

umid

and

sea

sona

lC

apill

ary

barr

ier,

760

mm

sto

rage

la

yer

719

3.7

(0.5

%)

552

Hum

id a

nd s

easo

nal

Cap

illar

y ba

rrie

r, 10

60 m

m s

tora

ge

laye

r71

93.

7 (0

.5%

)

Perc

enta

ge o

f pr

ecip

itatio

n in

par

enth

eses

.


Vegetation reduces erosion and, for water balance caps, is mostly responsible forremoving water stored in the cap. There are three important factors that affectthe success associated with establishing vegetation: proper preparation of the capsurface (e.g., not over-compacted), provision of nutrients, and selection of veg-etation that is consistent with the surrounding environment (e.g., a heavy grasscover should not be used for a water balance cap in the desert of Las Vegas,Nevada).

When these issues are considered during design and construction, vegetationhas largely been successful. For example, at the Hanford site, the survival rateof transplanted shrubs has been remarkably high (97% for sagebrush and 57%for rabbitbrush). Heavy invasions of tumbleweed have occurred (e.g., in 1995),but have not persisted. Grass cover consisting of 12 varieties of annuals andperennials, including cheatgrass, several bluegrasses, and bunch grasses, currentlydominates the surface. Approximately 75% of the surface remains covered byvegetation requiring no maintenance, which is a value typical of shrub-steppeplant communities (Gee et al., 1996). A similar example is shown in Figure 3.12for the water balance caps at the ACAP site in Sacramento, California. Withinone year of construction, a healthy cover of grasses and forbs was establishedwith a leaf area index on the order of 1.4 (Roesler et al., 2002).

Characterizing the transpiration that can be expected from vegetation is amore challenging issue (Figure 3.13). Figure 3.13 shows water balance quantitiesfor the thinner (1,080 mm) monolithic water balance cap in Sacramento beingmonitored by ACAP (test section on right-hand side of photographs shown inFigure 3.12). During the first growing season after construction (2000), thevegetation was able to extract the water and deplete the soil-water storage to thewilting point (approximately 180 mm), thereby providing an adequate soil res-ervoir for storing water during the subsequent winter. However, the vegetationwas far less effective in extracting the water in Spring 2001, even though theprecipitation record was similar in both years, the water stored at the end of bothwet seasons was comparable (approximately 400 mm), and the vegetation

TABLE 3.6Summary of Saturated Hydraulic Conductivities of Samples Retrieved from the Surface of Covers being Monitored by ACAP

Site

Geometric Mean Hydraulic Conductivity (cm/s)

End of Construction Summer 2002

Albany, GA 1.9 × 10–7 2.8 × 10–5

Cedar Rapids, IA 1.5 × 10–5 4.6 × 10–4

Helena, MT 5.0 × 10–7 1.6 × 10–7

Polson, MT 4.9 × 10–5 1.3 × 10–4


appeared no different during either growing season. Despite these similar condi-tions, the vegetation removed approximately 140 mm less water during the 2001growing season. Inadequate water removal resulted in inadequate storage capacitythe following wet season. As a result, the storage capacity (approximately 430 mm)was quickly exceeded during the wet period, and most of the water that infiltratedthe cap surface became percolation.

The inadequate transpiration observed during the 2000 growing season didnot persist. During the 2001 growing season, the vegetation removed all of theavailable stored water. However, the reason for these differences remains a mys-tery, and efforts are currently underway to better understand why transpirationwas greatly lower in 2001. This example illustrates, however, that characterizingand understanding the characteristics of vegetation is as important as understand-ing other materials used for caps, particularly for water balance caps that rely ontranspiration as a critical barrier system process.

FIGURE 3.12 ACAP test sections in Sacramento, CA, at the end of construction (a) andone year after construction (b).

(a)

(b)


3.3 MATERIAL PERFORMANCE FACTORS IN PRBS

In contrast to most containment systems, which are usually designed to impedethe flow of water, PRBs provide containment by treating contaminated water thatpasses through them. PRBs rely on a reactive material placed in the subsurface(or manipulation of the physico-chemical properties of the subsurface environ-ment) to treat contaminated groundwater (Figure 3.14). As contaminated waterpasses though the PRB, reactions occur between the contaminants and the reactivemedium, resulting in effluent that meets a target concentration, such as a maximumcontaminant level (MCL) (depicted as “remediated water” in Figure 3.14).

A variety of reactive media are used for PRBs, including granular iron metal,granular activated carbon, zeolitic minerals, compost, limestone, and other “solid”materials placed in the subsurface to promote the physical, chemical, and bio-logical conditions necessary for contaminated groundwater treatment. A summaryof many of the materials being used is provided in Table 3.7. A photograph ofgranular iron and clinoptilolite is shown in Figure 3.15.

The most commonly used treatment material is granular iron metal, which iseffective for treating groundwater affected by both organic and inorganic constit-uents (Gillham and O’Hannesin, 1994). Although the proportion of all PRBapplications using granular iron has not been computed, a reliable estimate isthat 70% to 90% of PRBs installed as tests or full-scale applications have used

FIGURE 3.13 Water balance quantities for thin cover (1080 mm thick) monolithic waterbalance covers being monitored by ACAP in Sacramento, CA. (Data from Roesler et al.,2002. Field Hydrology and Model Predictions for Final Covers in the Alternative CoverAssessment Program — 2002, Geo-Engineering Report No. 02-08, University of Wisconsin,Madison, WI; Albright, W. and Benson, C., 2002. Alternative Cover Assessment Program2002 Annual Report, Publication No. 41182, Desert Research Institute, Reno, NV.)

0

200

400

600

800

1000

1200

1400

0

50

100

150

200

7/1/99

Soil-water storage

Precipitation

Percolation

Surface runoff

1080-mm monolithic cover

Evapo-transpiration

Cum

ulat

ive p

reci

pita

tion,

eva

po-t

rans

pira

tion,

and

soil-

wat

er st

orag

e (m

m)

Percolation and surface runoff (mm

)

7/1/02 9/30/01 12/30/00 3/31/00


granular iron as the reactive medium. Other materials, such as granular activatedcarbon (GAC), compost, crushed limestone, alumino-silicates such as zeoliticminerals, and other materials are less used thus far, but are being tested in avariety of diverse applications.

3.3.1 APPROACH TO SELECTION OF PRB MATERIALS

The criteria for selecting a reactive material are described by Blowes et al. (2000)and include an assessment of the range of materials that can be used to removecontaminants and an assessment of the duration of material reactivity. Thesecriteria, coupled with an assessment of the potential for the release of hazardous

FIGURE 3.14 Schematic of a PRB used to intercept and treat a plume of contaminatedgroundwater.

TABLE 3.7List of Reactive Materials that have been Used in PRBs

Treatment Materials Contaminants Treated

Zero-valent metals (including iron) (may or may not include metal couples)

Methanes, ethanes, ethenes, propanes, chlorinated pesticides, freons, nitrobenzene, certain metals (Cr, U, As, Tc, Pb, Cd)

Ferric oxides Mo, U, Hg, As, P, SeZeolites Sr, Pb, Al, Ba, Cd, Mn, Ni, Hg, certain organicsActivated carbon Mo, U, Tc, chlorinated VOCs, BTEXLimestone Cr, Mo, U, acidic waterCompost Metals, acidic waterAlumina AsPeat, humate Mo, U, Cr, As, PbSawdust, compost NitrateOxygen Aromatic hydrocarbons, MTBE, vinyl chloridePhosphates Mo, U, Tc, Pb, Cd, Zn

(a)

Waste area

Groundwater

PlumeRemediated

water

ARTZ

Flow direction Aquifer


materials or contaminant by-products (e.g., release of vinyl chloride due to thereductive dechlorination of dichloroethylene), can be used to assess the potentialof the barrier material to provide adequate groundwater treatment. Interactionsbetween natural groundwater constituents can result in extensive formation ofsecondary mineral precipitates within the barrier. These precipitates can hinderbarrier performance by clogging the pore space and reducing barrier permeability,or by obscuring reactive particle surfaces. The assessment can be combined withan understanding of contaminant concentrations, groundwater geochemistry, andsite hydrogeology to determine whether a practical remedial system can beconstructed. Then, a preliminary cost estimate can be developed and comparedto remedial alternative estimates.

Implementation of a remedial system employing a PRB can proceed througha series of steps, with accompanying decision points leading to the installationof an optimized system. These steps start with a theoretical assessment of thepotential for treatment using existing PRB materials. State and federal guidancemanuals have documented the PRB materials that were employed at existing PRBinstallations, the contaminants that were treated, and the contaminant removalthat was attained [e.g., Interstate Technology Regulatory Council (ITRC), 1999a,b].This information can be used in conjunction with theoretical calculations, suchas the use of geochemical speciation/mass transfer computer codes or the use of

FIGURE 3.15 Examples of reactive media used in PRB applications: granular iron metal(left) and the zeolite clinoptilolite (right). U.S. quarter shown for scale.


pH–Eh diagrams to assess the potential for contaminant removal. If contaminantremoval is possible, then laboratory treatability testing is considered.

Laboratory treatability tests can be used to assess the potential for contami-nant removal and develop reaction parameters to assist in barrier design. Batchexperiments can be conducted to determine contaminant reactivity and measurereaction rates under static conditions. Column experiments can be used to measurerates of contaminant removal under dynamic flow conditions and assess the poten-tial for the precipitation of secondary minerals and barrier clogging. Where pos-sible, mineralogical examination of column materials following the testing programcan be used to verify the presence and structure of secondary precipitates to assessthe stability of these precipitates within the barrier and evaluate the potential forbarrier clogging. Complementary geochemical modeling, including reactivetransport modeling, can be used to develop design parameters at this stage. Thegeochemical modeling, coupled with groundwater flow and transport modeling,can be used to provide preliminary estimates of barrier performance and longevityand to design parameters for pilot- or full-scale installations.

3.3.2 EVALUATION OF FIELD PERFORMANCE USING PILOT TESTING

The decision whether to conduct a pilot-scale test or move directly to full-scaleimplementation depends on the history of the technology and the confidence ofthe client and regulators. Many PRB technologies have been demonstrated suf-ficiently to satisfy regulators that the treatment processes are well understood andthe installation success depends on site-specific processes. Pilot-scale installationsvary in scale and degree of monitoring, from small-scale column experimentsconducted ex situ at a field site to large-scale installations that ultimately form aportion of a full-scale PRB.

The key objective of the pilot-scale installation is to simulate conditions ina full-scale system as closely as possible. Using the candidate reactive materialsand natural aquifer materials in contact with site groundwater and typical con-taminant concentrations provides a close approximation to the characteristics offull-scale systems. The small size of pilot installations provides an opportunityfor monitoring at a level of detail that is sufficient to provide design parametersfor the full-scale installation. Pilot-scale installations should be sufficiently ver-satile so that variability in treatment media and groundwater flow rates can beassessed. The results of the pilot-scale installation can be used to confirm con-taminant reactivity and assess the potential for negative secondary reactions suchas scaling or clogging. The pilot-scale system should also have well-defineddimensions and performance characteristics to simplify scaling up to the finalremedial system.

One type of cost-effective in situ pilot test is conducted with a reactive testwell (RTW) consisting of reactive material placed in a 300-mm-diameter borehole(Figure 3.16). One or more 25-mm-diameter polyvinyl chloride (PVC) casings


are placed along the central axis of the borehole for groundwater sampling.Several well casings with slots at different depths can be used to obtain multiplesamples at different depths. A peristaltic pump is used to collect low-flow samplesfrom the slotted section of each casing for analysis.

RTWs were first used to test the efficacy of different reactive media forremoving arsenic from groundwater at a DuPont site in East Chicago, Indiana.Data collected from the RTWs over a nine-month period were used to select PRBmaterial. Basic oxygen furnace (BOF) slag was selected for use in the PRB basedon data collected from RTWs, whereas laboratory studies indicated that anothermaterial was more appropriate.

The coaxial configuration of the RTW ensures that groundwater passedthrough approximately 75 mm of reactive material before sampling regardless ofthe local groundwater flow direction. For accelerated tests, groundwater can becontinually extracted through the casing. Because RTWs are simpler and lesscostly than a full-scale pilot wall, multiple RTWs can be installed at a given siteto test different materials or act as controls. RTWs also have several advantagesover ex situ field demonstrations (Table 3.8).

Installation quality is important in a RTW providing reliable data. The drillingprocess should not create a smear zone at the well interface that might impedeflow. Centrality of the well casing is also important so that the flow path throughthe reactive medium is the same at all points in the well. A centralizer consistingof a plastic disk with threads that match the well string is generally placed atthe bottom of a RTW, along with conventional stainless-steel centralizers along

FIGURE 3.16 RTW using passive groundwater flow.

Groundwater samples

Bentonite seal

Reactive material in300-mm borehole

Slotted well casing

Ground-water


the length of the well casing (Figure 3.17). The stainless-steel centralizers areinstalled above the slotted section so that the water being sampled is not exposedto any extraneous reactivity.

Data from a RTW can be interpreted at several levels, from strict demonstra-tion of contaminant removal to development of break-through and capacity cor-relations and projections of service life. By manipulating flow rates, kineticexpressions can also be developed. A passive RTW (i.e., operating under naturalgroundwater flow conditions) can provide an assessment of effectiveness in nearlyreal time, i.e., one month of field data is equivalent to one month of ultimatePRB exposure. To project the ultimate life of a PRB, an extractive RTW can beemployed. In this technique, groundwater is pumped out of the central casing atan accelerated rate, analogous to using higher throughputs in a laboratory column.Avoiding kinetic limitations (i.e., from an extraction rate that is too high) withan extractive RTW is important unless a kinetic study is intended. An appropriaterate should be determined in the laboratory and then translated to the field test.

3.3.3 EFFECTS OF HYDRAULIC CONSIDERATIONS ON REACTIVE MATERIAL PERFORMANCE

To date, PRB research has focused mostly on the reaction mechanisms, kinetics,and conversion efficiency associated with the reactive materials (Tratnyek et al.,2003). Much less effort has focused on factors that affect PRB hydraulics, even

TABLE 3.8Comparison of Reactive Test Wells vs. Ex Situ Field Tests

Parameter In Situ Reactive Test Well Ex Situ Packed Columns

Key Technical ParametersGroundwater chemistry Actual Can be differentContaminant losses in system Essentially none Can be significantPotential data quality High Varies significantlyFlow rate through bed Natural (uncontrolled, cross-flow); or

enhanced (pumped), radial flowControlled, precise, axial

Logistical ParametersSystem complexity Low Medium to highEffluent disposal None ProblematicMultiple location tests Concurrent SequentialDuration limit Unlimited, at low cost Limited by cost, etc.Weather protection required None Can be significant

Overall AssessmentFinal wall approximation Very close; a mini-wall ApproximationTechnical certainty High Varies significantlySpecial potential Long-term performance evaluation Precise flow control


though hydraulic factors can have as large an impact on PRB effectiveness(Eykholt et al., 1999; Elder et al., 2002).

As more PRB systems are implemented and monitored, performance datasuggest that hydraulic characteristics of PRB materials need to receive greaterattention during design. Recent reviews of PRB applications have suggested thatmost cases of unintended performance are due largely to inadequate hydraulicperformance. Few cases are related to inadequacies in the chemical treatmentmethodology (Warner and Sorel, 2001; Battelle, 2002). These findings indicatethat designers need to consider hydraulics as a critical factor affecting successfulPRB deployment, and approach hydraulic design with the same level of care asreaction effectiveness. Hydraulic aspects that can have a large impact on PRBeffectiveness are aquifer material heterogeneity and spatial variability of thegroundwater flow field. The importance of geological heterogeneities and theneed for characterization was illustrated in a recent case study of a PRB con-structed near Kansas City, Missouri (Laase et al., 2000). The PRB was installedin an alluvial aquifer to intercept a plume containing trichloroethylene (TCE).Data from a hydrogeological study were used as input to a groundwater modelused to select PRB orientation and breadth. The breadth was to be sufficiently

FIGURE 3.17 Centralizers for maintaining casing position in a RTW: Base centralizer(left) and stainless steel centralizer (right).


large to capture the entire width of the plume. An extensive set of monitoringwells (12 upgradient, 16 downgradient, and 10 adjacent to the ends of the PRB)was installed to monitor influent and effluent conditions and check for bypassing.

Data from the monitoring program showed that the wall was not functioningas intended. While the reaction mechanisms appeared to have been accounted forproperly, a sandy gravel region toward the southern end of wall was not detectedduring hydrogeological characterization and caused a portion of the plume tobypass the PRB, as shown in Figure 3.18. In addition, reversals in the hydraulicgradient during recharge events caused the southerly extent of the plume to curlnorthward and, at times, flow backward through the PRB. Bypassing was occur-ring along the northern end of the PRB as well.

Few PRBs are monitored as closely as the PRB in Kansas City. Thus, thefrequency of problems caused by heterogeneity is unknown. However, a recentmodeling study by Elder et al. (2001, 2002) suggests that geological heterogeneitymay be having a much larger impact on PRB effectiveness than previouslythought. Elder et al. (2001, 2002) constructed a series of heterogeneous aquiferscontaining PRBs and simulated flow and transport through the aquifer and PRB.Because a model was used, effluent concentrations were characterized in fargreater detail than is possible in the field, even with a dense network of monitoringwells.

Typical results reported by Elder et al. (2001, 2002) are shown in Figure 3.19.The simulation consisted of a TCE source with a uniform concentration of 1000

FIGURE 3.18 Schematic of plume bypassing southern end of PRB installed near KansasCity. (Adapted from Laase, A. et al., 2000. In Wickramanayake, G. et al. (Eds.), ChemicalOxidation and Reactive Barriers, Remediation of Chlorinated and Recalcitrant Com-pounds, Battelle Press, Columbus, OH, pp. 417–424).

NPlume

Flow

PRB


micrograms per liter (μg/L) located 20 m upgradient of the PRB. By the timethe plume reached the PRB, dispersion induced by aquifer heterogeneities causedthe TCE concentration to range from 0.1 to 1000 μg/L. As groundwater flowedthrough the wall, the TCE concentration decreased, but not always below thetarget level (5 μg/L). In fact, the effluent concentration was as high as 500 μg/L

FIGURE 3.19 Concentrations at source (a), influent face of PRB (b), and effluent face ofPRB (c) in a heterogeneous aquifer. (Adapted from Elder, C. et al., 2002. Water ResourcesResearch, 38(8), 27-1 to 27-2).

Elev

atio

n (m

)

454035302520151050

1086420

Lateral distance (m)

Elev

atio

n (m

)

454035302520151050

1086420


Elev

atio

n (m

)

454035302520151050

1086420


TCE Concentration (mg/L)

1000500

10010 5 1 0.1 0.01

Monitoring well screensBoundary

of PRB

Monitoring well screensBoundary

of PRB

(a) Source concentrations

(b) Influent concentrations

(c) Effluent concentrations


in some locations. These high concentrations were due to preferential flowthrough the wall as a result of heterogeneity in the adjacent aquifer materials.

Elder et al. (2001) assessed whether the range in effluent concentrations, aswell as the peak effluent concentrations, could be detected using typical PRBmonitoring schemes. Most monitoring schemes were found to be too sparse tocapture most of the variability, and effluent concentrations detected by typicalsystems were found to underestimate peak effluent concentrations by an order ofmagnitude or more.

The findings reported in Elder et al. (2001, 2002) illustrate the need for bettercharacterization of PRB flow rates and flow paths. A variety of methods can beused for characterization. Tracer tests have been used to establish groundwaterflux and flow paths through PRBs. Dissolved tracers are well suited to determiningthe direction of groundwater flow, but are limited by the number of injectionwells that can be used without overlapping tracer plumes. In addition, flowvelocities obtained from tracer studies are sensitive to the number and distributionof monitoring points and to chemical dispersion. Accurate determinations ofdispersion are often lacking, particularly within a PRB where settling or otherconstruction-related effects can be significant. Another method is the use ofdownhole flow sensors. These instruments rely on dispersion of a heat pulse ormeasurement of colloidal particle velocities to determine groundwater flow veloc-ities. Velocities measured with this technique often vary considerably within anindividual well and between wells and may differ from those in the aquifer dueto the effects of an open borehole. In situ sensors embedded in the aquifer caneliminate the effects of an open borehole, but the higher cost associated withdedicated sensors generally limits their application to a few points within or neara PRB. Even so, the extent of representation of velocities from flow sensors isunclear. In a comparison of three different downhole flow sensors, Wilson et al.(2001) concluded that the three methods “rarely measured the same velocitiesand flow directions at the same measurement stations” and that repeat measure-ments “failed to consistently reproduce either flow direction, flow magnitude, orboth.”

A promising method that can be used to evaluate the average velocity in anoperating PRB using granular iron is reaction path monitoring. Geochemicalreactions within a granular iron PRB cause the precipitation of solids containingthe major constituents in the groundwater (e.g., calcium, magnesium, manganese,carbonate), as well as contaminants (e.g., arsenic, molybdenum, selenium, uranium,vanadium, zinc). More detail on these processes is contained in Section 2.3.Reaction path monitoring involves estimating a time-averaged groundwater veloc-ity from constituent concentrations in the aqueous and solid phases.

The following is an example of the method used for a PRB installed down-gradient from a former uranium ore-processing mill in Monticello, Utah. ThePRB is 31.4 m long, 2.2 m wide, and 4 m deep, and contains about 250 milligrams(mg) of granular iron (Figure 3.20). Two SB cutoff walls with a combined lengthof 103 m form a funnel that directs groundwater into the PRB. The PRB is dividedinto three panels: (1) 0.5 m wide panel of pea gravel mixed with 13% granular


iron (based on volume) at the upgradient face, (2) 1.2 m wide central portioncontaining 100% granular iron, and (3) 0.5-m-wide downgradient panel thatcontains only pea gravel.

The PRB was placed within a groundwater plume emanating from the formermill site. Groundwater entering the PRB has a uranium concentration of about0.4 mg/L. The plume also contained arsenic (0.01 mg/L), molybdenum (0.06 mg/L),nitrate (61 mg/L), selenium (0.02 mg/L), and vanadium (0.4 mg/L) as it enteredthe PRB. The PRB was very effective at treating each of these contaminants.Concentrations of all contaminants decreased to low levels in the PRB during2.7 years of its operation (Morrison et al., 2001).

FIGURE 3.20 Schematic of groundwater cutoff walls and PRB installed at Monticello,Utah, site. (ZVI, zero-valent iron.)

0.5 m of gravel/ZVI

1.2 m of 100% ZVI

0.5 m of gravel withair-sparging pipe

North slurry wall(29.6 m)Groundwater flow

PRB (31.4 m)

Southslurry wall(73.2 m)


Solid phases in the gravel-iron panel and the iron-only panel were sampledusing direct-push coring in February 2002. Cores were collected at 70 randomlocations within 10 evenly spaced PRB segments (Figure 3.21). The cores werecut into 4.1-cm lengths; 614 samples were collected, of which 279 were digestedand analyzed for calcium, uranium, and vanadium. Constituent concentrationsdissolved in the groundwater were also measured at 10 evenly spaced timeintervals from six wells upgradient and six wells downgradient of the gravel-ironpanel.

Core analysis showed that nearly all the uranium (Figure 3.22) and vanadiumwere deposited in the gravel-iron panel. In contrast, calcium was deposited inboth iron-containing panels (Figure 3.23). The distribution of calcium is morepervasive and indicates a slower rate of transfer to the solid phase. Calcium,uranium, and vanadium are distributed along the entire length of the PRB, indi-cating that the entire mass of iron is being used to treat the contaminated ground-water, and that groundwater has not flowed preferentially through specific portionsof the PRB.

Mean concentration differences (ΔCw) were calculated from the aqueousphase concentrations (Table 3.9). The mean groundwater flux (Qw) was thencomputed for each solid phase species using:

(3.1)

where Cs is the mean solid-phase concentration, Mg is the mass of solid materialinitially in the zone (70.2 mg), and Δt is the deposition period (2.7 years). Themean groundwater fluxes computed following this approach using uranium andcalcium data are summarized in Table 3.9. The mean groundwater flux (24 L/min)through the gravel-iron panel zone calculated using the calcium data was identicalto that calculated using uranium and was considerably less than the design valueof 189 L/min.

3.3.4 STRUCTURAL STABILITY FACTORS IN PERFORMANCE

Little post-construction assessment occurs regarding the integrity of the in-placereactive medium from the perspective of sustainability (e.g., reactivity, conduc-tivity) or structural stability (e.g., settlement, movement, strength). Propertiessuch as density or specific gravity, shape, and water content can affect the in-place density, porosity, and hydraulic conductivity. In addition, when two or morematerials are used in a PRB or the PRB contains multiple sections of materials,mixing uniformity or complete separation must be ensured. For example, thespecific gravity of the reactive materials must be considered so that a constructionprocedure can be developed that will promote uniform mixing.

QC M

t Cw

s g

w

=Δ Δ


FIGURE 3.21 Locations of cores for solid-phase samples and monitoring wells for aque-ous phase analyses in PRB installed at Monticello, Utah, site.

Met

ers

15

10

5

00 0.5 1.0 1.5

20

25

30

Meters

Core

Well

Flow

Gravel/ZVI ZVI


FIGURE 3.22 Distribution of uranium in the solid phase (mg/kg) in PRB installed atMonticello, Utah, site. Contour interval is 50 mg/kg.

Met

ers

30

25

20

15

10

5

00 0.5 1.0 1.5

Meters

Flow

Gravel/ZVI ZVI

70.0 319.3 0.1 0.10.1

0.10.10.9

384.4206.5

190.3

437.0 1.0

0.1 1.1

0.00.2156.692.7

249.8 0.0

0.00.0 0.0

0.00.00.9172.4226.0

288.8807.5

330.2

200

10.5 0.0 0.0 0.00.1

0.4 0.0 0.1

0.1

0.10.1

1.00.5

0.1

251.8

396.8 558.4334.5

343.5

350.0

539.5

200371.0 269.0

147.1 6.30.1 0.2

0.1

0.20.1

0.0 0.4

1.7

144.4112.6

200

89.3

119.0596.9


FIGURE 3.23 Distribution of uranium in the solid phase (g/kg) in PRB installed atMonticello, Utah, site. Contour interval is 2 g/kg.

Met

ers

30

25

20

15

10

5

00 0.5 1.0 1.5

Meters

Flow

Gravel/ZVI ZVI

46.8 44.1 24.8 10.3 14.1

13.9

22.9

2.120

16.0

10

5.3 11.5

27.7 11.4

26.525.9

21.914.8

15.2

11.5

20

15.4 33.5

16.8

17.3 28.3

24.8

11.5

20

7.3 8.8

10

8.26.011.019.7

17.19.9 8.7 0.8

22.213.3

20

25.3

17.8 12.023.5

20

33.2 20.520.4

30.7 25.7

29.0

32.326.9 27.1

23.1

30.3 29.1

25.9

25.7

23.8

37.626.0

37.830.5

17.2

25.924.8 29.8

30

35.6

23.0

45.3

4030

15.1

30

35.5


Specific gravities of typical reactive media are summarized in Table 3.10 anddiffer by as much as a factor of 5.6. Differences in specific gravity can causesegregation of materials as they settle, resulting in zones with too little or noreactive material. These factors are particularly important if a mixture of materialsis placed in water or a slurry.

The relative strength of the reactive material (both the shear strength of themedium and the crush strength of individual particles) can also be important.Granular iron forms a relatively dense section with high shear strength, lowcompressibility, and high hydraulic conductivity, although corrosion and miner-alization can affect these properties over time. In contrast, zeolites are weaker,more friable, and crush more readily, which can lead to the creation of fines thatfill pore spaces and lower hydraulic conductivity. The lower shear strength andhigher compressibility of some reactive materials such as mixtures with predom-inantly organic material can be insufficient to resist the earth pressures at depthin some PRBs, resulting in a wall that is too thin due to lateral compression.Additionally, a highly compressible medium can compress so much under lateralearth pressures that its hydraulic conductivity becomes too low.

TABLE 3.9Masses and Concentrations of Calcium and Uranium and Calculated Groundwater Flux for the Gravel-Granular Iron Panel in the Monticello PRB

Component in Analysis Ca U

Mean solid-phase concentration (Cs) (mg/kg) 22,700 162Mean groundwater concentration gradient (ΔCw) (mg/L)a 47.0 0.334Calculated groundwater flux (Qw) (L/min) 24 24Total mass (kg) 1600 11.4Total mineral mass (kg)b 4000 12.9Total volume of mineral deposited (L)b 1500 1.6

a Mean difference between influent and effluent in the gravel-iron panel.b Calcium as calcite (CaCO3) and uranium as uraninite (UO2).

TABLE 3.10Specific Gravities for Common Reactive Media Used in PRBs

Material Specific Gravity

Granular iron 7.5–7.9Clinoptilolite 2.0–2.5Well sorted sand 2.5–2.8GAC 1.4–1.5


The shear strength and compressibility of the reactive material can also affectfuture site uses, particularly in urban settings. For example, a PRB containing areactive medium that is too weak or too compressible can preclude developmentadjacent to or above the PRB because the PRB and the surrounding ground willnot support the loads associated with the structure being considered. Thus, futureland uses should be considered when a reactive medium is selected to ensurecompatibility.

3.3.5 MATERIAL DURABILITY FACTORS

A variety of chemical reactions occur in a PRB as groundwater contacts thereactive medium. Some of these reactions relate directly to treating the contam-inants in groundwater. Others occur due to interactions between the reactivemedium, groundwater, and the natural solutes in the groundwater. In a PRB usingZVI as the reactive medium, iron corrosion causes a variety of chemical reactionsto occur, some of which can result in secondary mineral precipitation that canplug the PRB or passivate the iron. This section on mineralization and foulingfocuses on PRBs employing ZVI because they are by far the most common PRBs.

A summary of some of the reactions reported for iron is provided in Table3.11. Not all reactions occur in a given PRB system. The set of relevant reactionsfor a specific PRB depends on groundwater quality, contaminants present, andlevel of microbial activity. The corrosion/precipitation process, illustrated inFigure 3.24, leads to a buildup of precipitates on the surface of the reactivemedium. Even in pure water, iron undergoes a series of corrosion and precipitationreactions that form iron oxyhydroxide surface coatings. In groundwater, siderite(FeCO3), aragonite (CaCO3), and magnesite (MgCO3) generally form as well.The presence of other naturally occurring carbonate (CO3

2–), sulfate (SO42–), and

chloride (Cl–) ions also leads to the formation of green rusts.The types of precipitates that form and cover the iron surface have important

implications in the contaminant removal process. Removal of halocarbons suchas TCE, and reducible metals such as chromium and uranium, depends on thedonation of electrons resulting from iron oxidation. When iron is in its fullyoxidized state, it cannot donate any more electrons and the reduction of TCE orchromium no longer occurs. Generally, iron must be in a zero-valent or +2oxidation state for an iron-related redox reaction to occur. Fully oxidized ironoxides such as FeOOH and Fe2O3 do not oxidize further. Coating the granulariron with these oxides leads to passivation or the loss of reactivity.

Many of the iron oxides and other precipitates listed in Table 3.11 have beenobserved in laboratory and field studies of PRBs using granular iron. Roh et al.(2000) found green rusts, iron hydroxides, and goethite in laboratory columnstudies conducted with waters from Portsmouth, Ohio, and Oak Ridge, Tennessee.After 15 months of operation, examination of a field-scale barrier at the Y-12plant site in Oak Ridge (Tennessee) yielded buildup of significant precipitateswhere the groundwater first enters the barrier (Phillips et al., 2000). CaCO3,FeCO3, goethite (α-FeOOH), akaganeite (β-FeOOH), and mackinawite (FeS)


TABLE 3.11Corrosion and Precipitation Reactions Common for Granular Iron PRBs

(biologically mediated)

Fe + 2H O Fe + H + 2OH02

2+2→ −

2Fe + O + 2H O Fe + H + 4OH02 2

2+2→ −

Fe + R Cl+ H O Fe + R H+ OH + Cl02

2+− → − − −

Fe + CrO H Fe + Cr + 4H O0 3+ 3+24

2− ++ →

Fe Fe e2 3+ + −→ +

Fe OH Fe OH2

2 2+ −+ → ( )

Fe OH + OH Fe OH + e2 3

( ) → ( )− −

3Fe OH Fe O magnetite + 2H O+ H2 3 4 2 2( ) → ( )

3Fe + 4H O Fe O magnetite + 6H + H2+2 3 4

+2→ ( )

Fe OH FeOOH goethite,lepidocrocite + H + e2

+( ) → ( ) −

4Fe OH + Cl Fe Fe OH Cl GRI + e2 3

II III

8( ) → ( ) ( )− −

4Fe +8H O+ Cl Fe Fe OH Cl GRI +8H + 9e02 3

II III

8

+− → ( ) ( ) −−

6Fe OH + CO Fe Fe OH CO GRI + 2e2 4

II2III

12 3( ) → ( ) ( )−32 −−

6Fe OH + HCO Fe Fe OH CO GRI + H2 4

II2III

12 3+( ) → ( ) ( )−

3 ++ e−

6Fe +12H O+ HCO Fe Fe OH CO GRI +1302 3

II III

8 33− → ( ) ( ) HH +14e+ −

6Fe OH + SO Fe Fe OH SO GRII + 22 4

II2III

12 4( ) → ( ) ( )−42 ee−

6Fe OH +12H O+ SO Fe Fe OH SO GR2 2 4

II2III

12 4( ) → ( )−42 III +12H +14e+( ) −

4Fe + O + 4H O 2Fe O hematite, maghemite +8H2+2 2 2 3→ ( ) ++

HCO OH CO H O23 32− − −+ → +

Fe + CO FeCO siderite2+33

2− → ( )

SO 4H S 4H O2 242 2− −+ → +

Fe + S FeS mackinawite2+ 2− → ( )


were identified within the barrier. Cementation of the granular iron was alsoobserved where the groundwater entered the barrier. Sass et al. (2001) reportprimary corrosion coatings of magnetite (Fe3O4) and hematite (α-Fe2O3) withvarious forms of amorphous iron hydroxides [Fe(OH)2 and Fe(OH)3] and smallamounts of CaCO3 and marcasite (FeS2). Core sample analysis of the iron cellfrom a pilot field study at Moffett Field (Mountain View, California) also founddominance of Fe3O4 with small amounts of α-Fe2O3 or maghemite, CaCO3, andFeS2.

3.3.5.1 Effect of Mineral Precipitation on Porosity and Hydraulic Conductivity

The precipitation of secondary minerals reduces the porosity and decreases thehydraulic conductivity of the reactive medium (Mackenzie et al., 1999). Hydrogengas generation and build up can also occlude pores, leading to an apparent lossof porosity and reduction in hydraulic conductivity. Yabusaki et al. (2001) useda geochemical transport model to predict mineral precipitation and porosityreductions of the PRB at Moffett Field. They predicted the porosity woulddecrease at a rate of 1.5% to 3.0% per year, primarily due to formation of CaCO3

and FeCO3 near the upgradient face of the reactive zone in the PRB. Calibrationof the geochemical transport model to field data from the Moffett Field PRB

FIGURE 3.24 Example reaction occurring as corrosion and precipitation occurs in pres-ence of granular iron.

Fe2+

e−

Fe0

TCE

• Fe0 + 2H2O → Fe2+ + H2 + 2OH−

• 2Fe0 + O2 + 2H2O → 2Fe2+ + 40H− + H2

• Fe0 + R−Cl + H2O → Fe2+ + R−H + OH− + Cl−

• Fe0 + CrO42− + 8H+ → Fe3+ + Cr3+ + 4H2O

Example Reactions

• Release of OH−, pH increases

• Increasing pH causes alkalinity to shift to more CO3

2−

• Precipitation and complexation of cations, Fe2+, Fe3+, Ca2+, Mg2+, etc. favored

• H2 generated as gas, important for anaerobic biological activity

H2OO2

CrO4−


indicated that that a Darcy flux of 0.04 m/day best fit the field data after one yearof operation, whereas the Darcy flux was believed to be 0.064 m/day at the time ofconstruction. Comparison of these Darcy fluxes suggests that the PRB hydraulicconductivity may have decreased by about 50% as a result of mineral deposition.However, this hypothesis has not yet been confirmed with actual field measure-ments of hydraulic conductivity.

Gillham et al. (2001) reported on similar levels of fouling in a PRB containinggranular iron. They found a decrease in porosity of 5% to 15% as a result ofhydrogen gas evolution and an additional 17% to 22% due to mineral precipita-tion. They also reported that the hydraulic conductivity decreased approximatelyone order of one magnitude as a result of hydrogen gas that formed when thePRB was first installed, but found no decrease in hydraulic conductivity due tomineral precipitates.

3.3.5.2 Effect of Mineral Precipitation on Reactivity

Mineral formation can also result in loss of reactivity (i.e., the rate at whichreactions occur). For granular iron PRBs, loss of reactivity is referred to aspassivation (i.e., the loss of redox reactivity). Passivation occurs when the ironsurface is coated by iron corrosion products and other precipitates. These mate-rials provide resistance to mass transfer to and from the iron surface, impedingthe corrosion reaction rate. A classic example of iron passivation is the coating ofiron (III) oxide that forms when steel structural members oxidize. The coatingprotects the steel by minimizing the rate at which the iron corrodes in theatmosphere. Similarly, in PRBs with granular iron, oxide coatings can minimizethe rate of corrosion either by dissolved oxygen or water. However, in a PRB, areduction in the corrosion rate is detrimental because it corresponds to a reductionin the rate of contaminant treatment.

The potential for passivation of granular iron by the iron (III) hydroxidesgoethite, hematite, lepidocrocite, and maghemite has been suggested becausethese fully oxidized iron corrosion products inhibit electron transfer and hydrogenformation reactions. However, there has been little experimental evidence indi-cating that these iron corrosion products actually form in PRBs. In contrast, fieldstudies have shown that mixed valent iron oxides, such as magnetite and greenrusts, are the more prevalent iron corrosion products. Because these iron corrosionproducts are able to promote reduction and hydrogenation reactions, remediationreactions are able to proceed in their presence.

Despite the positive field data, recent studies do suggest that passivationoccurs in granular iron permeated with typical groundwaters. Farrell et al. (2000)found that the TCE degradation rate decreased during a long-term column test.After nearly two years of operation, the effective half-life for TCE dechlorinationincreased from 400 to 2,500 per minute. The decrease in reaction rate wasproportional to the amount of iron corrosion products in the column. Lower TCEdegradation rates were observed where precipitate buildup was highest. In addition,


while Fe3O4 was found throughout the column, magehmite (Fe2O3) was foundonly in the initial portions of the column, where the decrease in reaction rate waslargest. Reduction reactions critical to TCE degradation do not occur with Fe2O3,which is composed of fully oxidized iron, but do occur with magnetite.

Köber et al. (2002) also observed a drop in the first-order reaction rateconstants for perchloroethylene (PCE), TCE, cis-1,2-dichloroethylene (cis-DCE),and vinyl chloride in a column test where 379 pore volumes of groundwater hadpassed through the granular iron. The reduction in reaction rates for PCE,cis-DCE, and vinyl chloride were so significant that treatment efficiencydecreased to less than 10% by the end of the experiment. The reduction intreatment efficiency was attributed to the loss of reactivity caused by iron andcalcium carbonate precipitates.

3.3.6 APPLICATIONS OF GEOCHEMICAL MODELS IN REACTION TRACKING

Although field and laboratory studies now show that mineral precipitation andhydrogen gas evolution in PRBs can cause an apparent reduction in porosity andhydraulic conductivity, little is known about the rate at which these changes occuror their long-term effects on PRB performance. One approach currently underdevelopment is the use of geochemical transport models such as OS3D (Yabusakiet al., 2001), MIN3P (Mayer et al., 2001, 2002), or RT3D (Clement, 1997;Mergener et al., 2002). Geochemical transport models combine algorithms thatsimulate flow under realistic aquifer conditions, advection, dispersion, and thekinetics of geochemical reactions. They can be used to predict the temporal andspatial distribution of mineral precipitation and gas evolution and the effects thatthese processes have on hydraulic conductivity.

The following is a sample application of a geochemical transport modeldeveloped by Mergener et al. (2002) specifically for evaluating PRB fouling dueto mineral precipitation and hydrogen gas evolution. The model simulates flow,transport, and geochemical processes in a three-dimensional (3-D) domain com-prised of an aquifer and PRB. The distribution of hydraulic conductivity in thedomain can be heterogeneous so that a realistic distribution of flow rates andresidence times in the PRB can be simulated. Incorporating heterogeneity isessential (Bilbrey and Shafer, 2001; Elder et al., 2002; Wilkin et al., 2002).Variations in flow velocity affect the rate at which dissolved constituents entervarious portions of the wall and the rate and location of mineral deposition(i.e., solutes may move faster or slower than the rate at which precipitation occurs,resulting in variable mineral distribution in the pore space due to geochemicaland hydraulic effects) (Mayer et al., 2001; Li, 2002; Mergener et al., 2002).

The model is based on the reactive transport model RT3D (Clement, 1997),which is a 3-D multi-component reactive transport model in the public domainthat simulates advective-dispersive transport of multiple aqueous and immobilespecies in saturated porous media. The head solution from the 3-D groundwater


flow simulator MODFLOW is used as input to RT3D. Mergener et al. (2002)incorporated geochemical processes occurring within a PRB using the “user-defined” reaction sub-module in RT3D. Emphasis was placed on making themodel efficient so that practical 3-D problems could be simulated with reasonablerun times, which led to some simplifications relative to other more fully developedproprietary codes (e.g., MIN3P by Mayer et al., 2002). However, the code capturesthe key mechanisms affecting fouling.

Groundwater entering the PRB is assumed to be in chemical equilibrium, andonly geochemical reactions within the PRB are considered. Water, oxygen, sulfate,and nitrate contribute to iron corrosion. Corrosion causes the pH to increase, acorresponding shift in the carbonate-bicarbonate equilibrium, release of hydrogengas, and precipitation of secondary minerals such as CaCO3, MgCO3, dolomite,brucite, pyrochorite, rhodochrosite, FeCO3, ferrous hydroxide, and ferrous sulfide.Corrosion caused by reduction of chlorinated compounds or toxic heavy metalsgenerally is not included. Even though it is intrinsic to the remediation process,corrosion by contaminants generally is negligible relative to that due to othercorrosion processes (Phillips et al., 2000; Morrison et al., 2001; Yabusaki et al.,2001).

A listing of the reduction-corrosion reactions included in the model is pre-sented in Table 3.12. All of the reactions are assumed to occur in parallel. Theaqueous species and reactions that have been incorporated generate the predom-inant secondary minerals responsible for fouling (Schuhmacher et al., 1997; Pulset al., 1999; Blowes et al., 2000; Phillips et al., 2000; Mayer et al., 2001).Corrosion reaction kinetics are described by first-order rate laws that are a func-tion of reacting species concentration and reactive medium surface area. Reactionrates based on transition state theory are used to describe the precipitation ofsecondary minerals. The kinetic model is assumed to be spatially homogeneousand time-invariant when the PRB is installed. Spatial and temporal variabilitiesevolve as concentrations in the PRB change in response to flow rate variability.

The following example corresponds to the heterogeneous aquifer shown inFigure 3.25, which contains a fully penetrating 100% granular iron PRB (Figure3.21) oriented orthogonal to the regional gradient. Groundwater entering the wallwas assumed to be anoxic (dissolved oxygen concentration = 10–8 M) and tocontain the following dissolved species: Fe2+, 10–10 M; Ca2+, 10–3 M; Mg2+, 10–3 M;OH–, 10–7 M; HCO3

–, 10–3 M; CO32–, 10–7 M; NO3

–, 10–3 M; SO42–, 10–3 M. The

initial porosity of the PRB was 0.6.Reductions in porosity predicted by the model for conditions after 10 years

of service are shown in Figure 3.26. Reductions in porosity as large as 0.10(corresponding to one sixth of the pore space) were common (Figure 3.26).CaCO3, MgCO3, and FeCO3 are the primary minerals that formed near the frontof the wall, whereas ferrous hydroxide precipitation increased with wall distance(Li, 2002). Material distribution was heterogeneous, as shown by the spatiallyvariable reduction in porosity and largely depended on the distribution of flowvelocity in the PRB. Pockets of CaCO3, MgCO3, and FeCO3 formed in the interiorof the wall along flow paths where the velocity was higher. In addition, the greatest


reductions in porosity occurred in regions of the PRB where the Darcy velocitieswere highest (Figure 3.27) because these regions received more groundwater andthus more dissolved constituents.

The importance of flow field heterogeneity is evident in Figure 3.26 andFigure 3.27. If the flow field is assumed to be uniform, the porosity reductionswould be uniform and focused on the front of the wall, resulting in uniformchanges in PRB hydraulics and reactivity. In contrast, realistic spatial variationsin porosity reduction would result in reorientation of flow paths, changes inresidence time, and changes in treatment effectiveness. These variations wouldreduce the overall PRB hydraulic conductivity, yielding a reduction in flow rate,evolution of backwater, and bypassing.

Although models such as these can provide estimates of the spatial andtemporal distribution of PRB fouling, their accuracy is sensitive to the kinetic

TABLE 3.12Geochemical Reactions in Fouling Model Developed by Mergener et al. (2002)

Reaction Type Geochemical Reaction Mineral Formed

Iron corrosion—

—

—

—

—

Microbial sulfate reduction

—

Aragonite

Magnesite

Dolomite

Brucite

Mineral precipitation Pyrochroite

Rhodochrosite

Siderite

Ferrous hydroxide

Ferrous sulfide

Fe H O O Fe OH02 2

20 5 2+ + → ++ −.

Fe H O Fe H OH02

222 2+ → + ++ −

4 7 1002 3

24Fe H O NO Fe OH NH+ + → + +− + − +4�

4 4 802 4

2 2 2Fe H O SO Fe OH S+ + → + +− + − −4�

HCO OH CO H O3 32

2− − −+ ↔ +

SO H S H O42

22

24 4− −+ → +

CaCO Ca CO32

32↔ ++ −

MgCO Mg CO32

32↔ ++ −

CaMg CO Ca Mg CO( )3 22 2

322↔ + ++ + −

Mg OH Mg OH( )22 2↔ ++ −

Mn OH Mn OH( )22 2↔ ++ −

MnCO Mn CO32

32↔ ++ −

FeCO Fe CO32

32↔ ++ −

Fe OH Fe OH( )22 2↔ ++ −

FeS Fe S↔ ++ −2 2


models and the reaction rate coefficients used as input. Currently, existing modelsprovide an estimate of changes that are likely to occur in a PRB over time. Morefield data are needed, however, to improve and calibrate the models before theycan be considered as predictive tools. A variety of characterization techniquesare available, ranging from optical microscopy to the examination of the reactionproducts. Optical and scanning electron microscopy can be used to observe thedistribution and structure of reaction products and secondary precipitates. Energy

FIGURE 3.25 Hydraulic conductivity distribution and location of PRB in a heterogeneousaquifer model. (From Elder, C. et al., 2002. Water Resources Research, 38(8), 27-1 to 27-2.)

FIGURE 3.26 Predicted reductions in porosity of PRB after 10 years of operation.

100 5030 80 90Longitudinal distance (m)

40 7060

Hydraulic conductivity (cm/s)

10–5 10–4 10–3 10–2 10–1

Elev

atio

n (m

)

1050

40

30

50

70

60

1020 Late

ral dist

ance

(m)

20

10

5

0

Elev

atio

n (m

)

20

Groundwater flow

Porosity reduction

0.01 0.05 0.09 0.13

Lateral distance (m)10

0 0 X (m)1


dispersive x-ray analysis (EDXA) provides qualitative chemical analysis, whereaselectron microprobe analysis provides quantitative measurements of the elementalabundance. X-ray photoelectron spectroscopy (XPS) provides chemical stateinformation, and surface ionization mass spectrometry (SIMS) provides detailedinformation on the distribution of reaction products on the mineral surface.

Blowes et al. (1997) used optical and electron microscopy coupled withEDXA analyses and X-ray diffraction studies to identify the reaction productsfrom batch studies in which hexavalent chromium reacted with ZVI. Pratt et al.(1997) used XPS to determine the oxidation state in precipitates on the surfacesof ZVI grains taken from a column experiment in which Cr(VI) was treated usingZVI. The XPS results confirmed that chromium on the iron surfaces was exclu-sively in the Cr(III) oxidation state. Auger electron spectroscopy (AES) was usedto examine the structure of the (Fe,Cr) (OH)3 precipitates.

3.4 MATERIAL PERFORMANCE FACTORS IN CUTOFF WALLS

In contrast to PRBs, cutoff walls are used to block flow. Cutoff walls continueto be widely used as components in site remediation systems despite limitedresearch on their long-term performance and considerable uncertainty regardingtheir effectiveness.

A variety of materials can be used to construct cutoff walls. Inyang (1992)reviewed and summarized the recommended ranges of material characteristicsfor cutoff walls as presented in Table 3.13. SB cutoff walls have been and continue

FIGURE 3.27 Reductions in porosity in PRB as a function of Darcy velocity (5 years ofservice).

0.03

0.04

0.05

0.06

0.07

0.5

Entrance faceMid-planeExit face

Darcy velocity (m/d)

Poro

sity r

educ

tion

0.0 0.1 0.2 0.3 0.4


to be used widely in the United States, where barriers with a hydraulic conduc-tivity less than 1 × 10–7 cm/s are needed. Soil-cement–bentonite (SCB) cutoffwalls are also used, albeit much less frequently, where a wall with higher uncon-fined compressive strength is desired along with a hydraulic conductivity less

TABLE 3.13Recommended Ranges of Material Properties for Cutoff Walls

Parameter

Bentonite Slurry Cement–Bentonite Slurry

Freshly Hydrated

During Excavation

Freshly Hydrated

During Excavation

Density (g/cm3) (pcf) 1.01–1.04 (1,2) 1.10–1.24 (2) 1.03–1.4 (8) ≥1.12 (10)65 (3) 69–85 (4)

Apparent viscosity(seconds marsh) 38–45 (1,5) 38–68 (6) 40–45 (8) 38–80 (8)(centipose) –15 –15 (7) >130 (7)

Plastic viscosity <20a (7) — 9 (7) 30–50 (7,10)Filtrate loss (mL) <30 (7); range

15–30 (3)Range 15–70 (6); apparent average 40–60 (6)

100–300 (3,7)

pH 7.5–12 (6) 10.5–12 (6) 12–13 (7)Water content (% by weight)

–93–97 –78–82 (7) 76 (7) 55–70 (7)

Cement water ratio — — — 0.16–0.35 (9,10)

Bentonite content (% by weight)

4–7 (6)

Other ingredients (% by weight)

Sand ∼ 1 (3) Sand <5a (3) Cement 18 (7) —

Solids ∼ 2 (6) Solids 3–16 (6) Solids 15–30 (7)

30–45 (7)

Gel strengths10 seconds, Pascal 15 (7) 10 (7)10 minutes, Pascal 7–30 (6) –20–40 (6) 18 (7) 22 (7)10 minutes, lb/100 ft2

(24 dynes/cm2)5–15 (2) — — —

Strain at failure (%) — — ≥ 15 (9) —

References: (1) Case International Company, 1992; (2) Xanthakos, 1979; (3) Millet and Perez, 1981;(4) U.S. Army Corps of Engineers, 1976; (5) Guertin and McTigue, 1982; (6) Boyes, 1975; (7) Jefferis,1981; (8) Ryan, 1976; (9) Ryan and Day, 1986; (10) PCA, 1984.

a Specification for construction of tremie concrete diaphragm walls.

Source: Inyang, H.I. (1992). Selection and design of slurry walls as barriers to control pollutantmigration, Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency,Washington, DC.


than 1 × 10–7 cm/s. SCB cutoff walls essentially are SB cutoff walls with cementadded to increase the compressive strength of the backfill. Cement–bentonite(CB) cutoff walls are used occasionally in the United States where unconfinedcompressive strength is desired and a higher hydraulic conductivity is permissible(typically <1 × 10–5 cm/s). In Europe, the most common cutoff wall is acement–bentonite-slag (CB-slag) cutoff wall, which has substantial unconfinedcompressive strength and a hydraulic conductivity less than 1 × 10–7 cm/s afterabout six months of curing (Jefferis, 1981). Use of CB-slag cutoff walls hasbecome more common in the United States in recent years as well (Evans et al.,2002). Composite cutoff walls employing geomembranes in conjunction with SBor CB backfill are used only occasionally. These types of walls have not beenwidely embraced because of the increased cost and the regulatory acceptance ofconventional cutoff wall materials.

3.4.1 IN SITU HYDRAULIC CONDUCTIVITY

Beyond barrier material characteristics, several factors control the ability of cutoffwalls to contain contaminants in the field. The most significant of these factorsare wall defects and windows beneath the bottom of the wall. The genesis of awall defect is varied. In some cases, granular materials can cave into the slurryduring wall construction, thereby creating permeable zones in the wall. In othercases, prevalent in dry climates, seasonal or artificially induced fluctuations inthe water table around walls can facilitate desiccation-induced cracking of pre-viously submerged wall portions. Cracks and fissures can develop and lead to thefluid flow patterns depicted by Bai et al. (1996) in Figure 3.28 when the watertable rises again.

Demonstrating that a cutoff wall meets its objectives as a flow barrier remainsa key unresolved issue, even though studies have shown that a few permeabledefects can have a significant impact on cutoff wall effectiveness (Tachavises andBenson, 1997; Lee and Benson, 2000). For example, Tachavises (1998) evaluatedthe importance of hydraulic defects in cutoff walls using a 3-D groundwater flowmodel (Figure 3.29). A horizontal wall having a breadth (WSB) of 500 m andthickness of 1 m was placed in the center of a permeable 40 m thick aquifer(hydraulic conductivity, KA = 10–4 m/s) underlain by a tight confining unit (hydrau-lic conductivity, KC = 10–10 m/s) 30 m thick. The regional gradient (iREG) in theaquifer was assumed to be 0.001 and the hydraulic conductivity of the wallbackfill (KSB) was assumed to be 10–9 m/s. The domain was made 3000 m wideand 1500 m long to prevent the boundaries from influencing the solution.

Small permeable windows were placed in the cutoff wall to evaluate howthey influence wall effectiveness (EW), defined as the groundwater flow ratethrough the portion of the aquifer containing the wall before the wall was placed(QAQW) divided by the groundwater flow rate past the wall (QAQW), i.e., EW =QAQW/QW. Walls that are more effective have higher values of wall effectiveness,and walls that have no impact on groundwater flow have an effectiveness of 1.0.Wall effectiveness is shown in Figure 3.30 as a function of the area of the window


(Aw) relative to the cross sectional area of the wall (A). For the scenario that wassimulated, EW = 100 for a wall without windows (i.e., the wall reduced flowwithin its breadth by a factor of 100), the effectiveness dropped appreciably asthe area of windows increased. If windows comprise more than 1% of the areaof the wall, the cutoff wall is rendered completely ineffective (Ew = 1).

Despite the dramatic effect that small defects can have on the overall effec-tiveness of a cutoff wall, the ability to test a completed cutoff wall as a systemis limited. The overall integrity of a wall is usually extrapolated based on datafrom a series of measurements obtained in the laboratory on small specimensprepared from disturbed samples collected during construction. Undisturbed spec-imens are tested in some cases, and on occasion field tests are conducted. Furthercomplicating the issue is the ill-defined state of stress in cutoff walls. Neverthe-less, inferences based on even the best testing methods can be misleading if themethod provides a point measurement of hydraulic conductivity rather than theoverall hydraulic conductivity of the wall.

An accepted procedure for measuring the overall hydraulic conductivity of acutoff wall has not been developed because of several complicating issues. Cutoffwalls are often very long and enclose a huge volume of the subsurface. In addition,the environment on both sides of the cutoff wall often is contaminated and leakageinto the containment system can come from the underlying floor (e.g., aquitard

FIGURE 3.28 Conceptual patterns of fluid flow through fractured media. (Adapted fromBai, M. et al., 1996. ASCE Journal of Environmental Engineering, 122(5), 416–423.)

Fracture

Matrix

Matrix

Fracture

Matrix

Matrix

(a) Matrix diffusion (b) Matrix replenishment


into which the wall is keyed) or from the overlying cap, which confounds howmuch water is actually passing through the wall. The drainage of aquifer materialsduring a pump test can also confound the volume of water passing through thewall. As a result of these complexities, methods to verify the overall hydraulicconductivity of cutoff walls have largely been unsuccessful.

One large-scale method that provides an indication of overall hydraulic con-ductivity is the in situ test box. A box-shaped loop is constructed in the wall withone side of the box forming part of the actual wall. A well is then set within thebox for extracting or injecting water, and piezometers are placed inside andoutside of the box to measure groundwater levels. Pumping is continued untilequilibrium is established, and then the overall hydraulic conductivity is computedfrom the measured water levels, flow rate, and box geometry. Several months oflow flow pumping may be required until equilibrium is established. The test boxshould be of sufficient size (at least 5 m by 5 m) to represent a typical wall sectionand reduce the potential for slurry to plug pores in the box interior. The top ofthe box may need to be capped to prevent groundwater infiltration. Leakage fromthe floor still remains a potential confounding issue with this method.

FIGURE 3.29 Schematic of 3-D model used by Tachavises (1998) to evaluate the effectof defects on the effectiveness of groundwater cutoff walls.

Groundwater passing through aquifer and around wall

Aquifer (KA)

Confining layer (KC)

40 m

30 m

Groundwater focusing on the wall

Cutoff wall

No flow


3.4.2 DESIGN CONFIGURATION

Another important factor that can significantly influence cutoff wall effectivenessis the integrity of the key into the underlying floor or aquitard. A risk alwaysexists that a wall is not properly keyed because of local variations in the soilprofile, errors in measuring the trench depth, or poor assessments of the penetra-tion depth into the aquitard. Independent monitoring of wall depth and excavationmaterials must be made during construction to ensure that an appropriate key isachieved. Tachavises (1998) used his 3-D flow model to evaluate a scenario wherea portion of the wall was unkeyed, forming a gap between the bottom of the walland the top of the aquitard. The gap was assumed to be filled with aquifer material.Gaps of different widths (WG) and heights (LG) were evaluated. Some typicalresults are shown in Figure 3.31, which depicts wall effectiveness (EW) as afunction of gap thickness (LG) and the ratio of gap width relative to wall width(WG /WSB). Even if the bottom of the wall is close, but not keyed into the confiningunit, the wall can be practically ineffective. For example, a 50-mm gap betweenthe bottom of the wall and the top of the confining unit can reduce the effectivenessfrom 100 to nearly 2. Even narrow zones that are poorly keyed can reduce cutoffwall effectiveness. In particular, missing keys reduce effectiveness appreciably

FIGURE 3.30 Wall effectiveness as a function of relative area of a fully penetratingpermeable window. (From Tachavises, 1998. Flow rates past vertical cut-off walls: influ-ential factors and their impact on wall selection. Ph.D. dissertation, University of Wiscon-sin–Madison. With permission.)

1

10

100

1000E W

= Q

AQW

/QW

KA = 10–4 m/s

KC = 10–10 m/s

KSB = 10–9 m/s

KW = KA

No window

0.0001 0.01AW/A (%)

1 100


unless the unkeyed region comprises less than 0.1% of the wall and the gapbetween the base of the wall and the confining unit is narrow.

Despite analyses such as those reported by Tachavises (1998), poor keys area common problem afflicting groundwater cutoff walls. The following case historyfrom Benson (2002) provides an example. A SB cutoff wall was installed in thewestern United States to isolate a lagoon from surrounding groundwater. Thelagoon and wall were installed in alluvium consisting of sands and gravelsoverlain with a thin fine-grained surface layer. The wall, which had a thicknessof 0.6 m and backfill with a hydraulic conductivity of 5 × 10–7 cm/s, wasconstructed along the perimeter (1.9 km) of the lagoon. Specifications for theproject required that the bottom of the wall be keyed 1 m into the underlyingbedrock, which was comprised of inter-bedded highly plastic claystone and sand-stone. The lagoon was constructed by excavating the alluvium to the underlyingrock. The thickness of the alluvium ranged from 7 to 10 m.

After the lagoon was completed and the dewatering system was removed,excessive leakage became readily apparent. A pump test was conducted to deter-mine the seepage rate past the wall. A variable-speed pump was installed in thelagoon, and the pumping rate was adjusted until the pump discharge was sufficientto maintain a constant water level in the lagoon. The leakage rate was determinedto be 1000 m3/day or approximately 0.06 m3/day/m2-wall. For unit gradientconditions, this flow rate corresponds to a hydraulic conductivity of more than100 times the hydraulic conductivity of the backfill.

FIGURE 3.31 Wall effectiveness as a function of size of the gap between the base of thewall and the top of the confining unit. (From Tachavises, 1998. Flow rates past verticalcut-off walls: influential factors and their impact on wall selection. Ph.D. dissertation,University of Wisconsin–Madison. With permission.)

1

10

100

1000

100WG/WSB (%)

E W =

QAQ

W/Q

W

No gap

1

LG (m)

KA

KC

Transverse section

KSB LG

iREG

KG

KA = 10−4 m/s

iREG = 0.001 KC = 10−10 m/s

KSB = 10−9 m/s KG = KA

Longitudinal section

WG 30 m 30 m

30 m

40 m

WSB WM

0.225

0.125

0.05

0.01 0.1 1 10


A forensic investigation was undertaken to determine the source of the exces-sive leakage. Paired piezometers were installed, additional pumping tests wereconducted, and drilling was performed to define the vertical extent of the wall.Undisturbed samples of the underlying rock were also collected for hydraulicconductivity testing. Results of the tests showed that the hydraulic conductivityof the sandstone was approximately 2 × 10–4 cm/s, whereas that of the claystonewas approximately 3 × 10–9 cm/s.

Results of the forensic investigation pointed at the key as the source ofleakage. A cross section obtained from the drilling program is shown in Figure 3.32.This cross section is typical of the wall condition. Most of the wall bottom restsin the permeable sandstone or alluvium rather than the relatively imperviousclaystone. Analysis of the entire cross section showed that 48% of the wall wasnot keyed into the claystone. Based on the curves shown in Figure 3.31, excessiveleakage rates are anticipated for this wall. For LG = 1 m and WG/WSB ≈ 50%, thewall effectiveness is approximately 1.3.

3.4.3 GEOSYNTHETICS IN VERTICAL CUTOFF WALLS

The use of geosynthetic materials, particularly geomembranes in slurry trenchcutoff walls is relatively new in the United States, although it has been more

FIGURE 3.32 Cross-section showing stratigraphy and location of bottom of trench alongthe alignment of the cutoff wall. SC = clayey sand, sand-clay mixtures; CH = fat clay,inorganic clays of high plasticity; GW = well-graded gravels, gravel sand mixtures, littleor no fines; SP = poorly graded sands, gravelly sand mixtures, little or no fines; CL = leanclay, inorganic clay of low to medium plasticity, gravelly clays, sandy clays, silty clays;SW = well-graded sand, gravelly sands, little or no fines; GP = poorly graded gravel,gravel-sand mixtures, little or no fines; SM = silty sands, sand-silt mixtures.

SandstoneSandstone Sandstone

SP

GW, SP

CHSC

Elev

atio

n (m

)

565

560

555

550

545

STA

.1

+ 30

7 m

STA

.1

+ 49

2 m

STA

.1

+ 57

3 m

STA

.1

+ 69

4 m

Groundsurface

Bottom oftrench

Sandstone

ClaystoneClaystone

Claystone,Silty-claystone

Claystone,silty-

claystone

Silty-claystone

GW

CLSW

SW

SW

SW

SPSP

GP

GWGP

SM

SM

SM

SM

SW

SW-SP

SPCL

CL, SC

GW

SP


widely used in Europe. The inclusion of a geomembrane sheet in cutoff walls isdriven by the need to enhance the factor of safety against the hydraulic effectsof construction-induced and service-related flaws that often develop in SB, SC,CB, SCB, and other backfilled materials in which soil is a principal component.Construction flaws generally enhance cutoff wall permeability to fluids at specificlocations such that a wide variability can exist in the spatial distribution of thepermeability magnitudes across the wall. The high permeability zones can begenerated by any or combinations of the following mechanisms:

• Collapse of coarse-grained wall materials into the trench during con-struction or backfilling operations

• Accumulation of sand or debris at the bottom of the slurry such thatthe wall is not properly keyed into a basal low permeable stratum

• Poor and variable mixing of backfill resulting in permeability zonationin the backfilled barrier material

• Existence of large aggregates of rocks or objects in the backfilledmaterials

During service, fluctuations in water table elevation around a cutoff wall canproduce cycles of desiccation and saturation that cause wall cracks.

Geomembrane sheets can bridge the flawed sections of the wall such that theflow characteristics of the composite wall are more uniform spatially. Most ofthe geomembranes that are used in vertical walls are compositionally thick(approximately 2.5 mm) HDPE, the long-term durability of which is discussedin Section 3.3. The geomembrane is usually emplaced as panels and made tointerlock into continuous sheets using various optional connections. The designdepth of each wall is the primary determinant of the installation method. Koernerand Guglielmetti (1996) summarized common installation techniques (Table 3.14).In general, cutoff walls that include geomembranes are expected to perform betterthan soil and cement walls because of the lower permeability of geomembranesto fluids and greater resistance to chemical attack in most cases.

3.4.4 PERMEANT INTERACTION EFFECTS

There are no standard methods for determining or evaluating the longevity ofcutoff wall materials. Some work has been done to evaluate the effects of chemicalincompatibility, but most of this work has been conducted over time frames thatare too short to provide a realistic assessment of the long-term effects thatcontaminated groundwater can cause in cutoff wall materials. In addition, limitedstudies have been conducted on other mechanisms that might cause long-termdegradation of cutoff wall materials (e.g., wetting and drying, frost action, dif-ferential settlements and distortion). Analyzing groundwater quality data collectedadjacent to in-place walls has been suggested as a method of assessing long-termcutoff wall performance. However, the complexity associated with most systems,which often integrate caps, floors, and a cutoff wall, usually prevents drawingdefinitive conclusions regarding field performance from groundwater quality data.


The effects of many chemical permeants may not be evident until many yearsafter installation. In some cases, an initial reduction in hydraulic conductivitymay occur, but then it is usually followed by an increase at much longer times.The long-term effects of chemical interactions can be illustrated by analyzing thecutoff wall as a one-dimensional, two-compartment plug-flow system as illus-trated in Figure 3.33a (Jefferis, 2001). The compartments are separated by areaction front and correspond to sections of the wall that have been affected andunaffected by chemical permeation. The upstream compartment is assumed to bein chemical equilibrium with the site groundwater and has a hydraulic conduc-tivity of kr. The downstream compartment is ahead of the reaction front, and itshydraulic conductivity (ku) is representative of the as-built condition. The overallhydraulic conductivity (ko) is the thickness-weighted harmonic mean of kr andku. The velocity of the reaction front is proportional to the average hydraulicgradient across the wall and ko and is inversely proportional to the retardation

TABLE 3.14Current Installation Methods for Geomembrane Vertical Walls

Method No.

Method or Technique

Geomembrane Configuration

Trench Support

Typical Trench Width

mm (in)

Typical Trench Depth

mm (in)

Typical Backfill

Type

1 Trenching machine

Continuous None 300–600 (12–24)

1.5–4.5 (5–15)

Sand or native soil

2 Vibrated insertion plate

Panels None 100–150 (4–6)

1.5–6.0 (5–20)

Native soil

3 Slurry supported

Panels Slurry 600–900 (24–36)

No limit, except for trench stability

SB, SC, CB, SCB, sand, or native soil

4 Segmented trench box

Panels or continuous

None 900–1200 (36–48)

3.9–9.0 (10–30)

Sand or native soil

5 Vibrating beam

Panels Slurry 150–220 (6–9)

No limit SB, SC, CB, or SCB slurry

Source: After Koerner, R.M. and Guglielmetti, J.L. (1996). In Rumer, R.R. and Mitchell, J.K. (Eds.),Assessment of Barrier Containment Technologies, National Technical Information Service, Springfield,VA, pp. 95–118.


factor and the porosity of the wall. The effects of diffusion and rate limitationson ion exchange are ignored.

This two-compartment model was used to create a set of curves relating overallhydraulic conductivity to time of permeation for different values of the ratio kr /ku

(Figure 3.33b). A key feature of these curves is that, for any reaction that signif-icantly increases the hydraulic conductivity (e.g., kr /ku > 10), predicting the finalhydraulic conductivity is impossible until the reaction front has passed completelythrough the barrier. Thus, short-term data from laboratory tests or in situ monitor-ing programs cannot be used exclusively as an indicator of long-term conditions.

Another aspect of chemical interactions with barrier materials in situ that hasreceived little attention is volume change, although this phenomenon has beenstudied under batch conditions in the laboratory (Chen et al., 2000; Murray andQuirk, 1982). Reactions that cause barrier material expansion are likely to beresisted by passive resistance provided by the surrounding soil, but shrinkage maybe more significant as it can lead to the opening of cracks that transmit preferentialflow. Unfortunately, small-scale laboratory tests are poor indicators of the effectsof cracking. Further work is needed in this area, preferably at field scale.

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FIGURE 3.33 Schematic of two-compartment model and change in hydraulic conductiv-ity of cutoff wall over time as contaminants react with backfill material.

Permeation time/ Time for full reaction, t/tf,

10−4

10−3

10−2

10−1

1

10

102

103 1000

100

51

0.001

0.01

0.10.5

10

Direction ofgroundwater flow

Lkο

kr

ku

X

(a) (b)

kr/ku

Ove

rall

perm

eabi

lity/

unre

acte

d pe

rmea

bilit

y, k ο

/ku

104

0 0.2 0.4 0.6 0.8 1 1.2


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209

4 Airborne and Surface Geophysical Method Verification

Prepared by*

Ernest L. MajerLawrence Berkeley National Laboratory, Berkeley, California

4.1 GEOPHYSICAL METHOD APPLICATION AND USE

The complexity of using geophysical and remote sensing methods for hazardouswaste containment transcends the already challenging problems associated withmineral exploration and groundwater and petroleum exploration and production.Hydrologists and petroleum reservoir engineers have studied the flow of water,oil, and gas in porous permeable rocks and unconsolidated sediments for manyyears. The oil industry has developed first-order methods of analysis that areremarkably successful in assessing the potential of an aquifer or reservoir tosupply a given fluid or gas for some period of time. However, these analysesseem almost trivial compared to the task of finding, monitoring, and removingsubsurface contaminants. In terms of monitoring barriers the task may or maynot be as challenging as finding and characterizing subsurface contaminants. Thisis due to several different issues specific to barriers. If one is trying to see achange in the properties of a barrier it is not as challenging as seeing absolutechanges. If one is trying to characterize or find a leak in the barrier this may bejust as difficult as finding a contaminant. The issue is particularly challengingbecause of the following:

* With contributions by Randolph J. Cumbest, Westinghouse Savannah River Company, Aiken, SouthCarolina; Bruce Davis, National Aeronautics and Space Administration, Stennis Space Center, Mis-sissippi; William E. Doll, Oak Ridge National Laboratory, Oak Ridge, Tennessee; Leland Estep,Lockheed Martin, Midland, Texas; Susan S. Hubbard, Lawrence Berkeley National Laboratory,Berkeley, California; John D. Koutsandreas, Florida State University, Tallahassee, Florida; David P.Lesmes, Boston College, Chestnut Hill, Massachussetts; H. Frank Morrison, University of California,Berkeley, California; Lee D. Slater, University of Missouri at Kansas City, Kansas City, Missouri;Anderson L. Ward, Battelle Pacific Northwest Laboratory, Richland, Washington; Chester Weiss,Sandia National Laboratories, Albuquerque, New Mexico.


In traditional oil and gas subsurface applications, a 50% recovery rate isconsidered a great success. The great majority of geophysical and remote sensingmethods were developed with this level of sensitivity. In remediation applications,this recovery rate is usually not sufficient.

Although oil and gas applications are multi-phase, the variations in the prop-erties are not as large as in near-surface, partially saturated systems encounteredin the vadose zone or even in saturated environments (i.e., groundwater contam-inants can be particles, chemicals that dissolve in water, or liquids or gases thatare only partially soluble in water). Under certain conditions, some contaminantscan move through unsaturated soils and rocks as vapor. Contaminants can alsointeract strongly with the minerals in the subsurface. Clays can absorb somecontaminants while some may form chemical complexes with other groundwaterchemicals. Immiscible dense liquids can settle vertically, while some may becomenutrients for microbes that are present naturally or have been introduced. All ofthese interactions may or may not affect the geophysical signals.

A variety of methods exist that could be classified as geophysical techniques;however, this chapter focuses on geophysical methods that are used to infervolumetric (average over a volume of material rather than at a point) rather thanpoint properties, i.e., crosshole, surface, and surface to borehole methods ratherthan well-logging techniques which usually only measure a few centimeters to ameter away from the borehole. The methods are assumed to be applied from thesurface and boreholes or by placing sensors and/or sources in or near the barriers,thus imaging the volume or planes between the surface and borehole, the volumefrom the surface to the borehole, or a volume from the surface to a reflector orother target in the subsurface. Last but not least, two main applications areassumed with respect to barriers: (1) the initial and subsequent characterizationof the subsurface volume to be contained, and (2) the verification of the integrityand performance of the barriers. These issues are linked and must be addressedto validate overall system performance.

4.1.1 CHARACTERIZATION AND GEOPHYSICS

A simple definition of characterization is mapping the distribution of contaminantsources and effluents as well as the physical, chemical, and biological propertiesof the subsurface materials that control their distribution, concentration, andmovement. Some of the physical properties required are lithology, fault/fractureproperties, porosity, permeability, grain size, and fluid type and saturation. Rockor soil types, mineralogy and distribution, and types of clay minerals are alsoneeded to model chemical processes. Chemical state, temperature, fluid satura-tion, and other factors that affect the presence and amount of nutrients are alsoneeded to determine microbe behavior. Characterization as defined here is theessential first step toward containment and/or remediation, but all too often theterm is used only to describe the extent of the contamination itself, usually over

Airborne and Surface Geophysical Method Verification 211

a small area or volume that is relatively small compared to the entire groundwatersystem in which it resides. This concept of total system characterization is criticalin containment applications because, as will be seen, the application of geophys-ical methods for containment depends on detecting changes from background orinitial conditions. As a result, characterization efforts are currently often limitedto determining the nature and extent of the toxic materials and not defining thewhole regime in which they are traveling, interacting, and evolving. This limiteddefinition can be useful in small-scale sites where the solution is excavation, butit is only half of the story at thousands of larger scale sites. The additional conceptthat the distribution of properties and processes should also be characterized isjust now being incorporated into idealized or conceptual models of hypotheticalsites in anticipation of when actual site data permit contaminant fate and transportsimulation and eventual remediation. Only in the last five years have geophysicalmethods been used to measure the spatial distribution of the properties at actualsites to provide constraints for ground water models in a quantitative sense(Hubbard et al., 2001, 2003; Grote et al., 2003). If the subsurface were uniformor even uniformly layered, drilling on a loose grid of holes would probably sufficeto characterize the site. Unfortunately, the subsurface is generally heterogeneous,and a program based on drill-hole samples and measurements would provideincomplete or, at worst, misleading information. Thus, volumetric information(information connecting the actual points of measurements) is needed.

Geophysical methods are needed to: (1) provide the spatial distribution ofcertain physical properties that are essential for site characterization; (2) map thedistribution of some contaminants; and, in some cases, (3) detect chemicalchanges associated with contaminant interaction with the subsurface and barriers.Indeed, a useful definition of applied geophysics is that it is the science of usingphysical measurements or experiments on the surface (or from boreholes drilledfrom the surface) to determine the physical properties and processes in thesubsurface. Geophysics is ideally suited for extrapolating measurements obtainedfrom a borehole to the large-scale volume away from the borehole (Peterson et al.,1985; Parra, 1991; Krohn, 1992; Sheets and Hendrickx, 1995; Majer et al., 1997).In this application, geophysical measurements obtained from the surface orbetween boreholes can be used to assess the continuity and homogeneity of theintervening material. Geophysics can also serve to map the subsurface in theabsence of boreholes and can be used to detect the unexpected such as a changein lithology, fractures, or fast paths (Leary and Henyey, 1985, Davis and Annan,1989, Hendrickx et al., 2002, Hubbard et al., 2002, 2003). Failure to be aware ofsuch gross heterogeneity has a major impact on hydrologic flow models andcontaminant transport (Majer et al., 1997). Finally, geophysical methods couldbe used to delineate contaminants if the waste was buried in containers becausethe waste containers produce a geophysical anomaly or the waste alters theproperties of the medium (Doll et al., 2000). Table 4.1 shows the different reso-lution of the seismic and electrical methods and their expected use and application.


4.1.2 PERFORMANCE MONITORING AND GEOPHYSICS

An important need for geophysics is for monitoring the processes that are imple-mented to remove, contain, or treat contaminants. In the case of containments,the ability of geophysical methods to monitor the emplacement and performanceof the barriers primarily depends on the geophysical contrasts of the barrier andsubsurface. However, in some cases, even though the barrier does not look anydifferent than the surrounding properties, geophysics could possibly monitorchanges in the barrier properties relative to the native materials, monitor flow

TABLE 4.1Possible Surface Geophysical Methods for Verification of Subsurface Barriers

Method Purpose Success CommentsExpected

Resolutiona

Surface MethodsSeismic Host

characterization, caps and walls

Fair Use for structure and lithology of interior

0.5–5 m

Electrical (electromagnetic, induced polarization, self potential, DC resistivity)

Host characterization, caps and walls

Good Fluid content and conductivity

1.0–10 m

Radar Host characterization, caps and walls

Good Water content and lithology

0.5–2.0 m

Borehole MethodsRadar zero off-set (ZOP) velocities

Barrier detection Excellent Processed for differences

0.25 m

Radar tomographic velocity Barrier detection Excellent Processed for differences

0.25 m

Radar tomographic amplitudes

Barrier detection Excellent Processed for differences

0.25 m

Radar well-to-well reflection

Barrier detection Poor Low signal-to-noise ratio

Electrical resistance tomography

Barrier detection Good 0.5 m

Electrical resistance tomography

Leak detection Excellent Differences during salt water flood

0.25 m

Seismic ZOP and tomography

Barrier detection Poor Injected air destroyed signal

a Estimated only for successful borehole methods.


paths within the contained zone, and/or detect processes occurring due to thepresence of contaminants. Once a site has been characterized and modeled anda remediation process designed and implemented, it is necessary to assess theeffectiveness of the remediation operation. Geophysical methods are ideallysuited to this task, because it is often easier to monitor changes in some portionof the subsurface than it is to uniquely determine the subsurface propertiesthemselves, i.e., time-lapse monitoring (Dailey and Ramirez, 2000). An exampleof time-lapse data is given in Figure 4.1. This is a plan view of a site wheremoisture monitoring is performed by observing the changes in signals fromground-penetrating radar (GPR) (Grote et al., 2003). As seen in the differences

FIGURE 4.1 Comparison of volumetric water content estimates obtained from 900-MHzcommon off-set GPR ground wave data during two different times of the year over a naturalfield study site. These images reveal a persistence of near-surface water content spatialdistribution at the site, which was interpreted to be controlled by near-surface soil texture.

Vine

num

ber

60900 MHz: Time 1

900 MHz: Time 2

WET

DRY

WET

DRY

40

20

012

m

30 m

155 105Row number

Row number

55

Vine

num

ber

60

40

20

0155

0.10 0.20Volumetric

watercontent

105 55


between the two plan views of the radar reflectivity, it is easy to determine wheremoisture changes occur.

Some of the information provided by geophysical methods is indirect, butthe parameters measured can be related to the rock/soil properties needed. Forexample, the distribution of electrical conductivity is not a parameter that isdirectly useful in hydrological modeling, but when conductivity is used to obtaininformation on porosity, saturation, pore fluid salinity, and clay content then itbecomes a vital parameter needed for characterization. The relationship betweenthe properties measured with geophysics and the hydrologic or mineralogic prop-erties is, in most cases, site-specific. To be effective, site characterization requiresclose integration of the geologic, hydrologic, chemical, and geophysical data.

4.1.3 GEOPHYSICAL METHODS FOR SITE CHARACTERIZATION AND MONITORING OF SUBSURFACE PROCESSES

The geophysical methods most directly applicable for characterizing and moni-toring hazardous waste sites can be divided into the following general categories:seismic; electrical and electromagnetic; natural field and magnetic (e.g., gravity,tilt); and remote sensing methods. These categories were chosen for the differentproperties that are fundamentally sensed.

Well-logging applications are considered here as point measurements and arenot included in the detailed discussions that follow. This is not to imply that welllogging should not be included in a geophysical program. The opposite is true.Well logging is fundamental to all databases and should be the rule, not theexception.

4.1.3.1 Seismic

Seismic methods are used to measure the distribution of elastic wave velocity(compressional and shear) and the attenuation of the different seismic waves inthe ground. Seismic velocity depends on many factors, but the primary factorsaffecting seismic measurements are porosity, mechanical compressibility, shearstrength, fracture content, density, fluid saturation, and clay content. Some ofthese parameters are directly related to important hydrologic properties and othersare used to map the distribution of soil and rock types. The most common useof seismic methods is mapping interfaces between materials of different seismicvelocities to provide high-resolution images of the locations of lithologic prop-erties and thus infer main flow channels and soil types. Cross-hole seismictomography is now used for petroleum reservoir characterization and will beequally important in hazardous waste site characterization.

4.1.3.2 Electrical and Electromagnetic

Electrical and electromagnetic methods are used to measure the distribution ofelectrical conductivity and the dielectric constant of the ground. Electrical con-ductivity of soils and rocks depends entirely on the conduction paths created by


fluids in the pore spaces and is determined by porosity, saturation, pore fluidsalinity, and clay content. In certain cases where the contaminants are ionicsolutions, the electrical conductivity directly maps contaminant distribution(Endres et al., 2000). However, in most cases, the conductivity is used to extrap-olate hydrologic measurements obtained from boreholes. The presence of claysthat is so important in fluid flow and chemical absorption models brings about adistinctive frequency-dependent conductivity — the induced polarization effect.This effect is of immense value in monitoring site remediation processes becausemany processes involve injecting materials that profoundly alter this effect (Slaterand Binley, 2003).

A separate electrical property of soils and rock is the streaming potentialeffect, which is but one aspect of a whole class of interactions called coupledflow phenomena. Basically, driving forces of temperature gradients, hydraulicpressure gradients, chemical potentials, and voltage gradients produce flows ofheat, fluid, chemicals, and electric current (Slater and Binley, 2003). These flowsare coupled in the ground in the sense that not only does a pressure gradient producea fluid flow but it also produces an electrical current flow — the streaming potential.

Similarly, temperature gradients drive currents to produce thermoelectriceffects. Another cross-coupling term of immense potential in contaminant studiesis electro-osmosis, which is a flow of fluid produced by a voltage gradient. Thisphenomenon has been used in geotechnical engineering applications to stabilizeembankments and assist in pile driving. It could be used to alter subsurface flowpatterns by directing a particular contaminant plume to an extraction or treatmentregion. Because electro-osmosis depends on fluid conductivity, rock permeability,and the configuration of the imposed voltage gradients, the site must be wellcharacterized in fluid conductivity and permeability before the design of a prac-tical system can be implemented.

4.1.3.3 Natural Field and Magnetic

Natural field methods consist of gravity, magnetic, and tilt methods. High accu-racy measurements of gravity over the surface of the Earth (i.e., microgravitysurveys) yield a measure of the subsurface density distribution, which, in turn,depends on the distribution of porosity, water content, and rock type. Boreholegravity measurements yield direct average volume values of density. Similarly,high accuracy measurements of magnetic field can be used to infer the distributionof magnetic minerals, usually magnetite, which, in turn, is related to rock typeand certain sedimentary depositional environments where heavy minerals settleout of fluid flows. Tilt measurements have recently been used to measure defor-mation associated with fluid withdrawal and injection. By monitoring the rate oftilt or deformation, the rate of fluid movement can be inferred and an averagepermeability for the formation can be determined. Tilt and strain methods arelow resolution, but for near-surface application they can be of some use in barriermonitoring. If gross changes in the density or geometry of the barrier changeson the order of a few percent, then these methods may be applicable. The drawback


to achieving the necessary resolution is the installation of the gravity meters ortilt meters. Careful attention to stability and repeatability of the data must bemaintained in addition to thermal stability and leveling. General directions offluid movement, steam injections, or other density changes can also be monitored.

In magnetic surveys, the distribution of the magnetization of the earth ismeasured from the surface, but these methods usually lack resolution for detailedsubsurface studies. Borehole magnetometers are now being used to supplementmore conventional well-logging tools to search for lithologic changes and chem-icals/minerals that cause magnetization to change.

4.1.3.4 Remote Sensing

Remote sensing is defined as the noninvasive observation of natural phenomena.It involves collecting information about an object by detecting differencesbetween the object and the surroundings without being in physical contact withthe object of observation. The differences that can be detected between objectsof interest and their background involve shifts in various fields as observationmoves from the background to an object of interest. Electromagnetic, acoustic,potential, and radiological are typical fields sampled by remote sensors for objectdetection. These types of sensors mounted on spaced-based (satellite) or airborneplatforms can be used to rapidly and noninvasively characterize and monitorfeatures and events on the earth’s surface with broad coverage and high resolution.

Space-based or airborne hyperspectral, thermal, radar, and/or radiation sensorscan provide a cost-effective alternative to traditional approaches. The spatiallysynoptic look achieved by remote sensing methods can improve the accuracy ofarea interpolations generated by point-sampled data. Ideally, the characterizationand monitoring of waste sites and their containment systems would includeremote sensing data, ground-based geophysical measurements, and point-sampleddata. These data streams could then be integrated in a geographic informationsystem (GIS) database with ancillary data concerning the barrier construction,geology, watershed hydrology, and climatology of the site.

4.2 SPECIFIC METHODS

Although each method has generally been described, there are subsets of eachmethod for specific applications. For example, seismic methods can be catego-rized further into active and passive methods, and even further into surface andborehole methods or some combination. Specific methods that are most applicableto environmental remediation needs are described below.

4.2.1 SEISMIC METHODS

Seismic methods can be divided into passive and active methods. Passive methodsinvolve listening to seismic energy being created by stress changes or naturalseismicity such as micro-earthquakes or acoustic emissions near the boreholes


or underground openings. Acoustic emissions for purposes described here are ofsecondary use. When monitoring a barrier, however, the barrier may emit acousticemissions if it is brittle and possibly failing. Monitoring would involve a simpleprocess of emplacing sensors in or near the barrier and monitoring for discreteevents above a certain threshold. Active methods involve introducing energy intothe ground with either an impact or controlled swept frequency source andobserving how the seismic waveforms change due to heterogeneity or anisotropyin the subsurface or barrier. Both the direct and reflected arrivals of seismic waves(i.e., travel time and amplitude) can be used for this process. More sophisticateduses can involve guided wave energy in the barrier either during emplacementor for monitoring. Seismic reflection methods are used extensively in the petro-leum industry for structural delineation and lithologic definition. New and sophis-ticated three-dimensional (3-D) surface and borehole methods have dramaticallyimproved imaging capabilities for the petroleum industry, and can potentially beapplied to remediation with proper instrumentation. The utility of seismic tech-niques also depends on the resolution obtainable in a given soil or rock type. Forthis reason, this discussion focuses on the seismic methods that have the highestresolution. Figure 4.2 shows the typical field configuration of a seismic surfaceand a cross-borehole configuration of a seismic survey. These configurations canbe generalized to other techniques such as radar and electrical methods. Knowingthe location of the source and receiver, the data can be inverted to derive theproperties of the earth.

A typical set-up of a surface geophysical survey (top image of Figure 4.2)consists of a source and receiver on the surface and documentation of the differentarrivals from the source. This example is typical for a radar or seismic survey(Hubbard et al., 2003). The bottom figure shows a typical example of a cross-borehole survey with different sources and receivers at different points so that atomographic and/or a reflection image between the boreholes is obtained.

The goal of seismic surveys is to describe or map the velocity and attenuationof seismic waves through the volume of interest. In general, this process is referredto as imaging, although the extent to which a complete or 3-D image can beformed depends on the availability of a suitable distribution of source–receivercombinations and the frequency content of the seismic waves. When a crosssection of seismic parameters can be determined, the process is also referred toas tomography. Surface methods depend on sources and receivers distributed onthe surface. Combined with sources and/or receivers in boreholes or the barriersthemselves, a true 3-D image can be formed. Figure 4.3 shows typical imagesfrom a surface radar survey and a cross-borehole tomographic survey. Shown arethe source and receiver pairs and the ray path coverage, very similar to seismicgeometry.

Seismic imaging could play an important role in site characterization, per-formance confirmation, and monitoring tasks. It could be used to estimate andextrapolate the extent and shape of soil property distributions that are measuredonly at discrete points with borehole methods. It can also be effectively used todetect features not mapped in the exploratory or initial phase of remediation and


to monitor changes in properties in the site area from measurements obtainedentirely outside the critical volume. The transmission and attenuation of seismicwaves through the subsurface depends on the elastic parameters, which dependon, among other things, the state of stress and strain, porosity, clay content, grainsize, and fluid saturation. As recent research shows, high frequency seismic wavepropagation is sensitive to discontinuities (fractures or joints) in the media (Majeret al., 1997). Seismic tomography can, therefore, be used to detect changes inthe soil column condition, locate major preexisting and new features, and measureoverall changes in the widths of these features. The methods that can be used forthese studies use sources on the surface and detectors either in a borehole [referredto as vertical seismic profiling (VSP)] or in cross-hole configurations with bothsources and receivers in boreholes. VSP techniques are primarily used for eluci-dating subsurface structures and determining seismic velocities of the variousrock and/or soil horizons. In addition to the more conventional uses of VSP, the

FIGURE 4.2 A typical set-up of a surface geophysical survey (top) where one places asource and a receiver and records the different arrivals from the source, this example isfor a radar or seismic survey (Hubbard et al., 2003). The bottom figure shows a typicalexample of a cross-borehole survey with different sources and receivers at different pointsso that one obtains a tomographic or reflection image between the boreholes.

Locationsof sources Locations

ofreceivers

0 1 2 3 4 5 6 7

0 1 2 3 4 5 6 7

7

6

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8

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Air wave

Criticallyrefracted

wave

Groundwave

Refracted wave

ε1

ε2

ε1 > ε1

Reflectedwave

AirTX RX

Example of tomographic data acquisition geometry


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use of three-component VSPs for detecting and characterizing 3-D features hasbecome routine in the oil industry.

In the last several years, the petroleum and gas industry have started to extendthe traditional uses of subsurface imaging from defining static properties tomapping changes in the reservoir conditions and monitoring production. Toachieve accurate monitoring for the petroleum industry, new methods using multi-component (P- and S-wave) seismic surveys have been developed to map sub-surface anisotropy and heterogeneities from the surface and between boreholes(Daley et al., 1988a,b; Majer et al., 1988, 1997). The key to using the data,however, is the ability to relate the physical parameters measured using geophys-ical techniques to the parameters of interest to the hydrologist or reservoir engi-neer. An example is the relationship of seismic velocity to permeability. Frompast work in a variety of complex lithologies (Majer et al., 1988; Majer and Geller,1992; Tura et al., 1992; Tura and Johnson, 1993; Geller and Myer, 1995; Hubbardet al., 2001; Geller et al., 2000), recent advances in wave propagation theory(e.g., shear wave splitting, fracture stiffness, guided waves, scattering, cross-wellseismic reflection, amplitude and frequency variation with azimuth) must beintegrated into the techniques employed in the petroleum industry and geotech-nical fields to fully utilize the potential of seismic techniques at any scale. Theconventional field and analysis techniques [e.g., lower frequency VSP and surfacereflection less than 100 hertz (Hz)] do not detect thin features such as fracturesor steeply dipping or near vertical faults, low velocity zones, zones of small orhigh seismic velocity contrasts, not to mention resolution on the scale to charac-terize process behavior.

To a large degree, the information contained in the cross-well/tomographictechniques offers promise of higher resolution, especially if more than first arrivalanalysis is performed, and the elastic solution as well as the acoustic case areincluded (i.e., S and P waves). Frequency effects must be investigated especiallywhen layered complex media exist. Using seismic tomography/cross-well tech-niques as a tool for resolving heterogeneity within bedded and fractured structuresremains in development. In terms of processing/inversion schemes for high-frequency seismic data, the following four main approaches are possible:

• Conventional and advanced ray and waveform tomography• Guided/channel waves• Scattered and reflected energy from voids/high contrast anomalies• Cross-well/VSP/single well imaging employing azimuthal frequency

and time-varying effects

4.2.1.1 Conventional and Advanced Ray and Waveform Tomography

Like most inverse problems, the quality of the solution depends directly on thecompleteness and accuracy of available solutions to the forward problem. Con-ventional and advanced ray and waveform tomography include such simple


approaches as algebraic reconstruction tomography (ART), simultaneous iterativereconstruction tomography (SIRT), and singular value decomposition (SVD)using first arrival data. Given sufficient data quality, these methods may be allthat are necessary. Ray and waveform tomography approaches also consider moreadvanced analysis methods such as waveform tomography using exact and Fresnelapproximations and amplitude tomography as well as ensemble averaging tech-niques. Conjugate gradient methods that can handle complicated structure andlow velocity/high contrast zones can also be considered.

4.2.1.2 Guided/Channel Waves

Guided wave continuity logging is emerging as a new tool in the oil and gasindustry (Krohn, 1992; Nihei et al., 1999), and it likely will evolve into a powerfulmethod for shallow subsurface environmental characterization (Liu et al., 1991).For example, the complex geometry and fracturing of the basalts at the IdahoNational Engineering and Environmental Laboratory (INEEL), Idaho, may sup-port Rayleigh interface waves that propagate along horizontal fractures (Gu et al.,1996), and a new type of channel wave that propagates in the fluid-saturatedrubblized zones on the tops and bottoms of the flows. Unlike body waves thatspread in three dimensions, channel waves are confined by the structure into twodimensions, resulting in less geometric spreading. Recent results by Nihei et al.(1999) support that channel waves can play an important role in the attenuationmechanism of seismic energy, thus being a diagnostic of fracture properties.Therefore, these waves can be used to probe geologic structures between wellsspaced over substantial distances.

4.2.1.3 Scattered and Reflected Energy

The third approach to consider is using scattered energy, particularly for detectingvoids and high-contrast heterogeneity. As in the case of guided wave analysis,scattered wave field analysis needs full waveform data as opposed to only arrivaltimes and amplitudes. This approach remains in the theoretical stage; practicalapplication, although very powerful, is still not routine. The exact solution forscattering elastic waves by a homogeneous spherical obstacle is available andincludes a complete analytical treatment of the problem and the implementationof the results in stable efficient computer codes (Korneev and Johnson, 1993a,b,c).The solutions were developed for incident P and S waves of arbitrary frequencyand for obstacles having arbitrary properties, including the cases of solid, fluid,and empty obstacles. While a sphere may not be an accurate representation ofmany of the underground structures of interest, the solution to the problem ofscattering by a sphere has fairly general applicability. A possible route of inves-tigation could be the numerous advances obtained for this type of problem, whichare an extension of the elastic inversion method found in Tura et al. (1992) andTura and Johnson (1993). (This last paper contains a list of related work.) Aninvestigation of the reliability of solutions to the inverse scattering problem could


make use of the developments in general inverse theory that are found in Vasco(1993) and Vasco et al. (1993).

4.2.1.4 Cross-Well/VSP/Single Well Imaging

Last but not least, cross-well/VSP/single well reflection methods are fairly newapproaches, where reflection-processing methods developed for surface reflectiontechniques are used to image reflectors between and possibly below boreholes.These methods are applicable in layered sections with good impedance contrasts.However, if sufficient well coverage exists, a 3-D approach with varying azi-muthal coverage using three-component data can provide useful information onmedia complexity, especially in fractured media.

In the cross-well method, the source is activated at various levels in one holeand the receiver is placed at similar levels in the other hole, creating a crossinggrid of ray paths for tomographic inversion. Usually in the radar and seismiccases, the first arrival times for each source-receiver pair are used for a tomo-graphic image. The two-dimensional cross section between wells is divided intosquare pixels and the velocity (in the seismic case) is estimated in each pixel.The resolution of each pixel is dependent on the ray density in the seismic orradar case (Peterson et. al., 1985) and on the frequency content in the electro-magnetic or DC resistivity. The data can also be inverted for attenuation. In thisanalysis, the amplitude of the first arrival is computed for each trace with sufficientsignal-to-noise ratio. The two-dimensional cross section between wells is thendivided into pixels, and each pixel is inverted for amplitude attenuation in decibelsper meter (dB/m). Cross-well seismic as well as radar surveys have been usedfor many years to tomographically image P-wave velocity between wells (e.g.,Mason, 1981; Peterson et al., 1985). More recently, cross-well S waves have alsobeen used to map S-wave velocity (Harris et al., 1995), and both P- and S-wavecross-well reflectivities have been analyzed for structural delineation. Until aboutfive years ago, nearly all cross-well seismic tomography was performed in sed-imentary formations important to oil and gas exploitation. A seismic source usedin the oil industry but not yet applied to environmental problems is the orbitalvibrator. The operating principle of the orbital vibrator is rotation of an eccentricmass in the horizontal plane at increasing speeds, generating a swept frequencysignal of clockwise and counter-clockwise polarizations (Daley and Cox, 1999).The orbital vibrator has a high frequency (now up to 750 Hz) and high power,is small (3.5 inches in diameter, 18 inches long), and puts out both P-wave andS-wave energy. It is easy to deploy and can work in fluid-filled holes. The orbitalvibrator propagated P waves up to 100 m in a fractured basalt aquifer (Daleyet al., 1999), significantly farther than a piezoelectric source used at the same site(albeit with a lower frequency band than the piezoelectric source). Tests usingthis source have been successful in acquiring P- and S-wave tomography datausing fluid-coupled hydrophone sensors. In the case of direct current (DC) resis-tivity, multiple electrodes are placed in the subsurface either in uncased holes orwith electrodes on the exterior of polyvinyl chloride (PVC) or fiberglass holes.


Each electrode acts as a source or receiver, making data collection very efficient.Electromagnetic sources and receivers have been developed and are in routineuse in the oil industry, but not efficiently downsized for the environmental field.

The application of cross-well seismic methods to crystalline rock is often amore difficult problem than the application in sedimentary rock. The advantageof seismic imaging is the ability to detect or image features away from theborehole. Cross-well seismic imaging in fractured crystalline rock has been usedto define the spatial distribution of velocity and attenuation that is related tofracture zones determined from other borehole techniques (e.g., Vasco et al., 1993;Cao and Greenhalgh, 1997). In fractured media, an important property definingthe rock is fracture anisotropy. Anisotropy will also play an important role inimaging waste sites, as will heterogeneity in general. Imaging using P and Swaves in borehole seismic studies is not a new idea (Stewart et al., 1981). It isbecoming increasingly apparent, however, that to utilize the full potential of theseismic methods for characterizing fractured media, three-component data shouldbe acquired. In imaging barrier sites and contaminated sites this is rare. Crampinnoted the importance of using three-component data in VSP work, particularlyfor fracture detection (Crampin, 1978, 1981, 1984a,b, 1985). These authors andothers have pointed out the phenomenon of shear wave splitting and the anisotropyeffects of horizontal and vertical shear component waves in addition to primaryand secondary wave anisotropy (Leary and Henyey, 1985). In addition to Crampin’stheoretical work on shear wave splitting (1978, 1985), laboratory (Pyrak-Nolteet al., 1990a,b) and theoretical work (Schoenberg, 1980, 1983) explain shear waveanisotropy in terms of fracture stiffness. The fracture stiffness theory differs fromCrampin’s theory in that at a fracture or a nonwelded interface, the displacementacross the surface is not required to be continuous as a seismic wave passes. Theonly solution boundary condition to the wave equation is that the stress mustremain continuous across an interface. This displacement discontinuity is takento be linearly related to the stress through the stiffness of the discontinuity. Theimplication of the fracture stiffness theory is that for very thin discontinuities(e.g., fractures), there can be significant effect on the propagation of a wave.Fracture sites, such as in basalt and other hard rocks, are of interest to barriersand their integrity. This implication applies to voids or any feature that representdiscontinuity in the subsurface. Usually one thinks of seismic resolution in termsof wavelength as compared to the thickness and lateral extent of a bed or otherfeature. In the stiffness theory, the lateral extent is still important, but if thestiffness of the feature is small enough (i.e., a sand-filled void), the thickness ofthe feature can be much less than the seismic wavelength.

In the case of unconsolidated sediments, a coupled solution must be foundthat takes into account the pore fluid (or gas) and matrix interactions. The situationbecomes even more complicated when clay content is introduced into the matrix.At this point, multi-phase models must be considered to account for the observedeffects. One such approach was tried for acoustic velocities in shale (Minear,1982) where a two-phase model following Kuster and Tokoz (1974) was used.One phase was assumed to be the solid rock matrix and the other phase clay


inclusions. This approach was attempted in order to explain deviations from whatconventional theory would predict. Marion (1990) and Marion et al. (1992) devel-oped relationships between seismic P-wave velocity and sand-clay mixtures usinglaboratory measurements. In this work, it was possible to establish an empiricalrelationship between porosity and sand-clay content. Klimentos and McCann(1990) developed empirical relationships between P-wave attenuation, porosity,and permeability in sandstone. Partially saturated materials pose a further com-plication. Anderson and Hampton (1980a,b) performed considerable work in boththeory and measurement to reach an understanding of seismic wave propagationin gas-bearing sediments. Bedford and Stern (1983) also developed models forwave propagation in sediments. Ito et al. (1986) and Mochizuki (1982) alsodeveloped relationships between seismic velocity and attenuation for partiallysaturated material. Parra (1991) analyzed elastic wave propagation in stratified fluid-filled media to examine the effect of porosity and permeability. He extended Biot’stheory to include a point force in fluid-filled porous media. In a related study,Yamamoto et al. (1994) used variations in seismic velocities at different frequenciesto map porosity variations. These are just a few empirical and model studies thathave been conducted to relate seismic properties to physical parameters. Theseapplications have been almost entirely for the petroleum industry.

4.2.1.5 Summary

In summary, seismic methods historically have been used to image subsurfaceelastic properties. Only in recent years have researchers focused on relatingseismic attributes to physical/chemical and microbial attributes at the scalesproposed for remediation (Hubbard et al., 1997, 1999; Chen et al., 1999). Seismicdata are well suited for extrapolating measurements obtained from a borehole tothe large-scale volume away from the hole. In this application, measurementsobtained from the surface or between holes can be used to assess the continuityand homogeneity of the intervening material. Therefore, field and modelingstudies have shown that such features as anisotropy, fluid content, and heteroge-neity have a measurable effect on the propagation of seismic waves. It appearspossible to use shear wave anisotropy and 3-D tomography to map the orientation,density, and spacing of these features in the field and to give the hydrologist/res-ervoir engineer useful information on the fluid flow regime. A few percent changein properties produces effects that are easily detectable. These seismic methodsare particularly informative if used in conjunction with the electrical methodsdiscussed below.

4.2.2 ELECTRICAL AND ELECTROMAGNETIC METHODS

Electrical methods seem particularly promising in mapping and monitoring thegroundwater regime of a site because the electrical conductivity of the subsurfacedepends almost entirely on the fluid saturation, salinity (conductivity), and dis-tribution. Electrical and electromagnetic methods traditionally have been used to


detect the presence of good electrical conductors (e.g., sulfide ore bodies) ordetermine the electrical layering in groundwater or petroleum exploration. Quan-titative interpretation in terms of rock properties or even accurate mapping of thesubsurface distribution of electrical conductivity (imaging) is not as advanced asthat conducted seismologically. Only recently have numerical and theoreticalstudies advanced to the point where quantitative imaging complementary toseismic imaging can be expected.

The electrical conductivity of rocks and unconsolidated sediments in theupper part of the Earth’s crust is governed by the water content and the natureof the water paths through the rock. Electrical current is carried by ions in thewater; therefore, the bulk resistivity depends on the ionic concentration, ionicmobility, and the saturation and degree of connected pores. Conductivity is alsotemperature and pressure dependent because as the temperature increases, ionmobility increases and the pressure affects the apertures of the conduction paths.Most studies on the electrical conductivity of rocks and soils have involvedsedimentary rocks because of their importance in petroleum and groundwaterexploration. Archie (1942, 1947) established an empirical relationship betweenthe pore fluid resistivity, Rp (inverse of conductivity); the porosity, P; and theformation resistivity, Rf, that is now referred to as Archie’s Law:

Rf = A × Rp × P–m (4.1)

where A and m are constants for a given rock type. For a wide range of sedimentaryrocks and some volcanic and intrusive rocks as well, the constant, A, is close tounity and m is close to 2.0.

Fluid saturation has a dramatic effect on the conductivity of porous materials(Telford et al., 1976). As water is withdrawn from a saturated rock, the largepores empty first; however, because small water passageways mainly control theresistivity, the bulk resistivity increases slowly. The dependence is roughly pro-portional to one over saturation squared. As desaturation progresses, criticalsaturation is reached when there is no longer any water to conduct along somepores. This breaking of conduction paths leads to a much more rapid increase inresistivity, roughly proportional to one over saturation to the fourth power. Thecritical saturation depends on the rock type (the nature of the porosity) and candepend strongly on the role of fast paths that are present. Combined with seismicvelocity and attenuation, electrical measurements are valuable for monitoringresaturation progress at a site.

An important and little studied aspect of rock and soil conductivity is therole of fast paths on the resultant bulk properties, particularly in barrier monitoringapplications. Laboratory studies concentrate on small intact samples that, almostby definition, do not include open voids or joints. Field studies using surfaceresistivity measuring arrays are usually too strongly influenced by the inhomo-geneous nature of the near surface to allow any distinction between voids andpore porosity of a particular rock unit. With the increased measurement accuracyand resolution provided by subsurface techniques and the interest in monitoring


time changes in resistivity, it is now possible to investigate more closely the roleof porosity on the electrical conductivity of large masses. It is well known thathydraulic conductivity is strongly influenced by the mean width, orientation, andspatial distribution of the fluid paths. Also, as noted in the preceding section,seismic velocities are strongly affected by discontinuities. However, expressionsfor the electrical conductivity of such material and taking advantage of thisvaluable physical property for characterizing and monitoring large subsurfacevolumes of soil remain to be developed.

Channeling plays an important role in rock resistivity and is practicallydemonstrated in the work by Brace and Orange (1968a,b). Their work on theeffects of confining pressure on the resistivity of a water-saturated granite showedthat, at low pressures, the resistivity increased as the confining pressure increased.They attributed this effect to the closure of fracture porosity. A resistivity increaseof a factor of 10 as the pressure increases could easily be explained by thedisappearance of only 0.1% fracture porosity in a granite of 1.0% pore porosity.

The electrical conductivity of the ground can be measured in two ways. Inthe first, referred to as the DC resistivity method, current is injected into theground through pairs of electrodes and the resulting voltage drops are measuredin the vicinity with other pairs of electrodes. Any or all of the electrodes can beplaced in the subsurface, although traditionally surface arrays have been employed.Electrical resistivity tomography (ERT) uses electrodes in the subsurface to mea-sure resistivity between the boreholes (Daily and Ramirez, 2000). Measurementsof voltage and current for different electrode geometries are then used to inferthe subsurface distribution of conductivity. These methods are indirect, but ideallysuited to measure the properties of a region for which it is impossible to gaindirect access. The resulting interpretation of the conductivity distribution is notunique nor does it provide high resolution of subsurface features. In many appli-cations, this latter property is an advantage because the measurements yield bulkaverage values of the conductivity that often include features that are not includedin hand samples or borehole logging measurements.

The electrical conductivity can also be measured inductively. Instead ofinjecting a DC current into the ground, currents can be induced to flow by achanging magnetic field. The source of the changing magnetic field could be aloop of wire carrying alternating current or a long grounded wire carrying alter-nating current rather than direct current or the Earth’s natural electromagneticfield. The currents induced in the ground are measured either by detecting themagnetic fields they produce or measuring the voltage drops in pairs of electrodes.Sources and receivers can be on the surface, below the ground, or a combinationof both. In these inductive or electromagnetic methods, the interpretation dependsboth on transmitter-receiver geometry and frequency used. In principle, the inter-pretation should be more definitive than with DC resistivity methods. Rigorousconfirmation of this statement in heterogeneous media awaits the developmentof generalized inversion techniques for electromagnetic methods.

Electromagnetic methods offer some proven advantages over DC methods.Measurements can be obtained without contacting the ground; measurements are


insensitive to high resistivity zones; the investigation depth can be controlled bythe frequency of operation so that large transmitter-receiver spacings are notrequired; and, because of the transmitter source field fall-off, the methods are notsensitive to conductivity inhomogeneities far from the zone of interest. Theresolution of subsurface features with electromagnetic methods is limited becausethe frequencies that are low enough to penetrate to the desired depth cannot havea wavelength short enough to define structural features. The problem is com-pounded by surface layers that are invariably conductive, highly variable inthickness, and often act like shields to the subsurface. To overcome these problems,promising borehole electromagnetic methods exist. Pulsed borehole radar is anexample of an electromagnetic technique that uses high frequencies (Hubbardand Rubin, 2000). Radar is becoming prevalent in a variety of environmentalapplications due to its ease of use and sometimes straightforward interpretation(Grote et al., 2003). If the ground conductivity is sufficiently low, megahertz radarwaves can penetrate up to 100 m and can respond to dielectric contrasts withinthe rock mass as well as conductivity anomalies. Radar has been used successfullyat some toxic waste sites to map buried objects and determine fine-scale structuralfeatures and map fluid flow in the vadose zone at a submeter scale (Hubbard andRubin, 2000). In typical soils the range of radar can be from a few meters (using500 MHz) to tens of meters (using 50 to 100 Hz) (Hubbard and Rubin, 2000).

In more conductive rocks, the frequency of the electromagnetic fields mustbe reduced to achieve significant penetration. Then, the resolution decreases asthe fields become diffusive in nature. The traditional low-frequency implemen-tation of electromagnetic methods (less than a few kilohertz) for ore prospectingrelies on quasi-static magnetic induction theory and basically ignores the wavepropagation properties of the fields. In subsurface applications, especially insingle- and cross-hole modes, there are exciting possibilities for electromagneticmethods in the frequency band between the prospecting and radar frequencies(i.e., the mid-frequency band).

4.2.3 NATURAL FIELD AND MAGNETIC METHODS

Dramatic developments have occurred in natural electromagnetic field methods,particularly magnetotellurics. Although magnetotellurics may not have the resolutionfor fine-scale studies, it is mentioned here for completeness. In magnetotellurics,the impedance of the ground is measured as a function of frequency. This impedancefunction is then interpreted in terms of a model of the earth. Traditionally,magnetotellurics has been plagued with problems in data quality and interpreta-tion when the simple layered models used are inadequate. The data qualityproblem has been solved by using the remote reference method developed byGoubau et al. (1978) and improved instrumentation (sensors and high dynamicrange acquisition systems now permit high-accuracy surveys that were previouslynot possible). Field evidence shows data errors of less than 1% in some frequencybands (Nichols et al., 1985). Interpretation has been a problem because the imped-ance was not sampled at adequate intervals on the surface. The electric fields


change rapidly in response to near-surface resistivity variations and bias theimpedances that, in effect, mask the deep structure that is sought. This bias canbe treated by conducting dense station sampling using larger lines for the electricfield measurements or, preferably, both. Many of these issues are being overcomewith advanced computational methods and joint inversion of data (Gasperikovaet al., 2003). In principle, the electric fields could be measured over a grid on thesurface, with magnetic fields measured at the grid nodes and the conductivitydistribution recovered accurately and unambiguously. Equipment is now availablefor such surveys but has not yet been tested.

4.2.4 AIRBORNE GEOPHYSICAL METHODS

Airborne geophysical methods hold a middle ground between the ground-basedgeophysical methods described above and conventional remote sensing methodsdescribed in Section 4.2.5. Remote sensing is generally used to refer to multi-spectral, hyperspectral, thermal, or radar systems, which are typically obtainedby satellites or aircraft at several hundred meters altitude. Airborne geophysicaldata include magnetic, electromagnetic, and GPR data, typically acquired atsensor altitudes ranging from 50 m to about 1 m. Conventional methods andapplications for airborne geophysics are described by the National ResearchCouncil (1995). These airborne magnetic and electromagnetic systems have beenused to image United States Department of Energy (USDOE) waste areas andcaps (Doll et al., 2000). Recently, airborne magnetic and electromagnetic systemshave been developed in which the sensors are housed in booms that are mounteddirectly to the helicopter. This technique allows airborne data to be acquired ataltitudes as low as 1 to 2 m above ground level (AGL), where topography, culturalfeatures, and vegetation permit. The boom-mounted systems have been used todetect and map unexploded ordnance and other metallic objects and can success-fully map these objects with < 0.2 m accuracy when the unexploded shells areas small as 3 to 5 kg (i.e., the size of a small soup can).

The Oak Ridge Airborne Geophysical System-Arrowhead (ORAGS-Arrowhead) is a production-level magnetometer system that is typically operatedat altitudes of 1.5 to 3.0 m AGL, depending on site conditions (Figure 4.4). Thesidebooms and foreboom house a total of eight cesium vapor magnetometers ata nominal spacing of 1.7 m, with two magnetometers each at the ends of the sidebooms and four spaced evenly across the V-shaped foreboom. The sensor posi-tioning is designed to minimize noise from the helicopter rotor and other sourceswhile maintaining a weight distribution that optimizes flight performance and,above all, safety. All data are recorded on a personal computer based console thatsamples the magnetometers and keys analog inputs (e.g., fluxgate) at 1.2 kHzand records laser-derived altitude and global positioning system (GPS) positionat the full output rates of those devices. The magnetometer data are downsampled,typically to 120 Hz, and the other data are interpolated to the same samplefrequency as the downsampled magnetometer data. Navigation is directed by anAgnav RT-DGPS system with Racal satellite real-time correction. Aircraft position


is recorded on the system console and updated by post-processing with a DGPSbase station to provide an accuracy of 0.2 m or better. Under optimal flightconditions, the system acquires data over a 12 m swath with a 1.75-m sensorspacing at a flight height of 1.5 m AGL. An Ashtech ADU-2 GPS-based systemis used to monitor the altitude of the system to provide accurate sensor positioning.The ORAGS systems are typically operated at an air speed of 50 knots, allowingfull coverage acquisition of a rate of about 50 to 70 acres per hour under favorableconditions.

Figure 4.5 shows an analytic signal map for a site in Maryland where previousground-based geophysical surveys were conducted. The airborne data set delin-eated a spider web of underground pipes that was overlooked during ground-based survey preparation and interpretation. Such a network of conductors almostcertainly had a negative impact on the processing and interpretation of the groundsurveys. The conductor network would not have been detected with a conventionalairborne survey at conventional altitudes.

Another ORAGS system is the ORAGS-Hammerhead system, which is usefulfor defining the boundaries and infrastructure of landfill sites that contain ferrouswaste materials or containers. This system provides considerably more detail thana conventional towed-bird system. Oak Ridge National Laboratory (ORNL) andpartners have recently completed a successful demonstration of an airborne time-domain electromagnetic prototype system, the ORAGS-TEM (Transient ElectricalMethods) system, as an electromagnetic complement to the ORAGS-Hammerheadsystem. A photograph of the system is shown in Figure 4.6, and data acquired

FIGURE 4.4 The ORAGS-Arrowhead total field magnetometer system in operation.


FIGURE 4.5 Analytic signal map for a site in Maryland showing anomalies associatedwith a network of piping that had been overlooked in more localized ground-based surveys.

FIGURE 4.6 ORAGS-TEM system in transit near the Black Hills, South Dakota.

23.722.421.219.918.617.316.014.713.512.210.9

9.68.37.15.84.53.21.90.6

nT/m100 0 100

Meters

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with the system are compared with data from the ORAGS-Arrowhead magneticsystem in Figure 4.7. The system records the entire decay curve for each trans-mission, as does the EM-643 ground-based system. It is possible that the TEMsystem can be adapted to provide resistivities through an appropriate calibrationprocedure, but this possibility is only beginning to be investigated. In its currentform, the TEM system responds to nonferrous metallic objects, ferrous materials,and some nonmetallic objects. Therefore, it is an appropriate tool for mappingmaterials in waste sites. If the TEM system can be successfully demonstrated asa tool for measuring resistivities, it could be suitable for time-lapse measurementsof moisture or other resistivity-dependent effects that should be monitored atlandfills or similar areas.

4.2.5 STATE-OF-THE-PRACTICE REMOTE SENSING METHODS

Despite the fact that geophysics has been used successfully for many years inmineral, petroleum, and geothermal exploration, it has not been used effectively

FIGURE 4.7 Comparison of (a) ORAGS-TEM measurements and (b) an analytic signalmap derived from ORAGS-Arrowhead magnetic measurements for a bombing target inSouth Dakota. TEM represent the first-time gate only, and data were acquired at 3 mnominal flight line spacing and 1.5–2 m altitude. Magnetometer results used the 8-sensormagnetometer system at the same altitude and 12 m flight-line spacing. The response ofboth systems to an east-trending barbed wire fence is seen across the center of the diagrams.The individual anomalies are associated with M-38 practice bombs, or their fragments.These are sand- or cement-filled devices with a mass of 10–15 kg when intact. Horizontalscale is in meters. (See color version insert of this figure.)

1374

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in remediation situations. By and large, the examples of geophysics applied tothese problems that have appeared in the literature are very basic and display alevel of application that characterized geophysics 15 to 20 years ago. Descriptionsof the state of the practice of remote sensing methods are described in thesubsections below.

4.2.5.1 Aerial Photography

Aerial photography is a useful tool due to its well-understood technology andthe many historical records of sites that contain aerial photos. Traditional aerialphotos provide high spatial resolution imagery using black and white, naturalcolor, or color infrared (CIR) film. Black and white film can still be useful incases where high contrast differences enhance detection or location of a targetarea. Natural color aerial photos are often used to overlay data layers when usinga GIS system. CIR imagery captures a scene in the near infrared (NIR) bands ofthe electromagnetic spectrum. The color imagery produced consists of false colorimages in which the colors serve to separate scene elements that reflect NIRradiant energy differently. CIR photos have been used to detect vegetation stress,which can be important in identifying plants that have become damaged due toleachate exposure. Moreover, CIR aerial photos can detect waterlogged areas andseparate out conifers from certain deciduous species (Jensen, 1968). For eitherfilm or digital camera technology, a current aerial photo allows the investigatora synoptic view of site geographic/environmental features as well as its culturalaspects. A significant aspect of aerial photos is the historical record that aerialphotos represent. For example, many waste sites have had poor or little docu-mentation on their location or contents.

Aerial photographs can also be used to construct digital elevation models(DEMs). Often stereo aerial photo capability is part of a standard collectionprocedure by many aerial photo firms. Pairs of images are acquired with 60%overlap, which allows for stereo pair generation. Standard photogrammetry isemployed to convert the information in the stereo pairs to digital contour mapsand/or DEMs. For each picture element (or pixel) that comprises an image, anelevation datum can be assigned to it. The DEM can be used to set up a baselinefor a waste site cap. Later, DEMs generated can be used to determine relativesubsidence of the cap with respect to the baseline imagery, which could be anearly sign of cap compromise.

4.2.5.2 Multi-Spectral Scanners

Multi-spectral scanners (MSS) are commonly used sensors for collecting imageryin diverse application areas. The National Aeronautics and Space Administration(NASA) Landsat satellite program established in the 1970s used filmless multi-spectral imagers. As the Landsat program evolved, improved technologies wereused to enhance the quality of the imagery produced by the sensor. In the 1980s


and 1990s, the number of spectral channels grew for both airborne and satellite-borne sensors while retaining good spatial resolution.

MSS sensors have decided advantages over photographic systems. For exam-ple, film technology limits the spectral range that can be covered by film-basedphotographic systems, which are more difficult to calibrate to radiometric unitsthan is digital data. The useable spectral range for film is about 300 nm to 900 nm,with wide spectral bandwidths. Where photographic systems generally need touse separate optical systems to break out the different spectral bands, MSSsystems can use the same optical train to record data from each optical band.Finally, if the aerial photo film will be analyzed in an electronic computer, itmust be digitized, i.e., scanned by an aerial photo film scanner and saved asdigital number data. The process of scanning not only degrades the spatial accu-racy inherent in the film, it is an extra step that is not needed with digital data(Lillesand and Kiefer, 1994).

4.2.5.3 Thermal Scanners

Thermal scanners record radiant emissions that span a range of thermal infrared(TIR) wavelengths. The TIR scanner integrates all of the emissions over thesewavelengths and composes an image of them using detectors specifically devel-oped for use in the TIR region of the spectrum. Often, the wavelengths integratedover the span range from 8 μm to 12 or 14 μm due to the atmospheric transmissionwindow for these wavelengths. The blue/green colors show cooler areas, whilethe orange/red show warmer areas. The temperature regime of a landscape variesnaturally with the amount of solar insulation. That is, solar input to a landscapedifferentially heats the constituent materials present (Elachi, 1987). Dependingon the application, the proper interpretation of thermal imagery must considerdiurnal heating effects. Often pre-dawn imagery is requested because it tends tominimize the thermal shadow effects and differences in the slope of the landeffects in the imagery. The optimum time for data collection depends on thespecific application and target characteristics.

4.2.6 STATE-OF-THE-ART REMOTE SENSING TECHNOLOGIES

Remote sensing systems, techniques, and practice are developing at a rapid pace.The use of hyperspectral sensors, light detection and ranging (LIDAR) topo-graphic systems, LIDAR fluorescence, satellite and airborne radar sensors, andsensor fusion approaches are rapidly moving from the research arena to applica-tions. However, the exciting new developments in geophysics, especially newmethods of imaging the subsurface properties, have not been fully applied in wastestudies. The subsections below reiterate the point that, in addition to monitoringthe emplacement, effectiveness, and performance of barriers, geophysics shouldbe used in a total system performance mode to monitor the total fluid matrixsystem that includes not only the barrier but also the zone being contained.


4.2.6.1 Hyperspectral Imaging Sensors

A hyperspectral imaging spectrometer (HIS) or hyperspectral scanner acquires aseries of images of the same scene in a range of colors (i.e., wavelengths orspectral channels) similar to that of a MSS sensor. The primary difference is inthe narrowness of the bandwidths of the spectral channels and their number. Ahyperspectral scanner attempts to perform laboratory quality spectroscopy of alandscape from an aircraft. Hence, the basic MSS technology has been enhancedand extended to handle and process the extracted spectral channels and concom-itant data load. HIS imagery is often thought of as forming a cube of data(Lillesand and Kiefer, 1994) because of the many bands of data forming a stackof images — one image of the same scene for each band. For large areas imagedand, in some cases, 200+ bands of spectral data, the data load can become onerous.Nonetheless, the spectral information concerning the scene can be invaluable indetermining or classifying unknowns in the landscape, much as spectroscopy isused to determine unknown compounds in a chemical laboratory. Figure 4.8shows a HIS cube.

Currently, the premier HIS instrument is the NASA Jet Propulsion LaboratoryAdvanced Infra-Red Imaging Spectrometer (AVIRIS). This system is flown typ-ically on an ER-2 aircraft at an altitude of 20 km, producing a ground cell sizeor pixel size of 20 m. Alternatively, the AVIRIS can fly on a slower Twin Otterplatform at 2 km and produce 2- to 3-m pixels. The AVIRIS possesses 224contiguous spectral channels that span 0.4 to 2.45 μm. These spectral channelsare about 10 nm wide. Figure 4.9 displays an AVIRIS image of Summitville,Colorado. The Summitville Mine is shown in the picture as is the mapping of

FIGURE 4.8 HIS (AVIRIS) image cube of Moffett Field, California. (See color versioninsert of this figure.)


iron-bearing minerals made possible by the detailed spectroscopic nature of theAVIRIS imagery.

4.2.6.2 LIDAR Systems

LIDAR remote sensing systems are active sensors. That is, LIDAR sensorsprovide their own illumination rather than relying on the sun for illumination.The basic principle of an airborne topographic LIDAR is time of flight of a round

FIGURE 4.9 AVIRIS HIS mapping of Summitville, CO, area. (See color version insertof this figure.)

AVIRIS Sept. 3, 1993

Summitville, Colorado Mining DistrictFe-Mineral Map

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trip of a light pulse to the ground and its return back to a LIDAR receiver. Becausethe airframe position can be known to centimeter-level accuracies, by extension,the point of the ground can be literally surveyed into the system. Thus, as theairframe flies, a dense set of laser pulses is scanned perpendicular to the directionof airframe motion and height and geographic position information for eachground return pulse are recorded (Measures, 1984). Another aspect of LIDARremote sensors is the recording of the intensity of the ground returning pulse aswell as its travel time to the target (time of flight). Because the reflectance ofvegetation and earth materials vary from one another at the wavelength of theLIDAR illumination, reflectance can be used to aid in separating out or classifyinga terrain.

4.2.6.3 Laser-Induced Fluorescence (LIF)

Lasers can be used in remote sensing systems to invoke a fluorescence responsein different materials termed laser-induced fluorescence (LIF). The evolvedfluorescence is detected by a receiver and used to target or, in some cases, imagethe irradiated object. Potential applications include pollutant/contaminant studiesand vegetation stress studies. LIF involves the use of laser pulses at a specifiedwavelength to pump target molecules to excited states, followed by de-excitationand concomitant release of radiation or, in this case, fluorescence at longerwavelengths (Goulas et al., 1997). For example, uranium (in the form of uranyloxide) can be stimulated by a laser to produce a fluorescent spectrum. Thus, LIFcan be used to detect uranium-bearing leachates or contamination hot spots on acap or in the surrounding cap environment.

When laser light energy is absorbed by the chloroplast (i.e., the plant organellethat houses chlorophyll), the light energy excites an electron from a ground stateto a first excited state. Plants that exhibit stress due to environmental factorsexhibit a decrease in the efficiency of photosynthesis (Bongi et al., 1994; Moyaet al., 1992). It has been shown that when photosynthesis is reduced, the amountof heat energy increases by a factor of about five and the amount of chlorophyllfluorescence by a factor of six (Noonan, 1998). However, it is important to realizethat many factors can cause stress in plants. Moreover, chlorophyll concentrationshave been known to alter because of shifts in lighting or season. So, althoughstress can be indicated by LIF, the cause of the stress must be resolved bysupplementary information.

Laser-induced fluorescence imaging (LIFI) is a project operated by theUSDOE that uses a camera to detect the fluorescence induced by a co-locatedlaser transmitter from selected targets (DiBenedetto et al., 1995). Contaminant-induced plant stress can be imaged and mapped by the LIFI instrument, as canuranyl-bearing soils or leachates. It is possible to detect heavy metals and volatileorganic compounds that are often associated with landfills. A handheld versionof the LIFI system was field tested at the ORNL K-25 site and was able to detecturanium during decontamination and decommissioning activities and on selected


surfaces. Also, the LIFI was able to detect chromium-induced stress in plants atthe site. A helicopter version of the LIFI is planned.

4.2.6.4 Radar Systems

Radar systems are active sensors like LIDAR systems, but radar uses microwavesrather than light waves to probe areas of interest, which is an advantage becausemicrowaves penetrate clouds and rain. Like LIDAR systems, radar systems usepulse transmissions of microwaves and record round-trip flight times from the radartransmitter to the target and back. Generally, microwaves penetrate more deeplyinto vegetation than very near infrared (VNIR) wavelengths. Penetration depthdepends on the actual microwave wavelength and the moisture content of thevegetation. Radar returns are processed not only for their range information butalso for the intensity of their scatter and volumetric returns. In VNIR wavelengths,scattering depends on the atomic/molecular makeup of the material irradiated.However, microwave scattering intensity depends on the following: (1) largerscale (on the order of centimeters) surface roughness features, (2) the dielectricof the landscape material (which can be a function of moisture present), (3) thepolarization (horizontal or vertical electric field orientation) of the radar trans-mission, and (4) the angle the incident wave makes with the landscape element.Volumetric return refers to the total return from large-scale landscape elementslike a forest canopy. Thus, total radar intensity return is the sum of the surface andvolumetric returns. Hence, tonal values in a radar image are related to the intensityof the radar return. Specifically, the greater the backscatter values, the brighterthe tonal value of a landscape element (Toomay, 1982).

Two different radar technologies are often employed when collecting remotesensing data: side-looking airborne radar (SLAR) and synthetic aperture radar(SAR). SLAR represents the first imaging radar used. SLARs are often referredto as real aperture radars because the along-track resolution depends on the sizeof the physical antenna of the radar system. However, SLARs are inherentlylimited in their resolution by the antenna size that an airframe can support. SARtechnology overcomes this limitation. Moreover, a SAR system, due to the virtualantenna, can work at longer wavelengths than a SLAR system. The greater rangeof wavelengths available to a SAR system increases its flexibility and value forapplications.

Typical satellite radar systems are the Japanese Earth Resources Satellite(JERS), European Resources Satellite (ERS-1 and ERS-2), and the CanadianRadarsat. Table 4.2 includes a brief summary of system specifications of interest.Note the evolution in the spatial resolution capability of these sensors. The 3-mresolution of Radarsat-2 means that the variety of applications for which the datacan be used is significantly increased.

Radar imagery can contribute significantly to site monitoring. Not only canDEMs be constructed from data, radar backscatter imagery can be used to lookthrough vegetation to reveal the ground surface beneath. Texture and backscatter


changes indicate moisture shifts across the cap and surrounding areas, whichcould be the harbinger of the onset of closure cap compromise or a true breach.Moreover, DEM and geomorphology differences (slope analysis) from some ear-lier baseline data add an important information layer to the site assessment. Radarimagery has been used to detect plant biomass and perform plant classifications(e.g., Ranson and Sun, 1994; Rignot et al., 1994; Dobson et al., 1998). Addition-ally, then, radar imagery can be used to detect changes in the composition of plantcommunities or plant biomass shifts that could be due to contaminant exposure.

4.2.6.5 Fused Sensor Systems/Data Streams

Fused sensor approaches include sensor systems that are flown on the sameplatform over a target area, sensors on different platforms used simultaneouslyover a site, and sensors on different platforms used at different times over a site.The latter case often is the rule for GIS data layer accumulation for a given site. Itis clear that data provided by multiple sensors, whether performing a simultaneousdata collect or not, are more valuable than data provided by a single sensor.Further, ancillary data concerning the construction, geology, watershed, and cli-matology of the site provide crucial data layers for input to the site GIS database.This is the systems approach to interrogating and monitoring waste sites. Theconfluence of remote sensing/geophysical and ancillary data streams inform oneanother and end users of conditions present at a given target area.

Examples of investigators using multiple data streams to successfully char-acterize a site include Vincent (1995), who used both aerial photos and MSS datafor assessing waste sites. Van Eeckhout et al. (1996) used aerial photos (somehistorical) and CIR photos to assess three landfill sites in New Mexico. Well et al.(1995) used both TIR and GPR with good results to investigate hazardous wastesites. Smyre et al. (1998) used aerial photos (some historical), CIR, TIR, MSS,magnetic, electromagnetic, and gamma ray data collection to assess an ORNL site.

TABLE 4.2Prominent Radar Resources Satellite System Characteristics

Name BandSpatial

Resolution Swath Width Revisit Time

JERS L 18 m 75 km 44 daysERS C 10–30 m 100 km 35 daysRadarsat C 8–100 m 45–500 km 3–24 daysRadarsat-2 (2003 launch) C 3, 28, 100 m 20, 100, 500 km 3–24 days

Note the evolution in the spatial resolution capability of these sensors. The 3-m resolutionof Radarsat-2 will mean the variety of applications for which the data can be used issignificantly increased.


4.3 PRBS

In this section, the potential application of geophysical methods for assisting inthe evaluation and monitoring of a PRB is discussed. A PRB presents an enticinggeophysical target, although reported geophysical applications are currently few.The granular reactive iron media used to construct a PRB has unique geophysicalproperties. Electronic conduction in iron results in high electrical conductivityrelative to near-surface geological formations. The electrical conductivity (inverseof resistivity) of iron is 1 × 107 siemens per meter (S/m) (Carmichael, 1989),whereas that of near-surface earth materials is typically less than 1 S/m. Iron hashigh magnetic susceptibility and will locally perturb the earth’s magnetic field.Endres et al. (2000) investigated the electrical and magnetic properties of granularreactive iron mixed with sand. Laboratory measurements, reproduced in Figure4.10a and Figure 4.10b, illustrate the strong dependence of electrical conductivityand magnetic susceptibility on the volume of granular iron. Note that the con-ductivity of the granular iron does not approach the reference value for theelectrical conductivity of iron, presumably due to the absence of continuouselectronic conduction paths in the granular media used in this study. PRBemplacement in the subsurface also creates an interface between iron and thesediment at which charge transfer must switch between electronic and electrolyticconduction, making the PRB an intriguing target for the induced polarizationgeophysical method that is sensitive to the electrochemistry of a metal–fluidinterface. Iron also has seismic properties distinctly different from most near-surface earth materials. The acoustic velocity of iron in solid form is 5900 m/s(McIntire, 1991), whereas it is typically less than 1500 m/s in near-surfaceunconsolidated sediments in a diffuse form. Seismic methods can also then assistin PRB investigations through characterization if it does present a seismic anom-aly or through general characterization structure.

4.3.1 REQUIREMENTS, SITE CHARACTERIZATION, DESIGN VERIFICATION, AND MONITORING

In this section, the utility of geophysical methods to PRBs is considered in respectto the following four objectives: site characterization, PRB construction verifica-tion, short-term monitoring of PRB performance, and long-term monitoring ofPRB performance. Case studies that illustrate the current state of the art ofgeophysical methods in PRB evaluation are subsequently presented. Finally,future directions and recommendations for research are presented. The potentialapplication of geophysical methods emerges at the design, installation/verifica-tion, and monitoring stages of the PRB life span. PRB assessment effectivenessis required over both the short term after PRB construction and over the long-term design life. Short- and long-term monitoring issues are thus treated sepa-rately in the subsections below.


4.3.1.1 Site Characterization

PRB performance depends on successful characterization of site geology andhydrogeology. Fundamental PRB design criteria necessitate quantification of thehydraulic properties of the host material. Estimates of hydraulic conductivity (K)

a

b

FIGURE 4.10 a (a) Electrical conductivity of sand-granulated iron mixtures with varyingiron content of solids. Mixtures were saturated with 0.01 M KCl solution. (b) Magneticsusceptibility of iron mixtures as a function of total volumetric content. (Reproduced fromEndres, A.L. et al., 2000. Proceedings of the Seventh International Symposium on BoreholeGeophysics for Minerals, Geotechnical and Groundwater Applications, Mineral and Geo-technical Logging Society, Golden, CO, pp. 1–8. With permission.) b (a) Schematic ofelectrical charge transfer mechanisms in earth containing metal minerals. (b) Simple circuitmodel for this system: Rnm represents the resistance exerted by the conduction pathassociated with free electrolyte, Rm represents the resistance exerted by conduction acrossa metal–fluid pathway (electronic and ohmic), and W is a Warburg impedance that dependson frequency (ω).

Cond

uctiv

ity (m

S/m

) 800

600

400

200

00 0.25

100 Hz1 kHz

Iron volume fraction (solids)(a) (b)

0.5 0.75 1Iron volume fraction (total)

Mag

netic

susc

eptib

ility

(cgs

× 1

06 )

10000

8000

6000

4000

2000

00 0.01 0.02 0.03 0.04 0.05 0.06

− +

−−−−−−−

+++++++

Electrolyte(ohmic conduction)

CationAnion

Non-metallic path (nm)

Metallic path (m)

Interlayer(polarization)

Granular iron(electronic conduction)

e−

(a) (b)

Rnm

Rm (iω X−c) = W


are required to determine PRB design thickness. Geophysical methods are rou-tinely used to qualitatively characterize variability in subsurface lithology. Low-permeability clay formations are distinguishable from hydraulically conductivesand units. Although direct quantification of K from geophysical methods iscurrently unachievable, recent advances illustrate the value of geophysical imag-ing for providing spatially extensive representations of K variation (for reviewsee Hubbard and Rubin, 2000). This information can aid in the identification oflithologic variability at the immediate PRB installation site and define preferentialflow zones that could complicate contaminant plume transport upgradient of thebarrier. Such techniques require ground-truth verification from whatever boreholerecords are available at the study site. Effective PRB performance necessitatesaccurate barrier emplacement in the immediate path of the contaminant plumeunder remediation. This implies that the plume geometry be well characterized.Direct geophysical detection of chlorinated solvents and heavy metals at typicalsite concentrations is unlikely. Geophysical monitoring of the transport of tracerevolution injected upgradient of a proposed PRB installation can determinewhether the barrier is well placed to capture the plume. Tracking electricallyconductive tracers using electrical resistivity, electromagnetic, and GPR methodshas been applied to characterize vadose zone transport (Daily et al., 1992, Hub-bard et al., 2002) and groundwater flow (White, 1988, 1994). These methods aredeployable using surface and/or borehole instrumentation. Borehole methods areexpensive but enhance resolution of tracer transport at depth. The results ofgeophysical tracer tests could assist in designing geochemical monitoring wellnetworks by identifying preferential flow paths and likely flow rates.

4.3.1.2 PRB Construction Verification

The granular reactive iron used in PRB construction profoundly affects the elec-trical and magnetic properties of the subsurface relative to the pre-installationcondition. Thus, geophysical methods have a high potential for PRB constructionverification. Geophysical imaging of subsurface conductivity structure usingresistivity, electromagnetic, or GPR techniques offers the possibility of definingthe continuity and uniformity (thickness) of the wall, as well as detecting thelocation of flaws in barrier construction. Cross-borehole electrical resistivitytomography was used to examine the subsurface distribution of granular ironinstalled at the USDOE Kansas City facility in Missouri (Slater and Binley, 2003).Joesten et al. (2001) used cross-borehole GPR to image differences in radar waveattenuation amplitude caused by PRB construction at the Massachusetts MilitaryReservation in Massachusetts. Endres et al. (2000) showed that downhole elec-tromagnetic tools are sensitive to the presence of granular iron injected into aformation and offer a potential approach to PRB construction verification. Tomo-graphic electromagnetic and seismic methods are also potentially valuable methodsin PRB verification.

Optimal implementation of geophysical methods in verification requireschanges to current installation practice. Geophysical imaging is often effective


when an image can be compared with an image from that of a pre-existingcondition. In the case of the PRB, differences in the electrical structure causedby the emplacement of reactive iron are of interest, necessitating geophysicaldata collection prior to PRB construction. Ideally, boreholes for geophysical dataacquisition would be drilled prior to any subsurface disturbance to permit acqui-sition of a representative background data set. The geometry of a typical PRB iswell suited to cross-borehole geophysical imaging. Instrumentation can be placedin boreholes drilled immediately upgradient and downgradient of the barrier,providing a two-dimensional cross-sectional image of the barrier wall (Joestenet al., 2001; Slater and Binley, 2003). A closely spaced nest of boreholes permits3-D imaging of the barrier installation (Slater and Binley, 2003).

4.3.1.3 Short-Term Monitoring

Short-term PRB monitoring primarily focuses on the wall efficiency to degradeand remove contaminants. The relatively low contaminant concentration typicallyencountered at a PRB installation site is unlikely to be detectable with geophysicalmethods. Short-term monitoring is also concerned with possible disruption of thenatural flow regime due to PRB emplacement. Most critical is that plume transportfollowing PRB construction is consistent with that predicted from the site char-acterization phase. A geophysical tracer test could be an effective noninvasivemethod for assessing plume transport immediately after construction. The use ofelectrical resistivity, electromagnetic, or GPR to track an electrically conductivetracer appears to be a promising technology and could be used in decision-makingregarding final placement of geochemical monitoring wells required for long-term performance evaluation.

4.3.1.4 Long-Term Monitoring

The long-term performance of PRBs is highly uncertain but operational life, itsperiod of effectiveness, is expected by the user to exceed ten years. Monitoringstrategies are required to determine deterioration in barrier performance as reac-tive iron is oxidized during hydrocarbon degradation. The exact mechanism ofdegradation of chlorinated compounds is not fully understood, and a variety ofpathways are likely involved (Gavaskar et al., 1998). A fundamental aspect ofPRB performance is that degradation of chlorinated organics is a surface phe-nomenon and the available specific surface area of the reactive medium governsthe rate (Gavaskar et al., 1998). Clogging of the barrier and the resulting perme-ability reduction are also current concerns relating to reduction in PRB perfor-mance and can be significant issues. Clogging at the influent end of the PRBcould potentially result from formation of iron precipitates under highly oxygenatedconditions (Gavaskar et al., 1998). In addition, deposition of inorganic suspendedsediments on the granular iron can also reduce permeability and performance.

The presence of granular iron modifies the subsurface electrical propertiesdue to the following charge transfer mechanisms: electronic conduction in the


metal and polarization of charges at the interface between a metal and the pore-filling electrolyte. Figure 4.10a is a simple conceptual illustration of the keycharge transfer mechanisms in a medium containing metal particles. Figure 4.10bis a circuit analogue of this system. A frequency-dependent interfacial (Warburg)impedance (W) is often used to simulate the electrical response of a metal–fluidinterface (e.g., Pelton et al., 1978). The magnitude of this interfacial impedanceis measured with the induced polarization method. The frequency dependence ofthis impedance is also determined when spectral (multi-frequency) induced polar-ization measurements are made. The chemistry of the metal–fluid interface exertsa strong control on the induced polarization response (Olhoeft, 1985). Oxidationof the granular iron surface as a result of continued chlorinated solvent degrada-tion might modify the induced polarization response of a PRB. Precipitation ontothe granular iron does reduce the surface area of the metal–fluid interface andwill presumably modify its impedance. It will also change the charge and thesurface complexation of the interface. Induced polarization is thus considered apromising technology for long-term PRB monitoring.

Self-potential is another geophysical method that is sensitive to interfacechemistry. Small intrinsic voltages exist where ionic concentration gradientsoccur. These gradients can result from physical movement of charge by fluid flow,charge diffusion at chemical interfaces, or thermal effects. Changes in electro-chemistry at the iron–fluid interface can result in characteristic self-potentialsignals. Extensive laboratory research is required to determine the induced polar-ization and self-potential signal as chlorinated solvent treatment by granular ironprogresses.

4.3.2 CASE HISTORIES

Few published examples of the application of geophysical methods to PRBinvestigations exist. The case studies that follow focus on the issue of constructionverification. These examples illustrate the potential that geophysical imagingtechnologies offer with respect to noninvasive PRB construction evaluation.Applications of geophysical methods to site characterization and PRB monitoring(either short or long term) are currently unreported.

4.3.2.1 Electrical Imaging of PRB Construction and Installation (Kansas City, Missouri)

Slater and Binley (2003) report the results of cross-borehole resistivity andinduced polarization imaging on a PRB installation at the USDOE Kansas Cityplant. This PRB was constructed as a continuous 40 m long by 1.8-m-wide trench.The first 1.8 m of the trench immediately above bedrock was filled with 100%ZVI. The remainder of the trench was filled with 0.6 m of zero-valent iron and1.2 m of sand. Figure 4.11a shows the cross-sectional geometry of the barrierand site geology. Superimposed is the position of electrodes and the finite elementmesh used to reconstruct the conductivity distribution between wells with electrical


imaging. Figure 4.11b is a plan view of the site showing 16 boreholes drilled tobedrock and installed with electrode arrays as per Figure 4.11a. Each boreholepair represents a two-dimensional panel for imaging the cross-sectional electricalstructure of the barrier. Two sets of four boreholes were used to investigate barrierintegrity with 3-D electrical imaging (Figure 4.12).

Two-dimensional electrical images were obtained between boreholes 5 and 6.Both the resistivity and induced polarization parameters illustrate high contrastswith background geology and accurately resolve PRB structure compared to thedesign structure in Figure 4.12 and Figure 4.13. These images clearly illustratethe capability of electrical resistivity and induced polarization imaging for in situPRB resolution. The resistivity response results from electronic conduction in thehighly conductive granular iron. The induced polarization response results fromthe impedance at the metal–fluid interface. Results of 3-D PRB visualization usingresistivity measurements are illustrated at two locations on the barrier in Figure4.13. The images illustrate variability in the in situ PRB structure, particularly in

FIGURE 4.11 PRB installation at USDOE Kansas City plant. (a) Cross-sectional geom-etry showing electrical imaging mesh superimposed. (b) Plan view showing location ofimaging boreholes along the barrier. (After Slater, L. and Binley, A., 2002. Geophysics,68(3), 911–921. With permission.)

1 2

13 14

Easting across barrier (m)

3 4

5 6 7 8

9 10

11 12 16 15

Cross Borehole Arrays

Control panel

0

−5

−10

−15

−20

−25

−30

−35

−40

Line of 2-D surface profile

Borehole clustersused for 3-D imaging

Panels used tocreate 3-D dataset

Distance from midpoint (m)

Reactive iron Sand Clay backfill Silty clay Basal gravel Shale bedrock

0

2

4

6

8

10

0 −1 −2 1 2

(a) (b)

Dep

th (m

)

Nor

thin

g al

ong

barr

ier (

m)

−6 −4 −2 0 2 4 6


the vicinity of BH 5, where the integrity of the upper thin section is compromised(Figure 4.12a).

4.3.2.2 Cross-Hole GPR Investigations (Massachusetts Military Reservation, Massachusetts)

Joesten et al. (2001) conducted cross-hole GPR imaging to monitor pilot-scaletesting of a hydraulic fracture method to install a PRB in unconsolidated sedi-ments at depth. They also conducted numerical modeling of cross-hole radarpulses to assist in the interpretation of the barrier structure from the radar data.Design specifications called for the installation of two iron walls 5 m apart, 12 mlong, and at a depth of 24 to 37 m. This installation depth precluded standardPRB installation procedures and emphasized the need for a noninvasive methodof emplacement evaluation. The application of GPR was based on the largereduction in transmitted wave amplitude associated with emplacement of highlyconductive iron.

Numerical finite difference modeling was used to predict the effects of holesand wall edges on the transmission amplitude of the radar pulse. Figure 4.14

FIGURE 4.12 2-D PRB visualization using (a) electrical conductivity obtained fromresistivity imaging, and (b) normalized IP obtained from IP imaging. Compare with idealPRB geometry as per installation specifications shown in Figure 4.5a. IP, induced polar-ization. (Modified from Slater, L. and Binley, A., 2003. Geophysics, 68(3), 911–921. Withpermission.)

Dep

th b

elow

BH

1 gr

ound

surfa

ce (m

)

0−2 −1 0 1 2

2

4

6

8

10 BH6

(a) (b)

BH5


Dep

th b

elow

BH

1 gr

ound

surfa

ce (m

)

0−2 −1 0 1 2

2

4

6

8

10 BH6 BH5

3

1.0 0.8 0.6Conductivity (S/m)

Normalized IP (mS/m)

0.4 0.2 0

2 1 0



compares the modeled response of a 3.1 m tall wall with the transmission ampli-tude data collected after PRB installation. The model result is a close fit to thegeneral shape of the field data, suggesting that the top of the wall and wall heightare well defined by the geophysical data. The results from cross-hole radaramplitude measurements between 14 boreholes were combined to define vari-ability in cross-sectional amplitude attenuation along the length of the two walls(Figure 4.15). Contour plots defined irregularly shaped walls about 8 m wide.Small-scale structure was tentatively interpreted as stringers of iron possiblyattributable to iron particles moving into higher permeability formations. Thisstudy illustrates the potentially high spatial PRB resolution obtainable with radardata.

4.4 VERTICAL BARRIERS

Constructed horizontal barriers are not included in this discussion. It is assumedthat horizontal barriers are natural aquitards.

The goal of vertical barriers is to prevent groundwater from either enteringor leaving a volume of interest, such that the contamination can be remediated orisolated. Therefore, such issues as the location of the barrier, thickness, life

FIGURE 4.13 3-D conductivity images obtained at two locations along PRB: (a) betweenBH 5 and 8, (b) between BH 9 and 12.

Dep

th b

elow

gro

und

surfa

ce at

BH

1 (m

)

4

5

6

7

8

9

2 1

0 0 1

2 3

Distance West from BH5 (m)

Distance North

from BH5 (m) D

epth

bel

ow g

roun

d su

rface

at B

H1

(m)

3

4

5

6

7

8

2 1

0 0 1

2 3

Distance West from BH9 (m)

Distance North

from BH9 (m)

Conductivity (siemen)1.0 0.8 0.6 0.4 0.2 0

(a) (b)


expectancy, and integrity are all important. Just as important is the environmentin which the barrier is being emplaced. If there is no floor to the containmentsystem, then there is the possibility that the barrier may be of little use. Theability of geophysical methods to characterize and monitor the containmentsystem (wall plus floor) primarily depends on the contrasts in the elastic, elec-trical, density, and magnetic properties between the native materials and contain-ment system. A variety of different materials are used for barriers, from variousgrouts to constructed barriers. Unfortunately, there is a lack of information onthe geophysical properties of many of these barrier materials. On the other hand,barriers made of metal sheets and more conventional materials can be considered,and, in a general sense, geophysical monitoring methods can be designed foralmost all barriers. In addition to characterizing and monitoring the actual barrier(wall plus floor), it is important to note that the volume inside of the containmentsystem can be characterized and monitored to determine if the system is perform-ing as designed. For example, if the barrier does not have a geophysical contrast,a leak can be detected if the flow or concentration of contaminants is causing ananomalous signal. Then, the total system can be monitored. As described in thissection, the most effective approach is to combine geophysical methods in a time-lapse sense to detect changes.

FIGURE 4.14 Comparison of normalized model wall amplitude for a 3.1 m wall andnormalized field data amplitude from the cross-well radar survey at Massachusetts MilitaryReservation. (After Lane et al., USGS Water Resources Investigation Report 00-4145,17 p. 2001.)

Mod

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, in

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−1.7

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0.3

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Normalized peak-to-peak amplitude0.8 1.0 1.2 1.4

Dep

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30

31

32

33

34

35

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Model data

Model w

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Field data


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20W

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200.

150.

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050.

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The potential application of geophysical methods emerges at the design, instal-lation/verification, and monitoring stages of the walls and floor. Barrier effective-ness assessments are required in the short term, after construction, and over thelong-term design life. Short- and long-term monitoring issues are thus treatedseparately in the following subsections.

4.4.1.1 Design

The design and performance of the barrier depends on successful characterizationof site geology and hydrogeology. The design of the containment system dependsmainly on the in situ flow and transport properties, contaminant to be contained,and the expected life of the barrier. Geophysical methods are routinely used toqualitatively characterize variability in subsurface lithology. Low-permeabilityclay formations are distinguishable from hydraulically conductive sand units.Although direct quantification of permeability using geophysical methods iscurrently unachievable, recent advances illustrate the value of geophysical imag-ing for providing spatially extensive representations of permeability variation (forreview see Hubbard and Rubin, 2000).

4.4.1.2 Installation/Verification

Effective performance necessitates accurate barrier emplacement in the path ofthe contaminant plume under remediation. This implies that the plume geometrybe well characterized. One of the most effective methods of characterizing verticalbarriers is with cross-well methods. Although surface imaging methods have beenwidely developed and used, the resolution is limited compared to the requirementsof most remediation applications. Therefore, the need for higher resolution imag-ing has led to borehole techniques that place sources and sensors in wells. Cross-well seismic, electromagnetic, radar, and ERT are all in use now. In a cross-wellconfiguration, a source is put in one hole and receivers in another. Figure 4.16shows an example of how high-resolution cross-well seismic and radar methodswere used to infer flow properties at the USDOE bacterial transport site in Oyster,Virginia (De Flaun et al., 2001). This was crucial information in designing bac-terial injection experiments at this site.

Direct geophysical detection of chlorinated solvents and metal species attypical site concentrations is unlikely; however, progress is being made in thedirect detection of free product nonaqueous phase liquids (NAPLs) (Geller et al.,2001). Figure 4.17 shows the results of characterizing a chlorinated solvent sitewith cross-well seismic methods (Geller et al., 2002). The radar also showed thestructure in this saturated soil, and the seismic showed attenuation of signal dueto the presence of NAPLs. Figure 4.18 and Figure 4.19 show examples of usingseismic and radar methods to map different but complementary properties (Majeret al., 2002). In Figure 4.18, the cross-well radar tomography is showing the


moisture content in the sediments at the USDOE Hanford site (note the correlationwith the neutron log data). The seismic (Figure 4.19) is showing the heteroge-neous porosity within the sediments. In any case, state-of-the-art methods arenow beginning to be applied for initial characterization. Additional methodsinclude surface seismic, surface radar, and high-resolution electrical methods suchas cross-well electromagnetic. ERT, gravity, and magnetic are generally too lowin resolution to be of use for anything other than broad site characterization.

Depending on the contrast between the barrier and the contained volume,geophysical methods may or may not be applicable to confirm the location ofthe emplaced barrier. Geophysical imaging of a subsurface conductivity structureusing seismic, resistivity, electromagnetic, or GPR techniques offers the possi-bility of defining the continuity and uniformity (thickness) of the wall, as wellas detecting the location of flaws in barrier construction. These techniques must beimplemented in the cross-well or surface to well configuration. Therefore, optimalimplementation of geophysical methods in verification requires changes to currentinstallation practice. Either sensor can be emplaced with cone penetrometer

FIGURE 4.16 An example of how high resolution cross-well seismic and radar werecombined to infer transport properties in a sandy aquifer at the USDOE bacterial transportsite in Oyster, Virginia. (From De Flaun, M. et al., 2001. EOS, 82(38), 417–425, LBNL-48440. With permission.)

Dep

th (m

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SL)

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Distance (m)downgradient from B2

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NWM3 T2

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Pipejoint

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S10 S12 B2SE

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FIG

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2000

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me (

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3000

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technology (CPT) in dedicated boreholes or in the wall itself. It is assumed thatthe floor can be characterized with high resolution seismic or radar techniques.

Geophysical imaging is often effective when an image can be compared withan image from that of a pre-existing condition. In the case of vertical barriers,the barrier provides a significant contrast to the surrounding medium. If the

FIGURE 4.18 Cross-well radar tomographic data compared with the neutron probe esti-mates of moisture content in sediments at the USDOE Hanford site (Majer et al., 2002).The higher moisture content is due to finer grain material.

0.210.200.190.180.170.160.150.140.130.120.110.100.090.080.070.060.050.04

Volu

met

ric w

ater

cont

ent (

m3 m

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X3 (m

eter

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from

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sing

3

4

5

6

7

8

9

10

11

12

13

14

150 1 2 3

6 8 10 12Moisture content (%)

14

X2 (m

eter

s) re

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nced

from

top

of ca

sing

3

4

5

6

7

8

9

10

11

12

13

14

15

GPR data Neutron probe dataBaseline data


FIGURE 4.19 The radar (left-hand side) compared to the seismic (right-hand side) cross-well tomography in the USDOE Hanford vadose zone. (From Majer, E.L. et al., 2002.Report LBNL-49022.)

X1 (m

eter

s) re

fere

nced

from

top

of ca

sing

X4 (m

eter

s) re

fere

nced

from

top

of ca

sing

0 1 2

0 1Preliminary

Hanford X1-X4SEISMIC

2X4

(met

ers)

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sing

0 1 2

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Hanford X4-X1RADAR

2

0.11 0.15Velocity (M/NS)

550 650 750Velocity (M/S)


geophysical methods are used in a time-lapse mode, then the barrier can be quitevisible. Such methods as cross-well and surface to borehole can be useful inidentifying the general geometry of the wall. If a time-lapse mode is used,geophysical data collection is required prior to construction. Ideally, boreholesfor geophysical data acquisition would be drilled prior to any subsurface distur-bance to permit acquisition of a representative background data set. The geometryof a typical vertical wall is suited to cross-borehole geophysical imaging. Instru-mentation can be placed in boreholes drilled immediately upgradient and down-gradient of the barrier, providing a two-dimensional cross-sectional image of thebarrier wall. A closely spaced nest of boreholes permits 3-D imaging of the barrierinstallation.

4.4.1.3 Short-Term Monitoring

Short-term monitoring primarily focuses on the efficiency of the wall in initialperformance due to construction and contaminant degradation and removal. Con-taminant concentrations typically encountered at a site with a vertical wall maybe unlikely to be detectable with geophysical methods, but free product densenonaqueous phase liquids (DNAPLs) or drums of material may be detectable andmonitored during remediation with some methods. Short-term monitoring alsofocuses on possible leaks from initial construction or flaws not detected duringemplacement. The allowable leak depends on the contaminant level and type.This, in turn, dictates the geophysical method(s) that can be applied to detect theleak. A geophysical tracer test could be an effective noninvasive method forassessing plume transport immediately after construction. Electrical resistivity,electromagnetic, or GPR tracking of an electrically conductive tracer appears tobe a promising technology. This technique could be used in decision-makingregarding final placement of geochemical monitoring wells required for long-term performance evaluations.

4.4.1.4 Long-Term Monitoring

The long-term performance of vertical walls is somewhat established, but whileoperational life is hoped to exceed 30 years, as of yet there is minimal experiencewith these time periods. Monitoring strategies are required to determine deteri-oration in barrier performance. If sensors are placed within the barrier duringconstruction, the electrical and structural properties could be measured over time.Again, depending on the physical, chemical, and geometric properties of thebarrier, the exact method varies. One possible simple method to determine a leakis self-potential. Flow through the barrier (in this case, a leak) can cause eitherstreaming potential or self-potential (if it is a rusting wall) effects.

4.4.2 CASE STUDIES

Excluding tanks and ponds, a great deal of work using geophysical methods forcharacterizing and monitoring vertical barriers has not been conducted. Daily and


Ramirez (2000) used ERT in a full-scale test to image a thin wall grout barrierinstalled by high-pressure jetting and a thick polymer wall installed by low-pressure injection at Brookhaven National Laboratory in New York. In anothercase, ERT, radar, and seismic methods were used to monitor and characterize verticalgrout wall emplacements at a test site in Dover, Delaware (Pellerin et al., 1998).The latter is discussed in detail below and is modified from Pellerin et al. (1998).

During 1997, a suite of cross-hole geophysical surveys was completed at theDover national test site at Dover Air Force Base to demonstrate the efficiencyand accuracy of geophysical methods in determining the areal extent ofcement–bentonite subsurface barriers. Two barriers were emplaced as verticalwalls that were keyed into a clay aquitard using a modified jetting technique.These barriers were denoted as the shallow active and deep passive barriers andextended to 7 and 16 m below ground surface, respectively. The active and passivedescriptors referred to the hydraulic and gaseous tracer work performed at thesites.

Before initiation of the barrier study, an extensive geophysical site charac-terization study was performed at the site. Surface GPR, ERT, and boreholeelectromagnetic data were reviewed for parameters of interest to the barrierverification study. Site characterization data were used to estimate the physicalproperties of the background host, and laboratory measurements were performedto estimate the properties of the grout. Based on these data, numerical modelswere computed for survey design and interpretation.

After barrier emplacement, all geophysical methods were deployed betweenboreholes surrounding or internal to the barrier enclosure or permanentlyemplaced vertical barrier. The locations of all of the geophysical access boreholesand vertical barriers installed at the shallow active barrier and the deep passivebarrier are shown in Figure 4.20. The vertical barrier consisted of stainless-steelelectrodes and multi-conductor cables grouted in place using a neat Portlandcement. Half of the electrical resistivity electrodes at the deep passive barrierwere part of the boreholes, while the other half were installed as permanentlyemplaced barriers. All electrodes for the shallow active barrier were installed asvertical barriers independent of the boreholes. Figure 4.20 shows the bore-hole/vertical barrier locations for the data that are presented.

Preliminary results indicated that the GPR and ERT methods were successfulat imaging the areal extent of the barrier and at detecting leaks through the barriersusing combined time-lapse acquisition modes and tracer tests. The demonstratedmethodologies summarized in the subsections below include cross-hole GPR,seismic, and ERT methods.

4.4.2.1 Cross-Hole GPR

To increase resolution, cross-hole data were acquired prior to and after the groutinjection, and then were differenced by subtracting data sets collected at one timefrom data sets collected at a different time. The cross-hole GPR data wereacquired with the Sensors & Software pulse EKKO 100 Borehole System prior


FIG

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20Sc

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to grout injection in June 1997 and after grout injection in July 1997. The cross-hole GPR data were acquired using both the zero off-set profile (ZOP)(i.e., constant transmitter-receiver off-set) and the multiple off-set profile (MOP)(i.e., variable transmitter-receiver off-set) modes from borehole pairs located atboth the shallow active barrier and the deep passive barrier. The ZOP data arerapid and simple to collect for interpretation of both reflection and transmissionmodes. The MOP data, which are slow to acquire, are needed to constructtomograms of the barrier walls. The survey design was appropriate for a trans-mission survey; the holes were spaced close to the barrier with a wide off-set.Although configuration allowed for a measurable signal to be propagated acrossthe attenuating barrier, but the wide off-set prohibited separation of the first wavereflected off the barrier from the direct arrival wave traveling from the transmitterborehole to receiver borehole.

The GPR data were acquired using both 100 and 200 megahertz (MHz)antennas. The 100 MHz measurements were collected at 0.25-m intervals alongthe length of the boreholes while the 200 MHz data were acquired at 0.125-mintervals along the boreholes.

A velocity analysis of GPR data is presented for the deep passive barrier inFigure 4.21. Data are shown as the difference in travel time of the first arrival asa function of depth for the two holes that straddle the barrier and two that are onthe same side of the barrier. The deep passive barrier is in the vadose and saturatedzones, and the GPR response is quite different, depending on the hydrologicaldomain within which the signal propagates. In the vadose zone, the grout dis-placed air in the pore space, which resulted in a slower wave propagation. In thesaturated zone, the grout displaced water in the pore space, resulting in a fastermedia. Figure 4.21 shows the difference in travel time when the barrier is present(left) and when no barrier is present (right).

The ZOP GPR data collected within the shallow active barrier are shown inFigure 4.22. The amplitude spectrum of the first arrival between holes SA-09 andSA-05 is shown on the left before injection and after injection, as well as the

FIGURE 4.21 Travel time analysis of GPR data across well pair DP-09/DP-01, wherethe barrier penetrates the saturation zone and well pair DP-05/DP-06, where no barrier ispresent. (From Pellerin, L. et al., 1998. EEGS 11.)

Diff

eren

ce in

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DP 09 – DP 01 DP 06 – DP 05

20

−2−4−6−8

−2 0 2 4 6 8Depth (m)

10 12 14 16 18 Diff

eren

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−2−4−6−8

−2 0 2 4 6 8Depth (m)

10 12 14 16 18


differenced data. A velocity analysis is also shown as differenced before and afterinjection in travel time for the same borehole pair. Borehole SA-05 has beencompleted with grout, as can be seen in the low-amplitude strip of the left sidein the before and after sections. The before injection shows an attenuating regionin blue at 4 to 5 m corresponding to the clay layer. After injection, the sectionfrom 1 to 5 m attenuates the signal, indicating the presence of the barrier. It isinteresting to note that after injection there is still a hint of the structure of thestratigraphy. The colors are reversed in the difference data; no change is shownin blue. The difference in travel time is roughly 3 nanoseconds (ns), as predictedin the sensitivity study, indicating a slowing of the wave as it propagates throughthe relatively wet barrier. A flaw evident at a depth of 3 m has been verified inthe excavation.

Figure 4.23 shows a velocity tomogram of the wall between boreholes SA-06and SA-09.The pre-injection tomogram shows three major velocity zones: sand(velocity approximately 0.11 m/ns), clay (velocity approximately 0.55 m/ns), andsand again. A transition layer can be observed between 2.5 and 3.5 m with avelocity of 0.075 m/ns. This is the area where a drop to zero in the velocitydifference tomogram can be observed. This drop may correspond to an area wherethe barrier is substandard.

FIGURE 4.22 Spectral analysis of first arrival amplitude for the difference between beforeinjection and after injection, and travel time analysis of GPR data across well pair betweenholes SA-05 and SA-09. (From Pellerin, L. et al., 1998. EEGS 11.)

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Frequency (MHz)

Zop wells 09-05 Zop18 09-05


4.4.2.2 Seismic

Modeling has shown that cross-well seismic and single well reflection seismicmethods should both work as well as radar in detecting the barrier. However, theseismic technique is primarily a saturated zone technique, and propagating energyinto the vadose zone was problematic. Further problems with the seismic methodsin the saturated zone were because of air being injected into the subsurface duringbarrier emplacement, resulting in a highly scattered post-injection seismic signal,even though the pre-injection signal was quite strong.

FIGURE 4.23 Radar velocity tomograms before injection and the velocity differencetomogram from data acquired after injection. (From Pellerin, L. et al., 1998. EEGS 11.)

0.4

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0.09 0.10 0.11

Wells 09-06 pre, 1997 Diff (aft1-pre)


4.4.2.3 ERT

The ERT data were acquired using the ERT system of Daily and Ramirez (2000)after grout injection in July 1997 and during a flood test in August 1997. Becauseof scheduling problems, no measurements were obtained before injection; there-fore, no difference data are available. The ERT measurements were obtained fromvertical electrical array (VEA) pairs with the electrodes spaced 1 m apart down-hole to a depth of 15 m at the deep passive barrier, and 6 m at the shallow activebarrier during the flood test.

ERT results between the plane defined between ERT-02 and ERT-03 at thedeep passive barrier are presented in Figure 4.24. Because it was not possible tocollect pre-injection data, only post-injection data was used to image the barrier.The barrier is a conductive anomaly vertically up the center of Figure 4.24. Theresults showed that the barrier does not appear to have a uniform thickness. Alsoimaged are lower clay layers in the section as seen in red. The top few metersof the image plane appear more conductive over a wider region than lower downon the image plane. This could be because of grout infiltrating the surface duringbarrier injection. The top three images show the horizontal planes through thebarrier; the three bottom figures show the vertical planes outside of the barrier(Pellerin et al., 1998).

FIGURE 4.24 Reconstructed time-lapse 2-D ERT images of the deep passive box betweenholes ERT-02 and ERT-03 (left-hand side) and reconstructed 3-D ERT image of the floodtest at the shallow active box (right-hand side). The top three images on the right showthe horizontal planes through the barrier while the three bottom figures show the verticalplanes outside of the barrier. (From Pellerin, L. et al., 1998. EEGS 11.)

0 50 100 Resistivity (ohm-m)

150 200 250

0

Electrical resistivity tomogramafter injection at deep passive site

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Dep

th (m

)

ERT03 ERT02

8/19/97 1137 8/19/97 1418 8/20/97

0 0 0 0 0 0 0

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0.5 0.6 0.7 0.8 0.9 1.0


In addition to directly imaging the barrier, a test was performed to map leaksand hence flaws of the barrier. Baseline ERT were obtained just before filling theshallow active barrier with groundwater whose conductivity was enhanced by theaddition of sodium chloride. Several data sets were obtained while filling thebarrier, and one data set was obtained after the barrier was filled. The right-handside of Figure 4.24 is a reconstruction of before and after data. The top threefigures are images of the horizontal planes through the barrier where the salt-water tracer is easily delineated. The lower three pictures show the vertical planesdefined by the emplaced barrier outside of the barrier. It is clear that much of thesalt water has migrated outside of the barrier. These flaws are also seen with thehydraulic and vapor tracers.

Cross-hole GPR data were used successfully to determine the presence ofthe barrier and the detection of flaws. From a practical point of view, reflectionmode is the preferred data acquisition mode because it does not require boreholesto be placed inside of the barrier enclosure. However, the GPR data were notinterpretable in reflection mode because data were acquired with the close cou-pling to the barrier and large off-set was necessary for the transmission interpre-tation. Analysis of the cross-hole GPR data suggested that the boreholes shouldbe placed a greater distance from the barrier walls with a ratio of 3:1 to 5:1 off-set from the barrier: distance between boreholes in order to enable analysis ofreflection mode arrivals. The radar velocity tomograms, as well as the ZOPamplitude and travel time analysis taken before and after barrier injection, showedsignificant differences. The differences are attributed to the presence of the barrierdue to the contrast in conductivity and permittivity dielectric with the hostmedium.

The ERT acquisition system illustrated the use of time-lapse ERT coupledwith a tracer test to detect leaks through failed barriers. Nevertheless, to increasethe resolution of the reconstruction, it is necessary to obtain baseline data, andit would be better to move the emplaced array farther away from the barrier.

4.5 CAPS AND COVERS

Stakeholders, regulators, and end users have recognized the difficulty in projectinglong-term, field-scale barrier performance from short-term, point measurements.Thus, there is a need for cost-effective, robust and long-lived monitoring tech-nologies to verify field-scale performance. Noninvasive techniques offer signifi-cant advantages over traditional methods. In the application of geophysics to capsand barriers noninvasive surface-based geophysical methods are particularlyeffective. The high speed of data acquisition leads to lower costs and highsampling resolution, and the integration of multiple spatial scales provides infor-mation that is more useful for monitoring field-scale performance. Furthermore,the nonintrusive nature minimizes damage to barrier integrity from sensor instal-lation or degradation.



The lack of cost-effective and robust monitoring technologies to evaluate long-term, field-scale performance, and the difficulty in projecting long-term, field-scaleperformance from short-term point measurements is a major challenge to barrierdeployment. Monitoring moisture dynamics in the near-surface layers of multi-layered barriers is one of the few viable options for long-term barrier monitoring.Given the size of a typical barrier, techniques that make short-term point-scalemeasurements have limited application. The most desirable are those technologiescapable of providing long-term, spatially continuous measurements of near-surfacemoisture conditions over a range of spatial scales. Of the technologies currentlyavailable, nonintrusive geophysical methods are perhaps the most attractive.Unlike many of the traditional monitoring techniques, nonintrusive methods donot impair the integrity of the protective cover, are immune to the effects of sensordegradation, and typically provide measurements at scales ranging from a pointto the field scale.

The potential of nonintrusive tools like electromagnetic induction (EMI) andGPR for obtaining information about soil-water content in the near surface iswell recognized. EMI provides distributions of bulk apparent electrical conduc-tivity, ECa, while GPR provides distributions of electromagnetic velocity, v, fromwhich the apparent dielectric permittivity, κ, is inferred. Both ECa and κ arehighly correlated with soil-water content, θ. The potential for nonintrusive EMIto monitor changes induced by changes in θ in the top few meters of variablysaturated soils has long been recognized (Kachanoski et al., 1988; Sheets andHendrickx, 1995). This technique has also been used successfully in aerial surveysto rapidly map large areas of electrical conductivity (Cook and Kilty, 1992; Dollet al., 2000), making it an attractive option for monitoring large numbers of field-scale barriers. The potential of surface GPR for measuring near-surface watercontent is also well recognized (Du and Rummel, 1994; Chanzy et al., 1996;Hubbard et al., 1997; Huisman et al., 2001). In engineered barriers, variations intexture and pore water concentration of electrolytes are small, and spatial varia-tions in the bulk apparent electrical conductivity, ECa, depend primarily onchanges in

~θ. Thus, θ in the storage layer of barrier can be inferred from ECa

using Rhoades et al. (1976):

(4.2)

where ECs is the apparent electrical conductivity of the solid phase, ECw is thepore water conductivity, and T is the transmission coefficient (linearly related toθ and to the tortuosity of the water film through which current flows in the liquidphase). Thus, temporal changes in soil-water storage, ΔW, can be determinedfrom multi-temporal measurements of ECa knowing the depth of penetration ofthe electromagnetic measurement as ΔW = L⋅{θ(ti) – θ(t–1)}. Alternatively, ECa

θ =−EC EC

EC Ta s

w


profiles can be inverted to obtain depth profiles of water content (Hendrickx et al.,2002). Equation (4.2) is generally linear for 0.0 ≤ θ ≤ 0.40 m3 m–3, but becomesnonlinear for θ > 0.40 m3 m–3 (Kachanoski et al., 1988; Sheets and Hendrickx,1995). The W(ECa) relationship should therefore be linear for the range of storageobserved in typical soils used to construct barriers in arid environments.

Both EMI and GPR have the potential to acquire data quickly and withsufficient spatial resolution to provide detailed subsurface moisture conditionsover large spatial scales. However, a few studies have investigated the use of EMIto monitor long-term trends in water content over large areas in arid environments.To date, there are no published accounts of the use of EMI to monitor waterstorage in surface barriers (Ward and Gee, 2001). The same can be said aboutGPR for which there are no published studies of its use to monitor spatial andtemporal changes in θ or soil-water storage, W, in engineered barriers. Successfulapplication of these techniques to field-scale monitoring requires a better under-standing of the nonlinear dependence of large-scale processes on θ and its vari-ability across multiple scales (Huisman et al., 2001). This need is the basis of thissection, which describes the use of nonintrusive geophysical techniques to mon-itor the spatial and temporal variability of W, from which hydrologic performanceof surface barriers might be inferred.

4.5.2 CASE HISTORIES

Several case histories are presented to illustrate how geophysical methods can beused to monitor moisture content in constructed and natural barriers.

4.5.2.1 EMI and GPR

A study was conducted on a prototype Hanford barrier located at the USDOEHanford site in southeastern Washington (Ward et al., 2003). The objective of thestudy was to investigate the relationship between the response of EMI and GPRto spatial and temporal variations in soil-water storage in a field-scale barrier.The prototype is a vegetated capillary barrier comprised of eight distinct layersof natural materials that has been monitored continuously for the last eight years(Ward and Gee, 1997, 2001). At the surface is a 1-m-thick layer of silt-loam with15% pea gravel, underlain by 1 m of silt-loam, followed by a coarsely gradedfilter of sand and gravel (Figure 4.25). The total thickness of the cover is about4.4 m, including the lowermost 0.15-m-thick asphalt concrete layer, which shouldform an ideal reflector for most nonintrusive geophysical instruments. The barrieris equipped with a variety of performance monitoring systems, including a drain-age monitoring system, access tubes for neutron probes and capacitance probesfor measuring water content, time domain reflectometry (TDR) probes for mea-suring water content, heat dissipation units for measuring soil-water suction, andsoil temperature probes (Ward and Gee, 1997, 2001).

Geophysical surveys were conducted in two phases using surface-deployedEMI and GPR (Table 4.3). The first phase was conducted in September 1994 and


the second over 10 months starting in March 2001. In the first phase, EMImeasurements were obtained on a 3 m by 3 m grid with the Geonics™ EM-38and EM-31 ground conductivity meters (Geonics, Mississauga, Ontario, Canada).Measurements with the EM-38 were obtained using both vertical and horizontaldipole orientations to achieve penetration depths of 0.75 m and 1.5 m, respec-tively. Measurements were also made at elevations of 0, 26, 54, 74, 94, 109, and124 cm above the barrier surface to allow estimation of the variations in ECa

with depth, z. The EM-31 survey was conducted with a vertical dipole orientationresulting in a penetration depth of 6.0 m. Measurements for determining theECa(z) were made using the same protocol as the EM-38 and from three additionalelevations: 154, 176, and 204 cm. Spatial and temporal variations in bulk apparent

FIGURE 4.25 Cross section of the northeastern quadrant of the prototype Hanford Barriershowing the layer sequence and riprap side slope. (From Clement, W.P. and Ward, A.L., Usingground penetrating radar to measure soil moisture content. Handbook of Agricultural Geo-physics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

TABLE 4.3Dates of Electromagnetic Surveys at the Prototype Hanford Barrier

Survey No. Survey Date Methods

1 September 30, 1994 EM38, EM312 March 9, 2001 GPR, EM313 May 22, 2001 GPR, EM314 September 19, 2001 GPR, EM315 January 9, 2002 GPR, EM31

West

Upper silt-loamw/pea gravel admix 1.0 m

Lower silt-loam 1.0 mSand filter 0.15 m Gravel filter 0.3 m

Basalt riprap 1.5 mDrainage gravel

0.3 m

Composite asphalt0.15 m (asphalt withfluid-applied asphalt

and curbed)

Top course 0.1 m

Sandy soil (structural) fill

In situ soil E9812066.2

East

50

Access roadway Basalt sideslope

Neutron probe access tubes 1

2 1


electrical conductivity were correlated with water content and storage. Neutronprobe measurements of θ(z) were used for comparison.

In the second phase, surveys were conducted with EMI and GPR. The GPRsurveys were conducted using two acquisition geometries. The first geometry wasthe common midpoint (CMP) method (Weiler et al., 1998; Greaves et al., 1996).The CMP profiles were acquired starting with an initial antenna separation of0.1 m and subsequently increasing the separation by moving each antenna 0.05 maway from each other (Figure 4.26). The wide off-set reflection geometry was

FIGURE 4.26 Plan view of barrier surface showing 3 by 3 m grid on which the geophys-ical surveys were made. EMI measurements can be taken in only a few areas, identifiedby (••••), without interference from buried instruments and cables. (From Clement, W.P. andWard, A.L., Using ground penetrating radar to measure soil moisture content. Handbookof Agricultural Geophysics, Allred, B.J., Daniels, J.J., and Ehsani, M.R., Eds., CRC Press,Boca Raton, 2003.)

N

E1

E2

E4

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E3

26

2423222120191817161514131211 10987654321

25NN

1

654

2E1

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1 2 3 4 5 6 7 8 9 10 11 12 13


the second configuration. In this configuration, the off-set between the antennasis much wider than in typical GPR reflection profiles. The CMP gathers wereused to determine the subsurface electromagnetic velocity and the optimal off-set for separating the air and ground waves. The optimal spacing was used toensure unambiguous identification of the airwave, the direct ground arrival, andthe reflection from deep reflectors.

Measurements were obtained with an initial spacing of 1.0 m, with subsequentreadings taken after moving the receiving antenna away in 0.1-m increments untilthe optimal off-set was reached. An optimal off-set of 3.5 m was determined fromthe CMP survey. Both antennas were then moved with a constant step size of0.25 m per trace while maintaining a constant separation of 3.5 m. Data fromboth geometries were filtered to remove low-frequency electronic and noise toincrease the signal to noise ratio of the arrivals. The GPR surveys were conductedwith a PulseEKKO™ 1000 GPR system with a 200 V transmitter (Sensors andSoftware, Mississauga, Ontario, Canada) with two sets of antennae with centerfrequencies of 100 and 200 MHz. After the first survey, data from the 200 MHzantennae proved inappropriate for the site conditions, and subsequent measure-ments were made with the 100 MHz.

The GPR data were processed using a combination of ground wave analysisand normal move-out analysis of the reflections (Yilmaz, 1987). Calculation ofθ was a three-step process. First, the velocities of the air and ground waves todepth L were calculated simply as v = L⋅t–1. The apparent dielectric permittivitywas calculated from the air and ground wave travel time picks as follows (Huis-man et al., 2001):

(4.3)

where c is the electromagnetic velocity in air, x is antenna separation (3.5 m),tground is the arrival time of the ground wave, and tair is the arrival time of the airwave. In the final step, κ was converted to a mean water content,

–θ, over the

sampling depth using the θ(κ) derived by Topp et al. (1980). Water storage overthe GPR sampling depth, L, was calculated simply as

–θL.

The penetration depth of the ground wave decreases with increasing antennafrequency, f, and increasing θ and is determined from the wavelength of theground wave, λ (Du and Rummel, 1994). The penetration depth can be expectedto vary between 0.5λ and λ with λ = c/(f ⋅ κ1/2). Use of 100 MHz antennae in thisstudy suggested a penetration depth of between 0.6 and 1.2 m, well within thethickness of the silt-loam layer (Figure 4.25). Soil-water content was also mea-sured using remote-shorting TDR to a depth of 1.8 m and with a neutron probeto a depth of 1.9 m (Ward et al., 2002).

Figure 4.26 is a plan view schematic of the barrier surface, including thelocations of surface and near-surface subsurface infrastructure. During each EMIsurvey, the 78 m by 40 m surface was mapped on a 3 m by 3 m grid for a total

κ =−( ) +⎡

⎣⎢⎢

⎤

⎦⎥⎥

c t t x

xground air

2


of 338 grid points. In addition, EM-31 surveys were conducted along transectN1 from south to north and along N2 from north to south. During the GPRsurveys, CMP gathers were collected to allow identification of the air and groundwaves and determine the optimal off-set for the wide off-set reflection surveys.A set of wide off-set reflection surveys was conducted along east-west transectsE1, E2, and E3 and along north-south transects N1 and N2.

4.5.2.2 Apparent Conductivity Maps

The presence of metallic components at and below the surface suggested thatelectromagnetic measurements might be adversely affected at some locations.However, the extent of the interference could not be determined a priori and inthe 1994 survey both the EM-38 and EM-31 conductivity meters were used. In the2001–2002 surveys, only the EM-31 meter was used. Maps of apparent electricalconductivity were prepared from the quadrature component of the EM-38 andEM-31 data. Figure 4.27 compares the EM-31 data from the September 1994and September 2001 surveys. All of the data sets show anomalous readings,including ECa < 0 mS/m and ECa > 25 mS/m outside the expected range deter-mined from independent measurements of θ and ECs. Areas of high ECa extendin an east–west direction at a northing of 26 m and 63 m and in a north–southdirection down the middle of the barrier. These anomalies are most likely due tometallic components (i.e., sensors, cables, and access tubes) of the monitoringstations in the barrier. Buried ferrous materials can influence electromagneticmeasurements by reducing the quadrature and in-phase response for all coilconfigurations. In an otherwise resistive soil, ferrous materials caused negativequadrature and in-phase measurements at low frequencies.

After the initial survey in 1994, many of the cables, particularly down themiddle of the plot, were encased in PVC conduit. This, plus generally drierconditions, caused a decline in ECa between the 1994 and 2001 surveys. Therelationship between ECa (W) derived from the filtered EM-31 data and W derivedfrom neutron probe measurements was good (Figure 4.28). Water content in thetop 1.9 m of soil was measured by neutron probe in vertical access tubes. Waterbetween the capillary break (2.0 m) and the in situ soil beneath the asphalt layerwas measured by neutron probe in horizontal access tubes (Figure 4.26). Apparentconductivities were standardized to 25°C using soil temperature data from thebarrier and the relationship described by Sheets and Hendrickx (1995).

Apparent conductivity maps from the 2001–2002 survey suggest that irriga-tion on the north end of the barrier between November 1994 and September 1997might have caused an increase in conductivity from the initial condition in 1994.The small size of the data set may limit use of this relationship for predictingthe full range of W from ECa measurements. However, it does suggest that themethod may hold promise for field-scale water storage monitoring. The mobilityof these instruments, the speed with which measurements can be made, and thesuccess of aerial EMI surveys in mapping large areas makes EMI an attractiveoption for monitoring large numbers of field-scale barriers. However, it is clear


that a larger data set is required to increase the robustness of ECa(W). Once thishas been accomplished, it is quite reasonable to expect that a relationship devel-oped for one cover design would be applicable to other covers constructed fromthe same materials and in a similar fashion.

The above approach is ideal for detecting lateral variations in ECa and pro-vides a measurement averaged over the depth of a profile. More information canbe derived from maps of the vertical changes in ECa. However, derivation of theECa profile from surface measurements requires solution of the inverse problem,a typically ill-posed problem. Such analyses, based on the assumption of linearity,have been reported (Wollenhaupt et al., 1986; Cook and Walker, 1992). Morerecently, linear and nonlinear methods combined with Tikhonov regularizationhave been proposed for the inversion of ECa profiles (Hendrickx et al., 2002). To

FIGURE 4.27 The quadrature component of the EM-31 surveys. (a) September 30, 1994;(b) September 18, 2001. (From Clement, W.P. and Ward, A.L., Using ground penetratingradar to measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J.,Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

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verify the utility of these methods, EM-38 measurements obtained at differentelevations were inverted using Tikhonov regularization. The data collected in the2001–2002 surveys were not amenable to this analysis. Profiles derived fromEM-38 and a combination of EM-38 and EM-31 were characterized by largefitting errors. The high fitting error may have been caused by the sensitivity ofthe EM-38 to ferrous components, the effect of which would increase as theheight of measurement increased. The inversion of EM-31 data only showed arelatively constant ECa of about 10 mS/m in the top 2 m followed by a rapiddecrease with depth. Joint inversion of EM-38 and EM-31 data showed an increasein ECa not supported by observed θ(z) profiles. However, this trend is consistentwith layer sequence of the barrier in which a 2 m layer of more conductive silt-loam is underlain by less conductive layers of sand, gravel, and basalt and riprap.

4.5.2.3 Electromagnetic Radar for Monitoring Moisture Content

Figure 4.29 compares the CMP profile with the calculated velocity at the easternintersection of transects E1 and N1 (easting of 26 m) in March 2001 and May2001. The ground wave in March was quite strong (Figure 4.29) and the 86 nstravel time projected to a 10-m antenna separation was practically identical to the88 ns observed later in January 2002 when the mean water contents were similar.Although the ground wave from May was weaker, calculation of travel time wasstill possible (Figure 4.29). The travel time at the 10-m antenna separation wasapproximately 75 ns, suggesting a higher velocity or lower water content andstorage compared to March. Mean velocities derived from ground wave analysiswere 0.119 m/ns in March, 0.115 m/ns in January, and 0.147 m/ns in May.

FIGURE 4.28 The relationship between soil-water storage and the standardized apparentelectrical conductivity, EC, derived from EM-31 measurements.

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FIGURE 4.29 CMP gathering and velocity analysis at the intersection of transects N1and E1 in (a) March 2001 and (b) May 2001. Note the changes in the ground wave andreflection character. The vertical white line in each plot shows the optimal antenna sepa-ration. (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measuresoil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J.,and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.) (See color version insert for thisfigure.)

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velocities of 0.105 m/ns in March and 0.120 m/ns in May. Although the velocityplots are quite similar, the green anomaly between 60 and 100 ns in the May plotis shifted to slightly faster velocities compared to the March plot. Although thiselectromagnetic velocity shift is small, it is indicative of a higher velocity in thematerial above the reflector. The increase in electromagnetic velocity, althoughsmall, is consistent with the electromagnetic velocity increase observed in theground wave arrival analysis.

The wide off-set reflection profiles also showed strong ground waves in Marchand January. Ground waves in May and September, although more difficult toidentify, were determined from a walk-away start of each survey. These data alsoshow larger ground wave arrival times (35 to 40 ns) or slower velocities in Marchand January than in May and September (30 ns). The higher velocities observedin May and September relative to those in March and January are consistent withthe CMP ground wave analysis and show a temporal change in velocity. Thesechanges are indicative of changes in water content in the silt-loam layer. Velocitieswere converted to κ with Equation (4.3) and to θ with Topp’s equation.

Figure 4.30 shows plots of the temporal changes in velocity of the groundwave and the water content along the transect E1. There was a notable increasein velocity and a decrease in θ from March 2001 to May 2001. There was asubsequent decrease in velocity and an increase in θ from September 2001 toJanuary 2002. These data also show a negative gradient in moisture content fromwest to east. At this point, the nature of the gradient is unknown, but it ishypothesized to be because of drier conditions on the east side of the barrier(Figure 4.29) caused by advective drying near the riprap sideslope. Until now,there were no data to confirm or reject this hypothesis apart from differences indrainage amounts from the sideslopes (Ward et al., 2002). In order to validate thetrends in θ, water storage was calculated for each transect and compared to datafrom the TDR and neutron probe.

As with the EMI measurements, the data set for validation was quite limited.Nevertheless, the radar data showed linear relationships between water storagederived for GPR measurements, WGPR, as well as that measured by neutron probe,WNP. The relationship between WGPR and WTDR is somewhat better with thecoefficient of determination being about twice that for the WGPR and WNP rela-tionship. A plot of W derived from the three methods showed that the neutronprobe generally underestimated θ and W relative to GPR and TDR. This is notsurprising because GPR and TDR measures essentially the same variable, κ, whilethe neutron probe responds to the presence of hydrogen, which is assumed toexist only because of the presence of water. The strength of the relationshipbetween GPR and TDR confirms that generalized TDR calibrations may be usefulfor the range of soil textures found in multi-layered barriers at arid sites. Signif-icant improvements in the relationship can be expected with site-specific calibra-tion. Of course, the relationship between κ and θ and hence the applicability ofGPR might be less appropriate for heavier soils used to construct barriers inwetter environments.


4.5.2.4 Aerial Photography

The following studies illustrate the use of aerial photography in characterizingand monitoring contaminated sites:

• Vincent (1995) used stereo aerial photos to compute a DEM of a landfillsite. The DEM was used to compute the volume of standing water thatcould be stored in cap depressions. The DEM was also used to computepotential surface water run off.

FIGURE 4.30 Dynamics of radar velocity and soil moisture along transect E1. (a) March2001, (b) May 2001. (March — red; May —green; September — yellow; January —blue). (From Clement, W.P. and Ward, A.L., Using ground penetrating radar to measuresoil moisture content. Handbook of Agricultural Geophysics, Allred, B.J., Daniels, J.J.,and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.)

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• Stohr et al. (1996) discusses the use of DEM extraction from a stereopair in aerial photos and the subsequent use of DEM in monitoringclosed landfill sites. The authors compare the results from the DEMand field-surveyed contours. Depths of 15 and 30 cm depressions werecorrectly located and computed by the DEM. All results fell within acontour interval of 0.15 m.

• Van Eeckhout et al. (1996) used historic aerial photos over Los AlamosNational Laboratory (LANL) in New Mexico, from 1947 to 1991, todetail and map surface-, trench-, and pit-buried wastes. Also, drainagepatterns of surface water run off were mapped as possible regions ofcontaminant movement.

4.5.2.5 Multi-Spectral Scanners

MSS technologies have been used to provide valuable imagery for a multiplicityof applications, such as the following:

• Vincent (1995) used MSS imagery to map changes in chemical con-stituents over a landfill. The author suggests that the data can be usedfor mapping stressed vegetation, clay horizons, and iron oxides asso-ciated with contaminated groundwater.

• Smyre et al. (1998) used a MSS sensor at the ORNL K-25 site to collectVNIR imagery. The imagery was used to detect vegetative stress dueto soil or groundwater contamination. The data were used to provideland cover and land use classification information for input into aregional database.

• Polosa (1995) used Landsat multi-spectral™ scenes to detect landfillsthat were abandoned. Some of the sites were relatively small. Usingancillary supporting data, the author was successful in demonstratingmapping of such sites.

• The Federal Energy Technology Center (1997) used SPOT satelliteimagery and airborne scanner imagery to detect buried trenches andseepages from capped waste sites. Hydrologic information was mergedwith the MSS imagery in a GIS system to plan soil sampling strategies.

4.5.2.6 Thermal Scanners

Examples of the use of thermal remote sensing imagery include the following:

• Ziloli et al. (1992) used a thermal camera to image thermal contrastsin and around waste sites. Their results demonstrated that TIR imagerywas useful for differentiating between consolidated wastes and wastesections where methane gas conversion was occurring. Also, a distinc-tion between water contaminated with acid slime and uncontaminatedwater due to a change in thermal capacity can be detected by thermalimagery.


• Van Eeckhout et al. (1996) used TIR imagery over LANL waste. TheTIR imagery was used as a GIS data layer. The imagery was valuablefor extracting the location of waste trenches and finding disturbedground. In general, because there was different packing of the soil inthe trench areas, the soil moisture in these trenches tended to be twicethat of the surrounding background areas. This had the effect of low-ering the temperature of these trench areas.

• Smyre et al. (1998) used pre-dawn and daytime TIR airborne imageryto delineate the hydrology of an area, including the identification ofseep and spring locations. Also, the TIR imagery was useful in mappingdifferent land cover materials and detecting waste trenches and zonesof disturbance from digging.

4.6.2.7 HIS Imagery

The following examples illustrate how HIS imagery has been used to characterizeand monitor waste sites:

• Mackey et al. (1995) used HIS data for the Savannah River site inAiken, South Carolina. The imaging spectrometer used 85 bands thatcovered the 466 to 880 nm range. The investigators used a narrow bandnormalized difference vegetation index (NDVI) to map biomass overthe relevant region. Some problems arose because no coeval grounddata was collected to aid in calibrating the acquired HIS imagery.However, the results clearly showed that HIS data was useful in mon-itoring landfill areas at the site where leachate effects on vegetationcould be mapped.

• As part of a NASA Stennis co-sponsored project, MTL Systems andthe University of South Carolina combined to analyze AVIRIS imagecubes over the Savannah River site to determine their value in moni-toring the integrity of waste site caps. The study showed that hyper-spectral data, when analyzed appropriately, provides valuableinformation on vegetation stress growing over or downslope fromcompromised caps. Additionally, based on associated work with soildisturbances due to erosion or bioturbation (Kelch et al., 1999), it issuggested that HIS imagery is able to discriminate such disturbancesfor a wide range of soil types.

4.6 SUMMARY

Despite geophysics being used successfully for many years in mineral, petroleum,and geothermal exploration, it has not been used effectively in remediation situ-ations. By and large, the examples of geophysics applied to problems appearingin literature are individual examples of specific applications. Exciting new devel-opments in geophysics, especially new methods of imaging subsurface properties,


seem to be lagging for environmental applications. Further work should focus onincorporating geophysical mapping of subsurface properties into site character-ization programs.

4.6.1 PRIMARY NEEDS FOR ADVANCEMENT

The four main needs for advancement are integration, processing and interpreta-tion, code development, and instrumentation.

4.6.1.1 Integration

The primary and greatest need is data integration to determine which methodsare appropriate for any particular application. If the state of practice of geophys-ical methods in the environmental industry is compared to the oil and gas industry,a need for case histories of geophysical method use in a variety of geologicsettings can be identified. Before the successes of geophysics in other industries,there were many failures. Geophysics requires knowledge of the appropriateapplication. No method works everywhere. We must learn when and how to usethe different methods, which will only occur through experience during use andapplication. In some cases, utility will become quickly evident (no data or poordata). Issues of resolution, investigation depth, and the linkage to various prop-erties and processes can then be more easily derived. To optimize not only thegeophysical methods themselves but also their use, an approach that differs frompast practice must be employed. Integration is a concept that is easy to visualizebut difficult to achieve. Integration must occur at a variety of levels, from datacollection to final interpretation and processing. Not only must the geophysicsbe integrated as a process, but it must also be integrated into the entire systemof site remediation along with other disciplines.

4.6.1.2 Processing and Interpretation

Individually, a wide range of processing and interpretation packages exists forprocessing and interpreting data. Methods are needed for using combined datasets to derive physical properties and either directly or indirectly relate data tochemical and microbial properties. Stated in another way, a map of seismicvelocity, radar images, and conductivity is of no use to the engineer unless it canbe transformed into a property of interest. A 3-D image of the distribution ofsuch properties as moisture content, the contaminant of interest, or a remediationtool (e.g., steam, water, microbes) is ideal. Therefore, future work should focuson integrating the various methods and interpretations. A statistical approach canbe taken by gathering sufficient data to derive meaningful correlation betweenthe geophysical parameters and a property of interest. This could be achievedusing both laboratory and field studies, although issues of scaling are importantto address when using these data, or an analytical approach can be taken bydeveloping theories on the various hypotheses of geophysical properties related


to some other property. Although it was empirically derived, Archie’s law relatingporosity and matrix properties to resistivity is an example.

4.6.1.3 Code Development

Code development is a continuing process driven by the data and needs of aparticular problem. Current code development needs are joint inversion schemesutilizing different types of data (e.g., data obeying the diffusion and wave equa-tion) and codes that can model and handle true 3-D data types (e.g., single-wellseismic and electromagnetic). Once the appropriate driver exists from the appli-cation and data needs and after a specific application can be identified, manydifferent activities in code development can be listed.

4.6.1.4 Instrumentation

Recent advances in high-resolution instrumentation have addressed many of theproblems associated with deploying modern geophysical methods for environ-mental applications. Ten years ago, there was a dearth of instrumentation thatcould take advantage of the powerful data processing approaches being deployedfor oil and gas. To a large extent, a wide range of commercially available methodsis ready to be applied at environmental cleanup sites, especially for the inductiveand DC electrical methods. However, a need exists for cost-effective instrumen-tation as applied to vadose zone issues. It should be noted for demonstrationswhere the prime objective is not minimizing cost but investigating applications,a wide range of systems are ready to be applied (e.g., electrical methods, magnetic,and deformation).

4.6.2 FUTURE DEVELOPMENTS

The preceding sections illustrate that geophysical methods are promising tech-nologies for enhancing construction and performance evaluations. Applicationsto site characterization prior to and during construction were also identified. Thebarrier/host is a complex dynamic system. Enhanced communication between thecontainment engineer and geophysicist is required in order for the geophysicistto better understand what needs to be monitored and what changes in subsurfacegeophysical properties are likely. For example, in a PRB emplacement, the distinctelectrical properties of granular iron encourage further work with technologiesthat are sensitive to the subsurface electrical conductivity. Imaging technologiesthat sense conductivity structure (i.e., electrical resistivity, electromagnetic, andGPR) should be developed as noninvasive tools for assessing construction veri-fication. In a vertical grout emplacement, the interaction and curing of the groutoffers challenges and opportunities in not only monitoring the emplacement butalso in assessing the performance as a function of time. The case studies previ-ously described demonstrate the potential of these methods. However, numerical,laboratory, and field studies could optimize these technologies as applied toconstruction verification.


Future developments in remote sensing that could improve the monitoring ofwaste sites include ultra-spectral airborne sensors (UIS), HIS thermal sensors,LIDAR technology, interference synthetic aperture radar (IFSAR or InSAR)technology (including polarimetric approaches), and open-path Fourier transforminfrared (OPFTIR) spectroscopy. The capabilities of these new remote sensingsystems and potential applications are described below.

• Developments in UIS, which is an extension of HIS technology, areunderway. Whereas the present state-of-the-art hyperspectral sensorscover the range of 400 to 2500 nm with 224 channels that are approx-imately 10 nm wide, a UIS would provide channels that would numberin the thousands with very narrow bandwidths. The advanced UISwould truly emulate an airborne chemical laboratory spectrometer.Given an adequate atmospheric correction, landscape chemistries couldbe interrogated to allow accurate assessments of leachate species.

• HIS thermal sensors represent a research area that is rapidly achievingoperational status. The emissivity channels would number in the hun-dreds. This spectral definition would become available and would boostthe application of thermal technology to landfill monitoring signifi-cantly. An example of a TIR HIS is the SEBASS sensor (Vaughan andCalvin, 2001). The SEBASS covers both the 3 to 5 μm and 8 to 12 μmrange with 128 bands in each spectral emission region. It provides a2-m ground sample cell and has a 256-m swath. Moreover, the avail-ability of portable TIR spectrometers (Korb et al., 1996) allows forfield measurements to be obtained to calibrate and validate airborneTIR HIS data.

• A scanned, multi-wavelength, airborne LIDAR sensor system wouldbe capable of emitting several user-selected, narrow laser wavelengthsat once to interrogate the environment. The return intensity of thelandscape-reflected LIDAR pulses would be captured by the systemreceiver and would be used to create a multi-spectral reflectance image.Because this would be an active system, it could be used at night andunder cloudy conditions as long as the sensor was flown under thecloud deck. Furthermore, landscape elevations could be extracted fromthe data to give highly accurate DEMs that could be used to orthorectifythe multi-spectral image obtained from the pulse-return intensities.Finally, with an additional receiver tuned to receive stimulated fluo-rescence emissions due to the LIDAR excitations, the fluorescent spec-troscopy of the landscape materials could be analyzed. This is importantbecause chemical species and vegetation stress could be detected acrossa selected site.

• IFSAR technology consists of radar sensors using coherent returnsfrom two radar systems along a common time baseline to beat one signalagainst another. This process creates an image interferogram of the givenscene. The interferogram provides spatial shift/change information of


the imaged scene. This technology could be used to assess smallchanges (millimeter range) in elevation or lateral dislocations in aclosure cap. IFSAR technology is relatively operational and could beutilized for waste site monitoring. The difficulty is the cost of the dataand the relative scarcity of usable radar sensor systems at present.

• OPFTIR spectroscopy can be used to measure and monitor chemicalcontaminants and fugitive emissions in situ at landfill sites. In fact, theUnited States Environmental Protection Agency (USEPA) has beeninterested in composing an infrared spectral database to supportOPFTIR remote sensing (Chu et al., 1999). A definitive set of spectralreference data is required because published molar absorptivity valuescan vary significantly. These systems have been used at Superfund sitesand have performed well. The sensors can detect contaminants at theparts per billion level. However, these systems can suffer from atmo-spheric noise sources (e.g., strong absorption bands of water vapor andcarbon dioxide) and detector limitations.

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287

5 Subsurface Barrier Verification

Prepared by*

David J. BornsSandia National Laboratories, Albuquerque, New Mexico

Carol Eddy-DilekWestinghouse Savannah River Company, Oxford, Ohio

John D. KoutsandreasFlorida State University, Tallahassee, Florida

Lorne G. EverettL. Everett and Associates, LLC, Santa Barbara, California

5.1 OVERVIEW

Waste containment system performance data are needed to conduct assessmentsthat reveal the integrity of the barrier and verify that the operational aspects ofthe systems are functioning as designed. Biological, chemical, and physicalphenomena in the subsurface or some combination thereof can impact the per-formance of subsurface barriers. To confirm the performance of the barrier andpossibly determine where a failure has occurred, a well-planned and implementedmonitoring system is required.

The design service life of a containment system can range from as little as10 years for slurry walls to more than 1000 years for radioactive waste storagestructures. The longer the service life of a containment system, the greater the

* With contributions by William R. Berti, DuPont Central Research and Development, Newark,Delaware; Skip Chamberlain, U.S. Department of Energy, Washington, DC; Thomas W. Fogwell,Fluor Hanford, Richland, Washington; John H. Heiser, Brookhaven National Laboratory, Upton, NewYork; John B. Jones, U.S. Department of Energy, North Las Vegas, Nevada; Eric R. Lindgren, SandiaNational Laboratories, Albuquerque, New Mexico; William E. Lowry, Science and EngineeringAssociates, Inc., Santa Fe, New Mexico; Keri H. Moore, National Research Council, Washington,DC; Horace K. Moo-Young, Jr., Villanova University, Villanova, Pennsylvania; Michael G. Serrato,Westinghouse Savannah River Company, Aiken, South Carolina; Matthew C. Spansky, WestinghouseSavannah River Company, Aiken, South Carolina;


probability of system failure. Because most components of containment systemsexist underground, direct visual inspection is not tenable as a monitoring method.Thus, several traditional and evolving techniques of indirect and direct observa-tions need to be employed to obtain performance data.

In terms of containment system effectiveness, two types of failure categoriescan be identified: structural failure and functional failure. Structural failure canoccur without functional failure, although it can eventually lead to functionalfailure. Thus, verification monitoring of barrier structural and/or functional fail-ures is essential over the life of the barrier. Long-term monitoring is an importantaspect in determining the integrity of the barrier over the lengthy lifetimes ofmany contaminants. This chapter discusses the state-of-the-art monitoring tech-nologies and recommends innovative methods such as in situ sensors to improveand reduce the cost of barrier monitoring.

5.2 GOALS

Subsurface verification is integral to achieving acceptance of covers, permeablereactive barriers (PRBs), and subsurface barriers such as walls and floors. Theroles of subsurface verification in this process of acceptance are as follows:

• Meet or exceed regulatory requirements• Verify performance of engineered barriers• Verify conceptual models of contaminant fate and transport• Verify models for containment systems• Conduct long-term performance monitoring• Ensure identification of trigger levels for contingency actions

At present, there are no specific regulations under the Comprehensive Envi-ronmental Response, Compensation, and Liability Act (CERCLA) or theResource Conservation and Recovery Act (RCRA), and there is no regulatoryguidance on subsurface barrier integrity or performance validation. The onlyregulatory standard for barriers is the RCRA requirement (40 CFR 264, SubpartN, Landfills) of a 10–7 cm/s hydraulic conductivity at a thickness of 0.91 m.Additional standards may be added in the near term because the United StatesEnvironmental Protection Agency (USEPA) Office of Emergency and RemedialResponse has launched the Superfund Initiative on Long Term Reliability ofContainment (Betsill and Gruebel, 1995). The USEPA is scheduled to work withother U.S. agencies to develop technical guidance and methodologies to evaluatecontainment technologies.

The American Society for Testing and Materials International (ASTM) hasstandards pertaining to barrier monitoring. Reference to these standards shouldbe made when considering potential methods. The ASTM D18.21.02 committee,chaired by Lorne G. Everett, on vadose zone monitoring standards is responsiblefor publishing the list of vadose zone standards provided in Table 5.1.

Subsurface Barrier Verification 289

5.3 VERIFICATION MONITORING

Monitoring plays a key role at all stages in environmental management — frominitial site discovery to site closure. Monitoring programs are essential in facili-tating site characterization and risk assessment, adequately conducting experi-mentation and evaluation, producing the data necessary for the performanceevaluation, determining whether residual contamination exists that will preventsite closure, and verifying the effectiveness of containment structures. The focusof monitoring programs is necessarily site and time specific. For example, a soilremedial action may primarily require sampling during excavation and immedi-ately after remediation work is complete (site closure). For sediment and ground-water remedial actions, longer-term monitoring programs might be developedthat have their roots in initial site characterization activities, continue throughremediation, and extend for significant periods of time beyond termination ofactive remediation. In the case of groundwater, most sites begin with an inheritedset of monitoring points already established and so part of the monitoring designprocess also includes determining to what extent the existing network can beused or must be abandoned or expanded. Depending on the selected remedialaction (Table 5.2), monitoring programs can represent the majority of remedialaction costs (e.g., monitored natural attenuation) or only a small percentage.

Traditional characterization and verification monitoring programs tend to pre-specify sample numbers, locations, sampling frequency, and analytics (i.e., off-site laboratory analyses). This traditional type of data collection presents several

TABLE 5.1ASTM International Vadose Zone Monitoring Standards

Vadose zone terminology (final)Soil pore-liquid monitoring (D 4696-92)Soil core monitoring (D 4700-91)Matrix potential determination (D 3404-91)Neutron moderation (D 5220-92/97)Soil gas monitoring (D 5314-93)Hydraulic conductivity (D 5126-90)Decontamination of field equipment (D 5088-90)Flux determination by time domain reflectometry (D 6565)Determining unsaturated and saturated hydraulic conductivity in porous media by steady-state centrifugation (D 6527)

Horizontal applications of neutron moderation (D 6031)Frequency domain capacitance (Z4302Z)Field screening guidance standard (final)Water content determination (draft)Vadose zone borehole flow rate capacity test (draft)Air permeability determination (outline)Thermalcouple psychrometers (outline)


TABLE 5.2Progressive Monitoring Steps for a Remediation by Natural Attenuation Program

Step Description Parties Involved

I Establish point of compliance

Specify point of compliance and the point at which monitoring must be conducted

Regional administrator

II Define what is to be monitored

Demonstrate that natural attenuation is occurring according to expectations accomplished by including steps to:1. Identify any potentially toxic transformation

products; Determine if a plume is expanding (either downgradient, laterally or vertically)

2. Ensure no impact to down gradient receptors3. Detect new releases of contaminants to the

environment that could impact the effectiveness of the natural attenuation remedy

4. Demonstrate the efficacy of institutional controls that were put in place to protect potential receptors

5. Detect changes in environmental conditions (e.g., hydrogeologic, geochemical, micro-biological, or other changes) that may reduce the efficacy of any of the natural attenuation processes

6. Verify attainment of cleanup objectives

Site operator and regional administra-tor (USEPA or the state-implementing agency)

III Establish the time period for monitoring

Continue as long as contamination remains above required cleanup levels, continue for a specified period (e.g., 1–3 years) after cleanup levels have been achieved to ensure that concentration levels are stable and remain below target levels.

Regional administrator (USEPA or the state-implementing agency)

IV Define how monitoring is to be done

Demonstrate of the monitoring approach being appropriate and verifiables accomplished by including steps to: 1. Specify methods for statistical analysis of data,

e.g., established tolerances, seasonal and spatial variability

2. Establish performance standards:• Information on the types of data useful for

monitoring natural attenuation performance in the ORD publications (EPA/540/R-97/504, EPA/600/R-94/162)

• EPA/600/R-94/123: a detailed document on collection and evaluation of performance monitoring data for pump-and-treat remediation systems

Site operator and regional administrator (USEPA or the state-implementing agency)


limitations, particularly in the context of subsurface characterization and moni-toring. The costs are sometimes prohibitive, driven both by sample analyticalcosts and the capital investment required for monitoring wells. High monitoringcosts, particularly for monitoring programs that extend over time, result in pres-sures to limit data collection. Limited data collection, in turn, results in decision-making that relies on data sets too sparse to adequately address the inherentheterogeneities and uncertainties associated with subsurface barrier systems.Finally, by prespecifying sample numbers and locations and relying on off-site

TABLE 5.2 (continued)Progressive Monitoring Steps for a Remediation by Natural Attenuation Program

Step Description Parties Involved

• Standard test methods such as described in EPA SW-846, “Test Methods for Evaluating Solid Waste - Physical/Chemical Methods” or EPA publication, “Methods of Chemical Analysis for Water and Wastes”

3. Establish a time interval agreed upon by regional administrator or agency, including reporting maps, tabulation of data and statistical analysis, identification of trends, recommendations for changes in approach, evaluation of whether contaminants have behaved as predicted, and whether other remedies are required

V Define action levels or process to be observed for monitoring

Establish metrics for the monitoring system:1. Establish background levels2. Define what criteria shows that a plume is

expanding or diminishing3. Define what criteria shows that the conceptual

model is applicable to a site4. Determine the metrics of cleanup objectives

and effectiveness

Site operator and regional administrator (USEPA or the state-implementing agency)

VI Define actions to be accomplished when action levels or processes are observed

Establishment of action plan to follow attainment of metric:1. Observe requirement to report to responsible

party or agency statistically significant variance compared to background

2. Identify extent and nature of nonpredicted behavior (e.g., release)

3. Re-evaluate conceptual model and evaluate feasible corrective actions from previous and evolving contingency plan

Site Operator will provide details of the monitoring program; should be provided to USEPA or the state-implementing agency as part of any proposed monitored natural attenuation remedy


laboratory analyses with long turnaround times for analytical results, traditionalcharacterization and monitoring programs are ill equipped to handle unexpectedresults. Fortunately over the last several years, technological advances haveoccurred in sensors, field analytics, and sample collection technologies that canhelp to lower costs and/or increase the effectiveness of monitoring programs (seeBox 5.1). New approaches for designing and implementing environmental datacollection programs have also been developed. A few of those innovative barrier-monitoring technologies are discussed in the subsections below.

5.3.1 METHODS

Methods for barrier monitoring generally fall into broad classes such as measure-ment of moisture change, collection of moisture and gas samples, temperature,flow/velocity, barometric pressure, and settlement. An in-depth evaluation ofbarrier-monitoring science and technology is provided in the National Departmentof Energy Vadose Zone Science and Technology Roadmap [Idaho National Envi-ronmental Engineering Laboratory (INEEL), 2001].

5.3.1.1 Moisture Change Monitoring Methods

A number of methods are available for barrier-monitoring moisture change insoils (Everett et al., 1984; Wilson et al., 1995; Looney and Falta, 2000a,b). Manyof these measurement techniques require laboratory testing to develop calibrationcurves relating instrument output to soil moisture content. Several of the morecommonly used methods are described below.

BOX 5.1Rapid Field Characterization of Sediments

Rapid field characterization techniques have been developed to speed assessment and reduce costs. These are field-transportable screening tools that provide measurements of chemical, biological, or physical parameters on a real-time or near real-time basis. Specific advantages include the ability to get rapid results to guide sampling locations, the potential for high data mapping density, and a reduced cost per sample. The approaches do have limitations including the nonspecific nature of some tests, sensitivity to sample matrix effects, and some loss in accuracy over conventional laboratory analyses. A variety of tools has been suggested for the rapid characterization of sediments, as shown in the table below.

Screening-Level Analyses Recommended by the Assessment and Remediation of Contaminated Sediments Program for Freshwater Sediments

Analytical Technique Parameter(s)

X-ray fluorescence spectrometry (XRF) MetalsUV fluorescence spectroscopy (UVF) Polycyclic aromatic hydrocarbons (PAHs)Immunoassays PCBs, pesticides, PAHsMicrotox Acute toxicity


• Neutron probe — The neutron probe contains a source of neutronsand detectors to measure backscattered neutrons. The magnitude andenergy of backscattering is primarily a function of the hydrogen contentof the material surrounding the probe. To take readings, the neutronprobe is lowered into the pipe and a continuous record of the responseis obtained. Changes in the readings over time at a particular depthindicate changes in the number of hydrogen atoms, i.e., water content.The neutron probe must be calibrated for specific soils. This methodis discussed in more detail in Section 5.9.1.1.

• Time domain reflectometer — In this method, an electromagneticwave is transmitted along a transmission cable buried in soil. At theend of the cable, a portion of the signal is reflected. The amplitude andtravel time of the reflected portion depend on the dielectric propertiesof the soil, which in turn are strongly dependent on soil moisturecontent. The output is typically monitored on an oscilloscope or cabletester. These probes can be monitored remotely and have no directanalytical costs associated with them other than initial calibration. Thistends to minimize life-cycle costs.

• Thermocouple psychrometer — This instrument measures relativehumidity within the soil pores, from which soil water potential andtherefore moisture content can be calculated. Humidity is determinedby the observed difference in temperatures between two thermocou-ples, one of which is exposed to the humidity in the surrounding soiland experiences cooling; the other thermocouple is located adjacent tothe first but is isolated from the humidity. Moisture content is deter-mined from relative humidity on the basis of laboratory calibration.

• Electromagnetic Induction (EMI) — EMI is a standard geophysicaltechnique (Chapter 4) that is used to measure the conductivity of soilmass. At the ground surface, a transmitter coil generates an electro-magnetic field that induces eddy currents in the underlying subgrade.Secondary electromagnetic fields created by the eddy currents aremeasured by a receiver coil that produces an output voltage related tothe subsurface conductivity. EMI is a rapid technique that is often usedto delineate contaminant plumes, buried wastes, and other features thathave conductivity contrasts with the surrounding soil.

• Electrical resistivity tomography (ERT) — ERT is based on a largenumber of soil resistance measurements (Chapter 4) analyzed by math-ematical methods (e.g., finite difference models employing inversiontechniques). Each resistance measurement involves several electrodes,some to apply a current through the soil and some to measure thevoltage drop. The location and spacing of the electrodes determinesthe soil volume being measured; in general, larger electrode spacings areused at greater depth. Commonly, a linear series of electrodes is placedon the ground surface or beneath a landfill. An automatic monitoring


system excites various pairs of electrodes according to a programmedsequence and measures the resistance between other pairs. When alldesired combinations have been read, the resulting data are analyzed.The result is a two-dimensional contour map (i.e., a vertical or hori-zontal slice) of soil resistivity along the electrode line. Changes inmoisture content over time appear as changes in resistivity. Laboratorycalibration of subgrade soil is required to develop quantitative relation-ships. High-resolution resistivity has shown particular merit in bothcap and subsurface liner monitoring but is not developed to a stagewhere it can be recommended in the near term.

• Fiber-optic cable — These systems could be considered as one of thelatest improvements in vadose zone sensor systems. Fiber-optic sys-tems already are measuring strain, temperature, acoustics, moisture,pH, flow, and chemicals. Fiber-optic cable could be included in thefuture applications of a monitoring system. The cable could bedeployed in the perforated stainless-steel tubing laid down below thebottom liner during construction. Consideration could be given toincluding fiber-optic cable in the horizontal and vertical monitoringorientations. The cost advantages expected with the use of fiber-opticsensors are substantial. The risk of causing preferential flow pathsassociated with installing a very small diameter fiber cable is smallrelative to the other technologies.

5.3.1.2 Moisture Sampling Methods

There are processes other than leakage through the barrier liner system that couldcause changes in moisture content of the vadose zone. Examples include moisturerelease from the admix layer as it consolidates under the load of the waste, andvapor migration due to temperature changes caused by excavation, lateral mois-ture, or vapor movement into the trench (from outside the trench), and removalof subgrade soils. Moisture change resulting from such processes could be diffi-cult to distinguish from leachate. In addition, those methods described above inSection 5.3.1.1 that use electrical properties of the soil would be influenced bydissolved constituents as well as moisture content alone. In spite of these limi-tations, in the case of a RCRA cap, which is designed as an impermeable cap,elevated moisture migration rates alone can be used as an indicator of increasedinfiltration through the cap.

To determine whether moisture is the result of leakage through the barrierliner, samples are collected and analyzed for constituents known to occur in thewaste material. A number of techniques are available and are described in theliterature (Everett, 1980; Everett et al., 1984; Wilson et al., 1995; Looney andFalta, 2000a,b).

• Suction lysimeter — The suction lysimeter consists of a porous cupor plate attached to a small diameter tube leading to a sampling chamber.


The lysimeter is buried in the soil at the location where a sample isdesired, and the tubing leads to an accessible location. To obtain asample, a reduced pressure is applied to the lysimeter. Water in the soilmatrix is sucked into the lysimeter and accumulates in the samplingchamber. There are various modifications utilizing additional tubes,check valves, and other components to allow samples to be retrievedfrom depth, but the basic operating principle is the same.

• Absorbent pads — This method uses pads of absorbent material, suchas felt, to collect soil moisture. One commercially available system(Flute) that has been used to collect samples beneath a radioactivewaste landfill at Los Alamos National Laboratory (New Mexico), usesa cylindrical flexible membrane that holds the pads. The membrane isinitially inside out, or inverted, and is everted as it is placed in theborehole so that the pads contact the borehole wall. After a period oftime, when the pads have reached equilibrium with the surroundingmaterial, the membrane is withdrawn, being inverted again during thisprocess so that the pads are not contaminated. In soil materials, wherean open borehole cannot be maintained over the long term, a permeablecasing is required.

• Sodium iodide gamma detector — This is a radiation-measuringinstrument that is lowered down an access pipe. Rather than returninga sample to the ground surface, the detector measures the radioactivityof the surrounding soil. This method identifies contaminants that aregamma emitters in sufficient concentrations to be clearly detectable.For additional details, refer to the discussion in Section 5.5.2.1.

• Basin lysimeter — The basin lysimeter consists of a broad, shallowbasin a few meters in dimension. It is lined with a geomembrane andbackfilled with vadose zone soil. The floor of the basin slopes to acollection point, and a pipe leads from this point up to the groundsurface. When a sample is required, a sampling pump is lowered downthe pipe, where quantifiable measurements can be obtained.

5.3.1.3 Vadose Zone Monitoring Considerations

To monitor flow and transport in covers, walls and floors, point-type probes suchas tensiometers, time-domain reflectometry probes (TDR), suction lysimeters,and thermistors can be used as well as geophysical imaging methods such asseismic surveys, ground penetrating radar (GPR), and three-dimensional (3-D)ERT (Hubbard et al., 1997). Point-type probes may or may not intersect singleflow paths (Figure 5.1). The shortcoming of point-type probe measurements isthe difficulty of combining their responses in a meaningful way, such as integrat-ing or volume averaging responses from a number of point measurements. Geo-physical imaging methods complement point-type measurements by providing aspatially distributed view of subsurface conditions. Each measurement representsan average over space and time; however, the volume affected cannot be determined.


The shortcomings of geophysical methods are their lack of spatial resolution indetecting small barrier leaks, and the difficulty of correlating values such aselectromagnetic responses and seismic velocities to hydrogeologic parametersgoverning fluid flow. Neither method can be used to observe flow in singlefractures of fluid movement at the fracture matrix interface in sufficient detail toaccurately represent transport through barriers.

5.4 VERIFICATION SYSTEM DESIGN

One of the key issues discussed at the workshop was integrating the verificationsystem design into the overall barrier design. The barrier must have a set ofperformance requirements that are site specific and risk based. Without a risk-based performance objective, the barrier is either intact and good or breachedand unusable. As stated previously, none of the regulatory agencies has a set ofcriteria for a barrier. De facto, the regulators take a risk-based approach toapproving such structures. Risk-based performance objectives are crucial to thesuccessful deployment of subsurface barriers.

This fact is demonstrated when comparing two identical failures in a barrierat distinctly different locations. Suppose an obstruction blocks the flow of groutduring installation of a barrier wall, resulting in a 1 m2 hole in the barrier wall.In one case the hole occurs within 1.2 m of the uppermost (shallowest) regionof the barrier. In the other case, the hole is located at the bottom region of thebarrier. Water flux through the waste site would result in contaminant mobilization

FIGURE 5.1 Schematic of the performance of local-type and cross-borehole monitoringmethods in a heterogeneous formation (In Situ Remote Sensors and Networks, 1999e).

1. Tenslometers, ER probes,TDR provide local (6–20 om)measurements

2. Vacuum watersampling and neutronlogging affect the 30–40 omnear borehole

3. Cross-hole radar and3D ER; tomography areeffective within thezone of up to 10–12 m

Preferred water

1

1

2

2

3

3


and transport with the water. Water flow would occur mostly in a vertical directiondue to gravity. Near the surface of the barrier, horizontal spread would be minimaland the likelihood that water will transport out of a hole near the top of the barrieris small. At the bottom of the barrier, water would collect and any hole in thisregion would serve as a drain, similar to a bathtub. These two nearly identicalflaws in the barrier have extremely different consequences. One would requirerepair and the other could be ignored entirely.

When designing a verification/monitoring system, it is crucial that a set offailure criteria be established. This may necessitate implementing an iterativeapproach to barrier and verification designs. Once the performance requirementsare established for the barrier and a conceptual model is developed, a conceptualverification system can be designed. The conceptual barrier design may need tobe modified to accept the verification design (e.g., use of plastic componentsinstead of metal to allow for the use of ground penetrating radar). Once conceptualmodels for both have been developed, the failure mechanisms of the barrier needto be identified. Using risk assessment models, the failure scenarios can besimulated to determine what constitutes unacceptable failure of the barrier.Depending on the results, the verification/monitoring system may requirechanges, which can result in further modifications to the barrier design and soforth. This process continues until an acceptable combination of barrier designand verification/monitoring system is achieved.

5.5 MOVING FROM STATE OF THE PRACTICE TO STATE OF THE ART

Subsurface verification suggests that containment design and implementationmove toward the state of the art rapidly from the current state of the practice. In1976, Everett et al. recommended neutron probes and suction lysimeters for capand floor barrier monitoring. Thirty years later, these same two techniques arestill primarily used for barriers in California. The basic steps to accomplish thisbadly needed state-of-the-art transition are twofold:

1. Take a full system approach in which design, implementation, charac-terization, and verification are iterative, inter-connected, and ongoing.This integrated approach includes optimizing the verification activities,defining the performance goals and action levels, and using methodsto quantify uncertainty.

2. Move implementation toward the smart structure approach now usedin buildings, bridges, roads, and other structures in which sensors andtelemetry are incorporated during construction. This smart structureapproach will affect a lowering of cost through in situ analysis andhelp achieve the end state at many sites that are expected to have noon-site restoration personnel.


5.5.1 SYSTEM APPROACH

The technical process of total system performance assessment (i.e., integrationdesign, prediction, and data collection) may appear complex initially. However,such processes are used in our everyday lives (e.g., buying a car, selecting anarea where to live, choosing a career). The approach here is to build on thefamiliar everyday aspects to develop a process that can be rigorously and defen-sibly applied to environmental remediation (Borns, 1997). The predictive toolsand data needs from subsurface monitoring programs for boosting long-termcontainment system performance are part of an integrated system of data collec-tion, decision analysis, and uncertainty analysis. The engineering process ofdecision analysis and uncertainty analysis bridges the gap of predictive tools usedbetween the engineering design and the long-term performance assessment meth-ods (tens of years to thousands of years of performance). Decision analysis anduncertainty analysis also provide a basis for an integrated and interactive approachusing design, predictive models, and the analysis of the accumulated data atdifferent stages of the project.

All projects, engineering and environmental, have built-in decision processesthat involve varying risk-reward scenarios (Lockhart and Roberds, 1996). Theseprocesses can be based on intuitive, analytic, numerical, and expert judgmentapproaches. Developers, end-users, and stakeholders evaluating in situ stabilizationand containment systems are faced with a similar problem of selection. However,the time periods of predicted performance are longer, and the consequences offailure are higher than these everyday examples of system prediction. The pre-dictive tools and the data, which are used to ascertain long-term performance,are required to be rigorous, documented, and defensible. Such predictions oflong-term performance are based on conceptual models of system design and thegeological environment (natural system) that encompasses the system. Theseconceptual models and the adequacy of the performance prediction reflect theuncertainties and data quality that describe natural and designed containmentsystem performance.

5.5.1.1 Links to Modeling and Prediction

An example of the important link among landfill design, modeling, and perfor-mance assessment is in the realm of permeable reactive barriers. Morrison et al.(2001) described the importance of reaction path modeling to predict and verifyPRB performance. Similarly, Roh et al. (2000) demonstrated the importance ofmodeling the corrosion, precipitation, redox reactions, and sorption in predictingPRB material performance. Hydrologic modeling was identified by Gupta andFox (1999) as essential for barrier design (including location, width, and materialselection) and for evaluating scenarios for performance predictions. These sepa-rate modeling activities should be linked into a system with the data flowing fromthe subsurface or other verification activities. The overall system can be linkedas in Figure 5.2.


5.5.1.2 Optimization

The integration of verification data and modeling permits another important step,which is the optimization of the integrated system. An optimization approach forverification is a set of tools, at this time conceived to be computer programs, thattells the PRB user or designer where and how often measurements or samplesneed to be obtained to determine (1) whether the remedial system is operatingproperly, and (2) if risks have increased. The goal is to monitor in space and timeto achieve the following:

• Meet regulatory requirements and/or assess residual risks using a min-imum number of monitoring stations located where the contaminantor surrogate variable is most likely to be.

• Sample at a frequency that captures contaminant movement to confirmthat all processes are operating effectively or trigger any necessarycontingency action.

Gupta and Fox (1999) describe how hydrologic data combined with modelingdefine the optimal monitoring well locations and range of variation in flowdirection and flux needed for verification.

5.5.1.3 Decision and Uncertainty Analysis

The decision analysis process (Figure 5.2) of Lockhart and Roberds (1996) canbe used as an example to identify the predictive tools and data needs for subsurfacecontainment projects. This process also provides a basis for implementing anintegrated and interactive approach using design, predictive models, and theanalysis of the accumulated data at different project stages. The tables are pro-vided to give an understanding of the types of parameters and processes that needto be determined to apply risk decision analysis processes to a given problem.

The evaluation of remediation sites demonstrates the difficulties in obtainingdata and the uncertainties of important parameters. Water balance modeling,

FIGURE 5.2 The decision–analysis process of Lockhart and Roberds (1996) (Civil Engi-neering, April, 62–64).

Optimumdecision

Implementation& feedback Potential

Consequences

Potential

Data

ParameterDefinitions

MathematicalModels

ConceptualModels

Sensitivity studies

ParameterAssessments

Potentialconsequences

DataProject description

Projectalternatives

Decisioncriteria

Screening &trade-offs

Stake-holders


which is a significant component in transport modeling, provides an example ofthe difficulties in evaluation. Such difficulties are due to the level of understandingof the process and the adequacy of the data to support the evaluation. For waterbalance modeling, it must be recognized that evaporation (or evapo-transpiration)cannot be reliably calculated in either humid or arid environments. The bestestimates for the evaporation parameters are for humid environments. Even forthe best of these estimates, a great deal of empirical judgment is required, andthe uncertainties are large. The resulting recharge estimates are in error by asmuch as 100% or more. It is virtually impossible to calculate evaporation for aridenvironments. Errors of two to three orders of magnitude or more are not uncom-mon. Because the understanding of processes is incomplete and because of thehigh degree of uncertainty for important parameters, there is no preferred codeor set of codes for hydrologic modeling at arid sites. Hydrologic models for aridsites are still being tested and calibrated.

5.5.2 SMART STRUCTURES

As barriers have become more complex, there is an ever-increasing need to buildintelligence into them so that they can sense and react to environmental changesand impacts. To achieve this, a nervous system is required that performs in amanner analogous to those living things sensing the environment, conveying theinformation to central processing unit (the brain), and reacting appropriately.

A number of sensor technologies are being modified for use in verificationmonitoring systems for barriers. These sensors can be embedded into the barriersor in close proximity to the barriers, resulting in smart barriers with a built-innervous system. These smart barrier systems offer the prospect of adding effectivemonitoring systems that are responsive to barriers but also are able to localizefailures and take appropriate action (Borns, 1997). Sensors incorporated intobarrier construction have the following advantages:

• They are inexpensive and can be placed in numerous positions wherepreviously only one data point was captured through expensive mon-itoring wells.

• They can be designed to change out easily upon failure.• They reduce the sampling waste created in conventional monitoring

programs.• They can be placed in difficult to reach locations and possibly eliminate

exposure to contaminated mediums for field workers who would nor-mally have to collect samples.

• Through the iterative process, they improve the model.• Because most barriers will outlive most monitoring sensors, Everett

and Fogwell (2003) have stressed the importance of long-term accessto critical subsurface monitoring locations. These locations for capsand liners are discussed later in this chapter.


One of the most effective monitoring technologies currently being employedis fiber optics. Fiber-optic systems involve fiber-optic sensors and communicationlinks that allow the measurements of critical parameters of materials, structures,liquids, and gasses. Surrogate parameters are good indicators of barrier perfor-mance and are easily achievable with fiber-optic sensors. Surrogate measurementssuch as moisture, pH, temperature, flow/velocity, and barometric pressure aregood indicators of barrier failures. The monitored moisture data facilitates site-specific understanding of the transport pathways and processes that influencecontaminant movement.

The technical discussions of how fiber-optic sensors operate are not discussedin this chapter because a number of manufacturing options exist. Simply stated,fiber-optic sensors rely on the interaction of a light beam in the core of the fiber-optic cable with the parameter to be measured or some interaction thereof. Thecladding on the fiber-optic cable can also be treated to produce the desired results.The advantages of this technology include lightweight systems, immunity toelectromagnetic interference, and the ability to be imbedded into hostile environ-ments with extremely high bandwidth capability. Fiber-optic sensor systems cansense environmental changes within or around the barriers, interpret the measure-ments, and initiate an appropriate reaction to these changes. Some of the param-eters that are being measured using this technology include strain, temperatures,acoustics, moisture, pH, flow, and chemicals (Udd, 1995).

Representative distributed fiber-optic sensors allow measurements of specificparameters and can help determine the location of where the measured-inducedchange occurs (Udd, 1995). Distributed chemical sensors can be constructed bycoating an optical fiber with indicator chemicals. The chemical to be senseddiffuses into the cladding, modifying the absorption of the dye and accordinglychanging the attenuation of the fiber laser or light beam, which represents thechemical to be measured. Additional information can be found in the bibliographyof Udd (1995).

For example, fiber-optic sensors have the potential to enable smart barriersthat would be difficult or impossible to implement using conventional electronictechnology. High priority barrier-monitoring parameters discussed at the Long-Term Monitoring Sensor and Analytical Methods Workshop sponsored by theUnited States Department of Energy (USDOE) and its Characterization, Moni-toring, and Sensors Technology (CMST) Program include moisture content, mois-ture flux, and moisture potential (USDOE/CMST, 2001). Engineering goals forlong-term monitoring sensors include making the sensors easy to understand,install, calibrate, operate, and maintain with a capability to service. Monitoringsystems could easily be automated with data transmission via telemetry for remotecontrol and data processing capability. Many sensors that meet short-term needsfor barrier performance could be used as springboards for long-term monitoringsensor development. Most costs would be significantly less than the currentbaseline cost for a deployable system with a replacement cycle every two years(USDOE/CMST, 2001).


5.5.2.1 Long-Term, Post-Closure Radiation Monitoring Systems (LPRMS)

An example of a new monitoring approach is the LPRMS that uses commerciallyavailable components in a reliable, low-cost, multipoint system for real-time,long-term, unattended monitoring of closed waste sites. The system measures awide range of radionuclides and activity levels applicable to a large number ofUSDOE sites.

The LPRMS is designed for gamma detection in subsurface soils. The radi-ation probe consists of a sealed assembly that contains a butt-coupled, thallium-doped sodium iodide NaI (TI) scintillator/photomultiplier tube (PMT) and amulti-channel analyzer (MCA). This assembly, termed the nanoprobe, can bedropped into polyvinyl chloride (PVC) casings that are pushed into the soil usingcone penetrometer technology (CPT). At the surface, solar-powered remote sta-tions (Figure 5.3) at each measurement location incorporate the system powersupply and a cell phone modem to communicate to an off-site host computer,which can be located hundreds or thousands of miles away. A large number ofremote stations can each operate independently (Figure 5.4) and, without humanintervention, send their daily or weekly results to the host computer for analysis,

FIGURE 5.3 Conceptual drawing of installed system (In Situ Remote Sensing and Net-works, 1999a).

6-17

System Architecture

1.5" × 6" NaI detector PMT and MCA

Power & digital Communication

Cable

OFF-SITE HOST COMPUTER

Cell phonecommunication

tower

PVC Pipe (installed using CPT)

Land line to host computer

Environmental enclosure

4" Schedule 40 steelprotective well cover

2" schedule 80 PVC well casing

Concrete pad

Cell phone modemantenna

824–896 MHz

Enclosure to well coveradapter and gasket Split cable grip

Deep cyclebattery

Cell phone modem

Solar panel

48 to 54"

Excess nanoprobecable storage

Modem power switch & RS485 to RS232

converter

REMOTE DETECTOR STATION

Modem

Mast Battery charge

controller


data trending, and alarming. If required, the nanoprobes are easily serviceablethrough retrieval from the PVC casing for repair or replacement.

This system is designed to be capable of monitoring large numbers of per-manently installed probes over long-term periods. The above ground location ofmost of the electronic components and the absence of below ground componentsthat require maintenance minimizes long-term costs.

This technology can remain unattended for long time periods while providingautomated data generation, analysis, formatting, and reporting from many mon-itoring locations. Additional advantages are as follows:

• Real-time detection of nine typical (within USDOE) radionuclides inthe media surrounding the sensor eliminates the long turnaround timeencountered with conventional sampling and laboratory analysis.

• Sensor-based automated data generation, although not currently assensitive as typical laboratory analysis, reduces the potential for error

FIGURE 5.4 Schematic of System Components (In Situ Remote Sensing and Networks,1999a).

Conceptual drawing of installed system

Antenna

Cell phonecommunication

tower Remote detector

stations

Solar panel

Environmental enclosure

NaI detector and MCA

PVC Casing


from manual sampling, sample tracking, laboratory data generation,analysis, and reporting.

• Minimal long-term manpower is required to operate the LPRMS whencompared with the baseline conventional sampling program.

5.5.2.2 Environmental Systems Management, Analysis, and Reporting (E-SMART™) Network

Another example of an intelligent new verification system is the E-SMARTnetwork. The E-SMART network installation includes the application of sensorsthat detect and measure contaminants in groundwater and soil gas as well asphysical parameters such as barometric pressure, pH, and temperature.

Conventional monitoring systems suffer from limited expandability. The goalof the E-SMART network is to eliminate these incompatibilities by defining anopen standard for constructing modular monitoring networks. This vision ofcompatible environmental sensors, sampling devices, control systems, and dataanalysis systems is shown in Figure 5.5.

The E-SMART network integrates diverse monitoring and control technolo-gies by using a modular, “building block” design approach to allow for flexiblesystem configuration. The network treats each smart device — whether a sensor,sampler, or actuator — as a black box that obeys the standard communicationprotocols and electrical interfaces for the network. This approach allows multiplevendors to produce different sensors that meet the same functional specificationand that can be interchanged without impacting operation.

Each E-SMART sensor or actuator contains its own microprocessor brainthat provides it with a means of storing calibration, control, status, and quality

FIGURE 5.5 E-SMART Vision (In Situ Remote Sensing and Networks, 1999b).

Workstation

Plume Smart sensors

Sampler E-Smart network

management system


assurance data. This brain communicates using the network protocol, managesdata, and controls operation of the smart device. Because the sensor manufacturerembeds the sensor-specific information within the smart device, the E-SMARTuser is not required to develop calibration or control programs for specific sensors.

5.5.2.3 Direct Push Technologies

Direct push technologies have proven to be effective site characterization andverification tools in recent demonstrations at the USDOE Hanford site (Wash-ington) and U.S. Air Force sites at Harrison Air Force Base (AFB) (Indiana)(closed since 1995), Misawa Air Base (Japan), and Kirtland AFB (New Mexico).CPT has met refusal in some geologies before being advanced to the desireddepths at dense nonaqueous phase liquid (DNAPL) sites. A sonic CPT systemcombines the speed and high penetration capabilities of sonic drilling with theeconomic, continuous data logging of CPT, thus allowing access through difficultstrata. An important application of CPT is to install monitoring points. Percussion-driven probes have been enhanced by integration with a laser-induced fluores-cence spectrometer and other sensors, providing a less expensive and more easilydeployed system. Successful integration of real-time DNAPL chemical sensingand geophysical instrumentation with horizontal directional drilling technologywill allow characterization of DNAPL-contaminated strata without introducing avertical conduit to underlying formations and other obstacles such as buildingsand barrier floors. Direct push technology is an excellent platform for makingcontinuous measurements of contamination: it is useful in pushing sensing sys-tems into the subsurface; for installing monitoring wells and points; and forobtaining gas, water, and soil samples for environmental testing.

CPT-associated sensor technologies such as soil strength stain gauges, resis-tivity, soil moisture, pore pressure, gas chromatography/mass spectrometry(GC/MS), multi-gas and organic vapor monitoring, and laser-induced fluores-cence (LIF) (Kram et al., 2001a,b), provide enhanced site characterization, and,while still on-site, can quickly and cost efficiently install monitoring wells.Kram’s group (Kram and Keller, 2004a,b; Kram et al., 2004) has optimizedseveral laser excitation sources for specific carbon ranges using LIF, allowingreal-time profiling of petroleum hydrocarbon and some DNAPLs. By includinga CPT well installation component during verification, plume delineation effortscan be accomplished within one field mobilization. When compared with con-ventional approaches, this seamless method of optimizing well placement reducestime and avoids additional data review, permitting, and mobilization/demobiliza-tion costs. Recent work by the U.S. Navy (Kram and Keller, 2004a,b; Kram et al.,2004) compares conventional well performance with pre-packed direct-push wellinstallations. If successful, this approach referred to as a Site Characterizationand Analysis Penetrometer System (SCAPS) and shown in Figure 5.6 will resultin significant verification monitoring cost savings.


FIGURE 5.6 SCAPS.

SCAPS-Site characterization and penetration system

Shaw The Shaw Group Inc.

Pipe handling

space 20-ton push truck

Data processing

space

VEHICLE

DATA ACQUISITION AND ANALYSIS

• Push probe configurations -Sensors -Sampling• Grouting capability• Equipment decontamination• Hazardous environment protection

• Acquisition • Sensors • Analysis • Visualization

Trailer


5.5.2.4 Nanotechnology Sensors

Nanotechnology enables the creation of functional materials, devices, and systemsby controlling matter at the atomic and molecular scales to exploit novel prop-erties and phenomena. Most chemical and biological sensors, as well as somephysical sensors, depend on interactions occurring at these levels. Potential appli-cations under development include chemical sensors and probe tips. Nanotech-nology such as carbon nanotechnology will impact almost every aspect of ourlives including fuel cells, portable X-ray machines, extremely lightweight strongfabrics, and artificial muscles. The discovery of carbon nanotubes (CNT) —extremely narrow, hollow cylinders made of carbon atoms — by Sir Harold Kroto(Florida State University Nobel laureate) and his colleagues initiated an entirelynew field of chemistry research aimed at understanding the properties of theseunusual molecules. The characteristics of and the ability to grow CNTs at specificlocations and manipulate them afterward make it likely that the tubes will haveconsiderable impact on electronics and sensors (Smith and Nagel, 2003).

High levels of integration made possible by nanotechnology give the sensorthe ability to be the device and possibly also the system. Nanotechnology takesthe complexity out of the system and puts it into the material. Fluorescence andother means of single molecule detection are being developed. Nanotechnologywill enable the design of sensors that are much smaller, less power hungry, andmore sensitive than current micro- or macro-sensors. Sensing applications willthus enjoy benefits far beyond those offered by micro-electromechanical systems(MEMS) and other types of micro-sensors. The ability to install hundreds ofsensors in a small space allows malfunctioning devices to be ignored in favor ofthe remaining good ones, thus prolonging a system’s useful lifetime.

Examples of current work include development of a miniaturized gas ioniza-tion detector that could be used for gas chromatography. Nanotube hydrogensensors have been incorporated in a wireless sensor network to detect hydrogenconcentrations in the atmosphere. In addition, a chemical sensor based on CNThas been developed for gaseous molecules such as nitrogen dioxide (NO2) andammonia (NH3).

Nanotechnology is certain to improve existing sensor applications and be astrong force in developing new ones. Nanoscale materials and devices are begin-ning to be integrated into real-world systems, and the future looks bright inparticular for integrating the wireless smart sensors into hazardous waste barriersand containment systems.

5.5.3 ADVANCED ENVIRONMENTAL MONITORING SYSTEM (AEMS)

Toshiba Corporation is providing technical coordination to an international con-sortium of academic institutions and companies working to develop AEMS, acontinuous, automated monitoring of groundwater pollutants. The consortiumseeks to bring the know-how of its member organizations to the development andcommercialization of a system providing enhanced monitoring and identification


of pollutants in the groundwater and subsoil below manufacturing facilities,including pharmaceutical, chemical, and food-processing facilities. AEMS isexpected to detect and identify leaks of contaminants at the source and in realtime to support the very earliest deployment of measures to clean up pollutedgroundwater and soil. In practical applications, AEMS will comprise an array ofon-site biosensor systems installed in wells drilled around a monitored barrier.These wells feed groundwater samples to the systems and provide the means forcontinuous monitoring of groundwater contamination around the designated area.The biosensor is bio-mimetic and consists of two layers of artificial lipid mem-branes that are used to evaluate the toxicity of chemicals in the groundwater. Themembranes generate specific responses to different types of organic compoundsin pollutants, allowing identification of hazardous substances. The sensitivity ofthe biosensor has been improved to the point where it is capable of detectinghazardous substances, such as trichloroethylene (TCE), in concentrations as lowas one part per billion (10–9 or 0.001 milligrams per liter).

5.5.4 A NEW DOE BARRIER DESIGN CODE

Under the direction of Dr. Thomas W. Fogwell, Scientific Director at FluorHanford, Richland, Washington, a modification of the transport modeling code,STOMP (Subsurface Transport Over Multiple Phases), is in development insupport of surface barrier designs. The need for a new code is driven by designrequirements for approximately 200 new surface barriers needed to close manyof the waste sites on the Hanford Central Plateau. Several different surface barrierdesigns have been proposed based on a graded approach that fits degree ofprotection with site risk. There is a clear need to be able to evaluate and comparedesign alternatives, while considering waste site-specific needs in view of tech-nical, regulatory and economic issues. Because all of the designs cannot be builtand evaluated over the appropriate spatial and temporal scales, computationalmodels offer an opportunity to perform side-by-side comparisons over the designlife for a range of conditions. The overall objectives of this work are as follows:

• Extend the plant-soil atmosphere dynamics module to 3-D space.• Add capabilities to analyze the effects of dynamic structural and hydrau-

lic properties that may result from deformation. (This will require theaddition of algorithms for static and dynamic localized grid refinement.)

• Calibrate and validate the model using data from Pacific NorthwestNational Laboratory’s (PNNL) Field Lysimeter Test Facility (FLTF),the prototype Hanford Barrier, and other selected experimental capil-lary barriers in the western U.S.

• Perform a sensitivity analysis to determine the influence of key param-eters and model discretization on model predictions, and identify thekey model parameters.

• Provide a barrier design tool as well as technical guidance and docu-mentation to support the preconstruction performance evaluation ofcandidate barriers.


New code to modify STOMP was completed at the end of fiscal year 2003.The code was calibrated in January and February 2004 and scheduled to be readyfor application by October 2005.

5.6 DRIVERS FOR IMPLEMENTATION OF NEW APPROACHES

A major issue in verification monitoring technology development is identifyingwhat motivates stakeholders, end users, and regulators to move from state of thepractice to state of the art. Such drivers are often a reduction in risk and a reductionin cost. In the realm of subsurface verification, the drivers for change are costand development of methods that enable the desired end states for remediationsites. Only recently has the USDOE begun to design verification systems thatmeet or exceed the regulatory requirements for barriers. Most communities stilluse old state-of-practice barrier verification systems. This chapter discusses sub-surface verification and monitoring for several types of barriers: landfill covers,PRBs, and walls and floors. The discussion here begins with landfill covers, whichto date are the most common containment barrier in use. But first, the drivers forimplementation of new approaches must be explored.

5.6.1 COSTS

For the 30 years or more life span of some sites that use covers or other barriers,long-term monitoring costs can be larger than the initial barrier implementationcosts. The system approach described in Section 5.4.1 allows several opportunitiesto affect life-cycle costs of remediation.

This first of these opportunities is optimization. Optimization, with its imbed-ded use of predictive tools, permits (1) the selection of the parameters to measure,(2) the selection of the sensitivities of sensors, (3) the location and timing ofmonitoring, and (4) the selection of appropriate action criteria. With optimization,the appropriate actions for a given site can be made, and, therefore, a cookie-cutter approach need not be followed.

The other major cost opportunity in applying state-of-the-art approaches isin situ physical and chemical analysis. In the mid-1990s, the USDOE was spend-ing more than $200 million on chemical analysis to support its environmentalmanagement and remediation activities. As an example, the USDOE SavannahRiver site (Aiken, South Carolina) requires 40,000 groundwater samples a yearat $100 to $1,000 per sample for off-site analysis (i.e., a total of $4 million to$40 million per year) (Ho and Lohrstorfer, 2001).

5.6.2 ENABLING DESIRED END STATES

Environmental remediation has begun to move toward different end states suchas brownfield rather than greenfield use (reapplication of the remediated landsfor industrial use), wildlife preserves, or other forms of public/private lands.INEEL led an inter-agency effort to develop the Long-Term Stewardship Science


and Technology Roadmap (2001) that suggests that remediated sites will betransferred to locations that are minimally staffed with remediation personnel ornonmanned. These sites will be required to be remotely monitor waste movementby relying on in situ sensors.

5.7 COVERS

This section discusses some potential deployments of the barrier verificationmethods mentioned in Section 5.3 that are applicable to covers. This list ofdeployment methods is not meant to be exhaustive, but represents some of thepossible configurations to move from state of the practice to state of the art. Thedata quality objectives (DQO) of the monitoring systems would need to be clearlyidentified, and the methods applied would provide a means of monitoring a landfillafter closure in lieu of certain groundwater monitoring. In addition to this dis-cussion, two USDOE case histories are portrayed: one in New Mexico and anotherin Ohio.

5.7.1 MOVING FROM STATE OF THE PRACTICE TO STATE OF THE ART

5.7.1.1 Methods

A review of other hazardous waste facilities by Everett and Fogwell (2003) showsthat where barrier monitoring is applied below the liner system, the primarymethod uses basin lysimeters of variable sizes. Basin lysimeters generally haveproven regulatory acceptance, reduced cost, ease of installation, and the abilityto collect quantifiable results. A typical design would be a basin lysimeter madeup of 100-mil high-density polyethylene (HDPE) installed under the bottomsump. The lysimeter can extend 1.52 m beyond the perimeter of the bottom sumpand can be designed with an access pipe that allows the removal of any liquidcollected. Due to the lateral flow patterns normally generated near capillarybarriers and those that exist at the interface between contrasting soil textures,such a basin lysimeter could be expected to detect most leaks in the bottom linerof a landfill.

Time-proven technologies like neutron moderation can be considered belowthe barrier liner systems of cells. As new technologies are developed and oldtechnologies improved, consideration should be given to deploying or improvingthese new options. Particular reference could be made to emerging volume-integrating technologies like high-resolution resistivity and cross-borehole ERT.This strategy of being prepared to employ future technologies as they developcould be facilitated by installing access tubing (probably perforated) beneath thebottom liners of new construction, providing a relatively inexpensive method ofaccommodating new technologies as they become available. Of the new technol-ogies, those giving volumetric information seem to be the most promising. Themain advantage of such a tubing network would be that ERT methods could beused to provide a spatial distribution of any detected leakage.


Even with today’s technologies, horizontally emplaced perforated accesstubes could be used for measuring parameters such as soil moisture movement,gamma detection, soil pore water sampling, and soil gas. The perforated toolaccess tubes should span the entire length of a cell buried in a 1.22- to 1.83-mdeep trenches along the bottom of each cell and located in areas of potential linerfailure. The multi-purpose, perforated access tubes could use the following typesof barrier-monitoring technologies in measuring the above-mentioned parameters:a neutron probe, a sodium iodide gamma detector, and absorbent pads for eval-uating soil pore water quality. The value of this monitoring approach is that itrepresents a cost-effective graded method that would allow spatial monitoringbelow the landfill in order to locate liner failure positions. Soil moisture alonecould be used as a cost-effective sentinel parameter, which could be supportedwith other parameters if required. Perforated casing below the landfill mightpermit the collection of soil gas samples and could be used as part of a leakageor performance check of both the barrier liner and the caps.

5.7.1.2 Verification Measurement Systems

Vertically emplaced perforated access tubes (open-holed at bottom) can beinstalled (for measuring soil moisture movement, gamma detection, and for col-lecting soil pore water samples). The access tubes can extend from the surface,through the barrier closure cover and the waste, but not through the bottom liner.These access tubes can be used for detecting vertical moisture changes throughoutthe waste, function as an access port for various other types of geophysical tools(e.g., neutron and gamma logging tools), provide access for absorbent pads, andpermit access for direct soil sampling through the open hole at the bottom. It isimperative that a good seal be completed around the perimeter of the access tubesto prevent preferential flow between the access tubes and soil material. Thefollowing are other sensors that can be used with such a vertical tube system:

• TDR probe monitoring stations for each vertical access casing can beinstalled for measuring volumetric soil moisture.

• Heat dissipation probe monitoring stations (co-located with the TDRprobes) can be installed on each of the vertical access casings tomeasure matrix potential, which is the driving force for unsaturatedmoisture movement.

• Suction lysimeters in a vertical profile can be installed to collect soilpore water samples for chemical and radiological analysis.

5.7.1.3 Barrier Cap Monitoring

At closure, instruments should be installed in the final barrier cover to measureits effectiveness of the cover in restricting moisture movement. There are manypotential designs. Some involve instrumentation of just the cap and some schemesinvolve vertical neutron access tubes installed in the cover and through the waste


to the bottom of the trench. Therefore, meaningful, post-closure, verificationbarrier-monitoring data should not be relied upon until a baseline has beenestablished and moisture equilibration has stabilized. Once stabilization has beenachieved in the post-closure monitoring system, it is anticipated that much of thegroundwater monitoring specific to a facility could be eliminated or reduced inscope.

Settlement is an important long-term risk associated with the barrier perfor-mance of both the liner and the cap. A system of determining settlement by usingeither survey stakes, topographic remote sensing, fiber-optic cables, GPR forsettlement plates, or visual inspection should be considered. A time-consistenttopographic survey of the cap should be generated to identify such items assettlement depressions, erosion features, and vegetative features that may developover time. This survey can also serve to give early warning to possible (but notcertain) future water leaks. The indication of subsidence can trigger monitoringin more localized areas.

5.7.2 CASE HISTORY: MIXED WASTE LANDFILL

The mixed waste landfill in Albuquerque, New Mexico, was established in 1959as a disposal area for low level radioactive and mixed waste generated by researchfacilities of Sandia National Laboratory. The landfill accepted low level radioac-tive and mixed waste from March 1959 through December 1988. Approximately30,480 cubic meters of low level radioactive and mixed waste containing approx-imately 6300 curies of activity were disposed of in the landfill. For the landfillcover design, Sandia National Laboratory and the state elected to use RCRASubtitle C facilities regulations as guidance. The goal of the USEPA-recom-mended design of final covers for RCRA Subtitle C facilities was to minimizethe formation of leachate by minimizing the contact of water with waste, minimizefurther maintenance, and protect human health and the environment consideringfuture use of the site.

The USEPA accepts alternative cover designs that consider site-specific con-ditions, such as climate and the nature of the waste, that meet the intent of theregulations. An alternative cover design consisting of a thick layer of native soilwas developed as the closure path for the mixed waste landfill. The design relieson soil thickness and evapo-transpiration to provide long-term performance andstability and is inexpensive to build and maintain because of the availability ofsuitable soils in the area. The cover meets the intent of RCRA Subtitle C regu-lations because of the following:

• Water migration is minimized through the cover.• A monolithic soil layer minimizes maintenance.• Erosion control measures minimize cover erosion.• A “soft” design accommodates subsidence.• Permeability of the cover is less than or equal to that of natural subsoils

present.


The proposed mixed waste landfill alternative cover incorporates a redundantinfiltration monitoring system that includes both baseline neutron probe accessholes and advanced distributed fiber optics. The cover infiltration monitoringsystem is coupled with a shallow vadose zone monitoring system deployeddirectly beneath the landfill. The shallow vadose zone monitoring system consistsof three neutron probe access holes drilled at 45° to a depth of 43.28 m belowground surface. The close-coupled cover and shallow vadose zone monitoringsystem, in essence, functions as an early warning system, providing early detec-tion of a potential threat to groundwater, and allows corrective action to beinitiated before significant contaminant migration occurs. This redundant moni-toring approach was designed to protect groundwater resources and was imple-mented because of its simplicity, low cost, and long-term viability.

The close-coupled monitoring system is monitored closely. The frequencyand duration of post-closure monitoring was established in consultation with thestate and formally documented in the mixed waste landfill long-term care plan.The cover and vadose zone monitoring system provides infiltration and perfor-mance information and early detection of potential contaminant migration fromthe landfill, as well as establishing background and trend analysis information.The close-coupled cover and shallow vadose zone monitoring system is a simpleyet robust system designed to meet the intent of long-term RCRA and USDOEperformance requirements: reducing labor-intensive, long-term groundwatermonitoring and allowing substantial cost savings.

5.7.2.1 Cover Infiltration Monitoring

The landfill alternative cover will contain six vertical neutron probe access holes,two in each of the original disposal areas. Each access hole will extend throughthe cover and an additional 2 ft into original landfill soils. Aluminum casings willbe installed after cover construction is complete by hand auguring 6.25-cm-diameter boreholes through the cover and driving the aluminum casing to properdepth. Each casing will be fitted with a perforated, tapered drive-tip. A 0.3 m by0.3 m concrete pad will be placed at the collar of each casing to prevent prefer-ential flow down the annulus. The cover will also contain a distributed fiber opticsinfiltration monitoring system that will be deployed in two lifts. The lowermostdeployment will be on the prepared sub-grade surface. The uppermost deploymentwill be 0.45 m above the prepared sub-grade surface between the third and fourthnative soil lifts. The uppermost fiber-optic grid will be transposed 90° from thelower grid to maximize spatial resolution and increase monitoring efficiency.

5.7.2.2 Neutron Moisture Monitoring

The neutron moisture probe is increasingly being applied to address character-ization and infiltration issues at environmental sites undergoing long-term care.Neutron moisture monitoring has become the industry standard for soil moisturemeasurement, and its operation and data interpretation is well established. The


principal advantages of this technique are repeatability, precision, and long-termviability. Nothing is permanently installed downhole, which allows for periodiccalibration of the neutron probe. Practical considerations and knowledge ofvadose zone hydrologic processes guide the number and location of neutron probeaccess holes.

5.7.2.3 Fiber Optics Distributed Temperature Moisture Monitoring

The distributed fiber-optic infiltration monitoring system proposed for the coveris based on the observation that a change in soil-water content causes a corre-sponding change in soil thermal conductivity. When constant power is dissipatedfrom a line heat source (in this implementation, an electrically conducting wirebundled with the optic fiber), the temperature increase near the heat sourcedepends on the thermal conductivity of the surrounding medium. As soil-watercontent increases so does its thermal conductivity. The temperature increase asmeasured by the fiber optic will be reduced because of the conduction of thethermal energy away from the heat source. Measurement accuracy is ±1°C witha resolution of approximately 1 m over the entire length of the cable. The opticalfiber and line heat sources are bundled in a hermetically sealed stainless-steelcable that is 0.6 cm in diameter.

An important advantage of fiber-optic sensors is their ability to providepassive sensing of a wide variety of physical parameters. This not only meansthat the sensor operates without the need for electrical power, but the overallsystem (including the input-output fibers that serve as the telemetry links) is alsoelectrically passive, and, thus, the entire system exhibits low intrinsic suscepti-bility to the effects of electro-magnetic interference. Experience to date in envi-ronmental monitoring indicates that electrically based sensors are extremelysusceptible to electrical storms, particularly in the semi-arid and arid west andsouthwest. Therefore, issues of electrical passivity are of paramount importancewhen a sensor is required for long-term monitoring and performance in anelectrically noisy environment.

5.7.2.4 Shallow Vadose Zone Moisture Monitoring

Three angled, 11.4-cm outside diameter, 0.5-cm inside diameter access holes willbe installed in the shallow vadose zone directly beneath the mixed waste landfill:two to the west and one to the east of the cover. The vadose zone access holeswill be spaced at equal increments: the east access hole bisecting the two westaccess holes. The access holes will be installed under separate contract usingresonant sonic drilling. Resonant sonic is the preferred drilling technique becauseit literally fluidizes and displaces the surrounding soil as the drill string advances,creating a very tight fit between the drill string and the formation. No cuttingsare generated, and no fluids are used to advance the drill string. Backgroundvalues for the soil volumetric moisture content will be measured during installation


of the neutron probe access holes. Each access hole will be collared approximately3 m outside of the toe of the cover side slopes. Each access hole will be drilled60 m at 45˚ to a true vertical depth of 42 m. As each access hole is completedat 60 m, the 11.4-cm sonic drill string will be left in place down-hole andunscrewed at the surface leaving about 0.6 m of stickup. Each sonic drill stringwill remain open to the vadose zone. A protective cover constructed of steel pipewill extend 0.6 m below grade and 0.9 m above grade. Each protective cover willbe fitted with locking caps and secured with locks.

5.7.3 CASE HISTORY: FERNALD ON-SITE DISPOSAL FACILITY

The Fernald Environmental Management Project (FEMP), located 29 miles north-west of Cincinnati, Ohio, is constructing an aboveground on-site disposal facility(OSDF) that is used to isolate low level radioactive waste generated by plantremediation activities. The disposal facility design allows for the construction ofnine cells filled with a total of 1.9 million m3 of low-level radioactive soil andconstruction debris from cleanup activities at the site. The disposal cells aredesigned to remain stable for 1000 years to the extent reasonable and, in anycase, no less than 200 years.

Each of the OSDF cells has a bottom liner system, including a leachatecollection system that is approximately 1.52 m thick. It is composed of multiplelayers of clay and gravel (Figure 5.7) and a geosynthetic liner that is designedto protect the underlying Great Miami Aquifer. The cap of each cell is a multi-component cover approximately 2.68 m thick with components to limit water

FIGURE 5.7 Multiple-layer system.

Vegetation (typ) Erosion mat

Vegetative soil layer

Biointrusion barrier

Cover drainage layer

Granular filter

Top soil

Compacted clay cap

Protective layer Leachate collection system (LCS) drainage layer

Leak detection system (LDS) drainage layer

Compacted clay liner

Subgrade

0.91 m

0.30 m 0.30 m

0.30 m

1.81 m

0.61 m

0.30 m

0.91 m

0.15 m

0.15 m

0.53 m

2.65 m

Primary geomembrane liner (80-ml)

Secondary geomembrane liner (80-ml)Secondary Geosynthetic clay liner

Primary Geosynthetic clay liner

Geomembrane cap (60-ml) Geosynthetic clay cap

Geotextile cushion

Geotextile cushion

Geotextile cushion

Geotextile filter


infiltration (geomembrane) and biointrusion (cobblestones) (Kumthekar et al.,2002). As of September 2003, Cell 1 was filled and capped with the monitoringsystem in place; Cell 2 was filled with capping planned for 2003; and Cells 3,4, and 5 were partially filled.

The objective was to create a monitoring system that generates data on thephysical conditions of the cell cover. This objective was selected because engi-neering experience with final covers incorporating composite barriers indicatesthat physical stability is the most important factor affecting long-term perfor-mance. The following five critical monitoring parameters were established basedon the functional requirements and design criteria of the OSDF:

1. Pore water pressure in the drainage layer — Buildup of water pressurein the drainage layer must be kept below a critical value to maintainphysical stability.

2. Total and differential settlement — Settlement must be kept at a min-imum so as not to impact barrier performance, hydraulic gradients, andthe free flow of moisture throughout the drainage layer. Distortionsmust be limited to less than 10%.

3. Soil-water content and soil-water potential — These elements are crit-ical to the health of the root zone within the vegetative layer, whichprotects all other layers and must remain in place for other layers toretain effectiveness.

4. Soil temperature above barrier layer — To function properly, the barriersystem must not freeze.

5. Overall condition of cover — This parameter includes institutionalcontrols such as maintenance of signage within the buffer area, as wellas ecological controls such as the monitoring of biotic intrusionthroughout the cover system. Erosion must be prevented through themaintenance of a healthy vegetative layer, which in turn ensures thatthe biointrusion layer remains functional.

A monitoring system was designed to monitor these critical parameters aswell as the following four criteria to maintain the OSDF for at least 200 years(Table 5.3): (1) long-term performance, (2) availability for deployment in nearterm (within 12 months), (3) remote access and control, and (4) capability tointegrate into a data management system. It was also essential to develop a systemthat was easily accessible for equipment maintenance and technology updates asnew cells are built and filled.

The monitoring system for Cell 1 was installed to address these criteria.Sensors were installed in a series of nests at the most appropriate area to monitorbarrier stability. There are 10 soil-water status nests that measure soil-water contentand potential, seven pressure transducer risers that monitor pore water pressurein the drainage layer, seven settlement plates and rods, and eight sets of GPRthat monitor total and differential settlement (Figure 5.8). There are three waterstatus nests on each of the west, east, and northern slopes of Cell 1 and one at


the top of the cell to observe conditions at the highest point and the shallowestslope. Each soil-water status nest has four content reflectometers and four soil-water potential probes equally spaced in the vegetative layer (Figure 5.8)(Kumthekar et al., 2002). Seven pressure transducer risers were installed along

TABLE 5.3Critical Parameters and Selected Monitoring Technologies in the OSDF Final Cover System

Component Parameter Monitored Monitoring Technology

Drainage layer Pore water pressure in drainage layer

Submersible pressure transducers

Surface and internal cover grades, barrier layer (distortion)

Settlement (total and differential)

Topographic survey using settlement plates and rods, GPR targets

Status of root zone Soil water content, soil water potential

Dielectric water content sensors, thermal dissipation potential sensors

Barrier layer (freezing) Soil temperature above barrier layer

Thermocouples

Cover system and buffer area

Overall condition of cover

Routine topographic surveyWeb camVisual and/or remote sensing

Source: Kumthekar, U. et al. (2002). Spectrum 2002: International Conference on Nuclear andHazardous Waste Management.

FIGURE 5.8 Layout of instrument nest on the final cover for Cell 1.

Soil water status nest Pressure Transducer Cabling Fiber optic GPR plate

Cover perimeter

Settlement plate

N C

Cell 1

615

620

630

640

650

605 610 615 620 625 630 635 640 645 650 655 660 665 670 670 665 660 655 650 645 640 635 630 625 620 610

645

Southernextent of finalcover systemconstruction


areas of Cell 1 where the slopes are the longest and pore water pressures are thehighest: one on top of the cell and two each down the northwest slope, northslope, and northeast slope. Along each slope, one of two transducers was placednear a drainage layer where high pore pressure could be expected if the layerbecame obstructed. Transducers were placed at the top and middle of the slopeto monitor the distribution of pressure along the slopes. Each transducer allowsunimpeded flow of water through the riser and is constructed with schedule PVCpipe to prevent damage and aid in the longevity of the riser. Geotextile is usedalong the riser pipe to prevent plugging of the pipe, movement of barrier materialsbetween layers, and material from entering the well. The geotextile also servesas a cushion to prevent any damage to the geomembrane below it. The settlementplates and rods were installed alongside of the pressure transducer risers. Plateswere installed on the surface of the drainage layer with the rods extending to theground surface. The GPR plates were installed on the west and east slopes andtwo each along the northwest, north, and northeast slopes.

A subterranean vault was installed at the top of the cell to house both thedata logger and multi-plexers. Within the sealed vault, humidity sensors monitorthe atmosphere for changes that could damage the equipment. To allow for easyaccess and equipment repair with minimal manpower, the vault can be raisedwithout difficulty above ground. The data logger is connected to a radio trans-mitter via a fiber-optic cable, allowing data to be uploaded to a managementsystem.

It is expected that modification to this design will be made to subsequentcells based on lessons learned from the installation and subsequent monitoringof this system.

5.7.4 VERIFICATION NEEDS

Verification needs for covers were established at the workshop through the PRBwork group and the subsurface verification subgroup and were as follows: (1) waterbalance (e.g., storage, percolation, soil moisture, flux, flow rates), (2) gases andvapor transport (e.g., methane, oxygen, radon), (3) physical state (e.g., stiffness,cracks), and (4) long-term monitoring trends (i.e., space and time). Wilson et al.(1995) identified additional needs for covers (Table 5.4). The dominant verificationneed that appears is the verification of the water balance within the cover system.

Both the vadose zone science and technology roadmap and the long-termstewardship science and technology roadmap strongly suggest that the compo-nents of subsurface verification be incorporated within the remediation designfrom the onset (INEEL, 2001; USDOE, 2002). This is a full system design. Fullsystem designs interactively incorporate prediction with optimization, sensorplacement, and approaches to trend analysis.

The case history described in Section 5.4.1 provides an example of movingfrom the state of the practice to the state of the art with end user and regulatoryacceptance. In this example, the monitoring approach was incorporated in theconstruction design of the cover. The monitoring approach is a combination of


tradition neutron probes and new applications of distributed fiber-optic sensors.Both approaches are aimed at measuring the water balance within the cover.

5.7.4.1 Optimization and Trend Analysis

Site closures involving residual contamination and engineered remediation sys-tems such as covers require monitoring relevant pathways to protect human health

TABLE 5.4Data Needs for In Situ Containment and Stabilization of DOE Sites

Data Needs Required Parametersa

I. Process model/understandingII. Boundary conditions

III. DesignA. Waste characteristicsB. Performance standards

IV. Regulatory/interagency agreement standardsA. Performance standardsB. Time period

V. Uncertainties/sensitivity of process model parametersA. Understanding of how data can be

applied to different scalesB. Spatial and temporal heterogeneity

1. Geology2. Flow/transport system3. Waste4. Engineered design

VI. Environmental changesA. ClimaticB. PedogeneticC. Human generated including human

intrusionD. Analog studies

I. Boundary conditionsA. Performance standards (e.g., regulatory,

multiparty agreement or design)1. Soil2. Water3. Period of performance (e.g., 30, 100,

1000, 10000 years)II. Material properties

A. Bulk densityB. Particle density

III. Hydrogeologic parametersA. Effective porosityB. Mass water contentC. Volumetric water contentD. Infiltration capacityE. Saturated hydraulic conductivityF. Soil-water characteristic curvesG. Conductivity/pressure head relationship

IV. Parameters related to climate A. RainfallB. Evapo-transpirationC. Temperature

V. Chemical parameters of waste, engineered, and natural systems

A. SolubilitiesB. Cation exchange capacityC. Partition coefficientsD. Diffusion coefficientsE. Biodegradation ratesF. Chemical degradation ratesG. Radioactive decay ratesH. Organic matter content

a Modified from Wilson, L.G. et al. (1995). Handbook of Vadose Zone Characterization andMonitoring, Lewis, Boca Raton.


and the environment and to ensure that remediation systems are operating prop-erly. Uncertainties in conceptual models, key parameters controlling importantfluxes, and forcing functions require a statistically-based monitoring networkcharacterized by the zone of influence (support) of the sensors/sampling device,the spacing between sensors, and the extent of the domain/site that needs to bemonitored. Initial applications will use tools for each pathway, air, surface, andsubsurface, because models and approaches that consider coupled systems arecurrently limited. However, as research proceeds, a coordinated monitoringapproach can be built.

Tools that optimize monitoring systems will lead to a 50% cost reduction anddecrease uncertainty by a factor of five over systems based on judgment or regulargrid systems. An optimized monitoring system will allow risks and the uncertaintyassociated with risks to be assessed more accurately at all remediation sites.

Over the life of a remediation project, monitoring costs can be substantialand can even exceed the costs of the remediation system. The capability to reducemonitoring while retaining the critical information for either the site or theengineered barrier will lead to enhanced efficiency.

5.7.4.2 Sensors and Other Hardware

Water balance is the critical verification need for covers. The technical baselinefor subsurface sensors utilized for this need was described by Scanlon et al.(1997). Further information regarding the sensor types that can be used is providedin Tables 5.5–5.8.

TABLE 5.5Toolbox: Water Balance

Approach Description Application Remarks

Unconfined groundwater balance

A water budget requires quantification of all aspects of hydrologic systems that add or remove water from the component of interest. The water balance equation can be solved for any individual component

Advantage: Useful at early stage of site characterization

Disadvantage: Field measurements are time consuming

Prediction of response of near surface groundwater levels to other parameters of the hydrologic cycle

Moisture profile for specific yield

The initial level of shallow well is measured and the moisture content is determined in intervals of 0.1 m in the capillary fringe above the water table

Advantage: Useful for sites that want to avoid pump test that bring contaminants to surface

Disadvantage: Shallow aquifers

Measure specific yield


5.8 PRBS

Since the 1995 International Containment Technology Workshop sponsored byDuPont, the USEPA, and the USDOE, the interest in PRB technology has greatlyincreased, along with the number of sites where this technology is the selectedremediation method (USEPA, 2002). The use of PRBs to remediate halogenatedhydrocarbons (Gillham and O’Hanneisin, 1994) and metals (Morrison et al., 2002)

TABLE 5.6Toolbox: Baseline In Situ Chemical Sensors

Sensor Description Application Remarks

Dissolved oxygen, Eh and pH probes

Various probes are available that measure dissolved oxygen, Eh, and pH in borehole fluids

Advantage: Undisturbed real-time measurements

Detect a contaminant plume

Ion-selective electrodes

Electrodes are designed to detect the presence of specific ions using a reference electrode

Advantage: Real time monitoring of contaminants

Disadvantage: Calibration

Detect the presence of specific ions

Fiber-optic chemical sensors(FOCs)

A variety of chemical sensors using fiber-optic technology are in development stages; FOCS are made of a reagent phase which is physically confined or chemically immobilized at the end of the optical fiber; the reagent phase contains a chemical or immunochemical indicator that changes its optical properties, usually absorbance or fluorescence, when it interacts with the analyte; the fiber-optic cable is attached to a spectrophotometer or fluorimeter which contains a light source and a detector; an excitation signal from the light source is transmitted down the cable to the FOCS and the sensor fluoresces and provides a constant intensity light source that is transmitted back up the cable and detected as a return signal

Advantage: Selective real-time measurement, eliminate chain of custody

Disadvantage: Equipment not readily available

Detect presence of specific organic compounds in water and vapor phase

Solid fibers: BTEX, DCE, TCE, carbon tetrachloride, chloroform, JP-5, gasoline

Porous fibers: Humidity, pH, ammonia, ethylene, CO, hydrazine, and BTX


has been demonstrated. Approximately 60% of the PRB applications to date aretreating halogenated hydrocarbons and 20% are treating metals (USEPA, 2002).

The background and description of PRBs are discussed in more depth in thebook that resulted from the 1995 International Containment Technology Work-shop (Rumer and Mitchell, 1995). The USEPA defines a PRB as “an emplacementof reactive materials in the subsurface designed to intercept a contaminant plume,provide a preferential flow path through the reactive media, and transform thecontaminant(s) into environmentally acceptable forms (Figure 5.9) to attain reme-diation concentration goals at points of compliance (USEPA, 1997).” The majorimplemented designs of PRBs are funnel and gate, continuous trench, and reactorvessels. New designs include deeper injection of reactive propants into fracturesthat are either natural or induced or into porous formations (Marcus and Bond,1999).

TABLE 5.7Toolbox: In Situ Chemical Sensor Examples (DOE/CMST)

Technology Description Application

Microcantilever sensors

Microcantilevers are micro electro-mechanical devices (MEMS); hence, they are small, simple, rugged, and inexpensive; in this application the micro-machined cantilevers have an absorbent coating that changes the bending, frequency, Q-factor, and amplitude response of the cantilever as the targeted species is absorbed or desorbed.

PhysicalChemicalRadiologicalIn air or in solutionOak Ridge National Laboratory

Electrochemical sensors

Such devices consist of a transduction element covered with a biological or chemical recognition layer; the analytical information is derived from the electrical signal that results from the interaction of the target analyte and the recognition layer.

Real-time reliable chemical composition on the environment surrounding the sensors

OrganicsNitratesMetalsPesticidesRadioactive materialsNew Mexico State University (J. Wang)

Chemiresistors Similar to above Sandia National Laboratories (Ho and Lohrstorfer)

Chemical fiber-optic sensor

Resonance-enhanced multi-photon ionization Volatile organic hydrocarbons

Lawrence Livermore National Laboratory (F.P. Milanvich)


Various reactive materials such as zero-valent iron, copper wool, limestone,carbon, and phosphate are used in PRBs. Zero-valent iron and mixtures of ironwith other materials such as sand, gravel, or wood chips accounts for 75% of theapplications of PRBs globally (USEPA, 2002).

TABLE 5.8Toolbox: Groundwater Monitoring

Groundwater Tracers Description Application Remarks

Unconfined groundwater balance

A water budget requires quantification of all aspects of hydrologic systems that add or remove water from the component of interest. The water balance equation can be solved for any individual component

Advantage: Useful at early stage of site characterization

Disadvantage: Field measurements are time consuming

Predict response of near-surface groundwater levels to other parameters of the hydrologic cycle

Moisture profile for specific yield

The initial level of shallow well is measured and the moisture content is determined in intervals of 0.1 m in the capillary fringe above the water table

Advantage: Useful for sites that want to avoid pump tests that bring contaminants to surface

Disadvantage: Shallow aquifers

Measure specific yield

FIGURE 5.9 Typical configuration of a PRB showing the source zone, plume of contam-ination, treatment zone, and plume of treated groundwater. (Reprinted with permissionfrom Powell and Associates.)

Water table

Groundwater flowPlume

Waste

Treated water

PRB


With the increased applications of PRBs since the mid-1990s, the databaseof case histories has been established and is constantly expanded. These databasesare also increasingly available to the public. An example is the Internet site(http://www.rtdf.org/public/permbarr/prbsumms/default.cfm) maintained by theprivate–public partnership called the Remediation Technology DevelopmentForum (RTDF). From these case histories, the following basic goals are definedfor subsurface verification [United States Corps of Engineers (USACE), 1997].

• Assurance that the contaminant plume is being adequately capturedand treated

• Assurance that the barrier meets design goals (e.g., permeability, res-idence time, reactivity)

• Estimation of the longevity of the barrier performance (e.g., reactioncompleteness, hydrologic flow maintained, availability of reactivematerials)

• Assurance that the PRB does not have downgradient adverse effectson groundwater quality

5.8.1 REGULATORY FRAMEWORK

The current state of the practice for subsurface verification is described as guide-lines by the USACE (1997) and USEPA (1997), and as case studies (Puls et al.,1999a). Such guidance and case histories stress the importance of initially char-acterizing the contaminant transport system and the groundwater chemistry asthe critical framework for verification monitoring. The USACE, for example,states that the design of a PRB and its verification relies on the initial character-ization of the groundwater flow system, organic composition of the groundwater,and the inorganic composition of the groundwater (USACE, 1997). The USEPA(1997) suggested similar guidelines with the goals to detect:

• Loss of reactivity• Decrease in permeability• Decrease in reaction zone residence time• Short-circuiting of the reactive zone• Funnel wall leakage

In USEPA guidance, the following compliance monitoring parameters exist:

• Contaminant(s) of interest• Potential contaminant daughter (degradation) products• General water quality parameters (including hydrologic parameters,

both baseline and over time; precipitates on iron surfaces; Eh; dissolvedoxygen; and ferrous iron)


USEPA guidance relies on monitoring wells to determine whether regulatorygoals are being achieved, contaminant breakthrough occurs, and contaminant flowaround the barrier occurs. According to guidance, monitoring well locationsshould be installed in the following locations:

• Upgradient of the barrier• Within the reactive zone of the barrier• Immediately downgradient of the reactive zone discharge• At each end of the of the barrier• Below the barrier• Above the reactive zone (if possible)

Similar to the USEPA, the USACE (1997) monitoring and verification strat-egy guidance uses groundwater analysis from monitoring wells. Specifically, theUSACE guidance has the following goals:

• Verify plume capture by the PRB through groundwater analysis frommonitoring wells and tracer tests (e.g., sodium bromide).

• Verify longevity of the PRB through geochemical monitoring of asample obtained from monitoring wells and through sample analysisfrom a sample cored from holes into the reactive material of the barrier.• Enable baseline technologies by analyzing volatile organic com-

pounds (VOCs) in the laboratory using GC/MS.• Perform metals, anions, and total organic carbon laboratory analysis.• Obtain water level, pH, Eh, temperature, and dissolved oxygen

measurements using in-hole probes.• Measure specific conductance, turbidity, and salinity with field

instruments.


The state of the practice for PRBs is in the infant stage. Some field applicationshave been very successful but an understanding of the chemical behavior of thePRBs remains in development. Excellent progress has been made in developingan understanding of barrier materials.

5.8.2.1 Flow Characterization and Monitoring

Tracer technology is the preferred method for flow characterization and monitor-ing. Borehole flow meters are in disfavor because different types give contradic-tory results. Without clarification of the reasons for the discrepancies, the endusers do not feel that the use of the borehole flow meters can be justified. Tracertechnologies for application to PRBs can be selected from Table 5.9.


TABLE 5.9Toolbox: Tracers


Ions Soluble salts are dissolved in water and injected into a well and monitoring wells downgradient are sampled; concentrations of ions are analyzed in the laboratory

Common ions include CaCl2, NaCl, LiCl, NH4Cl

Measure groundwater flow paths and velocity, monitoring sanitary landfill leachate migration, and dilution by receiving waters

Dyes Dye is poured on to the ground surface, down a drain, or injected into a well; suspected points of discharge are monitored and visually sampled

Dyes are inexpensive and simple to use; fluorescent or not fluorescent

Adsorption of dye on subsurface material can be a problem

Identify zones of preferential flow in the vadose zone, speed and direction of flow in karst, and movement, velocity and source of contaminants

Gases Gas tracers can be grouped into three major groups: inert natural, anthropogenic gas, gas isotopes; similar to ions in porous media; gas is injected into the space between the packers in one hole and air pumped out of the area between the packer in the other hole

Noble gas-nonreactive, nontoxic, and low natural concentrations

Difficult to maintain constant recharge rate, time required to develop equilibrium and loss to atmosphere

Detect fracture connectivity in the unsaturated zone

Stable isotopes Groundwater samples are collected and analyzed for isotopic composition; the average isotope composition including deuterium and 18O in precipitation reaches the groundwater through infiltration changes with elevation

Differentiate between natural and contaminant sources where nitrates, sulfates, and methane present

Disadvantage: Lab analysis required, not suitable for injection

Differentiate contaminant derived and naturally occurring chemical constituents in groundwater

Radioactive isotopes

Radioactive isotopes were used in 1950s as tracers in groundwater (Tritium, carbon-14, and radon-222); health concerns have stopped its utilization

Advantage: Normal groundwater sampling, analysis of tritium and radon-222 are simple

Disadvantage: Health risk exists

Estimate groundwater age, infiltration and discharging groundwater to surface water


5.8.2.2 Verification of Geochemical Gradients and Zones

Columns and field conditions, unlike well-mixed batch systems, result in thedevelopment of steep chemical gradients within the iron-bearing zone, at theinterfaces between the iron bearing zone and the surrounding material, and down-gradient where the plume of treated water interacts with the native aquifer material(Tratnyek et al., 2003). Although some early work recognized that these gradientscould be significant (Fryar and Schwartz, 1994; Johnson and Tratnyek, 1994;Tratnyek et al., 1995), further characterization of these geochemical gradients isneeded at the field scale before their effects on contaminant fate can be accuratelyassessed. Recently, considerable progress on this topic has occurred throughintegrated monitoring and modeling studies associated with several field sites,including Moffett Field in Mountain View, California (Gupta et al., 1998; Sasset al., 1998; Yabusaki et al., 2001), the U.S. Coast Guard Support Center inElizabeth City, North Carolina (Puls et al., 1999b; Blowes and Mayer, 1999;Blowes et al., 1999a,b), and the Y-12 uranium processing plant in Oak Ridge,Tennessee (Gu et al., 2002; Liang et al., 2000).

TABLE 5.9 (continued)Toolbox: Tracers


Water temperature

A pulse of hot water is injected into a well and temperature in one or more observation wells downgradient are measured

Advantage: Simple, inexpensive

Disadvantage: Less accurate

Measures groundwater travel time between two wells, detects of temperature anomalies associated with radioactive waste or microbial degradation of contaminants

Particulates Selected microbes, typically baker’s yeast or nonpathogenic bacteria, are injected in a well and monitored downgradient at different intervals; a few kilograms of spores can also be utilized; movement of the tracers are monitored downstream

Advantage: Microbes can be used in porous media, high injection concentration, spores pose no health concern

Disadvantage: Health concerns with use of viruses, detection

Trace velocity, direction flow


Some of the major geochemical gradients that have been observed associatedwith iron PRBs are summarized in Figure 5.10 and involve the following:

• Dissolved oxygen, which is completely removed within a few milli-meters of where groundwater enters the iron bearing zone

• Dissolved hydrogen, which rises over the width of the iron-bearingzone to near saturation

• pH and dissolved Fe (II), both of which usually rise rapidly inside thewall and then decline gradually in the downgradient region

• Dissolved carbon dioxide, which precipitates near the upgradient inter-face as iron carbonates

• Nitrite anion (NO3–), which is abiotically reduced to ammonia

• Sulfate anion (SO42–), which is reduced by anaerobic bacteria to sulfide,

much of which then precipitates as iron sulfides (Tratnyek et al., 2003)

Note that lateral diffusion is slow into the plume of treated groundwater, soreoxygenation by this mechanism is expected to be minimal and the anaerobicplume may eventually extend a considerable distance downgradient of the ironPRB.

As a consequence of the gradients in groundwater geochemistry describedabove, zones of authigenic precipitates develop along the flow path of iron PRBs

FIGURE 5.10 Schematic of a cross section of an iron PRB showing the major gradientsin groundwater geochemistry, zones of precipitation, and expected regions of microbio-logical influence.

Oxygen

Carbonate

Sulfate

Nitrate

Hydrogen

pH

Fe(I) Low

Varies

Varies

0

Varies

Varies

Varies

Contaminated groundwater Treated groundwater

0

0

Low

Low

Low

8–11

High

7


and columns designed to simulate these conditions (Tratnyek et al., 2003). Aconsiderable amount of research has been conducted on the iron oxides andcarbonates that accumulate near the upgradient interface because these solids cancement grains and decrease porosity, thereby preventing contaminated ground-water from flowing through the treatment zone. The effect of these precipitateson overall rates of contaminant reduction is not entirely clear, however, becausemost field data suggest that contaminant reduction occurs mainly near the upgra-dient interface, where precipitation of oxide and carbonates might contribute topassive iron surfaces and therefore slower overall rates of corrosion.

The zone of precipitation that develops on the native aquifer material beyondthe downgradient interface has received comparatively little attention to date(Tratnyek et al., 2003). It is known, however, that most of the dissolved iron thatis released by the treatment zone precipitates on the downgradient aquifer mate-rial, resulting in the accumulation of Fe(II)-containing oxyhydroxides (and favor-ing a decrease in pH). These changes minimize undesirable changes in ground-water geochemistry that might be caused by an iron PRB. In addition, theaccumulation of highly reactive forms of Fe(II) creates a zone that may result infurther contaminant degradation by abiotic and biologically mediated pathways.

5.8.3 CASE HISTORY: SUBSURFACE MONITORING

Puls et al. (1999b) describe a specific monitoring program for a former U.S. CoastGuard Support Center in Elizabeth City, North Carolina. At this site, seven roundsof performance monitoring were completed between 1996 and 1998 for a PRBthat remediates both chromate and chlorinated solvents. The monitoring andverification approach was described as follows:

• 10 2-cm diameter compliance wells• 15 multi-level samplers for TCE, cis-dichloroethylene, vinyl chloride,

ethane, acetylene, major anions, metals, Cr(VI), Fe(III), total sulfides,dissolved hydrogen, Eh, and pH, dissolved oxygen, specific conduc-tance, alkalinity, and turbidity

• Electrical conductance profile with Geoprobe™ to verify emplacementof continuous wall

• Coring into the barrier to evaluate rate of corrosion and precipitatebuildup (vertical and angled 15-cm core into the barrier)


Verification needs for PRBs were established (Table 5.10) and augmented bypublished monitoring system guidance (USACE, 1997) and in published journalarticles. Several high-order verification needs have emerged, all of which focuson the fact that variations in parameters such as flow and biomass are the necessarycomponents to monitor — not merely inflow and outflow.


5.8.4.1 Spatial and Temporal Flow Monitoring Considerations

Generally, the monitoring data from existing PRB applications show that theinstalled PRBs are treating the contaminants that flow into the treatment zone.However, the most common observation that compromises the overall PRB treat-ment system is not capturing the contaminant flow due to overflow, underflow,and side flow. For example, according to the RTDF’s web site, one fifth of theplume is migrating around the barrier and escaping the PRB capture zone at theCopenhagen, Denmark, Freight Yard. Gupta and Fox (1999) noted that the mostoverlooked factors affecting PRB performance are (1) aquifer heterogeneity(i.e., preferential flow and natural barriers, localized high-flow zones in boundingaquitards for PRB placement, and localized aquifer interconnection), and(2) variations in both the flow velocity and directions of contaminant transportsystem. For example, at the Borden site (Canadian Forces Base), the shape ofthe plume and changing flow direction made subsurface verification so difficultthat the contaminant concentrations were above the predicted levels and remained

TABLE 5.10Subsurface Verification Needs as Defined at the Baltimore Workshop, July 2002

A. Is the barrier emplaced as designed?B. Does PRB capture plume?

a. Capture of flow system — does all flow channel through PRB?b. General consensus — point sensors for flow don’t work. Is there a better way to measure

system flow?c. Placement of barrier into impermeable barrier/layer is criticald. Creation of preferential flow during construction

C. Effectiveness of the barriera. Chemical

i. Performance assessment: measure daughter products to show system is working; install monitoring well in barrier and horizontal boring across barrier to measure gradients

ii. Capacity: defined by modelingiii. Emplacement during construction of barrier, e.g., ERT electrodes can be used for IP

measurementsiv. Is material in PRB working; how long can it work?v. Sensors that measure chemistry in situ

vi. Geochemical indicators that barrier is performing chemically, pH, Ehb. Hydrologic

i. Creation of preferential flow during constructionii. Preferential flow into small part of barrier — is treatment adequate?

iii. How does flow change through time, clogging, channeling, etc.iv. Conductivity, porosity, precipitation of metals in barrier

c. Bio-barriersi. New performance parameters needed

ii. New technology to monitor needed


above the maximum contaminant level (MCL) (USACE, 1997). As a result ofsuch spatial and temporal variability, Eykholt et al. (1999) concluded that thebasic deterministic design approach for PRBs was nonconservative for heteroge-neous aquifers.

5.8.4.2 Geochemical and Hydrological Process Monitoring Considerations

Roh et al. (2000) noted that geochemical and hydrological processes are of highconcern in PRBs because these processes have high impact on the reactivity andpermeability of the treatment system. For example, Morrison et al. (2002) wrotethat the formation of a gas phase and the precipitation of a secondary mineralphase resulted in the loss of hydraulic conductivity of one treatment cell at theBodo Canyon site in Colorado. The USACE has identified that the monitoringof organic and inorganic composition of the groundwater upgradient of the PRBis important in assessing the potential for loss of hydraulic conductivity (USACE,1997). Also, construction of the barrier can lead to heterogeneities within thereactive material such as layers with different porosity, which can lead to trans-verse hydrologic conductivity. Construction also can result in water backflow intothe barrier from bounding surface units and in irregular surface topography thatcan produce heterogeneities in the surface infiltration.

5.8.4.3 Acoustic Wave Devices

At present, acoustic wave devices (Figure 5.11) have the highest potential toprovide the lowest detection limits for real-time measurements at low cost and

FIGURE 5.11 Acoustic wave sensor (In Situ Remote Sensors and Networks, 1999d).

Output transducer(detects acoustic wave)

Acoustic wavetraveling acrosssurface of device

Carbontetrachloride

plume

Sensor monitoring/data collection

equipment

Input transducer(creates acoustic wave)

Paws sensor

Mon

itorin

g w

ell

Electronic monitoringequipment

Coating sensitiveto carbon

tetrachloride


in portable configuration. Typically an acoustic wave sensor involves the appli-cation of a chemically sensitive film onto the surface of the oscillating resonatorcrystal. Interactions of the film with the analyte induce a change in the mass andviscoelastic properties of the film. This change is measured as the shift of theresonance frequency of the oscillating crystal and is related to the concentrationof the analyte. For detection of analytes differing in nature, the coating/analyteinteractions can include hydrogen bonding, hydrophobic, π-stacking, acid–base,electrostatic, and size/shape recognition. Selective analyte detection to verifyPRBs can be achieved by coating several sensors with different films and ana-lyzing the response pattern in such a sensor array by means of different patternrecognition techniques.

In the last decade, federal agency research and development programs havefocused on field analytics and sensor technologies that can be applied to hazardouswaste site characterization, remediation, and monitoring activities. For example,the USDOE’s Environmental Management Science Program web site currentlylists more than 70 research and development projects that address data collectionor sample analysis issues. Techniques as diverse as antibody methods, in situmicrosensors, spectroelectrochemical sensors, spectrometric DNA diagnostics,dielectrics and nuclear magnetic resonance partitioning tracers, electromagneticimaging, seismic technologies, acoustic probes, conductive luminescent poly-mers, cavity ringdown spectroscopy, gamma-ray imaging, optical array sensors,noble gas detectors, and BioCOM sensors are mentioned. Likewise, the U.S.Department of Defense (USDOD) Strategic Environmental Research and Devel-opment Program has funded more than 20 research and development activitieson its sites focused on characterization and monitoring technologies. Researcherswith the U.S. Navy Space and Warfare Systems Command (SPAWAR) havefocused specifically on technologies applicable to the more specialized needs ofsediment covers (Table 5.11) that are applicable to other barriers as well.

5.9 WALLS AND FLOORS

The basic functionality of a floor or wall is to prevent migration of contaminantsby providing a physical barrier to their transport. If the physical barrier is com-promised either locally or globally by a hole, breach, or flaw, then the ability ofthat barrier to successfully contain the contaminants can be diminished beyondacceptable levels. It is difficult to obtain stakeholder acceptance of barrier tech-nologies if the integrity and performance capabilities of the installed barriercannot be proven and the long-term stability cannot be monitored.

The requirements for monitoring walls and floors are divided between thevadose zone and the saturated zone, with each equally critical because failuresoften occur at the junction of the walls and floors regardless of location. Integra-tion of the sensors into the barrier during the design of the system is now practical.Some of the sensor monitoring requirements are as follows:


Tabl

e 5.

11Su

mm

ary

of S

enso

r an

d Fi

eld

Ana

lyti

cal T

echn

ique

s (N

atio

nal

Res

earc

h C

ounc

il, 2

003)

Tech

niqu

e

Med

iaPe

rfor

man

ceA

pplic

atio

n

Analytea

Soil/Sediment

Water

Gas/Air

Selectivity

Susceptibility to Interference

Detection Limits

Turnaround Time per SampleQuantitative Data CapabilityTechnology StatusRelative Cost per AnalysisScreen/IdentityCharacterize/QuantityCleanup PerformanceLong-Term Monitoring

VO

C,

SVO

C, T

PH a

nd P

CB

(in

sit

u an

alys

is)

Solid

/por

ous fi

ber-

optic

11E

AB

BA

BA

AI

AA

BA

BL

aser

-ind

uced

fluo

resc

ence

5, 1

1B

AN

AB

BB

AB

III

AA

BA

B

VO

C,

SVO

C, T

PH a

nd P

CB

(ex

sit

u an

alys

is)

Phot

oion

izat

ion

dete

ctor

1, 3

EE

AB

CB

AC

III

AA

CA

CFl

ame-

ioni

zatio

n de

tect

or1-

–3E

EA

BC

AA

CII

IA

AC

AC

Exp

losi

met

er1

EE

AC

CB

AC

III

AA

CA

CG

as c

hrom

atog

raph

y (G

C)

plus

det

ecto

r1-

–6,

11E

EA

AA

AB

AII

IB

AA

AA

Cat

alyt

ic s

urfa

ce o

xida

tion

1,3

EE

AB

BB

AC

III

AA

BA

AD

etec

tor

tube

s1,

3E

EA

BB

BA

CII

IA

AC

AC

Mas

s sp

ectr

omet

ry (

MS)

1-–6

EE

AA

BB

BA

IIC

BA

AB

GC

/MS

1-–6

EE

AA

AA

CA

III

CA

AA

BG

C/io

n tr

ap M

S1-

–6E

EA

AA

AC

AII

CA

AA

BIo

n tr

ap M

S1-

–6E

EA

AB

AB

AII

CA

AA

AIo

n m

obili

ty s

pect

rom

eter

1-–4

, 6

EF

AA

BA

AA

IIB

AB

AB

Ultr

avio

let

(UV

) fl

uore

scen

ce1,

3,

5B

AB

CB

AB

BII

BA

BA

A


TAB

LE 5

.11

(con

tinu

ed)

Sum

mar

y of

Sen

sor

and

Fiel

d A

naly

tica

l Tec

hniq

ues

(Nat

iona

l R

esea

rch

Cou

ncil,

200

3)

Tech

niqu

e

Med

iaPe

rfor

man

ceA

pplic

atio

n

Analytea

Soil/Sediment

Water

Gas/Air

Selectivity

Susceptibility to Interference

Detection Limits

Turnaround Time per SampleQuantitative Data CapabilityTechnology StatusRelative Cost per AnalysisScreen/IdentityCharacterize/QuantityCleanup PerformanceLong-Term Monitoring

Sync

hron

ous

lum

ines

cenc

e/fl

uore

scen

ce1-

–4E

AB

BB

AB

BI

BA

BA

AU

V-V

isib

le s

pect

roph

otom

etry

1, 3

, 5

EA

BC

CA

AB

IB

AB

AA

Infr

ared

spe

ctro

scop

y1-

–4E

EA

BC

BA

BII

BA

BA

AFo

urie

r tr

ansf

orm

inf

rare

d (F

TIR

) sp

ectr

osco

py1,

3,

11E

EA

AB

AA

BII

BA

BA

ASc

atte

ring

/abs

orpt

ion

LID

AR

1, 3

EE

AC

CC

AB

IB

AB

AA

Ram

an s

pect

rosc

opy/

surf

ace

enha

nced

Ram

an

scat

teri

ng (

SER

S)1-

–5,

11E

AE

CC

AA

BII

BA

BA

A

Nea

r IR

refl

ecta

nce/

tran

smitt

ance

spe

ctro

scop

y1,

3A

NA

NA

CC

CA

BI

BA

BA

AIm

mun

oass

ay c

olor

imet

ric

kits

1-–6

, 11

AA

NA

BB

BA

BII

AA

BA

BA

mpe

rom

etri

c an

d ga

lvan

ic c

ell

sens

or1,

3E

NA

AA

BA

AB

IIA

AB

AA

Sem

icon

duct

or s

enso

rs1,

3F

AA

BB

AA

BI

AA

BA

APi

ezoe

lect

ric

sens

ors

1, 3

FE

AA

CA

AB

IA

AB

AA

Fiel

d bi

oass

essm

ent

1-–6

AA

AC

CN

AC

CII

CA

AC

BTo

xici

ty t

est

1-–6

AA

AC

CN

AB

BII

AA

AC

AR

oom

-tem

pera

ture

pho

spho

rim

etry

4, 5

, 6,

12

(PC

Bs)

BA

BA

CA

BB

IB

AB

AA

Subsurface Barrier Verification 335C

hem

ical

col

orim

etri

c ki

ts2,

4,

5, 1

1B

AN

AB

BB

AB

IIA

AB

AA

Free

pro

duct

sen

sors

11N

AA

NA

CA

CA

CII

IA

AA

AA

Gro

und

pene

trat

ion

rada

r11

BC

NA

CC

CC

BI

BB

AB

BT

hin-

laye

r ch

rom

atog

raph

y2

EA

NA

BB

AB

AII

CA

AA

A

Met

als

(ex

situ

ana

lysi

s)A

tom

ic a

bsor

ptio

n (A

A)

spec

tros

copy

7E

EA

AA

AC

AI

CC

AC

BIn

duct

ivel

y co

uple

d pl

asm

a-at

omic

em

issi

on

spec

tros

copy

(IC

P-A

ES)

7E

EA

AA

AB

AI

CC

AC

B

X-r

ay fl

uore

scen

ce7

AA

FA

AB

AA

III

AA

BA

BC

hem

ical

col

orim

etri

c ki

ts7,

9B

AN

AA

BB

BB

IIA

AB

AA

Titr

imet

ry k

its7,

9B

AN

AA

BB

BB

III

AA

BA

AIm

mun

oass

ay c

olor

imet

ric

kits

7, 1

2 (H

g)A

AN

AB

BA

AB

IIA

AB

AA

Ano

dic

stri

ppin

g vo

ltam

etry

7E

AN

AA

BA

AA

IIB

BA

AB

Fluo

resc

ence

spe

ctro

phot

omet

ry7,

12

(Hg)

EE

AA

BA

AA

IIB

AA

AA

Am

pero

met

ric

and

galv

anic

cel

l se

nsor

7E

AN

AA

BB

AB

IIA

AB

AA

Fiel

d bi

oass

essm

ent

7, 9

AA

AC

CN

AC

CII

CA

AC

BTo

xici

ty t

ests

7, 9

AA

AC

CN

AB

BII

AA

AC

AIo

n ch

rom

atog

raph

y7

EA

NA

BB

AA

AI

BA

AA

A

Expl

osiv

es (

ex s

itu

anal

ysis

)G

as c

hrom

atog

raph

y (G

C)

plus

det

ecto

r10

EE

BA

AB

BA

IIC

BB

BB

Mas

s sp

ectr

omet

ry10

EE

BB

CB

AA

IIC

BB

BB

GC

/MS

10E

LA

AA

BB

AII

CB

BB

BIo

n m

obili

ty s

pect

rom

eter

10E

EA

AC

AB

AI

CA

CC

CFi

eld

bioa

sses

smen

t10

AA

AC

CN

AC

CII

CA

AC

BTo

xici

ty t

ests

10A

AA

CC

NA

AB

IIA

AA

AA

Che

mic

al c

olor

imet

ric

kits

10E

AN

AB

BB

AB

III

AA

BB

AIm

mun

oass

ay c

olor

imet

ric

kits

10E

AN

AB

BB

AB

III

AA

BB

A


TAB

LE 5

.11

(con

tinu

ed)

Sum

mar

y of

Sen

sor

and

Fiel

d A

naly

tica

l Tec

hniq

ues

(Nat

iona

l R

esea

rch

Cou

ncil,

200

3)

Leg

end

aA

naly

tes:

1, n

onha

loge

nate

d vo

latil

e or

gani

cs; 2

, non

halo

gena

ted

sem

ivol

atile

org

anic

s; 3

, hal

ogen

ated

vol

atile

org

anic

s; 4

, hal

ogen

ated

sem

ivol

atile

org

anic

s;5,

pol

ynuc

lear

aro

mat

ic h

ydro

carb

ons

(PA

Hs)

; 6,

pes

tici

des/

herb

icid

es;

7, m

etal

s; 8

, ra

dion

ucli

des;

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• Flux through walls• Continuity and uniformity (thickness, depth, wall/floor connection)• Total flow of contaminant• Joints (contaminants, moisture, pH, flow, temperature, conductivity)• Slurry wall drawdown• Sheet pile grout (pH, temperature, flow, conductivity, moisture)• Upstream vs. downstream verification• System for leachate collection• Sensors for vadose and saturated zones• Changes in subsurface over time• Subsidence of walls and floors

The fact that barriers and/or waste from materials are so vastly different thanthe surrounding soils yields high signal to noise ratios for geophysical techniques.As a whole, geophysical methods are good for determining gross field changesand estimating boundaries. Most contaminant transport pathways (e.g., holes,cracks, thins) are missed by geophysics and may be better searched for by othertechniques such as gaseous tracers. Although tracers are best suited for determin-ing pathways, it is difficult if not impossible to determine variables such as wallthickness to fractions of a foot, special placement of the entire barrier (determin-ing an as-built blueprint), density, or soil moisture using tracers.

It is follows that a suite of verification/monitoring technologies will berequired to meet stakeholders’ needs.


Clearly, technologies are required that can verify the integrity and performanceof newly installed walls and floors and that can be used to monitor the integrityand performance of those barriers for the expected service life of the containmentsystem. Preferably, those technologies will be predictive in nature so as to fore-cast/detect early or impending failure (as defined by contaminant release beyondthe containment boundary).

5.9.1.1 Neutron Well Logging

Currently, neutron well logging has become an important tool for estimatingporosity and moisture content of a formation. Neutron logging is used to measurethe hydrogen index, Ih, which is defined as the equivalent volume fraction of freshwater containing the equivalent amount of hydrogen. Neutrons generally interactwith atomic nuclei and therefore interactions are less frequent and neutron rangesare longer than other nuclear radiation. The most common neutron interaction iselastic scattering. Classical mechanics show that the neutron is moderated moreefficiently by nuclei with a mass similar to the neutron, such as hydrogen andother low mass elements. There are two types of neutron sources, chemical and


accelerator. Both sources produce fast neutrons, and the logging type is usuallydistinguished by the detector type, either thermal or epithermal. Chemical sourcesproduce neutrons with an energy of about 4 millivolt equivalents (MeV). Accel-erators produce neutrons with an energy of about 14 MeV. Chemical sources havethe advantage of being cheap and reliable, while accelerators have the advantageof being able to turn off the neutron source.

There are two common methods of measuring water content using neutrondiffusion: the neutron log and the moisture gauge. An extended comparison ofthe two methods can be found in Hearst and Carlson (1994). Moisture gaugesare sensitive to thermal neutrons and have an affected radius of 10 to 20 cm.Neutron logs measure thermal or epithermal neutrons depending on sonde con-figuration and have a measurement radius of 20 to 30 cm. Thermal neutronmethods are used in fluid-filled boreholes and are of little value in air-filledboreholes. Epithermal methods are preferred for air-filled boreholes and can alsobe used in fluid- or foam-filled boreholes.

Neutron methods depend on many different parameters such as porosity,matrix, pore fluid, salinity, temperature, pressure, standoff, and borehole geom-etry. A complete mathematical solution incorporating all of these parameters isnot feasible; therefore, numerical approximations are used and are field calibrated.Such approximations do not allow exact pictures of the subsurface but yieldstatistical equivalents that are averages over the affected range. Neutron loggingcan be very useful in following soil moisture within the contained area. Long-term calibration standards are recommended for barrier applications.

5.9.1.2 Perfluorocarbon Tracer (PFT) Monitoring/Verification

Brookhaven National Laboratory has developed rapid and sensitive analyticalmethods for a host of PFTs. These tracers were originally used in atmosphericand oceanographic studies and have since been applied to a great variety ofproblems, including detecting leaks in buried natural gas pipelines and locatingradon ingress pathways in residential basements.

Leaks/flaws are located by injecting a series of tracers on one side of a barrierwall and then monitoring for those tracers on the other side (Figure 5.12). Theinjection and monitoring of the tracers is accomplished using conventional lowcost monitoring methods, such as existing vadose zone monitoring wells or multi-level monitoring ports placed using CPT techniques. The amount, type of tracer(speciation), and arrival times can all be used to characterize the size and locationof a fault.

It is easy to see that the larger the opening in a barrier the greater the amountof tracer that is transported across the barrier. Locating the breach requires moresophistication in the tracer and/or analysis methodology. Multiple tracer typescan be injected at different points along the barrier in both vertical and horizontaldirections. Investigation of the spectra of tracers coming through a breach givesinformation on the location relative to the various tracer injection points. Arrivaltimes of the different tracers can also be measured to obtain a more detailed


analysis. Having multiple tracers also allows for confirmation of holes and dif-ferentiation between holes and spill over.

PFT technology consists of the tracers themselves, injection techniques, sam-plers, and analyzers. PFTs have the following advantages over conventionaltracers:

• Negligible (a few parts per quadrillion) background concentrations ofPFTs exist in the environment. Consequently, only small quantities areneeded.

• PFTs are nontoxic, nonreactive, nonflammable, environmentally safe(contains no chlorine), and commercially available.

• PFT technology is the most sensitive of all nonradioactive tracer tech-nologies and concentrations in the range of parts per quadrillion (1 in1015) are routinely measured.

• The PFTs technology is a multi-tracer technology permitting up to sixPFTs to be simultaneously deployed, sampled, and analyzed with thesame instrumentation, resulting in a lower cost and flexibility in exper-imental design and data interpretation. All six PFTs can be analyzedin 15 minutes on a laboratory-based GC.

• Several real-time, portable instruments are available that allow rapid(less than five minutes) analysis of tracers with slightly reduced sen-sitivity (parts per trillion).

Understanding mass transport through defects in barriers is central to evalu-ating barrier continuity. The migration of tracers is analyzed using computercodes that predict the transport of the gas tracer through a porous soil and barrier

FIGURE 5.12 Schematic of PFT technology with multiple tracers.

Injection well

Perfluorocarbontracers

Subsurface barrier wall

Extraction well fitted withmultiple sampling ports


with defects. Existing computer codes can be adapted as necessary for the prob-lem. PFT technology allows locating and sizing of breaches at depth and hasbeen shown to have a resolution of fractions of an inch. The technology hasregulatory acceptance and is used commercially for nonwaste management prac-tices (e.g., detecting leaks in underground power cables). This technology hasbeen used in a variety of soils and is applicable to other USDOE sites as well ascommercial waste sites.

PFT technology is expected to and has been shown to operate under a varietyof conditions. The technology is unaffected by waste type, temperature (withinthe confines of expected environmental temperatures at waste sites), or pH/Eh.Tracer transport is affected by geologic or physical differences such as soil type,layering, degree of fracturing, or void volume, but all of these are expectedvariations and are easily accounted for through normalization, modeling, orexperimental measurement. The fundamental principal behind the technologyoperation and, hence, success remains unchanged.

Two parameters that can adversely affect PFT measurements are soil moistureand barometric pressure. As soil moisture content increases, the air-filled porosityof the soil decreases and changes the transport rate of the tracers. For subsurfacebarriers, this change has not been an issue. For the range of soil moisture encoun-tered in deeper soils (greater than 3 m), no significant changes occur in soilmoisture over the duration of a test and, therefore, transport rates are unaffectedand this parameter can be ignored. For surface barriers, soil moisture issues area greater concern. Cover systems can be at saturated conditions in the upperlayers after a severe rainfall event. This would clog the pore structure and dras-tically reduce tracer transport. For lesser degrees of saturation, the effect wouldbe a reduction in transport. The relationship of tracer transport rates vs. soilmoisture content needs to be determined. Once the relationship is known, it canbe accounted for or minimized (e.g., by not testing immediately after a severeprecipitation event).

Barometric pressure is only important to cover system measurements andonly through barometric pumping. Rapid changes in atmospheric pressure cancause pumping of the soil gases to the surface. This phenomenon is limited (interms of affecting PFTs) to the first 0.9 to 1.35 m of soil and therefore does notaffect subsurface barrier measurements. Even with a shallow surface layer(approximately 0.03 m), barometric pumping has not precluded the technologyfrom successful deployment. In this case, the dilution of the tracer due to near-surface effects was about one order of magnitude and was well within the rangeof the technology’s sensitivity.

A cost estimate and life-cycle assessment need to be developed. The tech-nology developers have spoken with several commercial interests, including aninstrument manufacturer to produce and sell or rent PFT instrumentation, atechnology vendor to provide complete packages, and service vendors to providePFT technology to sites on a service contract. While initial interest is high andthe instrument vendor is ready to provide units, no formal cost estimate has beenperformed.


5.9.2 CASE HISTORY: COLLOIDAL SILICA DEMONSTRATION

During the summer of 1997, a subsurface barrier was installed at BrookhavenNational Laboratory in Upton, New York. The barrier consisted of a colloidalsilica grout that was placed using permeation grouting. Upon gelling, the groutforms an impermeable barrier that can be used to contain subsurface contami-nants. The barrier was installed at a clean site. The site was chosen because ofthe geology (porous sand matrix) and the stated possible need for containmentbarriers in future remediation efforts.

Colloidal silica was injected into the subsurface in an attempt to provide animpermeable barrier for waste isolation. The internal dimensions of the barrierformed an approximately 6 m square with the barrier walls nominally 1.3 m thick.The west wall of the barrier was injected at a 45° angle to the ground surface,and the east wall was installed vertically. This resulted in the north and southwalls (installed vertically) having a triangular shape. Injection rods were pushedinto the ground, and grout was injected to form a bulb. The rod was withdrawnslightly, and another bulb was injected to overlap the first. This process wascontinued until a column of grout was injected. A second column was injectednext to and overlapping the first. In this manner, a barrier was formed thatconsisted of a series of overlapping columns. The integrity of the barrier wasstrongly dependent on the location of the injection rods to provide proper place-ment and overlap of the grouted sections. The performance of the barrier wasdependent on initial integrity, grout performance (e.g., proper gelling, initialpermeability reduction), and long-term stability of the grout (e.g., desiccation,seepage away from the injection zone).

After installation, the integrity/performance of the barrier was investigatedusing a suite of nondestructive subsurface investigation techniques, includinggeophysics, a gaseous PFT technology, and a sulfur hexafluoride (SF6) gas tracer.Ultimately, the barrier was unearthed and the actual dimensions/location of thebarrier were ascertained and compared to the results obtained using the investi-gation tools. The results clearly demonstrated that the geophysical investigativetechniques for determining the integrity/performance of a subsurface barrier weretechnically lagging the installation techniques and materials development.

One particular flaw in the installed barrier serves as a prime example of thechallenge that subsurface structures can present. A leak or flaw in the barrieroccurred due to a misaligned column. When the injection rod was pushed intothe subsurface, it wandered off course. The rod bowed in a banana-shaped fashion.The result was similar to a plank floor with one plank pried upward. At a pointalong the column, the lift was high enough to create a large opening that wouldallow contaminant migration to occur. Figure 5.13 presents two photographs ofthe excavated colloidal silica barrier, shown from the north and south views. Inthe left photograph, the misaligned column is clearly visible. The misalignmentwas enough to allow contaminants to escape but was not observed by geophysics.The colloidal silica grout contains approximately 85% water and, as such, presentsan enormous signal (and clutter) for virtually any geophysical technique. The


result was that the electroresistivity method used detected the rough shape of thebarrier, but could not differentiate anomalies that occurred on fractions of a meterscale. In this case, the opening created by the lifted column was 0.3 to 0.6 mhigh and 1 to 2 m in length.

Both the SF6 and PFT technology deployments were designed as rudimentaryleak tests, but also allowed some analysis to refine flaw location information. Theprimary objective was to test the barrier integrity by injecting tracers inside thebarrier and measuring their concentration outside the barrier as a function of time.

The PFT technology was successful in identifying two locations with weakbarrier integrity. This tracer technology deployed three different gaseous tracersin three different zones within the barrier confines. The east vertical wall showedleakage centered at a depth of 4.5 m below grade approximately 3.6 m into thepanel. In addition, the multi-tracer technology was able to show that tracer leakedover the top of the barrier, thereby reaching the outside monitoring points withouthaving to go through a flaw in the barrier. The actual leak was detected by thetracer oc-PDCH, and the spillover was detected with the tracer PMCH.

The west (slant) wall also showed evidence of a large leak that was approx-imately 3.6 m into the panel at a depth of 5.1 m below grade. This leak was firstdetected with the tracer PMCH. Leakage also occurred over the top of the panelas evidenced by the tracer oc-PDCH. This leak was easily confirmed uponexcavation of the barrier and coincided with the misaligned column. The PFT

FIGURE 5.13 Excavation of the colloidal silica barrier showing a major flaw in the slantwall.


technology was also used to estimate the gaseous diffusion coefficient for thegrouted panels.

The SF6 tracer was able to locate the two major leaks, but also detected otherpossible leaks. The possible leaks were, in fact, measurements of tracer spilloverat the top of the barrier.

The tracer technologies appear to be the best suited for leak detection, asthey can trace even small (i.e., fractions of an inch) faults in a barrier. Althoughthe tracers reveal pathway information, they cannot identify items such as theexact location of a barrier wall, its thickness, or density. While identifying ifpotential contaminant migration paths exist is generally considered the mostimportant factor for subsurface barriers, spatial location of the barrier is importantif precise repairs are needed. In addition, information on subsurface anomaliesthat might affect installation (e.g., large rocks, unexpected waste forms), repairs,monitoring, and long-term stability are also important.

5.9.3 CASE HISTORY: BARRIER MONITORING AT THE ENVIRONMENTAL RESTORATION DISPOSAL FACILITY (ERDF)

The USDOE ERDF located in Hanford, Washington, is a double-lined wastedisposal facility that complies with the USEPA’s Minimum Technology Require-ments for hazardous waste landfills (Figure 5.14). The design of the disposal cells

FIGURE 5.14 ERDF showing Cells 1 and 2 partially full.

Environmental restoration disposal facility


(including new Cells 5 and 6) call for the following: a primary (upper) liner witha 60-mil textured HDPE sheet, and a secondary (lower) liner with a 60-miltextured HDPE sheet in direct contact with a 0.91-m-thick layer of soil–bentoniteadmixture in the bottom of each cell. Although there is a 100-mil HDPE sheetattached to the sump carrier pipe, it has no containment function (Bechtel Han-ford, 1995a,b).

The side slopes of the landfill have grades of 3H:1V, while the floors slopetoward the sump at grades of 1.5% to 3%. Thus, any leachate should drain towardthe sumps. Under normal conditions, the liner systems outside of the sumpsshould not experience any standing leachate (pressure head). Within the sumps,submersible pumps remove leachate so that the head pressure on the floor of thesump, except for transient storm conditions, should be less than 0.30 m.

The low-permeability soil used as the lower component of the secondary linerconsists of silty fine sand mixed with approximately 12% bentonite by weight.This material was carefully moisture conditioned, placed in lifts, and compactedin the field. To establish compaction requirements, a sealed double-ring infiltrom-eter (SDRI) test was performed prior to construction of the liner in the landfillitself. The SDRI verification test is a large-scale simulation of the actual linerand is intended to identify any flaws in construction techniques. SDRI resultsindicated a soil layer permeability of about 1 × 10–8 cm/s.

The top and bottom leachate collection systems were sampled, and the vol-umes from each recorded. In general, the volume ratio was 100:1 between theupper and lower leachate collection system, and well within the allowable leakagethrough the primary liner of 175 gallons per day per acre.

In general, neutron probes and pressure vacuum lysimeters were the barrierverification monitoring tools of choice. Everett and Fogwell (2003) conducted astudy evaluating barrier verification monitoring for Cells 5 and 6 and subsequentcells at the site. Each cell in Figure 5.14 is 21.33 m deep and 152.4 m on a side.The cells are arranged in pairs such that they look like one large cell 152.4 m by304.8 m. The National Academy of Engineering held discussions on the subjectof barrier monitoring through caps and liners, and the consensus was that anymonitoring system that penetrated through the bottom liner would be unaccept-able. Discussions related to monitoring systems that breach the surface cap werefound to be troubling, although the concern related to breaching the cap dimin-ished as the size of the access holes was reduced. Neutron access holes in thecap present some problems due to potential preferential flow between the soiland the casing tubing. Horizontally installed TDR wave-guides and dissipationprobes, however, do not present these problems. Monitoring below the liners didnot appear to be a problem.

Another possible consideration for monitoring systems is redundancy (i.e., asystem that does not rely on only one type of barrier-monitoring system). Thefollowing are some possible benefits that redundancy provides:

• A backup system in the event of instrument failure• A mechanism to crosscheck instrument accuracies


• More confidence in the data• A method for identifying false positives• It can assist in applying the graded approach utilizing an automated

monitoring systems first, and then, if necessary, using a manual systemthat can include analytical costs

• Extension of the life expectancy of the entire monitoring system byproviding backup systems in the event of instrument failure, particu-larly for the nonretrievable elements of the monitoring system

5.9.3.1 Study Conclusions

The above study indicates that barrier verification monitoring has been used atseveral commercial landfill sites in the western part of the United States, wherearid conditions guarantee the existence of a relatively deep vadose zone. Theseapplications of barrier monitoring are generally kept simple and reasonably inex-pensive. They have generally been employed to give an early warning of leakageand, thus, have resulted in a reduction in required groundwater monitoring.

Barrier monitoring is used specifically in two general areas of a landfill,beneath the bottom layer of the landfill and in the final cap. These correspond tothe use of monitoring at two distinct stages of the landfill’s life cycle. The first isduring the operation of the landfill, while it is being filled and before the final capis installed. The second is during the long-term storage phase, while the final cap isin place. Thus, the most appropriate monitoring for the first operational phase is asystem installed below the bottom of the landfill, whereas the most appropriatemonitoring for the long-term phase is one that monitors the integrity of the cap.The above analysis provides potential candidate technologies and approaches foruse in either operational or closure applications.

5.9.3.2 Study Recommendations

Although several reasonable candidates for barrier verification monitoring wereevaluated by Everett and Fogwell (2003), some are more applicable at this sitethan others. For all the ERDF cells, when they are closed, barrier monitoring ofthe caps is strongly recommended (Everett and Fogwell, 2003). The most cost-effective approach to use during the operational phase of the landfill, however,would be to instrument new cells with basin lysimeters below the secondaryleachate sumps. Because of the proven regulatory acceptance, reduced cost con-siderations, ease of installation, and the ability to collect quantifiable results, abasin lysimeter made up of 100 mil HDPE installed under the secondary sumpand beneath the lower compacted low-permeability soil layer in each new cell isthe first recommendation. This lysimeter would extend 1.52 m beyond the perim-eter of the secondary sump, and would be designed with an access pipe thatallows the removal of any liquid collected. It is important that the basin lysimeterbe placed beneath the lowest point of the low-permeability layer.

In addition to the basin lysimeter, Everett and Fogwell (2003) recommendedthat access tubes be laid down beneath the secondary barrier liner. The access


tubes should extend the full length of each cell with spacing sufficient to allowfuture cross-borehole tomography. Because the tubes would be laid down duringconstruction of the new cells, the costs would be minimal. These access tubeswill provide access for a variety of instruments and would accommodate newtechnologies as they are developed. Installation at Cells 5 and 6 or future ERDFcells will provide a relatively controlled setting for evaluating the performance andutility of access tubes at future multi-use facilities (Everett and Fogwell, 2003).

During the capped long-term storage period of the landfill, instrumentationshould be used for maintaining surveillance of the integrity of the barrier cap.Noninvasive methods can be used, including lysimeters around the edge of thecap, subsidence monitoring of the cap structure, and tomographic methods forthe spatial resolution of possible failure points. Invasive methods would entailestablishing entry points through the cap into the interior of the landfill. Inaddition to instrumentation of the cap, sensors could be implanted in the bodyof the landfill in order to monitor its state. Also, any tomographic methods at thesurface could be combined with the underlying access tubes to give tomographicdata on the interior of the landfill. Several possible current technologies havebeen described in this chapter.

The approach outlined above is consistent with other accepted programs, withadditional emphasis placed on access to below the new cells during the operationalphase and cap integrity monitoring of final coverings. Almost all monitoringmethods are expected to be become obsolete or to have some aspect fail overtime; thus, it is prudent to consider new technologies and new testing protocolsas they are developed, and to allow for the possibility of changing out instrumen-tation components.


The ability to verify barrier integrity is valuable to many government agenciesand the commercial sector. Verification needs identified at the Baltimore workshopin July 2002 are similar to those identified for PRBs in Table 5.10. The Officeof Environmental Management of the USDOE outlined a series of technicaltargets in a needs document in 2001. Technical Target #5 addresses advancedsustainable containment systems. The key word here is sustainable, as contain-ment systems cannot be considered sustainable if the long-term monitoring andstewardship concerns cannot be addressed. This is likely the biggest obstacle toclosure many USDOE sites will have. There are many waste treatment technol-ogies and cover system designs available for final disposition of waste streams,but very little available technology to address long-term monitoring/stewardshipissues. The Technical Target further states “Properly applied and monitored (boldadded for emphasis) physical containment and barriers will remain a centralactivity in DOE environmental management for the foreseeable future. Advancingthe science and technology base relatively rapidly is particularly important toclosure sites that need to implement and document such systems in the nextseveral years.”


In order for a wall or floor to protect the environment, it must remain freeof significant holes and flaws throughout its service life. Currently, containmentsystem failures are detected by monitoring wells downstream of the waste site.Clearly this approach is inefficient, as the contaminants have already migratedfrom the disposal area before they are detected. Methods that indicate early barrierfailure (prior to contaminant release) or predict impending failure are needed.Early detection of cover failure or pending failure allows repair or replacementto be made before contaminants leave the disposal cell.

There are clearly two distinct subsets of barriers: cutoff walls/floors andcontainment barriers. The verification needs of these subsets are different. Thevast majority of cutoff walls are slurry wall installations where the greatestverification need is initial integrity. Finding a weak point along the barrier isessential so that the weak spot can be repaired. It appears that the present hydraulicgradient-based methods of testing cutoff walls is working well; therefore, furtherdevelopment of advanced monitoring/measurement methods is not warranted. Forcontainment barriers, the opposite appears to be true. That is, there are no reliable,commercially available integrity/performance measuring technologies available.Therefore, this discussion focuses on containment barriers. It is important to notethat advances in containment barrier verification/monitoring technologies could,in most cases, be readily applied to cutoff walls/floors.

5.9.4.1 Adequacy of the Containment Region

The barrier must meet the required containment goals. The most commonlyobserved failure for installed walls/floors is incomplete grouting (e.g., misalign-ment of injection/drill rods, local incomplete grout cure, blockage of the groutinjection/delivery by subsurface obstructions). All of these lead to a localized areaof the barrier that has reduced containment. The imperfection may or may notaffect the overall performance of the waste site. For instance, a hole in a contain-ment barrier at the top of a wall will not allow significant contaminant migrationbecause horizontal flow in the vadose zone is expected to be minimal and thespread at the top of the barrier will also be minimal. However, should the samesize hole occur at the bottom of the barrier (particularly in V-shaped containmentdesigns), the containment characteristics of the barrier could be compromised. Thecontainment becomes a bathtub with the stopper pulled out, and it can drainquickly. Thus, adequacy of the containment requires knowing the size and locationof the flaw, and the effect the flaw will have on the overall site performance.

5.9.4.2 Long-Term Performance of the Containment

The containment must continue to meet the site performance requirements forthe lifetime of the barrier. As the earlier workshop publications discuss (Rumerand Mitchell, 1995), subsurface barriers are subject to a wide variety of failuresor loss of performance. Desiccation, chemical attack, geotechnical changes(e.g., earthquakes, subsidence) and many other pathways can lead to reduced


barrier performance. When these changes occur, stakeholders must be informedso that corrective actions (if needed) can be implemented. Ideally, barrier perfor-mance monitoring would be such that stakeholders could predict impendingfailure and take action prior to contaminants escaping from the containmentconfines. The following are important considerations in long-term monitoringand verification:

• Monitoring should allow prediction of failure, if possible, rather thandetection of failure through detection of contaminants in downstreamwells.

• Measured parameters need to feed into risk assessment models so thatthe effect of changes in performance can be fully understood in termsof protection of and risk to the public and environment.

• Systems should require as little on-site presence as possible.

The key variable for a containment system is water flux. To a lesser degree,volatile contaminant flux is important. Because volatiles are not expected to bemajor components of new waste/waste forms and are likely to be dispersedalready at historical sites, water flux remains the key variable. (Containmentsystems are not expected to be installed without some sort of cover system;therefore, the water flux through the site is co-dependent on both the containmentbarrier and the cover barrier.) While water flux can be a good indicator of changesover time and trends in performance, simply measuring flux is not enough.Predictive capabilities are also needed and indicator variables that can be tied towater flux or that give indirect evidence of possible changes in water flux needto be measured. Parameters of concern include soil moisture content, permeability(gas/water), precipitation, run off, evapo-transpiration, short-term climate abnor-malities, unusual animal intrusion, changes in the containment barrier materials(e.g., plasticity of clays, oxidation of geotextiles), porosity of the barrier, and thecondition and location of monitoring devices.

5.10 CONCLUSIONS

There are numerous opportunities for sensor development and application in thevarious types of barriers. Sensors can be manufactured cheaply and reliably oncethere is a demand for this type of technology. Acceptance by the regulatorycommunity would follow once the benefit and cost-effectiveness of the sensorshave been demonstrated. A collaborative effort among United States federalagencies would expedite the development of the sensor technologies and shouldbe undertaken immediately. The National Research Council (NRC) recently urgedthe development of sensors for fielded systems for emergency use in counteringterrorism, urging that such a program should build on relevant sensor researchunderway at agencies throughout the federal government because much of thetechnology is transferable to other disciplines (e.g., hazardous wastes, counter-terrorism, medical) (NRC, 2002).


A systematic approach to the selection, implementation, and operation of abarrier-monitoring strategy should be adopted. Because several alternative tech-nologies, monitoring objectives, and barrier configurations exist, a single technol-ogy may not be the most effective for all applications. Barriers exposed toenvironmental and human-induced stresses deteriorate as time progresses fromdecades to centuries. Structural deterioration of some components of a barriermay not always lead to a total functional failure of the system. A uniform approachneeds to be developed for specifying the failure condition of barriers. Monitoringdata can be combined with models to forecast future performance levels and/ormaintenance requirements. Integrated sensor monitoring technologies are expectedto play a large part in barrier performance monitoring and verification in additionto being cost-effective methods for long-term monitoring.

REFERENCES

Bechtel Hanford, Inc. (1995a). Design Analysis, Construction of W-296 EnvironmentalRestoration Disposal Facility, BHI-00355, Rev. 00, Vol. 1, U.S. Department ofEnergy Office of Environmental Restoration and Waste Management, June 1995.

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353

APPENDIX AWorkshop Panels

PANEL 1PREDICTION: MATERIALS STABILITY AND APPLICATION

PANEL LEADER

Craig H. Benson, University of Wisconsin at Madison

PANEL CO-LEADER

Stephen F. Dwyer, Sandia National Laboratories

PANEL GRADUATE FELLOW

Sazzad Bin-Shafique, University of Wisconsin at Madison

PANEL MEMBERS

David W. Blowes, University of WaterlooDavid A. Carson, United States Environmental Protection Agency, National Risk

Management Research LaboratoryPeter W. Deming, Mueser Rutledge Consulting EngineersJeffrey C. Evans, Bucknell UniversityGlendon W. Gee, Battelle Pacific Northwest National LaboratoryLaymon L. Gray, Florida State UniversityKathleen E. Hain, United States Department of Energy, Idaho Operations OfficeStephan A. Jefferis, University of Surrey, United KingdomMark R. Matsumoto, University of California at RiversideStanley J. Morrison, Environmental Sciences LaboratoryScott D. Warner, Geomatrix Consultants, Inc.John A. Wilkens, DuPont

PANEL 2PREDICTION: BARRIER PERFORMANCE PREDICTION

PANEL LEADER

Charles D. Shackelford, Colorado State University


PANEL CO-LEADER

Jack C. Parker, Oak Ridge National Laboratory


Alyssa Lanier, University of Wisconsin at Madison

PANEL MEMBERS

Clifford K. Ho, Sandia National LaboratoriesRichard C. Landis, DuPontEric R. Lindgren, Sandia National LaboratoriesMichael A. Malusis, GeoTrans, Inc.Mario Manassero, Politecnico, Torino, ItalyGreg P. Newman, Geo-Slope International Ltd.Robert W. Puls, United States Environmental Protection Agency, National Risk

Management Research LaboratoryTimothy M. Sivavec, General ElectricBrent E. Sleep, University of TorontoTerrence M. Sullivan, Brookhaven National Laboratory

PANEL 3PREDICTION: DAMAGE AND SYSTEM PERFORMANCE PREDICTION

PANEL LEADER

Hilary I. Inyang, University of North Carolina at Charlotte

PANEL CO-LEADER

Steven J. Piet, Idaho National Engineering and Environmental Laboratory


Paul Wachsmuth, University of North Carolina at Charlotte

PANEL MEMBERS

James H. Clark, Vanderbilt UniversityThomas O. Early, Oak Ridge National LaboratoryJohn B. Gladden, Westinghouse Savannah River CompanyPriyantha W. Jayawickrama, Texas Tech UniversityW. Barnes Johnson, United States Environmental Protection Agency, Office of

Solid Waste and Emergency ResponseRobert E. Melchers, University of Newcastle, Australia

Workshop Panels 355

V. Rajaram, Black and Veatch CorporationW. Jody Waugh, United States Department of Energy, Environmental Sciences

LaboratoryThomas F. Zimmie, Rensselaer Polytechnic Institute

PANEL 4VERIFICATION: AIRBORNE AND SURFACE/GEOPHYSICAL METHODS

PANEL LEADER

Ernest L. Majer, Lawrence Berkeley National Laboratory

PANEL CO-LEADER

David P. Lesmes, Boston College


Marcel Belaval, Boston College

PANEL MEMBERS

Randolf J. Cumbest, Westinghouse Savannah River CompanyWilliam E. Doll, Oak Ridge National LaboratoryEdward Kavazanjian, Jr., GeoSyntec ConsultantsJohn D. Koutsandreas, Florida State UniversityJohn W. Lane, United States Geological SurveyLee D. Slater, University of Missouri at Kansas CityAnderson L. Ward, Battelle Pacific Northwest National LaboratoryChester J. Weiss, Sandia National Laboratories

PANEL 5VERIFICATION: SUBSURFACE-BASED METHODS

PANEL LEADER

David J. Borns, Sandia National Laboratories

PANEL CO-LEADER

Carol Eddy-Dilek, Westinghouse Savannah River Company


Matthew C. Spansky, Westinghouse Savannah River Company


PANEL MEMBERS

William R. Berti, DuPontGeorge K. Burke, Hayward Baker, Inc.Bruce Davis, National Aeronautics and Space AdministrationJohn H. Heiser, Brookhaven National LaboratoryDiana J. Hollis Puglisi, Los Alamos National LaboratoryJohn B. Jones, United States Department of Energy, Nevada Operations OfficeJohn D. Koutsandreas, Florida State UniversityWilliam E. Lowry, Science and Engineering Associates, Inc.Horace K. Moo-Young, Jr., Villanova UniversityMichael G. Serrato, Westinghouse Savannah River Company

357

Index

A

Absorbent pads, 295ACAP, see Alternative Cover Assessment

Program (ACAP)Acar, Alshawabkeh and, studies, 130Acar and Haider studies, 122Acceleration in bedrock, 31Acoustic wave devices, 331, 331–332, 333–336Adamson and Parkin studies, 99Adequacy, containment region, 347ADRE, see Advection-dispersion reaction

equation (ADRE)Advanced Infra-Red Imaging Spectrometer

(AVIRIS), 234, 235Advancement needs, 275–276Advection-dispersion reaction equation

(ADRE), 114, 128, 131AEMS, 307–308Aerial photography, 232, 272–273AES, see Auger electron spectroscopy (AES)AFRL, see Air Force Research Laboratory

(AFRL)Airborne geophysical methods, see Geophysical

method verificationAirborne methods, 228–229, 229–231, 231Air Force Research Laboratory (AFRL), 93, 96,

98, 105, 107, 109ALARA (as low as reasonably attainable), 23ALARP (as low as reasonably practical), 23Albrecht and Benson studies, 89, 160Albright and Benson studies, 157, 159–160, 163Algebraic reconstruction tomography (ART),

221Alshawabkeh and Acar studies, 130Alternative Cover Assessment Program

(ACAP), 159–160, 163, 165Alves, Genuchten and, studies, 114, 116American Society of Testing and Materials

(ASTM), 288–289Anaerobic biodegradation, 98–99Analytical framework, 8–10, 8–11Analytical models, walls and floors, 115, 120,

120–123, 123Anderson, Zhu and, studies, 105Anderson and Hampton studies, 224

Anderson and Woessner studies, 91Animal species, intrusive events, 29–30Annan, Davis and, studies, 211Anon studies, 111Apparent conductivity maps, 265, 267–269Appelo, Parkhurst and, studies, 106–109Applications, geophysical method verification,

209–216Aqueous-phase transport, 112–117, 115Archie studies, 225ART, see Algebraic reconstruction tomography

(ART)Arthur and Markham studies, 28Arthur studies, 28Auger electron spectroscopy (AES), 191AVIRIS, see Advanced Infra-Red Imaging

Spectrometer (AVIRIS)Ayorinde, Chamberlain and, studies, 32

B

Badu-Tweneboah studies, 153Badv, Rowe and, studies, 128–129Badv and Rowe studies, 128Bai and Inyang studies, 26Bai studies, 26, 30, 193Baouchelaghem, Gouvenot and, studies, 124Barbour and Fredlund studies, 117, 126Barbour studies, 117, 126Barrier cap monitoring, 311–312Barrier layers, hydrologic cycle, 74–75Barrier verification, see Subsurface barrier

verificationBasin lysimeter, 295Battelle studies, 98, 173Bayesian method, 54, 60Bayes studies, 54Bear and Verruijt studies, 91Bear studies, 112Bedford and Stern studies, 224Benchmarking, 87–88Bench-scale tests, 144, 147Benner studies, 93, 98Benoit studies, 32Benson, Albrecht and, studies, 89, 160


Benson, Albright and, studies, 157, 159–160, 163

Benson, Lee and, studies, 193Benson, Tachavises and, studies, 193Benson studies, 32, 143–201Bernabe studies, 26Berti studies, 287nBethke studies, 105, 107–108Betsill and Gruebel studies, 288Bilbrey and Shafer studies, 187Binley, Slater and, studies, 215, 241–243Biological processes, 24–29, 25, 29Blackmore and Miller studies, 35Blowes and Mayer studies, 327Blowes studies, 143–143n, 168, 188, 191, 327Bodo Canyon site, Colorado, 331Bogardi studies, 24Bohn studies, 129Bolen studies, 163Bond, Marcus and, studies, 322Bongi studies, 236Booker, Rowe and, studies, 116, 122–123Borns studies, 287–349Born studies, 287–349Bostick studies, 93Boundary conditions, 115, 115–117Bowerman and Redente studies, 29Bowman studies, 93Brace and Orange studies, 226Bradley and Chapelle studies, 100Bray, Merry and, studies, 26Breckenridge, Piet and, studies, 14Bresler studies, 117, 126Britton studies, 131Brookhaven National Laboratory, 255, 338, 341

C

Cadwell studies, 15Calibration, 88–89Calvin, Vaughan and, studies, 277Canadian Forces Base, Borden (Ontario,

Canada), 95, 330Canadian Radarsat, 237Capillary break layers, 74Caps, material performance factors

basics, 153–155, 154–155composite barriers, 155–160, 156, 158–159hydraulic considerations, 165vegetation and materials relationship, 163,

165–167, 166–167water balance designs, 153, 160–163,

161–162, 164–165

Caps and coversaerial photography, 272–273apparent conductivity maps, 265, 267–269calibration, 88–89caps, 72–90case histories, 263–274code quality assurance, 87–88current practice, 75, 76–80, 81–85data needs, 86–87design verification, 262–263electromagnetic interference, 263–267,

264–265electromagnetic radar, 269–271, 270, 272FEHM, 85geophysical method verification, 261–274GPR, 263–267, 264–265HELP model, 81heterogeneities, role, 90HIS imagery, 274hydrologic cycle, 72, 73HYDRUS-2D, 83infiltration, arid sites, 90layers and features, 74–75limitations, 86–89long term effectiveness, 12material stability and applications, 153–166,

154–155moisture content, 269–271, 270, 272monitoring, 262–263multi-spectral scanners, 273performance issues, 72–75PRBs, 72–90quality control, 87–88RAECOM, 85requirements, 262–263research needs, 86–89role, 86site characterization, 262–263SoilCover, 82–83thermal scanners, 273–274time-varying properties and processes,

89–90TOUGH2, 84–85unresolved challenges, 89–90UNSAT-H, 82VADOSE-W, 84validation and verification, 88–89water balance method, 75, 81

Carlson, Hearst and, studies, 338Carmichael studies, 239Carson studies, 143nCase histories

caps and covers, 263–274colloidal silica demonstration, 341–343

Index 359

Environmental Restoration Disposal Facility, 343, 343–346

Fernald on-site disposal facility, 315, 315–318, 317

geophysical method verification, 243–246mixed waste landfill, 312–315subsurface monitoring, 329vertical barriers, 254–261

Cement-bentonite (CB) cutoff walls, 193Centralizers, 173Cepic and Mavako studies, 42CERCLA, see Comprehensive Environmental

Response, Compensation, and Liability Act (CERCLA)

Chamberlain and Ayorinde studies, 32Chamberlain and Gow studies, 24Chamberlain studies, 287nChanzy studies, 262Chapelle, Bradley and, studies, 100Characterization, geophysical method

verification, 210–211, 212, 214–216Characterization, Monitoring, and Sensors

Technology (CMST) program, 301Charbeneau and Daniel studies, 129Charbeneau studies, 112Chemical additives, 146–147Chemico-osmotic efficiency, 127Chen studies, 24, 201, 224Cherry, Pankow and, studies, 112Chien studies, 71nChu studies, 278Clarke studies, 1nClark studies, 62, 160Clay soils, membrane behavior, 126–127, 127Clement studies, 187CMST, see Characterization, Monitoring, and

Sensors Technology (CMST) programCoa and Greenhalgh studies, 223Code development, geophysical method

verification, 276Code quality assurance, 87–88Colloidal silica, 341–343, 342Colorado subalpine forest, 27Compliance, 22, 37–42, 39–41Complicating factors

anions, 129–131, 131complexation, 131complicating factors, 128–132constant seepage velocity, 128constant volumetric water content, 128–129effective porosity, 129nonlinear sorption, 129–130organic contaminant biodegradation,

131–132

rate-dependent sorption, 130seepage, 128temperature effects, 132volumetric water content, 128–129

Component failurecontaminant containment, 53–54probability, 22–23, 34, 44–47, 45–46

Composite barriers, 155–160, 156, 158–159Comprehensive Environmental Response,

Compensation, and Liability Act (CERCLA), 288

Conca and Wright studies, 128Containment, long-term performance, 347–348Containment region adequacy, 347Contaminant release source term, 37–42, 39–41,

55Contaminants

concentration reduction, 99organic, biodegradation, 131–132transport processes, 112–123

Contingency plans, 91Cook and Kilty studies, 262Cook and Walker studies, 268Corey studies, 112Corser and Cranston studies, 160Costs, subsurface barrier verification, 309Coupled solute transport, 117–119, 120,

125–126Covers, 11, 310–320, see also Caps and coversCox, Daley and, studies, 222Cox studies, 104Crampin studies, 223Cranston, Corser and, studies, 160Cross-hole GPR investigations

geophysical method verification, 245–246, 247–248

vertical barriers, 255, 257–258, 257–259Cross-well imaging, 222–224Cultural preferences, 6Cumbest studies, 209nCurrent practices

caps, 75, 76–80, 81–85covers, 310–312PRBs, 325–329transitioning, 297–309walls and floors, 111–112, 337–340

Cutoff walls, material stability and applicationsbasics, 191–193, 192design configuration, 196–198, 197–198geosynthetics, 198–199, 200hydraulic considerations, 193–195,

194–196material property ranges, 192permeant interaction effects, 199–201, 201


in situ hydraulic conductivity, 193–195, 194–196

vertical cutoff walls, 198–199, 200Cyclical stressing mechanisms, 32, 34, 34–37,

36, 38

D

Dailey and Ramirez studies, 213, 226, 260Daily studies, 241Daley and Cox studies, 222Daley studies, 220, 222Damage and system performance prediction

analytical framework, 8–10, 8–11basics, xiv–xv, 1–7, 2–4, 7biological processes, 24–29, 25, 29compliance, 22, 37–42, 39–41component failure, 22–23, 34, 44–47,

45–46, 53–54contaminant release sources, 37–42, 39–41cyclical stressing mechanisms, 32, 34,

34–37, 36, 38degradation mechanism categories, 24–37economic criteria, 18empirical prediction approach, 11–12,

11–12estimation, long-term failure probabilities,

42–53event consequences and connectivities, 42event trees, 42, 44failures, 42–53fault trees, 42, 43indexing analysis, 21, 23–24intrusive events, 29–30less empirical (theoretical) modeling

approach, 14–15life cycle approach, 61–62, 62long-term performance analysis, 7–15maintenance, 59–61mixed criteria, 23, 23modeling, 59–61monitoring, 59–61multi-dimensional case, 51–53, 52–53performance prediction approaches, 11–15prescriptive design criteria, 19–20pseudo-economic criteria, 18qualitative analysis, 21, 21, 23–24quantification, long-term issues, 24–58random resistance, 45, 47–48, 48regulatory criteria, 19, 19relationship, containment concentrations

and risks, 54–58, 55–56, 58

risk assessment, 37–42, 39–41, 54–58, 55–56, 58

risk criteria, 20–22, 21–22semi-empirical prediction approach, 12–14simplifications of theory, 48–51slow physico-chemical processes, 24–29,

25, 29structure-functional failure relationship,

15–24, 17–18system failure, 22, 43–44, 53–54system management, updating, 60–61, 61theory simplifications, 51transient events, 30, 31, 32, 33–34updating, 59–61, 60–61

Damage models, improvement needs, 5–6Daneshjoo and Hushmand studies, 30Daniel, Charbeneau and, studies, 129Daniel, Estornell and, studies, 152Daniel, Koerner and, studies, 152, 155Daniels studies, 24, 34Daniel studies, 143D' Appolonia studies, 145Darcy's Law and properties, 82, 119, 186Dasgupta studies, 18Dasog studies, 35Data needs, 86–87, 319Data streams, 238Davidson, Schaff and, studies, 35Davis and Annan studies, 211Davis studies, 209nDay, Ryan and, studies, 145DCM, see Dichloromethane (DCM)Decision analysis, 2, 299, 299–300De Flaun studies, 249Degradation mechanism categories, 24–37Dehalococcoides ethenogenes, 100Deming studies, 143nDense nonaqueous phase liquid (DNAPL) sites,

305De Paoli studies, 124Department of Defense, see U.S. Department of

Defense (USDOD)Design configuration, cutoff walls, 196–198,

197–198Design verification

caps and covers, 262–263geophysical method verification, 239,

241–244, 244–246vertical barriers, 249–250, 250–253, 252,

254Desorption curve, 102DiBenedetto studies, 236Dichloromethane (DCM), 100, 103–104Direct push technologies, 305, 306

Index 361

Dissolved organic carbon, 100–101Dobson studies, 238DOD, see U.S. Department of Defense

(USDOD)DOE, see U.S. Department of Energy (DOE)Doll studies, 209n, 211, 228, 262Donnegan and Rebertus studies, 27Dover Air Force Base, 255Downgradient biodegradation processes,

98–101Du and Rummel studies, 262, 266DuPont, 321DuPont site, East Chicago (Indiana), 171Durability

geosynthetics, 149–153PRBs, material performance factors, 183,

184–185, 185–187Dwyer studies, 111, 143–201Dzombak, Roy and, studies, 57

E

East Chicago (Indiana), 171Economic criteria, structure-functional failure

relationship, 18Eddy-Dilek studies, 287–349EDXA, see Energy dispersive x-ray analysis

(EDXA)Einarsson and Rausand studies, 24Elachi studies, 233Elder studies, 173–174, 176, 187Electrical and electromagnetic methods,

214–215, 224–227Electrical imaging, case study, 243–244,

244–246Electrical resistivity tomography (ERT), 260,

260–261, 293–294Electromagnetic induction (EMI), 262–267,

264–265, 293Electromagnetic radar, 269–271, 270, 272Electromagnetic surveys, dates, 264Electron donor production, 100Elias studies, 24, 26Elizabeth City, North Carolina, 97, 108, 329Ellis studies, 100EMI, see Electromagnetic induction (EMI)Empirical prediction approach, 11–12, 11–12Endres studies, 215, 241End states, 309–310Energy dispersive x-ray analysis (EDXA), 191Energy Science and Technology Software

Center, 85Envelope of resistance, 46

Environmental Management Science Program, 332

Environmental Restoration Disposal Facility, 343, 343–346

Environmental Systems Management, Analysis, and Reporting (E-SMART) network, 304, 304–305

EPA, see U.S. Environmental Protection Agency (USEPA)

ERT, see Electrical resistivity tomography (ERT)

E-SMART network, 304, 304–305Estimation, long-term failure probabilities

basics, 42–43component failure, 22–23, 34, 44–47, 45–46multi-dimensional case, 51–53, 52–53quantification, long-term issues, 42–53random resistance, 45, 47–48, 48simplification of theory, 48–51, 51system failure, 22, 43–44

Estornell and Daniel studies, 152European Resources Satellite (ERS-1.ERS-2),

237Evaluation

materials, 147–149, 152performance factors, 16PRBs, material performance factors,

170–172, 171–173Evans studies, 143n, 193Evapo-transpiration, 81, 90Event consequences and connectivities, 42Event trees, 42, 44Everett, Lorne G., 288Everett and Fogwell studies, 300, 310, 344–346Everett studies, 287–349Exposures, 7, 56, 58Eykholt studies, 173, 331

F

Failures, quantification, 42–53Falta, Looney and, studies, 292, 294Farrell studies, 186Fault trees, 42, 43Federal Energy Technology Center, 273FEHM, see Finite element heat and mass

(FEHM)FEMP, see Fernald Environmental Management

Project (FEMP)Fennelly and Roberts studies, 100Fenn studies, 81, 86Fernald Environmental Management Project

(FEMP), 315


Fernald on-site disposal facility, 315, 315–318, 317

Fernandez and Quigley studies, 24Ferrell studies, 94Fiber-optic cable, monitoring, 294Fiber optics distributed temperature moisture

monitoring, 314Fick's Law, 82Fiedor studies, 97Field Lysimeter Test Facility (FLTF), 308Field performance, see Performance and

performance factorsFinite element heat and mass (FEHM), 85Finsterwalder and Spirres studies, 124First-order second moment (FOSM) method,

50, 52Fleming and Inyang studies, 24, 147Floors, 110–127, see also Walls and floorsFlow characterization and monitoring, 325,

326–327, 330–331Flow charts, 2, 40FLTF, see Field Lysimeter Test Facility (FLTF)Fluor Hanford (Richland, Washington), 308Fogwell, Everett and, studies, 300, 310,

344–346Fogwell studies, 287nFoose studies, 120, 123Forrester studies, 14FOSM, see First-order second moment (FOSM)

methodFouling model, 189Fourier's Law, 82Fox, Gupta and, studies, 298–299, 330Fraser, Rowe and, studies, 57Fratalocchi studies, 124–125Fredlund, Barbour and, studies, 117, 126Fredlund and Xing studies, 87Freedman and Gossett studies, 100Freight Yard, Copenhagen (Denmark), 330Fritz and Marine studies, 117Fritz studies, 118Fruchter studies, 93Fryar and Schwartz studies, 327Fused sensor systems, 238Future developments, 276–278

G

Gallegos studies, 38Gasperikova studies, 228Gavaskar studies, 143, 242GCL (geosynthetic clay liner), see

Geosynthetics

Gee, Meyer and, studies, 20Gee, Ward and, studies, 160, 263Gee and Ward studies, 15Gee studies, 143n, 165Geller, Majer and, studies, 220Geller and Myer studies, 220Geller studies, 220, 249Geochemical processes

modeling, 92–97, 94–96, 104–109monitoring, 331

Geomembrane vertical walls, installation, 200Geophysical method verification

advancement needs, 275–276aerial photography, 232, 272–273airborne methods, 228–229, 229–231, 231apparent conductivity maps, 265, 267–269applications, 209–216basics, xv, 274–278caps and covers, 261–274case histories, 243–246, 254–261, 263–274characterization, 210–211, 212, 214–216code development, 276cross-hole GPR investigations, 245–246,

247–248, 255, 257–258, 257–259cross-well imaging, 222–224data streams, 238design verification, 239, 241–244, 244–246,

249–250, 250–253, 252, 254, 262–263electrical and electromagnetic methods,

214–215, 224–227electrical imaging, case study, 243–244,

244–246electromagnetic interference, 263–267,

264–265electromagnetic radar, 269–271, 270, 272ERT systems, 260, 260–261fused sensor systems, 238future developments, 276–278geophysics, 210–214, 212–213GPR, 263–267, 264–265guided/channel waves, 221HIS imagery, 274hyperspectral imaging sensors, 234, 234–235instrumentation, 276integration, 275laser-induced fluorescence, 236–237LIDAR systems, 235–236moisture content, 269–271, 270, 272monitoring, 239, 240, 242–243, 249, 254,

262–263multi-spectral scanners, 232–233, 273natural field and magnetic methods,

215–216, 227–228performance monitoring, 212–214, 213

Index 363

PRBs, 239–246, 240radar systems, 237–238, 238ray tomography, 220–221reflected energy, 221remote sensing, 216, 231–238requirements, 239, 249, 262–263scattered energy, 221seismic methods, 214, 216–224, 218–219,

259single well imaging, 222–224site characterization, 214–216, 239–241,

249, 262–263specific methods, 216–238thermal scanners, 233, 273–274tomography, 220–221vertical barriers, 246–261VSP imaging, 222–224wave tomography, 220–221

Geophysics, 210–214, 212–213Geosynthetics

clay liners, 152, 156–159degradation, 26durability, 149–153vertical cutoff walls, 198–199, 200

Gibbs free energy, 99Gilbert, Liu and, studies, 24Gilbert and Tang studies, 24Gillham, O' Hannesin and, studies, 95Gillham and O' Hannesin studies, 93, 167, 321Gillham studies, 98, 186Giroud studies, 26, 120, 151Gladden studies, 1nGoals, subsurface barrier verification, 288, 289Gossett, Freedman and, studies, 100Goubau studies, 227Goulas studies, 236Gouvenot and Bouchelaghem studies, 124Gow, Chamberlain and, studies, 24Granular iron PRBs, 184–185Greaves studies, 265Greenberg studies, 117Greenhalgh, Cao and, studies, 223Grote studies, 211, 213, 227Ground surface layer, hydrologic cycle, 74Groundwater chemistry, 95Groundwater hydraulics, PRBs, 91–92Gruebel, Betsill and, studies, 288Guar, 101Guglielmetti, Koerner and, studies, 199Guided/channel waves, 221Gunter studies, 107Gupta and Fox studies, 298–299, 330Gupta studies, 327Gu studies, 97, 99–100, 221, 327

H

Hagemeister studies, 12Haider, Acar and, studies, 122Hampton, Anderson and, studies, 224Hanford Central Plateau, 308Hanford (DOE site), Washington

barrier monitoring, case history, 343direct push technologies, 305electromagnetic surveys, dates, 264EMI/GPR relationship, 263installation/verification, 250, 252–253intrusive events, 29–30vegetation, 165water balance designs, 160, 161–162

Harbaugh, McDonald and, studies, 119Hardware, verification needs, 320, 320–323Harrison Air Force Base (Indiana), 305Harris studies, 222Hartley studies, 24Hathorn studies, 57Haxo studies, 152Hayes adn Marcus studies, 93Hazard inventory, 6–7Hazardous materials, 3–4, 146–147Hearst and Carlson studies, 338Heiser studies, 287nHELP, see Hydrologic evaluation of landfill

performance (HELP)Hendrickx, Sheets and, studies, 211, 263, 267Hendrickx studies, 211, 262–263, 268Henyey, Leary and, studies, 211, 223Heterogeneities, role, 90HIS imagery, 27, 274, 277Historical developments, xiii–xivHo and Lohrstorfer studies, 309Hood studies, 6Ho and Webb studies, 84Horizontal barriers, PRBs, 110–111Ho studies, 16, 20, 28–29, 71nHsuan and Koerner studies, 160Hubbard and Rubin studies, 227Hubbard studies, 209n, 211, 217, 220, 224, 241,

262, 295Huisman studies, 262–263, 266Hushmand, Daneshjoo and, studies, 30Hydraulic considerations

caps, material performance factors, 165conductivity, 240–241cutoff walls, material stability and

applications, 193–195, 194–196heterogeneous aquifer model, 190mineral precipitation effect, 185–186reactive material performance, 172–178,

174–175, 177, 179–182


samples summary, 165time-varying properties and processes, 125

Hydraulic head gradient, 122Hydrogen, 99–100Hydrological process monitoring, 331Hydrologic cycle, 72, 73Hydrologic evaluation of landfill performance

(HELP)calibration, 89caps, 81data needs, 86–87risk criteria, 20water flow through barriers, modeling, 119

Hydrology, site, 91HYDRUS-2D, 83, 87Hyperspectral imaging sensors, 234, 234–235

I

Idaho National Engineering and Environmental Laboratory (INEEL)

cover verification needs, 318guided/channel waves, 221intrusive events, 29–30less empirical modeling approach, 14Long-Term Stewardship Science and Map,

309–310Vadose Zone Science and Technology

Roadmap, 292IFSAR technology, 277–278Implementation drivers, 309–310Indexing analysis, 21, 23–24Infiltration, 90, 313Input parameters, 123–125In situ hydraulic conductivity, 193–195,

194–196Inspection time point, 61Installation, vertical barriers, 249–250,

250–253, 252, 254Instrumentation, geophysical method

verification, 276Integration, geophysical method verification,

275International Containment Technology

Workshop, 321Interstate Technology Regulatory Council

(ITRC), 169Intrusive events, 29–30Inverse modeling, 108–109Inyang, Bai and, studies, 26Inyang, Fleming and, studies, 24, 147Inyang, Reddi and, studies, 54, 143Inyang and Tomassoni studies, 12

Inyang studies, 1–62, 143n, 145, 191Ito studies, 224ITRC, see Interstate Technology Regulatory

Council (ITRC)

J

Japanese Earth Resources Satellite (JERS), 237Jayawickrama and Lytton studies, 26Jayawickrama studies, 1nJefferis studies, 125, 143n, 193, 200Jensen studies, 232JERS, see Japanese Earth Resources Satellite

(JERS)Jessbeger studies, 124Joesten studies, 241–242, 245Johnson, Korneev and, studies, 221Johnson, Tura and, studies, 220–221Johnson and Tratnyek studies, 327Johnson studies, 1nJones studies, 287n

K

Kachanoski studies, 262–263Kachanov studies, 35Kansas City (DOE facility), Missouri, 173–174,

241, 243Katzmann studies, 111Kauschinger studies, 110Kavazanjian and Matasovic studies, 30Keijzer studies, 117, 126Kelch studies, 274Keller, Kram and, studies, 305Kemper and Quirk studies, 117Kemper and Rollins studies, 117, 126–127Khalil and Moraes studies, 35, 37Khandelwal, Rabideau and, studies, 111, 114,

116–117, 121–122, 130Khandelwal studies, 130Khire studies, 160Kiefer, Lillesand and, studies, 233–234Kilty, Cook and, studies, 262Kirtland Air Force Base (New Mexico), 305Klimentos and McCann studies, 224Köber studies, 187Koerner, Hsuan and, studies, 160Koerner, Lord and, studies, 26Koerner and Daniel studies, 152, 155Koerner and Guglielmetti studies, 199Korb studies, 277Korneev and Johnson studies, 221

Index 365

Korte studies, 93Koutsandreas studies, 209n, 287–349Kozak studies, 37Kram and Keller studies, 305Kram studies, 305Krohn studies, 211, 221Kroto, Sir Harold, 307K-25 site, Oak Ridge National Laboratory, 236,

273Kumthekar studies, 316–317Kuster and Tokoz studies, 223

L

LaGrega studies, 143Lake and Rowe studies, 26Landis studies, 71nLand use analysis, safety targets, 19Lanier studies, 71nLANL, see Los Alamos National Laboratory

(LANL)Laplace transforms, 122–123Laser-induced fluorescence imaging (LIFI),

236–237Lasse studies, 173Layard studies, 18Layers and features, 74–75LEA, see Local equilibrium assumption (LEA)Leary and Henyey studies, 211, 223Lee, Miller and, studies, 32Lee and Benson studies, 193Lesmes studies, 209nLess empirical (theoretical) modeling approach,

14–15Liang studies, 327LIDAR systems, 233, 235–236, 277LIF, see Laser-induced fluorescence imaging

(LIFI)Life cycle approach, 61–62, 62Lillesand and Kiefer studies, 233–234Limitations, modeling

caps, 86–89PRBs, 109–110walls and floors, 123–127

Lim studies, 128Lindgren studies, 287nLinear least squares spectral analysis (LLSSA),

35–36Liners, 11, see also Caps and coversLink studies, 15Li studies, 188Liu and Gilbert studies, 24Liu studies, 221

LLSSA, see Linear least squares spectral analysis (LLSSA)

Local equilibrium assumption (LEA), 130Lockhart and Roberds studies, 298–299Lohrstorfer, Ho and, studies, 309Long-Term Monitoring Sensor and Analytical

Methods Workshop, 301Long-term performance, see also Performance

and performance factorsdamage and system performance prediction,

7–15estimation necessity, 2processes and parameters interaction, 8quantitative methods, 2, 4–5subsurface barrier verification, 347–348

Long-term post-closure radiation monitoring systems (LPRMS), 302–303, 302–304

Looney and Falta studies, 292, 294Lord and Koerner studies, 26Los Alamos National Laboratory (LANL),

273–274, 295Low permeability walls, design, 120Lowry v, 287nLPRMS, see Long-term post-closure radiation

monitoring systems (LPRMS)Lytton, Jayawickrama and, studies, 26

M

Mackenzie studies, 185Mackey studies, 274Maintenance, damage and system performance

prediction, 59–61Majer and Gellar studies, 220Majer studies, 209–278Malone studies, 57Malusis and Shackelford studies, 117–119, 127Malusis studies, 71n, 117, 127Manassero and Shackelford studies, 122Manassero studies, 71n, 124–125, 130Marcus, Hayes and, studies, 93Marcus and Bond studies, 322Marine, Fritz and, studies, 117Marion studies, 224Markham, Arthur and, studies, 28Maryland, 229, 230Mason studies, 222Massachusetts Military Reservation, 241Matasovic, Kavazanjian and, studies, 30Matasovic studies, 30Material and performance relationship, 144,

144–145, 146–151, 147Material stability and applications


basics, xv, 143–144caps, 153–166, 154–155composite barriers, 155–160, 156, 158–159cutoff walls, 191–201, 192design configuration, 196–198, 197–198durability, 149–153, 183, 184–185, 185–187evaluation, 147–149, 152, 170–172,

171–173geosynthetics, 149–153, 198–199, 200hydraulic considerations, 165, 172–178,

174–175, 177, 179–182, 185–186, 193–195, 194–196

material and performance relationship, 144, 144–145, 146–151, 147

mineral precipitation effect, 185–187performance and material relationship, 144,

144–145, 146–151, 147permeant interaction effects, 199–201, 201pilot testing, 170–172, 171–173porosity, 185–186PRBs, 167–191, 168–169reaction tracking, 179, 187–191, 189–191reactivity, 186–187selection, 147–149, 152, 168–170in situ hydraulic conductivity, 193–195,

194–196structural stability factors, 178, 182,

182–183vegetation relationship, 163, 165–167,

166–167vertical cutoff walls, 198–199, 200water balance designs, 153, 160–163,

161–162, 164–165Mather, Thornthwaite and, studies, 81, 86Matsumoto studies, 143nMavko, Cepic and, studies, 42Mayer, Blowes and, studies, 327Mayer studies, 97, 108, 187–188Maymo-Gatell studies, 99Mazurek studies, 57McCann, Klimentos and, studies, 224McCurdy studies, 57McDonald adn Harbaugh studies, 119McIntire studies, 239McKenzie, Orth and, studies, 93Measurement accuracy, walls and floors,

123–125Measures studies, 236Melchers, Stewart and, studies, 6, 18, 23, 43–45,

47Melchers studies, 1n, 45, 48, 51, 53–54Melchior studies, 158, 160Membrane behavior, clay soils, 126–127, 127Menezes studies, 143n

Mercer studies, 1nMergener studies, 187–188, 189Merry and Bray studies, 26Methane concentration, 38Meyer and Gee studies, 20Meyer and Orr studies, 20Meyer and Taira studies, 20Meyer studies, 105Miller, Blackmore and, studies, 35Miller and Lee studies, 32Milne-Home and Schwartz studies, 145Mineral precipitation effect, 185–187Minerals, 146–147Miner studies, 223Misawa Air Base (Japan), 305Mitchell, Rumer and, studies, 143, 322, 347Mitchell studies, 117, 124, 126–127Mixed criteria, 23, 23Mixed waste landfill, 312–315Mochizuki studies, 224Modeling, fluid transport through barriers

anaerobic biodegradation, 98–99analytical models, 115, 120, 120–123, 123anions, 129–131, 131aqueous-phase transport, 112–117, 115basics, xv, 71calibration, 88–89caps, 72–90clay soils, membrane behavior, 126–127,

127code quality assurance, 87–88complexation, 131complicating factors, 128–132constant seepage velocity, 128constant volumetric water content, 128–129contaminants, 99, 112–123coupled solute transport, 117–119, 120,

125–126current practice, 75, 76–80, 81–85, 111–112data needs, 86–87dissolved organic carbon, 100–101downgradient biodegradation processes,

98–101effective porosity, 129electron donor production, 100FEHM, 85floors, 110–127geochemical processes and modeling,

92–97, 94–96, 104–109groundwater hydraulics, 91–92HELP model, 81heterogeneities, role, 90horizontal barriers, 110–111hydrogen, 99–100

Index 367

hydrologic cycle, 72, 73HYDRUS-2D, 83infiltration, arid sites, 90input parameters, 123–125inverse modeling, 108–109layers and features, 74–75limitations, 86–89, 109–110, 123–127measurement accuracy, 123–125membrane behavior, clay soils, 126–127,

127nonlinear sorption, 129–130organic contaminant biodegradation,

131–132performance issues, 72–75PRBS, 90–110quality control, 87–88RAECOM, 85rate-dependent sorption, 130reactions, 98, 106–107reactive transport modeling, 107–108reduction, contaminant concentration, 99research needs, 86–89, 109–110, 123–127role, 86seepage, 128SoilCover, 82–83speciation modeling, 105–106system dynamics, 101–104, 102–103temperature effects, 132time-varying properties and processes,

89–90, 125TOUGH2, 84–85transport process, contaminants, 112–123unresolved challenges, 89–90UNSAT-H, 82VADOSE-W, 84validation and verification, 88–89vertical barriers, 110volumetric water content, 128–129walls, 110–127water balance method, 75, 81water flow modeling, 119–120

Modeling limitationscaps, 86–89PRBs, 109–110walls and floors, 123–127

Models and modelinganalytical, 115, 120, 120–123, 123current practices, 75, 76–80, 81–85,

111–112damage and system performance prediction,

59–61fouling model, 189geochemical models, reaction tracking, 179,

187–191, 189–191

inverse modeling, 108–109subsurface barrier verification, 298, 299

MODFLOW, 119, 188Moffet Field, see Naval Air Station (NAS)

Moffet Field, Mountain View (California)Mohamed studies, 32Moisture content

caps and covers, 269–271, 270, 272change monitoring methods, 292–294fiber-optics distributed temperature

monitoring, 314neutron moisture monitoring, 313–315sampling methods, 294–295shallow vadose zones, monitoring, 314–315subsurface barrier verification, 292–295

Monitoring, see also Geophysical method verification; Material stability and applications

basics, 2caps and covers, 262–263, 313damage and system performance prediction,

59–61fiber-optics distributed temperature

monitoring, 314geophysical method verification, 239, 240,

242–243, 249infiltration monitoring, covers, 313moisture change, 292–294neutron moisture, 313–314perfluorocarbon tracers, 338–340, 339shallow vadose zones, 314–315verification monitoring, 289, 290–292,

291–296vertical barriers, 254

Monterey, California, 159–160Monticello Mill Tailings Repository (Utah),

17–18, 20, 176, 177, 179–182Moore studies, 20, 287nMoo-Young, Jr., studies, 287nMoo-Young and Zimmie studies, 26Moo-Young studies, 1nMoraes, Khalil and, studies, 35, 37Morrison, H.F., studies, 209nMorrison, S.J., studies, 143nMorrison studies, 177, 188, 298, 321, 331Mountain View, California, 106–107, 109, 185Moya studies, 236Muftikian studies, 93Muller-Kirchenbauer studies, 124Multi-dimensional case, 51–53, 52–53Multi-spectral scanners, 232–233, 273Murray and Quirk studies, 201Myer, Geller and, studies, 220


N

Naftz studies, 143Nagel, Smith and, studies, 307Nanotechnology sensors, 307NAS, see Naval Air Station (NAS) Moffet Field,

Mountain View (California)NASA, 232NASA Jet Propulsion Laboratory, 234NASA/Stennis co-sponsored project, 232Nataf transform, 51National Aeronautics and Space Administration

(NASA), 232National Department of Energy Vadose Zone

Science and Technology Roadmap, 292National Research Council

airborne geophysical methods, 228aqueous-phase transport, 113life-cycle decisions, 61sensor and field analytical techniques,

333–336sensors for fielded systems, 348

Natural attentuation, 290–291Natural field and magnetic methods, 215–216,

227–228Naval Air Station (NAS) Moffet Field,

Mountain View (California), 106–107, 109, 185, 234, 327

Nazarali studies, 37Neutron moisture monitoring, 313–314Neutron probes, 293Neutron well logging, 337–338Newman studies, 71nNibras, Park and, studies, 131Nichols studies, 227Nihei studies, 221Noonan studies, 236NRC, see U.S. Nuclear Regulatory Commission

(USNRC)Nyhan studies, 28

O

Oak Ridge, TennesseeK-25 site, 236, 273successional sequences, timing, 27TOUGH2 source code, 85Y-12 plant, 95, 96, 183, 327

Oak Ridge Airborne Geophysical System-Arrowhead (ORAGS-Arrowhead), 228–229, 229

Oak Ridge Airborne Geophysical System-Hammerhead (ORAGS-Hammerhead), 229

Oak Ridge Airborne Geophysical System-Transient Electrical Methods (ORAGS-TEM), 229–231, 230–231

Oak Ridge National Laboratory (ORNL), 229, 236, 238

Office of Emergency and Remedial Response, 288

Office of Scientific and Technical Information (OSTI), 85

O' Hannesin, Gillham and, studies, 93O' Hannesin and Gillham, studies, 167, 321Olhoeft studies, 243Olsen studies, 117, 126OPFTIR technology, 278Optimization, verification needs, 299, 319–320Orange, Brace and, studies, 226ORNL, see Oak Ridge National Laboratory

(ORNL)Orr, Meyer and, studies, 20Orth and McKenzie studies, 93OS3D models, 187OSTI, see Office of Scientific and Technical

Information (OSTI)Othman studies, 152Oyster (DOE facility), Virginia, 249

P

Pacific Northwest National Laboratory, 82, 308Pankow and Cherry studies, 112Park and Nibras studies, 131Parker studies, 71–132Parkhurst and Appelo studies, 106–109Parkin, Adamson and, studies, 99Park studies, 131Parra studies, 211, 224Paschle and van der Heijde studies, 105Peclet number, 121Pellerin studies, 255, 260Pelton studies, 243Penman-Wilson formulation, 82, 84Percolation, 72, 73, 159–160, 163, 164Perfluorocarbon tracers, 338–340, 339Performance and performance factors

caps, 72–75composite barriers, 155–160, 156, 158–159containment, long-term, 347–348cutoff walls, 191–201, 192geophysical method verification, 212–214,

213

Index 369

hydraulic considerations, 165, 172–178, 174–175, 177, 179–182

long-term performance analysis, 7–15materials and mix composition, 144,

144–145, 146–151, 147pilot testing, evaluation, 170–172, 171–173PRBs, 167–194, 168–169prediction approaches, 11–15reactive materials, 165, 172–178, 174–175,

177, 179–182structural stability, 178, 182, 182–183vegetation and material relationship, 163,

165–167, 166–167water balance designs, 155, 160–163,

161–162, 164–165Permeable reactive barriers (PRBs)

acoustic wave devices, 331, 331–332anaerobic biodegradation, 98–99basics, 90–91, 321–324caps, 72–90case histories, 329contaminants, 99current practices, 325–329design verification, 239, 241–242dissolved organic carbon, 100–101downgradient biodegradation processes,

98–101electron donor production, 100floors, 110–127flow characterization and monitoring, 325,

326–327, 330–331geochemical processes and modeling,

92–97, 94–96, 104–109geochemical process monitoring, 331geophysical method verification, 239–246,

240groundwater hydraulics, 91–92horizontal barriers, 110–111hydrogen, 99–100hydrological process monitoring, 331improvements needed, 325–329inverse modeling, 108–109limitations, 109–110material stability and applications, 167–191,

168–169monitoring, 239, 240, 242–243reactions, 98, 106–107reactive transport modeling, 107–108reduction, contaminant concentration, 99regulatory framework, 324–325requirements, 239research needs, 109–110site characterization, 239–241spatial flow monitoring, 330–331

speciation modeling, 105–106subsurface barrier verification, 321–332subsurface monitoring, 329system dynamics, 101–104, 102–103temporal flow monitoring, 330–331time-varying properties and processes,

89–90unresolved challenges, 89–90verification, 327–332, 328, 330vertical barriers, 110walls, 110–127

Permeable reactive barriers (PRBs), material performance factors

basics, 167–168, 168–169durability, 183, 184–185, 185–187evaluation, 170–172, 171–173hydraulic considerations, 172–178,

174–175, 177, 179–182, 185–186mineral precipitation effect, 185–187pilot testing, 170–172, 171–173porosity, 185–186reaction tracking, 179, 187–191, 189–191reactivity, 186–187selection, 168–170structural stability factors, 178, 182,

182–183vegetation relationship, 165–167, 166–167

Permeant interaction effects, cutoff walls, 199–201, 201

PET, see Potential evapo-transpiration (PET)Peterson studies, 211, 222Petrov studies, 152Peyton and Schroeder studies, 81, 86–87Phillips studies, 95, 97, 183, 188Piet and Breckenridge studies, 14Piet studies, 1–62Pilot testing, 170–172, 171–173Plummer studies, 109POC, see Point of compliance (POC)POE, see Point of exposure (POE)Point of compliance (POC), 98, 111–112Point of exposure (POE), 111–112Political processes, 6Polosa studies, 273Porosity, 185–186, 190Porter studies, 128Potential evapo-transpiration (PET), 81Pratt studies, 191PRBs, see Permeable reactive barriers (PRBs)Precipitated minerals, 94Prediction, see Damage and system

performance prediction; Modeling, fluid transport through barriers

Prediction links, 298, 299


Prescriptive design criteria, 19–20Probabilistic risk analysis (PRA), 41–42Pruess studies, 84Pseudo-economic criteria, 18Psychological aspects, 6Puls studies, 71n, 95, 97, 188, 324, 327, 329Pyrak-Nolte studies, 223

Q

Qualitative analysis, structure-functional failure relationship, 21, 23–24

Quality control, caps, 87–88Quantification, long-term issues

biological processes, 24–29, 25, 29compliance, 37–42, 39–41component failure, 34, 44–47, 45–46, 53–54contaminant release sources, 37–42, 39–41cyclical stressing mechanisms, 32, 34,

34–37, 36, 38damage and system performance prediction,

24–58degradation mechanism categories, 24–37estimation, long-term failure probabilities,

42–53event consequences and connectivities, 42event trees, 42, 44failures, 42–53fault trees, 42, 43intrusive events, 29–30multi-dimensional case, 51–53, 52–53random resistance, 45, 47–48, 48relationship, containment concentrations

and risks, 54–58, 55–56, 58risk assessment, 37–42, 39–41, 54–58,

55–56, 58simplifications of theory, 48–51slow physico-chemical processes, 24–29,

25, 29system failure, 43–44, 53–54theory simplifications, 51transient events, 30, 31, 32, 33–34

Quantified risk analysis (QRA), 39, 41Quigley, Fernandez and, studies, 24Quirk, Kemper and, studies, 117Quirk, Murray and, studies, 201

R

Rabideau, Rubin and, studies, 121Rabideau and Khandelwal studies, 111, 114,

116–117, 121–122, 130

Rabideau and Van Benschoten studies, 93Radar systems, 237–238, 238Radiation attenuation effectiveness and cover

optimization with moisture effects (RAECOM), 85

Radioactive metals, 146–147Rad studies, 152RAECOM, see Radiation attenuation

effectiveness and cover optimization with moisture effects (RAECOM)

Ramirez, Dailey and, studies, 213, 226, 260Ramirez studies, 255Random resistance, 45, 47–48, 48Ranson and Sun studies, 238Ray tomography, 220–221Rausand, Einarsson

and, studies, 24RCRA, see Resource Conservation and

Recovery Act (RCRA)Reactions, 98, 106–107Reaction tracking, 179, 187–191, 189–191Reactive test wells (RTWs), 170–172, 172Reactive transport modeling, 107–108Reactivity

materials, 168–169PRBs, material performance factors,

186–187specific gravity, 182

Reddi and Inyang studies, 54, 143Redente, Bowerman and, studies, 29Redmond, Shackelford and, studies, 130–131Reduction, contaminant concentration, 99Reflected energy, 221Regulatory criteria, 19, 19Regulatory framework, 4, 324–325Relationship, containment concentrations and

risks, 54–58, 55–56, 58Remediation Technologies Development Forum

(RTDF), 93, 324Remote sensing, 216, 231–238Requirements

caps and covers, 262–263geophysical method verification, 239vertical barriers, 249

Research needscaps, 86–89PRBs, 109–110walls and floors, 123–127

Resistance, random, 45, 47–48, 48Resource Conservation and Recovery Act

(RCRA)design criteria, 19–20geosynthetics, 152goals, 288mixed waste landfill case history, 312–313

Index 371

moisture sampling methods, 294site characterization, 91

Richards' equation, 82Rignot studies, 238Risk

contaminant concentrations relationship, 54–58, 55–56, 58

contaminant release source terms, 37–42, 39–41

decision analysis, 2flow chart, 40psychological aspects, 6structure-functional failure relationship,

20–22, 21–22Roberds, Lockhart and, studies, 298–299Roberts, Fennelly and, studies, 100Robertus, Donnegan and, studies, 27Roesler studies, 156, 159–160, 165Rogers studies, 85Roh studies, 95, 183, 298, 331Role, caps, 86Rollins, Kemper and, stuides, 117, 126–127Rosenblatt transform, 51Rouyn-Noranda (Quebec, Canada), 32Rowe, Badv and, studies, 128Rowe, Lake and, studies, 26Rowe and Badv studies, 128–129Rowe and Booker studies, 116, 122–123Rowe and Fraser studies, 57Rowe and Sargam studies, 160Rowell studies, 128Rowe studies, 112, 131–132Roy and Dzombak studies, 57RT3D models, 187–188RTW, see Reactive test wells (RTWs)Rubin, Hubbard and, studies, 227Rubin and Rabideau studies, 121Rumer and Mitchell studies, 143, 322, 347Rummel, Du and, studies, 262, 266Ryan and Day studies, 145

S

Sacramento, California, 165, 166Safety case concept, 22Saleem studies, 131Sanchez studies, 62Sandia National Laboratory, 312Sargam, Rowe and, studies, 160Sass studies, 111, 185, 327Savannah River site, Aiken (South Carolina),

274, 309Scanlon studies, 320

Scattered energy, 221Schackelford, Malusis studies, 127Schackelford and Redmond studies, 130–131Schaff and Davidson studies, 35Schoenberg studies, 223Schroeder, Peyton and, studies, 81, 86–87Schroeder studies, 119Schuhmacher studies, 188Schwartz, Fryar and, studies, 327Schwartz, Milne-Home and, studies, 145Seaman studies, 130Seismic methods

geophysical method verification, 214, 216–224, 218–219

vertical barriers, 259Selection, PRBs, 168–170Semi-empirical prediction approach, 12–14Sensors, verification needs, 320, 320–323Serrato studies, 287nShackelford, Malusis and, studies, 117–119Shackelford studies, 24, 71–132Shackleford, Manassero and, stuides, 122Shackleford studies, 72–132Shafer, Bilbrey and, studies, 187Shakshuki studies, 48Sheets and Hendrickx studies, 211, 263, 267Shi studies, 57Shu studies, 57Side-looking airborne radar (SLAR), 237Simplifications of theory, 48–51SIMS, see Surface ionization mass spectrometry

(SIMS)Simultaneous iterative reconstruction

tomography (SIRT), 221Single well imaging, 222–224SIRT, see Simultaneous iterative reconstruction

tomography (SIRT)Site characterization

adequacy, 91caps and covers, 262–263geophysical method verification, 214–216,

239–241vertical barriers, 249

Site Characterization and Analysis Penetrometer System (SCAPS), 305

Site hydrology, 91Siu studies, 38SLAR, see Side-looking airborne radar (SLAR)Slater and Binley studies, 215, 241–243Slater studies, 209nSleep studies, 71–132Slow physico-chemical processes, 24–29, 25, 29Smart structures, 300–307Smith and Nagel studies, 307


Smith studies, 27, 29Smyre studies, 238, 273–274Social aspects, 6Sodium iodide gamma detector, 295Software, 76–80Soil-cement-bentonite (SCB) cutoff walls,

192–193SoilCover, 82–83Sorel, Warner and, studies, 173Sorption characteristics, 146–147Spanksy studies, 287nSpatial flow monitoring, 330–331SPAWAR, 332Speciation modeling, 105–106Specific methods, geophysical method

verification, 216–238Spirres, Finsterwalder and, studies, 124SPOT satellite imagery, 273Staverman studies, 117Steady-state flux, 122Steefel and Yabusaki studies, 108Stella studies, 14Stern, Bedford and, studies, 224Stewart and Melchers studies, 6, 18, 23, 43–45,

47Stewart studies, 223Stohr studies, 273STOMP, see Subsurface Transport Over

Multiple Phases (STOMP)Storage layers, hydrologic cycle, 75Stormont studies, 160Strategic Environmental Research and

Development Program, 332Strength distributions, 36Stressors, 32, 33–34Stress-strain behavior, 124Structural stability factors, 178, 182, 182–183Structure-functional failure relationship

basics, 15–24, 17–18compliance demonstration, 22economic criteria, 18indexing analysis, 21, 23–24mixed criteria, 23, 23prescriptive design criteria, 19–20pseudo-economic criteria, 18qualitative analysis, 21, 23–24regulatory criteria, 19, 19risk criteria, 20–22, 21–22safety case concept, 22

Subsurface barrier verificationacoustic wave devices, 331, 331–332,

333–336AEMS, 307–308barrier cap monitoring, 311–312

barrier monitoring case history, 343, 343–346

basics, xv–xvi, 287–288, 348–349case histories, 312–318, 329, 341–346colloidal silica, 341–343, 342containment region adequacy, 347costs, 309covers, 310–320current practice, improvements needed,

297–312, 325–329, 337–340decision analysis, 299, 299–300direct push technologies, 305, 306end states, 309–310Environmental Restoration Disposal

Facility, 343, 343–346E-SMART network, 304, 304–305Fernald on-site disposal facility, 315,

315–318, 317fiber optics distributed temperature moisture

monitoring, 314flow characterization and monitoring, 325,

326–327, 330–331geochemical process monitoring, 331goals, 288, 289hardware, 320, 320–323hydrological process monitoring, 331implementation drivers, 309–310infiltration monitoring, covers, 313long-term performance, containment,

347–348LPRMS approach, 302–303, 302–304methods, 292–296mixed waste landfill, 312–315modeling links, 298, 299moisture, 292–295, 313–315nanotechnology sensors, 307neutron moisture monitoring, 313–314neutron well digging, 337–338new DOE barrier design code, 308–309optimization, 299, 319–320perfluorocarbon tracers, 338–340, 339PRBs, 321–332prediction links, 298, 299regulatory framework, 324–325sensors, 320, 320–323smart structures, 300–307spatial flow monitoring, 330–331subsurface monitoring, 329system performance, 298–300temporal flow monitoring, 330–331transitioning needed, 297–309trend analysis, 319–320uncertainty analysis, 299, 299–300

Index 373

vadose zone monitoring, 295–296, 296, 314–315

verification, 327–329, 328verification measurement systems, 311verification monitoring, 289, 290–292,

291–296verification needs, 318–320, 319, 329–332,

330, 346–348verification system design, 296–297walls and floors, 332, 337–348

Subsurface monitoring, 329Subsurface Transport Over Multiple Phases

(STOMP), 308Suction lysimeter, 294–295Sullivan studies, 71nSummitville, Colorado, 234, 235Sun, Ranson and, studies, 238Superfund Initiative on Long Term Reliability

of Containment, 288Surface geophysical methods, see Geophysical

method verificationSurface ionization mass spectrometry (SIMS),

191Suter studies, 29Systems, see also Damage and system

performance predictiondynamics, PRBs, 101–104, 102–103failure, 22, 43–44, 53–54management, updating, 60–61, 61performance, 5–6, 298–300

T

Tachavises and Benson studies, 193Tachavises studies, 193, 196–197Taira, Meyer and, studies, 20Tang, Gilbert and, studies, 24Tausch studies, 110TCM, see Trichloromethane (TCM)Tedd studies, 125Telford studies, 225Temporal flow monitoring, 330–331Theory simplifications, 51Thermal scanners, 233, 273–274Thermocouple psychrometer, 293Thibodeaux studies, 72Thornthwaite and Mather studies, 81, 86Thorstad studies, 157Time domain reflectometer, 293Time frames, waste containment performance, 4Time-varying properties and processes, 89–90,

125Tinoco studies, 118

Tokoz, Kuster and, studies, 223Tomassoni, Inyang and, studies, 12Tomography

algebraic reconstruction tomography, 221electrical resistivity tomography, 260,

260–261, 293–294ray tomography, 220–221wave tomography, 220–221

Toolboxbaseline in situ chemical sensors, 321groundwater monitoring, 323in situ chemical sensors examples, 322tracers, 326–327water balance, 320

Toomay studies, 237Topp studies, 266Toshiba Corporation, 307Total risk integrated methodology (TRIM), 56,

56TOUGH2, see Transport of unsaturated

groundwater and heat (TOUGH2)Transient events, 30, 31, 32, 33–34Transitioning, see Current practicesTransport of unsaturated groundwater and heat

(TOUGH2)caps, 84–85data needs, 87source code, 85

Transport process, contaminants, 112–123Tratnyek, Johnson and, studies, 327Tratnyek studies, 172, 327–329Trend analysis, 319–320Trichloromethane (TCM), 103, 173–175,

186–187, 308TRIM, see Total risk integrated methodology

(TRIM)Tura and Johnson studies, 220–221Tura studies, 220–221

U

Udd studies, 301Uncertainty analysis, 299, 299–300United States Corp of Engineers (USACE),

324–325, 331United States Soil Conservation Society, 87Unresolved challenges, 89–90UNSAT-H, 82, 87Updating, 59–61, 60–61Uranium Mill Tailings Remedial Action

(UMTRA) site, 28U.S. Department of Defense (USDOD), 332U.S. Department of Energy (DOE)


airborne geophysical methods, 228barrier design code, new, 308–309design verification systems, 309geosynthetics, 152goals, 288Hanford site cap, 160–163International Containment Technology

Workshop, 321LIFI project, 236successional sequences, timing, 27Y-12 plant, Oak Ridge (Tennessee), 95, 96,

183, 327U.S. Environmental Protection Agency

(USEPA)HELP model, 81International Containment Technology

Workshop, 321PRBs, 323regulatory framework, 324–325risk criteria, 22total risk integrated methodology, 56, 56

U.S. Navy Space and Warfare Systems Command (SPAWAR), 332

U.S. Nuclear Regulatory Commission (USNRC), 37

USDOE, see U.S. Department of Energy (DOE)USEPA, see U.S. Environmental Protection

Agency (USEPA)USNRC, see U.S. Nuclear Regulatory

Commission (USNRC)

V

V. Rajaram, Black and Veatch Corporation, 1nVADOSE-W, 84, 87Vadose zone monitoring, 289, 295–296, 296,

314–315Vadose Zone Science and Technology

Roadmap, 292Validation, caps, 88–89Van Benschoten, Rabideau and, studies, 93Van der Heijde, Paschke and, studies, 105Van Eeckhout studies, 238, 273–274Van Genuchten, Wierenga and, studies, 129Van Genuchten and Alves studies, 114, 116Van Genuchten studies, 87Vanmarcke studies, 47–48van't Hoff equation, 118Vasco studies, 222–223Vaughan and Calvin studies, 277Vegetation

ecological succession, 26–27layers, hydrologic cycle, 74

materials relationship, 163, 165–167, 166–167

Verification, see also Geophysical method verification; Subsurface barrier verification

caps, 88–89covers, 318–320, 319geochemical gradients and zones, 327–329,

328measurement systems, 311monitoring, 289, 290–292, 291–296perfluorocarbon tracers, 338–340, 339PRBs, 329–332, 330subsurface, 330system design, 296–297vertical barriers, 249–250, 250–253, 252,

254walls and floors, 330, 346–348

Verruijt, Bear and, studies, 91Vertical barriers

basics, 246–261case histories, 254–261cross-hole GPR investigations, 247–248,

255, 257–258, 257–259design verification, 249–250, 250–253, 252,

254ERT systems, 260, 260–261geophysical method verification, 246–261monitoring, 249, 254PRBs, 110requirements, 249seismic methods, 259site characterization, 249

Vertical cutoff walls, 198–199, 200Vertical seismic profiling (VSP), 218, 220,

222–224Vertical walls, installation, 200Vincent studies, 238, 272–273VOCs, see Volatile organic compounds (VOCs)Vogan studies, 95Volatile organic compounds (VOCs), 129VSP, see Vertical seismic profiling (VSP)

W

Wachsmuth studies, 1nWaite Amulet failings soil cover system, 32Walker, Cook and, studies, 268Walls and floors

analytical models, 115, 120, 120–123, 123aqueous-phase transport, 112–117, 115basics, 110

Index 375

clay soils, membrane behavior, 126–127, 127

contaminants, 112–123coupled solute transport, 117–119, 120,

125–126current practice, 111–112horizontal barriers, 110–111input parameters, 123–125limitations, 109–110, 123–127measurement accuracy, 123–125membrane behavior, clay soils, 126–127,

127research needs, 109–110, 123–127subsurface barrier verification, 332,

337–348time-varying properties and processes, 125transport process, contaminants, 112–123vertical barriers, 110walls, 110–127water flow modeling, 119–120

Ward, Gee and, studies, 15Ward and Gee studies, 160, 263Ward studies, 209n, 263, 266, 271Warner and Sorel studies, 173Warner studies, 143nWater balance

caps, 75, 81, 155–156material stability and applications, 153,

160–163, 161–162, 164–165sensors, 320thin cover, 167

Water flow modeling, 119–120Waugh studies, 29, 62Wave tomography, 220–221Webb, Ho and, studies, 84Weibull relationship, 36Weiler studies, 265Weiss studies, 209nWell studies, 238White studies, 241

Wierenga and van Genuchten studies, 129Wilkens studies, 143nWilkin studies, 187Wilson studies, 75, 82, 84, 176, 292, 294, 318WinUNSAT-H, 82Woessner, Anderson and, studies, 91Wolery studies, 106–107Wolford studies, 13Wollenhaupt studies, 268Wright, Conca and, studies, 128

X

Xing, Fredlund and, studies, 87XPS, see X-ray photoelectron spectroscopy

(XPS)X-ray diffraction, 191X-ray photoelectron spectroscopy (XPS), 191

Y

Yabusaki, Steefel and, studies, 108Yabusaki studies, 105, 187–188, 327Yamamoto studies, 224Yebusaki studies, 108Yeung stuides, 117Yilmaz studies, 266Y-12 plant, Oak Ridge (Tennessee), 95, 96, 183,

327

Z

Zero-valent iron (ZVI), 92–109Zhu and Anderson studies, 105Ziegler studies, 124Ziloli studies, 273Zimmie, Moo-Young and, studies, 26Zyvoloski studies, 85

COLOR FIGURE 4.7 Comparison of (a) ORAGS-TEM measurements and (b) an ana-lytic signal map derived from ORAGS-Arrowhead magnetic measurements for a bombingtarget in South Dakota. TEM represent the first-time gate only, and data were acquired at3 m nominal flight line spacing and 1.5–2 m altitude. Magnetometer results used the8-sensor magnetometer system at the same altitude and 12 m flight-line spacing. Theresponse of both systems to an east-trending barbed wire fence is seen across the centerof the diagrams. The individual anomalies are associated with M-38 practice bombs, ortheir fragments. These are sand- or cement-filled devices with a mass of 10–15 kg whenintact. Horizontal scale is in meters.

COLOR FIGURE 4.8 HIS (AVIRIS) image cube of Moffett Field, California.

COLOR FIGURE 4.9 AVIRIS HIS mapping of Summitville, CO, area.

Summitville, Colorado Mining DistrictFe–Mineral Map

AVIRIS Sept. 3, 1993 U.S. Geological Survey

Summitville Mine

N

Crospy Mountain

Alum Creek

Bitter Creek Wightman Fork

Alamosa River

1 KM

Reynolds Tunnel Sludge

Fe–hydroxide

K–Jarosite

Goethite

Na-Jarosite

Ferrihydrite

Hematite

not mapped

COLOR FIGURE 4.29 CMP gathering and velocity analysis at the intersection oftransects N1 and E1 in (a) March 2001 and (b) May 2001. Note the changes in the groundwave and reflection character. The vertical white line in each plot shows the optimalantenna separation. (From Clement, W.P. and Ward, A.L., Using ground penetrating radarto measure soil moisture content. Handbook of Agricultural Geophysics, Allred, B.J.,Daniels, J.J., and Ehsani, M.R., Eds., CRC Press, Boca Raton, 2003.) (See color versioninsert for this figure.)

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Ground waveafter injection

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Barrier systems for environmental contaminant containment and treatment

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