Investigation of expansive soil for design of light ...Investigation of Expansive Soil for Design of...

Investigation of Expansive Soil for Design of

Light Residential Footings in Melbourne

Aruna Nishantha Karunarathne

Submitted for the Degree of Doctor of Philosophy, Ph.D.

Faculty of Engineering and Industrial Sciences

Swinburne University of Technology

2016

Abstract

Expansive soils are found in most Australian states. In fact, it is estimated that 20% of

surface soils in Australia are categorized as moderate to highly expansive clays.

Quaternary basalt clays generally exhibit expansive characteristics and are commonly

found in the Western part of Victoria. These expansive soils undergo heave and

settlement due to moisture changes. Such ground movements are capable of creating

differential movement in footings which results in cracks and damage to light structures.

Recently, it has been reported that more than 5000 houses experienced damage in

Victoria due to changes in soil moisture caused by extreme climate events. Since the

climate condition is the natural cause of soil moisture changes, it must be considered in

the design stage of relevant structures.

This study is part of a comprehensive research programme aimed at enhancing

knowledge about expansive soil behaviour and mitigating damages to residential

structures due to ground movement caused by climate influences. This particular

dissertation focused on estimating soil moisture changes in response to climate

conditions and its consequences. The Australian standard (AS2870) considers the effect

of climate on footing design in terms of Thornthwaite Moisture Index (TMI). It was

found in this study that there are several methods to calculate TMI, which produce

different values for a particular climate condition and hence result in different footing

designs. Furthermore, TMI depends mostly on rainfall and may not be adequate to

consider the variations in soil moisture condition particularly when the TMI values are

based on averaging of long periods.

Soil moisture changes and subsequent ground movement were monitored in a field site

established in Braybrook in Melbourne, which has typical basalt clay soils. The

collected data shows that soil moisture contents follow the rainfall pattern and a

subsequent ground movement, with seasonal variation. Field monitoring over a two year

period revealed that the changes in soil moisture were recorded mainly in top soils

which contributed to the ground movement.

A comprehensive laboratory investigation was performed to characterise the basic

properties of Braybrook soils. These properties suggested that the site has a consistent

profile of highly expansive clay. Further investigations were performed to obtain

specific expansive properties such as mineral composition, soil suction changes and

hydraulic conductivity. These results confirmed the presence of expansive clay soils in

Braybrook. Moreover, a series of shrink swell tests were performed using undisturbed

soils at various in situ moisture contents. These test results indicated the dependency of

shrink swell index on in situ moisture content, which is in contrast to the specifications

outlined in the Australian standard AS1289. The outcome of the laboratory

investigation led to publication of a comprehensive data set that benefits both

practitioners and researchers.

The soil properties collected from the Braybrook site were then used to develop a finite

element model to predict the soil moisture changes in response to climate conditions.

The climate data were obtained from a nearby weather station and the model was

validated against the monitoring data over a two-year period. The validated model was

used to investigate the soil moisture changes due to long-term climate conditions,

including extreme events such as the millennium drought and the subsequent above

average rainfall period in Melbourne. In addition, the soil moisture predictions taken

from this model were fed into another model, developed as part of this comprehensive

research programme, to obtain the ground movement. The results of ground movements

obtained from these models were then compared with the outcomes from the current

Australian standard (AS2870). The results from the model suggest that considerable

additional ground movement has occurred due to the millennium drought, which was

not captured by the AS2870. Furthermore, the model predictions were used to consider

the mound shapes underneath flexible cover slabs placed at different times of the recent

years. Finally, available climate predictions were used to examine the possible future

changes in soil moisture and ground movement.

This research provides a versatile prediction tool for soil moisture changes due to

climate conditions and, therefore, will greatly assist the footing design procedure given

in AS2870. The model can be used to observe future changes of soil moisture within the

design life of a structure using various climate prediction scenarios. Hence, it is an

invaluable tool for designing residential structures that can withstand different severities

of climate conditions as well as uphold the homeowner’s expectations.

Acknowledgement

I am deeply indebted to my principal supervisor, Professor Emad Gad for his endless

guidance, support and constructive criticisms. Working with Professor Emad is the most

pleasurable experience I had in my life. In addition to his assistance in my research

study, the discussions with Professor Emad enhanced my attitude towards success and

personal knowledge.

I also thankful to my second supervisor, Professor John Wilson, for his guidance and

support. I was very lucky to have the luxury of five supervisors including three co-

supervisors from various backgrounds. I wish to express heartfelt appreciation to co-

supervisors Dr. Mahdi Miri Disfani, Dr. Siva Sivanerupan and Dr. Pathmanathan

Rajeev. The guidance in laboratory work from Dr. Mahdi was really important. If I had

not received the invaluable assistance from Dr. Siva, I would not have been able to

initiate field monitoring in the very early stage of this research study. Dr. Rajeevs’s

assistance in finite element model development has been significant. I wish to express

sincere appreciation to all three co-supervisors for their enormous support.

I would like to acknowledge the guidance I had from Mr. Dominic Lopes. He has been

a mentor for our research group. The assistance through his vast knowledge in

expansive soil area has laid the sound foundation for my research study. I also thank Dr.

Robert Evans for giving me the opportunity to undertake tutoring in Geotechnical

Engineering subject, which enhanced my knowledge about footing design.

My warm thanks are due to the administrative and technical staff at the Department of

Civil and Construction Engineering of Swinburne University of Technology. Special

appreciation must be given to Senior Technical Officer, Alec Papanicolaou, in the

workshop for his help in modifications of testing devices and organising various

experimental setups. In addition, PC Support Officer Andrew Zammit in Information

Technology Services kindly provided assistance in various occasions.

I would like to acknowledge Australia Research Council (ARC), the main contributor of

this research project from the ARC Linkage Grant (LP100200306). I gratefully

acknowledge the financial and technical support provided by the collaborating

organizations, namely; Victorian Building Authority (VBA), Victorian Office of

Housing (OoH), Foundation and Footings Society of Victoria (FFSV), Association of

Consulting Structural Engineers Victoria (ACSEV) and Housing Engineering Design

and Research Association (HEDRA). I would like to recognise the invaluable feedback

from adversary panel members who represented the above-mentioned organizations. I

wish to express my deep and sincere gratitude to my colleagues of the research group;

Jenny Boyer and Deepti Wagle for their support during the study.

Finally, I owe my loving thanks to everyone in my family. Special thanks should be

given to my brother who has been looking after my parents while I was far from them.

This thesis would not have been possible without their love, encouragement and

understanding.

Declaration

I hereby declare that this thesis contains no material which has been accepted for the

award of any other degree or diploma in any university or institution. To the best of my

knowledge and belief, this thesis contains no material previously published or written

by another person, except when due reference is made in the text of the thesis.

Aruna Nishantha Karunarathne

August 2016

Preface

This dissertation is produced as part of a comprehensive research study aimed to assist

in mitigating damage to residential structures due to ground movement. The study

involved three PhD students and several resource persons directing at a number of

engagements of the research problem. The author of this dissertation has been

responsible for the geotechnical section of the study which indeed focused on

estimation of soil moisture and ground movement induced by climate conditions. This

dissertation is original, unpublished and independent work by the author, Aruna

Nishantha Karunarathne.

Following peer reviewed publications were produced from various outcomes of the

research and they are based on certain sections of thesis chapters.

Journal papers

KARUNARATHNE, A. M. A. N., SIVANERUPAN, S., GAD, E. F., DISFANI,

M. M., RAJEEV, P., WILSON, J. L. & LI, J. 2014. Field and laboratory

investigation of an expansive soil site in Melbourne. Australian Geomechanics,

49, 85-93.

KARUNARATHNE, A. M. A. N., GAD, E. F., DISFANI, M. M.,

SIVANERUPAN, S. & WILSON, J. L. 2016. Review of Calculation Procedures

of Thornthwaite Moisture Index and its Impact on Footing Design. Australian

Geomechanics, 51, 85-95.

FARDIPOUR, M., GAD, E., SIVAGNANASUNDRAM, S., RAJEEV, P.,

KARUNARATHNE, A. & WILSON, J. 2016. Interaction analysis of waffle

slabs supporting houses on expansive soil. Innovative Infrastructure Solutions,

1, 1-10.

Conference papers

KARUNARATHNE, A. M. A. N., GAD, E. F., SIVANERUPAN, S. &

WILSON, J. L. Review of Residential Footing Design on Expansive Soil in

Australia. In: SAMALI, B., ATTARD, M. M. & SONG, C., eds. 22nd

Australasian Conference on the Mechanics of Structures and Materials, 11-14

December 2012 Sydney, NSW. Taylor & Francis Group, 575-579

KARUNARATHNE, A. M. A. N., SIVANERUPAN, S., GAD, E. F., DISFANI,

M. M., WILSON, J. L. & LI, J. Field monitoring of seasonal ground movements

in expansive soils in Melbourne. In: KHALILI, N., RUSSELL, A. &

KHOSHGHALB, A., eds. 'UNSAT 2014', Unsaturated Soils: Research and

Applications - the 6th International Conference on Unsaturated Soils, 2-4July

2014 Sydney, NSW. Taylor & Francis Group, 1359-1365.

i

Table of contents

1. Introduction ............................................................................................................... 1

1.1 Background ........................................................................................................ 1

1.2 Research objectives ............................................................................................ 8

1.3 Overview of the research methodology .............................................................. 9

1.4 Perceived specific contributions of the research .............................................. 10

1.5 Outline of the thesis .......................................................................................... 11

2. Literature review ..................................................................................................... 13

2.1 Introduction ...................................................................................................... 13

2.2 Expansive behaviour of soil ............................................................................. 13

2.2.1 Overview ................................................................................................... 13

2.2.2 Mineral composition of expansive clay .................................................... 14

2.2.3 Identification of shrink - swell potential based on soil properties ............ 17

2.2.4 Effects of moisture changes on soil properties ......................................... 20

2.2.5 Reasons for soil moisture change .............................................................. 27

2.3 Investigations on expansive soil problems ....................................................... 29

2.3.1 Expansive soils - a global issue ................................................................. 29

2.3.2 Field monitoring systems in expansive soil research ................................ 30

2.3.3 Previous expansive soil research investigations in Australia .................... 35

2.3.4 Forensic investigations .............................................................................. 42

2.4 AS2870 footing design procedure .................................................................... 44

2.4.1 Characteristic ground movement of expansive soil .................................. 46

2.4.2 Factors affecting ys calculation ................................................................. 49

2.5 Limitations of soil moisture predictions ........................................................... 57

2.5.1 Effectiveness of AS2870 design procedure with changes in TMI ............ 57

2.5.2 Standard design outcome and home owner’s expectations ....................... 58

ii

2.6 importance of a robust method of estimating soil moisture changes ............... 59

2.7 Summary .......................................................................................................... 59

3. Effects of climate on footing design ....................................................................... 61

3.1 Influence of climate conditions on soil moisture content ................................. 61

3.2 Climate consideration in AS2870 ..................................................................... 65

3.3 Thornthwaite Moisture Index (TMI) ................................................................ 66

3.3.1 Calculation of TMI .................................................................................... 67

3.3.2 Definitions and Assumptions .................................................................... 67

3.3.3 Different methods of TMI calculation ...................................................... 71

3.3.4 Comparison of TMI results from different methods ................................. 76

3.3.5 Sensitivity of climate parameters of TMI calculation ............................... 77

3.4 Correlation of TMI and expansive soil behaviour ............................................ 81

3.5 Issues of TMI being used in AS2870 ............................................................... 84

3.6 Effect of soil moisture condition on AS2870 design parameters ..................... 93

3.6.1 Variation of Iss with moisture content ....................................................... 93

3.6.2 Effect of Iss changes on site classification ................................................. 97

3.7 Summary .......................................................................................................... 98

4. Field and laboratory investigations of expansive soil behaviour .......................... 101

4.1 Introduction .................................................................................................... 101

4.2 Site selection criteria ...................................................................................... 101

4.3 Soil classification ........................................................................................... 105

4.3.1 Soil profile ............................................................................................... 106

4.3.2 Atterberg limits and linear shrinkage ...................................................... 107

4.3.3 Particle size distribution and density tests .............................................. 110

4.3.4 Mineral composition of the soil .............................................................. 111

4.4 Site classification according to AS2870 ......................................................... 112

4.4.1 Shrink-swell characteristics of Braybrook soil ....................................... 112

iii

4.4.2 Site classification .................................................................................... 113

4.5 Development of main expansive soil parameters ........................................... 113

4.5.1 Soil Water Characteristic Curve (SWCC)............................................... 114

4.5.2 Hydraulic conductivity function ............................................................. 134

4.6 Summary ........................................................................................................ 142

5. Field instrumentation and data analysis ................................................................ 144

5.1 Introduction .................................................................................................... 144

5.2 Field monitoring system ................................................................................. 144

5.2.1 Overview ................................................................................................. 144

5.2.2 Soil moisture monitoring ........................................................................ 144

5.2.3 Ground movement monitoring ................................................................ 149

5.3 Site layout ....................................................................................................... 152

5.4 Investigation of field monitoring data ............................................................ 153

5.4.1 Soil moisture profiles with time .............................................................. 153

5.4.2 Ground movement monitoring ................................................................ 160

5.5 Summary ........................................................................................................ 167

6. Modelling of moisture changes in expansive soil ................................................. 169

6.1 Introduction .................................................................................................... 169

6.2 Finite element modelling tool selection ......................................................... 169

6.3 Modelling of soil moisture movement using Vadose/w ................................. 172

6.4 Soil parameters ............................................................................................... 176

6.4.1 Soil Water Characteristic Curve (SWCC)............................................... 176

6.4.2 Hydraulic conductivity function ............................................................. 177

6.4.3 Thermal properties of soil ....................................................................... 177

6.5 Climate data .................................................................................................... 180

6.6 Vegetation influence ....................................................................................... 182

6.7 Development of one dimensional soil column ............................................... 185

iv

6.7.1 Selection of soil layers ............................................................................ 185

6.8 Calibration of 1D soil model against measured data ...................................... 187

6.9 Development of two dimensional soil model ................................................. 195

6.9.1 Selection of model parameters ................................................................ 195

6.9.2 2D model predictions .............................................................................. 201

6.10 Model generalization .................................................................................. 201

6.10.1 Sensitivity of the material model ............................................................ 201

6.10.2 Sensitivity of climate parameters ............................................................ 205

6.11 Summary ..................................................................................................... 211

7. Model applications ................................................................................................ 214

7.1 Overview on model predictions of soil moistures .......................................... 214

7.1.1 Prediction of soil moistures ..................................................................... 215

7.1.2 Prediction of ground movement .............................................................. 219

7.2 Model predictions due to Long term climate conditions ................................ 221

7.2.1 Variation of suction profiles.................................................................... 222

7.2.2 Variation of soil moisture contents ......................................................... 224

7.2.3 Variation of ground movement ............................................................... 225

7.2.4 Comparison of ground movement estimations ....................................... 227

7.2.5 Effects of the depth of bedrock on ground movement ............................ 232

7.2.6 Effects of site drainage condition on ground movement ........................ 235

7.3 Short term climate variations ......................................................................... 237

7.4 Long term climate predictions ........................................................................ 240

7.5 Soil moisture changes beneath cover slabs .................................................... 242

7.6 Changes of the mound profiles ....................................................................... 246

7.6.1 Slab subjected to heave condition (1983 to 1992) .................................. 248

7.6.2 Slab subjected to settlement condition (1992 to 2010) ........................... 251

7.6.3 Comparison of mound shape predictions ................................................ 255

v

7.7 Effect of abnormal moisture conditions ......................................................... 255

7.7.1 Soil slope towards the cover slab ............................................................ 256

7.8 Summary ........................................................................................................ 257

8. Conclusions and future work ................................................................................ 262

8.1 Overview of the study .................................................................................... 262

8.2 Summary of conclusions ................................................................................ 263

8.2.1 Ground movement, climate changes and TMI ........................................ 263

8.2.2 Characterization of typical basaltic clay in Western Melbourne ............ 265

8.2.3 Field monitoring of expansive soil behaviour ......................................... 266

8.2.4 Finite element modelling approach of expansive soil and climate

interaction .............................................................................................................. 267

8.2.5 Prediction of ground movement due to several site conditions and climate

scenarios ................................................................................................................ 268

8.3 Recommendations for future work ................................................................. 271

9. References ............................................................................................................. 274

10. Appendices

A: Hyprop measurements of Braybrook soil

B: WP4C measurements of Braybrook soil

C: Filter paper suction measurements of Braybrook soil

D: Saturated hydraulic conductivity measurements of Braybrook soil

E: Model calibration data

vi

List of figures

Figure 1-1: a) Expansive soil distribution in Australia (Richards et al., 1983); b)

Geographic distribution of population (Statistics, 2012) .................................................. 2

Figure 1-2: Areas of reported damaged houses................................................................. 4

Figure 1-3: Crack in an interior plasterboard lined wall (ACA, 2012) ............................. 4

Figure 1-4: Another example of a crack in an interior plasterboard lined wall (ACA,

2012) ................................................................................................................................. 5

Figure 1-5: Large crack in a plasterboard lined wall (THE-AGE, 2011) ......................... 5

Figure 1-6: A crack in a wall caused by edge lift of footing (Photo taken by the author) 6

Figure 1-7: Crack appeared in a wall caused by edge lift of footing (Photo taken by the

author) ............................................................................................................................... 6

Figure 1-8: Separation of up to 50mm in a wall and the window frame caused by

footing movement (Photo taken by the author) ................................................................ 7

Figure 1-9: An internal wall has been lifted by roof truss due to edge heave of footing

(Photo taken by the author) ............................................................................................... 7

Figure 2-1: Schematic diagrams of the mineral structure of Kaolinite, Illite and

Montmorillonite (Nelson et al., 2015) ............................................................................ 15

Figure 2-2: Conceptual model of sequential crystalline swelling of smectite (Likos,

2004) ............................................................................................................................... 16

Figure 2-3: : Index test correlation – Volume change vs Liquid Limit (Kay, 1990) ...... 19

Figure 2-4: Matric suction variation of a soil column(Nelson et al., 2003) .................... 21

Figure 2-5: Osmotic pressure across the semipermeable membrane (Nelson et al., 2003)

......................................................................................................................................... 22

Figure 2-6: Measured total, matric, and osmotic suctions for Glacial Till from Chao

(2007) after Krahn and Fredlund (1972) ......................................................................... 23

Figure 2-7: Measured soil moisture change with suction for some Adelaide soils

(Mitchell, 1984b)............................................................................................................. 24

Figure 2-8: Typical shape of a SWCC (Fredlund, 2000) ................................................ 25

Figure 2-9: Global distribution of reported expansive soil sites (Nelson et al., 2015) ... 29

Figure 2-10: Schematic depiction of neutron probe deployment(Ward and Wittman,

2009) ............................................................................................................................... 32

Figure 2-11: Spider magnet of the extensometer ............................................................ 34

vii

Figure 2-12: Magnetic extensometer arrangement ......................................................... 35

Figure 2-13: Ground Movement Stations (GMS) used in Swinburne's study in the 1970s'

(Washusen, 1977) ............................................................................................................ 36

Figure 2-14: Hygrometers used in Swinburne's study in the 1970s' (Washusen, 1977) . 37

Figure 2-15: Model 4000 Borehole Rod Extensometers (HMA, 2014).......................... 41

Figure 2-16: Measured and predicted soil moistures at 300 mm depth in Altona North

(Chan, 2014) .................................................................................................................... 41

Figure 2-17: Propagated cracks on wall even after remedial actions were taken (A house

in Taylors Hill) ................................................................................................................ 43

Figure 2-18: Contours showing deviations from assumed planar initial condition (in

mm) of a damaged house in Wyndham Vale measured over a year ............................... 43

Figure 2-19: Typical wet and dry suction profiles in different Australian regions (Walsh

and Cameron, 1997) ........................................................................................................ 45

Figure 2-20: Comparison between measured and predicted free surface movement in

O'Halloran Hill, Adelaide (Mitchell and Avalle, 1984) .................................................. 49

Figure 2-21: Idealized water content profile (Nelson et al., 2001) ................................. 50

Figure 2-22: Theoretical suction profiles given in (Mitchell, 1979) ............................... 51

Figure 2-23: Simplified suction profile and the effect of bedrock and water table on ΔU

and Hs(AS2870, 2011) .................................................................................................... 52

Figure 2-24: Sample calculation of Ipt from different Iss values for cracked soil ........... 56

Figure 3-1: The hydrologic cycle (NWS, 2010) ............................................................. 61

Figure 3-2: Redistribution of the soil moisture (Dingman, 2002) .................................. 63

Figure 3-3: Variation of monthly rainfall and evapotranspiration with soil moisture

conditions in various sites (Russam and Coleman, 1961)............................................... 64

Figure 3-4: Flow chart of the TMI calculation................................................................ 67

Figure 3-5: TMI variation in Melbourne CBD for the last 50 years ............................... 76

Figure 3-6: TMI and annual rainfall variation in Melbourne CBD for last 50 years ...... 77

Figure 3-7: Relationship between TMI and annual rainfall (Melbourne) ....................... 78

Figure 3-8: TMI and annual average temperature variation in Melbourne CBD for the

last 50 years ..................................................................................................................... 79

Figure 3-9: Relationship between TMI and annual average temperature (Melbourne) .. 79

Figure 3-10: Sensitivity of averaging period on TMI ..................................................... 80

viii

Figure 3-11: Variation of soil suction of road subgrade with TMI (Russam and

Coleman, 1961) ............................................................................................................... 81

Figure 3-12: Edge moisture variation distance determination in Post Tensioning

Institute (PTI, 2004) ........................................................................................................ 82

Figure 3-13: Correlations of equilibrium soil suction and TMI (Mitchell, 2008) .......... 82

Figure 3-14: Correlation of ΔU and TMI (Mitchell, 2008) ........................................... 83

Figure 3-15: Correlation of Hs and TMI (Mitchell, 2008) ............................................. 84

Figure 3-16: (a) Average Annual Rainfall in mm for 2100 predicted climate; (b) TMI

map for 2100 predicted climate(Austroads, 2004) .......................................................... 85

Figure 3-17: Victorian mean annual rainfall map (BoM, 2015a) ................................... 85

Figure 3-18: TMI map for Victoria for 1913 to 1932 (Leao and Osman, 2013) ............ 86

Figure 3-19: TMI map of Victoria given in AS2870 (1996) .......................................... 87

Figure 3-20: TMI map of Victoria given in AS2870 (2011) .......................................... 89

Figure 3-21: TMI calculation for Victorian cities ........................................................... 90

Figure 3-22: TMI of Victorian cities in different climate zones specified in AS2870

(1996) .............................................................................................................................. 91

Figure 3-23: TMI of Victorian cities in different climate zones specified in AS2870

(2011) .............................................................................................................................. 91

Figure 3-24: Vertical strain and suction relationship (Braybrook soil) .......................... 94

Figure 3-25: Iss variation with starting moisture content for soils at 0.5-1.0 m depth in

Braybrook ........................................................................................................................ 96

Figure 4-1: Geology of Melbourne and the location of Braybrook site - extracted from

1:31680 map of Melbourne (Maps, 2015) .................................................................... 102

Figure 4-2: Distribution of expansive soils in Victoria (after Mann (2003)) ................ 103

Figure 4-3: Google map view of the Braybrook site and samples collected locations

(Google image was taken in 2010)................................................................................ 104

Figure 4-4: Three adjacent blocks of Braybrook Site ................................................... 105

Figure 4-5: Cross section of an undisturbed sample extruded from a tube (2.5 -3.0 m)

....................................................................................................................................... 106

Figure 4-6: Cross section of the soil profile of Braybrook site exposed through an

excavation ..................................................................................................................... 107

Figure 4-7: Atterberg limits and linear shrinkage variation with depth ........................ 109

Figure 4-8: Location of Braybrook clay in plasticity chart (ASTM-D2487, 2011) ...... 109

ix

Figure 4-9: a) Hydrometer test, b) Specific gravity test................................................ 110

Figure 4-10: Specific gravity and fine particle percentages variation with depth in

Braybrook Soil .............................................................................................................. 111

Figure 4-11: Hyprop sample in the ring ........................................................................ 117

Figure 4-12: Excavation of a pit in Braybrook site to collect Hyprop samples ............ 117

Figure 4-13: Excavation of undisturbed samples using Hyprop sampling device ........ 118

Figure 4-14: Hyprop samples saturation under a surcharge.......................................... 119

Figure 4-15: Refilling of de-gassed water; a) into tensiometer, b) into Hyprop sensor

unit ................................................................................................................................ 120

Figure 4-16: Suction measuring unit of Hyprop device(UMS, 2013) .......................... 121

Figure 4-17: The auger adapter and the sample with two holes drilled in the bottom

surface ........................................................................................................................... 122

Figure 4-18: The soil sample attached to the Hyprop sensor unit ................................. 122

Figure 4-19: The Hyprop test is running inside the environmental chamber ............... 123

Figure 4-20: The soil sample at the end of the Hyprop test .......................................... 124

Figure 4-21: Relationship between volumetric and gravimetric moisture consents in

Braybrook soil ............................................................................................................... 125

Figure 4-22: A portion of typical SWCC developed using Hyprop ............................. 125

Figure 4-23: Schematic of chilled-mirror dew-point device (after Leong et al. (2003) )

....................................................................................................................................... 126

Figure 4-24: Standard liquids used to calibrate the WP4C ........................................... 128

Figure 4-25: Soil sampling devises used to prepare WP4C samples ............................ 128

Figure 4-26: The sample is ready to measure suction using WP4C ............................. 129

Figure 4-27: A portion of typical SWCC developed using WP4C ............................... 130

Figure 4-28: Filter paper suction measurements of Braybrook soil .............................. 131

Figure 4-29: Calibration Suction-Water Content Curves for Wetting of Filter Paper

(ASTM-D5298, 2003) ................................................................................................... 132

Figure 4-30: SWCCs of soil from Braybrook site at different depths .......................... 134

Figure 4-31: Saturated hydraulic conductivity test for Braybrook soil using tri-axial

machine ......................................................................................................................... 135

Figure 4-32: Variation of Ksat with time of measurement - top two layers ................... 137

Figure 4-33: Variation of Ksat with time of measurement - bottom two layers ............ 137

x

Figure 4-34: Predicted hydraulic conductivity functions for Braybrook soil at 0-0.4 m

....................................................................................................................................... 141

Figure 4-35: Hydraulic conductivity functions (based on Fredlund’s model) of

Braybrook soil at different depths ................................................................................. 141

Figure 5-1: Neutron probe access tube pushing into the borehole ................................ 145

Figure 5-2: CPN 503DR neutron probe used in the Braybrook site ............................. 146

Figure 5-3: Calibration curve of the neutron Probe ...................................................... 147

Figure 5-4: Schematic of neutron probe measuring arrangement ................................. 148

Figure 5-5: Releasing mechanism of the spider magnet in extensometer ..................... 150

Figure 5-6: Magnetic extensometer installation at the Braybrook site ......................... 151

Figure 5-7: Ground surface movement measurements using extensometer ................. 151

Figure 5-8: Monitoring Plan of the Braybrook Site ...................................................... 152

Figure 5-9: Volumetric moisture content profiles at CN1 location .............................. 154

Figure 5-10: Volumetric moisture content profiles at the CN2 location ...................... 154

Figure 5-11: Volumetric moisture content profiles at the TN6 location ....................... 155

Figure 5-12: Crack measurements using a steel cable .................................................. 156

Figure 5-13: Comparison of moisture contents obtained from the neutron probe and the

samples .......................................................................................................................... 158

Figure 5-14: Volumetric moisture content (VMC) change comparison with monthly

rainfall (Location – CN1) .............................................................................................. 159

Figure 5-15: Volumetric moisture content (VMC) change comparison with daily rainfall

(Location – CN1) .......................................................................................................... 160

Figure 5-16: Surface movements measured at 3 locations and monthly rainfall .......... 163

Figure 5-17: Soil movements in response to monthly rainfall - E1 extensometer ........ 164



Figure 5-20: Incremental paver movements with monthly rainfall .............................. 167

Figure 6-1: Thermal conductivity functions used in this study..................................... 178

Figure 6-2: Specific heat capacity functions used in this study .................................... 179

Figure 6-3: Initial soil temperature function used in this study .................................... 180

Figure 6-4: Hourly rainfall distribution used in vadose software (for data set given in

Table 6-1) ...................................................................................................................... 181

Figure 6-5: Grass cover in Braybrook site .................................................................... 183

xi

Figure 6-6: Estimated leaf area index function for Braybrook site ............................... 184

Figure 6-7: Typical PML function used in the study (Vadose, 2013) .......................... 184

Figure 6-8: Root depth function for Braybrook site...................................................... 185

Figure 6-9: Summary of one-dimensional Vadose/w model ........................................ 187

Figure 6-10: Initial moisture content measured at various depths; (b) corresponding

suction at various depths ............................................................................................... 188

Figure 6-11: Measured soil moisture contents at 0.35 m and model predictions with

rainfall variation ............................................................................................................ 190







Figure 6-15: Measured average soil moisture contents at 0.35 m and model predictions

with rainfall variation .................................................................................................... 192







Figure 6-19: Actual measurements and model predictions for two extreme measurement

dates; a) recorded wettest, b) recorded driest ........................................................... 194

Figure 6-20: Model predictions against neutron probe measured data ......................... 194

Figure 6-21: A large soil chunk from Braybrook ......................................................... 196

Figure 6-22: Two-dimensional Vadose/w model .......................................................... 199

Figure 6-23: Characteristic wettest and driest suctions at 300 mm depth taken from the

2D model with different sizes ....................................................................................... 199

Figure 6-24: Soil moisture profiles obtained from models with different mesh sizes .. 200

Figure 6-25: 20% changes applied to SWCC of surface layer in sensitivity analysis .. 202

Figure 6-26: 20% changes applied to hydraulic conductivity of surface layer in

sensitivity analysis ........................................................................................................ 203

xii

Figure 6-27: 20% changes applied to thermal conductivity of surface layer in sensitivity

analysis .......................................................................................................................... 203

Figure 6-28: 20% changes applied to specific heat capacity of surface layer in

sensitivity analysis ........................................................................................................ 204

Figure 6-29: Sensitivity of soil parameters ................................................................... 204

Figure 6-30: Daily rainfall variation of 3 locations around Braybrook (April 2013) ... 206

Figure 6-31: Variation of evaporation in Fawkner ....................................................... 207

Figure 6-32: Comparison of pan evaporation and Penman potential evaporation in

Fawkner ......................................................................................................................... 207

Figure 6-33: Sensitivity of climate parameters ............................................................. 209

Figure 6-34: Effect of vegetation layer on soil moisture at Braybrook site .................. 210

Figure 6-35: Effect of ponding condition on soil moisture at Braybrook site .............. 211

Figure 7-1: Annual rainfall recorded in Essendon airport weather station ................... 216

Figure 7-2: Flow chart of AS2870 method ................................................................... 219

Figure 7-3: Flow chart of Vadose/w + AS2870 method ............................................... 220

Figure 7-4: Soil stiffness versus moisture content relationship for Braybrook soil ...... 221

Figure 7-5: Flow chart of Vadose/w + FLAC model .................................................... 221

Figure 7-6: Predicted characteristic suction profiles; a) Braybrook-VB1 model and b)

Fawkner-VF1 model ..................................................................................................... 223

Figure 7-7: Variation of volumetric moisture content near surface and at Hs– Braybrook

(VB1 model) ................................................................................................................. 224

Figure 7-8: Variation of volumetric moisture content near surface and at Hs – Fawkner

(VF1model) ................................................................................................................... 225

Figure 7-9: Braybrook ground movement prediction from VB1 and FLAC model ..... 226

Figure 7-10: Fawkner ground movement prediction from VF1 and FLAC model....... 227

Figure 7-11: Idealized characteristic suction profiles in Braybrook site (VB1 model) 228

Figure 7-12: Changes in characteristic suction profiles within 25 year periods; a)

Braybrook -VB1 model and b) Fawkner-VF1 model ................................................... 231

Figure 7-13: Changes in characteristic suction profiles -VB2 model; a) Extreme profiles

in three periods b) Idealized triangles for AS2870 calculations ................................... 233

Figure 7-14: Ground movement prediction from VB2 and FLAC model .................... 234

Figure 7-15: Soil moisture predictions without any runoff correction ......................... 236

Figure 7-16: Ground movement predictions with different runoff conditions ............. 237

xiii

Figure 7-17: 12 month moving average ground movement – Braybrook ..................... 239

Figure 7-18: 12 month moving average ground movement –Fawkner ......................... 239

Figure 7-19: Effect of long-term climate predictions on ground movement – Braybrook

....................................................................................................................................... 241

Figure 7-20: Effect of long-term climate predictions on ground movement – Fawkner

....................................................................................................................................... 241

Figure 7-21: Predicted moisture variation with the distance at 300 mm depth in

Braybrook soil ............................................................................................................... 243

Figure 7-22: Predicted edge moisture variation (e) at 300 mm depth in Braybrook soil

....................................................................................................................................... 244

Figure 7-23: Discrete points along the distance where soil moisture variations

considered to obtain ground movement ........................................................................ 247

Figure 7-24: Suction profiles during 1983-1992 at distances 3 m and 4 m from axis of

symmetry ....................................................................................................................... 249


symmetry ....................................................................................................................... 249


symmetry ....................................................................................................................... 250

Figure 7-27: Maximum edge heave profile during 1983-1992 ..................................... 251


symmetry ....................................................................................................................... 252


symmetry ....................................................................................................................... 253


symmetry ....................................................................................................................... 253

Figure 7-31: Maximum centre heave profile during 1992-2010 ................................... 254

Figure 7-32: Comparison of lateral moisture movement at 300 mm depth in with and

without slope condition ................................................................................................. 256

xiv

List of tables

Table 2-1: Typical Atterberg limit ranges of pure clays (Fratta et al., 2007) ................. 17

Table 2-2: Identification of shrink-swell potential using shrinkage limit and linear

shrinkage (Altmeyer, 1955) .......................................................................................... 18

Table 2-3: Identification of shrink-swell potential using Plasticity index (Holtz and

Gibbs, 1956) .................................................................................................................... 18

Table 2-4: Site classification by characteristic surface movement (AS2870, 2011) ...... 45

Table 3-1: Climate types together with their TMI limits (Thornthwaite, 1948) ............. 66

Table 3-2: TMI calculation steps in Method 1 ................................................................ 72




Table 3-6: Climate zones and corresponding Hs inferred from AS2870 (1996) ............. 88

Table 3-7: Relationship between TMI and Hs(AS2870, 2011) ...................................... 90

Table 3-8: Hs and ΔU values specified in AS2870 ......................................................... 92

Table 3-9: Iss test results from different samples collected at similar locations from

Braybrook ........................................................................................................................ 96

Table 3-10: Iss results of Burnside samples ..................................................................... 97

Table 3-11: Calculation of ys using different Iss values .................................................. 98

Table 4-1: Soil profile at Braybrook ............................................................................. 106

Table 4-2: Basic soil test result - Location 1................................................................. 108



Table 4-5: Mineral composition of Braybrook clay ...................................................... 112

Table 4-6: Iss values of Braybrook soil at different depths ........................................... 113

Table 4-7: ys calculation ................................................................................................ 113

Table 4-8: Approximate measurement ranges and times for equilibration in

measurement and control of soil suction (Murray and Sivakumar, 2010) .................... 115

Table 4-9: Filter paper readings of Braybrook soil ....................................................... 132

Table 4-10: Saturated hydraulic conductivity data sheet .............................................. 136

Table 4-11: Saturated hydraulic conductivities of Braybrook soil ............................... 138

Table 5-1: Results from neutron probe measurements ................................................. 149

xv

Table 5-2: Description of crack depth measurements at CN1, CN2 and TN6 locations

....................................................................................................................................... 157

Table 5-3: Soil layer movements from E1 extensometer .............................................. 161



Table 5-6: Movements of paving blocks ....................................................................... 166

Table 6-1: Hourly rainfall distribution (sinusoidal) of daily rainfall – assumed data set

....................................................................................................................................... 181

Table 6-2: Typical set of data used in climate boundary in Vadose/w software .......... 182

Table 7-1: Soil profile at Fawkner site (Rajeev et al., 2012) ........................................ 217

Table 7-2: Geotechnical properties of Fawkner soil (Rajeev et al., 2012) ................... 217

Table 7-3: Estimation of ys for Braybrook site ............................................................. 229

Table 7-4: 25 year periods and corresponding TMI...................................................... 230

Table 7-5: Estimation of ys based on AS2870 (2011) for Braybrook ........................... 230

Table 7-6: Estimation of ys for 25 year periods – Braybrook site ................................ 232

Table 7-7: Estimation of ys for 25 year periods – Fawkner site .................................... 232

Table 7-8: Estimation of ys for Braybrook site with bedrock at 3m depth (from VB2

model) ........................................................................................................................... 235

Table 7-9: relationship of ym and ys (AS2870, 2011) ................................................... 245

Table 7-10: Comparison of changes in 'e' distances ..................................................... 245

Table 7-11: Ground movement estimation during 1983-1992 ...................................... 251

Table 7-12: Ground movement estimation during 1992-2010 ...................................... 254

Table 7-13: Mound shape parameters obtained from models ....................................... 255

1

1. INTRODUCTION

This thesis is a documentation of PhD research undertaken at Swinburne University of

Technology, Australia from 2012 to 2015. This doctoral programme was part of a larger

research project carried out in association with five industry organizations namely,

Victorian Building Authority (VBA), Victorian Office of Housing (OoH), Foundation

and Footing Society of Victoria (FFSV), Association of Consulting Structural Engineers

Victoria (ACSEV) and Housing Engineering Design and Research Association

(HEDRA). The overall objective of the programme was to assist in the mitigation of

damages to residential structures due to ground movement. The following section

describes the background of the problem and the specific objective of this doctoral

research.

1.1 BACKGROUND

Expansive soil has been a great concern in design and construction of lightly loaded

structures in Australia. Approximately 20% of the surface soils in Australia can be

categorized as moderate to highly expansive soils (Richards et al., 1983) and these

expansive soils are frequently found in populated areas, as shown in Figure 1-1.

Expansive soils undergo changes in volume mainly due to moisture variations. This

volume change behavior causes heave and settlements of the ground surface which can

result in substantial differential footing movements resulting in damage to houses and

other lightly loaded structures.

The moisture changes of the soil beneath house footings can result from various factors

including climate conditions, gardening around the house and pipe failures.

Unfortunately, it is not possible to completely eliminate these causes. While the

maintenance issues can be minimized, the environmental effects have to be accepted.

However, the detrimental consequences of the soil moisture changes under footings can

be minimized by taking suitable procedures in the design. For instance, the majority of

damage can be minimized by designing footings to sustain the expected ground

movement. Consequently, the construction and maintenance procedures can also be

adjusted based on the footing design.

2

Figure 1-1: a) Expansive soil distribution in Australia (Richards et al., 1983); b) Geographic distribution of population (Statistics, 2012)

Soil moisture is also dependent on the climate. Indeed, weather patterns and extreme

climate events are reflected in soil moisture contents. Drought conditions, for example,

can decrease the moisture of the soil underneath the footing around the house. Hence,

edge settlements of footings can be expected during droughts. In contrast, moisture

content increases during wet periods which result in edge heave of the houses. Apart

from climate effects, soil moistures are also influenced by the type of soil. Therefore,

the climate condition and the soil type of the area are key design parameters of

residential footings. Since both of these parameters vary from place to place it is

difficult to develop a generalized approach for the design and, therefore, many

assumptions must be implemented in ground movement estimations (Cameron and

Walsh, 1984, Mitchell, 1984a, Walsh, 1975).

There has been some research on designing footings on expansive soils (Cameron,

1977, Lytton, 1970b, Lytton, 1970a, Lytton and Woodburn, 1985, Mitchell, 1984b,

Nelson et al., 2003, Walsh, 1975, Wray, 1978, Pitt, 1982, Washusen, 1977). These

researchers mainly concentrated on strengthening the footings to withstand the ground

movement. The estimation of expected ground movement has also been considered and

a) b)

3

various methods have been developed. All these methods are based on moisture

variation, which is the primary cause of volume change behaviour of expansive soils.

Research on the design of footings on expansive soils has resulted in the development

of an Australian standard which offers guidelines for the design of reliable and

economical footings (AS2870, 1986). This standard was updated twice, in 1996 and

2011, but remains largely unchanged in relation to the design philosophy and approach.

The standard provides a simplified method to classify the sites by calculating the

characteristic ground movement (ys). Additionally, deem-to-comply footing designs are

provided for each site classification and construction type, which are expected to

tolerate the calculated surface movement. In addition, the standard allows engineers to

design footings from first principles and provides simple design assumptions to follow.

However, in recent years, there have been many reports in the media (ACA, 2012, THE-

AGE, 2011, THE-AGE, 2014a, THE-AGE, 2014b) as well as anecdotal evidence

regarding footing movements and house cracks. The Housing Industry Association

(HIA) has estimated that more than 1000 houses in Melbourne’s west have been

damaged due to slab heave (THE-AGE, 2011) while other reports claim that up to 4300

houses could be suffering from this problem (THE-AGE, 2014a). Victoria experienced

a severe drought from 1996 to early 2009 which was broken in 2010 followed by above

average rainfall for two years (BoM, 2012). According to HIA, the damage to the

houses arose due to abnormal moisture conditions in the soil that was created by the

drought-breaking rains. During the drought period, older houses experienced damage

due to edge settlement. But after the breaking of the drought, it was newer houses,

which were built during the drought, which were reported to experience the most

damage (THE-AGE, 2011).

The damaged houses were recorded in most of the Western suburbs (Figure 1-2)

including Melton, Werribee, Hoppers Crossing, Tarneit, Truganina, Deer Park, Point

Cook, and Caroline Springs (THE-AGE, 2011). Cracks in plasterboards and brick wall

ranged from the size of a hairline to more than 20 mm. In addition, interior walls were

lifted off the floor, windows and doors shifted from their frames and the floors moved

causing objects to roll off the floor and tabletops. Figures 1-3 to 1-5 show typical

damage as reported in the media.

4

Figure 1-2: Areas of reported damaged houses

Figure 1-3: Crack in an interior plasterboard lined wall (ACA, 2012)

MeltonCaroline Springs

Hoppers CrossingWerribee

Point Cook

Deer ParkTruganina

TarneitMelbourne CBD

5

Figure 1-4: Another example of a crack in an interior plasterboard lined wall (ACA, 2012)

Figure 1-5: Large crack in a plasterboard lined wall (THE-AGE, 2011)

Further to the media reports, the author of this thesis has been involved in a number of

damaged houses investigations in association with advisory panel members of this

research programme. Figures 1-6 to 1-9 illustrate examples of damage to houses in the

Wyndham Vale and Taylors Hill areas in West Melbourne.

6

Figure 1-6: A crack in a wall caused by edge lift of footing (Photo taken by the author)

Figure 1-7: Crack appeared in a wall caused by edge lift of footing (Photo taken by the author)

7

Figure 1-8: Separation of up to 50mm in a wall and the window frame caused by footing movement

(Photo taken by the author)

Figure 1-9: An internal wall has been lifted by roof truss due to edge heave of footing (Photo taken

by the author)

8

It appears that changes in the climate conditions, caused by back-to-back extreme

events, have contributed substantially to the damage observed in these houses.

Importantly, the above-mentioned problems have occurred despite these houses being

designed according to the Australian standard. This has raised question whether the

current standard is capable of capturing ground movements due to recent climate

changes. Moreover, as these damages are observed in the western part of Melbourne

which has moderate to highly expansive basaltic clay soils, the moisture changes and

subsequent ground movement of such clay soils is needed to be thoroughly examined.

The inappropriate procedures for design, construction and maintenance of houses on

expansive soils could lead to damage and hence require identification and vigilant

attention.

The houses built during the drought were designed based on the 1996 edition of the

standard. This edition used climate data from 1940-1960 to define the parameters of ys

calculation. While certain changes were made in the latest edition in 2011, the climate

consideration in ys calculation is still not clearly explained and has been questioned by

many researchers (Leao and Osman, 2013, Karunarathne et al., 2012, Lopes and Osman,

2010). However, it must be noted that Australian climate conditions have changed and

more extreme weather conditions can be expected (Austroads, 2004). As a result,

designing footings for soil moisture changes based on past climate conditions may not

be appropriate and more frequent modifications may have to be included for the

standard.

The aim of this doctoral research is to provide further understanding of the behaviour of

expansive soils in Western Melbourne and investigate the expected surface movement

due to seasonal climate changes. The following section describes the specific objectives

of this research.

1.2 RESEARCH OBJECTIVES

I. Review key characteristics of expansive soils and associated recent findings

from field and laboratory studies in Australia.

II. Review the effects of climate on expansive soils and establish likely effects on

soils from changes of climate conditions.

9

III. Undertake a comprehensive study of typical expansive basaltic clay found in

West Melbourne through field sampling and laboratory investigation.

IV. Establish typical behaviour of expansive soil in the field over multiple seasons

through ongoing monitoring of a field site. The results from this work will

establish data for calibration and validation of analytical models

V. Develop an analytical model to predict the moisture and suction variation of

expansive soils under varying climate conditions. Further, use the model output

to predict the ground movement using other tools.

VI. Use the validated model to predict the ground movement for different climate

conditions and site conditions.

1.3 OVERVIEW OF THE RESEARCH METHODOLOGY

A literature review was undertaken to acquire a thorough understanding of the

behaviour of expansive soils under moisture changes and the available estimating

methods, particularly emphasising the procedure given in Australian Standard. The

reports on research and forensic investigations of soil moisture changes and ground

movement were studied to determine the causes and the consequences. Moreover, the

climate consideration approach used in the current Australian footing design standard

was critically investigated. The recent changes of climate conditions in Victoria and its

effects on soil moisture were also examined. Subsequently, the changes of expansive

soil properties in response to moisture changes were studied using various laboratory

experiments. These studies were required to select the most appropriate approach to

develop a prediction method.

A field site was established in one of the Western suburbs in Melbourne where

expansive soils are widely spread. The site has a consistent profile of typical basaltic

clay. The moisture content at various depths, and the subsequent soil movements were

regularly monitored using the most sophisticated equipment available at the time of the

study. Soil samples were collected at different depths. A laboratory investigation was

conducted to develop a comprehensive database for that site, including the basic

properties and more specific properties such as the soil water characteristic curve,

hydraulic conductivity and mineral composition. Soil moisture changes at different

10

depths and the corresponding ground movements were monitored regularly. The climate

data during the monitored period was collected from a nearby weather station.

A finite element approach was implemented to model the soil moisture changes due to

climate conditions. The Vadose/w package, available in GeoSlope software, was used to

develop the model. The material model was developed using extracted soil properties

from the Braybrook site and climate data was used as an input parameter. This model

was validated against the monitored soil moistures from a Neutron probe. The validated

model results were then used in a different software to investigate the ensuing ground

movement. The development of a ground movement prediction model was a part of this

major research programme but not form part of this thesis. However, the results are

reported herein. The results of the model using the Vadose/w are compared with

AS2870 standard estimations in this thesis. The validated Vadose/w model was then

used to investigate the soil moistures due to different climate scenarios including

drought and wet periods. The subsequent ground movements were also compared. The

model was extended to investigate the soil moisture changes beneath footings due to

different situations on adjacent open ground. Climate effects and various manmade

causes were investigated to predict the abnormal soil moisture changes beneath

footings.

1.4 PERCEIVED SPECIFIC CONTRIBUTIONS OF THE RESEARCH

Using up-to-date technology and equipment, a complete test series related to expansive

soil was performed within a reasonably short time period. The behaviour of expansive

soil in typical basaltic clay soil area was thoroughly investigated in this study. As a

result, a comprehensive data set was developed and published which is beneficial for

both practitioners and researchers. More specifically, a series of shrink swell tests were

performed using undisturbed soils at various in situ moisture contents. These test results

indicated the dependency of shrink swell index on in situ moisture content. This

contradicts the Australian standard-AS1289 which states the shrink swell index as a

constant for a given soil type.

The validated analytical model is capable of predicting soil moisture changes due to

climate variations. The model can be used to estimate the expected soil moisture and

suction profiles within a lifespan of a structure. The model was used to investigate the

11

soil moisture changes due to long-term climate conditions including various extreme

events. The model was also used to study the moisture changes of sites with different

soil types. Furthermore, the model was used to investigate the moisture changes caused

by different site situations such as sloping ground.

The soil moisture predictions from this model were also used to investigate the ground

movement in another part of the research programme. In this thesis, ground movement

predictions from the model were compared with the ys calculations based on the lab

testing and the Australian standard. Hence, the outcome of this doctoral research is

valuable in assessing the footing design procedure given in the current Australian

standard and for its further modifications.

1.5 OUTLINE OF THE THESIS

Following the introduction of this PhD research given here, the next chapter provides a

comprehensive literature review associated with the characteristics of expansive soils.

The reasons for volume changes in expansive soils are discussed in Chapter 2 together

with the influences of ground movement on the design of footings on expansive soils.

The recent findings of research investigations in the expansive soils field are also

discussed in the next chapter.

Chapter 3 provides a critical description of the standard procedure of considering the

effects of climate conditions on footing design given in AS2870. The issues related to

employing Thornthwaite Moisture Index to evaluate the soil moisture condition in

response to climate conditions are discussed with example calculations. Furthermore,

certain issues of calculation of ground movement given in AS2870 are presented in

Chapter 3.

Chapter 4 describes the field and laboratory investigation performed in this study. The

selection criterion of the field site to monitor the expansive soil behavior is explained.

Moreover, the soil characterisation and the development of specific properties of

expansive soils are presented in this chapter.

Chapter 5 presents the field instrumentation used for regular monitoring of soil moisture

changes and subsequent ground movement. The analysis of collected data over a two-

year period is also discussed.

12

Chapter 6 explains the development of the finite element model to predict soil moisture

changes in response to climate conditions. The 1D model was validated using data

collected from the site monitoring. Hence, a comparison of field measurement and the

model outcomes is presented in this chapter. The one-dimensional model was also

extended to a two-dimensional model to observe the soil moisture movement in the

lateral direction. Therefore, the details of two-dimensional model development are also

provided in this chapter.

Chapter 7 discusses the applications of the developed finite element models. The one-

dimensional model was used to observe soil moisture changes in long-term climate

conditions. The effects of recent extreme climate events on soil moisture conditions

were studied using finite element models. The model results were used to identify the

changes in parameters required to calculate the ground movement based on AS2870.

The model results were also used to obtain ground movements using another model

developed as a part of this comprehensive research programme. The ground movement

predictions from the AS2870 procedure and from developed models are compared in

Chapter 7. Furthermore, the two-dimensional model was used to simulate the changes in

edge moisture variation in response to different climate conditions, and those changes

are compared with the guidance from AS2870.

Chapter 8 provides a summary of the conclusions of the many aspects of this research

study and presents the recommendations for future research.

13

2. LITERATURE REVIEW

2.1 INTRODUCTION

The investigation of climate induced soil moisture changes in expansive soils requires a

thorough understanding of the fundamentals of expansive soil behaviour. Certain soil

properties are sensitive to the moisture changes and hence they can be used to describe

the expansive characteristics of the soil. The mechanism of the moisture changes and

the subsequent volume changes provides the background to predicting the expected soil

moisture changes. The first part of the literature review focused on studying the

expansive soil behaviour, soil properties and their responses to moisture variations.

Next, the details of recent research and forensic investigations were examined to

determine moisture changes and their consequences on residential structures. Finally,

the standard approach to Australian residential footing design on expansive soil is also

reviewed and explained in this chapter, with an emphasis on the estimation of soil

moisture variation. The following section describes the behaviour of expansive soils due

to moisture changes.

2.2 EXPANSIVE BEHAVIOUR OF SOIL

2.2.1 Overview

Expansive soil is susceptible to volume changes in response to variations in moisture

content. Expansive soils swell on wetting and shrink on drying by significant amounts

(Walsh and Cameron, 1997) and are often termed “reactive soil”. The clay consists of

fine grained material with particles smaller than 0.002 mm (ASTM-D422, 2007). As

such, clay content of the expansive soils governs the reactivity (Gray and Allbrook,

2002). Clay is a general term including many combinations of one or more minerals

with traces of metal oxides and organic matter (Guggenheim and Martin, 1995).

Geologic clay deposits are mostly composed of sheet silicate minerals with water

trapped in between the mineral structure (Nelson and Miller, 1992). These smaller

particles combined with the layered crystalline composition produce properties of

plasticity during wet conditions and significant strength during dry conditions (Nelson

and Miller, 1992).

14

Effect of the expansive clay content on soil reactivity has been measured with respect to

the Coefficient of Linear Extensibility (COLE) by Gray and Allbrook (2002). They

carried out experiments on various soils in New Zealand and noted that COLE linearly

increases with the clay content. Specifically, it was observed that shrink–swell potential

is governed by the amount of water absorbed and desorbed from soil surfaces (Gray and

Allbrook, 2002). Clay particles can adsorb water due to their surface charge and the

layered arrangement. Therefore, the higher the clay contents the higher the reactivity in

soil. This behaviour can be explained by considering the micro scale factors and is

discussed further in the next section together with the mineralogy of expansive clay.

2.2.2 Mineral composition of expansive clay

Micro scale factors of expansive soils are sensitive to the moisture movements and their

responses can be investigated from the macro scale factors. Mineralogy, pore fluid

chemistry and soil structure are the main micro scale factors of soil (Nelson et al.,

2015). The expansive behaviour of clay soil can be explained using the mineralogy and

its reactions with soil moisture.

Clay minerals primarily consist of microscopic platelets made of silicates of aluminium,

iron and magnesium and they stack to form a layered type structure. A typical

microscopic platelet has negative electrical charges on its surfaces and positive

electrical charges on its edges. The atoms of oxygen, aluminium and/or magnesium

attract cations to equilibrate the imbalances. The various arrangements of those atoms

are the result of different crystalline structures and represent the different clay minerals.

The sheets of these minerals stack on each other and form a sequence to crate the clay

structure. The bond between stacked sheets depends on the arrangement of the charges.

The minerals are grouped according to the stack sequence as shown in Figure 2-1. There

are several clay mineral types, but common soils are mainly composed of Kaolinite,

Illite and Smectite (Galleries, 2014). The Kaolinite group includes Kaolinite, Dickite

and Nacrite whereas the Illite group mainly consists of a rock forming mineral; Illite.

The Smectite group, also called Montmorillonite, includes mainly Montmorillonite,

Sauconite, Saponite and Nontronite (Galleries, 2014). All these minerals contain strong

bonds between the elements of the platelet. The bonds between staked sheets are

different as shown in Figure 2-1. Illite has the strongest bond between its platelets

whereas Montmorillonite has the weakest bond.

15

Figure 2-1: Schematic diagrams of the mineral structure of Kaolinite, Illite and Montmorillonite (Nelson et al., 2015)

The Smectite category is the main type of clay mineral which is sensitive to soil

moisture, and hence governs the reactivity of clay soil (Chen, 1988). Montmorillonite is

the main component in Smectite. In Montmorillonite, the bond between the bases of the

two sheets is formed by weaker Van der Waals forces and thus the sheets will easily

separate at the weak bond. (Nelson and Miller, 1992). Therefore, the inter layer cations

can adsorb moisture. Figure 2-2 shows the swelling process of smectite illustrated by

Likos (2004). This figure shows four consecutive stages of hydration for a smectite

particle that contains two unit layers. Initially, the particles are in dry state such that the

negative charges concentrated on the surfaces and the positive charges are in between

the inter layers. As the water is absorbed by the inter layer cations, smectite layers move

apart which allows for transition from one stable hydration state to the next. Hence, the

gaps between platelets are expanded and the soil volume increases.

The reasons for the above phenomenon can be categorized into three micro scale

mechanisms of water absorption, namely; hydration, capillarity, and osmosis (Wayllace,

2008). Hydration is the attraction of water molecules into the soil. Capillarity originates

due to the pressure difference between two sides of air-water interfaces within the

porous soil fabric. Unsaturated soil pores have built up negative pressure and hence tend

to adsorb moisture. Radius of pore water menisci is inversely proportional to the

magnitude of pore pressure. This is the soil suction phenomenon and it is discussed

further in the succeeding sections. The osmotic water absorption occurs due to

concentration difference of dissolved ions between inter layer pore water and free water

(Wayllace, 2008).

Strong bond

Very weak bond

Strong bondWeak bond

Kaolinite Illite Montmorillonite

16

On the other hand, the water absorption and expulsion in clay minerals is also affected

by the changes of the density due to surcharge forces or compaction (Nelson and Miller,

1992). Collectively, this phenomenon of interaction between water and clay particles

causes the shrink-swell behaviour of expansive soils.

Figure 2-2: Conceptual model of sequential crystalline swelling of smectite (Likos, 2004)

The soil moisture influences in micro scale factors are reflected as shrink-swell

movements in expansive soils and can be qualitatively assessed using properties of soil

(Covar and Lytton, 2001). Plasticity, density and moisture content are the main macro

scale factors, which are used to describe the engineering behaviour of soil. Those

responses are discussed in the next section.

Crystal layer Negative charges on surfaces Interlayer cations

9.7 x 10-10 m

1.2 x 10-9 m

1.55 x 10-9 m

1.83 x 10-9 m

Zero-layer hydrate state

1-layer hydrate state



(a)

(b)

(d)

(c)

Molecular layer of H2O

17

2.2.3 Identification of shrink - swell potential based on soil properties

The basic soil properties vary based on the presence of the above-mentioned clay

minerals in soils. Typically, the high amount of Montmorillonite present in soils can

result in very high Atterberg limits as shown in Table 2-1.

Table 2-1: Typical Atterberg limit ranges of pure clays (Fratta et al., 2007)

Clay mineral Liquid limit % Plastic limit %

Kaolinite 35 - 100 25 - 35 Illite 50 - 100 30 - 60

Montmorillonite 100 - 800 50 - 100

Many researchers have investigated the links between basic soil properties and the

shrink-swell potential. As a result, a number of correlations have been proposed

(Altmeyer, 1955, Bandyopadhyay, 1981, Hazelton and Murphy, 2007, Holtz, 1959,

Holtz and Gibbs, 1956, Ranganatham and Satyanarayana, 1965) and most of these

correlations are associated with Atterberg limits (AS1289.3.1.1, 2009, AS1289.3.2.1,

2009), linear shrinkage (AS1289.3.4.1, 2008) and shrinkage limits (ASTM-D4943,

2008).

Table 2-2 shows relations given by Altmeyer (1955) using linear shrinkage and

shrinkage limits. Shrink-swell potential is less sensitive to the extreme ends of the

moisture content (Fityus et al., 2005). When moisture content is decreased starting from

wet condition, a significant volume reduction can be observed until the shrinkage limit

is reached (ASTM-D4943, 2008). There is no significant shrinkage if soil moisture is

further decreased. The opposite behaviour can be observed when the moisture content is

increased starting from dry state. No swelling occurs until the moisture content passes

the shrinkage limit but, beyond that, significant swelling can be observed. Therefore,

the soils with lower shrinkage limit may have a wider range for the shrink-swell

movement and hence can be identified as highly expansive. The linear shrinkage test

starts from the liquid limit of the soil which is the highest moisture that the soil would

behave in the plastic state. Therefore, highly expansive soils, which have higher liquid

limits, generally produce a greater amount of shrinkage movement during the drying

process of the linear shrinkage test. Hence, the higher the linear shrinkage amount, the

higher the reactivity of the soil. In conclusion, as shown in Table 2-2, soils with lower

18

shrinkage limit and higher linear shrinkage has high potential for shrink-swell

behaviour.

Table 2-2: Identification of shrink-swell potential using shrinkage limit and linear shrinkage (Altmeyer, 1955)

Shrinkage Limit % Linear Shrinkage % Probable swell % Degree of expansion

< 10 > 8 > 1.5 Critical 10 - 12 5 - 8 0.5 - 1.5 Marginal

> 12 < 5 < 0.5 Non-critical

Holtz and Gibbs (1956) suggested that the plasticity index alone can be used to indicate

the swelling potential of moist clay because both liquid limit and swell potential depend

on the soil’s water absorbability within the plastic state (Nelson and Miller, 1992).

Table 2-3 gives a qualitative assessment on swell potential based on plasticity index

(Holtz and Gibbs, 1956). The soils with a higher plastic index have a wider moisture

content range to behave plastically and, consequently, have a greater potential for

volume change.

Table 2-3: Identification of shrink-swell potential using Plasticity index (Holtz and Gibbs, 1956)

Plasticity Index % Swelling potential

0 - 15 Low 10 – 35 Medium 20 - 55 High

35 and above Very high

In addition to the qualitative measures of shrink-swell potential of soil, various

researchers have developed methods to quantify the shrink-swell movements using

basic soil properties (Seed et al., 1962, Skempton, 1953, Al-Rawas and Goosen, 2006).

Most of the relationships have been developed for compacted expansive soil however,

Chen (1988) proposed an empirical correlation to determine the swell percentage (S) of

undisturbed soils using plasticity index (PI) as shown in Equation 2-1. This relationship

was developed using swell results under surcharge of 6.9 kPa for soils with dry density

between 16 - 17.6 kN/m3 and limited moisture variation. For that particular range of

soils, A and B constants are equal to 0.0838 and 0.2558, respectively.

19

𝑆 = 𝐵𝑒𝐴(𝑃𝐼) ……………………………………………………….…… Equation 2-1

In conclusion, it is difficult to obtain a reliable estimation of shrink-swell movements

for a wide range of soils using basic soil properties. This is observed in the liquid limit

and volume change data plotted in Figure 2-3 (Kay (1990). The measured results are

highly scattered regardless of the qualitative assessment. Delaney et al. (2005)

attempted to find a correlation between the shrink-swell test and other basic soil tests

including linear shrinkage, plastic index and liquid limit but they concluded that a

considerable scatter exists in relationships of soil reactivity and basic properties. A

number of rigorous procedures, specific test methods and instruments have therefore

been developed to quantitatively measure the volume change of soil (Fityus et al., 2005,

Golait and Wakhare, 1999, Jennings et al., 1973, Jennings and Knight, 1957, Mitchell,

1979, Sridharan, 1999). However, the quantitative measurement of volume change

using laboratory test methods is out of the scope of this thesis.

Figure 2-3: : Index test correlation – Volume change vs Liquid Limit (Kay, 1990)

The above-mentioned properties are constants for a particular soil type. However,

certain soil properties vary with the soil moisture and therefore they can be used to

0 20 40 60 80 100 1200

10

20

30

40

50

60

70

Extremely expansive

Highly expansive

Vol

ume

chan

ge (%

)

Liquid limit (%)

Salinity > 10000 ppm Salinity < 10000 ppm

Moderately expansive

20

explain the expansive behaviour against moisture variation of the soil. The Atterberg

limits and linear shrinkage, which are correlated with shrink-swell potential as described

in the previous section, are obtained from disturbed and sieved soil samples. Hence,

they do not reflect the effect of soil structure. Some properties of undisturbed soils are

associated with the arrangement of particles and the pore structure. Pore structure of soil

is affected by hydration process as described in section 2.2.2. Therefore, undisturbed

soil properties vary with the moisture content changes. The following section describes

the soil properties affected by the moisture content.

2.2.4 Effects of moisture changes on soil properties

2.2.4.1 Soil suction

The main soil parameters used to describe expansive behaviour resulting from moisture

variation are suction and permeability. Both of these properties depend on the

arrangement of the pore structure. Among the various properties of soil, suction is

widely used to describe the expansive behaviour. It is one of the main stress state

parameters of the constitutive models developed to quantify volume changes (Alonso et

al., 1990, Alonso et al., 1999, Fredlund and Rahardjo, 1993, Fredlund and Vu, 2003,

Jones et al., 2009). The suction is defined as the potential of soil water in a soil

undergoing changes (Mitchell, 1984b). This potential arises due to two main

components usually referred to as “matric suction” and “osmotic suction” and the

summation of these two components is called “total suction”.

The matric suction depends on the pore structure which governs the capillary tension

(Mitchell, 1984b). A porous medium has an ability to absorb and hold a certain amount

of water due to its capillarity, texture and surface adsorptive forces. The openings

between soil particles are termed “necked” capillaries, which can absorb and hold water

until the maximum possible quantity under gravity is reached (Shroff, 2003). The water

held within the capillaries is in the state of negative pressure, which is identified as the

matric suction of the soil corresponding to particular moisture content. When the

moisture content of the soil is increased, the negative pressure in the held water is

reduced. Therefore, the matric suction reduces with increasing soil moisture content.

At saturation, all the pore spaces are completely filled with moisture that results in zero

matric suction. Therefore, the matric suction at the water table is zero. The suction

21

variation along the soil depth above the water table is called suction profile. Suction

profile can be identified using a saturated soil column as shown in Figure 2-4, which

shows the matric suction variation of soil column placed on a water container. The soil

column (Figure 2-4_b) is initially saturated and then allowed to drain from the bottom

under gravitation forces. The water level of the container is similar to the water table of

a soil profile. A certain height of the soil above the water level remains saturated with a

non-zero suction (Figure 2-4_a) due to capillary tension of soil pores. Once the

capillary tension passes a certain limit, the air starts to enter into soil pores. The air-

water interfaces of the pore water are curved towards water phase (Figure 2-4_c) which

indicates lower pressure in the water than in the air phase, which in turn indicates that

the pore water is in negative pressure state. This negative pore water pressure is the

matric suction, which generally measures in kPa units. The conventional unit of suction

is pF which is the logarithmic value of equivalent pressure of a water column in

centimetres (Schofield, 1935).

Figure 2-4: Matric suction variation of a soil column(Nelson et al., 2003)

The osmotic suction component, also known as solute suction, is the negative pore

water pressure created by the dissolved ions in soil moisture (Nelson et al., 2003). For

example, this is equal to the pressure difference of a pool of water which is divided by a

hd

MAT

RIC

SU

CTI

ON

, h c

DEGREE OF SATURATION100%

(a) (b)

WATER

SOLIDS

AIR

Uw = WATER PRESSURE

Ua = AIR PRESSURE

R

(c)

22

semipermeable (i.e. permeable to water molecules only) membrane such that one side

contains a solution identical in composition with the soil moisture while the other side

contains pure water (Aitchison, 1965). This is illustrated in Figure 2-5. The

semipermeable membrane shown in Figure 2-5 allows water molecules to pass through

but prevent salt molecules passing through. Then, a pressure will build up at the side of

salt solution, which is reflected in the height difference of the salt and pure water

columns in Figure 2-5. This pressure is the osmotic suction. Based on that illustration,

the osmotic suction varies due to dissolved salt in soil water. The presence of dissolved

ions in water reduce the energy state of the soil by reducing soil vapour pressures and

relative humidity, which ultimately increases the total suction (Nelson et al., 2003). The

higher the salt concentration in soil moisture the higher the osmotic suction in soil.

Figure 2-5: Osmotic pressure across the semipermeable membrane (Nelson et al., 2003)

Osmotic suctions of salt solutions are generally used to calibrate the suction

measurement equipment such as filter papers and psychrometers (ASTM-D5298, 2003,

ASTM-D6836, 2008). Osmotic suctions can be calculated using available relationships

(Lang, 1967, Bulut, 2001) and the standard salt solutions are readily available in the

literature (Goldberg and Nuttall, 1978, Hamer and Wu, 1972, Goldberg, 1981, ASTM-

D5298, 2003).

ho

SEMIPERMEABLE MEMBRANE

PURE WATER

SALT SOLUTION

23

In conclusion, total suction is influenced by the amount of moisture in soil pores and the

concentration of salts in soil moisture. However, for some soils, osmotic suction, which

is driven by salt concentration, can be constant over a certain moisture range as shown

in Figure 2-6. Soil suction is preferred over the moisture content in expansive soil

research sector as it represents the stress state of the soil (Fredlund and Rahardjo, 1993).

Therefore, the variation of suction with moisture content is the most important function

in describing expansive soil behavior. The following section describes the importance

of that relationship.

Figure 2-6: Measured total, matric, and osmotic suctions for Glacial Till from Chao (2007) after Krahn and Fredlund (1972)

2.2.4.2 The moisture characteristic

The same value of suction leads to different moisture contents of soils with different

textures (Mitchell, 1984b). The stress state of the soil depends not only on the moisture

content but also on the pore arrangement. Figure 2-7 shows the suction versus moisture

content variation for different soils in Adelaide, South Australia, as measured by

Mitchell (1984b). According to the curves in that figure, the higher the plasticity index

(PI) the higher the suction at a given moisture content. Table 2-3 concludes that the

higher the PI, the higher the expansiveness of soil. Therefore, observation of Figure 2-7

8 10 12 14 16 180

500

1000

1500

2000

2500

3000

Suc

tion

(kP

a)

Moisture content (%)

Total suction Matric suction Osmotic suction Osmotic + Matric suction

24

indicates that the highly expansive soils have higher suction values at given moisture

contents compared to less expansive clays. That is, at a particular suction (or stress

state) highly expansive soils can hold more moisture than less expansive clays. This

moisture holding capacity depends on the clay content and the clay type of the soil

(Mitchell, 1984b). The higher the clay content, the higher the value of moisture content

at a given suction (Morris and Gray, 1976). Therefore, highly expansive soils have

lesser slope in the suction and moisture relationship, as shown in Figure 2-7. The

relationship between soil suction and moisture content is called Soil Water

Characteristic Curve (SWCC) and the slope of the SWCC is called soil moisture

characteristic.

Figure 2-7: Measured soil moisture change with suction for some Adelaide soils (Mitchell, 1984b)

Figure 2-7 shows the variation of suction against moisture. However, in most expansive

soil studies, suction has been used as the independent variable and volumetric moisture

content is plotted against it (Chao, 2007, Fredlund, 2000, Fredlund and Rahardjo, 1993,

Hung, 2002, Likos, 2000). This is because the suction represents the stress level and one

of the main constitutive parameters of expansive soils.

Figure 2-8 shows typical features of a SWCC explained in Fredlund (2000). SWCC can

be developed in two different ways. The moisture content of initially dry soil can be

increased incrementally and the suction measured, to develop the wetting curve. The

Moisture Content %

Tota

l Suc

tion

(pF)

10 20 30 40 50

7

6

5

4

3PI=4 PI=22 PI=31

PI=45

PI=76

PI=101

25

drying curve can be developed by decreasing moisture from initially wet soil. Typically

these methods produce two different curves for SWCC. The non-uniform pore

arrangement is the main reason for this hysteresis of SWCCs from drying and wetting

methods (Fredlund and Rahardjo, 1993).

Figure 2-8: Typical shape of a SWCC (Fredlund, 2000)

Three phases can be identified in a typical soil moisture characteristic curve including

the boundary effect stage, transient stage and residual stage (see Figure 2-8). Two major

points can be identified in SWCC which divide the three stages; the air entry value and

the residual water content. The air entry value is the suction corresponding to the point

at which air begins entering into the saturated soil pores (Chao, 2007). Beyond the

residual water content, a very large suction should be provided for further removal of

moisture from the soil (Fredlund and Xing, 1994). Therefore, SWCC has mild slopes

during boundary effect stage and residual stage. It has a steeper slope in the transient

stage and this slope is the soil moisture characteristic, which is actually shown in Figure

2-7. Most of the volume changes in expansive soil occur during the transient stage. The

slopes of these three stages depend on the soil type (Fredlund, 2000, Fredlund and Xing,

1994). SWCC starts at saturated state that corresponds to very low suction. Suction

26

becomes substantially higher in low moisture contents. In general, the suction value at

zero moisture content is approximated to 106kPa (7 pF) in Fredlund and Xing (1994).

Some experimental data (Croney and Coleman, 1961, Richards, 1965, Mitchell, 1984b)

also confirms that it would be less than 106 kPa. A more detailed description on

developing SWCC is given in Chapter 4.

In addition to suction, the moisture flow rate is also affected by the pore structure and

moisture content. These changes can be identified from the permeability of soil at

different suction levels, which is described in next section.

2.1.2.3 Permeability

The permeability of soil describes the rate of moisture flow through the porous structure

of soil. The pore structure determines the path, length and the available cross sectional

area for moisture flow (Fredlund and Rahardjo, 1993). The clay soils have lower

permeability than sandy soils due to their closely arranged pore structure with finer

particles. Changes of conductive area can result in changes in permeability. Since the

pore structure is influenced by the volume change behaviour, the permeability of

expansive soils varies with the moisture content. In addition to the changes of pore

arrangement, fissures and layered soils also significantly contribute to the permeability.

Unsaturated soil pores are filled with both air and water. Therefore, when the

permeability of fluid through unsaturated soil pores is considered, both air and water

phases need to be taken into account. Therefore, it is difficult to measure the

permeability of unsaturated soils. Moreover, the compressibility of air in soil pores

creates uncertainties in these estimations. (Ng and Menzies, 2007).

When the permeability of moisture is considered, the driving potential of moisture flow

is important. The moisture flow can occur due to pressure difference or moisture content

difference at two points. However, the most suitable driving potential to be considered

is the energy difference of the points. The energy state of a point depends on the

hydraulic pressure, elevation and the velocity (Fredlund and Rahardjo, 1993). The

moisture flow through unsaturated porous mediums at different moisture contents is

commonly described using Darcy’s flow equation (Fredlund and Rahardjo, 1993).

Darcy (1856) developed an equation to calculate the rate of water flow through soil

using the energy state of the soil (Equation 2-2).

27

𝑣𝑤 = −𝑘𝑤

𝜕ℎ𝑤

𝜕𝑦 .……………………………………………………… Equation 2-2

where, vw is the flow rate of water, kw is the coefficient of permeability of the soil and

𝜕hw/𝜕y is the hydraulic head gradient in the y direction. According to Darcy, the flow

rate of water is proportional to the hydraulic head gradient. The coefficient of

proportionality is the permeability of the water phase and is also known as hydraulic

conductivity. Hydraulic conductivity is positively associated with moisture flow such

that the higher the hydraulic conductivity of the soil, the higher the capability of

moisture to flow through the soil. The hydraulic conductivity is constant for saturated

soils whereas it is a function of matric suction for unsaturated soils (Fredlund and

Rahardjo, 1993). This function is called hydraulic conductivity function which

describes the rate of moisture flow at different suction levels of the soil. A further

description on developing a hydraulic conductivity function is given in Chapter 4.

Since the expansive soil properties described in the sections above are dependent on

moisture changes, it is important to identify the reasons behind the soil moisture

changes. There are various causes of soil moisture changes and identifying them is

highly useful in the prevention of structural damage and to decide suitable remedies.

The following section describes possible causes for soil moisture changes.

2.2.5 Reasons for soil moisture change

Soil moisture changes occur as a result of various causes. The natural causes arise from

the environment that makes soil to absorb or desorb moisture. The main natural cause is

the climate condition. Several components of climate condition affect the soil moisture

in different ways. Precipitation is the main component, which increases the soil

moisture. Evaporation is the next important component and it causes loss of moisture

from surface soils. Relative humidity affects the moisture transfer between atmosphere

and soil and mainly governs the rate of evaporation from the surface. The climate

condition can be categorized as normal or extreme, depending on the amount of

influence from each component. Extreme conditions include floods and droughts, which

can cause substantial changes in soil moistures. The climate influences are generally

considered in design of footings for structures. However, the extreme conditions are not

28

predictable and therefore cannot be fully accounted for in the design. More details on

climate effects on soil moisture are given in Chapter 3.

The next important cause of soil moisture change is the influence of vegetation.

Vegetation, including trees, shrubs and grass covers, can deplete moisture from soil and

discharge to the atmosphere through a transpiration process. The effect of vegetation on

soil moisture depends on many factors including type of vegetation, root depth and root

sizes (Biddle, 1998). In general, the effects of trees are included when designing

residential footings however, a more specific approach would be effective which

considers the effects of different tree species, gardening, and grass covers. The

consideration of tree influence on soil moisture is a part of this group research

programme but it is not within the scope of this doctoral thesis.

In addition to those natural causes, there are various man-made causes that change the

moisture contents of soil beneath structures. These causes are mainly maintenance

issues such as water pipe failures, leaks and inappropriate gardening around houses.

Maintenance issues such as these can produce abnormal changes in soil moistures

which can outburst as differential movements in soil and footings. Importantly, these

issues can be minimized with proper maintenance and preventive measures. Since the

magnitude of these types of influences is not predictable, allowances are generally not

included in footing designs.

Based on the anecdotal evidence, in most situations, expansive soil problems arise not

only due to a single reason, but also due to a combination of several reasons. Therefore,

it is very complex to determine and fix the causative problems before taking remedial

actions. In contrast, a number of research investigations are performed to quantify

expansive soil behavior due to moisture changes. Moreover, forensic investigations

have been performed to ascertain the specific reasons behind residential property

damages due to expansive soil problems. The following section describes the

investigations of expansive soil problems, which are important in predicting moisture

movement and consequences.

29

2.3 INVESTIGATIONS ON EXPANSIVE SOIL PROBLEMS

2.3.1 Expansive soils - a global issue

Expansive soils are widely found in many countries in the world. Reported expansive

soil sites shown in Figure 2-9 indicate that in addition to Australia, expansive soils can

be commonly found in USA, Canada, South Africa, India, China, Israel, etc. The

expansive soils in these countries affect light structures and road pavements, and

researchers from across the globe undertake relevant research to reduce their adverse

effects.

Figure 2-9: Global distribution of reported expansive soil sites (Nelson et al., 2015)

Expansive soils can frequently be found in humid tropics and semi-arid zones in

England with most of these soils having more than 50% clay content with a significant

amount of mica-smectite (Driscoll, 1984). For such locations, seasonal soil moisture

variation under typical climatic conditions is small, and therefore ground movement is

not a major issue. However, the condition of tree drying which causes settlement has

been given most attention in designing light structures (Clarke and Smethurst, 2010).

Many research studies were focused on performance of deep narrow strip footings under

the influence of trees (Cutler and Richardson, 1981, Samuels and Cheney, 1975, Biddle,

2001, Biddle, 1983)

30

Regina, Saskatchewan in Canada is known to have preglacial, lacustrine clay sediments

which exhibit high plasticity characteristics (Nelson et al., 2015). Regina clay soils

have about 50% clay content with a liquid limit of about 80% and plasticity index of

about 50% (Yoshida et al., 1983, D.G.Fredlund, 1975). Lightweight structures built on

these soils may experience about 50-150 mm movement. (Fredlund et al., 2012). There

has been extensive research performed about these soils particularly which focused on

developing equations for SWCC (Fredlund and Xing, 1994).

Highly expansive soils can also be found in some areas of USA. In Colorado, clay soils

found which have liquid limits and plasticity index vary from 35-75% and 15-50%

respectively (Nelson et al., 2015). Those soils have significant influence on lightweight

structures resulting in structural deformations (Chao, 2007). Some buildings have

basements built removing most of the expansive soil within the active zone, but these

structures are subjected to influences of pore pressure rises particularly in initially dry

soils (Nelson et al., 2015). Highly expansive soils have been found in Texas, which can

cause damage to residential structures. Research on these soils led to developing a

standard practice to design suitable footings for those structures (Lytton et al., 2004).

The research studies on moisture-induced ground movement in expansive soils

performed in various parts of the world were mostly associated with field monitoring to

study the various factors affect soil moisture changes. The following section describes

the techniques used in such filed monitoring systems.

2.3.2 Field monitoring systems in expansive soil research

The monitoring of soil moisture content and the subsequent movement has been a

challenging task. Several approaches can be found in the literature. Field investigations

have been performed for many different purposes and a variety of equipment has been

used.

2.3.2.1 Neutron moisture measuring technique

The moisture content can be monitored by occasionally collecting samples at different

depths. However, depending on the available space and the variation of soil properties,

this procedure can be ineffective in the long-term. A non-destructive and repetitive

method is necessary to perform long-term monitoring of soil moisture. The neutron

probe moisture measuring technique is the most suitable method and is an indirect

31

method of moisture measurement. The neutron moisture measuring technique was

developed more than 60 years ago (Belcher et al., 1950) and since then has been widely

used in many different applications including in agriculture, water management and

building design (Chanasyk and Naeth, 1996, Evett et al., 1993, Hupet and Vanclooster,

2002, Nixon and Lawless, 1960, Ren and Li, 2010).

CPN 503DR neutron probe (Ward and Wittman, 2009) was successfully used in most

recent studies (Chan, 2014). Sources of neutrons in CPN 503 DR probes are Americium

and Beryllium. The probe, connected through a cable into the control unit, is inserted

into the access tube and clenched at the required position. The probe emits neutrons

during the measurement as a result of reaction involving Americium and Beryllium.

Americium ( 𝐴𝑚95241 ) is an unstable isotope with an excess of protons. It decays to

Neptunium ( 𝑁𝑝93237 ) by releasing an alpha (α) particle with energy (E) according to

Equation 2-3 (Ward and Wittman, 2009).

𝐴𝑚 → 𝑁𝑝 + 𝛼24

93237

95241 + 𝐸 .…………….....……………………...…… Equation 2-3

Beryllium ( 𝐵𝑒49 ) reacts with the emitted‘α’ particles and is converted into Carbon 𝐶6

13

which then decays to 𝐶612 , releasing ‘‘fast neutrons (n)’’ in the process, as described in

Equation 2-4 (Ward and Wittman, 2009).

𝐵𝑒 + 𝛼24 → 𝐶 → 𝐶6

12 + 𝑛01

613

49 + 𝐸 .…………….………………...…… Equation 2-4

These fast neutrons interact with the soil particles and soil moisture that surround the

probe. The sizes of the neutron and the hydrogen atoms are similar and therefore, in a

collision, much of the energy of the fast neutron can be imported to the hydrogen,

causing the neutron to become slowed, or thermalised (Ward and Wittman, 2009). Some

of these thermalised neutrons are back-scattered back to the detector in the probe. The

concentration of back-scattered neutrons detected is proportional to the concentration of

hydrogen in the soil. Finally, the corresponding moisture content can be obtained

through a calibration curve.

The radius (R) of the neutron scattering (in cm units) shown in Figure 2-10 depends on

the volumetric soil moisture content percentage (θ), as illustrated in Equation 2-5.

32

Hence, the drier the soil, the larger the radius of the neutron scattering sphere and the

smaller the rate of back-scattered neutrons detected.

Figure 2-10: Schematic depiction of neutron probe deployment(Ward and Wittman, 2009)

𝑅 =100

1.4 + 0.1 × 𝜃 ………...…………….....……………………...…… Equation 2-5

The main advantages of using the neutron probe technique is that it is a non-destructive

method which gives reliable, repetitive readings (Chanasyk and Naeth, 1996). This

method overcomes the sample collection procedure and hence it can be used

irrespective to the condition of the sample. This method also facilitates the measurement

of rapid changes of moisture content of soil (Chanasyk and Naeth, 1996). Since the

measurements consider a certain spherical volume of soil to obtain the moisture content,

it could be more reliable than using a fairly small sample to measure the gravimetric

moisture content (Nixon and Lawless, 1960).

However, there are some disadvantages to this technique. First, it uses radioactive

material and therefore requires special protection measures, training and an

authorization is required to use it. In addition, the readings may not represent the

measured depth due to consideration of the spherical volume of soil. However, this is

largely affected only for the layered soils (Nixon and Lawless, 1960). The other main

R

33

drawback of this technique is the difficulty in taking the near surface measurements. It

considers a spherical volume of soil which radioactive material is scattered and

therefore it is ineffective in measuring the soils shallower than the radius of the

influential sphere. The top soil layer is largely affected by the climate variations and

therefore the soil moisture fluctuates more frequently. But it is unlikely to reliably

capture the near surface moisture changes using the neutron probe technique. More

details on neutron probe technique are given in Chapter 5 of this thesis.

2.3.2.2 Monitoring of moisture ground movement

The volume changes of the soil with respect to the moisture variation have also

previously been performed in many places. The primary purpose of these types of

monitoring is related to residential building design applications (Fityus et al., 2004,

Sattler and Fredlund, 1991, Yoshida et al., 1983).

The main challenge of ground movement monitoring is to locate a permanent datum

point. In the late 1950’s, ground movement was measured using precise surveying

equipment and deep bench-marks (Sattler and Fredlund, 1991). In the 1960’s, Yoshida

et al. (1983) used deep bench-marks and vertical movement gauges to monitor soil

movement under a slab. They installed 3 gauges to measure movements at different

depths. Another gauge, inserted beyond 14 m, was considered as the datum. Later,

Fityus et al. (2004) used surface movement probes made constructed with galvanized

steel rods. This technique is similar to the technique used by Yoshida et al. (1983).

Fityus et al. (2004) used 25 mm diameter galvanized steel rods of different depths and

grouted to the bases of 100 mm diameter augured holes. The datum probes were

embedded to 5 m from the surface. One probe gives the movement at one particular

depth therefore they used a number of probes embedded from 0.5 to 3 m depths to cover

the soil layer movements of that site.

In most field studies, magnetic extensometers have been successfully used to monitor

movements of clay barriers, embankments, tunnels, earth dams, etc (Gikas and

Sakellariou, 2008, Liu et al., 2005, Wijeyesekera et al., 2001). The magnetic

extensometers were incorporated with a datum mechanism that was positioned below a

certain depth from the ground surface. According to the reactivity of the soil and the

given Hs, the depth of the datum can be determined by assuming the soil at that depth is

34

stable. The extensometers contain spider magnets placed at certain distances. The

distance of the magnets can be decided according to the number of measurements

expected within the total depth. Figure 2-11 and 2-12 show the spider magnet and the

arrangement of the extensometer. The spider magnets are attached to a collapsible pipe

around a PVC conduit, as shown in Figure 2-12. The legs of the spider magnets

penetrate the surrounding soil after installation and then move up and down along the

PVC conduit with respect to the movements of surrounding soil. The datum magnet is

attached to the bottom of the conduit. A measuring tape with a probe is used to identify

the location of the magnets and therefore can measure the distances between the spider

magnet positions. This tape can measure layer movements with ±2 mm error margin.

Figure 2-11: Spider magnet of the extensometer

35

Figure 2-12: Magnetic extensometer arrangement

The specific details of studies provide more information regarding installation and data

collection. The following sections describe some of the major investigations performed

in Australia over the last few decades. The details of these studies assist in the

development of the most convenient approach to this research programme.

2.3.3 Previous expansive soil research investigations in Australia

2.3.3.1 Swinburne research study in 1970’s

At Swinburne University of Technology, a major research programme was undertaken

in the 1970’s to investigate the Melbourne expansive soil issues on footings. Many

researchers were involved in this programme. Therefore the details of the study can be

found in many theses (Cameron, 1977, Crichton, 1974, Pitt, 1982, Washusen, 1977).

Various conclusions of this study can be also found in other publications (Holland and

Lawrance, 1980, Holland et al., 1980, Holland., 1978, Holland. et al., 1975).

The main purpose of the investigation was to develop a rational and economical method

for residential footing design on expansive soil. There were several field sites

established to monitor slabs in expansive soil areas in Melbourne including in Sunshine,

36

Waverley, Frankston, Keilor and Werribee. Several Ground Movement Stations (GMS)

were installed at each site to observe the soil and slab movements. GMSs consist of a

steel probe and a surface plate, as shown in Figure 2-13. The bottom end of the probe

was placed at a stable depth and anchored to the base of the borehole. A protective

casing was used around the probe and the hole and casing filled with a Cardium

compound to prevent moisture penetration into the borehole. The purpose of the casing

was to prevent the obstructions against the side of the hole. This probe acts as a datum

for the measurements. A surface pate was placed next to the GMS and changes of its

level were measured using an automatic level. An accuracy of ±0.1 mm was achieved

for ground movements. In this method, the top soil movement is measured in reference

to the bottom level of GMS. Hence, GMSs with various probe lengths were used to

measure soil movements within different depths.

Figure 2-13: Ground Movement Stations (GMS) used in Swinburne's study in the 1970s' (Washusen, 1977)

In addition to the ground and slab movements, soil moisture changes were also

measured using hygrometers. The hygrometers consisted of WESCOR thermocouple

probes to measure suction which were placed at 500 mm intervals in a borehole with

compacted clay fill, as shown in Figure 2-14. These probes were installed in open areas

Precise levelling cap Surface plate

Ground movement probe

100mm diameter hole filled with cardium compound to prevent moisture penitration

Protective casing

37

and beneath the slabs. Soil pressure transducers were also installed to determine the

tendency of slabs to lift off due to soil swelling. In this case, before casting the slab, the

soil beneath the slab was levelled, and the transducers were attached to the polythene

moisture barrier between slab and supporting soil. The transducers measure the changes

of bearing pressure when the soil is moving, and the slab is lifting off.

Figure 2-14: Hygrometers used in Swinburne's study in the 1970s' (Washusen, 1977)

Reports of this study identified certain differences in hygrometer results and laboratory

measurements. These differences may be attributed to a number of reasons including

smaller samples used in laboratory measurements, high sensitivity of hygrometer

probes, damages during installations and dissimilarities in compacted soils in borehole

and laboratory samples.

The slab movements were monitored regularly at different sites and the deflected slab

contours were presented. The rainfall and evaporation data were obtained from nearby

Probe leads Metal cover

100mm diameter borehole

Bentonite clay plug moisture barrier (approximately 50-75 mm thick)

Compacted clay soil

Hygrometer (psychrometer) thermocouple at 0.5 m intervals

38

weather stations. These field results of slab and soil movements were presented together

with soil moisture, rainfall and evaporation data (Washusen, 1977). For example, in the

Sunshine site, approximately 20% of the surface moisture change and subsequent

ground movements in the range of 50-60 mm were observed between 1974 and 1975.

Overall, this research has provided a comprehensive data set of expansive behavior of

Melbourne soils. The observed mound shapes of the soil beneath slabs were used to

develop a reliable and economical footing design. Indeed, the outcome of this research

has been helpful in developing a standardized procedure of slab design which is

described in the next sections. However, the prediction of soil moisture movements was

not a part of the study in the 1970s and hence hydraulic properties (e.g., soil water

characteristic function, permeability) of those soils, which are essential to investigate

the soil moisture changes, cannot be found in the relevant literature.

2.3.3.2 Expansive soil site monitoring at Newcastle

In the 1990s, a long term research investigation on expansive soil behaviour was

undertaken in Newcastle (Fityus et al., 2004). In this research programme, moisture

changes and subsequent soil movements were monitored in 20 different sites in the

Hunter area, NSW. This extensive research was aimed at assessing the design procedure

used in New South Wales. There are several publications from this research study

which provide the details of monitoring aspects and also the conclusions of the research

(Delaney et al., 1996, Delaney et al., 2005, Fityus et al., 2004, Fityus et al., 1998, Li et

al., 2003b).

During this research study, laboratory investigations were performed to obtain soil

properties of the monitored sites. Atterberg limits, linear shrinkages, particle size

distributions and cation exchange capacities were investigated (Delaney et al., 2005). In

addition to those soil properties, shrink-well index (Iss) values were obtained in order to

compare the monitoring results with AS2870 standard calculations.

In the field monitoring, soil moisture variations were monitored using neutron probe

technique. Therefore, access tubes were installed at the required depth to collect neutron

probe measurements. The ground movements were monitored using probes similar to

GMS, as explained in the previous section. Surface and sub-surface movement

39

measuring probes were installed at different depths. The site monitoring continued from

2 to 7 years.

Characteristic ground movements were estimated based on AS2870 (1996) guidelines

using Iss values. Delaney et al. (2005) concluded that AS2870 predictions are slightly

lower than the probe measurements but do not considerably under predict the ground

movements. However, some sites showed more than 30 mm surface movement

difference over the predictions. The movement probes at intermediate depths provided

important conclusions. On average, each of the soil layers of depth of 0-0.5 m, and 0.5-

1.0 m contributed 30% to the total movement. Soils at 1.0-1.5m and 1.5m to below

layers contributed 20% each. However, this is dependent on soil type and moisture

changes. The depth of variation of soil moisture was specified in 1996 edition of the

standard as 1.5 m for the Newcastle area. According to Delaney et al. (2005), this limit

causes an under estimation of ground movement due to avoiding about 20% of

contribution from soils below 1.5 m. The profiles indicate that the moisture change

occurred down to about 2.5 m within the monitored period. However, this depends on

the climate conditions of those sites during the monitoring. Therefore, these

observations may not represent the behavior during a life span of a structure and,

consequently, the characteristic ground movement calculations may differ from the

measurements.

This research study provides valuable information on soil moisture and ground

movement monitoring. The details of experimental and analytical investigations given

about neutron probe technique have been presented (Li et al., 2003a, Li et al., 2003b).

However, similar to Swinburne’s research programme, described in the previous

section, the modelling of soil moisture changes was not the primary objective of the

Newcastle study and therefore, some of the required soil properties are not available.

2.3.3.3 Investigation of buried pipes in expansive soil

Recently, an extensive research programme on the expansive behaviour of Melbourne

soils was undertaken in Monash University. The specific aim of the study was to

investigate the effects of climate and soil interaction on buried pipes in expansive soils.

Laboratory and field investigations, together with finite element modelling, were

performed in this research and the details have been previously described (Chan et al.,

40

2007, Chan et al., 2010, Chan, 2014, Kodikara et al., 2013, Rajeev et al., 2012, Rajeev

and Kodikara, 2011).

Two major sites were monitored during this study in Altona North and Fawkner. These

sites were nature strips where service pipes were installed beside the roads beneath the

nature strip. The soils of those sites were mainly typical basaltic clays that continued to

bedrock at about 2 m depth. Basic properties of the soils were investigated at different

depths. In addition, this comprehensive data set includes specific properties. For

example, soil water characteristic curves and hydraulic conductivity functions were

developed for the soils at various depths. Thermal properties required to develop finite

element models to study the soils effect on service pipes were also determined. This

includes thermal conductivity and specific heat capacity functions at different depths.

The field monitoring includes soil moisture, ground movement and temperature

monitoring together with pipe pressure and strains. The soil moistures were monitored

using neutron probe technique similar to the Newcastle study. Custom-built model 4000

rod extensometers, shown in Figure 2-15, were used to monitor soil movement. This

system is commonly used in measuring deformations in tunnelling, underground mining

and dam construction. These rod anchors can measure movements with ±0.1 mm

accuracy (HMA, 2014) and were installed at different depths starting at 400 mm from

surface. Moreover, weather stations were built on each site to collect critical climate

parameters including rainfall, evaporation, humidity, solar radiation, wind speed etc.

Importantly, the surface movements were not measured. The rod anchors used in this

study are very sensitive and can be damaged due to higher movements in expansive

soils. In fact, in this study, the rod extensometer installed in Fawkner site had some

problems and the movements were not able to be captured.

41

Figure 2-15: Model 4000 Borehole Rod Extensometers (HMA, 2014)

The soil moisture and temperature variations were modelled using Vadose/w software

(Vadose, 2013). Figure 2-16 shows the measured and predicted soil moisture in Altona

North during the period of monitoring. This suggests that the model can predict trends

of soil moisture changes against variations of climate conditions.

Figure 2-16: Measured and predicted soil moistures at 300 mm depth in Altona North (Chan, 2014)

42

Most of the conclusions of this buried pipe study were published after 2012 and hence

they were useful at the middle stage of this doctoral research. Even though this study

provides a comprehensive approach for predicting moisture changes in expansive soils,

the variations of soil moisture or suction profiles with respect to long-term climate

conditions have not been considered. However, the collected data, implemented

procedures and the results of this study is further used to investigate the soil moisture

profile variation and subsequent ground movement predictions described in Chapter 7

of this thesis.

2.3.4 Forensic investigations

In addition to the research investigations related to expansive soil behaviour described

in above sections, there have been a number of forensic investigations performed on

damaged houses. According to the media, more than 4300 houses recorded damage after

the drought-breaking rainfall in Melbourne (THE-AGE, 2014a). Most owners of those

damaged homes have relied on expertise in geotechnical and/or structural investigations

to determine the cause of the damages before taking further legal actions.

The forensic investigations were undertaken with a senior geotechnical investigator,

Dominic Lopes, who is also a member of the adversary panel of this research

programme. The author accompanied Dominic Lopes to observe investigations of some

damaged houses. According to the personal communication with him, most of the

damages have occurred due to more than one cause of abnormal moisture changes in

soil beneath footings.

A typical forensic investigation consists of inspecting soil moistures near the damaged

area using samples collected by manual drilling (e.g., beneath the footing at heaved or

settled external walls), taking level measurements of deflected floor slab to develop

contour plots, investigating pipe failures, investigating the possible effects from nearby

trees (existing and already removed trees), the gardening around the houses and

inspecting the design reports of the house. Even if an expert uses these several aspects

in an investigation, it is difficult to ascertain all combinations of reasons for the

abnormal moisture changes. Figure 2-17 shows an example of this difficulty. The

damaged house shown in this figure was less than 5 years old when cracks appeared.

After an extensive investigation, the footing under the damaged wall was under-pinned

43

after addressing the cause of moisture change in 2012. However, the cracks further

propagated over the next two years. In a similar case, Figure 2-18 shows the floor

contours have changed due to the progression of differential movements within a period

of one year, after taking remedial action. These incidents emphasize the importance of

preventing possible causes of abnormal moisture conditions and considering certain

allowances for them at the design stage.

Figure 2-17: Propagated cracks on wall even after remedial actions were taken (A house in Taylors Hill)

Figure 2-18: Contours showing deviations from assumed planar initial condition (in mm) of a damaged house in Wyndham Vale measured over a year

44

The outcomes of these forensic investigations are very useful in identifying weaknesses

in construction, design and maintenance of houses which excessive damages.

2.4 AS2870 FOOTING DESIGN PROCEDURE

Research studies on expansive soils commenced in the early 1950’s in Australia.

Aitchison and Holmes (1953) investigated soil suctions and ground movements and

examined the compatibility of the relationship between soil moisture and movement in

clay soils. Swinburne’s major research study described in section 2.3.3 was followed by

further investigations on designing of footings on clay soils by Walsh (1978) and

Mitchell (Mitchell, 1979, Mitchell, 1980, Mitchell, 1984b). These research efforts led

to the establishment of a standard design for residential footings in Australia called

AS2870, which was first published in 1986. Later, two revised editions were published

in 1996 and 2011.

The standard provides a simplified approach to calculate characteristic surface

movement (ys) . AS2870 classifies the expansive soil potential of a site based on the

magnitude of ys. The ys indicates the probable ground settlement or heave within the

design life, which is considered as 50 years for residential structures. AS2870 describes

ys as a function of instability index (Ipt), soil suction at ground surface (∆U) and the

design depth of suction change (Hs), as shown in Equation 2-6. In general, a suction

profile has a champagne flute shape as shown in Figure 2-19. In the Standard, a suction

profile is considered to be triangular and it is defined using ∆U and Hs. The ∆U and Hs

values depend on soil type and climate conditions, as shown in Figure 2-19. The

Standard also provides some typical values of Hs for certain locations in Australia. The

expected vertical movement of a soil layer of thickness ‘h’ is calculated and then the

total surface movement is obtained as the summation of each layer movement up to Hs.

Ipt, used in Equation 2-6, is considered a constant for a particular soil type (layer) which

accounts for vertical strain per unit suction. The ∆U is in units of suction (pF) and the

‘h’ is given in millimetres, hence ys is in millimetres.

ys = ∑(Ipt × ∆U × h)

Hs

0

…..…………………………………………… Equation 2-6

45

Figure 2-19: Typical wet and dry suction profiles in different Australian regions (Walsh and Cameron, 1997)

The footing design procedure described in AS2870 is based on site classification.

AS2870 (1996) classifies the sites from slightly reactive to extremely reactive using ys.

Highly reactive sites are further divided into H1 and H2 in AS2870 (2011). Table 2-4

shows the site classification given in AS2870 (2011).

Table 2-4: Site classification by characteristic surface movement (AS2870, 2011)

Characteristic Surface Movement, ys (mm)

Site Classification

0 < ys≤ 20 S

20 < ys≤ 40 M

40 < ys≤ 60 H1

60 < ys≤ 75 H2

ys> 75 E

Areas with more than 3 m suction change depths are categorized as deep seated

moisture variation sites and further classified as S-D, M-D, H-D and E-D.

46

Walsh (1978) developed a method to design footings on expansive soil using idealized

mound shapes. The mound shapes are defined by edge moisture variation distance (e)

and differential mound movement (ym). There are two different mound shapes identified

as centre heave and edge heave. Walsh (1978) suggested that ym can be taken as 0.7ys in

centre heave condition whereas 0.5ys in edge heave condition. The requirements of

moment, shear and stiffness are calculated using these ym and e values.

Mitchell (1979) also developed another method to design footings on expansive soils

using a similar approach. He also suggested idealized mound shapes. However, in

Mitchell’s (1979) method ym is taken as 0.7ys for both centre heave and edge heave

conditions. He suggested equations for e distance and depth of embedment of edge

beams using Hs and ym. These values are then used to obtain moment capacity

requirements of the footing.

AS2870 (1996 and 2011) design procedure was derived from both Walsh (1978) and

Mitchell (1979) methods and provides suitable footing types according to the site

classification in the deemed-to-comply provisions. However, it also guides design of

footings for any site classification using engineering principles.

According to the approach described above, the site classification based on ys

calculation is the most significant aspect in designing footings for houses. Therefore,

the calculation procedure of ys needs to be carefully investigated together with the

sensitivity of the associated assumptions. The following section provides the

background of ground movement calculation used in AS2870.

2.4.1 Characteristic ground movement of expansive soil

The quantitative estimation of movement in expansive soil is important in the design of

footings. Since the stress state of the soil is considered in estimating volume changes,

suction has been the commonly accepted soil parameter to obtain the quantitative

measures (Fratta et al., 2007, Mitchell, 1979, Mitchell and Avalle, 1984, PTI, 2004,

Matyas and Radhakrishna, 1968). Soil suction is defined as the potential of undergoing

a change in moisture content (Mitchell, 1984). It is measured as a negative pressure and

expressed in kPa but the conventional units of expressing suctions measurements is pF

(Schofield, 1935). More details on soil suction are given in the next sections of this

chapter.

47

The gradient of SWCC, which is the moisture characteristic (c), is shown in Equation

2-7 where Δw is the change in moisture content and Δu is the change in suction

(Mitchell, 1984b).

𝑐 =Δw

Δu ………………..…..…………………………………………… Equation 2-7

The moisture characteristic depends on the composition of the soil. The higher the clay

content of the soil, the higher its moisture characteristic (Mitchell, 1979). The “c”

values can be used to replace the change in water content in soil in terms of suction.

Mitchell and Avalle (1984) provide a comprehensive description on estimating the free

surface movement of expansive soils in terms of the fundamental concepts associates

with soil suction. They used the saturated soil theory to develop an explanation. The

volumetric strain of the soil can be calculated (Equation 2-8) in terms of void ratio (e),

specific gravity (Gs) and Δw. “V” is the volume of soil and “ΔV” is the change of the

volume. The compressibility factor “f” is to account for the ratio of volume change to

moisture content change (Mitchell, 1984b).

ΔV

𝑉= 𝑓

Δe

1 + 𝑒= 𝑓

𝐺𝑠 × Δw

1 + 𝑒 …………………………………………… Equation 2-8

By introducing a lateral restraint factor (g) to account for the effects from surrounding

soil and the shrinkage cracks during the dry period, the volumetric strain can be

converted into vertical strain as given in Equation 2-9.

𝑔ΔV

𝑉= 𝜀𝑣𝑒𝑟𝑡 = 𝑔𝑓

𝐺𝑠 × Δw

1 + 𝑒 ………………………………………… Equation 2-9

The change in soil moisture given in Equation 2-9 can be replaced by suction using

Equation 2-7 and the moisture characteristic. It is shown in Equation 2-10.

𝜀𝑣𝑒𝑟𝑡 = [𝑔𝑓𝐺𝑠 × 𝑐

1 + 𝑒 ]ΔU …………………………………………… Equation 2-10

48

Rahardjo and Leong (2006) experimentally showed that for a particular soil type (with

constant void ratio and specific gravity) the strain of the soil is proportional to the

suction change and a constant called “Instability index” has been introduced to represent

the linear relationship. It is similar to the constant shown within the brackets in

Equation 2-10. The instability index is denoted by “Ipt”. A further description of this

constant is given in section 2.4.2.3. The Equation 2-10 can be used to obtain the vertical

movement of a certain soil layer of Δl thickness and therefore the free surface

movement (y) can be calculated from the summation of each layer movements down to

the depth of suction change (Equation 2-11).

y = Σ [ 𝐼𝑝𝑡 × ΔU × Δl ] ……………………………………… Equation 2-11

This equation is similar to the Equation 2-6 which is used in AS2870 to calculate

characteristic ground movement.

Mitchell and Avalle (1984) provide clear evidence that Equation 2-11 predicts the free

surface moment with good agreement. They have measured the Ipt by using core

shrinkage and suction tests. The free surface has been measured together with field

suctions. The depth of changing suctions has been decided by the suction profiles

between the considered time intervals and then the free surface movement has been

calculated using Equation 2-11. Figure 2-20 shows the comparison between

measurements from O'Halloran Hill area in Adelaide and the predicted free surface

movements.

49

Figure 2-20: Comparison between measured and predicted free surface movement in O'Halloran Hill, Adelaide (Mitchell and Avalle, 1984)

This procedure has been widely accepted and experimentally supported by different

researchers (Rahardjo and Leong, 2006, Fratta et al., 2007, Mitchell, 1979, Cameron

and Walsh, 1984, Cameron, 1989, Walsh and Cameron, 1997). AS2870 implemented

the procedure explained in Mitchell and Avalle (1984) to calculate the characteristic

surface movement (ys), which is given in Equation 2-6. It is important to investigate the

influences of factors used to calculate ys which are described in the next sections.

2.4.2 Factors affecting ys calculation

2.4.2.1 Design Depth of Suction Change (Hs)

Moisture content of the soil varies with the depth and reaches an equilibrium value at a

certain depth (Fityus et al., 2004). Since the suction is related to the soil moisture

content, the suction throughout the depth can also be identified as a gradual variation

that follows a similar trend.

Figure 2-21 shows typical moisture variations for open ground and under a covered slab

given in Nelson et al. (2001). The profile ‘A’ shows the moisture content variation of

uniform soil for open ground in a dry climate. The moisture content varies from ground

surface up to the depth ‘Zs’ and after that, the equilibrium moisture content value

continues. Above the depth of ‘Zs’ the moisture content varies with the depth and the

time. The changes of suction in soil above the depth ‘Zs’ is affected by various

50

environmental factors including precipitation, evaporation, transpiration and the

location of water table depth (Lu and Griffiths, 2004).

When a slab is placed on expansive soil, the slab becomes a moisture barrier and the

suction profile differs from the typical suction profile of an open ground, which is

shown in profile “B” in Figure 2-21. The soil beneath the slab edge is affected by the

environmental influences at the open ground, and the moisture changes are gradually

reduced towards the slab centre where it is normally assumed that the soil moisture is

more stable. During the dry season, top soil is desiccated and the top soil layers can

have moisture contents lower than the equilibrium value. During the wet season the top

layers are influenced by wetting due to precipitation and can have higher moisture

contents than the equilibrium value. Therefore, during the summer and winter season,

the profile varies around ‘B’ and the profiles ‘C’ and ‘D’ represent the corresponding

variations at two extremes. The slab prevents the moisture loss due to environmental

factors and hence the moisture content reaches an equilibrium value at a depth lower

that Zs.

Figure 2-21: Idealized water content profile (Nelson et al., 2001)

51

The wet and dry suction values usually change rapidly with depth (Fityus et al., 2004,

Fityus et al., 1998). Mitchell (1979) assumed a “trumpet” shaped suction profile (Figure

2-22) to derive the concept of swelling of expansive soil. However, the wet and dry

suction variation is approximated to a triangular shape in AS2870, as shown in Figure

2-23.

Figure 2-22: Theoretical suction profiles given in (Mitchell, 1979)

This triangular shape is defined using surface suction change and the depth of suction

change. The depth of suction change is influenced by many factors including climate,

depth to the groundwater table, type and amount of clay minerals, soil profile, and

vegetation. Different researchers defined the depth of suction/moisture variation of soil

using different terminologies (Hamilton, 1969, Nelson and Miller, 1992). Nelson et al.

(2001) summarized these terminologies such as depth of potential heave, depth of

seasonal moisture variation, depth of wetting, active zone, and depth of suction change,

as illustrated below.

The depth of potential heave defines as the depth at which the overburden vertical stress

equals or exceeds the swelling pressure of the soil (Nelson et al., 2001).

The depth of seasonal moisture fluctuation is defined as the depth of soil in which the

soil moisture content of an open area varies seasonally due to climate conditions at the

ground surface (Nelson et al., 2001).

52

The depth of wetting is defined in Nelson et al. (2001) as the depth in which the soil

moisture increases due to introduction of water from external source due to capillary

action of soil neglecting the evapotranspiration. In a case of cracking clay soils, this

depth can be abruptly increased by the presence of cracks during dry period where rain

water can easily flow in.

Since the shrink-swell behavior of the expansive soil depends on the suction variation as

well as the overburden pressure; the depth of suction variation related to residential

footing design is slightly different from the definitions based purely on moisture

fluctuations. A more sensible definition is given in Nelson et al. (2001), termed “Active

Zone” which is the depth of soil beneath a structure that contributes to the actual heave.

The actual heave may occur due to various climate conditions including extreme events.

The depth of active zone observed in normal seasonal climate conditions is called

‘Design depth of suction change (Hs)’ in AS2870.

The Hs is also affected by the location of bedrock and the ground water table (AS2870,

2011). Based on the location of bedrock and ground water table, the typical values

appropriate to the particular area need to be adjusted, as shown in Figure 2-23. Since,

the suction below ground water table is constant at saturated value; the suction profile

must be modified if the water table is encountered within the defined Hs of the area

(Figure 2-23). If the bedrock is encountered within the specified Hs, the suction profile

will remain same. However the calculation of free surface movement is only considered

up to the depth of bedrock, because Ipt of bedrock is insignificant.

Figure 2-23: Simplified suction profile and the effect of bedrock and water table on ΔU and Hs(AS2870, 2011)

53

2.4.2.2 Suction Change at Surface (∆U)

The difference between wet and dry suctions at the surface is defined as surface suction

change (∆U) (Walsh and Cameron, 1997). AS2870 (2011) provides a single value of 1.2

pF for all specified locations in Australia. However, higher ∆U values have been

recorded in some field monitoring (Fityus et al., 1998, Fityus et al., 2004). The

approximation of the suction profile into a triangular distribution in AS2870 slightly

underestimates the ∆U (Walsh and Cameron, 1997).

2.4.2.3 Instability Index (Ipt)

The amount of volume change of expansive soil in response to change in suction is

represented by the Instability Index, Ipt. Mitchell (1979) suggested a simple method to

obtain the Ipt using the soil strain measured over a certain range of moisture content and

the moisture characteristic. The method is shown in Equation 2-12.

Ipt =

ΔL

L

Δw×

Δw

ΔU ………..…………………………………………… Equation 2-12

The Ipt depends on the vertical strain of soil per unit change in suction which is defined

by volume change indices. There are number of ways to obtain these indices of soil, as

explained in Cameron (1989).

The core shrinkage test (ASTM-D5084, 2003) can be used to obtain the core shrinkage

index (Ics) by using unloaded shrinkage test. The test uses 38 to 65 mm diameter

undisturbed soil samples which has a length of 1.5 to 2.0 times of its diameter. The test

starts from the in situ moisture content and the initial moisture content is measured from

the sample trimmings. The soil samples are then allowed to air dry for a few days before

being placed in an oven to determine the final moisture content. The strain and the

weight is monitored regularly from the beginning to obtain the stain-moisture curve.

The Ics is calculated for the linear part of the curve using shrinkage strain and the

moisture content difference as given in Equation 2-13.

Ics = ε × c

Δw ………..……………………………………………...…… Equation 2-13

54

“ε” is the shrinkage strain and “c” is the moisture characteristic. The moisture

characteristic can be calculated by measuring suctions during the test or assuming

appropriate values. However, this method does not include the surcharge to

accommodate the effects of load coming from footings.

Another method of obtaining Ipt is using a loaded shrinkage test that considers the

surcharge upon shrinkage. A surcharge of 25 kPa, to account the footing load, is applied

during this test and measures the shrinkage stain and the moisture contents. The loaded

shrinkage index (Ils) is obtained using an equation similar to Equation 2-13.

These two methods require measuring the moisture content and the soil moisture

characteristic by measuring the suctions. However, the shrink-swell test (AS1289.7.1.1,

2003) has bypassed the suction measurements and produced reliable results (Fityus et

al., 2005). Walsh and Cameron (1997) also describe the core shrinkage test and loaded

shrinkage test but recommended the shrink-swell test to obtain the instability index.

The shrinkage strain and the swell strain started at the in situ moisture content of

undisturbed soil sample are measured separately during the shrink-swell test

(AS1289.7.1.1, 2003). The shrinkage strain (εsh) is measured from a shrinkage test that

is similar to the core shrinkage test (ASTM-D5084, 2003) but the moisture contents are

not measured. The swell strain (εsw) is taken from a one-dimensional swell test. This test

is performed using a consolidation cell so that only the vertical strain occurs. A

surcharge of 25 kPa is applied during the swelling process to account for the effect of

the footing. Then, the total strain is calculated from εsh and εsw. The free shrinkage test

accounts for the three-dimensional strain with εsh while εsw is a one-dimensional strain

due to lateral restraint applied from the ring. Those two strain values cannot be added

together without correcting the dimensional inequality. Cameron and Walsh (1984)

concluded that the unrestrained three-dimensional strain of the soil is commonly in 0.3

to 0.6 of vertical strain of the laterally restrained soil. This effect must be

accommodated in the context of the results of the one-dimensional consolidation taken

from the laboratory tests. Therefore, the swell strain is divided by a factor of 2

(Equation 2-14) to convert it to the free swell strain before adding to the shrinkage

strain (AS1289.7.1.1, 2003). This factor has been investigated in many studies

(Cameron, 1989, Leong et al., 2002) and was subsequently accepted for use in AS1289

55

(Fityus et al., 2005). Equation 2-14 shows the estimation of shrink-swell index from εsh

and εsw.

Iss =

εsw

2+ εsh

1.8 ..……………………………………………...…… Equation 2-14

Since the instability index accounts for the strain per unit suction, the suction change

during the test must be obtained. However, an advantage of using the shrink-swell index

to obtain Ipt is to bypass the measurement of suction. Since this test considers the total

stain of the soil sample from saturated condition to the oven dry condition, an

approximated value can be used to obtain the suction change during the volume change

process. The researchers in this area suggest the use of the suctions corresponding to the

wilting point and saturation point of the soil (Fityus et al., 2005). This idea is based on

the notion that significant volume change will not occur beyond the limits of the wilting

point and the saturation point of soil. Observations suggest that the wilting point suction

varies around 4.2 pF for clay soil (Cameron, 2001, Wray, 1998). Fredlund and Rahardjo

(1993) argued that the total suction of saturated soil is about 2.2-2.5 pF. Therefore, the

suction change during the total strain of the shrink-swell test has been assumed to be 1.8

pF for all soils (Equation 2-14). In the hand book of AS2870, Walsh and Cameron

(1997) specified that the shrink-swell test is the most appropriate soil reactivity index to

obtain Ipt because it generates a significantly lower coefficient of variation compared to

other tests. It is assumed that the Iss is a constant irrespective of the starting moisture

content of the undisturbed soil sample (AS2870, 2011). However, there is anecdotal

evidence from forensic investigations demonstrating that Iss values can be obtained that

are different to the designed values due to changes to the in situ moistures. The changes

of Iss affect the estimation of ground movement. Therefore, this issue has been further

investigated using experimental results by the author and it is described in Chapter 3.

Both accurate research techniques and practical engineering procedures need to be

considered to derive the instability index from the soil reactivity indices. The soil

beneath the surface cannot swell freely because of lateral restraint by the surrounding

soil and the surcharge due to the weight of the above soil layers. During the shrinking of

clay soil, the lateral restraint is not affected and the cracks will propagate to a certain

56

depth. The probable crack depth depends on many factors including the soil type,

shrinkage amount, moisture content and depth of soil layers. During the swelling

process, the soil can freely swell until the cracks close and then the three-dimensional

swell ceases as the lateral restraint is initiated by the adjacent soils. Then, the swell

would occur more over the vertical direction and will be controlled by the surcharge

pressure.

Ipt is derived from reactivity indices by modification by a specific restraint factor (α)

depending on the site condition (AS2870, 2011). The restraint factor accounts for the

effect of cracks and the surcharge by assuming that, below 10 m depth, no soil

movement occurs. Hence, ‘α’ at depth ‘Z’ from the ground surface is defined by

Equation 2-15 for the uncracked zone (AS2870, 2011). The factor, α is taken as 1 for

the cracked zone to represent zero restraint.

α = 2.0 −Z

5 ……...……………………………………………...…… Equation 2-15

Figure 2-24 illustrates the use of Equation 2-15 to obtain Ipt from the various Iss values

at different soil depths. Since the soil in the uncracked zone is highly affected by the

lateral restrain from the surrounding soil, the instability index has been increased by the

“α” factor.

Figure 2-24: Sample calculation of Ipt from different Iss values for cracked soil

Even though AS2870 considers these factors of soil moisture changes and reactivity to

estimate the ground movement, the outcome of the standard procedure has certain

Iss = 3%

Iss = 4%

Iss = 4.5%

Iss = 6%

1 m

1 m

1 m

2 m

α = 1

α = 1

α = 1.5

α = 1.2

Ipt = 3%

Ipt = 4%

Ipt = 6%

Ipt = 7.2%

Crack

depth

= 2 m

57

limitations. Therefore, homeowners have been constrained to a particular way of usage

and maintenance requirements to prevent abnormal moisture changes beneath footings.

Those limitations are described in next section.

2.5 LIMITATIONS OF SOIL MOISTURE PREDICTIONS

2.5.1 Effectiveness of AS2870 design procedure with changes in TMI

The estimation of soil moisture change and ground movement specified in AS2870 is

principally based on parameters of suction profile; ∆U and Hs. The standard procedure

defines them based on the climate condition of the area. Climate condition is classified

by Thornthwaite Moisture Index (TMI) and is correlated with Hs. In addition to this

correlation, the standard includes a climate zone map of Victoria, which enables the

Victorian designers to pick the TMI of the location and then the corresponding Hs. The

climate zone map given in the 1996 edition of the standard was a part of Australian

climate map developed by Aitchison and Richards (1965) based on climate data from

1940-1960. The climate data suggest that there has been a significant change in climate

condition in Australia in the last few decades and hence past climate data may no longer

represent the current or future conditions (Hughes, 2003, Murphy and Timbal, 2008,

Smith et al., 2009). AS2870 was refined in 2011 and has incorporated some changes to

the TMI ranges. In contrast, the climate zone map of Victoria has remained identical to

the previous version. Since the climate continues to change, further modifications to

AS2870 will be required and this will create complications in designs. On the other

hand, several changes to the normal weather pattern was observed recently and more

frequent extreme climate events are expected (BoM, 2012). Therefore, the dependence

on past climate data in designing footings for 50 years of lifespan appears to be

deficient.

Moreover, the effectiveness of TMI to correlate the soil moisture changes has been a

concern because it relies on many assumptions and different definitions (Karunarathne

et al., 2012). Indeed, there exists various ways to calculate TMI due to different

definitions of the associated parameters. Furthermore, researchers have used different

numbers of years to calculate the average TMI from yearly calculations and hence their

conclusions on TMI and soil moisture correlations cannot be compared (Chan and

58

Mostyn, 2008, Fityus et al., 1998, Fox, 2000). This issue was critically investigated in

this study, and will be described in the next chapter of this thesis.

In summary, the AS2870 procedure of estimating soil moisture changes, and hence

ground movement, requires review in response to uncertainties in the normal climate

condition. Moreover, foundations in accordance with AS2870 require tight maintenance

to maintain “normal” soil moisture condition and prevent damage to the super structure

as described in next section.

2.5.2 Standard design outcome and home owner’s expectations

Design is based on past climate conditions and therefore soil moistures must be

maintained within the limits of the corresponding normal condition. However, many

influences can create abnormal moistures beneath footings. For example, trees can

absorb moisture from the soils within the root zone and create unexpected dry

conditions. Hence, differential settlements can be observed due to existing trees within

their influential zone. Gardening around the house can also lead to increase moisture

due to watering. Similarly, sloping ground towards the footing leads to increase in the

water available for infiltration. Pipe breaks or leaks can also increase soil moisture.

AS2870 is deemed to provide a reliable and economical footing design. The footings

should therefore be able to tolerate the ground movements to transfer an acceptable

effect into the superstructure. However, AS2870 (2011) provides information about

expectable cracks in walls and floors of houses even if they are correctly designed based

on the AS2870. It stated that cracks less than 1 mm in width do not need to be repaired

whereas less than 5 mm wide cracks can be easily filled. The author inspected some

damaged houses with cracks up to 30 mm in width. Some home owners do not tolerate

that a properly designed and constructed house can have the tolerable cracks stated in

AS2870. Since these cracks are mostly caused by differential movements, a better

system to predict soil moisture changes and estimate ground movement is vital to

provide homeowners with different performance options depending on their

expectations and financial investment.

59

2.6 IMPORTANCE OF A ROBUST METHOD OF ESTIMATING SOIL MOISTURE

CHANGES

Since climate is a parameter varying within periods shorter than lifespans of houses, the

footing design must be based on expected climate conditions. Future climate condition

can be predicted based on various scenarios and hence an effective footing design can

be achieved by using the following options.

I. A design based on predicted future climate condition within the lifespan

II. A design based on probability of severity of extreme climate events

Both approaches require a reliable method of estimating future soil moisture changes

due to climate conditions. Such a method will overcome the limitations of the standard

described in previous section, which is based only on historical data.

A reliable prediction method of soil moisture changes will enable the consideration of

soil moistures and related ground movements due to various climate scenarios including

different frequencies of extreme events. Hence, several footing designs can be

introduced to withstand different severities of climate. This also allows the study of

damage on superstructure due to different climate scenarios. Moreover, a robust

prediction system of soil moisture will facilitate the study of the various causes of

abnormal moistures. This PhD research has focused on developing a better prediction of

soil moisture changes due to climate conditions.

2.7 SUMMARY

This chapter describes the features of expansive soils and the investigations of

expansive soil behaviour in Australia. Expansive soils consist of layered structures that

are formed by platelets of clay minerals. The distribution of charges in these platelets

attracts water, which increases the gap between layers. This phenomenon causes the

volume change in expansive soils. Therefore, moisture changes represent the primary

cause of volume changes in clay soils. Such expansive behaviour can be characterized

quantitatively and qualitatively using several soil index tests.

Since these volume changes can lead to ground movement that can damage lightly-

loaded structures that are built on such soils, much research has been carried out to

investigate moisture-induced ground movements. Most of these studies aimed to

60

develop reliable footing designs that could withstand expected ground movements.

These investigations led to the development of the standard for residential footing

design in Australia, termed AS2870, which was first published in 1986. This Standard

was updated twice, in 1996 and 2011, but remains largely unchanged in relation to the

design philosophy and approach. Specifically, there are certain issues in considering

climate effects on footing design in the AS2870 including the use of historical climate

data. Moreover, there has been some severe climate condition in Victoria, Australia

which led to significant damage to some houses. It is therefore imperative that we

review the Standard procedure of estimating soil moisture changes and ground

movement.

A number of studies have informed the management of impacts of expansive soil

behaviour on structures. In the 1970s, a comprehensive study was undertaken at

Swinburne University that focused on the performance of residential footings built on

expansive soils at various places around Melbourne. The hygrometer mechanism was

used to monitor soil moisture changes whereas ground movement stations were used to

measure surface movements. Another field investigation was undertaken at the

University of Newcastle, to investigate the moisture and ground movements in an open

ground and under a flexible cover. The neutron probe technique was used to monitor

soil moisture changes while surface and sub-surface movement were monitored using

probes. This research revealed the rainfall variation, seasonal ground movements and

the corresponding variation of mound shape beneath the flexible cover. Other, more

recent, research was undertaken at Monash University to determine the performance of

buried pipes in expansive soils. The neutron probe technique and rod extensometers

were used to monitor moisture and ground movement, respectively. Soil moisture

changes in response to climate conditions were modelled in this research using field

measurements taken from two expansive soil sites in Melbourne.

Even though the above studies were not focused on estimating soil moisture changes in

expansive soils, they provide details of applicable mechanisms in monitoring and

modelling the expansive soil behaviour. Furthermore, they emphasize the effect of

climate conditions for the design of footings for light-weight structures. The next

chapter describes the results of an extensive investigation on climate effects on footing

design together with a critical examination of the current procedure adapted in AS2870.

61

3. EFFECTS OF CLIMATE ON FOOTING DESIGN

3.1 INFLUENCE OF CLIMATE CONDITIONS ON SOIL MOISTURE CONTENT

Soil and climate interaction is the natural mechanism by which moisture enters and

leaves the soil. Figure 3-1 shows the hydrologic cycle which explains how the moisture

content of the soil is influenced by the climate. Soil receives water mainly from

precipitation. Certain amounts of the received water infiltrate the soil while the

remainder runs off along the surface and adds to water bodies. Water then evaporates

directly from the surface. The infiltrated water also returns to atmosphere through

upward diffusion and transpiration. These processes depend on climate conditions,

including humidity, temperature and the wind. In addition to these climate parameters,

soil moisture changes also depend on other factors, including vegetation, permeability

of the soil, ground slope and human interactions.

Figure 3-1: The hydrologic cycle (NWS, 2010)

Rainfall, snowfall and dewfall are the main components of precipitation which provide

moisture into the soil. However, rainfall is the prominent component. It has different

patterns throughout the year. The moisture content of exposed surface soil follows a

62

similar pattern while the moisture content of subsequent layers depends mainly on the

permeability of the soil. If the precipitation rate exceeds the hydraulic conductivity of

the soil, then the surface layers become saturated and the excess water ponds on the

ground or runs off towards the downslope. However, the presence of cracks can

increase the amount of water infiltration and recharge the deeper soil layers.

Furthermore, runoff is also reduced by soil cracks.

It is estimated that more than 75% of the precipitation on land infiltrates and affects the

soil moisture content (Maps, 2015). Once the water infiltrates into the soil, it can

redistribute within the subsequent soil layers. The depth of the soil to which the

moisture content is prone to change significantly is called the “active zone” (McKeen

and Johnson, 1990). The redistribution of moisture within the active zone is influenced

by many different processes. The main process is exfiltration, which withdraws soil

moisture. Exfiltration includes evaporation from near surface soil and transpiration from

vegetation. These two processes are collectively called “evapotranspiration” (Dingman,

2002) The soil moisture transforms from a liquid state to a gas state during these two

scenarios. Evapotranspiration depends on the types of vegetation and their distribution.

For example, trees have different canopy types and root systems which govern the

amount of water they suck from the soil and transfer to the environment. If water is

deficient, vegetation is sparse and if more water is available, then trees grow closer

together (Thornthwaite, 1948).

Other redistribution processes include capillary rise, recharge and interflow (Figure

3-2). Capillary rise is the movement of moisture from a saturated zone to an unsaturated

zone due to capillary action of the pore spaces. Recharge is the movement of moisture

from an unsaturated zone into the ground water storage. Interflow is the flowing of

water through the soil layers which can only occur in downslopes (Dingman, 2002).

63

Figure 3-2: Redistribution of the soil moisture (Dingman, 2002)

Russam and Coleman (1961) investigated the interaction between climate and soil

moisture and provided a comprehensive data set. They considered the effect of climate

cycles on soil moisture condition under airfields in different countries including

Australia, England, Singapore, Sudan, Egypt, and Rhodesia. The climate effects on soil

moisture were considered in terms of moisture surplus and deficit, as defined by the

Thornthwaite Moisture Index (TMI). A more detailed description of the TMI is given in

the next sections of this chapter. Russam and Coleman (1961) divided the areas they

investigated into three categories, based on surplus and deficit, namely Wet, Dry and

Intermediate. The wet areas were defined as having zero deficits throughout the year

while the areas with zero surpluses throughout the year were defined as dry areas. Areas

with zero surpluses for certain months and zero deficits for other months were termed

intermediate areas. Figure 3-3 shows the monthly variation of surplus and deficit in

different sites examined by Russam and Coleman (1961). The figure also shows how

the soil moistures vary and the related processes due to the variation of the balance

between precipitation and evapotranspiration.

The authors found that areas in the wet category experience little seasonal change in

volume and moisture condition. Hence, moisture conditions under the pavements would

be expected to differ little from those in exposed soil. Areas in the dry category consist

of deserts and semi deserts where seasonal changes in soil moisture content are likely to

64

be very small. It was concluded that if the water table is maintained within 25 feet of the

ground surface, it will dominate the moisture regime of the subgrade in dry areas.

Otherwise, climate conditions govern the soil moistures.

Figure 3-3: Variation of monthly rainfall and evapotranspiration with soil moisture conditions in various sites (Russam and Coleman, 1961)

65

In the intermediate areas, soil moisture recharge occurs in certain rainy periods and a

surplus can be observed if more precipitation is received after the soil reached the field

capacity. The volume increase of expansive soil can be observed in this situation.

However, if the precipitation rate becomes less than the evapotranspiration rate, then the

recharged moisture is utilized to balance the additional requirement and the expansive

soils undergo volume reduction. Further, reduction in precipitation would lead to water

deficiency in the soil.

This reflects the influence of characteristics of the climate cycles on moisture and the

volume change of soil. Hence, the impact of climate must be a vital parameter in

designing lightweight structures built on expansive soils.

3.2 CLIMATE CONSIDERATION IN AS2870

Climate condition drastically affects the soil moisture change, as described in the

previous section. Expansive soils undergo heave and settlement due to increment and

decrement of the soil moisture, respectively. These soil movements can create

differential movements under footings and they are large enough to cause distress in

lightly loaded structures such as houses and pavements (ACA, 2012, THE-AGE, 2011).

Since about 20% of the surface soils in Australia have been classified as expansive soil

(Richards et al., 1983), climate conditions have a huge impact on residential footing

design in Australia.

The site classification procedure given in AS2870 (2011) takes into consideration the

climate conditions of the area. The standard allows for use of the Thornthwaite

Moisture Index –TMI (Thornthwaite, 1948) to estimate the depth of moisture change.

TMI is a commonly used climate classification index that characterises different climate

conditions from arid to humid.

Since the depth of seasonal moisture variation depends on climate conditions, AS2870

(2011) has categorized Hs values in relation to the TMI of the area. The standard has

given Hs for certain Australian cities, whereas for other areas it may be obtained from

the relationship of Hs versus TMI provided. This relationship is shown in Tables 3-6

and 3-7, and further discussed in section 3.5. The climate zones have been specified

66

based on the TMI ranges. The standard has provided a TMI map of Victoria to facilitate

the identification of the climate zone without using the TMI calculation.

Since the climate effects on footings are considered through TMI, it is important to

review the calculation procedure of the TMI. This calculation is associated with many

uncertainties, which are described in the next sections.

3.3 THORNTHWAITE MOISTURE INDEX (TMI)

The Thornthwaite Moisture Index was introduced by C.W. Thornthwaite (Thornthwaite,

1948) to classify climate conditions. It is a dimensionless index varying from +100 to -

100, which represent the climate conditions given in Table 3-1. TMI is calculated using

two indices called aridity index (Ia), and humidity index (Ih). These indices are defined

by water deficit (D) and run-off or surplus (R) based on a water balance calculation. The

water balance calculation can be performed in various ways, which result in different

values for TMI. Indeed, recent researchers have used different methods to calculate TMI

(Austroads, 2004, Fityus et al., 1998, Jewell and Mitchell, 2009, Lopes and Osman,

2010, Mather, 1978) and this has curtailed the ability to compare their results.

While the primary objective of the TMI was to classify the climate, it has been widely

applied in different areas such as agriculture, hydrology, pavement design and footing

design (AS2870, 2011, Austroads, 2004, Keim, 2010, Philp and Taylor, 2012).

Moreover, recent concerns about climate change and its effects on footing design have

also been discussed in terms of the TMI (Austroads, 2004, Leao and Osman, 2013).

Table 3-1: Climate types together with their TMI limits (Thornthwaite, 1948)

Climate type TMI

A Perhumid 100 and above B4 Humid 80 to 100 B3 Humid 60 to 80 B2 Humid 40 to 60 B1 Humid 20 to 40 C2 Moist subhumid 0 to 20 C1 Dry subhumid -20 to 0 D Semiarid -40 to -20 E Arid -60 to -40

67

3.3.1 Calculation of TMI

Thornthwaite (1948) introduced the TMI in 1948 and later published a number of

papers (Thornthwaite, 1952, Thornthwaite and Mather, 1955, Thornthwaite and Mather,

1957) to provide a clearer understanding of the calculation. According to these

publications, the TMI calculation procedure can be expressed in the flow chart shown in

Figure 3-4. Precipitation and temperature are the main input parameters of the TMI.

Water balance is calculated using those inputs and this provides the surplus and deficit.

The surplus and deficit are then used to obtain Ih and Ia to calculate the TMI.

Figure 3-4: Flow chart of the TMI calculation

3.3.2 Definitions and Assumptions

TMI calculation is associated with various terms that have been defined and modified at

different times. However, certain terms are defined in alternative ways, which has

caused alterations in the calculation.

Precipitation (P), also known as rainfall, is the main soil moisture input.

Evapotranspiration causes soil moisture loss which transfers the water from soil to air

by evaporation and transpiration. Potential Evapotranspiration (PE) is defined as the

amount of water that would be evapotranspired under certain climate conditions given

an unlimited supply of water. However, the amount of water lost from soil in a

particular climate condition is always restrained by the water availability and is defined

as Actual Evapotranspiration (AE).

Precipitation (P)

Mean Maximum

Temperature

Mean Minimum

Temperature

Average

Temperature

Potential Evapotranspiration

(PE)

Water Balance

Surplus (R) and Deficit (D)TMI Aridity index (Ia) and Humidity index (Ih)

Field capacity and initial storage

Latitude of location

68

The TMI calculation generally considers the soil body as a tank, hence the soil moisture

storage (S) is defined as the amount of water held in the soil at any particular time. The

maximum amount of water the soil can hold is called the field capacity (Smax). Based on

the monthly values of P and AE, soil moisture storage changes when monthly P is not

equal to AE and this change in storage is denoted as ∆S.

A number of definitions exist for moisture surplus (R) or runoff. Thornthwaite (1948)

states that water surplus refers to seasonal additions to subsoil moisture and ground

water. Thornthwaite and Mather (1955) defined the moisture surplus as the precipitation

in excess of potential evapotranspiration which occurs when soil is at the field capacity.

Later, Mather (1978) gave a more descriptive explanation that “surplus is the excess

water available to percolate through the soil both as recharge to the ground water table

or as through flow. This amount is P-PE in the months of soil moisture is at the field

capacity. When the soil storage is not at its capacity, no surplus can exist.” These

definitions contain slight differences, which can cause inconsistencies in the water

balance calculation.

Moisture deficit (D) is defined as the additional water that would be necessary to

achieve potential evapotranspiration when the precipitation is not sufficient. Mather

(1978) stated that the deficit is the difference between the water demand in a particular

climate condition and the actual evapotranspiration losses which can be calculated as

PE-AE.

In addition to contrasting definitions, the TMI calculation also includes some

assumptions. To account for the difficulty of water extraction from its adsorbed state in

a soil, Thornthwaite (1948) assumed a surplus of 60% in one season will counteract a

deficiency of 100% in another. The TMI calculation assumes the excess precipitation

(P-PE) that comes after a deficiency period will entirely infiltrate into the soil and

recharge the soil moisture storage until it reaches the field capacity. The excessive P

received when the soil is at the field capacity is becomes a runoff. Therefore, surface

runoff which may occur when the soil is being recharged is not considered, which

frequently happen when the rain falls in high intensity. The Australian TMI map has

also been developed employing the same assumption (Aitchison and Richards, 1965).

69

The next important assumption is the value of field capacity. Chan and Mostyn (2008)

suggested that the Smax depends on the climate and proposed the use of 0 mm for dry, 50

mm for temperate and 100 mm for wet conditions. Even though Thornthwaite and Mather

(1957) specified different values for field capacities based on soil types, most

researchers (Aitchison and Richards, 1965, Jewell and Mitchell, 2009, Russam and

Coleman, 1961) have assumed a constant value over a number of different soil types

and 100 mm has been used commonly. Indeed, Aitchison and Richards (1965) assumed

Smax of 100 mm to obtain the TMI for more than 600 locations to develop the Australian

TMI map.

Another assumption of the TMI calculation relates to the behaviour of soil moisture

storage. Thornthwaite and Mather (Mather, 1978, Thornthwaite and Mather, 1955)

assumed that, when soil becomes dryer, the removal of water from the soil becomes

increasingly difficult and soil cannot extract the same amount of moisture from the

storage. Therefore, the soil moisture storage never becomes zero. In contrast, most of

the recent research (Barnett and Kingsland, 1999, Chan and Mostyn, 2008, Fityus et al.,

1998, Fox, 2000, Jewell and Mitchell, 2009, Lopes and Osman, 2010, McManus et al.,

2004, Mitchell, 2008) has assumed that the soil can provide the required additional

amount of moisture until the storage level becomes zero.

The initial storage (S0) needs to be assumed to perform the water balance in the TMI

calculation. This is the water storage available at the first month of the first year of TMI

calculation. When the calculation is performed over a longer period, the impact of this

assumed value becomes insignificant.

Based on the above definitions and the stated assumptions, TMI has been defined by an

aridity index (Ia) and humidity index (Ih). Ia is a relationship between moisture deficit

and water necessity (Equation 3-1) whereas Ih is a relationship between moisture

surplus and water necessity (Equation 3-2).

Ia = 100 ×D

PE ……...…………………………………………...…… Equation 3-1

70

Ih = 100 ×R

PE ……...…………………………………………...…… Equation 3-2

Thornthwaite (1948) suggests that, PE be calculated using Equation 3-3 for each month

and then the monthly summation is taken as annual PE. The unit of D, R and PE is

centimetres.

PE = 1.6 × (10 × t

I)

a

.………...…………………………………...…… Equation 3-3

‘t’ is the average temperature in a particular month and ‘I’ is annual heat index in a

particular year which is taken as the summation of monthly heat index values (i)

calculated using Equation 3-4. Parameter ‘a’ is calculated using Equation 3-5.

i = (0.2 × t)1.514 .……...……...…………………………………...…… Equation 3-4

a = 6.75 × 10−7 × I3 − 7.771 × 10−5 × I2 + 0.01792 × I + 0.49239 ... Equation 3-5

In Equation 3-3, PE is assumed as a 30-day month for a location with a 12 hour daylight

period. Therefore, it must be multiplied by two factors which account for daylight hours

for the location for a given month (f1) and number of days per month (f2),

f1 =d

12 …………..…...…………………………………………...…… Equation 3-6

f2 =N

30 …………….....…………………………………………...…… Equation 3-7

where ‘d’ is number of hours in a day between sunrise and sunset in a month and ‘N’ is

number of days for the particular month. The value of ‘d’ depends on the location which

can be related to the latitude. Thornthwaite (1948) provided a table to find out “d” at

each latitude for each month of the year.

71

PE is calculated on a monthly basis to perform the water balance and then the

summations of monthly results are used to calculate Ia and Ih annually. The TMI

equation using Ia and Ih is shown in Equation 3-8 (Thornthwaite, 1948).

TMI = Ih – 0.6 × Ia ……………………………………………...…… Equation 3-8

Even though the equations given for PE calculation are widely accepted by most of the

investigations (Austroads, 2004, Barnett and Kingsland, 1999, Chan and Mostyn, 2008,

Fityus et al., 1998, Fox, 2000, Jewell and Mitchell, 2009, Mather, 1974, Mather, 1978,

Mitchell, 2008, Thornthwaite, 1948, Thornthwaite and Mather, 1957), the water balance

calculation has been performed in different ways. Hence, three different methods of

calculation were identified during the critical literature review of this study. The

uncertainties in calculation have resulted in the simplification of the TMI equation to

bypass the calculation of water balance. However, the simplified method also gives

different results. Therefore, based on the definitions and assumptions, four different

approaches have been identified and they are discussed in the next section.

3.3.3 Different methods of TMI calculation

3.3.3.1 Method 1

In 1957, Thornthwaite and Mather published an explanation of the procedures used to

calculate TMI which is denoted as Method 1 in this study (Thornthwaite and Mather,

1957). They developed tables for the water retention calculation based on the

phenomenon of increasing difficulty of water removal from the soil when it becomes

dry. According to their tables, soil moisture storage cannot be empty at any time.

Mather (1978) used these tables to calculate soil moisture storage depending on the field

capacity. Thornthwaite and Mather (1957) proposed Equation 3-9 to calculate change in

soil moisture (∆S) in successive months.

∆S = 𝑆𝑖 – 𝑆𝑖−1 .……...……...…………………………………...…… Equation 3-9

Si and Si-1 are soil moisture storages in the current month and the previous month

respectively as obtained from the water retention tables.

72

Based on the change in soil moisture storage of the current month, actual

evapotranspiration (AE) is calculated using Equation 3-10. The difference between PE

and AE was also explained in Tucker (1955) using a similar equation to that provided

by Thornthwaite and Mather (1957).

AE = PE; when P ≥ PE .…………….………………………...…… Equation 3-10

= P + ∆S; when P < PE

Soil moisture deficit (D) is taken as the difference between PE and AE (Equation 3-11),

while surplus is calculated using P, PE and S, as shown in Equation 3-12.

D = PE − AE .………………...……….………………………...…… Equation 3-11

R = Si−1 + (P − PE)i − Smax ; Only when Si = Smax ...……………… Equation 3-12

These D and R values are then used to calculate TMI from Equations 3-1, 3-2 and 3-8.

Table 3-2 shows the calculation steps for Method 1 assuming 10 cm of field capacity

and 8 cm of initial storage.

Table 3-2: TMI calculation steps in Method 1

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual

P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1

PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0

P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8

∆S -2.0 -2.1 -0.9 -0.3 4.5 2.7 0.0 0.0 -0.8 -2.8 -2.6 -2.1

S 6.0 3.9 3.1 2.8 7.3 10.0 10.0 10.0 9.2 6.4 3.8 1.7

AE 4.9 8.1 6.8 5.4 3.8 2.6 2.7 3.1 4.7 5.7 6.3 5.1

R 0.0 0.0 0.0 0.0 0.0 1.9 3.2 2.2 0.0 0.0 0.0 0.0 7.3

D 7.7 2.1 1.6 0.6 0.0 0.0 0.0 0.0 0.0 0.7 2.4 5.9 20.9

TMI -7

73

3.3.3.2 Method 2

Recently, researchers (Austroads, 2004, Barnett and Kingsland, 1999, Chan and

Mostyn, 2008, Fityus et al., 1998, Fox, 2000, Mitchell, 2008) have avoided employing

the water retention tables given by Thornthwaite and Mather (1957) in order to simplify

the calculation and make it more accessible. Instead, they adapted a different definition

to calculate the soil moisture storage which shown in Equation 3-13.

Si = Si−1 + (P − PE)i and 0 ≤ Si ≤ Smax ......………….………...…… Equation 3-13

In these studies, except Austroads (2004), the ΔS and AE calculation have been

skipped. This produces different values for the TMI and it is denoted as Method 2 in

this study.

In this method, moisture surplus is calculated using the same equation used in Method 1

(Equation 3-12) but Equation 3-14 is used for the moisture deficit.

D = Si−1 + (P − PE)i ; Only when Si = 0 …….…….………...…… Equation 3-14

These D and R values are then used to calculate the TMI from Equation 3-8. Table 3-3

shows the calculation steps for Method 2 assuming 10 cm of field capacity and 8 cm of

initial storage.



P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1

PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0

P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8

∆S ∆S is not used in this method

S 0.0 0.0 0.0 0.0 4.5 9.1 10.0 10.0 9.2 5.7 0.7 0.0

AE AE is not used in this method

R 0.0 0.0 0.0 0.0 0.0 0.0 2.3 2.2 0.0 0.0 0.0 0.0 4.5

D 0.0 4.2 2.4 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3 14.7

TMI -5

74

3.3.3.3 Method 3

Austroads (2004) used a different definition for ΔS (Equation 3-15) and AE (Equation

3-16) to calculate the moisture deficit, which is denoted here as Method 3.

ΔS = Si−1 − Si .………………...……….………………………...…… Equation 3-15

AE = PE ; when P + ∆S ≥ PE .……...….………………………...…… Equation 3-16

= P + ∆S ; when P + ∆S < PE

Similar to Method 1, this method uses Equation 3-11 to calculate the deficit however

moisture surplus is calculated in a different way, as shown in Equation 3-17.

R = P − AE ; Only when P > AE .………………….…………...…… Equation 3-17

This equation produces values for surplus when the soil moisture storage begins

recharging from an additional amount of water provided by the difference between P

and PE. In Methods 1 and 2, the storage recharge is not considered as a surplus and it is

calculated only when the storage is at its maximum. Hence, Method 3 calculates a

surplus higher than those obtained from Methods 1 and 2. This consequently shifts TMI

towards a more humid condition. Table 3-4 shows the calculation steps for Method 3

assuming 10 cm of field capacity and 8 cm of initial storage.



P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1

PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0

P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8

∆S 8.0 0.0 0.0 0.0 -4.5 -4.6 -0.9 0.0 0.8 3.5 5.0 0.7

S 0 0 0 0 4.5 9.1 10 10 9.2 5.7 0.7 0

AE 10.9 6.0 5.9 5.1 3.8 2.6 2.7 3.1 4.7 6.4 8.7 3.7

R 0.0 0.0 0.0 0.0 4.5 4.6 3.2 2.2 0.0 0.0 0.0 0.0 14.5

D 1.7 4.2 2.4 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3 16.4

TMI 6

75

3.3.3.4 Method 4

Uncertainties in water balance calculations have encouraged researchers to modify the

TMI equation. Mather (1974) presented a simplified version to obtain the TMI

(Equation 3-18), which omits the 0.6 factor from Equation 3-8. Moreover, this

simplification assumes that there is no net change in the storage in long-term and hence

on an annual basis R and D can be obtained from Equation 3-19 and 3-20. By

substituting them into Equation 3-18, the simplified version given in Equation 3-21 can

be obtained and it does not require water balance calculation.

TMI = 𝐼ℎ − 𝐼𝑎

.………….…….………………………...…… Equation 3-18

R = P − AE

.………….…….………………………...…… Equation 3-19

D = PE − AE

.………….…….………………………...…… Equation 3-20

TMI = 100 × (P

PE− 1) .………….…….………………………...…… Equation 3-21

This method also gives different values for the TMI. Table 3-5 illustrates the calculation

steps for Method 4.



P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1

PE (cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0

P-PE

These factors are not used in Method 4

∆S

S

AE

R

D

TMI -25

76

3.3.4 Comparison of TMI results from different methods

The variation in TMI results obtained using the four different methods is compared in

this section. Climate data collected from Melbourne regional office weather station has

been used in this comparison. Melbourne regional office is one of the main weather

stations in Melbourne Central Business District (CBD) where climate data is available

since 1850’s. Figure 3-5 shows calculated TMI using each of the four methods for the

last 50 years.

Figure 3-5 suggests that, even though different equations are used to calculate soil

moisture storage and deficit, Methods 1 and 2 appear to produce similar results.

Thornthwaite and Mather (1957)water retention tables and the Equation 3-13 used in

Method 2 give similar storage values for certain months in a year depending on P and

PE. While the two methods produce slightly different deficit values, the 0.6 factor used

in TMI equation (Equation 3-8) minimises the difference.

Figure 3-5: TMI variation in Melbourne CBD for the last 50 years

Method 3 uses a different definition for moisture surplus and it produced higher R

values than Methods 1 and 2. Therefore, TMI values have become more positive,

expressing a more humid climate condition compared to Methods 1 and 2.

Method 4, which uses completely different equation for TMI (Equation 3-21), has

simplified the calculation but the results tend towards more negative values expressing a

more arid climate condition. The PE calculation proposed in Thornthwaite (1948) has

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010-60

-40

-20

0

20

40

TMI

Year

Method 1 Method 2 Method 3 Method 4

77

shown that the lesser the P, the higher the PE. Since, Method 4 uses the ratio of P and

PE it reflects higher peaks in extreme dry weather conditions. In wet extremes, peaks

shown in Method 4 are within the range of the other methods.

When the four different methods produce different TMI results, it is questionable which

method should be implemented in the footing design. Since AS2870 provides a climate

zone map of Victoria, which is extracted from Australian TMI map produced in 1965, it

appears that the Method 1 is considered in the Standard. All the methods show the same

trend of long-term climate variation. However, the yearly TMI values differ and hence

different average values will lead to classifying a particular area into different zones. In

addition, the capability of TMI to capture the effects of climate conditions on soil is

debatable. The TMI calculation requires only the rainfall and temperature as climate

parameters. Sensitivities of those parameters are discussed in the next section.

3.3.5 Sensitivity of climate parameters of TMI calculation

Since all four methods express the same trend on climate condition variation with time

and both Methods 1 and 2 produce similar values, Method 1 is used to investigate the

impact of the climate parameters on TMI.

3.3.5.1 Rainfall (Precipitation)

Monthly rainfall values are used in the TMI calculation to perform the monthly water

balance that is then used to obtain annual TMI. Therefore, annual TMI is compared with

annual rainfall. Figure 3-6 shows TMI and annual rainfall variation for the last 50 years

in Melbourne.

Figure 3-6: TMI and annual rainfall variation in Melbourne CBD for last 50 years

1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008-40

-30

-20

-10

0

10

20

30

40 TMI (Method 1) Annual Rainfall (mm)

Year

TM

I

200

300

400

500

600

700

800

900

1000

1100

Ann

ual R

ainf

all (

mm

)

78

Figure 3-6 provides evidence that TMI is almost entirely dependent on rainfall. Indeed,

the annual TMI has the same variation as annual rainfall. The annual rainfall and the

corresponding TMI are plotted in Figure 3-7 and it demonstrates a linear relationship

with a coefficient of determination of 0.89. It is therefore proposed that such an

extended calculation associated with many uncertainties can be summarized to a liner

relationship of annual rainfall with an acceptable reliability. Li and Sun (2015) observed

the similar behavior in the TMI and rainfall in Victorian cities. Consequently, the

annual rainfall can certainly replace the TMI without the hysteresis of calculation.

Figure 3-7: Relationship between TMI and annual rainfall (Melbourne)

3.3.5.2 Temperature

The other climate parameter used in TMI is the average temperature. It is obtained by

averaging the mean minimum and maximum temperatures. The average temperature is

then used to calculate PE. Figure 3-8 shows the variation of TMI and annual average

temperature in Melbourne. PE is the denominator of Ia and Ih equations used to

calculated TMI (Equation 3-1 and 3-2) therefore, an inverse variation is observed

between TMI and average temperature. The TMI values are plotted against the

corresponding average temperatures as shown in Figure 3-9. It suggests that the TMI

only has a weaker correlation with the temperature.

300 400 500 600 700 800 900 1000-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

TMI (

Met

hod

1)

Annual Rainfall (mm)

R-Square = 0.8982

79

Figure 3-8: TMI and annual average temperature variation in Melbourne CBD for the last 50 years

Figure 3-9: Relationship between TMI and annual average temperature (Melbourne)

3.3.5.3 Sensitivity of averaging period on TMI

Since the yearly TMIs fluctuate within a short period, AS2870 (2011) recommends the

use of average TMI for at least 25 years for designing residential structures. Average

TMI is obtained by averaging the annual TMIs calculated for particular number of

1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008-60

-50

-40

-30

-20

-10

0

10

20

30

40 TMI (Method 1) Average Temperature (0C)

Year

TMI

14

15

16

17

18

Ave

rage

Tem

pera

ture

(0 C)

13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

TMI (

Met

hod

1)

Average Temperature (0C)

80

years. Figure 3-10 shows the impact of changing the averaging period from 3 years to 5,

10, 20 and 25 years on the TMI for Melbourne. Lowering the number of average years

results in an increase in the sensitivity of TMI to extreme climate events. A 20 or 25

year average TMI neutralizes most of the extreme events and shows the long-term

drying trend over the years. In contrast, 3, 5 and 10 year TMIs have more fluctuations

with peaks smaller than the annual TMI variation and reflect the short-term trends.

Average TMI values are less sensitive for consecutive extreme climate events. For

example, a severe drought followed by a few wet years will make a significant impact

on soil moisture and hence the ground movement in expansive soil. However, average

TMI is unable to reflect such changes. Indeed, consecutive extreme climates have

occurred in Melbourne in the recent years. Severe drought from the late 1990’s to early

2000s followed by a few years of above average rainfall was recorded for Melbourne.

This phenomenon is clearly shown in the yearly TMI line in Figure 3-10. TMI values

calculated for averaging periods of 5 and 10 years are less sensitive to these consecutive

events. In fact, the 20 and 25 years averaged TMIs do not reflect this extreme event at

all.

Figure 3-10: Sensitivity of averaging period on TMI

While Figure 3-10 shows the impact of averaging period on TMI results, determining

the most appropriate averaging period also depends on the type of soil. The climate

1938 1944 1950 1956 1962 1968 1974 1980 1986 1992 1998 2004 2010-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

TMI

Year

Yearly TMI 3 years 5 years 10 years 20 years 25 years

81

impact on soil moisture is largely a site dependent phenomenon because of the soil

properties and the local effects. Therefore, the average years need to be considered in

association with many factors including permeability of the soil and vegetation cover.

3.4 CORRELATION OF TMI AND EXPANSIVE SOIL BEHAVIOUR

TMI has become the most popular climate index to be correlated with the soil moisture

or suction (PTI, 2004, Russam and Coleman, 1961, Aitchison and Richards, 1965).

Since the moisture content of the surface layer fluctuates more frequently, the long-term

average TMI has been used to correlate the equilibrium suction (constant suction below

depth of seasonal moisture change) by Russam and Coleman (1961). Figure 3-11 shows

the variation of equilibrium suction with TMI. The suction values obtained from this

correlation were used in designing road subgrades. In the Post Tensioning Institute

method of footing design, TMI is correlated with the edge moisture change distance of a

cover slab (Figure 3-12) in centre lift and edge lift situations (PTI, 2004). Figures 3-10

and 3-11 are also referred to in the hand book of AS2870 (Walsh and Cameron, 1997).

However, none of the above publications mentioned that the TMI calculation procedure

or period of averaging years must be considered.

Figure 3-11: Variation of soil suction of road subgrade with TMI (Russam and Coleman, 1961)

82

Figure 3-12: Edge moisture variation distance determination in Post Tensioning Institute (PTI, 2004)

Mitchell (2008) summarised the conclusions of a number of research outcomes about

TMI and the equilibrium suctions in Australia, shown in Figure 3-13. Figure 3-13 shows

the reduction in equilibrium suction towards a humid climate condition, which is similar

to Figure 3-11.

Figure 3-13: Correlations of equilibrium soil suction and TMI (Mitchell, 2008)

83

The AS2870 design procedure is based on the shape of the suction profiles rather than

the equilibrium suction. The extreme suction profiles in dry and wet conditions shows

the possible range of suction variation at different times. Walsh and Cameron (1997)

argued that the overall variation has the shape of a champagne flute. The ground

movement calculation given in AS2870 depends on the area within the extreme suction

profiles. Since it is difficult to calculate the area of the champagne flute shape, it has

been simplified to a triangular shape defined by ΔU and Hs. The AS2870 standard has

defined climate zones based on TMI and provided ∆U and Hs for each zone.

Figure 3-14 shows the corrections of ΔU and TMI suggested by various researchers. All

the references except AS2870 (2011) and Fox (2000) suggested that ΔU increases with

increasing the aridity of the climate. However, irrespective of the different climate

conditions and soil types in Australia, AS2870 (2011) has specified a single value (1.2

pF) for all the cities.

Figure 3-14: Correlation of ΔU and TMI (Mitchell, 2008)

Figure 3-15 shows the suggestions from the same researchers for TMI verses Hs

relationship. It clearly shows that the higher the aridity in the climate the higher the Hs

value. AS2870 shows a discrete variation in the climate zones and the corresponding Hs

depths.

84

Figure 3-15: Correlation of Hs and TMI (Mitchell, 2008)

3.5 ISSUES OF TMI BEING USED IN AS2870

The main issue of TMI being used in footing design is its ability to represent the soil

moisture condition. The TMI is largely based on rainfall and temperature with a

negligible contribution from soil parameters. As described in the section 3.3.5.2,

temperature has minimal impact on TMI however, the influence of rainfall on TMI is

clearly observed by considering the contour maps. Figure 3-16 shows predicted rainfall

and TMI maps in year 2100 for Australia (Austroads, 2004). The contours of rainfall

and TMI are almost similar which strengthens the linear correlation shown in Figure

3-7. Figure 3-17 shows Victorian mean annual rainfall map (BoM, 2015a). These

annual rainfall contours are almost identical to the TMI contours shown in Figure 3-18.

85

Figure 3-16: (a) Average Annual Rainfall in mm for 2100 predicted climate; (b) TMI map for 2100 predicted climate(Austroads, 2004)

Figure 3-17: Victorian mean annual rainfall map (BoM, 2015a)

(a) (b)

86

Figure 3-18: TMI map for Victoria for 1913 to 1932 (Leao and Osman, 2013)

Another issue of TMI is the use of average TMI. Various researchers, who studied TMI

and Hs, have used different average periods. The number of years used to calculate the

average has varied within a broader range (from 5 to 144 years) and some researchers

used the average TMIs based on the entire years of available data (Chan and Mostyn,

2008, Fityus et al., 1998). This may be due to the recommendation of AS2870 to

consider the average TMI of at least 25 years. Figure 3-10 shows that the higher the

averaging years, the lesser the sensitivity to extreme weather events such as droughts.

The long-term average TMI clearly displays the long-term trends. However, for the

residential footing design, this averaging period needs to be considered together with

more soil specific parameters.

During a drought period, the surface soils can become dry depending on the severity of

the moisture deficit. If the rain comes immediately after, a certain amount of water will

infiltrate through the surface soil while some rain will move in to the cracks. However,

there is a runoff on the surface depending on the surface condition. Since the TMI

calculation is associated with monthly rainfall to obtain the water balance, it assumes

that all the rainwater after a deficit period infiltrates the soil moisture storage until it

reaches the field capacity. Any possible runoff while soil is being recharged is not

considered. Hence, TMI results indicate a more humid condition than the actual

87

situation. This highlights the lack of ability of TMI to capture effects of rainfall spread

given the overall rainfall kept constant.

The next issue of using TMI in AS2870 is the uncertainty surrounding the time of

climate data to be used in the calculation. Many researchers concluded that climate

change has been ongoing in Australia since the 1950s’ (Karunarathne et al., 2013,

Lopes and Osman, 2010, McManus et al., 2004, Mitchell, 2008, Hughes, 2003, Murphy

and Timbal, 2008, Smith et al., 2009). However, the climate classification given in

AS2870 is based on the climate data collected from 1940 to 1960 and therefore is likely

to be out-dated (Lopes et al., 2003).

Aitchison and Richards (1965) developed the Australian TMI map using 1940-1960

climate data. The Victorian TMI map shown in Figure 3-19 was extracted from the

Australian TMI map produced in 1965 (Aitchison and Richards, 1965). This map shows

the TMI contours and the climate zones based on the TMI ranges given in Table 3-6.

According to the map shown in Figure 3-19, Melbourne city and the Western suburbs

fall in to climate zones 2 and 3 which have TMI variations from -5 to +40. In these

climate zones, Hs varies from 1.8 m to 2.3 m.

Figure 3-19: TMI map of Victoria given in AS2870 (1996)

88

Table 3-6: Climate zones and corresponding Hs inferred from AS2870 (1996)

TMI Range

Hs (m)

Climate Zone

TMI > 40 1.5 1

40 > TMI >= 10 1.8 2

10 > TMI >= -5 2.3 3

-5 > TMI >= -25 3.0 4

-25 > TMI 4.0 5

The effect of climate variation on Hs has been considered in several studies in different

Australian states (Barnett and Kingsland, 1999, Chan and Mostyn, 2008, Fityus et al.,

1998, Fox, 2000, Lopes and Osman, 2010, McManus et al., 2004, Smith, 1993). Fityus

et al. (1998) calculated the TMI for 38 locations and proposed a detailed TMI map for

the Hunter Valley area. Moreover, McManus et al. (2004) produced TMI maps for

Queensland, South Australia, Western Australia, New South Wales and Victoria to

describe the climate change. They developed TMI maps for two different periods; 1940-

1960 and 1960-1991. Their results highlighted that those areas have shown a trend of

drying since the 1960’s.

Lopes and Osman (2010) calculated the TMI for certain Victorian towns for three

different time periods; 1948-1967, 1968-1987 and 1988-2007. Based on the results, they

have concluded that TMI values of those towns have changed and Aitchison and

Richards (1965) TMI map is not valid for the climate condition for the period of 1988-

2007. Furthermore, Lopes and Osman (2010) proposed updated Hs values

corresponding to the TMI results for 1988-2007 period.

The 2011 edition of AS2870 provided an updated relationship for TMI and Hs shown in

Table 3-7. The TMI ranges of each climate zone have been shifted towards more

negative values to accommodate the drying trend. Consequently, a new climate zone has

been introduced as “Zone 6” which represents the main difference between Tables 3-6

and 3-7.

89

Even after the modifications given in AS2870 (2011), some problems remain uncertain

in the new climate map and the corresponding Hs relationship (Lopes and Osman

(2010). The updated Victorian climate map is shown in Figure 3-20. The TMI contour

maps given in the 1996 and 2011 editions are identical, as shown in Figure 3-19 and

Figure 3-20. The only difference is that the TMI values shown in 1996 map were

deleted in the 2011 map. The TMI contours and the zone numbers are the same in both

maps. Therefore, even if the calculations indicated decrease in the TMI, the map

suggests that zone 6 areas are not identified in Victoria.

Recently calculated TMI values show a considerable change in climate conditions

(Karunarathne et al., 2012). During this study, TMI was calculated in two different

periods for more than fifty locations in Victoria. Ten cities from each climate zone were

considered. Figure 3-21 shows the results and indicates that all the locations have lower

TMI values for the period 1991 to 2011 compared to 1940-1960. Most of the

differences are 10-15 units. This indicates the drying trend of the climate. The updated

TMI ranges in AS2870 (2011) were able to encompass the changes to certain extent and

the TMI limits in each climate zones were reduced by 10 to 15 units in 2011 edition.

However, these changes were not implemented in terms of Hs.

Figure 3-20: TMI map of Victoria given in AS2870 (2011)

90

Table 3-7: Relationship between TMI and Hs(AS2870, 2011)

TMI Range Hs (m) Climate Zone

TMI > 10 1.5 1

10 > TMI >= -5 1.8 2

-5 > TMI >= -15 2.3 3

-15 > TMI >= -25 3.0 4

-25 > TMI >= -40 4.0 5

-40 > TMI > 4.0 6

Figure 3-21: TMI calculation for Victorian cities

Figures 3-22 and 3-23 show the positions in the TMI bands for each climate zone

specified by the 1996 and 2011 edition of the standard, respectively. The highlighted

areas are the TMI bands of each climate zone in the particular edition of the standard.

The TMI values are calculated using Method 1. In general, in Figures 3-22 and 3-23,

most of the cities were captured by the specified TMI bands in both editions of the

standard. However, in zone 3 of Figure 3-22 and zone 4 of Figure 3-23, most of the

cities fell outside the bands.

Ap

ollo

Bay

Ararat

Ballan

B

allarat B

eaufo

rt C

ashim

ore A

irpo

rt C

olac

Daylesfo

rd

Dim

bo

ola

Do

nald

East Sale Ech

uca

Elmo

re Essen

do

n

Gisb

orn

e H

amilto

n

Heyw

oo

d

Ho

rsham

K

aniva

Keran

g K

ew

Kyab

ram

Laverton

Leo

ngath

a Lism

ore

Lon

gerno

ng

Man

galore

Marib

yrno

ng

Melb

ou

rne

Mered

ith

Mild

ura

Mo

e M

orn

ingto

n

Mu

rrayville N

hill

Ou

yen

Po

rtland

Q

ueen

scliff R

ainb

ow

R

ob

invale

Ro

chester

Sea Lake Seym

ou

r Skip

ton

Sp

eed

St. Arn

aud

Tatu

ra Taw

on

ga W

arracknab

eal W

atson

ia W

erribee

Wo

nth

aggi W

ychep

roo

f

-50-40-30-20-10

01020304050607080

TMI

Method 1 (1940-1960) Method 1 (1991-2011)

91

Figure 3-22: TMI of Victorian cities in different climate zones specified in AS2870 (1996)

Figure 3-23: TMI of Victorian cities in different climate zones specified in AS2870 (2011)

-50-45-40-35-30-25-20-15-10

-505

10152025303540455055606570

1.00 2.00 3.00 4.00 5.00 6.00

TMI

Mather

Zone 1 Zone 2 Zone 3 Zone 4 Zone 5

Method 1 (1940-1960)

-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

40

45

50

1.00 2.00 3.00 4.00 5.00 6.00 7.00

TMI

Mather

Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 6

Method 1 (1991-2011)

92

Overall, the modifications adopted in the 2011 edition of the standard are able to predict

most of the recent climate changes. However, the corresponding Hs values have not

been updated for zone 2 and 3 which cover Melbourne’s Western suburbs. This leads to

some confusion in the use of the TMI map and the TMI verses Hs relationship given in

Table 3-7. Subsequently, the ys calculation for Western suburbs based on both editions

of the standard would produce same values.

Some of the specified Hs values for Australian cities have been updated in 2011 edition

of the standards, as shown in Table 3-8. In most cases, Hs was increased to

accommodate the effects from the drying trend of the climate. In contrast, the ΔU values

were reduced from 1.5 pF to 1.2 pF for some regions making all parts of Australia

having ΔU value of 1.2 pF (Table 3-8). However, even after the 1996 edition of the

standard was published, some researchers have found ΔU value to be greater than 1.5

pF for some areas (Barnett and Kingsland, 1999, Fityus et al., 2004).

Table 3-8: Hs and ΔU values specified in AS2870

Location Hs (m) ∆U(pF)

AS2870 (1996)

AS2870 (2011)

AS2870 (1996)

AS2870 (2011)

Adelaide 4 4 1.2 1.2 Albury/ Wodonga 3 3 1.2 1.2 Brisbane/ Ipswich 1.5 – 2.3 1.5 – 2.3 1.2 1.2 Gosford Not given 1.5 – 1.8 Not given 1.2 Hobart 2 2.3 – 3.0 1.5 1.2 Hunter Valley 2 1.8 – 3.0 1.5 1.2 Launceston 2 2.3 – 3.0 1.2 1.2 Melbourne 1.5 – 2.3 1.8 – 2.3 1.2 1.2 Newcastle 1.5 1.5 – 1.8 1.5 1.2 Perth 3 1.8 1.2 1.2 Sydney 1.5 1.5 – 1.8 1.5 1.2 Toowoomba 1.8 – 2.3 1.8 – 2.3 1.2 1.2

Austroads (2004) predicted the expected changes in Australian climate to the year 2100.

This report concluded that most of Australian cities will have a dryer climatic condition

in 2100 than they had in 2000. According to the prediction, current TMI values in most

of the Victorian cities will be reduced by 15 in 100 years. Indeed, based on the results

presented in Figure 3-21, some locations have seen a reduction of 20 in the TMI value

93

over the last 50 years. Therefore, given that TMI, and consequently Hs, values are based

on historical data, an allowance should be made for potential changes during the design

life of the structure. It is therefore proposed to adopt a Hs value for design that is based

on a probabilistic design event based on more recent climate data and future forecasts

which suggest potentially greater drying.

In addition to the dependency of Hs on climate condition, other soil parameters vary

with the moisture content, which can affect the ground movement as described the next

section

3.6 EFFECT OF SOIL MOISTURE CONDITION ON AS2870 DESIGN PARAMETERS

3.6.1 Variation of Iss with moisture content

According to the site classification procedure given in AS2870 and described in the

previous chapter, ΔU, Hs, shrinkage index and assumed cracking depth are the

parameters that represent the site condition. ΔU and Hs depend on the long-term climate

condition, as described in the previous section. AS2870 considers that shrinkage indices

are constant for a given soil type. The shrink swell test considers total strain of

undisturbed soil from both shrinkage and swell movements irrespective to the initial

moisture content. Therefore, the hand book of AS2870 recommends Iss is the most

reliable index among others such as core shrinkage index and loaded shrinkage index

(Walsh and Cameron, 1997).

Shrinkage indices represent the volume change of expansive soils per unit suction

change. Iss includes strains from both shrinkage and swell movements. Vertical

movement is most critical, because lateral movement is restrained by the surrounding

soils. Therefore, Iss considers only the vertical strain per unit suction. The Iss test starts

at the in situ moisture content and proceeds to swell and shrinkage movements. Swell

strain is measured from the one-dimensional swell test whereas shrinkage strain is

measured from the core shrinkage test.

As shown in Figure 3-24, variation of soil strain with suction is a curvilinear function.

This figure is developed using the core shrinkage test starting from a very wet

condition. The weight and the length of the sample are measured until the sample

reaches an oven dry condition. Then, the moisture contents are calculated and the

94

corresponding suction values are obtained from the soil water characteristic curve (more

details on soil water characteristic curve are provided in Chapter 4). Iss is the gradient of

the strain versus suction curve. According to Figure 3-24, the relationship has an “S”

shape with three different stages. The main stage is the darkened area of Figure 3-24,

which has a linear variation with steep slope. Therefore, soils in this section experience

significant strain per given suction change. Very wet soils and very dry soils represent

either side of that area, as illustrated in the figure. These two sections of the curve have

mild and changing slopes implying that less strain will be observed for a given suction

change.

Figure 3-24: Vertical strain and suction relationship (Braybrook soil)

According to AS1289.7.1.1 (2003), the Iss test starts from the in situ moisture content

which can be at any suction value shown in Figure 3-24. AS1289.7.1.1 (2003) specifies

to stop the swell test when the movement between the last reading and a reading at least

3 hours previously is less than 5% of the total swelling of the specimen. Most of the

soils will reach this limit close to the end of the linear section of the relationship. The

author has experienced this incident for the clays collected from different areas

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.50

3

6

9

12

15

18

21 Strain (%) Polynomial fit

Stra

in (%

)

Suction (pF)

Very wet soil Very dry soil

95

including Braybrook, Burnside, Taylors Hill, Point Cook, Melton and Plumpton in

Victoria, Australia. Those soils have shown a considerable swelling after this specific

limit and continued swelling for more than 5 days. Most of those soils are moderate to

highly expansive clays. Even though the standard neglects strain after this 5% limit, it

can represent a significant amount compared to the total strain. However, the shrinkage

test has no restricted stopping point and continues to the oven dry state. The total

vertical strain is then divided by suction change to obtain the gradient.

The Iss test is purposely developed to bypass the difficulties of measuring soil suction.

Therefore, it assumes that the suction varies by 1.8 pF over most of the significant strain

change in soil. This suction change is commonly accepted by many researchers (Fityus

et al., 2005). However, since the relationship of suction and strain has “S” shape (Figure

3-24), its gradient varies at suctions close to the extreme ends. Thus, Iss can have

different values at different operating suctions. Moreover, based on the Iss equation

explained in Chapter 2 (Equation 2-14), tests started at high moisture contents have

lower swell movements and higher shrinkages, which result in higher total strains.

Consequently, tests started at different in situ moistures produce different Iss results.

This phenomenon was experimentally observed in this study. Undisturbed samples were

collected around a specific location at the field site of Braybrook (see Chapter 4) at

different times of the study. Hence, the samples were assumed to be identical and they

were at different in situ moisture levels. Results of Iss tests performed on those soils are

presented in Table 3-9.

Within the period of sample collection, March 2013 was recorded as driest month

whereas August 2013 was the wettest. Moisture contents of the top soil varied by more

than 15% between these two conditions. However, the soil moistures below 1.5 m were

stable. Table 3-9 shows the different Iss results obtained corresponding to different

moisture contents particularly for soils up to 2.0 m. This difference is higher in top

soils, as shown in Figure 3-25. Shrinkage strain becomes increasingly higher when in

situ moisture content is increased. Swell strain showed the opposite variation against in

situ moisture. However, according to the calculation based on those two strain values,

Iss increased with in situ moisture content. Interestingly, Iss changed by 2.5% for a

change of soil moisture of 15%.

96

Table 3-9: Iss test results from different samples collected at similar locations from Braybrook

Sample date Depth (m) In situ mc % Shrinkage

(%) Swell (%) Iss (%)

02/08/2012

0.5-1.0 28.53 8.75 2.35 5.51 1.5-2.0 26.78 8.83 2.70 5.65 2.5-3.0 26.06 8.86 1.45 5.33

26/03/2013

0.5-1.0 21.86 3.95 7.20 4.19 1.5-2.0 26.01 7.92 3.25 5.30 2.5-3.0 24.26 8.53 3.10 5.60

20/06/2013 0.5-1.0 32.15 9.89 0.25 5.56 1.5-2.0 25.02 7.93 5.10 5.82

08/08/2013

0.5-1.0 37.12 11.54 0.16 6.46 1.5-2.0 30.83 9.14 5.91 6.72 2.5-3.0 25.42 8.70 3.78 5.88

21/10/2013

0.5-1.0 34.42 10.29 1.45 6.12 1.5-2.0 25.86 7.90 3.51 5.37 2.5-3.0 25.30 7.99 2.66 5.17

Figure 3-25: Iss variation with starting moisture content for soils at 0.5-1.0 m depth in Braybrook

20 22 24 26 28 30 32 34 36 38 400

1

2

3

4

5

6

7

8

9

10

11

12 Shrinkage strain (%) Swell strain (%) Iss (%)

Stra

in a

nd I ss

(%)

Gravimetric moisture content (%)

97

Another set of samples was taken from a different site which was tested for Iss during

this study. The site is located in Burnside area, which is one of the western suburbs of

Melbourne. Red-brown clay soil was found within the top layer of this site. The site had

a house which was damaged due to abnormal moisture condition. The collected samples

had different in situ moisture content even if the boreholes were closely located (within

2 m radius). Four samples were tested, and Table 3-10 shows the Iss results for those

samples. There is a considerable increase in Iss with the increase in moisture content.

Hence, these results suggest that Iss can be dependent on in situ moisture content. The

effect of such changes of Iss on site classification is described in the next section.

Table 3-10: Iss results of Burnside samples

In situ moisture content

(%)

Shrinkage %

Swell % Iss

27 8.9 3.9 6.1 41 13.2 0 7.4 46 15.9 0.1 8.9 49 17 0 9.4

3.6.2 Effect of Iss changes on site classification

According to the calculation of ys for classifying the site, the instability index is

calculated using Iss and crack depth, as described in the previous chapter. The instability

index increases the effect of Iss below the crack depth by means of lateral restraint factor

(α). Therefore, even deeper depths show a slight variation in moisture and hence Iss,

which can significantly affect the ys calculation.

The ys was calculated using different Iss values given in Table 3-9 and the specified

parameters in AS2870 (2011). The standard specified that a suitable Hs of 2.3m and a

crack depth of 0.75Hs for the Melbourne area. ΔU is specified as 1.2 pF. The ys was

calculated from Iss obtained at three different periods representing wet, dry and

moderate soil moisture content, as shown in Table 3-11.

98

Table 3-11: Calculation of ys using different Iss values

Depth (m) ΔZ (mm)

Average ΔU (pF) for layer

α

Iss (%) at different soil moisture condition ys (mm)

Wet

08

/08/

2013

Mod

erat

e 02

/08/

2012

Dry

26

/03/

2013

Wet

Mod

erat

e

Dry

0-1.0 1000 1.026 1 6.46 5.51 4.19 66.3 56.5 43.0 1.0-1.5 500 0.591 1 6.46 5.51 4.19 19.1 16.3 12.4

1.5-1.725 225 0.378 1 6.72 5.65 5.3 5.7 4.8 4.5 1.725-2.3 575 0.2 1.62 6.72 5.65 5.3 12.5 10.5 9.9

Total ys 103.6 88.1 69.7

This site was then classified based on ys values and the site classification given in

AS2870 (2011). According to the standard, the highly reactive class (H2) includes ys

values from 60 to 75 mm. Sites with ys higher than 75 mm are classified as extremely

reactive (class E). Based on the different ys values obtained at different periods, this site

can be classified as class E in wet and moderate soil moisture conditions whereas it is

classified as H2 in dry conditions. Hence, a footing design performed for the same soils

collected at different times of the year would result in different designs.

3.7 SUMMARY

This chapter describes the impact of climate on the footing design procedure given in

AS2870. Soil and climate interaction is the natural mechanism by which changes occur

in soil moisture. The climate condition governs the amount of water available for

infiltration and, therefore, it influences the changes in moisture contents at the surface

as well as the depth of moisture change. The Australian Standard uses TMI to classify

the climate condition and then correlates the parameters in soil moisture profile with the

climate categories. Six climate zones are given in the current Standard, based on TMI

values and the corresponding depth of suction change (Hs) values. The suction change at

the surface (ΔU) is also dependent on the climate condition; however, the current

Standard provides a single value (1.2pF) for all regions in Australia. Hs and ΔU are the

key parameters in estimating surface movement and hence govern the footing design.

99

There are certain issues in using TMI to consider the impacts of climate on footing

design. The first issues relates to its ability to correlate the soil moisture condition. The

TMI largely depends on rainfall and consequently, linear correlations were observed

between annual rainfall and TMI variations in most of the cities in Victoria. Therefore,

the influence of the other climate components such as evaporation, relative humidity

and wind are not considered in in determining soil moisture changes.

Second, several methods exist to calculate the TMI and each method produces different

values. Irrespective of the calculation method, it appears that there is an ongoing drying

in the Victorian climate. The calculation method used in AS2870 is not clearly

identified. Since the Standard provides the TMI map developed in 1960s and Method 1

is based on the procedure given by Thornthwaite in 1957, it appears that Method 1

produces the closest results to the values provided by the Standard.

Since each TMI calculation method produces different values, the correlation between

TMI and Hs results in different values for the same climate condition. This can result in

different footing designs. In addition, the use of the average TMI also produces different

values. Specifically, the more years used in the average calculation, the lesser the

sensitivity to extreme weather events, such as droughts. The long-term average TMI is

appropriate to reflect long-term trends. However, for the residential footing design, this

averaging period needs to be considered together with more soil specific parameters.

Apart from these issues in using the TMI to correlate with soil moisture changes, the

correlations given in AS2870 are based on climate data in 1960s. The modifications to

AS2870 in the 2011 edition captured the changes of TMI due to the drought effect

experienced in the last 25 years. However, this may not be enough to capture ongoing

changes. Furthermore, the values of Hs and ΔU have not been updated to reflect the

recent changes and possible changes in the future.

In addition to Hs and ΔU, Iss is the next important parameter in estimating surface

movement which also appear to be dependent on in situ moisture content. The

Australian standard AS1289 specifies Iss as a constant for a given soil type. In this

research, soils collected from a field site at different times of the year were tested and a

number of Iss values were obtained for the same soil. The results indicated that the Iss

increases with increasing in situ moisture. This shows the dependency of Iss on in situ

100

moisture, which is in contrast to the specifications outlined in the Australian standard

AS1289. It can result in different footing designs for a particular site, when the soils are

tested at different times of the year. These issues highlight the importance of a

comprehensive understanding of the impacts of climate conditions on soil moisture

changes and the subsequent ground movements. The climate-induced soil moisture

changes governed by site and soil characteristics are described in the next chapter.

101

4. FIELD AND LABORATORY INVESTIGATIONS OF EXPANSIVE

SOIL BEHAVIOUR

4.1 INTRODUCTION

For this research, a suitable field site was necessary to collect soil moisture and ground

movement data. The site required to have typical expansive soils (Basaltic clays) which

would be found in Western Melbourne. Lab testing on soils was undertaken to establish

the suitability of the various sites for the study. The lab tests included Atterberg limits,

linear shrinkage, shrink swell index test, particle size distribution and mineral

composition. This chapter describes the site selection and the lab test results of the

selected site.

4.2 SITE SELECTION CRITERIA

The main purpose of site selection was to identify a vacant block of land with

reasonably reactive soils. Therefore, the available geology maps were examined to find

an appropriate area.

Most of the Melbourne suburbs have been established on blankets of lava flows rest on

an erosion surface of Tertiary and Quaternary sediments such as Brighton group

sediments (Thomas, 1967). These extensive lava flows belong to newer volcanos

(Werribee plane phase) which is comparatively young in terms of geological time

(Thomas, 1967). The thickness of basalt flows varies from place to place. Deep surface

weathering occurred over millions of years resulted in deposits of residual clay. These

newer volcanic soils extent most parts of western Victoria towards the corner of South

Australia (Dahlhaus and O'Rouke, 1992). These quaternary volcanic soils are mostly in

dark to light grey, and associated with inter-bedded silty sands and backed soils

(Thomas, 1967). The distribution of Quaternary Basalts soil is shown as pink colour in

Figure 4-1 (Maps, 2015). Mann (2003) provided an expansive soil map of Victoria, as

shown in Figure 4-2, which suggests that most of the basalt soils shown in Figure 4-1

are expansive. The dark red and orange areas in Figure 4-2 have highly reactive

cracking clay soils whereas the yellowish areas have calcareous clay soils. According to

this map, most of the soils in west part of Melbourne are moderate to highly reactive.

102

Therefore, the investigations were aimed at the Western suburbs to find a suitable site to

be monitored.

Figure 4-1: Geology of Melbourne and the location of Braybrook site - extracted from 1:31680 map of Melbourne (Maps, 2015)

More than ten typical residential blocks of land were initially investigated in the

Western part of Victoria, which were likely to have reactive soils. Most of these sites

are owned by the Victorian Office of Housing who is one of the supporting partners of

this research project. The soils collected from Heidelberg, Rosebrook, Horsham,

Taylors Hill, Williams landing, Point Cook and Braybrook were tested for an indication

of reactivity. A primary consideration was to find a vacant land with reactive soils that

could be categorized as class H to E based on AS2870. A tree on the site was also a

desirable feature. Most of the sites previously contained dwellings but these dwellings

had been demolished for redevelopments. The monitoring plan was to use the intact area

of the lands that corresponded to the old back yards of the dwellings.

Alluvial flats, mud flats, beach & estuarine depositsAlluvial terraces

Basalts

Basalts

Non-marine silts & clays (pre-Tertiary basalt)

Mudstones, siltstones & sandstones

Marine & non-marine sands, cays, ferruginous sand& gravels

Quaternary

Tertiary

Silurian

Melbourne CBD

N

Braybrook

103

Figure 4-2: Distribution of expansive soils in Victoria (after Mann (2003))

Figure 4-1 shows the location of the Braybrook site in the west part of the Melbourne.

Braybrook was an industrial suburb, however, residential areas have begun to appear in

this area due to the expansion of the Western suburbs. Therefore, many redevelopments

have been ongoing since last decade. The selected site consists of three adjacent blocks

of about 1000 m2 each, which previously held three single storey houses. Figure 4-3

shows the aerial view of the Braybrook site that was taken before the demolition of the

houses. Those houses were demolished in 2010 for redevelopments and the land

currently belongs to the Victorian Office of Housing. Each of the blocks had relatively

large back yards as shown in Figure 4-3, making them ideal for field monitoring. Some

trees are visible in Figure 4-3 and most of them were also pulled down during the

demolition work. However, there are plenty of intact areas to perform a field

investigation on expansive soil behaviour.

N

Highly calcareous loamy earth soils (Alluvial)

Sandy soils with clayey subsoils (Alluvial)

Hard setting loamy soils with clayey subsoils Clay soils (Alluvial)

Hard setting loamy soils with clayey subsoils Clay soil (Basaltic)

Cracking Clay soil (Alluvial)

Cracking Clay soil (Basaltic)

Friable loamy soils (Basaltic)

Peats

Lakes

Braybrook

104

Figure 4-3: Google map view of the Braybrook site and samples collected locations (Google image was taken in 2010)

The identified site in Braybrook is virtually a flat site. One of the blocks has a mature

and isolated Paper Bark tree, which is an optimal condition for the purpose of

monitoring. Figure 4-4 shows the current view of the three blocks in Braybrook site.

N

Location 1

Location 2

Location 3

105

Figure 4-4: Three adjacent blocks of Braybrook Site

Based on the Atterberg limits and linear shrinkage results at different depths, Braybrook

soils appeared to be highly reactive. The descriptive explanation of the basic soil test

results is provided in the next sections.

Since the Braybrook site can be categorized as a highly reactive site that has space and

fulfils the other requirements of the study, this site was selected for long-term field

monitoring.

4.3 SOIL CLASSIFICATION

In Braybrook, clay soils with a slight colour variation along the depth were found

during the soil sampling. Disturbed and undisturbed soil samples were collected from

depths down to 3.5 m in various locations. Tubes of 50 mm diameter were used to

obtain the undisturbed soil samples. The length of a tube sample is 0.5 m and samples

were capped as soon as they were taken out of the ground to prevent moisture loss.

Tubes were labelled on site with the date, location and depth. Normally three

undisturbed soil samples were collected from each borehole at various depths.

Disturbed soil samples were collected in between the depths of tube samples and

continued up to 3.5 m. Disturbed soils were collected into polythene bags, tied to

prevent moisture loss and labelled.

106

Tube samples were extruded using a hydraulic extruder and used to determine shrink-

swell index, suction and mineral composition measurements. Figure 4-5 shows the cross

section of an extruded undisturbed sample at 2.5-3.0 m depth. The appearance of the

soil below 2.0 m depth seems to be consistent as shown in Figure 4-5. Both disturbed

and undisturbed samples were used to obtain the Atterberg limits, linear shrinkage and

particle size distribution.

Figure 4-5: Cross section of an undisturbed sample extruded from a tube (2.5 -3.0 m)

4.3.1 Soil profile

The soil profile of the Braybrook site appears to be consistent and the soil colour

changes gradually towards the bottom. The top soil layer contains a certain amount of

grass roots and the soil between 1.0 to 1.5 m is slightly calcareous. The soils at the

bottom tend to be stiffer, as shown in Table 4-1.

Table 4-1: Soil profile at Braybrook

Depth (m) Soil description

0.0-0.3 Clay (CH), Dark Brown, Soft, Root fibres present

0.3-0.5 Clay (CH), Dark Brown, Stiff,Root fibres present

0.5-1.0 Clay (CH), Brown, Stiff, Slightly calcareous

1.0-1.5 Clay (CH), Brown to dark gray, Stiff, Slightly calcareous

1.5-2.0 Clay (CH), Dark gray to light gray, Very stiff, Slightly calcareous

2.0-2.5 Clay (CH), Light gray, Very stiff, Slightly calcareous

2.5-3.0 Clay (CH), Light gray, Very stiff

3.0-5.0 Clay (CH), Light gray, Very stiff

107

Figure 4-6 shows a cross section of the soil profile. This pit was excavated to collect

undisturbed samples for further testings. The isolated calcrete layer about 1.5 - 2.0 m

depth can be clearly seen in Figure 4-6. The gradual change of the colour is also visible.

The site has a deep clay profile and the bedrock was not hit even after excavating to 4.5

m depth.

Figure 4-6: Cross section of the soil profile of Braybrook site exposed through an excavation

4.3.2 Atterberg limits and linear shrinkage

Atterberg limits tests (AS1289.3.1.1, 2009) were performed at different depths to

identify the variation of the properties. The tests were conducted from soils collected at

three different locations (shown in Figure 4-3). Tables 4-2 to 4-4 show the results of

Atterberg limits and linear shrinkage tests. All three locations show similar variation of

soil properties, and the variation of average results are shown in Figure 4-7. The plastic

limit varied from 20 to 25% and the liquid limit varied from 70 to 80% throughout the

depth. Linear shrinkage test (AS1289.3.4.1, 2008) results were within 17 to 19%.

According to the values of plasticity index (PI) and linear shrinkage, the Braybrook soil

was recognized as highly reactive (Hazelton and Murphy, 2007).

Ground level

~0.5 m

~1.0 m

~1.5 m

~2.0 m

~2.5 m

Isolated layer of calcrete

108

Table 4-2: Basic soil test result - Location 1

Depth Range(m)

LL PL PI LS (%)

0-0.5 77.0 30.1 46.9 16.5

0.5-1.0 74.1 23.0 51.1 18.9

1.0-1.5 74.2 24.0 50.2 18.1

1.5-2.0 58.7 24.8 33.9 17.8

2.0-2.5 82.6 24.7 57.9 19.5

2.5-3.0 66.1 19.3 46.8 18.3

3.0-3.5 72.8 20.9 51.8 18.1

3.5-4 77.0 23.8 53.2 17.3


Depth Range(m)

LL PL PI LS (%)

0-0.5 75.3 25.4 50.0 17.5

0.5-1.0 73.3 26.3 47.0 18.1

1.0-1.5 64.8 22.3 42.4 18.6

1.5-2.0 72.0 22.5 49.5 16.4

2.0-2.5 66.6 17.8 48.8 17.3

2.5-3.0 68.3 23.2 45.1 16.7

3.0-3.5 73.0 21.0 52.0 19.0

3.5-4 81.0 24.4 56.6 16.9


Depth Range(m)

LL PL PI LS (%)

0-0.5 70.6 27.7 42.9 21.5

0.5-1.0 81.8 18.6 63.2 19.7

1.0-1.5 82.5 23.1 59.4 19.4

1.5-2.0 82.6 18.3 64.3 20.4

2.0-2.5 81.7 21.1 60.6 18.1

2.5-3.0 95.4 26.4 69.0 16.3

3.0-3.5 88.1 23.4 64.7 17.2

3.5-4 68.9 16.4 52.5 20.7

109

Figure 4-7: Atterberg limits and linear shrinkage variation with depth

Based on the Liquid Limits and Plasticity Index values given in Figure 4-7, the fine-

grained soil up to 3.5 m depth can be located above the “A” line in Figure 4-8.

Therefore, this soil can be classified as Fat clay (CH) according to the Unified soil

classification (ASTM-D2487, 2011).

Figure 4-8: Location of Braybrook clay in plasticity chart (ASTM-D2487, 2011)

Braybrook clay

110

4.3.3 Particle size distribution and density tests

The fine particle percentages of the soils at different depths were analysed using

Hydrometer test (ASTM-D422, 2007). A solution of sodium hexametaphosphate was

used as dispersing agent as the Braybrook soil is slightly calcareous and may tend to

remain aggregated. The specific gravity of the soils, which is a required parameter to

analyse the Hydrometer test results, was obtained using a water pycnometer (ASTM-

D854, 2010) as shown in Figure 4-9.

Figure 4-9: a) Hydrometer test, b) Specific gravity test

Figure 4-10 shows the variation in particle size with depth. According to the results, the

clay content of the soil below 0.5 m depth is about 45% and is consistent up to 3.5 m.

The top soil layer was contaminated with grass roots and some organic material.

Specific gravity and clay content values are lower at the top layer which reflects the

presence of organic material.

111

Figure 4-10: Specific gravity and fine particle percentages variation with depth in Braybrook Soil

4.3.4 Mineral composition of the soil

A clay mineralogy analysis was performed using X Ray Diffraction (XRD; (Burnett,

1995) to determine the mineral composition of the Braybrook soil. Results from the

quantitative XRD analysis are shown in Table 4-5. The mineral compositions of the soil

at two different depths are almost identical, which confirms the consistency of the basic

soil properties.

The high content of Quartz is related to Silica in the soil that comes from different sizes

of minerals. They can be originated from sandstone, fine argillaceous sediments,

mudstone, claystone or siltstone. However, Braybrook soils have less than 10% of sand,

and therefore, this Quartz may represent the clay size and silt size minerals. The higher

content of Montmorillonite provides evidence of the expansive properties. Similar

expansive properties were reported in Tadanier and Nguyen (1984) for soils with

similar clay mineralogy.

112

Table 4-5: Mineral composition of Braybrook clay

Mineral Depth

0.5-1.0 m 1.0-1.5 m

Quartz (%) 53 59

Montmorillonite (%) 32.5 31

Mica/ Illite (%) 5.5 2

Kaolinite (%) 4 4

Albite (%) 2.5 2

Orthoclase (%) 2 2

Anatase (%) <1 <1

4.4 SITE CLASSIFICATION ACCORDING TO AS2870

The next purpose of soil tests was to classify the site that states the effect of the

reactivity of the site on residential structures. The site classification procedure explained

in AS2870 is based on the shrink-swell characteristics of the soil. This behaviour of the

clay soil can be obtained using the shrink-swell test (AS1289.7.1.1, 2003).

4.4.1 Shrink-swell characteristics of Braybrook soil

A one-dimensional consolidometer was used to measure the swell percentage of the soil

under a 25 kPa surcharge load. The core shrinkage test (Mitchell and Avalle, 1984) was

performed to obtain the shrinkage percentage. The two tests were started at in situ

moisture condition for the undisturbed samples collected at three different depths. Then

the shrink-swell index (Iss) values were calculated in accordance with AS1289.7.1.1

(2003) and their variation with depth is shown in Table 4-6. Iss test was performed many

times during this study to investigate its dependency on in situ moisture content as

described in section 3.6.1. However, the values shown in Table 4-6, which were

considered in site classification, are the results at one location tested during the initial

stage of site selection.

113

Table 4-6: Iss values of Braybrook soil at different depths

Depth from

surface (m)

Iss

(%)

0.5 – 1.0 5.69

1.5 – 2.0 5.62

2.5 – 3.0 5.88

4.4.2 Site classification

The site classification requires the Hs, ΔU and the depth of the soil cracks in that

particular area. According to AS2870 (2011), Hs is 2.3 m for Melbourne and ΔU is 1.2

pF. The crack depth is defined as 0.75 of Hs for Melbourne. Based on those values and

the Iss values given in Table 4-6, the layer movements have been calculated and the ys is

obtained as shown in Table 4-7.

Table 4-7: ys calculation

Layer depth - Z(m)

∆Z (m) ∆U

Iss (%)

α Ipt

(%) ys

(mm) 0.0 – 1.0 0.5 0.963 5.69 1 5.69 54.8 1.0 - 1.725 0.725 0.514 5.62 1 5.62 20.9 1.725 – 2.0 0.275 0.236 5.62 1.63 9.16 5.9

2.0 - 2.3 0.3 0.104 5.88 1.58 9.29 2.9 Total ys 84.5

The calculated ys is higher than 75 mm which is the lower limit of class E (Table 2-4)

and hence the site was classified in the Extremely reactive category.

4.5 DEVELOPMENT OF MAIN EXPANSIVE SOIL PARAMETERS

Models developed to describe the volume change behaviour of expansive soil due to

moisture changes commonly use suction as a main soil characteristic (Fredlund and

Rahardjo, 1993, Fredlund and Vu, 2003, Mitchell and Avalle, 1984). This is because

suction represents the stress state of the soil (Fredlund and Rahardjo, 1993). The

relationship between suction and moisture content is one of the two main constitutive

114

parameters (Likos, 2000). The amount of water that can be held by the soil pores at

certain suctions varies with the soil type (Likos, 2000). Water can be trapped in soil

pores and this amount can also change with the compaction of the soil (Dingman,

2002). Hence, the relationship of suction and water content (SWCC) is an important

parameter, which is essential to study expansive soil behaviour.

The moisture content of soil varies with time due to changes in climate conditions. This

phenomenon associates with the permeability of the soil at different moisture contents.

The hydraulic conductivity allows water to flow easily through the porous media and

therefore depends on many soil parameters including pore size, soil grain size and the

amount of water held in the pores (Fratta et al., 2007). It can therefore also be correlated

to the soil suction. This relationship is called the hydraulic conductivity function.

The following sections describe the details of the development of SWCC and the

hydraulic conductivity function of Braybrook soil.

4.5.1 Soil Water Characteristic Curve (SWCC)

The negative pore water pressure created due to water content in soil pores is called

matric suction (Fredlund and Rahardjo, 1993). The variation of matric suction with

water content is expressed by SWCC. Therefore, matric suction and the corresponding

moisture content should be measured to obtain the coordinates of SWCC. The moisture

measurements are straight forward and can be performed simultaneously with the

suction measurements. The moisture content of the soil can be expressed in various

forms. Therefore, SWCC function can be plotted using volumetric water content,

gravimetric water content or degree of saturation. However, the constitutive model

explanations of volume change in expansive soil are associated with volumetric basis

(Fredlund and Rahardjo, 1993, Fredlund and Vu, 2003, Mitchell and Avalle, 1984) and

therefore Braybrook SWCCs have been developed based on both the matric suction and

the volumetric water content.

4.5.1.1 Soil suction

A variety of equipment and different techniques can be used to measure soil suction.

Each of the techniques has its own measuring range and different equilibration time to

produce readings. Table 4-8 shows approximate equilibration time and the measuring

rage of different instruments and techniques. None of the available equipment can

115

measure the full range of suction in SWCC function and therefore the development of

SWCC must be performed in different stages with different equipment.

Table 4-8: Approximate measurement ranges and times for equilibration in measurement and control of soil suction (Murray and Sivakumar, 2010)

Instrument Suction component measured

Typical measurement range (kPa)

Equilibration time

Pressure plate Matric 0-1,500 Several hours to days Tensiometers and suction probes Matric 0-1,500 Several minutes Thermal conductivity sensors Matric 1-1,500 Several hours to days

Electrical conductivity sensors Matric 50-1,500 Several hours to weeks

Filter paper contact Matric 0-10,000 or greater 2-57 days

Thermocouple psychrometers Total 100-8,000 Several minutes to several hours

Transistor psychrometers Total 100-70,000 About 1 hour Chilled mirror psychrometer Total 1-60,000 3-10 minutes

Filter paper non-contact Total 1,000-10,000 or

2-14 days greater

Electrical conductivity of pore water extracted using pore fluid squeezer

Osmotic entire range —

Suction control

Negative (or Hanging) water column technique Matric

0-30 or greater with multiple columns or vacuum control

Several hours to days

Axis translation technique Matric 0-1,500 Several hours to days Osmotic technique Matric 0-10,000 up to 2 months Vapour equilibrium technique Total 4,000-600,000 1-2 months

During the development of Braybrook SWCCs, the high suctions (dry soils) were

measured using WP4C (Decagon, 2012). WP4C uses the chilled mirror psychometric

technique and hence it measures the total suction of the soil. The low suctions (wet

soils) were measured from Hyprop (UMS, 2013). The Hyprop uses the tensiometer

technique which measures the matric suction. However, there is a gap between the

measurable suction ranges of these equipment and that gap was filled using

conventional filter paper measurements. Both total suction and the matric suction can be

measured using the filter paper test and, as a result, the osmotic suction can be

116

calculated. The osmotic suction, which is created by salt concentration of the soil,

appears almost as a constant with the moisture content (Fredlund and Rahardjo, 1993).

The filter paper test was therefore used in this study to obtain the osmotic suction and

then to convert the WP4C readings into matric suction.

4.5.1.2 Hyprop measurements

Hyprop (UMS, 2013) is an instrument specifically developed to produce SWCC of soil

in wet conditions. This instrument uses the tensiometer technique to measure the suction

of soil. The tensiometers consist of a high air entry ceramic tip connected to one end of

a hollow shaft carrying de-gassed water and the other end of the shaft is connected to a

pressure transducer. When the porous tip is inserted into the soil sample, the water is

drawn from the tensiometer due to the suction difference until the stress of the water

inside the tensiometer is equal to the suction of the soil (Murray and Sivakumar, 2010).

The soluble salts that create the osmotic suction can transfer freely through the porous

tip (Murray and Sivakumar, 2010). Therefore, pressure transducer records only the

matric suction. The Hyprop arrangement can take continuous weight measurements of

the soil and can measure the suction in addition to the corresponding moisture content,

which are essentially the coordinates of SWCC.

The initialization of the instrument takes few hours and some experience to set it up

properly. The measurements begin from the saturated stage and continue until the

sample is dried out. The moisture evaporates from the top surface of the sample during

the test. The clay soils take a longer time than sandy soils to reach the dry stage so the

total measurement time can vary from a few hours to few weeks depending on the soil

type.

The Hyprop device uses undisturbed soil samples of 80 mm diameter and 50 mm

height, as shown in Figure 4-11. The samples cannot be taken out of normal tube

sampling, which has a 50 mm diameter. Indeed, 80 mm is an uncommon tube size and it

is difficult to push this size of a ring into soil using a vehicle mounted rig to collect

undisturbed soil at deeper depths. Therefore, the Hyprop samples were collected from a

pre-excavated pit in the Braybrook site shown in Figure 4-12. An eight tonne excavator

was used to dig a 3 m deep pit in a 2x3 m area. The pit was excavated as steps of 0.5 m,

117

as shown in Figure 4-12, to allow access at roughly 0.5 m depths for sample collection.

This pit also helped to visually examine the soil profile in Braybrook site (Figure 4-6).

Figure 4-11: Hyprop sample in the ring

Figure 4-12: Excavation of a pit in Braybrook site to collect Hyprop samples

118

Undisturbed soils were collected into sampling rings using the apparatus that is

provided with the Hyprop devices, as shown in Figure 4-13. The sampling rings were

pushed into soils by hammering and removed by clearing the surrounding soil. The

samples were trimmed at the site, as shown in Figure 4-11, and labelled with the depths

before being taken to the laboratory.

Figure 4-13: Excavation of undisturbed samples using Hyprop sampling device

The samples were saturated under a surcharge pressure corresponding to their depth.

The soil bulk density was about 2 gcm3. For example, soil samples at 0.5 m depth were

saturated under 10 kPa pressure and two porous plates were placed at the top and

bottom to prevent the samples dispersing in water. Next, the samples were submerged in

distilled water (Figure 4-14) and the swelling of the soil was also monitored during

saturation. The samples were left submerged for at least two weeks to confirm that full

saturation was achieved.

119

Figure 4-14: Hyprop samples saturation under a surcharge

Once the saturation process was completed, the Hyprop apparatus was initialized to start

the test. This process involves refilling the tensiometers and the Hyprop sensor unit. The

refilling kit provided with the Hyprop device was used. Figure 4-15 shows the initial

steps of the refilling process. Distilled and de-gassed water must be used for refilling.

De-gassing can be performed using syringes with spacer snaps and once the water is de-

gassed, the tensiometers should be filled without trapping air bubbles. The tensiometers

must be kept in an upright position as shown in Figure 4-15(a). The bottom syringe is

filled with de-gassed water and all the air bubbles must be removed before connecting

to the ceramic tip of the tensiometer. The top syringe is half filled with de-gassed water

and suction is applied by locking the spacer snaps, as shown in Figure 4-15(a). The de-

gassed water from the bottom syringe is forced to travel to the top syringe through the

ceramic tip and the shaft of the tensiometer. This process removes all the air entrapped

in the tensiometers and at least 2 hours is required for this process. The Hyprop consists

of two tensiometers and both of them can be refilled at the same time using four

syringes. The Hyprop sensor unit must also be filled with de-gassed water using the

acrylic attachment and a syringe as shown in Figure 4-15(b).

120

Figure 4-15: Refilling of de-gassed water; a) into tensiometer, b) into Hyprop sensor unit

The refilled tensiometers are then attached to the sensor unit while monitoring the

pressure developed at the pressure sensors. The “tensioVIEW” software, which comes

with the Hyprop equipment, was used to monitor the pressure during the initialization

process. The Hyprop sensor unit needs to be connected to a computer before the

tensiometers attach to the provided slots in the sensor unit. The pressure reading of the

sensor must be carefully monitored and, as described in the manual, should not be

allowed to exceed 100 kPa during the tensiometer attaching process (UMS, 2013). O-

rings are pushed over each of the tensiometer shafts to prevent the entering of dirt

during the test and a silicon gasket is also placed through tensiometers to avoid contact

between the sensor base and the sample as shown in Figure 4-16.

The Hyprop device comes with a balance that can be connected to a computer. The

weight measurements can be recorded using “tensioVIEW” software. Therefore, the

Hyprop sensor unit and the balance were connected to a laptop computer to record the

suction and weight during the test period.

a) b)

121

The saturated soil sample is then prepared to insert two tensiometers. The tensiometers

are in two different heights, as shown in Figure 4-16. This is to measure the suction at

top and bottom of the sample. The top tensiometer is 50 mm long and penetrates about

37.5 mm into the soil samples. The tip of the top tensiometer is located approximately

12 mm below the top surface of the soil. The bottom tensiometer is 25 mm long and

penetrates about 12.5 mm into the soil. An augur with an adapter is provided with the

Hyprop device to make two holes in the soil sample similar to the heights of the two

tensiometers to be penetrated into the soil.

Figure 4-16: Suction measuring unit of Hyprop device(UMS, 2013)

Figure 4-17 shows the sample, with two holes drilled at the bottom surface, ready to

insert the tensiometers. The holes must be filled with de-gassed distilled water before

inserting the tensiometers. The sensor unit with tensiometers is attached to the soil

sample using two fastener clips at either side (Figure 4-18). The sensor is then

connected to the laptop computer and the arrangement is placed on top of the balance

(Figure 4-19). The readings can be recorded in pre-specified time period. The readings

have been recorded in 1 minute intervals during the first few hours of the test and

extended to 10 minutes later.

122

Figure 4-17: The auger adapter and the sample with two holes drilled in the bottom surface

Figure 4-18: The soil sample attached to the Hyprop sensor unit

The moisture evaporates during the test period from the surface of the sample, which

leads to changes in suction and the weight of the soil. The test was conducted inside an

environmental chamber to smoothen the evaporation process and to avoid the unwanted

interruptions such as turbulent wind over the samples surface, disturbance to the

balance, etc. The humidity and the temperature were set to 60% and 20 0C inside the

chamber.

123

Figure 4-19: The Hyprop test is running inside the environmental chamber

The measurements continued for 5 to 7 days. The moisture evaporation from the top

surface crated cracks, as shown in Figure 4-20, which propagated towards the bottom.

Once a developed crack reaches the tensiometer, the porous tip is exposed to the air. At

this point, the tensiometer fails and starts reading an untrue value for the soil suction.

The Hyprop test can be stopped at this point. The dried out sample is shown in Figure

4-20. During the drying process of the Hyprop test, the clay samples tend to stick to the

tensiometer shaft and therefore, it is difficult to remove the samples immediately after

the test. This can be overcome by placing the sample in a water bath after the test

without letting water get into the cable outlet of the sensor unit. Leaving the sample in a

water bath for a few hours will moisturize the samples and facilitate removal from the

sensor unit. The entire soil sample needs to be collected including soils attached to

124

sample ring and the tensiometer shafts. Then, the sample is placed in an oven at 105 0C

to determine the oven dry weight.

Figure 4-20: The soil sample at the end of the Hyprop test

UMS (2013) has provided another software called “HYPROP” to analyse the data

collected from tensioVIEW to develop the SWCC. This software requires the data file

from tensioVIEW and the oven dry weight of the soil sample. The “HYPROP” software

uses the top and bottom tensiometer readings and calculates the representative matric

suction of the soil at a particular time. It uses the initial volume of the soil (the volume

of the sampling ring) and the provided oven dry soil weight to calculate the volumetric

moisture content of the soil. However, for expansive soil, the calculation procedure of

volumetric moisture content of the soil is incorrect in the drying stage. This is because

the expansive soils undergo a significant volume change and cracking during the drying

process hence, the volume of the soil at a particular time cannot be considered as the

volume of the sampling ring. This problem has been overcome using the relationship

between volumetric moisture content and the gravimetric moisture content for the

Braybrook soil. The instant weight of the soil at each record has been extracted from

“HYPROP” software and then the gravimetric moisture contents were calculated using

the oven dry soil weight. Next, they were converted into volumetric moisture contents

using the relationship shown in Figure 4-21. This relationship has been developed using

125

undisturbed samples collected from Braybrook site at different depths. The first point

has been assumed such that, at the zero percent volumetric moisture content,

gravimetric moisture content is also zero. The relationship has an R2 value of 0.99.

Figure 4-21: Relationship between volumetric and gravimetric moisture consents in Braybrook soil

Figure 4-22 shows a portion of SWCC obtained using Hyprop devices as described

above. Appendix-A provides the necessary calculations related to the Hyprop test.

Figure 4-22: A portion of typical SWCC developed using Hyprop

0 5 10 15 20 25 30 35 400

10

20

30

40

50

60V

olum

etric

Moi

stur

e C

onte

nt (%

)

Gravimetric Moisture Content (%)

y = -0.014x2 + 1.9168xR2= 0.99

1 10 1000.35

0.40

0.45

0.50

0.55

Volu

met

ric M

oist

ure

Con

tent

Matric Suction (kPa)

Hyprop measurements

126

4.5.1.3 WP4C measurements

WP4C (Decagon, 2012) measures the total suction of the soil using the chilled-mirror

psychometric technique. The suction readings can be observed in “MPa” units and the

conventional “pF” units. As shown in Figure 4-23, the WP4C consists of a temperature

controller, temperature sensor, mirror and a photo detector cell. The sample must be

placed in a standard ring of 37.5 mm diameter and about 8 mm in height. The sample

ring is made out of plastic or metal. The sample is placed on the drawer and pushed into

the chamber. When the switch is turned to the “READ” position, the sample is raised

and the chamber is sealed to begin the measurement process. Therefore, the sampling

cup must not entirely fill with the samples to prevent the contamination of the sensor

while sealing the chamber.

Figure 4-23: Schematic of chilled-mirror dew-point device (after Leong et al. (2003) )

When the switch is turned to the “READ” position, the equilibration process begins

which makes the relative humidity of the air above the soil equal to the relative

humidity of the air in the soil pore spaces (Murray and Sivakumar, 2010). This takes a

certain amount of time depending on the soil type and the moisture content of the soil.

Once the equilibrium is achieved, the mirror is cooled by carefully controlling the

temperature using a Peltier current (Murray and Sivakumar, 2010). When the

temperature of the mirror reduces, the vapour starts to condensate on the mirror at a

certain point, called the dew point, and it can be recognized by the photo detector cell

because of the difference of the reflection from the mirror (Leong et al., 2003). By using

dew point temperature and the controlling temperature, the relative humidity is

127

calculated and then it can be correlated to the total suction using Equation 4-1 (Bulut et

al., 2001, Leong et al., 2003, Likos, 2000).

𝛹 = −𝑅 × 𝑇

𝜐 × 𝜔ln (𝑅𝐻) .……………...……………………………...…… Equation 4-1

where, Ψ is the total suction in kPa, R is the universal gas constant (8.31432 J/mol.K), T

is the absolute temperature in K, υ is the specific volume of water and ω is the

molecular mass of water vapour in kg/kmol. RH is the relative humidity.

According to Equation 4-1, the total suction is zero when RH is 1 (100% relative

humidity) and it increases with decreasing RH. The chilled-mirror dew point device can

measure the relative humidity up to an accuracy of ±0.01% (Leong et al., 2003). If pure

water is placed in the sample cup, it would record 100% relative humidity, because the

partial pressure of pure water at the equilibrium stage is similar to the saturated vapour

pressure at a particular temperature. This means that the suction of the pure water,

which is essentially the matric component, is zero. However, the partial pressure of the

unsaturated soil pores is less than the saturated vapour pressure of the pure water due to

the pore structure and the free ions of salts in pore water (Bulut et al., 2001). Therefore,

it will result in a relative humidity less than 100% and hence a higher total suction.

The above-mentioned phenomenon is also used to calibrate the chilled-mirror

psychometric devices. The slope of the linear correlation of suction and relative

humidity shown in Equation 4-1 is fixed during the factory calibration and hence only

the zero offset needs to be occasionally fixed (Decagon, 2010). Therefore, the

calibration process needs only one measurement of known suction. Any salt solution

with known osmotic suction can be used to calibrate WP4C. Osmotic suctions of

different salt solutions can be found in the literature (ASTM-D5298, 2003, Decagon,

2010, Bulut et al., 2001). The calibration was achieved by measuring the suction of 0.5

molar KCl and adjusting the value to 2.2 MPa, its suction at 20 0C. However, in this

study, two more standard liquids were used to confirm the measurements from WP4C,

as shown in Figure 4-24. The WP4C manual recommends checking the calibration at

least once in every 50 sample measurements (Decagon, 2010).

128

The WP4C is capable of reliably measuring higher suctions, up to 300 MPa.

Measurements less than 5 MPa can have ±0.05 MPa error whereas the suctions above 5

MPa only have a ± 1% error (Decagon, 2010).

Figure 4-24: Standard liquids used to calibrate the WP4C

For the suction measurements in Braybrook soil, undisturbed samples were used. The

extruded tube samples were prepared to place into WP4C sampling cups using a special

cutting ring and a piston arrangement shown in Figure 4-25. This cutting ring and the

piston arrangement used to prepare the samples without touching the soil. This is

required to measure in situ suctions without losing moisture. However, for the purpose

of measuring suctions to obtain SWCC, the moisture contents of the samples have been

changed in the laboratory. Those samples were prepared in the WP4C sample cups and

then different amounts of water drops were added to change the moisture content. The

sample cups were then sealed and left for few days to achieve the equilibrium before

measuring the suction.

Figure 4-25: Soil sampling devises used to prepare WP4C samples

129

Figure 4-26 illustrates measuring the suction using WP4C. The samples were placed in

the oven in order to achieve the correct moisture content after the suction

measurements. The gravimetric moisture contents were measured and then converted

into volumetric moisture contents using the same relationship used in Hyprop

measurements shown in Figure 4-21.

Figure 4-26: The sample is ready to measure suction using WP4C

Figure 4-27 shows a typical set of suctions obtained from WP4C to develop the later

part of the SWCC. The WP4C measurement data related to Braybrook soil can be found

in Appendix-B. The matric suctions have been used to plot graphs which were obtained

using the osmotic suctions. A filter paper test was employed to obtain osmotic suction

which is described in the next section.

130

Figure 4-27: A portion of typical SWCC developed using WP4C

4.5.1.4 Filter paper measurements

The filter paper method is one of the conventional methods of suction measurements.

By allowing filter papers to attain equilibrium with the soil through vapour or liquid

transfer, the suction can be estimated. If a filter paper equilibrates to the soil’s vapour,

without contacting the specimen, it measures the total suction of the soil. At the same

time, if another filter paper makes contact with the soil and equilibrates with the soil

moisture, it measures the matric suction component (Bulut et al., 2001). The

equilibrium time can vary from days to weeks depending on the soil type and the

moisture content of the soil (Murray and Sivakumar, 2010). Once the equilibrium state

is achieved, the moisture content of the filter papers can be measured and the suction

can be obtained using calibration curves. The contacted filter papers can measure

suctions in a broader range (0-10,000 kPa) compared to non-contacted filter papers

which can only measure suctions within 1000-10000 kPa (Murray and Sivakumar,

2010, Rahardjo and Leong, 2006). A further description of the filter paper suction

procedure can be found elsewhere (ASTM-D5298, 2003, Bulut et al., 2001, Leong et

al., 2002, Fredlund and Rahardjo, 1993).

1000 10000 1000000.10

0.15

0.20

0.25

0.30

0.35

0.40

Vol

umet

ric M

oist

ure

Con

tent


WP4C measurements

131

The undisturbed soil samples collected at different depths were used to measure filter

paper suctions in Braybrook soil. Whatman No. 42 filter papers were used and 47 mm

diameter filter papers were used to measure the total suction whereas matric suction

measurements were taken using 42.5 mm diameter papers. Soil samples of 50 mm

diameter and 100 mm height were used as shown in Figure 4-28. The samples were kept

at least 14 days to reach the equilibrium before measuring the weights of the filter

papers. The standard calibration equations (Figure 4-29) provided in ASTM-D5298

(2003) have been used to obtain the total and matric suctions from filter paper moisture

contents.

Figure 4-28: Filter paper suction measurements of Braybrook soil

Table 4-9 shows the filter paper suction measurements of Braybrook soil. The

calculated osmotic suctions have also been presented in Table 4-9. The Braybrook soil

is slightly calcareous from 0.5 m to 2.5 m and an isolated calcrete layer was observed

about 1.5 to 2.0 m in some places (Figure 4-6). The effect of calcrete can be clearly

observed in terms of osmotic suctions. The soils containing CaCO3 have higher osmotic

suctions than the rest of the soils. All the filter paper suction measurement data related

to Braybrook soil can be found in Appendix-C.

132

Figure 4-29: Calibration Suction-Water Content Curves for Wetting of Filter Paper (ASTM-D5298, 2003)

Table 4-9: Filter paper readings of Braybrook soil

Depth (m)

Gravimetric moisture

content of sample (%)

Total suction (kPa)

Matric suction (kPa)

Osmotic suction (kPa)

0.3-0.8 23.01 2346 1630 716 36.84 779 47 732 29.05 858 238 620

0.5-1.0 24.41 1580 488 1091

1.5-2.0 21.11 4682 2379 2303 23.15 3990 1322 2669 23.45 3958 1355 2604

2.5-3.0 22.18 2243 1586 657

Even though some soils as depicted in Figure 2-6 show almost constant osmotic suction

values irrespective of the moisture contents (Fredlund and Rahardjo, 1993), the

Braybrook results in Table 4-9 show a considerable variation. However, if the soils that

0 10 20 30 40 50 60 70 80 90 1000

1

2

3

4

5

6

Log(kPa) = 2.412 - 0.0135w

Suc

tion,

Log

(kP

a)

Filter paper water content (%)

Log(kPa) = 5.327 - 0.0779w

133

are not contaminated with calcrete are considered, the osmotic suction has changed

within a small range (from 620 kPa to 732 kPa) which appears to be acceptable with the

errors of measurements.

4.5.1.5 Braybrook SWCC

SWCC functions were developed for soils taken at different depths from the Braybrook

site. Matric suction and the corresponding volumetric moisture contents were obtained

as described in the previous sections. The osmotic suction of a particular soil is fairly

constant with the moisture content (Fredlund and Rahardjo, 1993). Apart from the

isolated calcrete layer, the Braybrook soil appears to be consistent. Table 4-9 suggests

that the soils with no calcrete contamination have approximately constant osmotic

suction over a wide moisture range. Since WP4C provides total suction, the osmotic

suctions calculated from the filter paper test were used to convert them into matric

suctions. However, when converting the total suction into matric suction, the very high

suction measurements taken from WP4C have a minimal influence from the osmotic

component.

VADOSE/W package in Geo-Slope (2013) software was used to draw appropriate

curves of SWCCs using measured points. Since there were enough measurements of

suction and corresponding moisture content, SWCCs were drawn using a smooth line

along the measured point and therefore, available estimating models in GeoSlope were

not used. Figure 4-30 shows the developed SWCCs for different depths in Braybrook.

Different markers used in Figure 4-30 to indicate the measurements made using

Hyprop, Filter paper method and WP4C. These SWCCs were used to develop the finite

element model of expansive soil described in the following chapters. SWCCs of soils at

different depths have almost identical functions and this reflects the consistency of the

soil properties discussed in the previous sections.

134

Figure 4-30: SWCCs of soil from Braybrook site at different depths

4.5.2 Hydraulic conductivity function

The moisture movement in soils can be explained by the hydraulic conductivity

(permeability) of soil and is dependent on the void ratio and the moisture content

(Fredlund and Rahardjo, 1993). The saturated hydraulic conductivity (Ksat) depends on

the void ratio of the soil, however, it is usually considered as a constant in transient flow

analysis (Fredlund and Rahardjo, 1993). The ability of moisture movement in

unsaturated soils can be observed using hydraulic conductivity verses matric suction

relationship, which is called hydraulic conductivity function.

Ksat can be measured using conventional methods such as the falling head and constant

head permeability test. However, measuring unsaturated hydraulic conductivity is

difficult as it changes considerably in the transient process (Fredlund and Rahardjo,

1993). Therefore, certain empirical correlations can be used to develop the hydraulic

conductivity function. The following section describes the Ksat measurement and the

development of hydraulic conductivity function for Braybrook soil.

1 10 100 1000 10000 1000000.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

Vol

umet

ric M

oist

ure

Con

tent


0-0.3 m 0.3-0.8 m 0.8-1.3 m 1.3-1.8 m 1.8-2.5 m

Markers for different measurements; Squares:- Hyprop, Circles:- Filter paper, Triangles:- WP4C

135

4.5.2.1 Saturated hydraulic conductivity

The saturated hydraulic conductivities of Braybrook soils were obtained using the

constant head method. The tri-axial apparatus was used to apply the head differences.

The undisturbed soil samples collected at different depths were used to perform the

tests. The specimen diameters were approximately 50 mm and the lengths

approximately 100 mm. The specimens were covered with a flexible membrane and

then placed in a tri-axial machine as shown in Figure 4-31. An appropriate surcharge

pressure was applied based on the depth of the sample and then the sample was allowed

to become saturated before proceeding to the consolidation stage, as explained in

ASTM-D5084 (2003). When the sample is consolidated, a pressure difference was

applied between the top and the bottom flows while maintaining a constant sample

pressure. The pressure difference was kept at 2-3 kPa as explained in the standard. The

flow rates were recorded in 60 minute intervals. Table 4-10 shows a typical data sheet

of the Ksat test. All the Ksat measurement data related to the Braybrook soil can be found

in Appendix-D.

Figure 4-31: Saturated hydraulic conductivity test for Braybrook soil using tri-axial machine

136

Table 4-10: Saturated hydraulic conductivity data sheet

Material Specification

Saturation Duration

Reading Duration

Sample Diameter (cm)

Sample Area (cm2)

Sample height, L

(cm)

24 hours

48 hours

0.50 19.634375 10.6

Curing Duration

Water Temperature (°C)

Cell pressure

(kPa) Flow

direction Cell

Diameter (cm)

Water density at test temperature

(gr/cm3)

24 hours 20 410.4 Downward 0.75 0.998207

Readings

Reading No

Reading (cm3)

Q (cm3)

Time (sec)

q (cm3/sec)

Top Pressure (kPa)

Bottom pressure (kPa)

Δ h (cm)

i=Δh/L k (m/sec)

1 127.936 13.5 3600 0.00377 410.4 407.9 24.48 2.31 8.32E-07

2 141.521 12.4 3600 0.00345 410.4 407.9 24.48 2.31 7.62E-07

3 153.959 12.5 3600 0.00349 410.4 407.9 24.48 2.31 7.71E-07

4 166.538 12.3 3600 0.00342 410.4 407.9 24.48 2.31 7.56E-07

5 178.883 12.1 3600 0.00337 410.4 407.9 24.48 2.31 7.44E-07

6 191.032

3600

410.4 407.9 24.48 2.31

Average value 7.73E-07

Q: - flow amount, q:- flow rate, Δ h:- pressure head difference, L:- sample thickness, i:- hydraulic gradient, k:- hydraulic conductivity

Figures 4-32 and 4-33 show the variation of Ksat with the time of measurement. The

tests were continued til at least five consecutive readings appear fairly constant and

then the average of those readings was taken as the Ksat of the particular layer as shown

in Table 4-11. The Ksat of the surface layer is higher than that of the bottom layers

indicating that the top layer is different from the other layers as shown in basic soil

properties variation (Figures 4-7 and 4-10). The values of other layers are in the range

of dense clay soils (Das, 1998).

137

Figure 4-32: Variation of Ksat with time of measurement - top two layers

Figure 4-33: Variation of Ksat with time of measurement - bottom two layers

0 30000 60000 90000 120000 150000 180000 210000-1

0

1

2

3

4

5

6

7

8

9

10

Sat

urat

ed h

ydra

ulic

con

duct

ivity

(m/s

) x 1

0-7

Time after starting test (sec)

0-0.4 m 0.5-1.0 m

0 20000 40000 60000 80000 100000 1200000.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Sat

urat

ed h

ydra

ulic

con

duct

ivity

(m/s

) x 1

0-9

Time after starting test (sec)

1.0-1.4 m 1.5-1.8 m

138

Table 4-11: Saturated hydraulic conductivities of Braybrook soil

Sample depth (m)

Saturated Hydraulic

conductivity (m/s)

0.0 - 0.4 7.73 x 10-07 0.5 - 1.0 1.57 x 10-07

1.0 - 1.4 3.43 x 10-09

1.5 - 1.8 1.99 x 10-09

4.5.2.2 Prediction of hydraulic conductivity function

Hydraulic conductivity of unsaturated soils is less than Ksat of the soil because of the

reduction of area available to moisture flow (Briaud, 2013). It is difficult to measure the

hydraulic conductivity in the unsaturated state of the soil therefore empirical

correlations were used to develop the hydraulic conductivity function. GeoSlope

software has incorporated models to predict the hydraulic conductivity function using

SWCC. There are two models available in the software which were developed by

Fredlund et al. (1994) and Van Genuchten (1980). The software requires defining the

SWCC and Ksat of the particular soil to develop the hydraulic conductivity function.

However, a number of different equations are employed in these models, and they are

presented here.

Equations 4-2 to 4-4 show the equations used by Fredlund et al. (1994) to predict the

hydraulic conductivity function using the SWCC

𝑘𝑤 = 𝑘𝑠

∑𝜃𝑒𝑦−𝜃𝛹

𝑒𝑦𝑖𝜃′𝑒𝑦𝑖𝑁

𝑖=𝑗

∑𝜃𝑒𝑦−𝜃𝑠𝛹

𝑒𝑦𝑖𝜃′𝑒𝑦𝑖𝑁

𝑖=𝑗

.……...…….……………………...…… Equation 4-2

kw = the conductivity for a specified negative pore-water pressure (m/s),

ks = the measured saturated hydraulic conductivity (m/s),

θs = the volumetric water content,

e = the natural number 2.71828,

139

y = a dummy variable of integration representing the logarithm of negative pore-water

pressure,

i = the interval between the range of j to N,

j = the least negative pore-water pressure to be described by the final function,

N = the maximum negative pore-water pressure to be described by the final function,

Ψ = the suction corresponding to the jth interval

θ’ = the first derivative of the Equation 4-3

𝜃 = 𝐶(𝛹)𝜃𝑠

[ln [𝑒 + (𝛹

𝑎)

𝑛

]]𝑚 ………...…….……………………...…… Equation 4-3

a = approximately the air-entry value of the soil,

n = a parameter that controls the slope at the inflection point in the volumetric water

content function,

m = a parameter that is related to the residual water content,

C(Ψ) = a correcting function defined in Equation 4-4,

𝐶(𝛹) = 1 −ln (1 +

𝛹

𝐶𝑟)

ln (1+1,000,000

𝐶𝑟) ……..…….……………………...…… Equation 4-4

where, Cr is a constant related to the matric suction corresponding to the residual water

content and the typical value is 1500 kPa.

More details about the correlation can be found in Fredlund et al. (1994) and Vadose

(2013). For certain soils, Fredlund et al. (1994) predicts low conductivity in high

suction ranges. For example, the given correlation for the Yolo light clay given in

Fredlund et al. (1994) has a close match only up to 4 kPa. Therefore, the other available

correlations have also been considered in this study.

Van Genuchten (1980) also provided a correlation to predict the hydraulic conductivity

function using SWCC and saturated conductivity. Equation 4-5 shows the relationship

given by Van Genuchten (1980).

140

𝑘𝑤 = k𝑠

[1 − (𝑎𝛹(𝑛−1))(1 + (𝑎𝛹𝑛)−𝑚)]2

[(1 + 𝑎𝛹)𝑛]𝑚

2

….………......……...…… Equation 4-5

ks= saturated hydraulic conductivity,

a,n,m = curve fitting parameters,

n = 1/(1-m)

Ψ = required suction range.

Van Genuchten (1980) noted that the curve fitting parameters can be properly estimated

at the halfway point between saturated water content and the residual water content of

the SWCC of the soil. Therefore, those points must be specified to estimate the

hydraulic conductivity function. More details on the estimation procedure can be found

in Van Genuchten (1980) and Vadose (2013).

Figure 4-34 shows the predicted hydraulic conductivity functions for the surface layer

in the Braybrook site using Fredlund et al. (1994) and Van Genuchten (1980) models.

The predictions of the Fredlund et al. (1994) model are slightly higher at low suctions

whereas the Van Genuchten (1980) model predictions are considerably higher than the

Fredlund et al. (1994) model predictions at in the high suction range. The hydraulic

conductivity functions obtained from both models were used in a finite element model

analysis of Braybrook soil behaviour, which is described in the next chapters. However,

it appears that the conductivity functions obtained from the Fredlund et al. (1994) model

produces a closer match with field measured soil moisture contents. Figure 4-35 shows

hydraulic conductivity functions developed for the Braybrook site using the Fredlund et

al. (1994) model. The functions were obtained using SWCCs shown in Figure 4-30 and

the saturated hydraulic conductivities given in Table 4-11.

141

Figure 4-34: Predicted hydraulic conductivity functions for Braybrook soil at 0-0.4 m

Figure 4-35: Hydraulic conductivity functions (based on Fredlund’s model) of Braybrook soil at different depths

0.1 1 10 100 1000 10000 1000001E-16

1E-15

1E-14

1E-13

1E-12

1E-11

1E-10

1E-9

1E-8

1E-7

1E-6

1E-5

Hyd

raul

ic c

ondu

ctiv

ity (m

/s)


Van Genuchten (1980) model Fredlund et al (1994) model

0.1 1 10 100 1000 10000 1000001E-16

1E-15

1E-14

1E-13

1E-12

1E-11

1E-10

1E-9

1E-8

1E-7

1E-6

1E-5

Hyd

raul

ic c

ondu

ctiv

ity (m

/s)


0 - 0.4 m 0.5 - 1.0 m 1.0 - 1.4 m 1.5 - 1.8 m

142

4.6 SUMMARY

This chapter describes the selection of Braybrook site and the characterization of the

Braybrook soil. Since Western suburbs of Melbourne are well known for expansive

soils, more than 10 sites in West Melbourne were considered to select an appropriate

field site. The Braybrook site contains three large vacant blocks of lands and is

primarily a flat site. There is a deep profile of clay soils in Braybrook site. The top soil

layer of about 0.5 m consists of silty clay and some organic matter. Below the top soils,

plasticity indices are higher than 50% whereas linear shrinkages are about 18%

throughout the profile. These basic soil tests indicated that the soils are highly

expansive and consistent with depth. Taken together, these factors resulted in the

selection of the Braybrook for long-term field monitoring.

In addition to the basic soil tests, more specific properties were examined during the

laboratory investigation. A shrink well test was performed for soils collected at different

depths to determine the Iss. Then, the site was classified based on the AS2870 and was

classified in the extremely reactive category. However, X-Ray Diffraction tests revealed

that there is more than 50% of Quartz, which can be originated from sandstone, fine

argillaceous sediments, mudstone, claystone or siltstone. Since Braybrook soils have

less than 10% of sand, the Quartz content may represent the clay size and silt size

minerals. However, there is more than 30% of Montmorillonite in the mineral

composition in Braybrook clay that is a primary cause of the expansiveness. Similar

expansive characteristics were recorded in different Australian soils with a similar

Montmorillonite composition to the Braybrook clay.

More measurements were taken to determine the expansive soil characteristics. During

the development of SWCC, various equipment including Hyprop, WP4C and filter

papers were used to measure suctions at different moisture levels. SWCCs were

developed for soils collected at different depths. The soils below the top 0.5 m showed

similar SWCCs. Furthermore, saturated hydraulic conductivities were obtained using tri

axial apparatus. The top soils had higher Ksat value compared to the dense clay at the

bottom layers due to the presence of silty clay and organic matters. The ksat of bottom

layers were in the range of 10-9 ms-1. The hydraulic conductivities of unsaturated soils

143

were determined from available correlations with SWCC. These hydraulic conductivity

functions were developed for soils collected at different depths in the Braybrook site.

This comprehensive data set is beneficial for both practitioners and researchers. It

provides characteristics of typical basaltic clay found in West Melbourne which are

useful in site classification and modelling. Indeed, Braybrook soil properties were used

in prediction models developed in this study. The models require field monitoring data

and the next chapter describes the field monitoring and data analysis.

144

5. FIELD INSTRUMENTATION AND DATA ANALYSIS

5.1 INTRODUCTION

The selection and the soil properties of the Braybrook test site are described in the

previous chapter. The aim of the field instrumentation was to install devices required to

monitor the seasonal variation of soil moisture content and the subsequent ground

movement. The soil moisture variation was recorded using the neutron probe technique

and magnetic extensometers were used to measure the movement of the soil layers at

different depths. The movement of ground surface was monitored using small paving

blocks laid next to the magnetic extensometers. Details of those devices, the installation

procedure, calibration, data collection and the interpretation are described in this

chapter.

5.2 FIELD MONITORING SYSTEM

5.2.1 Overview

As described in the literature review chapter, the monitoring of soil moisture content

and the subsequent movement is a challenging task. A non-destructive and repeatable

technique is essential in the regular monitoring of soil moisture in a particular location

over long periods. In the current research, this task was achieved by using neutron probe

moisture measuring technique in this study.

Most previous investigations used ground movement probes to monitor soil movements.

However, in this technique, soil movement at different depths cannot be measured using

a single probe and hence many probes have to be used at different depths. This issue has

been overcome by using magnetic extensometers (HMA, 2013) in this study. The

magnetic extensometers consist of a datum magnet at the bottom, which can be placed

at a stable depth. The extensometer can be used to measure the soil movements at

different depths. More details on the magnetic extensometer are provided in the next

sections of this chapter.

5.2.2 Soil moisture monitoring

The neutron moisture measuring procedure followed in this study requires a neutron

probe and access tubes inserted to the deepest measurement depth. The following

145

section describes the installation, calibration and data collection of the neutron probe

technique.

5.2.2.1 Installation of access tubes

According to AS2870, Hs is specified as 1.8 – 2.3 m for Melbourne, which is the

possible depth of suction variation. It was decided to investigate moisture and soil

movements up to 3 m depth from the ground surface to cover the specified Hs with an

allowance for possible changes. At the Braybrook site, aluminium access tubes with a

diameter of 50 mm were installed up to 3 m depth. A gap between the soil and the

access tube can cause erroneous reading in neutron counts (Li et al., 2003b) and allow

unwanted ingress of surface water, therefore, the boreholes for the access tubes drilled

to the same diameter as the tubes and then the tubes were pushed into the holes (see

Figure 5-1) to achieve a neat fit. The first 200-300 mm of soils was very dry and hence

created certain gaps around the pipe. However, these gaps were closed after the

installation using the surrounding soil. Hence the rain water was not able to infiltrate

along the surface of the tube. Upon insertion of the access tubes into the ground about

100 mm of each tube was maintained above ground for the placement of the neutron

probe control unit, as shown in Figure 5-2. Access tubes were capped at the top to

prevent water intrusion while not in use.

Figure 5-1: Neutron probe access tube pushing into the borehole

146

Figure 5-2: CPN 503DR neutron probe used in the Braybrook site

5.2.2.2 Calibration of Neutron probe

The neutron probe provides the count of thermalised neutrons through interaction with

soil moisture. Therefore, a calibration curve is needed to convert the neutron count into

the volumetric moisture contents. The relationship between neutron counts and

volumetric moisture content is an exponential curve through the zero intercept (Ward

and Wittman, 2009). Undisturbed samples were collected from the bore holes cored to

insert the access tubes, and used to measure the volumetric moisture content. These

moisture contents and the probe readings collected on the installation date were used to

develop the calibration curve.

Volumetric moisture content (θ) and neutron counts (N) follow the relationship given in

Equation 5-1 where ‘A’ and ‘B’ are constants.

𝜃 = 𝑒𝐴 × 𝑁𝐵 ……………..…………….....……………………...…… Equation 5-1

Equation 5-1can be converted into a linear relationship to determine the A and B

constants as shown in Equation 5-2. The calibration curve of the neutron probe is shown

in Figure 5-3. The linear fit has an R2 of 0.86 (standard error = 0.028).

147

Equation 5-3 shows the calibration line with the obtained constants for the Braybrook

soil. This calibration was further checked and confirmed with more measurements

(neutron probe and collected soil samples) made during different days of the study.

These measurements are given in section 5.4.1.

ln(𝜃) = 𝐴 + 𝐵 × ln (𝑁) …..…………….....……………………...…… Equation 5-2

ln(θ )= -2.9406+0.7005 × ln(N) ….……….………………........…… Equation 5-3

Figure 5-3: Calibration curve of the neutron Probe

5.2.2.3 Neutron probe measurement procedure

The neutron probe is connected to its control unit via a cable and the length of this cable

is decided based on the required maxim depth of measurements. A 5 m cable was used

in the present study. The stoppings are attached to the cable (see Figure 5-2) to hold the

probe while collecting measurements.

9.15 9.20 9.25 9.30 9.35 9.40 9.453.45

3.50

3.55

3.60

3.65

3.70

Ln(V

olum

etric

mc

%)

Ln(Neutron counts)

Measured data Linear Fit Upper 95% Confidence Limit Lower 95% Confidence Limit

148

In this study, the stoppings were attached to the cable to collect readings at every 250

mm distance from the topmost measurement. Therefore, 11 stoppings were connected to

the cable, as shown in the schematic in Figure 5-4. When the probe is lowered into the

access tube via cable, the stopping can be clamped into the control to hang the probe at

the required depth. The lengths of the probe and the control unit are 300 m and 350 mm

respectively. A 100 m height portion of access tube protrudes from the ground to hold

the control unit, as demonstrated in Figure 5-4. The locations of stoppings of the cable

were arranged by considering those distances.

Figure 5-4: Schematic of neutron probe measuring arrangement

Once the probe is clamped at a certain depth, the measurements can begin. The time

allowance for emissions and the detection of neutrons can be selected as 16, 32 or more

seconds. An initial test was performed to observe the sensitivity of the time allowance

on the accuracy of the repetitive readings. It was found that 16 seconds produces

reliable, repetitive neutron counts. It was also useful to finish the measurements of all

149

the access tubes installed in the Braybrook site within a day. Measurements were taken

two times at each depth to calculate the average neutron count represent the moisture

level at particular depth. The distances of the stopping locations were converted to depth

from the ground surface and then the results expressed as shown in Table 5-1.

Table 5-1: Results from neutron probe measurements

Stop No

Depth from

Ground (mm)

NP Reading Trial 1

NP Reading Trial 2

Average NP

counts

Volumetric MC (%)

11 350 10613 10689 10651 35.00 10 600 11211 11234 11223 36.31 9 850 10897 10933 10915 35.61 8 1100 10913 10919 10916 35.61 7 1350 11527 11392 11460 36.84 6 1600 11795 11801 11798 37.60 5 1850 11826 11700 11763 37.52 4 2100 12119 11939 12029 38.12 3 2350 12185 12183 12184 38.46 2 2600 12225 12425 12325 38.77 1 2850 12538 12387 12463 39.07

Since, the radioactive material can be harmful for the health, the amount of neutron

absorbed to the persons involved in the measuring was carefully monitored. An

authorization certificate and training were required to use the neutron probe and users

wore a monitoring badge at all times. The badge was independently checked every three

months for neutron absorption.

5.2.3 Ground movement monitoring

5.2.3.1 Installation of magnetic extensometers

The installation procedure of the extensometer is a challenging task. After the spider

magnets are attached to the collapsible pipe at the desired spacing, the magnet legs are

folded and held together with temporary ties, as shown in Figure 5-5. Magnetic

extensometers are installed into pre-drilled boreholes. The diameters of the bore holes

are limited by the size of the folded legs of the magnets and the capability of them to

penetrate to the soil. If the borehole diameter is too large then the magnet legs cannot

penetrate the surrounding soil. The spider magnets used in this study were capable of

150

penetrating soil in a borehole up to 150 mm diameter. However, the compressed legs of

the magnets were able to push into 100 mm diameter borehole safely. The temporary

ties must be removed after installation, which will release the legs and allow them to

penetrate the soil. All the temporary ties are held by a steel code which is parallel to a

collapsible pipe and attached to the bottom using a glue tape. The steel cord is removed

after the installation and the magnet legs are allowed to unfold. They enter the soil with

the sudden releasing of the ties. Figure 5-6 shows the installation of one of the magnetic

extensometers in the Braybrook site. The prearranged spacing between the spider

magnets could change during the installation due to the flexibility of the collapsible pipe

and the pressure applied to insert into the borehole.

Figure 5-5: Releasing mechanism of the spider magnet in extensometer

151

Figure 5-6: Magnetic extensometer installation at the Braybrook site

The extensometers were covered using plastic caps as shown in Figure 5-7. Since the

measuring probe reads the distance between the spider magnets, a reference point at the

surface is required to convert the readings into layer depths. A concrete paver was

placed and kept undisturbed next to the extensometer (see Figure 5-7). The depths of

spider magnets were measured with respect to the level of this paver and its level was

considered as the ground level at that location. As demonstrated in Figure 5-7, a spirit

level was used to transfer the top level of the paver to the top of the extensometer

conduit pipe to obtain the measurements.

Figure 5-7: Ground surface movement measurements using extensometer

152

5.3 SITE LAYOUT

Figure 5-8 shows the monitoring locations in the Braybrook site. Three extensometers

are located on the site marked as E1, E2 and E3. All the extensometers were located in

the intact area of the blocks and away from the trees. The datum of the E1 extensometer

was placed 5 m below the ground surface while E2 and E3 had datum magnets at 4 m

depth. The access tubes for neutron probes were located next to each extensometer to

monitor the moisture variations along with the soil layer movements. Concrete paving

blocks of measuring 300x300 mm in plain area and 50 mm thick were placed on the

ground surface at locations marked as TP and CP. The purpose of the paving blocks was

to measure the movement of the ground surface which was done using a surveying

level. Moisture changes have been monitored close to each TP paver to monitor the

effect of trees on soil moisture. However, the measurements related to the tree are not in

the scope of this thesis. The E1 extensometer was located in the first block where the

tree is situated, while E2 and E3 extensometers were located in third block away from

the tree. CP paving blocks around E2 and E3 extensometers were placed in a grid of 2

m x 5 m. The purpose of those paving blocks was to check the deviation of ground

surface movement around extensometers.

Figure 5-8: Monitoring Plan of the Braybrook Site

TP 1 to 14 : Paving blocks around the treeCP 1 to 10 : Paving blocks away from the tree siteE 1 to 3 : Magnetic extensometersTN 6 : Neutron probe access tube close to E1CN 1 : Neutron probe access tube close to E2CN 2 : Neutron probe access tube close to E3

Location marks are not to scale

TN6

CN1

CN2

153

5.4 INVESTIGATION OF FIELD MONITORING DATA

The extensometers and the neutron probe access tubes were installed at two different

times. The extensometer E1 was installed in October 2012 and the other two were

installed in March 2013. The neutron probe access tubes which were inserted next to

extensometers are considered in this analysis. Neutron probe access tube denoted as

“TN6” was located next to the E1 extensometer. The neutron probe access tubes, CN1

and CN2 were located next to E2 and E3 extensometers, respectively. The data

collected from those locations are described in the following section.

5.4.1 Soil moisture profiles with time

The CN1 and CN2 were located close to each other and hence a similar moisture

variation was expected. However, slight differences in the clay content of surface soils

at two locations were observed. The CN2 location has a sandy top layer about 200 mm

and then gradually changed to silty clay and clay soil. Apart from the CN2 location,

such a different soil profile was not observed in other areas of the Braybrook site.

Hence, it could be a site disturbance from its previous usage. However, the area used to

perform the ongoing monitoring had been part of the back yard as shown in Google map

photo taken in 2010 (Figure 4-3). Some potholes surrounded by clay soil chunks were

observed near the CN1 location. There was also a slope difference on the ground.

Figures 5-9 and 5-10 show the moisture variation at CN1 and CN2 locations.

154

Figure 5-9: Volumetric moisture content profiles at CN1 location

Figure 5-10: Volumetric moisture content profiles at the CN2 location

The neutron probe calibration equation gives the volumetric moisture content and it also

has been used in the finite element modelling. Therefore, volumetric moisture content

has received more interest than gravimetric moisture content. The volumetric moisture

20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Dep

th (m

)

Volumetric moisture content (%)

10/04/2013 20/06/2013 21/08/2013 21/10/2013 11/12/2013 29/01/2014 26/02/2014 01/04/2014 01/05/2014 05/06/2014 08/07/2014 12/11/2014 25/03/2015

20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Dep

th (m

)


10/04/2013 20/06/2013 21/08/2013 21/10/2013 11/12/2013 29/01/2014 26/02/2014 01/04/2014 01/05/2014 05/06/2014 08/07/2014 12/11/2014 25/03/2015

155

content profiles at different times are considered in both figures. Since the top soils in

the CN1 and CN2 locations differ, a considerable offset can be observed in the moisture

results of the surface layer. The first measurements were taken at 0.35 m. Apart from

the top most measurements; the rest of the soil showed a similar moisture variation in

CN1 and CN2. There is not a significant moisture change below 1.25 m depth within

this 18-month period.

Figure 5-11 illustrates the volumetric moisture contents obtained from the TN6 location.

While the moisture variation is slightly different to the CN1 and CN2 locations, the

depth of moisture variation can be observed up to 1.25 m depth which is similar to the

other two locations. Interestingly, there was not a significant moisture variation

recorded at this location from May to November in 2014. Indeed, the moisture readings

at 0.41 m and 0.66 m depths appear to be constant during that period. This may be due

to a certain problem in that location or the access tube. These erroneous readings are

further discussed in the next section by comparing these readings to the extensometer

data from that location.

Figure 5-11: Volumetric moisture content profiles at the TN6 location

22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 520.0

0.5

1.0

1.5

2.0

2.5

Dep

th (m

)


10/04/2013 20/06/2013 21/08/2013 21/10/2013 11/12/2013 29/01/2014 26/02/2014 01/04/2014 01/05/2014 05/06/2014 08/07/2014 12/11/2014 25/03/2015

156

There can be a considerable influence from the cracks on the moisture content of deep

soil. Cracks were observed at the Braybrook site during the summer months and the

depths of these cracks were recorded using a thin steel cable, as shown in Figure 5-12.

Table 5-2 lists the crack depths around the access tubes that were observed in different

site visits. Some cracks of more than 0.75 m depth were also observed in the Braybrook

site. The observations given in Table 5-2 show the depth that steel cable can penetrate,

however, the actual crack depths could be greater than that. The runoff water from

rainfall can easily penetrate those cracks and can cause sudden moisture increments at

deeper depths. When the rainwater penetrated the cracks along the surface of the access

tube, it will result a high moisture reading from the neutron probe. This is an

unavoidable shortcoming of using the neutron probe technique in cracking soils. The

penetrated moisture becomes entrapped in the cracks when they close in the winter and

this can cause changes in the bottom soil. Therefore, even in a relatively small area of a

site, there can be locations with considerable differences in moisture contents. This

scenario can be observed in Figures 5-9 and 5-10.

Figure 5-12: Crack measurements using a steel cable

157

Table 5-2: Description of crack depth measurements at CN1, CN2 and TN6 locations

Date Crack description

CN1 CN2 TN6

26/02/2014

Few cracks around the

tube. Maximum depth was ~400 mm

Few cracks

around the tube.

Maximum depth was ~150 mm

Few cracks around

the tube. Maximum depth was ~100 mm

1/04/2014

Few cracks around the

tube. Maximum depth was ~650 mm

Two cracks

around the tube.

Maximum depth was ~300 mm

Few cracks around

the tube. Maximum depth was ~300 mm

1/05/2014 No cracks No cracks No cracks 5/06/2014 No cracks No cracks No cracks 8/07/2014 No cracks No cracks No cracks

12/11/2014

Few cracks around the tube with 300-500

mm deep. A gap of 350 mm deep

was observed beside the

tube

Few cracks

around the tube with 100 mm deep. A

small gap of 30 mm deep was observed beside the

tube

No cracks around the tube

but a small gap of 50 mm deep was observed beside the

tube

Gravimetric moisture contents were occasionally measured to observe the differences of

the neutron probe results. The samples were collected at different depths around the

TN6 location and the gravimetric moisture contents were measured from the collected

disturbed samples. The volumetric moisture contents obtained from the neutron probe

(NP) were converted into gravimetric moisture contents using the relationship shown in

Figure 4-21. Figure 5-13 shows a comparison highlighting that the direct measured

moisture contents are slightly different from the NP measurements. There is a difference

158

of approximately 3% between the direct measurements and NP measurements in deeper

depths. However, this difference was observed even within the measured values at

depths greater than 1.5 m, where it is unlikely to have such a moisture change. It should

be noted that gravimetric moistures corresponding to neutron probe readings shown in

Figure 5-13 were obtained using two conversions. The neutron counts were converted to

volumetric moistures using the calibration equation (Equation 5-3) and then were

converted to gravimetric moisture contents using the relationship shown in Figure 4-21.

The errors associated with those conversions could be a reason for the differences of

neutron probe and actual measurements shown in Figure 5-13. The surface soils have a

huge variation due to local effects. However, the NP measurements successfully

captured the trend of moisture variation.

Figure 5-13: Comparison of moisture contents obtained from the neutron probe and the samples

All three locations shown in Figures 5-9 to 5-11 have similar moisture variation at

deeper depths. The moisture contents have fluctuated severely within the surface layer.

The changes below 1.25 m are negligible and within the standard error of the NP

calibration. Figure 5-14 shows the soil moisture variation at CN1 with the monthly

rainfall. The rainfall data were obtained from nearby weather station from the Bureau of

15 20 25 30 35 40 45 50

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Dep

th (m

)

Gravimetric moisture content (%)

20-Jun-13 NP 21-Aug-13 NP 21-Oct-13 NP 11-Dec-13 NP 20-Jun-13 Measured 21-Aug-13 Measured 21-Oct-13 Measured 11-Dec-13 Measured

159

Meteorology. According to Figure 5-14, the moisture content of the top soil changed in

response to the monthly rainfall. The moisture contents of upper layers reflect the

rainfall pattern with a certain time lag, which is due to the permeability of the soil. This

pattern can also be interrupted by the cracks on the surface in dry season. The

fluctuations of the moisture contents are gradually decreasing with the depth. The

moisture content variation at 1.6 m depth provides evidence of this lower sensitivity to

monthly rainfalls within those 18 months.

Figure 5-14: Volumetric moisture content (VMC) change comparison with monthly rainfall (Location – CN1)

Interestingly, when the moisture variation is plotted with the daily rainfall, as shown in

Figure 5-15, it highlights that the surface moisture variation is more sensitive to the

daily rainfall variation rather than the monthly rainfall. This behaviour is prominent in

the summer and hence indicates the effect of the cracks on the moisture content of the

surface layer.

Jan-13 Apr-13 Jun-13 Sep-13 Dec-13 Mar-14 Jun-14 Sep-140

10

20

30

40

50

60

70

80

90

100 Monthly Rainfall (mm) VMC at 0.35 m VMC at 0.60 m VMC at 0.85 m VMC at 1.10 m VMC at 1.35 m VMC at 1.60 m

Month

Mon

thly

Rai

nfal

l (m

m)

20

25

30

35

40

45

50

Vol

umet

ric m

oist

ure

cont

ent (

%)

160

Figure 5-15: Volumetric moisture content (VMC) change comparison with daily rainfall (Location – CN1)

5.4.2 Ground movement monitoring

The extensometer readings were also taken on the same dates as the NP measurements.

Tables 5-3 to 5-5 show the soil movements observed from E1, E2 and E3

extensometers, respectively. Distances between the spider magnets measured on the

installed date are considered as the initial thickness of the layers. The distance between

the ground surface paving block and the first spider magnet is considered as the top

layer. The results of the regular measurements are shown as the differences of the layer

thicknesses with respect to the immediate previous measurements. Hence, the positive

values represent swell movement and the negative values indicate shrink movement.

1/01/2013 31/05/2013 28/10/2013 27/03/2014 24/08/20140

5

10

15

20

25

30

35

40 Daily Rainfall (mm) VMC at 0.35 m VMC at 0.60 m VMC at 0.85 m

Date

Dai

ly R

ainf

all (

mm

)

20

25

30

35

40

45

50

Vol

umet

ric m

oist

ure

cont

ent (

%)

161

Table 5-3: Soil layer movements from E1 extensometer

Initial layer

thickness (m)

Change of the layer thickness with

respect to previous visit reading (mm)

05/1

0/20

12

07/0

2/20

13

26/0

3/20

13

20/0

6/20

13

21/0

8/20

13

21/1

0/20

13

11/1

2/20

13

29/0

1/20

14

26/0

2/20

14

01/0

4/20

14

01/0

5/20

14

05/0

6/20

14

08/0

7/20

14

03/0

9/20

14

12/1

1/20

14

25/0

3/20

15

Top layer 0.983 -9 -3 30 13 1 3 -24 -11 -3 15 4 3 3 -18 -13 2nd layer 0.748 -3 1 -3 4 2 2 1 0 -1 -1 0 1 -1 2 2 3rd layer 1.062 2 -1 3 -2 0 1 0 1 -1 0 0 0 0 0 0 4th layer 0.450 3 0 2 -2 0 0 0 0 1 0 0 0 0 0 0 Bottom layer 1.727 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 4.970 -7 -3 32 13 3 6 -23 -10 -4 14 4 4 2 -16 -11 Incremental change (0 mm at start)

0 -7 -10 22 35 38 44 21 11 7 21 25 29 31 15 0


Initial layer

thickness (m)

Change of the layer thickness with respect to previous visit reading

(mm)

04/0

3/20

123

26/0

3/20

13

20/0

6/20

13

21/0

8/20

13

21/1

0/20

13

11/1

2/20

13

29/0

1/20

14

26/0

2/20

14

01/0

4/20

14

01/0

5/20

14

05/0

6/20

14

08/0

7/20

14

03/0

9/20

14

12/1

1/20

14

25/0

3/20

15

Top layer 0.750 -1 14 2 0 -4 -16 -2 0 8 4 -5 2 -5 6 2nd layer 0.976 0 12 -4 1 4 -3 -4 -3 -3 -2 0 2 0 -2 3rd layer 1.044 0 0 0 0 0 0 0 0 -1 1 0 -1 1 1 Bottom layer 1.078 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 Total 3.848 -1 26 -2 1 0 -19 -6 -3 4 3 -5 3 -5 5 Incremental change (0 mm at start)

0 -1 25 23 24 24 5 -1 -4 0 3 -2 1 -4 0

162


Initial layer

thickness (m)

Change of the layer thickness with respect to previous visit reading

(mm)

04/0

3/20

123

26/0

3/20

13

20/0

6/20

13

21/0

8/20

13

21/1

0/20

13

11/1

2/20

13

29/0

1/20

14

26/0

2/20

14

01/0

4/20

14

01/0

5/20

14

05/0

6/20

14

08/0

7/20

14

03/0

9/20

14

12/1

1/20

14

25/0

3/20

15

Top layer 0.803 1 23 9 0 -4 -29 -2 0 9 3 5 2 -13 7 2nd layer 1.092 -1 0 6 3 1 1 -5 -3 -2 -1 0 0 0 0 3rd layer 1.059 0 4 -4 1 0 -1 1 0 0 0 0 0 -1 1 Bottom layer 1.036 0 0 0 -1 0 1 0 0 0 0 -1 0 1 -1 Total 3.990 0 27 11 3 -3 -28 -6 -3 7 2 4 2 -13 7 Incremental change (0 mm at start)

0 0 27 38 41 38 10 4 1 8 10 14 16 3 0

All three extensometers reveal that there are significant movements occurred in the top

layer and less movement in the second layer. The spider magnets of the magnetic

extensometers are roughly 1 m apart. A change of level between adjacent magnets,

which are embedded in the surrounding body of soil, is considered to be a movement of

the soil layer contained between the two magnets. The top layer shows more than 80%

movements of the total movement in all three locations. The lower layers moved a little

and in fact, they moved by less than the error margin of the extensometer (±2mm).

Therefore, the remaining 20% of movement is likely to be within the second layer of

soil. However, moisture changes plotted in Figures 5-9 to 5-11 show that no significant

moisture changes occurred below 1.25 m, and hence it is suggested that no significant

soil movement occurred beyond that depth. This is mainly because the observations are

limited to a short period of monitoring (approx. 2 years).

Figure 5-16 shows incremental ground surface movements measured at three locations.

Extensometer E1 recorded a total seasonal movement of 54 mm within the two-year

period, whereas E2 and E3 recorded 29 mm and 41 mm seasonal movement,

respectively, in the 18-month period. The higher movement recorded in E1 suggests that

there is a variation of soil properties and other local effects within the site. The unusual

163

changes in moisture content in CN2 location as described in Section 5.4.1 could be the

reason for lesser ground movement observed in E2 location.

Figure 5-16: Surface movements measured at 3 locations and monthly rainfall

Figures 5-17 to 5-19 shows the variation of soil movements from the extensometer with

rainfall. The three locations showed similar variations in soil movement patterns. These

figures illustrate the swell movements in winter and settlements in the summer. Surface

movements follow the monthly rainfall pattern, i.e., the higher the depth of soil, the

lesser the sensitivity of soil to the rainfall pattern.

0

20

40

60

80

100

120

Mon

thly

rain

fall

(mm

)

29 mm

1/10/2012 1/04/2013 1/10/2013 1/04/2014 1/10/2014-15

-10

-5

0

5

10

15

20

25

30

35

40

45 Monthly rainfall (mm) E1 - Surface movement E2 - Surface movement E3 - Surface movement

Date

Incr

emen

tal s

oil m

ovem

ent (

mm

)

54 mm

41 mm

164

Figure 5-17: Soil movements in response to monthly rainfall - E1 extensometer


0

20

40

60

80

100

120

140

Mon

thly

rain

fall

(mm

)

25/10/2012 25/04/2013 25/10/2013 25/04/2014 25/10/2014-15

-10

-5

0

5

10

15

20

25

30

35

40

45

50 Monthly rainfall (mm) Surface movement Movement at 0.983 m Movement at 1.731 m Movement at 2.793 m Movement at 3.243 m

Date

Incr

emen

tal s

oil m

ovem

ent (

mm

)

0

20

40

60

80

100

120

Mon

thly

rain

fall

(mm

)

1/03/2013 1/09/2013 1/03/2014 1/09/2014-15

-10

-5

0

5

10

15

20

25

30 Monthly rainfall (mm) Surface movement Movement at 0.750 m Movement at 1.726 m Movement at 2.770 m

Date

Incr

emen

tal s

oil m

ovem

ent (

mm

)

165


This behaviour of the soil movements is comparable with the moisture variation

described in the previous section. The severe moisture changes in the top layer caused

the subsequent volume changes. Even though soil movements recorded in the E1

extensometer were relatively similar to the E3 during May to November 2014, the TN6

access tube, which is next to E1, showed no change in moisture contents during that

particular period. This provides strong evidence that there was something went wrong at

TN6 location during that period. Therefore, TN6 readings were ignored and CN1 and

CN2 locations were considered in modelling the moisture changes of the Braybrook soil

using a finite element model.

The level changes of paving blocks placed around E2 and E3 extensometers provide

evidence for differential ground movement in a relatively small area. Table 5-6 shows

the movement paving blocks CP1 to CP10 in the site layout shown in Figure 5-8. The

datum of E3 extensometer was considered in measuring these levels. The pavers also

indicate a similar settlement and heave movement trend to the extensometers. They

follow similar pattern in heave and settlements with the monthly rainfall variation as

shown in Figure 5-20. However, there are some level differences among these blocks,

which highlight the influence of local effects such as surface slope differences, potholes

and cracks which created differential moisture changes and hence ground movement

0

20

40

60

80

100

120

Mon

thly

rain

fall

(mm

)

1/03/2013 1/09/2013 1/03/2014 1/09/2014-15

-10

-5

0

5

10

15

20

25

30

35

40

45 Monthly rainfall (mm) Surface movement Movement at 0.803 m Movement at 1.895 m Movement at 2.954 m

Date

Incr

emen

tal s

oil m

ovem

ent (

mm

)

166

within 10 m2 area. Cracks were observed around the pavers during the summer months.

However, soils were certainly wet underneath the pavers due to prevention of

evaporation from the paver.

Table 5-6: Movements of paving blocks

Paver No

Height (m) above the datum

on 26/03/2013

Change of the height above datum with respect to previous visit reading (mm)

20/0

6/20

13

21/0

8/20

13

21/1

0/20

13

11/1

2/20

13

29/0

1/20

14

26/0

2/20

14

1/04

/201

4

1/05

/201

4

5/06

/201

4

8/07

/201

4

3/09

/201

4

12/1

1/20

14

CP1 4.008 31 12 2 -3 -36 -6 7 5 2 4 2 -22 CP2 3.981 30 15 5 0 -44 -6 8 5 0 4 3 -17 CP3 3.985 32 11 2 -4 -28 -5 4 3 -1 4 4 -4 CP4 3.976 30 8 2 -4 -28 -6 8 2 0 4 4 -5 CP5 3.985 25 3 0 -4 -11 -1 7 -5 0 3 0 0 CP6 3.951 27 7 -1 -2 -24 -1 8 0 1 3 1 2 CP7 3.970 30 10 0 -3 -28 -4 7 1 1 3 2 -14 CP8 3.959 31 13 1 -4 -35 -5 7 9 0 4 3 -12 CP9 3.977 32 17 1 -2 -32 -5 6 0 2 4 3 -7 CP10 3.981 26 8 3 -2 -22 -5 7 -1 1 3 1 -4 Average 29 11 1 -3 -29 -5 6 3 1 4 2 -9 Stdv 3 4 2 1 8 2 3 4 1 1 1 8 Min 25 3 -1 -4 -44 -6 -3 -5 -1 3 0 -22

Max 32 17 5 0 -11 -1 8 10 2 4 4 2

167

Figure 5-20: Incremental paver movements with monthly rainfall

5.5 SUMMARY

This chapter explains the installation of field monitoring instruments in Braybrook site

and the details of the monitored data over a two year period. Monitoring soil moisture

changes and consequent ground movements were the focus of the field monitoring. The

neutron probe technique was used to monitor soil moisture changes. Hence, neutron

probe access tubes were installed at a number of locations in the Braybrook site. The

neutron probe reads the number of neutrons that interact with soil moisture. Therefore, a

calibration equation was developed between neutron counts and volumetric moisture

content. Field samples were collected at different times to cross check the results

obtained from the neutron probe readings. Another correlation was developed between

volumetric and gravimetric moisture contents to help in comparing readings obtained

from neutron probe and the field samples in Braybrook site. The comparison showed

that neutron probe readings gave similar moistures as field sample measurements but

include about 3% difference, possibly due to errors in measurement and calibration.

Magnetic extensometers were installed in Braybrook at three locations next to the

neutron probe access tubes. They were used to measure surface and sub-surface soil

0

20

40

60

80

100

120

Mon

thly

rain

fall

(mm

)

1/09/2012 1/03/2013 1/09/2013 1/03/2014 1/09/2014-10

-5

0

5

10

15

20

25

30

35

40

45

50

55 Monthly rainfall (mm) CP1 CP2 CP3 CP4 CP5 CP6 CP7 CP8 CP9 CP9 CP10

Date

Incr

emen

tal p

aver

mov

emen

t (m

m)

168

movements. This monitoring was continued regularly from April 10th, 2013 to March

25th, 2015.

Seasonal moisture variations were observed at three locations over the two year period.

All these locations showed similar moisture profiles at deeper depths. However, there

were some differences in near surface measurements possibly due to local effects such

as slope differences, potholes and grass cover changes. The soil moisture changes were

observed to occur down to about 1.25 m over the monitored periods. The most

significant changes were observed in the top 0.75 m soils. Monthly moisture values of

near surface soils followed the rainfall pattern with a certain time lag. This time lag

indicated the influence of soil permeability. The seasonal heave and settlements were

observed in three magmatic extensometer located next to the neutron probe access

tubes. Similar to the moisture changes, most of the movements occurred in the top soil

layers. The maximum average seasonal ground movement was in the range of 40-50

mm. In addition to the magnetic extensometer readings, surface movements were

measured using paving blocks placed at certain grid points around the extensometer

locations. The levels of paving blocks confirmed the overall ground movement pattern

as shown in the extensometers. The monitoring data collected from this field monitoring

were used to developing a prediction model that is described in the next chapter.

169

6. MODELLING OF MOISTURE CHANGES IN EXPANSIVE SOIL

6.1 INTRODUCTION

As described in the previous chapter, the moisture changes of expansive soils under

open field condition in response to seasonal climate conditions were observed during

the regular site monitoring. These types of soil moisture changes occur during the

design life of a residential structure and the difference of changes in open ground and

covered areas can have substantial consequences on the performance of the structures.

Therefore, the footings of light weight structures must be designed to withstand such

conditions. It is impractical to monitor the expansive soil behaviour for a long period,

therefore, modelling such effects helps to observe the long term responses and to review

the relevant design procedures.

In this study, the finite element modelling approach was used to determine the long-

term moisture movement in expansive soil. More specifically, the Vadose/w package of

GeoSlope, a commercially available software, was used to analyse the soil and climate

interaction. The initial phase of the study was performed using a one dimensional model

to observe the vertical moisture movement in an open ground. The model was validated

using the Braybrook field data collected over a period of two years as presented in the

previous chapter. Using this validated model, the effect of different climate conditions

on soil moisture was investigated. The model was then extended into two dimensional

domain to observe the effect of cover slabs on lateral moisture movements. This chapter

describes the modelling approach, calibration and the model predictions.

6.2 FINITE ELEMENT MODELLING TOOL SELECTION

Much research has been undertaken on expansive soil modelling, however, the

objectives of these models varied considerably. The major limitation of previous studies

is the inability to consider direct soil climate interaction. Hung (2002) developed a

comprehensive model to observe expansive soil behaviour using the finite element

approach. The model uses the uncoupled and coupled approach to predict soil moisture

changes and the consequent volume changes. In the uncoupled approach, the soil

moisture changes were analysed first and then the results were used to determine the

volume changes in the next stage. In coupled approach, both soil moisture and the

170

volume changes analyse simultaneously . The uncoupled analysis was performed using

a partial differential equation solver called FlexPDE whereas the software COUPSO

(Pereira, 1996) was used to perform the coupled analysis.

In Hung’s (2002) study, soil moisture changes due to abnormal moisture conditions

such as leaky pipes and tree drying were considered. Since these models produce

moisture and volume changes, a number of input parameters are required. Elastic

parameters of the soil with respect to net normal stress and matric suction, elastic

parameters of water phase with respect to net normal stress and matric suction are the

main parameters required in these models. In addition, SWCC, coefficient of

permeability, Poisson's ratio and swelling index are also required. Certain assumptions

are commonly accepted in the modelling of expansive soil behaviour. For example, the

air phase is considered as continuous and the soil is considered as isotropic and non-

linear elastic material. Moreover, the pore water is treated as incompressible. The effect

of air diffusing through water, air dissolving in water and the movements of water

vapour are not considered. The effects of cover slabs on soil moisture were also

considered in these models. However, in Hung’s study, consideration of climate

condition is limited to only rainfall and the other climate influences were not

considered. The rainfall influence was considered as an external moisture source to the

soil. More details on these models can be found in previous literature (Hung, 2002, Vu

and Fredlund, 2004). Both coupled and uncoupled approaches resulted in a similar

outcome but the displacements from the coupled analysis were slightly smaller.

Wray (2005) developed a FORTRAN programme, “SUCH”, to predict the expansive

soil behaviour in a three dimensional domain. This model uses the moisture diffusion

concept suggested by Mitchell (1979) and the volume change model developed by

Wray (1997). The model can be used to investigate the moisture variation and volume

changes of soil in response to different edge conditions such as ponding, evaporation

and infiltration and tree drying. The model was validated for three different cities in

different countries. Climate effects on soil moisture were considered in the “SUCH”

model using surface suction boundary condition. Mitchell’s (1979) diffusion model

describes the suction variation in the top surface of the soil as sinusoidal variation

depending on a frequency related to the number of wetting-drying cycles per year. The

TMI of the areas was used to obtain the equilibrium suction from the correlation given

171

by Russam and Coleman (1961). This equilibrium suction is used as the bottom

boundary condition. Further details about this model have been previously described

(Mitchell, 1984a, Mitchell, 1979, Wray, 1997, Wray, 2005). While climate effects were

considered in this model, real weather data were not used. Therefore, a discrepancy can

be observed between the measured and predicted results in certain locations. This could

be due to an ineffectiveness of TMI in representing soil moistures at different climate

conditions.

Fatahi (2007) developed a comprehensive three dimensional model to study the changes

of soil suction induced by vegetation. He used ABACUS software and developed

specific sub routines using FORTRAN to accommodate the suction effects on moisture

flow through a porous media. Initial soil suction, evapotranspiration and the relevant

soil properties were used as input parameters. The hydraulic conductivity of soil was

not directly considered in this model due to inclusion of potential evapotranspiration

rate. The model produced soil suction and displacement in response to tree root drying.

However, real weather data was not used. In contrast, Jones et al. (2009) used a two

dimensional model to study the unsaturated behaviour of Adelaide clay. The purpose of

the model was to investigate the slope stability of saline clay soil due to flooding and

leaking pipes. SVFlux and SVSlope packages available in SVOffice (SVOffice, 2015)

were used to combine the unsaturated and saturated mechanics to develop the model.

SWCC and hydraulic conductivity of the soil were the main soil parameters used in this

model. In saline clays in Adelaide, osmotic suction is the dominant suction component

(Jones et al., 2009) and therefore, total suction was considered instead of matric suction

in developing SWCC. The climate effects were also included but were limited to rainfall

and evaporation. The balance between rainfall and potential evaporation was calculated

prior to determining whether the soil is drying or wetting, which reduced the number of

time steps to run the model. The model produces soil suction profiles at different times.

Rajeev et al. (2012) modelled the soil and climate interaction as a part of a study related

to the failure issues of pipes buried in expansive soils. A one dimensional soil column

was modelled using Vadose/w package in GeoSlope software (Geo-Slope, 2013). The

main soil parameters considered in this model were SWCC, hydraulic conductivity,

thermal conductivity and specific heat capacity. Soil properties were measured in two

different sites in Melbourne to validate the model and weather data was taken from

172

weather stations in the two sites. Regular soil moisture measurements were collected

using neutron probe technique. The model was capable of predicting soil moisture

profiles and temperature changes at different times and produced results in good

agreement with measured data.

The Vadose/w software is capable of handling climate boundary using readily available

weather data. The climate boundary condition includes rainfall, evaporation, relative

humidity, temperature and wind. The software uses actual evaporation instead of

potential evaporation in considering the climate effects on vadose zone. The actual

evaporation is calculated using the available rainfall and the other climate parameters.

In addition to the climate, the influence of vegetation and water ponding can also be

included. Vadose/w software tool is equipped with all the required conditions in this

study and hence it was selected to develop the finite element model.

6.3 MODELLING OF SOIL MOISTURE MOVEMENT USING VADOSE/W

The finite element models of investigating climate effects on expansive soils was

previously limited to selecting the flux boundary condition as potential evaporation

(Jones et al., 2009, Wray, 2005). But Vadose/w was developed to accommodate actual

evaporation using the observations from Wilson (1990). The actual evaporation is

calculated from Penman-Wilson formulation as shown in Equation 6-1.

AE = ΓQ + υEa

υA + Γ .…………….………….....……………………...…… Equation 6-1

AE = actual vertical evaporative flux (mm/day)

Γ = slope of the saturation vapour pressure versus temperature curve at the mean

temperature of the air (kPa/0C)

Q = net radiant energy available at the surface (mm/day)

υ = psychometric constant

Ea = f(υ)Pa (B-A)

173

f(υ) = function dependent on wind speed, surface roughness and eddy diffusion

= 0.35(1+0.15Ua)

Ua = wind speed (km/hr)

Pa = vapour pressure in the air above the evaporating surface (kPa)

B = inverse of the relative humidity of the air = 1/hA

A = inverse of the relative humidity at the soil surface = 1/hr

This formulation requires wind speed, relative humidity and net radiation from climate

parameters. However, if the net radiation data is not available, the evaporative flux can

also be calculated using Equation 6-2.

E = PE (hr − (

Vp.sat.air

Vp.sat.soil)hA

1 − (Vp.sat.air

Vp.sat.soil)hA

) …………..….…………………...…… Equation 6-2

E = evaporative flux (mm/day)

PE = user supplied potential evaporation (mm/day)

hr = relative humidity at the soil surface

Vp.sat.air = saturated vapour pressure of air

Vp.sat.soil= saturated vapour pressure of soil surface

hA = relative humidity of air above the soil surface

The temperature of the soil surface can be calculated using Equation 6-3 (Wilson, 1990)

for “no snow” conditions.

Ts = Ta +1

υf(υ)(Q − E) …………..….…………………...…… Equation 6-3

Ts = temperature at the soil surface (0C)

174

Ta = temperature of air above the soil surface (0C)

υ = psychometric constant

AE = actual vertical evaporative flux (mm/day)

Q = net radiant energy available at the surface (mm/day)

Vadose/w calculates the relative humidity and the water vapour pressure at the soil

surface using equations presented by Edlefsen and Anderson (1943) which are based on

thermodynamic relationships. The saturated vapour pressure at the soil surface is

dependent on the soil surface temperature, and it can be calculated as described by

Lowe (1977).

The effects of the vegetation on surface soils can be included in Vadose/w using three

different formulations. The variations of leaf area index and depth of the roots must be

specified as functions of the time period of the analysis. In addition, the moisture

limiting factor, which is dependent on the ability of vegetation to suck moisture from

soil at different sections, has to be specified.

The actual evaporation is limited by the water absorption from the vegetation and it is

calculated from Equation 6-4 (Vadose, 2013).

𝐴𝐸 = 𝐴𝐸∗[1 − (−0.21 + 0.7 × √𝐿𝐴𝐼)] ………….……………...…… Equation 6-4

AE* = actual vertical evaporative flux (mm/day)

AE = modified actual vertical evaporative flux (mm/day)

LAI = leaf area index

The potential transpiration is dependent on potential evaporation as can be defined in

Equation 6-5.

𝑃𝑇 = 𝑃𝐸(−0.21 + 0.7 × √𝐿𝐴𝐼) ………………….……………...…… Equation 6-5

PE = potential evaporation (mm/day)

175

PT = potential transpiration (mm/day)

The actual transpiration depends on the ability of tree roots to suck moisture from the

soil. Therefore, it is related to the plant moisture limiting factor and root depth, as

shown in Equation 6-6.

𝐴𝑇 = 𝑃𝑅𝑈 × 𝑃𝑀𝐿 ……….….…….…….....……………………...…… Equation 6-6

AT = actual transpiration (mm/day)

PML = plant moisture limiting factor

𝑃𝑅𝑈 =2𝑃𝑇

𝑅𝑇(1 −

𝑅𝑛

𝑅𝑇) 𝐴𝑛

RT = total thickness of root zone

Rn = the depth of the node in question

An = the nodal contributing area of the node in question

Then, the modified actual evaporative flux is used in governing flow equations.

Equations 6-7 and 6-8 show the governing differential equations for the one

dimensional coupled process of moisture and heat flow.

𝜕

𝜌𝜕𝑧(𝐷𝑉

𝜕𝑃𝑉

𝜕𝑧) +

𝜕

𝜕𝑧(𝑘𝑧

𝜕[𝑃

𝜌𝑔+ 𝑧]

𝜕𝑧) + 𝑄 = 𝜆

𝜕𝑃

𝜕𝑡 ………..…...…… Equation 6-7

𝐿𝑉

𝜕

𝜕𝑧(𝐷𝑉

𝜕𝑃𝑉

𝜕𝑧) +

𝜕

𝜕𝑧(𝑘𝑡𝑧

𝜕𝑇

𝜕𝑧) + 𝑄𝑡 + 𝜌𝑐𝑉𝑧

𝜕𝑇

𝜕𝑧= 𝜆𝑡

𝜕𝑇

𝜕𝑡 ..….…… Equation 6-8

ρ = water density,

z = elevation head,

Dv = vapour diffusivity coefficient

176

Pv = vapour pressure of soil moisture

kz = hydraulic conductivity in the z (vertical) direction

P = water pressure

g = acceleration due to gravity

Q = applied boundary flux

Λ = slope of the volumetric water content function

t = time

Lv = latent heat of vaporization

ktz = thermal conductivity in the z-direction

T = soil temperature,

Qt = applied thermal boundary flux

ρc = volumetric specific heat value

Vz = Darcy's water velocity in vertical direction

λt = volumetric specific heat value.

The above governing equations are solved in finite element method as programmed in

Vadose/w software. The detailed solving procedure can be found in the software manual

(Vadose, 2013). The key input parameters required to analyse those equations are

described in next section.

6.4 SOIL PARAMETERS

6.4.1 Soil Water Characteristic Curve (SWCC)

SWCC is the most important parameter considered in unsaturated soil mechanics

(Fredlund and Rahardjo, 1993). The Vadose/w model determines the nodal suction

values based on the applied flux boundary results in a particular time step and then

selects the corresponding hydraulic conductivity to disperse the moisture to surrounding

nodes. Therefore, SWCC governs the moisture movement modelling in Vadose/w.

177

There are three options available in Vadose/w to include the required SWCC of a soil

material. There are typical SWCCs for different soil types, available in Vadose/w to be

used in general studies. Those SWCCs are useful for preliminary studies, however, for

comprehensive studies, those typical curves may not be suitable. As a second option,

SWCCs can be estimated using basic soil properties of soil. The results from particle

size distribution and liquid limit are required to estimate the SWCC using a modified

method of Kovács (1981) model. Third, the software allows defining the measured

points and creating unique SWCC. The curve can be adjusted to obtain a smooth shape

of a SWCC while representing the measured points. Soil suctions and the corresponding

moisture contents were measured in this study as described in chapter 4 and the SWCC

curves were developed using Vadose/w software. SWCCs at different depths shown in

Figure 4-30 were used to develop the model.

6.4.2 Hydraulic conductivity function

Since it is difficult to measure the unsaturated hydraulic conductivity of soil, the

relationship between hydraulic conductivity and matric suction was estimated using

available prediction models as described in Chapter 4. Two correlations were

considered provided by Fredlund et al. (1994) and Van Genuchten (1980). It was

observed that the Van Genuchten (1980) model predicts high conductivity in high

suctions. The predictions from the method developed by Fredlund et al. (1994) provide

a closer match between predicted and measured moisture contents. Therefore, hydraulic

conductivity functions obtained from Fredlund et al. (1994) correlation were used in the

Vadose/w model (Figure 4-35). In the Braybrook site, bed-rock was not found up to

depth of 5 m, therefore 6 m of soil model was considered. Hydraulic property functions

were developed only up to about 2 m depth. Therefore, appropriate assumptions were

made in using hydraulic conductivity functions of the bottom layers as described in

section 6.7.1.

6.4.3 Thermal properties of soil

Full thermal soil materials in Vadose/w require specifying the thermal properties of soil

against the volumetric moisture content. Thermal conductivity and the specific heat

capacity of Basalt clay soils have linear variation with moisture content (Barry-

Macaulay et al., 2011, Barry-Macaulay et al., 2013, Rajeev et al., 2012). The sensitivity

analysis of the developed model (section 6.10.1) shows that thermal properties have

178

minimal impact on soil moisture content. Therefore, the thermal properties of soils were

not measured in this study and those properties available in literature (measured from

sites close to Braybrook) were used to develop the model. The variation of thermal

conductivity and specific heat capacity with volumetric moisture content were measured

in Altona soil by Rajeev et al. (2012). Altona is approximately 6 km from Braybrook

and has Basalt clay soil. Therefore, thermal properties shown in Figures 6-1 and 6-2

were taken from Altona site and used at appropriate depths to develop the Vadose/w

model in this study.

Figure 6-1: Thermal conductivity functions used in this study

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

20

40

60

80

100

120

140

160

180

Ther

mal

con

duct

ivity

(kJ/

days

/m/°

C)

Volumetric moisture content

0 - 0.3 m 0.3 - 0.8 m 0.8 - 1.3 m 1.3 - 6.0 m

179

Figure 6-2: Specific heat capacity functions used in this study

The Vadose/w software requires defining a profile of an initial soil temperature to

calculate the relative humidity and the water vapour pressure at the soil surface. These

values were not measured in this study. However, observations of Rajeev et al. (2012)

suggest that there is a small spatial variation in soil temperature (measured at two sites

in suburbs which are about 20 km away from the Braybrook and have basaltic clay

soil). Hence, the measured soil temperature profile in Altona (Rajeev et al., 2012) was

used as soil temperature in Braybrook as shown in Figure 6-3.

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Vol

umet

ric S

peci

fic H

eat C

apac

ity (k

J/m

³/°C

)


0 - 0.3 m 0.3 - 0.8 m 0.8 - 1.3 m 1.3 - 6.0 m

180

Figure 6-3: Initial soil temperature function used in this study

6.5 CLIMATE DATA

Vadose/w uses five climate parameters to define the climate boundary condition that are

specified as daily inputs for the analysis period. Since the weather data has not been

monitored in the Braybrook site, the nearest Meteorology department weather station

was used to collect data. The main parameter is the rainfall, which is the moisture input

component. Essendon airport weather station has climate data starting from 1889. The

daily rainfall data was obtained for the period of 1889 to 2015. The software requires

specifying the starting and finishing time of rainfall. This information is difficult to

collect due to different rain patterns throughout a day, and hence it is not available.

Therefore, 0.00 and 24.00 hours were used as the starting and finishing time of rain by

assuming the rain occurred throughout the entire day. The variation of rainfall within

that time period was specified as a sinusoidal variation. The hourly rainfall variation

considered in Vadose/w software is shown in Figure 6-4 for a typical (assumed) data set

given in Table 6-1.

11 12 13 14 15 16 17 18

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

Soil temperature (0C)

Dep

th (m

m)

181

Table 6-1: Hourly rainfall distribution (sinusoidal) of daily rainfall – assumed data set

Hourly rainfall distribution (mm) Hour Day

1 Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

1 0.000 0.000 0.000 0 0.000 0 0.000 2 0.014 0.021 0.007 0 0.003 0 0.011 3 0.056 0.084 0.028 0 0.011 0 0.045 4 0.122 0.183 0.061 0 0.024 0 0.098 5 0.208 0.312 0.104 0 0.042 0 0.167 6 0.309 0.463 0.154 0 0.062 0 0.247 7 0.417 0.625 0.208 0 0.083 0 0.333 8 0.525 0.787 0.262 0 0.105 0 0.420 9 0.625 0.937 0.313 0 0.125 0 0.500

10 0.711 1.067 0.356 0 0.142 0 0.569 11 0.778 1.166 0.389 0 0.156 0 0.622 12 0.819 1.229 0.410 0 0.164 0 0.655 13 0.833 1.250 0.417 0 0.167 0 0.667 14 0.819 1.229 0.410 0 0.164 0 0.655 15 0.778 1.166 0.389 0 0.156 0 0.622 16 0.711 1.067 0.356 0 0.142 0 0.569 17 0.625 0.938 0.313 0 0.125 0 0.500 18 0.525 0.787 0.262 0 0.105 0 0.420 19 0.417 0.625 0.208 0 0.083 0 0.333 20 0.309 0.463 0.154 0 0.062 0 0.247 21 0.208 0.313 0.104 0 0.042 0 0.167 22 0.122 0.183 0.061 0 0.024 0 0.098 23 0.056 0.084 0.028 0 0.011 0 0.045 24 0.014 0.021 0.007 0 0.003 0 0.011

Total (Daily rainfall - mm)

10 15 5 0 2 0 8

Figure 6-4: Hourly rainfall distribution used in vadose software (for data set given in Table 6-1)

0 24 48 72 96 120 144 1680.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Rai

nfal

l (m

m)

Hours

Hourly rainfall (mm)

182

Solar radiation or evaporation is required to calculate the actual evaporation in

Vadose/w as described in section 6.3. However, solar radiation is not available for all

weather stations. Therefore, evaporation was used in this study to define a climate

boundary. Relative humidity, temperature and the wind speed data were also obtained

from Essendon airport weather station. These data is also treated as sinusoidal variation

in Vadose/w software (Vadose, 2013). Table 6-2 shows typical data set provided to the

climate boundary in Vadose/w software.

Table 6-2: Typical set of data used in climate boundary in Vadose/w software

Day

Temperature (0C)

Relative humidity (%) Wind Rainfall Rainfall period Evaporation

Max Min Max Min (m/s) (mm) Start (hr) End (hr) (mm/day)

1 23.9 9.8 83 47 7.8 0 0 24 4.2

2 17.4 12.7 93 82 9.7 0 0 24 3

3 26.8 10.1 84 61 9.2 0 0 24 0.8

4 24 15.2 55 50 15.8 0.2 0 24 7

5 22.2 14.6 73 68 8.6 0 0 24 4

6 15 12.3 100 96 11.4 6.3 0 24 1.2

7 18.6 8.6 77 62 9.7 3 0 24 0.2

8 17.7 8.8 85 74 9.7 0 0 24 4

9 16.4 8 100 65 15 0 0 24 2.8

10 16.7 8.1 61 54 12.8 3.6 0 24 2.4

6.6 VEGETATION INFLUENCE

The vegetation effects on surface soil moisture were considered in terms of three

functions in Vadose/w software, namely Loaf Area Index (LAI), Root Depth (RD) and

Plant Moisture Limiting (PML) factor. LAI accounts for the growth of vegetation

during the period of analysis. The portion of solar radiation absorbed by the leaves of

vegetation governs the amount that falls onto the surface soils (Vadose, 2013). The crop

growing season data can be used to develop the LAI variation during a year. While the

grass cover of Braybrook site was properly maintained throughout the monitoring

period, the growing of the grass cover depends on the weather condition of the area. In

183

the Braybrook site, the grass cover began to grow in March. It begins dying during the

summer and becomes deadly dry at the end of December. Hence the LAI function has

been defined from March to December. The variation of the grass cover in Braybrook is

shown in Figure 6-5. This grass cover was categorized as poor based on the

observations. LAI can vary with the density of the vegetation cover (Atwell et al.,

1999). Therefore, highest LAI was selected as 1.0 and the given typical function in

Vadose (2013) manual was modified accordingly. The LAI function used in the model

shows in Figure 6-6.

Figure 6-5: Grass cover in Braybrook site

The PML function defines the capability of vegetation to suck moisture from soils at

different soil suction levels. When the soil is saturated, vegetation can suck moisture at

its highest capability. This capability gradually reduces while soil is drying and

becomes impossible when the soil is dried below the wilting point. The typical PML

function given in Vadose/w manual shows that, below 1500 kPa suction, the trees

cannot draw moisture from the soil (wilting point). This typical function has been used

in this study (Figure 6-7).

184

Figure 6-6: Estimated leaf area index function for Braybrook site

Figure 6-7: Typical PML function used in the study (Vadose, 2013)

The effect of roots spread throughout the top soil layer was considered using a root

depth function. The depth of the root zone experiences a moisture loss due to tree root

drying. The root depth varies with the growth of the trees and hence it is varies during

the analysis period. The beginning and end times of this variation is similar to the LAI

function. In Braybrook, the clay soil layer becomes stiffer towards the bottom and

0 50 100 150 200 250 300 350 4000.00

0.25

0.50

0.75

1.00

Leaf

Are

a In

dex

Days in a year

0 200 400 600 800 1000 1200 1400 16000.0

0.2

0.4

0.6

0.8

1.0

1.2

Pla

nt m

oist

ure

limiti

ng fa

ctor


185

therefore it is difficult for grass roots to proceed. A rich layer of grass roots was

observed in the top 100 mm and it was gradually sparser towards 300 mm depth. Apart

from some occasional roots, no grass roots were observed beyond 300 mm. Therefore,

the average depth of grass roots was considered as 200 mm. The root depth function

was taken from Rajeev et al. (2012) and modified to represent the roots up to 0.2 m

depth, as shown in Figure 6-8.

Figure 6-8: Root depth function for Braybrook site

6.7 DEVELOPMENT OF ONE DIMENSIONAL SOIL COLUMN

The vertical moisture movement in the Braybrook site was modelled in Vadose/w

software as a one dimensional (1D) soil column. The climate condition occurring on the

ground surface of an open area was applied to the surface layer. The soil properties

obtained from Braybrook at different depths were allocated to different layers of the soil

column. The variation of moisture content was given as the output of the model.

6.7.1 Selection of soil layers

The top layer of the soil column has to be modelled using the surface layer option in

Vadose/w software. The surface layer allows the application of a climate boundary. The

soil layers were defined as full thermal material where both thermal and hydraulic

property functions need to be specified.

0 50 100 150 200 250 300 350 400

-0.20

-0.15

-0.10

-0.05

0.00

Roo

t dep

th (m

)

Days in a year

Root depth (m)

186

The soil properties obtained for different depths were used in separate layers to

represent the soil profile. The sub layers of the soil column were modelled as separate

regions. In reality, the soil properties gradually vary with the depth and therefore the

changing layers can be barely identified. However, this is difficult to include in a model.

The soil samples were collected at different depths and their results represent the

corresponding depth of the sample. Therefore, the effects of discrete variation of soil

properties have to be expected from the model predictions.

Figure 6-9 shows the selection of layers and the properties used in Vadose/w model.

Since in Braybrook site bed-rock was not found up to 5 m, the depth of the one

dimensional soil model was considered more than 5 m. The hydraulic property

functions were developed only up to 2 m depth. Therefore, following appropriate

assumptions were made for SWCC and hydraulic conductivity functions for the bottom

layers. Figure 4-30 shows that Braybrook soils have similar SWCCs below surface layer

hence, the measured SWCC at 2.0 m is also used for the depths below 2 m. The bottom

layer, from 5 to 6 m, was considered as bed-rock. Hydraulic conductivity of the bottom

layer must be very low to prevent the moisture movement through bedrock (Rajeev et

al., 2012). Compacted clay with very low permeability can have saturated hydraulic

conductivity values in the range of 10-11 to 10-12 m/s (Benson and Trast, 1995).

Therefore, 1x10-12 m/s was used as saturated hydraulic conductivity of the bed-rock

layer. Hydraulic properties of soil gradually vary with the bulk density (Fu et al., 2011).

The basic soil properties and SWCCs are consistent in Braybrook site, as described in

Chapter 4. However, bulk density depends on the compaction of soil, which in this case

is governed by the surcharge. Therefore, a gradual variation of saturated hydraulic

conductivities of the soil between 2 and 5 m were considered to develop hydraulic

conductivity functions using the Fredlund et al. (1994) method. No-flow boundary

condition is specified at the bottom to represent the impermeable rock.

The moisture flow in soil can be adversely affected by the cracking behaviour of the

clay soils during the dry period. The cracking of soils occurs in different ways at

different locations of a site, and it is highly dependent on local effects. The crack depth

measurements in Braybrook site (Table 5-2) showed that the depth could vary even

within a small area. Therefore, it is difficult to model the cracks and their consequences.

187

Subsequently, the cracking of soils was not considered in Vadose/w model developed in

this study.

Figure 6-9: Summary of one-dimensional Vadose/w model

6.8 CALIBRATION OF 1D SOIL MODEL AGAINST MEASURED DATA

The one dimensional soil model was analysed for the period of regular monitoring in

Braybrook, from 10th April 2013 to 25th March 2015. Essendon airport is the nearest

weather station, which is 8 km away from the Braybrook, and it records all the required

daily climate data. Therefore, climate data collected from Essendon airport was used for

the calibration period. The initial moisture contents have been specified, as shown in

Figure 6-10(a). These data were collected from the neutron probe measurements on 10th

April 2013. The moisture measurements were collected only up to 3 m depth and, since

there is constant moisture content at the bottom layers, the same value was used up to 6

m depth. Figure 6-10(b) shows corresponding matric suction values obtained using

SWCCs at different depths given in Figure 4-30.

Distance - m-0.5 0.0 0.5 1.0 1.5

Ele

vatio

n - m

-6.5

-6.0

-5.5

-5.0

-4.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

Sub layer 3 (300-800 mm) 0.3 – 0.8 m 0.5 – 1.0 m

Sub layer 4 (800-1300 mm) 0.8 – 1.3 m 1.0 – 1.4 m

Sub layer 5 (1300-1800 mm) 1.3-1.8 m 1.5 – 1.8 m

Sub layer 6 (1800-2500 mm) 1.8 – 2.5 m

Sub layer 7 (2500-3500 mm)

Sub layer 8 (3500-5000 mm)

Sub layer 9 (5000-6000 mm)

Sub layer 1 (0-200 mm) 0 – 0.4 m

Hydraulic conductivity functionSub layers SWCC

No flow Boundary

Climate Boundary

0 – 0.3 mSub layer 2 (200-300 mm) 0 – 0.3 m 0 – 0.4 m

188

Figure 6-10: Initial moisture content measured at various depths; (b) corresponding suction at various depths

The analysis was performed using a laptop computer. The parallel direct equation solver

option available in Vadose/w was preferred over the direct equation solver option,

which makes the analysis faster (Vadose, 2013). Time steps were considered in days, a

main requirement in Vadose/w analysis. However, adaptive time steeping was used to

minimize the higher nodal head changes applied due to daily climate inputs during a

time step. The 1D model typically takes about 4 hours to analyse the model for a 100

year period.

The volumetric moisture contents obtained from the model were compared with the

measured values. There were errors in moisture contents recorded at TN6 as described

in section 5.4.1. Therefore, TN6 location was neglected in model validation. Figures 6-

11 to 6-14 show the comparison of model predictions and neutron probe measurements

at CN1 and CN2. Figure 6-11 shows the model predictions and measured volumetric

moisture contents at 0.35 m depth. It demonstrates that the model has reliably picked

the moisture changes in both wet and dry periods. However, certain offsets between

measurements and predictions can be observed at some dates. The least accuracy is due

to proximity to the surface where neutron moisture measurements could result in greater

0.30 0.32 0.34 0.36 0.38 0.40 0.42 0.44

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0100 1000 10000

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

b)

Average of CE1 and CE2


Dep

th (m

)

a)


Dep

th (m

)

189

errors, cracking of top soils and variability of soil properties due to the presence of

organic matter. The surface moisture contents are largely affected by various local

influences such as slope differences, potholes, cracks and vegetation layer differences.

Apart from these influences, the ground surface directly interferes with the climate

conditions. Therefore, the surface moisture varies more frequently and the surface

moistures measured at different locations in the same site can have dissimilar values.

This phenomenon can be clearly observed in Figures 5-9 to 5-11, which show the same

day measurements of the CN1, CN2 and TN6 locations. Even though the CN1 and CN2

locations are within 10 m distance, in some days, different moisture contents at the

surface layers have been recorded. Therefore, the model results are difficult to compare

with the measurements close to surface.

Occasionally, these local influences can affect the moistures of the bottom layers. When

there are cracks on the surface, the rainfall and the runoff water can infiltrate easily

through them and increase the moisture contents of the bottom layers. This phenomenon

was observed in measurements made straight after rainy days during the summer. The

stagnated water on potholes can also infiltrate the bottom layers and can show high

moisture contents than other locations.

The surface layer moistures are largely affected by the rainfall, which is one of the main

components of climate boundary. Therefore, the moisture measurements followed the

pattern of daily rainfall variation shown in Figure 6-11. Figures 6-12 to 6-14 show that

the model can precisely predict the moisture changes at the bottom layers. The rainfall

influences the moisture contents at 0.6 m and 0.85 m whereas no moisture change was

recorded at 1.6 m during this calibration period.

190

Figure 6-11: Measured soil moisture contents at 0.35 m and model predictions with rainfall variation


10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35

40 Daily Rainfall (mm) CN1 - Neutron Probe Measurements at 0.35 m CN2 - Neutron Probe Measurements at 0.35 m Model Predictions at 0.35 m

Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

191



Since CN1 and CN2 are close to each other, the average moisture contents at CN1 and

CN2 locations were considered as shown in Figures 6-15 to 6-18 which indicates that

model predictions are more consistent with the averaged measurements.

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

192

Figure 6-15: Measured average soil moisture contents at 0.35 m and model predictions with rainfall variation


10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35

40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model Predictions at 0.35 m

Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

193



Figure 6-19 shows moisture content profiles at two dates with extreme moisture

contents recorded at 0.35 m. This figure confirms that the model can reliably capture the

changes of moisture profiles. The other profiles for all the measurement dates are shown

in Appendix-E.

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35


Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

194

Figure 6-19: Actual measurements and model predictions for two extreme measurement dates; a) recorded wettest, b) recorded driest

Figure 6-20: Model predictions against neutron probe measured data

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 29/01/2014 CN1 - 29/01/2014 CN2 - 29/01/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 21/10/2013 CN1 - 21/10/2013 CN2 - 21/10/2013

a) b)

0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5

0.35 m 0.60 m 0.85 m 1.10 m 1.35 m 1.60 m 1.85 m 2.10 m 2.35 m 2.60 m 2.85 m

Mod

el p

redi

ctio

ns

Neutron probe measurements

Model predictions and Averages of CE1 & CE2 Neutron probe measurements

195

Overall, the 1D model results are within the limits of measured values and hence the

predictions against measured values, plotted in Figure 6-20, show a good correlation.

Therefore, this model can be considered as a validated model. However, it should be

noted that during the monitoring period of this study, extreme dry or wet climate events

were not recorded. Further, greater moisture changes occur in the surface soils, and the

neutron probe technique is less effective in capturing them. Hence, the impacts of an

extreme climate conditions could not be considered in the validation process.

This model has been used to observe the soil moisture changes due to different climate

conditions, which is described in the next chapter. Furthermore, this model has been

extended to a two dimensional model to observe the lateral moisture movements.

6.9 DEVELOPMENT OF TWO DIMENSIONAL SOIL MODEL

Since the 1D model predicts moisture changes of an open ground, it is interesting to

observe the climate induced moisture changes under a cover which simulates the effect

of a slab. A two dimensional (2D) model with a flexible cover slab and open area was

developed to observe the edge moisture variation which is also an important parameter

in footing design on expansive soils. In this model, the slab cover had no stiffness and

applied no load to the soil.

6.9.1 Selection of model parameters

The 2D model is an extension of the 1D model and, as such, most of the soil properties

are similar to the 1D model. Soils in the 2D model have same layered arrangement as

1D model and hence, they have same properties.

The only additional material property that must be considered for the 2D model is the

hydraulic conductivity in “x” direction, which governs the moisture flow in lateral

direction.

The moisture flow directions of soil depend on the anisotropic arrangement of soil

pores. Apart from the cracks, the soil grains govern the anisotropic arrangement. If the

grains have spherical shapes, then there will be an isotropic moisture flow. But most of

the clay soils have plate type grains and they tend to arrange in a layered pattern with

plat sides deposited on each other. Hence, the lateral moisture flow is usually higher in

layered soils than that of non-layered soils (Zaslavsky and Rogowski, 1969, Todd,

196

1980). In Braybrook, it was difficult to observe differences between soil layer patterns

or cracks in both vertical and lateral directions. Figure 6-21 shows a large piece of soil

taken from Braybrook, which shows the homogeneity of the soil in every direction.

Therefore, the vertical and lateral hydraulic conductivity were assumed to be the same

in Braybrook soils. However, this assumption is based on the visual inspection of the

soil. The elevation head was the only influence between vertical and lateral moisture

movement and was considered in the partial differential equation shown in Equation

6-7.

In addition to the soil and climate parameters specified in 1D model, there are additional

considerations incorporated in the 2D model and they are described in the next section.

Figure 6-21: A large soil chunk from Braybrook

6.9.1.1 Effect of flexible cover on soil moisture

The main purpose of the 2D model is to investigate the effect of climate on soil beneath

a covered area. The condition of cover was introduced by applying a “No flow”

boundary condition on a portion of surface layer. The rest of the surface layer is

considered as an open ground and hence the climate boundary was applied. A very low

hydraulic conductivity was specified for the 0.3 m thick layer below the “No flow”

197

boundary on surface. This prevents the moisture changes of that section of the model,

which represent the ideal condition of a 0.3 m deep slab.

The depth of edge beams of waffle/ stiffened raft slabs designed for H to E class site is

about 385 to 460 mm. When these slabs are placed the top soil is removed to level the

site. In addition, to avoid the side of the edge beams to be exposed, further excavation

may be done to bury the slab further below the natural ground surface. Hence, it is taken

the base of the edge beams on average to be about 300 mm from the natural ground

surface. The model represents a typical cover and therefore, a 300 mm deep uniform

layer was selected to avoid the complexity of slab-beam arrangement.

6.9.1.2 Selection of side boundary conditions

The 2D model represents the conditions of a house footing and the adjacent open area.

Therefore, the climate condition needs to be applied from both sides of the slab, which

represent the garden around the house. Only one side of the area was modelled to reduce

the analysis time. The no flow boundary was applied on the inner side of the slab to

represent the axis of symmetry.

The other end of the model contains variable moisture contents depending on the

climate condition and therefore a specific hydraulic boundary (head or flow) cannot be

specified. As a result, that side is selected to be far enough from the zone of interst such

that the effects of that boundary are minimal. This condition is defined as a far field

boundary condition in Vadose/w modelling (Vadose, 2013), and hence this boundary

can be ignored without specifying any condition. The length of the open area is selected,

such that the moisture changes at the margin of the open area are exactly the same as the

1D model results for the same analysis period. The size selection of the 2D model is

described in the next section.

The top surface outside the cover slab is provided with climate boundary similar to the

1D model. Similarly, the bottom surface is specified as No-flow boundary to represent

an impermeable rock.

6.9.1.3 Selection of model size

The depth of the 2D soil model was 6 m, similar to 1D soil column. The lengths of the

covered and open ground segments were selected based on a sensitivity analysis.

198

Different slab widths and open area widths were considered and the moisture changes at

various locations were observed. The following different model sizes were considered:

Model 1: Cover slab length 6 m and open area length 5 m




Figure 6-22 shows Model 1, which has a 6 m deep and 11 m long soil model with a 6 m

long cover slab. Since the 1D model suggested that most of the moisture changes occur

in soils above 4 m, a finer mesh has been used in the top 4 m of the model. More details

on mesh size selection are given in the next section. Boundary conditions were applied

as explained in section 6.9.1.2. Model 2 to Model 4 have the similar conditions as

Model 1 with changes only in slab length and the total model length. These models

were analysed for a 2 year period same as the 1D model calibration starting from 10th

April 2013 to 25th March 2015 using the climate data collected from Essendon airport

weather station.

The suction changes at 300 mm depth were examined in four different models. The

characteristic maximum and minimum values at that depth at different dates were

considered here, to be able to compare the results of four models. Figure 6-23 shows the

results of the characteristic highest and lowest suctions obtained for the two year period.

This figure also shows a sketch of the arrangement of model sizes based on “x” distance

which facilitates the interpretation of the results. The length of the models was

considered starting from the outside edge of the slab to be able to clearly express the

different model sizes. Figure 6-23 shows that all the models predicted similar results

and the results coincide with each other.

Model 1 and Model 4 were further checked for an analysis period of 100 years. The

climate data from Essendon airport weather station for the period of 1915 to 2014 were

used in this analysis. The analysis time taken for the model 1 was about 5 days. There

was a constant difference between driest and wettest moisture contents starting from

about -3m through -10m (symmetric axis) under the slab. The difference was about 1%

and it is due to the continuous lateral moisture flow along layer interface of the soil

model as the soil below 0.3 m has lower hydraulic conductivity compared to the top

199

soil. However, both models produced similar suction and moisture variations and

resulted higher moisture movement towards the inside of the slab. The smaller models

require less time for the analysis hence, Model 1, which has 6 m long cover slab and 5

m long open area, was selected to continue the 2D model analysis.

Figure 6-22: Two-dimensional Vadose/w model

Figure 6-23: Characteristic wettest and driest suctions at 300 mm depth taken from the 2D model with different sizes

Distance - m-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0

Elev

atio

n - m

-6.5

-6.0

-5.5

-5.0

-4.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

Climate BoundaryNo flow Boundary on cover slabAxis of symmetry

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 52.00

2.25

2.50

2.75

3.00

3.25

3.50

3.75

4.00

Log

[Mat

ric S

uctio

n (k

Pa)]

Distance (m)

Model 1 (wettest) Model 1 (driest) Model 2 (wettest) Model 2 (driest) Model 3 (wettest) Model 3 (driest) Model 4 (wettest) Model 4 (driest)

Suction variation at 0.3 m soil layer

Cover slab Open area exposed to climate effects

300 mm

Soil

Model 1Model 2Model 3

Model 4

200

6.9.1.4 Effect of mesh size

The size of the mesh has an influence on modelling in terms of accuracy, convergence

of iterations and the analysis time (Vadose, 2013). Therefore, it is important to select

the optimum size of the mesh to develop a reliable and time effective model. The

Vadose/w model results are used in a separate model (developed using FLAC 3D

software) to analyse the changes on soil volume. According to the requirements of that

software, the same square mesh is preferred over the zone of interest of the Vadose/w

model.

The Vadose/w model response to mesh size was investigated by using different square

mesh sizes from 10 mm to 200 mm. The volumetric moisture contents at different

depths in a 30-day period were observed, as shown in Figure 6-24. This figure

illustrates that the 10 mm mesh has caused different results compared to the other

models. This could be due to poor convergence in finer mesh near the climate boundary

and the layer interfaces. Moreover, it takes more time to run the model. Mesh size 200

seems to be too large to develop a moisture profile to compare with field data. Apart

from the 10 mm and 200 mm mesh sizes the other models produced same results. Hence

by considering the efficient run time of the analysis, 100 mm mesh size was selected for

top soil layers. However, a coarser mesh was used for the soil below 4 m as shown in

Figure 6-22.

Figure 6-24: Soil moisture profiles obtained from models with different mesh sizes

0.15 0.20 0.25 0.30 0.35 0.40

-2.5

-2.0

-1.5

-1.0

-0.5

0.0


Dep

th (m

m)

Mesh size 10 mm Mesh size 25 mm Mesh size 50 mm Mesh size 100 mm Mesh size 200 mm

201

6.9.2 2D model predictions

The 2D model was analysed for the calibration period to compare the moisture contents

at the open area with the 1D model results. The moisture contents profiles at 4 m from

the slab edge (at distance 10 m, as shown in Figure 6-22) produced the same results as

the 1D model shown in Figures 6-11 to 6-14. The 2D model was used to obtain soil

moisture variations underneath cover slabs due to different climate conditions and the

results are presented in the next chapter.

6.10 MODEL GENERALIZATION

Predictions of the Vadose/w model depend on both material properties and input

parameters. The accuracy of the material model governs the moisture content and the

flow rate at different depth of the model. In actual conditions, the material properties

gradually vary along the depth of the soil. Soil layer separation cannot be clearly

identified and, therefore, field moisture profiles tend to be smooth. This condition

cannot be easily modelled because the material properties obtained from soils at

different depths must be specified for different layers. Since there is a difference in

properties between layers, it results in abrupt changes of moisture content at the

interface of the soil layers as evidenced in Figure 6-24. However, the effect of material

properties on soil moisture can be studied through a sensitivity analysis and then the

most sensitive parameters can be precisely defined.

In addition to the material properties, the input parameters can alter the model results

from actual measurements. Vadose/w model contains components of climate boundary

as input parameters. In this study, climate data obtained from a weather station 8 km

from the site and hence they may not represent the exact climate condition at Braybrook

site. Therefore, some sensitivity analysis for the climate data was also considered.

6.10.1 Sensitivity of the material model

There are four soil parameters specified in material model developed in Vadose/w

software. SWCC and hydraulic conductivity can be categorized as hydraulic properties

while thermal conductivity and specific heat capacity can be categorized as thermal

properties. The hydraulic properties are defined with respect to matric suction and the

thermal properties are defined against volumetric moisture content.

202

In this sensitivity analysis, the model with real soil property functions from measured

soil results was considered as the “control” model. Each of the material properties was

modified by ±20% and used separately. There were 8 modified parameter models

considered as follows:

20% increment and decrements of volumetric moisture contents corresponding

to suction values in all the SWCCs used in control model (Figure 6-25)

20% increment and decrements of hydraulic conductivities corresponding to

suction values in all the hydraulic conductivity functions used in control model

(Figure 6-26)

20% increment and decrements of thermal conductivities corresponding to

volumetric moisture contents in all the thermal conductivity functions used in

control model (Figure 6-27)

20% increment and decrements of specific heat capacities corresponding to

volumetric moisture contents in all the specific heat capacity functions used in

control model (Figure 6-28)

These changes applied to the soil parameters at the surface layer are shown in Figure

6-25 to 6-28. Similar changes were applied to the parameters of the other layers.

Figure 6-25: 20% changes applied to SWCC of surface layer in sensitivity analysis

0.01 0.1 1 10 100 1000 10000 1000000.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric W

ater

Con

tent

(m³/m

³)


Control input 20% Increment 20% Decrement

203

Figure 6-26: 20% changes applied to hydraulic conductivity of surface layer in sensitivity analysis

Figure 6-27: 20% changes applied to thermal conductivity of surface layer in sensitivity analysis

0.1 1 10 100 1000 10000

1E-12

1E-11

1E-10

1E-9

1E-8

1E-7

1E-6

Hyd

raul

ic c

ondu

ctiv

ity (m

/s)



0.0 0.1 0.2 0.3 0.4 0.5 0.60

25

50

75

100

125

150

175

200

Ther

mal

Con

duct

ivity

(kJ/

days

/m/°

C)

Volumetric Water Content (m³/m³)


204

Figure 6-28: 20% changes applied to specific heat capacity of surface layer in sensitivity analysis

6.10.1.1 Sensitivity analysis results

SWCC is the governing parameter of moisture changes of expansive soil (Fredlund and

Rahardjo, 1993) and this was reflected in the sensitivity results. Figure 6-29 illustrates

the percentage changes of moisture content at 0.3 m depth due to modifications of the

soil parameters. This figure shows the variation of results from 8 modified models

(given in the previous section) compared to the control model.

Figure 6-29: Sensitivity of soil parameters

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Vol

umet

ric S

peci

fic H

eat C

apac

ity (k

J/m

³/°C

)

Volumetric Water Content (m³/m³)


-24 -20 -16 -12 -8 -4 0 4 8 12 16 20 24

Hydraulic conductivity

SWCC

Thermal conductivity

Specific Heat Capacity

Percentage change of moisture content

climate parameters at 0.3 m depth - 21/10/2013

Due to 20% Increment Due to 20% Decrement

205

Following conclusions were made from the results shown in Figure 6-29.

SWCC has been the most influential soil parameter of the material model.

Increments of the SWCC caused increments in soil moisture at 0.3m depth. 20%

change of the SWCCs resulted in about 22% change in soil moistures.

The hydraulic conductivity is the next important soil parameter. Since hydraulic

conductivity governs the moisture flow rate, the higher the hydraulic

conductivity at a node, the higher the capability of allowing moisture to flow

away. Therefore, changes of hydraulic conductivities are inversely proportional

to the soil moisture changes. 20% change in hydraulic conductivities resulted

in about 2% soil moisture change.

Thermal conductivity and specific heat capacity caused less than 1% changes in

soil moisture. Hence, soil moisture changes are less sensitive to the thermal

properties.

6.10.2 Sensitivity of climate parameters

The Vadose/w model associates five climate components as input parameters; rainfall,

evaporation, relative humidity, wind speed and temperature. The influence of each

component is different. Therefore, the model prediction should be considered with the

sensitivity of those parameters.

6.10.2.1 Rainfall

In this sensitivity analysis, three nearby weather stations were used where daily rainfall

data is available for the analysis period. These stations are located at different distances,

as given below.

Flemington racecourse: 4.1 km away from Braybrook

Essendon airport: 8.0 km away from Braybrook

Burnside: 10.2 km away from Braybrook

Figure 6-30 shows daily rainfall variation for a typical month. It is observed that all of

them have similar rainfall variation with a maximum daily rainfall difference of about 5

mm.

206

Figure 6-30: Daily rainfall variation of 3 locations around Braybrook (April 2013)

Some weather stations have only a certain type of weather data while others have all the

required data types. Since weather data types are dependent on each other, all the

required data collected from one weather station should provide better model

predictions. Essendon airport provides all the data for the Vadose/w model and hence

that weather station was considered in this study. These data was modified by 20% and

used in the model to observe the sensitivity of the rainfall on soil moisture.

6.10.2.2 Evaporation

Soils lose moisture due to evaporation process at the surface. Therefore, it is an

important parameter in climate boundary. In the Vadose/w model, potential evaporation

should be specified to calculate the moisture flow (Equation 6-2). Potential evaporation

can be calculated from Penman method (Penman, 1948) using specifically measured

weather data. Since the potential evaporation depends on other climate components (for

example, temperature, rainfall and solar radiation) it is not a readily available in typical

weather stations. However, pan evaporation data can be directly collected from the

Bureau of Meteorology.

The difference of two evaporation types was investigated using measured weather data

in Fawkner. These data was provided by Dr. Pathmanathan Rajeev, which were

collected for research published elsewhere (Chan et al., 2010, Rajeev et al., 2012,

Rajeev and Kodikara, 2011). Penman potential evaporations were calculated from those

data for a two-year period. Pan evaporations were obtained for the same period from a

weather station, which is 6 km far from Fawkner. Figure 6-31 shows daily variation of

1/04/2013 8/04/2013 15/04/2013 22/04/2013 29/04/20130

1

2

3

4

5

6

7

Dai

ly ra

infa

ll (m

m)

Date

Flemington Racecourse Essendon airport Burnside

Total rainfallFlemington Racecource: 23.1 mm Essendon airport: 17.6 mmBurnside: 10.2 mm

207

pan evaporation and Penman potential evaporation for a two-year period. It shows that

both evaporations have similar values.

Figure 6-31: Variation of evaporation in Fawkner

Figure 6-32 suggests that pan evaporation data from 6 km away from the location can

reliably represent the calculated values. Therefore, in this study pan evaporation data

collected from Essendon airport weather station was used in the climate boundary.

Figure 6-32: Comparison of pan evaporation and Penman potential evaporation in Fawkner

1/06/2009 1/09/2009 1/12/2009 1/03/2010 1/06/2010 1/09/2010 1/12/2010 1/03/2011 1/06/20110

3

6

9

12

15 Pan Evaporation Penman Potential Evaporation

Evap

orat

ion

(mm

)

Date

Fawkner

0 5 10 150

5

10

15

Pen

man

Pot

entia

l Eva

pora

tion

Pan Evaporation

Fawkner

208

The pan evaporation data collected from Essendon airport weather station were

modified by 20% and used separately in sensitivity analysis models to observe the effect

of evaporation on soil moisture.

6.10.2.3 Relative humidity, temperature and wind

Maximum and minimum relative humidity values were collected from Essendon airport

weather station. They were also modified by 20% in the sensitivity analysis. However,

the minimum and maximum values were kept between 0 and 100. Temperature and

wind data were also collected from the same weather station and, again, 20%

modifications were made for the sensitivity analysis. However, minimum values were

kept to zero. These modified parameters were applied one at a time into the control

model and the resulted soil moisture predictions were observed.

6.10.2.4 Sensitivity analysis results

Figure 6-33 shows the moisture contents at 0.3 m depth due to 20% changes in each

climate parameters. Following conclusions were made regarding the sensitivity of

climate parameters using the results shown in Figure 6-33.

Rainfall is the main influence of soil moisture changes followed by evaporation

and relative humidity.

The higher the rainfall the greater the amount of water available for infiltration.

High relative humidity creates less evaporation and hence increase the soil

moistures at top layers. Therefore, rainfall and relative humidity are positively

correlated to the soil moisture change, whereas evaporation is negatively

correlated.

20% change in rainfall creates about 5% change in soil moisture at 0.3m depth.

20% change in evaporation crate about 3-4% change in soil moisture at 0.3m

depth

20% change in relative humiditys crates about 1.5-2.5% change in soil moisture

at 0.3m depth

Soil moistures are less sensitive to both temperature and wind

209

Figure 6-33: Sensitivity of climate parameters

6.10.2.5 Model response to vegetation effect

The vegetation layer affects the evaporation from soil surface by reducing the soil’s

exposure to the solar radiation. Therefore, soil moisture can be higher in a grass land

than in bare land. On the other hand, vegetation reduces the soil moisture due to

transpiration process. This depends on the depth of the root zone and the plant moisture

limiting function (Vadose, 2013). Soil moisture condition is a result of balance between

these two scenarios due to vegetation.

Vadose/w has an option to analyse the models including and excluding the vegetation

effect. Figure 6-34 shows the model predictions at 0.35 m with and without the

vegetation effect. Inclusion of vegetation has resulted in a high moisture condition at

surface layer. This is due to the prevention of evaporation as a result of grass cover.

Since the Braybrook site had a relatively shallow root zone, the transpiration process

has a small influence.

In the Vadose/w model, the influence of vegetation can be controlled using the root

depth function, leaf area index and plant moisture limiting factor described in section

6.6. In the Braybrook site, the grass cover was identified as LAE of 1 which is a poor

cover. However, if the grass cover is thicker and remains throughout the year, it can

significantly reduce the evaporation from the surface, which leaves more water to

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

Rainfall

Evaporation

Relative Humidity

Temperature

Wind

Percentage change of moisture content

Sensitiviy of climate parameters at 0.5 m depth - 21/10/2013Due to 20% Increment Due to 20% Decrement

210

infiltrate. Hence a significant increase in soil moisture can be observed. However, if the

roots grow further down and are denser, they increase the water removal from the soil.

Therefore, selecting appropriate vegetation functions in Vadose/w analysis is important.

Inclusion and exclusion of vegetation effect can be considered in long term analysis

models to observe the soil moistures for different land conditions.

Figure 6-34: Effect of vegetation layer on soil moisture at Braybrook site

6.10.2.6 Model response to ponding effect

Rainwater can collect on ground surface because of varying local effects at different

places of the site. Cracks and potholes can hold water for some time and therefore

infiltration at those locations can become higher than other places. This effect can be

included in Vadose/w model by allowing ponding on the surface. If the ponding is

allowed in the analysis, the model does not consider runoff and keeps the excessive

precipitation at a time step for the subsequent evaporation or infiltration at later time

steps. Figure 6-35 shows the effect of the ponding allowed and ignored conditions on

soil moisture at 0.35 m. The ponding allowed condition resulted in higher moisture

contents at surface layer. The ponding effect has great influence on soil moisture after

heavy rain days.

Even though Braybrook generally has a flat ground surface, surface is uneven at some

places. Furthermore, cracks were observed during the summer. However, in general, the

pooling of water during wet periods was not observed. Therefore, ponding was not

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35

40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model prediction with Vegitation included Model prediction with Vegitation excluded

Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

211

allowed in the validated model. But these two scenarios can be considered in model

applications to observe the effect of local conditions.

Figure 6-35: Effect of ponding condition on soil moisture at Braybrook site

6.11 SUMMARY

This chapter describes the development of a finite element model to predict soil

moisture changes in response to climate conditions. Vadose/w package, available in

GeoSlope software, was used to develop the finite element model. A 1D soil column

was modelled using the material properties of Braybrook soils described in Chapter 4.

The model requires specifying SWCC, hydraulic conductivity, thermal conductivity and

the specific heat capacity of the soil. A sensitivity analysis suggested that the thermal

properties had a minimal impact on soil moisture changes. Therefore, thermal

conductivity and specific heat capacity obtained from literature related to a site close to

Braybrook were deemed appropriate for this research. The soil properties were defined

at different depths of the soil column to represent actual soil profile. The depth of the

soil column is governed by the location of bedrock. In Braybrook site, bedrock was not

hit at 4.5 m, therefore a 6 m deep soil column with bottommost meter (5m to 6m) of

bedrock was modelled. Soil properties of Braybrook soils were measured up to 2.5 m

depth. Braybrook soils have similar SWCCs below surface layer and therefore, the

measured SWCC at 2.0 m is also used for the depths below 2 m.. Since hydraulic

properties of soil gradually vary with the bulk density and the soil properties and are

consistent in Braybrook site, a gradual variation of saturated hydraulic conductivities of

10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140

5

10

15

20

25

30

35

40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model prediction with Ponding not allowed Model prediction with Ponding allowed

Date

Dai

ly R

ainf

all (

mm

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Vol

umet

ric m

oist

ure

cont

ent

212

the soil between 2 and 5 m were considered where bulk density is governed by the

surcharge. These saturated hydraulic conductivities were used to develop hydraulic

conductivity functions using the Fredlund et al. (1994) method.

The model requires specifying boundary conditions to represent the moisture flow

conditions. The climate boundary was specified at the top surface. Vadose/w software

uses daily inputs of rainfall, evaporation, relative humidity, wind and temperature to

define the climate boundary. These climate components were collected from a weather

station close to the Braybrook site. The no-flow boundary was defined at the bottom of

bedrock to prevent the moisture flow from bedrock.

This model was analysed for the two year period of field monitoring. The model

predicts soil moisture and suction profiles at different times. These predictions were

compared with the neutron moisture measurements described in Chapter 5. The results

showed a good agreement between soil moisture predictions and monitored data and

hence the model was considered as validated.

Next, the 1D model was extended to a 2D model to determine lateral moisture

movements. The only additional parameter required in the 2D model is hydraulic

conductivity in lateral direction. During the mass excavation in Braybrook site,

homogeneous soil chunks were found where no layer changes could be observed.

Hence, it was assumed the both lateral vertical hydraulic conductivities are the same in

Braybrook soils. The 2D model was developed to incorporate impervious cover in order

to observe the soil moisture beneath cover slabs due to the climate influences on

adjacent open ground.

The sensitivity analysis of the input parameters revealed that soil moisture changes are

mostly affected by SWCC of soils followed by the hydraulic conductivity. Rainfall is

the most sensitive climate component in changing soil moistures. Furthermore,

evaporation and relative humidly have significant impacts on soil moisture contents.

The responses of the models to vegetation effects and ponding conditions were also

considered. Grass covers prevent the evaporation and increase the water available for

the infiltration. Therefore, both grass covers and pooling effects significantly increase

the soil moisture. These sensitive input parameters must be given more attention in

obtaining soil moisture using prediction models. This model was then used to determine

213

the soil moisture changes due to long-term climate conditions, which is described in the

next chapter.

214

7. MODEL APPLICATIONS

7.1 OVERVIEW ON MODEL PREDICTIONS OF SOIL MOISTURES

The validated model described in the previous chapter was used to investigate the soil

moisture changes in response to various long-term climatic conditions. A number of

models were analysed to consider different site conditions and climate scenarios.

Following notations were used in this chapter to denote these different models.

VB1 1D Vadose/w model, Braybrook site, 6 m deep, period 1945-2015

(Section 7.1.1.1)

VB2 1D Vadose/w model, Braybrook site, 3 m deep, period 1945-2015

(Section 7.2.5)

FLAC 1D soil column developed in FLAC-3D software which uses moisture

predictions from Vadose/w models

VB3 1D Vadose/w model, Braybrook site, 6 m deep, short term wet condition,

period 1945-2018 (Section 7.3)

VB4 1D Vadose/w model, Braybrook site, 6 m deep, short term dry condition,


VB5_A 1D Vadose/w model, Braybrook site, 6 m deep, typical average climate,

period 50 years (Section 7.4)

VB5_M 1D Vadose/w model, Braybrook site, 6 m deep, modified climate, period

50 years (Section 7.4)

2DVB1 2D Vadose/w model, Braybrook site, 6 m deep, period 1945-2015

(Section 7.5)

2DVB2 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover,

period 1983-1992 (Section 7.6.1)

2DVB_I 2D Vadose/w model, Braybrook site, 6 m deep, without flexible cover,


215

2DVB3 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover,


2DVB4_S 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover, soil

dipping towards slab edge, period 1992-2010 (Section 7.7.1)

VF1 1D Vadose/w model, Fawkner site, 3 m deep, period 1945-2015 (Section

7.1.1.1)

VF2 1D Vadose/w model, Fawkner site, 3 m deep, short term wet condition,


VF3 1D Vadose/w model, Fawkner site, 3 m deep, short term dry condition,


VF4_A 1D Vadose/w model, Fawkner site, 3 m deep, typical average climate,

period 50 years (Section 7.4)

VF4_M 1D Vadose/w model, Fawkner site, 3 m deep, modified climate, period

50 years (Section 7.4)

7.1.1 Prediction of soil moistures

The models described in this chapter were analysed using climate data collected from

Essendon airport weather station. Figure 7-1 shows the variation of annual rainfall from

Essendon airport weather station from 1945 to 2014. Isolated dry and wet years were

recorded pre-1995; however, overall, the rainfalls prior to 1995 can be considered

average conditions. However, a significant reduction of annual rainfall occurred during

the millennium drought (1996-2009). The drought-breaking rainfalls in 2010 and 2011

are clearly noticeable and created back-to-back extreme events. Since 2012, a gradual

reduction of annual rainfall was observed. Interestingly, 2014 was recorded as the

warmest year for Victoria (BoM, 2015b), which suggests that climate conditions are

heading towards another dry period (Hannam, 2015).

216

Figure 7-1: Annual rainfall recorded in Essendon airport weather station

The Vadose/w model developed in this study was used to investigate the soil moisture

changes due to these different conditions, including different climate predictions.

7.1.1.1 Sites considered in the long term model predictions

Soil moisture changes depend not only on the climatic conditions, but also on the soil

profile. AS2870 defines sites with clay soil deeper than 3 m as deep-seated moisture

sites. Braybrook has a clay soil profile deeper than 4.5 m; hence, it is one of the deep-

seated moisture sites. Therefore, a 6 m deep soil column was considered in Vadose/w

modelling for Braybrook site. The 1D Vadose/w model analysed for Braybrook to

consider the 1945-2015 period is denoted as VB1 hereafter.

The required soil parameters were found in Rajeev et al. (2012) for Fawkner, which is

another expansive soil site in Melbourne. This site is a nature strip located beside a

road, and it was used to investigate the effect of expansive soil on buried gas pipeline.

In contrast to Braybrook, Fawkner has a clay soil profile of up to only 2 m. Table 7-1

shows the details of the Fawkner soil which has a shallow profile. There are MH silts in

the top 300 mm. Brown coloured ashes were observed in the top layers, which appears

the signs of filled material. A high plasticity clay layer continues for only about 1.7 m

below the top layer before meeting the bedrock. Table 7-2 lists the soil properties of the

Fawkner site. Atterberg limits in the Fawkner site are lower than those of Braybrook,

which suggests that Fawkner soils are less reactive than Braybrook soils. This site was

not classified based on AS2870, because the Iss values are not available for Fawkner

soils. However, hydraulic and thermal properties are available in Rajeev et al. (2012)

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 20150

200

400

600

800

1000

1200

Ann

ual R

ainf

all (

mm

)

1945-1995 1996-2009 2010-2011 2012-2014

217

and therefore another 1D model was analysed using them to observe the predictions in

the 1945-2015 period. This model is denoted as VF1 hereafter.

Table 7-1: Soil profile at Fawkner site (Rajeev et al., 2012)

Depth (m) Soil description

0.0-0.3 MH Silty Clay, brown ashes with root fibres, dry to moist

0.3-2.0 CH inorganic clay with high plasticity, brown ashes, moist, Stiff

Below 2.0 Basalt rock

Table 7-2: Geotechnical properties of Fawkner soil (Rajeev et al., 2012)

Depth (m)

Average dry

density (kN/m3)

Atterberg limits Ksat (m/s)

Liquid limit

Plastic limit

Plasticity index

0-0.25 19 69.1 22.4 46.7 2.25x10-5 0.25-0.75 19 70.4 20.1 50.3 1.97x10-9 0.75-1.0 19.9 60.3 17.5 42.8 2.3x10-10 1.0-1.5 20.5 65.9 20.7 45.2 2.3x10-10 1.5-2.1 20.3 61.5 19.5 42 2.3x10-10

7.1.1.2 Surface runoff considered in the long term model predictions

Models developed in Vadose/w software require climate data as an input parameter. The

software considers the runoff when the rainfall is distributed over 24 hours of the day

provided that the surface layer is saturated. The daily rainfall is considered in Vadose/w

models such that it is sinusoidal distributed throughout 24 hour period as described in

section 6.5 and Figure 6-4. Hence, even if the daily intensity is high, the hourly intensity

can be low, and the model has enough time for the infiltration. Therefore, depending on

the intensity of rainfalls on certain days, there can be sudden extreme changes in soil

moisture content in the model results. This phenomenon is highlighted in periods after

heavy rainfall. However, in most rainy days, rainfall is not distributed throughout but

falls at high intensity during part of the day and most of such rainwater runs off,

allowing only a small amount to infiltrate the soil. Therefore, in such intense rainy days,

a further correction is added to the data before they input to the model.

218

The higher the moisture content of the surface soil, the higher the runoff amount. There

is a well-established rational formula for surface runoff that considers that 50% to 70%

of rainfall can be runoff in suburban residential areas (Corbitt, 1999). Since the results

of this model will be used to design residential structures, a 60% runoff condition was

adopted during heavy rain periods. However, there were some days with extremely high

rainfall. For example, in February 2005, there were two days with more than 130 mm of

daily rainfall, which created flash flood conditions in parts of Melbourne. In modelling,

such high rainfall can make a huge impact on predicted moisture levels in deeper layers.

However, as the surface layer is saturated, the runoff amount will be greater than 60%.

Therefore, such extreme dates were adjusted accordingly in this model analysis. Based

on the observations of the model results, the following adjustments were made for the

long-term climate data sets:

If the summation of daily rainfall for the past 7 days (including the 7th day) is

less than or equal to 15 mm, no corrections were applied to the 7th day rainfall

(ractual)

If the summation of daily rainfall for the past consecutive days (including the 7th

day) is higher than 15 mm, the following corrections were applied to the 7th day

rainfall (ractual). The corrected rainfall (rcorrected) also depends on the amount of

ractual

I. If ractual> 10 mm and 0.4 x ractual≤ 10 mm, then rcorrected = 0.4 x ractual

II. If ractual> 10 mm and 0.4 x ractual> 10 mm, then rcorrected = 10 mm

III. If ractual≤ 10 mm then rcorrected = ractual

The climate data provided daily inputs into the Vadose/w models. However, the model

predictions were only saved for every 30-day interval in this analysis period to optimise

the analysis. The moisture of surface soils fluctuates more frequently because the soil

surface is directly exposed to climate conditions. Hence, 12-month average soil

moisture content levels were considered to observe the patterns of soil moisture

variation with the long-term changes in climate conditions. Moreover, 95th percentile

confident limits were considered to identify the variations in suction profiles in order to

investigate the characteristic changes in ΔU and Hs. The outcome of the models

developed in Vadose/w software was used to study ground movement changes as

describe in the next section.

219

7.1.2 Prediction of ground movement

Ground movement due to long-term climate conditions was calculated using three

different methods.

7.1.2.1 AS2870 method

The flow chart shown in Figure 7-2 was followed to obtain ys using the AS2870

method, which considers TMI of the particular period to obtain Hs. ΔU was considered

to be 1.2 pF as specified in the standard. Iss values of the Braybrook site were obtained

during the laboratory investigation described in Chapter 4 (Table 4-6). Those Iss values

were used for the Braybrook soil profile in the calculations shown in this chapter. Due

to the non-availability of Iss values, the AS2870 method was not used to obtain ys for the

Fawkner site.

Figure 7-2: Flow chart of AS2870 method

7.1.2.2 Vadose + AS2870 method

The next method of estimating ground movement is a combination of the Vadose/w

model predictions and the AS2870 method (flow chart shown in Figure 7-3). The

models developed in Vadose/w software produced soil suction profiles at every 30-day

interval. Characteristic maximum and minimum suctions were obtained from those

results for the different considered periods to determine ΔU and Hs. Then, ys values

were calculated using the AS2879 method. Similarly to the previous method, measured

Iss values were used for Braybrook soils. This method was not used in estimating ys in

Fawkner, because of the non-availability of Iss.

ysAS2870

Method

TMI

Hs

ΔU

Iss

220

Figure 7-3: Flow chart of Vadose/w + AS2870 method

7.1.2.3 Vadose + FLAC method

The third method of ground movement estimation is the use of the Vadose/w model

predictions as inputs in the FLAC model. A one-dimensional soil column was modelled

in FLAC3D software by another researcher as part of this comprehensive research

program.

This model considered the changes in the moisture content of soils and predicted the

corresponding ground movement using a function of soil moisture versus stiffness

(elastic modulus), shown in Figure 7-4. The soil stiffness was obtained at different

moisture contents using oedometer tests and power low method (Lu and Kaya, 2014).

This figure shows that the Braybrook soil has a stiffness of about 250 kPa at field

capacity (~33% of gravimetric moisture content), and it increases to about 1 MPa when

moisture content reduces to about 28%. The soil is modelled using the classical Winkler

springs. Poisson's ratio of the soil was assumed as 0.45. The shear modulus and bulk

modulus were obtained using elastic modulus and Poisson’s ratio. These properties

were obtained for both the Braybrook and Fawkner sites during the study. The soil

moisture predictions, saved at 30-day intervals, were fed into the FLAC model.

The FLAC model is a soil column developed in three-dimensional domain. The height

of the soil column is 5 m and meshed similarly to the 1D Vadose/w model down to the

depth of bedrock. It is fixed at the bottom (at the depth of bedrock) and then the rest of

the soil is allowed only vertical movement. The flow chart in Figure 7-5 shows the

estimation of ground movement using the Vadose/w and FLAC models.

Vadose model

SWCC


Climate data

ys

Soil suction

profiles

Hs

ΔU

Characteristic

suction profiles

AS2870 Method

Iss

221

Figure 7-4: Soil stiffness versus moisture content relationship for Braybrook soil

Figure 7-5: Flow chart of Vadose/w + FLAC model

7.2 MODEL PREDICTIONS DUE TO LONG TERM CLIMATE CONDITIONS

The changes of the soil moisture in response to long-term climate conditions were

investigated for the Braybrook and Fawkner sites. The climate conditions from 1900 to

2015 were used in the analysis. Since the initial conditions were not known, the initial

conditions of the validated model were used in this long-term analysis. These initial

conditions were measured up to only about 3.0 m depth and the values of deeper depths

were assumed, as described in Chapter 6. Hence, the first 30 to 40 year predictions were

ignored, considering that the soil moisture requires time to reach an equilibrium state to

avoid the influence from the initial condition. The model results starting from 1945 are

0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24 0.26 0.28 0.300

5000

10000

15000

20000

25000

Soi

l stif

fnes

s (k

Pa)

Gravimetric Moisture Content

PickedY1

y = 563895x2 - 355467x + 56146

Vadose model

SWCC


Climate data

Ground

movementFLAC model

Soil moisture vs strain

relationship

Soil moisture

profiles

222

considered in this section. There are three periods considered here, emphasising the

effect of millennium drought as given below.

1. 1945-1995: 50-year period prior to the millennium drought. Short-term severe

weather events occurred during this period. However, taking into account the

overall rainfall variation shown in Figure 7-1, this period can be considered as

showing average conditions in terms of the life span of a structure.

2. 1996-2009: millennium drought period in Victoria.

3. 2010-2011: two years of above average rainfall after the drought.

7.2.1 Variation of suction profiles

Minimum and maximum suction profiles were observed from the 1D model for the

three periods mentioned in the previous section to investigate the changes in ΔU and Hs.

Figure 7-6 shows major influences on characteristic suction profiles in Braybrook and

Fawkner. The minimum and the maximum suction profiles are plotted for the average

climate condition period. Drought conditions affected the dry suction profile while

heavy rainy periods affected the wet suctions. Therefore, Figure 7-6 shows only the

maximum suction for the 1996-2009 period and minimum suction profile for the 2010-

2011 period. Suction profiles have a champagne flute shape as observed in most of the

field investigations. The minimum and the maximum suction profiles in the 1945-1995

period shows that significant suction changes occurred down to about 3.0 m in

Braybrook (VB1 model). The suction profiles predicted by the model have slight

difference even at the bottom of the profile. However, suction changes less than 1% of

the ΔU were neglected. Hence, the depth that suction change reaches 1% of the ΔU was

considered as Hs. In Fawkner (VF1 model), changes were observed down to only about

1.4 m. Even though the climatic condition is similar in both sites, the location of

bedrock and the different clay properties created a significant difference in the depth of

suction change. Since moisture was able to penetrate deeper in the Braybrook site, the

fluctuations at the near surface soils are less than that of Fawkner. In Braybrook, at 0.3

m depth, suction changed by 1.3 pF prior to the drought period, whereas, in Fawkner,

the suction change at that depth was about 1.5 pF.

The maximum suction profile observed during the millennium drought period shifted to

the dry side in both sites. This highlights the effect of prolonged drought on soil

223

moisture levels, which consequently affects ground movement. However, this drying

effect occurred down to only about 1.4 m in Braybrook (where driest suction profile in

1996-2010 cross over the driest suction profile of 1945-1995 period), compared to 0.6

m in Fawkner. There is about 0.2 pF of additional suction change at 0.3 m depth due to

the drought conditions in both sites. The minimum suctions observed in the rainy period

show a shifting of suction profiles towards the wet side. However, these wet profiles did

not overtake the wet suction profile of average conditions during 1945-1995. Therefore,

this figure suggests that both sites have not fully recovered from the moisture deficit

they experienced during the millennium drought. This could be due to the greater deficit

condition in soil at the end of the Millennium drought. Moreover, the 2010-2011 wet

years were not as intense as the other wet years during 1945-1995 period as illustrated

in Figure 7-1.

Overall, these predictions suggest that not only climate conditions, but also soil

properties and site conditions, affect suction profiles. Hence, all of them need to be

considered in obtaining the design parameters, ΔU and Hs. Furthermore, the millennium

drought contributed dramatically to the changes in typical suction profiles.

Figure 7-6: Predicted characteristic suction profiles; a) Braybrook-VB1 model and b) Fawkner-VF1 model

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-2.4

-2.1

-1.8

-1.5

-1.2

-0.9

-0.6

-0.3

0.0

Log (Matric Suction)

Dep

th (m

)

1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min

50 yrs and extremes

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)


50 yrs and extremes

-0.3

a) b)

224

7.2.2 Variation of soil moisture contents

Figures 7-7 and 7-8 show the variation of volumetric moisture content in the Braybrook

and Fawkner sites respectively. Monthly results indicate more fluctuation near the

surface (at 0.1 m) and hence it is difficult to identify the trend of moisture change.

Therefore, the 12-month moving average moisture variation at 0.1 m is also plotted on

each figure. The 12-month average moisture variation clearly demonstrates the

reduction in soil moisture during the drought period from 1996 to 2009. The surface

moisture increased immediately after the drought-breaking rainfalls in 2010 and 2011,

but has started to reduce since 2012 due to the reduction in rainfalls in 2012 to 2014.

However, the volumetric moisture content at about Hs (3.0 m for Braybrook and 1.5 m

for Fawkner) is constant throughout all the periods in both sites.

Figure 7-7: Variation of volumetric moisture content near surface and at Hs– Braybrook (VB1 model)

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55 at 0.1 m - 12 month average results at 0.1 m - monthly results at 3.0 m - monthly results Daily rainfall (mm)

Date

Vol

umet

ric m

oist

ure

cont

ent

POND_OFF

0

25

50

75

100

125

150

Dai

ly ra

infa

ll (m

m)

225

Figure 7-8: Variation of volumetric moisture content near surface and at Hs – Fawkner (VF1model)

7.2.3 Variation of ground movement

Ground movements subsequent to soil moisture changes were obtained using the

different methods described in section 7.1.2.

Figure 7-9 shows the variation of ground movement obtained using VB1 predictions

and the FLAC model (Vadose + FLAC method described in section 7.1.2.3). The

seasonal fluctuations of ground surface are clearly shown in this figure and the recorded

droughts in Melbourne during the considered period are also evident. Before 1950, the

seasonal ground movement (within a year) was about 25 mm. This period was greatly

affected by the World War II drought, which occurred from 1937 to 1945. The ground

appears to recover from that drought after 1950 and then average conditions can be

observed until the 1990s. The seasonal ground movement is about 40 mm during this

period, despite few droughts experienced in this period, as shown in Figure 7-9. The

ground shows a settling trend during these events. The 12-month moving average

movement clearly illustrates the long-term trends. The millennium drought seems to be

the most severe drought, with seasonal ground movement reduced to about 20 mm

within this period. The effect of an above average rainfall period is also clearly visible

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55 at 0.1 m - 12 month average results at 0.1 m - monthly results at 1.5 m - monthly results Daily rainfall (mm)

Date

Vol

umet

ric m

oist

ure

cont

ent

POND_OFF

0

25

50

75

100

125

150

Dai

ly ra

infa

ll (m

m)

226

after 2010, which indicates a short term ground heaving. However, the ground was not

able to fully recover from the drought and remains in a moisture deficit condition.

Moreover, another dry period was observed from 2012, as shown in annual rainfall

(Figure 7-1); hence, the ground has begun to settle.

After the 1950’s, ground movement was considered to be in average condition. Based

on peak values, Figure 7-9 suggests that there was a total ground movement (peak to

peak) of approximately 80 mm prior to the millennium drought. A trend of ground

settlement started from around 1997 consequent to the dry period. The additional

ground movement that occurred due to the millennium drought is about 15 mm.

Figure 7-9: Braybrook ground movement prediction from VB1 and FLAC model

Figure 7-10 shows the variation of ground movement obtained from the VF1 model and

FLAC model (Vadose + FLAC method described in section 7.1.2.3). Because of the less

reactive and shallower soil profile, ground fluctuations in Fawkner are smaller than

those of Braybrook. Subsequently, the Fawkner site appears to be less sensitive to

extreme climate events. The effect of the World War II drought is also lesser in

Fawkner than in Braybrook. The seasonal ground movement in Fawkner is about 20

mm during 1950 to 1995. This was reduced to about 10 mm within the millennium

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

Wo

rd W

ar 2

dro

ug

ht

~193

7-19

45

Rep

ort

ed d

rou

gh

t

~196

5-19

68

Rep

orte

d d

rou

gh

t,

~198

2-19

83A

sh W

edn

esd

ay,

Feb

198

3

Bla

ck S

atu

rday

,

Feb

2009

Mill

enn

ium

d

rou

gh

t,

~199

6-~2

009

Ground movement 12 month average

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

ys = ~ 80 mm

Additional ys = ~ 15 mm

227

drought period. Based on peak values, Figure 7-10 suggests that there was a total

ground movement of 37 mm prior to the millennium drought. An additional 7 mm of

ground movement occurred due to the millennium drought. This increment is 19%

compared to the ground movement in the pre-drought period.

Figure 7-10: Fawkner ground movement prediction from VF1 and FLAC model

7.2.4 Comparison of ground movement estimations

7.2.4.1 Influence of millennium drought of ground movement

In this section, the AS2870 method and the predictions from the VB1 and VF1 models

were used to estimate ground movement using the three methods described in section

7.1.2. The estimations were obtained for two periods (1945-1995 and 1945-2012),

excluding and including the millennium drought.

Firstly, ground movements were calculated using the AS2870 method only (described

in section 7.1.2.1). TMI was calculated using Method 1 (explained in Chapter 3) and it

is -6 for the period from 1945 to 1995. TMI is -9 for the total period including the

millennium drought and wet conditions (1945-2012). According to AS2870 (2011), the

climatic conditions belong to climate class 3 for both periods. Therefore, the proposed

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-35-30-25-20-15-10

-505

10152025303540

Wo

rd W

ar 2

dro

ug

ht

~193

7-19

45

Rep

ort

ed d

rou

gh

t

~196

5-19

68

Rep

orte

d d

rou

gh

t,

~198

2-19

83A

sh W

edn

esd

ay,

Feb

198

3

Bla

ck S

atu

rday

,

Feb

2009

Mill

enn

ium

d

rou

gh

t,

~199

6-~2

009

Ground movement 12 month average

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

ys = ~ 37 mm


228

Hs is 2.3 m for both periods. AS2870 (2011) recommended a ΔU of 1.2 pF irrespective

of the climatic condition. These values and measured Iss values were used to estimate ys

of Braybrook. Iss values for Fawkner are not available and therefore this calculation was

not considered for Fawkner site.

Ground movement in Braybrook was also calculated using the VB1 model results and

the AS2870 method together (method described in section 7.1.2.2). The calculation

given in the AS2870 method considered the area of the minimum and maximum suction

profile by approximating the shape to a triangle. The triangular shape is defined using

ΔU and Hs. Figure 7-11 shows that there is a very high suction change near the ground

surface. Therefore, if ΔU is taken from the surface suction change of model predictions,

it will add a large area, which is outside of the actual champagne flute shape.

Further, during the construction of footings, the topsoil is normally removed. For waffle

slabs, they are placed at this new surface level, whereas stiffened slabs would involve

digging trenches for the stiffening beams. Hence, the slab would normally be founded

below the natural ground surface. Therefore, in this calculation, ΔU is considered at 0.3

m depth below the ground surface. The AS2870 method was used only for the

Braybrook site using measured Iss values.

Figure 7-11: Idealized characteristic suction profiles in Braybrook site (VB1 model)

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)

1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max

50 yrs and extremes

-0.3

229

These round movement calculations were compared with the ground movement results

described in section 7.2.3. Table 7-3 lists the summary of estimation of ys for Braybrook

using the different methods explained above. According to the AS2870 method,

Braybrook has similar ys values irrespective of the periods. Consequently, Braybrook

was classified as E in both periods. When Hs and ΔU are taken from the Vadose/w

model, the Braybrook site is classified as E class in both periods. However, there is an

additional estimated ground movement of 18 mm due to extreme climate conditions

after 1995. The ground movement in response to different climatic conditions was

properly expressed in the FLAC model results, because this method does not simplify

the suction variation into a triangular shape but calculates ground movement due to

changes in successive monthly moisture profiles which directly obtained from the

Vadose/w model. It predicted an additional 15 mm in the Braybrook site due to the

millennium drought. Overall, the model predictions highlight the influence of the

millennium drought on ground movement, which created an approximately 15% to 20%

increment.

Table 7-3: Estimation of ys for Braybrook site

Method 1945 - 1995 period 1945 - 2012 period Percentage

increment of ys

Hs (m)

ΔU (pF)

ys (mm)

Site class

Hs (m)

ΔU (pF)

ys (mm)

Site class

AS2870 2.3 1.2 83 E 2.3 1.2 83 E 0 Vadose + AS2870

3.0 1.3 116 E 3.0 1.5 134 E 16

Vadose + FLAC

-* -* 80 E -* -* 95 E 19

-* :- not involved in this method

7.2.4.2 Ground movements in 25 year periods

AS2870 recommends considering at least 25 years to calculate TMI in determining the

effect of climate conditions on ground movement. Section 3.3.5.3 suggests that the

effects of isolated extreme events are neutralized by considering a higher number of

years in the TMI calculation. Hence, the use of a longer period (or all available data)

may not represent the actual condition of the soil. However, selecting a limited number

230

of years makes the TMI biased, if there are influential short-term climate events. Hence,

in this study, the climate conditions in 25-year periods were investigated to observe the

TMI changes and the ground movements emphasizing the impact of the millennium

drought. Table 7-4 shows the 5 different periods during 1950 to 2014. TMI values were

calculated using Method 1 (explained in Chapter 3) and then the climate zones were

selected as specified in AS2870 (2011).

Table 7-4: 25 year periods and corresponding TMI

Period TMI Climate zone (AS2870, 2011)

1950-1974 -4 2 1960-1984 -7 3 1970-1994 -6 3 1980-2004 -12 3 1990-2014 -16 4

Hs and ΔU were selected from the standard for the corresponding climate zone. Table

7-5 lists ys calculations for 25-year periods.

Table 7-5: Estimation of ys based on AS2870 (2011) for Braybrook

Period Hs (m)

ΔU (pF)

ys (mm)

Site class

1950-1974 1.8 1.2 66 H2 1960-1984 2.3 1.2 83 E 1970-1994 2.3 1.2 83 E 1980-2004 2.3 1.2 83 E 1990-2014 3.0 1.2 107 E

According to Table 7-5, the Braybrook site classification changed from H2 to E during

25-year periods. The influence of drought reduced the TMI value in the last two 25-year

blocks. Since Hs increased from 2.3 m to 3.0 m when changing the climate zone from 3

to 4, the estimated ys was increased.

The 25-year blocks were considered in the Vadose/w model predictions. In contrast to

the standard specifications, the model predictions have shown that the ΔU has changed

as a result of climate conditions. Hs of Braybrook is higher than that of Fawkner, but

both sites have shown no changes in Hs during the 25-year periods (Figure 7-12).

231

Figure 7-12: Changes in characteristic suction profiles within 25 year periods; a) Braybrook -VB1 model and b) Fawkner-VF1 model

Hs and ΔU were taken from the Vadose/w model, which is shown in Figure 7-12(a). The

crack depth is considered as 0.75 of Hs. Measured Iss values were considered along the

depth of the Braybrook soil profile. Table 7-6 summarises the ys estimation for

Braybrook using different methods. The calculations and model predictions shown in

Table 7-6 are broadly consistent with the AS2870 method calculations given in Table

7-5. The effect of the millennium drought can be observed in the last 25-year block in

1990-2014. Table 7-7 shows that ys of the Fawkner site has also increased due to the

inclusion of the drought period in 1990-2014, but the magnitude of increment is lower

than that of Braybrook. This is possibly due to the less reactivity and the shallower soil

profile in Fawkner. However, these values suggest that the impacts of extreme events

can possibly be captured using the AS2870 method by reducing the average period of

TMI.

1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-3.0

-2.7

-2.4

-2.1

-1.8

-1.5

-1.2

-0.9

-0.6

-0.3

0.0


Dep

th (m

)

1950-1974 Characteristic min 1950-1974 Characteristic max 1960-1984 Characteristic min 1960-1984 Characteristic max 1970-1994 Characteristic min 1970-1994 Characteristic max 1980-2004 Characteristic min 1980-2004 Characteristic max 1990-2014 Characteristic min 1990-2014 Characteristic max

25 yr periods

a) b)

1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)

1950-1974 Characteristic min 1950-1974 Characteristic max 1960-1984 Characteristic min 1960-1984 Characteristic max 1970-1994 Characteristic min 1970-1994 Characteristic max 1980-2004 Characteristic min 1980-2004 Characteristic max 1990-2014 Characteristic min 1990-2014 Characteristic max

25 yr periods

-0.3

232

Table 7-6: Estimation of ys for 25 year periods – Braybrook site

Period Vadose + AS2870 Method Vadose + FLAC

Method Hs (m)

ΔU (pF)

ys (mm)

Site class

ys (mm)

Site class

1950-1974 3.0 1.2 107 E 70 H2 1960-1984 3.0 1.2 107 E 70 H2 1970-1994 3.0 1.3 116 E 85 E 1980-2004 3.0 1.3 116 E 85 E 1990-2014 3.0 1.3 116 E 101 E

Table 7-7: Estimation of ys for 25 year periods – Fawkner site

Period Vadose + FLAC

Method ys (mm) Site class

1950-1974 38 M 1960-1984 32 M 1970-1994 37 M 1980-2004 37 M 1990-2014 44 H1

7.2.5 Effects of the depth of bedrock on ground movement

The bedrock depth is frequently observed to be within 2 m to 4 m in the Western

suburbs of Melbourne. However, in the Braybrook site, the depth to the bedrock is

greater. The model was therefore developed up to 6 m depth. The measured soil

properties were available down to only about 2.5 m depth. In this research, a second,

modified model was created using the same soil properties, assuming that the bedrock is

located at 3 m depth. This model is denoted as VB2 hereafter. The VB2 model can be

considered as a general case for typical basaltic soil sites in the Western suburbs. The

VB2 model was developed with a 4 m soil column and the bottommost meter was

considered as the bedrock. The SWCCs of soils were considered similar to the VB1

model. The Ksat of soils between 1.8 m and 3 m were considered to be decreasing

gradually from the measured value at 1.8 m to the Ksat of bedrock. Then, the hydraulic

conductivity functions were developed accordingly as explained in Chapter 4.

Figure 7-13 shows the characteristic suction profiles obtained from the VB2 model. The

surface suction values highly depend on extreme climate events; hence, they are similar

233

to the results of the actual model with bedrock at 5 m. However, the shallower bedrock

caused a reduction in the depth of suction change. The VB2 model predicts that the Hs

is approximately 2.7 m for the pre-drought period. The suction profiles in this period

can be considered as typical shapes similar to the VB1 model results. The millennium

drought moved the dry suction profile further towards the dry side and the wettest

suction profile recorded after drought-breaking rainfalls was within the typical suction

profile. Figure 7-13 also shows the idealised triangular shapes drawn to calculate ys

using the AS2870 guideline.

Figure 7-13: Changes in characteristic suction profiles -VB2 model; a) Extreme profiles in three periods b) Idealized triangles for AS2870 calculations

Figure 7-14 shows the variation of ground movement obtained for the Braybrook site

using the VB2 and FLAC models. The fluctuations of the ground due to seasonal

movements in this figure are similar to the predictions of the VB1 model shown in

Figure 7-9. The seasonal ground movement was about 40 mm during the pre-drought

period and reduced to 25 mm during the millennium drought. Figure 7-14 shows that

there was a total ground movement (peak to peak) of 85 mm prior to the millennium

drought. Approximately 16 mm of additional ground movement occurred due to the

millennium drought.

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.02.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0


Dep

th (m

)

1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max

a) b)

-0.3


Dep

th (m

)


234

Figure 7-14: Ground movement prediction from VB2 and FLAC model

Table 7-8 shows a summary of estimation of ys using the VB2 model predictions and

the AS2870 method. The standard recommends similar Hs and ΔU values, even for the

modified case, because they are only dependent on climate conditions. Therefore, the ys

calculation for this modified case is essentially similar to the actual model (section

7.2.3) and produced no changes due to the inclusion of the millennium drought.

Although the Hs of the VB2 model is less than that of the VB1 model, the ys calculation

based on the Vadose and AS2870 method show similar ys values. The additional ground

movement of 16 mm due to millennium drought caused an increase of about 15% in the

typical ys. Similarly, in the Vadose and FLAC model, an additional 16 mm caused an

increase to the ys value of about 19%. According to the model predictions for 6 m and 3

m deep bedrock soil profiles, there was a 15% to 20 % increase in ground movement

due to the millennium drought.

Even though the depth of the bedrock is reduced in this analysis to consider the effect of

depth of bedrock, it is not considered to be less than the Hs limit of 3 m observed in the

VB1 model. It is only reduced to represent the typical depth of Bedrock in Melbourne

area. Hence, in this case, Hs is not affected by bedrock and the ground movement was

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-40

-30

-20

-10

0

10

20

30

40

50

60

70 Ground movement 12 month average

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

ys = ~ 85 mm


235

not expected to be reduced. However, the bedrock represents a no-flow boundary in the

model, which the reduction of depth of this impervious layer resulted in greater

moisture fluctuations at top layers during the analysis. These fluctuations resulted in a

slight increase of ground movement.

Table 7-8: Estimation of ys for Braybrook site with bedrock at 3m depth (from VB2 model)

Method 1945 - 1995 period 1945 - 2012 period Percentage

increment of ys

Hs (m)

ΔU (pF)

ys (mm)

Site class

Hs (m)

ΔU (pF)

ys (mm)

Site class

AS2870 2.3 1.2 83 E 2.3 1.2 83 E 0 Vadose + AS2870

2.7 1.3 105 E 2.7 1.5 121 E 15

Vadose + FLAC

-* -* 85 E -* -* 101 E 19


7.2.6 Effects of site drainage condition on ground movement

Runoff conditions govern the availability of water for infiltration into the soil. Since this

study focused on soil moisture changes in regards to urban residential footing design, an

appropriate runoff condition for residential areas was used, as explained in section

7.1.1.2. However, different runoff conditions can cause different soil moisture results

and hence it is important to maintain proper conditions to minimise possible damages.

In this section, different runoff conditions were considered to observe the possible

influences on ground movement. Figure 7-15 shows the soil moisture predictions from

the Vadose/w model without using a runoff correction. Hence, even if the daily rainfall

is much higher and spread over a few hours of the day, the full rainwater amount is

made available for infiltration until the saturation is achieved. This condition is similar

to flat, open areas of grassland with poor drainage. The predictions show that, in such

cases there is a considerable change in soil moisture even at deeper layers. This analysis

emphasizes the significance of a runoff correction in the Vadose/w model.

236

Figure 7-15: Soil moisture predictions without any runoff correction

In the earlier models presented in this chapter, a surface runoff correction of 60% was

considered. To provide further understanding of the effect of different levels of runoff,

another case of 30% runoff correction was analysed. Figure 7-16 shows the ground

movement predictions for the conditions of 60%, 30% and no runoff corrections.

Figure 7-16 indicates that the ground can have very high heave movements during wet

periods if the site has a poor drainage condition. In contrast, all the different runoff

conditions will produce similar ground movements during dry periods. There was a

considerable wet period in the early 1990s before the millennium drought. Hence, the

grounds were in a heaved state at the beginning of the drought and this has been the

main reason for the resulting excessive settlements within the drought period. The 60%

runoff correction considered in the above sections predicted a settlement of about 95

mm within this period. If the runoff condition is 30%, the settlement will increase by

about 20%. The condition with no runoff correction will increase it by about 45%.

Therefore, as expected, ground movement can be significantly reduced by providing

proper site drainage around a residential structure. A proper drainage condition (slope

away from the footing) with an appropriate runoff condition will minimise the water

available to infiltrate the soil underneath the footings.

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.25

0.30

0.35

0.40

0.45

0.50

0.55 at 1.0 m depth at 2.0 m depth at 3.0 m depth at 4.0 m depth Daily rainfall (mm)

Date

Vol

umet

ric m

oist

ure

cont

ent

POND_OFF

0

50

100

150

Dai

ly ra

infa

ll (m

m)

237

Figure 7-16: Ground movement predictions with different runoff conditions

7.3 SHORT TERM CLIMATE VARIATIONS

In order to further examine ground movement due to different weather scenarios, more

models were analysed for an additional 4-year wet period as extended versions of the

models described in section 7.2.2. In this case, both the Braybrook and Fawkner soils

were considered. The climate data set used in the VB1 model was modified to include

an additional 4-year wet period at the end of 2014. The climate forecast of the wet

period was created by replicating the climate condition of the years 2010 and 2011 over

4 years. Hence, the soil moisture changes were considered from 1945 to 2018 with a

forecasted wet period in 2015-2018. The Braybrook model analysed using this climate

data set is denoted as VB3 hereafter. The Fawkner model is denoted as VF2.

Similarly, another 4 years of dry weather was forecast by replicating the climate

condition of 2013 and 2014. This condition was then added to the end of the climate

data set used in VB1. This data set was then used to consider the effect of a short-term

dry period. The Braybrook and Fawkner models analysed using this climate data set are

denoted as VB4 and VF3 respectively.

1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-50

0

50

100

150

200 No surface runoff No surface runoff (12 month average) 30% surface runoff 30% surface runoff (12 month average) 60% surface runoff 60% surface runoff (12 month average)

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

238

Figure 7-17 shows the variation of the 12-month moving average ground movement

obtained from the VB1, VB3 and VB4 model predictions fed into the FLAC model. The

VB3 model outcome suggests that if a wet climate condition occurs in the next 4 years,

the ongoing settling trend will terminate and the ground will reach conditions similar to

2011. However, 4 years is not enough to recover from the millennium drought and to

reach the typical conditions experienced in the pre-1995 period. VB3 model was

analysed further with 2 more years of wet climate condition similar to 2010-2011. The

results suggest that the ground would recover to the condition it had in the 1980s in

about six years in total.

The VB4 model predictions suggest that the ground will remain in the moisture deficit

condition experienced during the millennium drought. A similar outcome was observed

in the Fawkner site from the VF2 and VF3 models, shown in Figure 7-18. Since

Fawkner has a less reactive and shallower soil profile than Braybrook, changes due to

short-term climate conditions create smaller changes in ground movement. Hence, both

the wet and dry 4-year models showed only small changes in terms of the 12-month

moving average. Further, this emphasises the impact of soil and site conditions on

ground movement in terms of recovery from extreme climate events. However, this

model does not consider cracking of soils which accelerates the wetting process after a

severe dry period in an actual condition. The cracks allow water to fill in and start to

wet the deeper soils. Hence, the recovery process could be faster in actual condition

than the model prediction.

239

Figure 7-17: 12 month moving average ground movement – Braybrook

Figure 7-18: 12 month moving average ground movement –Fawkner

1945 1953 1961 1969 1977 1985 1993 2001 2009 2017-60

-50

-40

-30

-20

-10

0

10

20

30

40

50

60 from VB3 model - Predicted wet climate: 2015 - 2018 from VB4 model - Predicted dry climate: 2015 - 2018 from VB1 model - Actual climate: 1945 - 2014

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

1945 1953 1961 1969 1977 1985 1993 2001 2009 2017-25

-20

-15

-10

-5

0

5

10

15

20

25 from VF2 model - Predicted dry climate: 2015 - 2018 from VF3 model - Predicted wet climate: 2015 - 2018 from VF1 model - Actual climate: 1945 - 2014

Date

Gro

und

mov

emen

t (m

m)

POND_OFF

240

7.4 LONG TERM CLIMATE PREDICTIONS

Climate predictions for Australia suggest that the ongoing drying trend will continue

into the future (Austroads, 2004, Smith et al., 2009, Hughes, 2003). Most Australian

cities will experience a reduction in rainfall and an increase in temperature. According

to the average of several scenarios, there would be a reduction in annual rainfall by

about 14% and an increase in temperature by 2.5 0C within the typical 100-year period.

These predictions were incorporated in the 1D models developed in Vadose/w software

to observe possible future changes in soil moisture content.

In this case, the climate data set period of 1987-1992 from Essendon airport was chosen

and considered as an average weather condition. This 5-year period was replicated over

50 years to create a typical average climate data set. Then, the Austroads (2004) climate

predictions were applied to this data set. Minimum and maximum temperatures were

modified to show a gradual increase of 1.25 0C at the end of the 50 years. A gradual

reduction of rainfall was also applied to the average data set, such that there is a total

reduction of 7% by the end of the 50-year period. 1D models developed in Vadose/w

software were analysed for these climate data sets for both the Braybrook and Fawkner

soil properties. The Braybrook models analysed using average and modified climate

data are denoted as VB5_A and VB5_M respectively. Similarly, the Fawkner models

are denoted as VF4_A and VF4_M.

Figures 7-19 and 7-20 show changes in ground movement due to predicted climate

changes. They clearly indicate that there would be an additional settlement in ground

surface due to predicted conditions compared to the average typical condition. The

Braybrook site indicated 12 mm of additional settlement, whereas Fawkner indicated 6

mm. The settlement in Braybrook appears to be severe compared to Fawkner, which is

due to the shallower bedrock and less reactive soil in Fawkner.

241

Figure 7-19: Effect of long-term climate predictions on ground movement – Braybrook

Figure 7-20: Effect of long-term climate predictions on ground movement – Fawkner

2013 2018 2023 2028 2033 2038 2043 2048 2053 2058-8

-4

0

4

8

12

16

20

24

28

32

36 from VB5_A model from VB5_M model

Number of years

Gro

und

mov

emen

t (m

m)

POND_OFF - typical vs predicted

12 mm

0 5 10 15 20 25 30 35 40 45 50

2013 2018 2023 2028 2033 2038 2043 2048 2053 2058-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

from VF4_A model from VF4_A model

Number of years

Gro

und

mov

emen

t (m

m)

POND_OFF - typical vs predicted

6 mm

0 5 10 15 20 25 30 35 40 45 50

242

The moisture deficit condition of the soils would create conditions for severe results.

For example, failures in water pipes or excessive garden watering could create severe

differential movements due to the ability of soil to have high absorption. Thus, potential

climate change can create such situations.

7.5 SOIL MOISTURE CHANGES BENEATH COVER SLABS

The effects of long-term climate conditions were further studied using the 2D model to

observe the changes underneath the footing, together with some effects from abnormal

conditions.

The 2D model was mainly developed to observe the lateral soil moisture movements

beneath cover slabs. The model predictions were used to examine the changes in edge

moisture variation, which is an important parameter in residential footing design.

The long-term climate data used in the 1D model explained in section 7.1 was used in

the 2D model. Hence, the effects of different climate conditions on the extent of

moisture change from the slab edge (‘e’ distance) in three periods were considered and

described in this section. The 2D model incorporated a 0.3 x 6 m cover slab and 5 m

long open area, as shown in Figure 6-22. The cover slab was assumed to be perfectly

flexible with no applied load. Hence, the slab is just a cover in this analysis. The soil

moisture variation underneath the cover slab (at 300 mm depth) was used to investigate

the changes in ‘e’ distance. This model was analysed for the same climate data used in

the VB1 model and this is denoted as 2DVB1 hereafter.

Figure 7-21 shows the variation of soil moisture at 300 mm depth during the period

1945–2015. All the soils were at about 35% volumetric moisture content at the initial

stage. Figure 7-21 shows that even though the slab shields the soils beneath it from

climate influences, the moistures changed up to a significant distance. The far end has

been defined as a no-flow boundary (prevents moisture movement), which is the axis of

symmetry. The 2D model results show that there is a slight change in soil moisture even

at the far end of the slab. This is due to long term equilibrium occurring under the slab

where impacts of climate conditions at the outside of the edge cannot be reached.

However, this moisture change is less than 1% within 70 years and hence can be

considered negligible.

243

Figure 7-21: Predicted moisture variation with the distance at 300 mm depth in Braybrook soil

Since soil suction is the preferred parameter over moisture content, the suction variation

under the cover slab was considered to examine the changes in ‘e’ distance. There was a

slight continuous change in suction that proceeded towards the far end of the slab,

similar to the moisture variation shown in Figure 7-21. It was corrected by adjusting all

the suctions by adding an offset to make no suction variation at the far end. Figure 7-22

shows the corrected critical suctions along the 300 mm depth layer. Since the wettest

suction profile during the 2-year wet period in 2010 and 2011 was found within the

suction profiles of the typical condition in 1945-1995 as shown in Figure 7-6(a), the

post-drought period was not considered here. However, the driest suction during 1996-

2010 was plotted to observe the effects of the millennium drought.

During wet periods, the soil moisture content increased due to water infiltration. Hence,

edges of the slabs tended to heave due to the swelling of surrounding soils. This was

identified as an edge heave condition. During a dry period, moisture content reduces

and thus soils around the slab edge settle down, which is referred to as edge settlement.

In Figure 7-22, the suctions on the ‘y’ axis were plotted in the reverse direction to

graphically identify the edge heave and edge settlement conditions. The ‘e’ distances

0 1 2 3 4 5 6 7 8 9 10 110.22

0.24

0.26

0.28

0.30

0.32

0.34

0.36

0.38

0.40

0.42

0.44

Axis of symmetry6 m long cover slab Open area exposed to climate effects

Volu

met

ric m

oist

ure

cont

ent

Distance (m)

300 mm

Soil

244

obtained were compared to the initial condition shown in Figure 7-22. The suction

variations in 1945-1995 show the typical ‘e’ distance in the Braybrook soil, which is

about 4 m for edge heave condition and 3 m for centre heave condition. The extraction

of soil moisture is difficult compared to absorption. Hence, the soil moisture changes in

the edge heave condition continued far into the bottom of the slab, compared to the

centre heave condition. However, during the millennium drought, the variation of the

driest suctions closely approached the similar ‘e’ distance as the edge heave condition.

Figure 7-22: Predicted edge moisture variation (e) at 300 mm depth in Braybrook soil

AS2870 provides two equations for ‘e’ distance for centre heave (can be treated as edge

settlement) and edge heave conditions, as given in Equations 7-1 and 7-2 respectively,

𝑒 =𝐻𝑠

8+

𝑦𝑚

36; For centre heave condition ……..……………...………... Equation 7-1

𝑒 = 0.2 × 𝐿 ≤ 0.6 +𝑦𝑚

25; For edge heave condition ………....………... Equation 7-2

where ‘Hs’ is the design depth of suction change in metres, ‘ym’ is differential mound

movement in millimetres and ‘L’ is slab length in metres.

0 1 2 3 4 5 6 7 8 9 10 112.50

2.75

3.00

3.25

3.50

3.75

4.00

4.25

4.50

Edge settlement

Edge heave

Intial condition

Characteristic wettest suctions 1945-1995 Characteristic driest suctions 1945-1995 Characteristic driest suctions 1996-2010

Log

(Mat

ric s

uctio

n)

Distance (m)

6 m long cover slab Open area exposed to climate effects300 mm

Soil

Axis of symmetry

245

These equations estimate ‘e’ in metres. The value of ym depends on ys and the heave

condition as shown in Table 7-9. The Mitchell's method shown in Table 7-9 provides

conservative values for ym and hence for ‘e’ distance. Therefore, this method was used

to calculate ‘e’ distance in this section to compare with the model predictions. ys values

obtained from the AS2870 estimation and the 1D model (described in section 7.2.3 and

Table 7-3) were used to obtain ‘e’ distance from Equations 7-1 and 7-2. ‘e’ distance

given in Equation 7-2 depends on the slab length and is limited by ym. Since the cover

in the 2D model represents only half of the cover, it can be taken as an infinitely long

slab. Hence, in the edge heave condition, ‘e’ distance was taken from the limit related to

ym in Equation 7-2. The values taken from these equations are compared with the 2D

model predictions in Table 7-10.

Table 7-9: relationship of ym and ys (AS2870, 2011)

Table 7-10: Comparison of changes in 'e' distances

Heave condition Method

1945 - 1995 period 1945 - 2009 period Hs (m)

ys (mm)

e (m)

Hs (m)

ys (mm)

e (m)

Centre heave

AS2870 2.3 83 1.9 2.3 83 1.9 1D Vadose model 3.0 80 1.9 3.0 95 2.2

2D Vadose model (Figure 7-22)

-* -* 3.0 -* -* 3.5

Edge heave

AS2870 -* 83 2.9 -* 83 2.9 1D Vadose model -* 80 2.8 -* 95 3.3

2D Vadose model (Figure 7-22)

-* -* 4.0 -* -* 4.0


As described in section 7.2.3, the AS2870 model estimates the same ys values for the

two periods excluding and including the millennium drought condition. As a result, both

Heave condition

ym for Walsh's method

ym for Mitchell's method

Centre heave 0.7 ys 0.7 ys Edge heave 0.5 ys 0.7 ys

246

Equations 7-1 and 7-2 produce the same ‘e’ values for those two periods. However,

these two equations are sensitive to the difficulty of extraction and absorption of soil

moisture and therefore the calculated ‘e’ value in the edge heave condition is higher

than that of the centre heave condition. The predicted ys values from VB1 model were

used in Equations 7-1 and 7-2 to calculate ‘e’ distances. The results show an increase of

about 15% in ‘e’ distance in both heave conditions due to the millennium drought. The

2DVB1 model results suggested that ‘e’ distance is higher than the calculated values

based on ys. Furthermore, there is also a 20% increase in ‘e’ due to the millennium

drought. Since the wettest recorded condition in the rainy period (2010 and 2011) was

within the average conditions (Figure 7-6(a)), there is no change in ‘e’ distance in edge

heave condition for pre- and post-drought periods.

The 2DVB1 model indicates that the moisture can proceed far underneath the slab

compared to the predictions from the VB1 model and the AS2870 method. This

moisture change is governed by the hydraulic conductivity in the lateral direction, as

described in the previous chapter. At the Braybrook site, there is a change in soil layers

at 300 mm depth. The hydraulic conductivity of soils below 300 mm is lower than the

top layer. Hence, the moisture prefers to accumulate on the layer interface than

penetrate the below soil. These moistures then tend to travel along the lateral direction.

In actual conditions, this phenomenon may not occur, and the cracks can accelerate the

vertical moisture movement that reduces the moisture change in lateral direction.

Hence, the magnitude of ‘e’ distance can be lower in actual condition. However, in

terms of percentage change of ‘e’, the model results suggest that the millennium

drought created an increase of 15% to 20%.

7.6 CHANGES OF THE MOUND PROFILES

In addition to the estimation of the ‘e’ distance via soil moisture predictions, the 2D

Vadose/w model results were fed into the FLAC model (described in section 7.1.2.3) to

observe the variation of mound shapes. The FLAC model is essentially a one-

dimensional soil column. In this case, the 2D Vadose/w model results at several discrete

points along the width of the model were saved separately to produce moisture profiles

at those points. These profiles were then used in the one dimensional soil column in the

FLAC model to obtain ground movement at the discrete points to draw the mound

247

shape. Nine discrete points were selected at 1 m intervals both underneath the slab and

open ground, as shown in Figure 7-23. The cover slab was 6 m long; therefore, those

discrete points selected were symmetrical to the slab edge.

There are certain limitations in using the 2D Vadose/w model results in the FLAC

model to obtain the ground movement. As the one-dimensional soil column in the

FLAC model does not consider the movement of adjacent soils, the predictions appear

to be higher than actual conditions. In actual conditions, the shear effects in adjacent

soil particles restrain the free movement and reduce severe movements in adjacent soils.

Such influences can be observed near the edge of the slab where greater changes in ΔU

and Hs occur in adjacent soils. The FLAC model outcome showed greater mound slope

near the slab edge where actual conditions would create a smooth mound shape. This

issue can be overcome by developing a two-dimensional FLAC model that considers

the shear effects. This part of the model development is yet to be finalised and the

FLAC model development is out of the scope of this PhD research.

Figure 7-23: Discrete points along the distance where soil moisture variations considered to obtain ground movement

Distance - m-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0

Elev

atio

n - m

-6.5

-6.0

-5.5

-5.0

-4.5

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

Climate BoundaryNo flow Boundary on cover slab

2m 3m 4m 5m 6m 7m 8m 9m 10m

Axis of symmetry

248

The generated deflected shapes (mound shapes) due to heave and settlement conditions

were considered in this case to identify the mound parameters (ym, ys and ‘e’ distance)

as defined in AS2870. Therefore, the worst dry period and wet period were selected

based on Figure 7-9. Based on the ground movements shown in Figure 7-9, the

Braybrook site had a gradual heave condition from 1983 to 1992 followed by a

settlement condition, during the millennium drought, until 2010. If a slab had been

constructed in 1983, it would have experienced the maximum edge heave in 1992.

Similarly, if a slab had been constructed in 1992, it would have experienced the

maximum edge settlement at the end of 2010. Therefore, the 1983-1992 and 1992-2010

periods were selected to observe the mound shapes in edge heave and edge settlement

conditions. The following sections describe the predictions of those mound shapes.

7.6.1 Slab subjected to heave condition (1983 to 1992)

The 2D Vadose/w model with cover slab (similar to the model shown in Figure 7-23)

was analysed for the period of 1983-1992 to represent the situation of a newly placed

slab in 1983. This model is denoted as 2DVB2 hereafter. The 2DVB2 model requires

the defining of initial moisture conditions at each node point of the model. Hence,

another 2D model with the same size as that shown in Figure 7-23 was analysed without

any cover slab. This model was essentially developed to define initial moisture content

at different starting points of any model to be considered with a cover slab and is

denoted as 2DVB_I. Analysis of the 2DVB_I model for the period from 1945 to 2012

produced identical results to the VB1 model described in section 7.2. However, since it

is a two-dimensional model of the same size, it can be used to define the initial moisture

contents corresponding to all the nodes in the 2DVB2 model.

Figures 7-24 to 7-26 show the characteristic minimum and maximum suction profiles at

certain discrete points along the width of the model. The changes of suctions are

minimal at 3 m distance, which indicates only a small ground movement. The ΔU and

Hs increase towards the edge of the slab and as expected have the highest values at the

open ground. These ΔU and Hs values were used to calculate ground movement at the

discrete points based on AS2870 procedure. Measured Iss values were used along the

depth to represent the Braybrook soil condition. In addition, the monthly variations in

moisture profiles at those discrete points were used in the 1D FLAC model to obtain the

ground movements. The ground movements along the distance are shown in Table 7-11.

249

Figure 7-24: Suction profiles during 1983-1992 at distances 3 m and 4 m from axis of symmetry


1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)

Characteristic min at 3 m Characteristic max at 3 m

-0.3 -0.3


Dep

th (m

)


1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)



Dep

th (m

)


-0.3-0.3

250


Figure 7-27 demonstrates that the calculations using Vadose/w + AS2870 method are in

strong agreement with the FLAC model predictions. However, the ground movement

results given in Table 7-11 show differences in some values, especially at the open

ground which may be due to the idealisation of suction triangles in AS2870 procedure.

Moreover, the AS2870 method considers the effect of crack depth, such that movement

is higher at the depths below the crack depth. This effect is enhanced in open ground

where Hs values are higher compared to the soil under the slab.

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)



Dep

th (m

)


-0.3-0.3

251

Figure 7-27: Maximum edge heave profile during 1983-1992

Table 7-11: Ground movement estimation during 1983-1992

Parameter Distance from axis of symmetry

2m 3m 4m 5m 6m 7m 8m 9m 10m ΔU (pF) 0.17 0.21 0.30 0.44 0.87 1.16 1.19 1.20 1.20 Hs (m) 1.0 1.0 1.3 1.5 2.0 2.0 2.0 2.0 2.0

ys (mm) from Vadose + AS2870 method 5 6 12 20 52 70 72 72 72

Ground movement (mm)from Vadose +

FLAC method 4 6 10 17 46 57 60 61 61

7.6.2 Slab subjected to settlement condition (1992 to 2010)

Similar to the edge heave condition investigated in 2DVB2 model, the centre heave

condition was also considered during a wet period. Since there was a wet period

recorded before the millennium drought, the soils continued to settle starting from a

high value in 1992. This model considered the climate condition from 1992 to 2010 and

0 1 2 3 4 5 6 7 8 9 10 11-10

0

10

20

30

40

50

60

70

Edge heave

FLAC model predictions Vadose model predictions+ AS2870 method

Gro

und

mov

emen

t (m

m)

Distance (m)


Soil

Axis of symmetry

Extent of cover

Intial condition

252

is denoted as 2DVB3 hereafter. The 2DVB_I model was employed to obtain the initial

moisture contents in 1992 and then the 2DVB3 model was analysed up to 2010.

Figures 7-28 to 7-30 show the characteristic minimum and maximum suction profiles at

certain discrete points along the width of the model. The changes of suctions are

minimal at 3 m distance indicating only a small ground movement, similar to the edge

heave condition. The ΔU and Hs increase towards the edge of the slab and as expected

have the highest values at the open ground. These ΔU and Hs values were used to

calculate ground movement at those discrete points based on AS2870 procedure. The

FLAC model was also used to obtain ground movements at the discrete points using

monthly soil moisture profiles.


1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)


-0.3 -0.3

Log (Matric Suction)D

epth

(m)


253



Figure 7-31 shows the edge settlement profile obtained from the two methods. Similar

to the edge heave case, both methods produced similar mound shapes. Table 7-12 shows

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)



Dep

th (m

)


-0.3 -0.3

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

-6

-5

-4

-3

-2

-1

0


Dep

th (m

)



Dep

th (m

)


-0.3 -0.3

254

the ground movement values from both methods. The corresponding location values are

similar in both methods apart from values at the open area, which is possibly due the

consideration of crack with in Vadose + AS2870 method. Further, the FLAC model

results show a sudden settlement near the slab edge, which caused this difference. This

is possibly due to the non-availability of shear resistance from adjacent soils, which is

lacking in the one-dimensional soil column in the FLAC model.

Figure 7-31: Maximum centre heave profile during 1992-2010

Table 7-12: Ground movement estimation during 1992-2010

Parameter Distance from axis of symmetry

2m 3m 4m 5m 6m 7m 8m 9m 10m ΔU (pF) 0.12 0.23 0.49 0.55 0.84 1.15 1.17 1.18 1.18 Hs (m) 0.9 1.0 1.2 1.5 2.0 2.5 2.5 2.5 2.5

ys (mm) from Vadose + AS2870 method 3 7 18 25 51 86 88 89 89

Ground movement (mm)from Vadose +

FLAC method 2 5 10 19 60 73 77 79 79

0 1 2 3 4 5 6 7 8 9 10 11

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

10

Edge settlement

FLAC model predictions Vadose model predictions+ AS2870 method

Gro

und

mov

emen

t (m

m)

Distance (m)


Soil

Intial condition

Axis of symmetry

Extent of cover

255

7.6.3 Comparison of mound shape predictions

Based on the 2DVB2 and 2DVB3 model results described in the previous two sections,

important parameters for mound shapes can be identified. The ground movement

immediately under the edge of the slab (ym) and the movement in open ground (ys) can

be compared in each mound shape. The ratios between these two parameters are

proposed in Walsh’s and Mitchell’s methods as listed in AS2870 and shown in Table

7-9. Table 7-13 shows those ratios obtained from the modelling results presented in the

previous two sections. For the edge heave condition in 1983-1992 in the Braybrook site,

ym/ys factors are 0.7 and 0.8. For the edge settlement condition in 1992-2010 in the

Braybrook site, ym/ys factors are 0.6 and 0.8. These values are in line with the proposed

0.7 factor in Mitchell’s method. By using more analyses of different sites, these

relationships, including ‘e’ distance, can be established.

Table 7-13: Mound shape parameters obtained from models

Method

Edge heave (1983-1992)

Edge settlement (1992-2010)

ys (m)

ym (m) ym/ys ys

(m) ym (m) ym/ys

Vadose + AS2870 72 52 0.7 89 51 0.6

Vadose + FLAC 61 46 0.8 79 60 0.8

7.7 EFFECT OF ABNORMAL MOISTURE CONDITIONS

Climate conditions can significantly affect moisture conditions around and underneath

slabs, as described in the above section. These influences can be exaggerated due to

improper maintenance of the area adjacent to footings, which includes non-attendance

to broken water pipes. The author observed house construction sites and visited some

damaged houses during the study period. In most cases, the soils around the footing

were not given adequate attention during construction. In some cases, rainwater

downpipes were not connected to the drain lines, which created significant amounts of

water next to the slab edges during the construction period. Moreover, some sites have

open areas with slopes towards the footing. Some new houses had additions after

constructions, such as pavements with slopes towards the houses. As a result, runoff

water flowed towards the slab, which increased the amount of water available for

256

infiltration. In this study, the modelling of a sloping ground was used to investigate soil

moisture changes.

7.7.1 Soil slope towards the cover slab

In this case, a mild slope of 1:50 towards the cover slab was introduced over the 5 m

length of open area in the 2D Vadose/w model. The model was analysed from 1945 to

2012 to observe the suction changes in different climate conditions. This model will be

denoted as the 2DVB4_S model hereafter. Since the effect of the slope of open ground

and consequent water collection next to the slab was required in the 2DVB4_S model, a

ponding effect available in Vadose/w software was used. In this case, the model allows

water to travel along the dip and collect at the lowest point of the surface. Hence, more

water is available for infiltration at the edge of the slab. The 2DVB4_S model results

were compared with the 2DVB1 model, which had no slope in any direction and

pooling on the surface was also not allowed. Figure 7-32 shows the suction variation at

300 mm depth observed in the 2DVB1 and 2DVB4_S models.

Figure 7-32: Comparison of lateral moisture movement at 300 mm depth in with and without slope condition

0 1 2 3 4 5 6 7 8 9 10 11

2.6

2.8

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

0.45 pF

Soil

1

}Distance (m)

Log

(Mat

ric s

uctio

n)

1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min 1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min

Open area exposed to climate effects

300 mm

Soil

}from 2DVB1model

}from 2DVB4_Smodel

6 m long cover slab

50Axis of symmetry

257

Since rainwater can flow towards the cover, the moisture content of the soils next to

slab edge is higher in the 2DVB4_S model than in the 2DVB1 model. Specifically, the

amount of water available to move laterally beneath the cover slab is substantially

increased. This phenomenon reaches significant proportions in 2011 and 2012, the two

years of above average rainfalls after the millennium drought. During this wet period,

suction at the edge of the slab is 0.45 pF lower in the 2DVB4_S model than in the

2DVB1 model, which emphasises the influence of water flow, and collects near the slab

edge. The decrease in moisture content during the drought period was also lower in the

2DVB4_S model predictions than in the 2DVB1 model. This is because the additional

amount of water available at the slab edge moves into the soils beneath and decreases

the deficit. Taken together, the model results suggest that soil moisture changes beneath

covers can be significantly increased due to slopes towards the footing.

7.8 SUMMARY

This chapter describes the applications of the finite element models developed in this

study to predict soil moisture changes. The models were used to determine soil moisture

changes due to several long-term climate scenarios and site conditions. In addition to

the Braybrook site, Fawkner, another reactive soil site in Melbourne, was also

considered. Fawkner has a shallower soil profile and less reactive soils than Braybrook.

Each analysed model was denoted based on the considered climate data set and the site

conditions. The model predictions were then used to obtain ground movements using

three different methods - the AS2870 method, the Vadose + AS2870 method and the

Vadose + FLAC method.

The long-term climate data were taken from Essendon airport weather station for the

analysis period of 1900 to 2015. The initial conditions were not known for these periods

and hence the initial conditions corresponding to calibration (given in Chapter 6) were

used. However, the model results for the first 30 to 40 years were ignored to avoid the

effects of the initial condition. The model results considered the period commencing 50

years before the millennium drought. This period was divided into three sections based

on the millennium drought: pre-drought (1945-1995), millennium drought (1996-2010)

and the wet period after the drought (2011-2012). The condition in the 1945-1995

period was considered as the average climate condition during a lifespan of a structure.

258

ΔU and Hs values were obtained from the models’ results for different periods. There

was a very high suction change observed at the ground surface, which is due to direct

interaction with climate conditions. Nevertheless, during the construction of footings,

the top soil is normally removed and the slab would typically be founded below the

natural ground surface. Therefore, in this calculation, ΔU is considered at 0.3 m depth,

below the ground surface.

The predictions of VB1 (the Braybrook model for 1945-2012) suggest that between

1945 and 1995, ΔU and Hs for Braybrook were 1.3 pF and 3.0 m respectively.

Similarly, VF1 (the Fawkner model for 1945-2012) suggests that Fawkner had ΔU and

Hs of 1.5 pF and 1.8 m respectively. Deep-seated moisture change was observed in the

VB1 model as Braybrook has a deep soil profile. However, because of the shallower

soil profile in Fawkner, the VF1 model showed a smaller Hs value than VB1 for the

Fawkner site. Since the moisture movements continue at a deeper depth in Braybrook,

the fluctuations and changes near the surface (at 0.3 m depth) were less than those of

Fawkner. Both the VB1 and VF1 models predicted that these sites experienced an

additional increase of suction of 0.2 pF due to the moisture deficit created by the

millennium drought. Ground movement predictions of the FLAC model using the VB1

and VF1 model results showed variations in seasonal ground moments. These results

suggest that the millennium drought was the worst drought recorded during the past 70

years and highlight the settlement trend during the 1996-2009 period. According to the

ground movement calculations from these model results, the millennium drought

created a 15% to 20% increase in the ground movement experienced in the pre-drought

period. This increment was not captured by the AS2870 method, which depends on

average TMI over the calculated period. However, when the TMI was calculated in 25-

year blocks instead of over the total period, the impact of the drought was reflected in

the ground movements.

The VB2 model was analysed to consider the effect of the depth of bedrock. Here, the

bedrock of Braybrook was assumed to be at 3 m, which represents the typical condition

of a basaltic soil site. This model resulted in a lesser Hs value (2.7 m) but the ΔU was

the same as in VB1, indicating the influence of bedrock on the depth of Hs. ΔU

primarily depends on soil properties and extreme climate conditions. However, the VB2

259

model also predicted a 15% to 20% increase in ground movement due to the millennium

drought.

The Vadose/w software considers the runoff when the rainfall is distributed over 24

hours of the day provided that the surface layer is saturated. The daily rainfall is treated

in Vadose/w models such that it is a sinusoidal distribution over 24 hours and hence,

even if the daily intensity is high, the hourly intensity can be low. However, in most

rainy days, rainfall is not evenly spread throughout but falls at high intensity during

certain parts of the day, and most of such rainwater runs off, allowing only a small

amount to infiltrate the soil. Therefore, in such intense rainy days, a further correction is

added to the data before they input to the model. A surface runoff correction of 60%

(typical value for urban residential areas) was considered in all the models discussed

here. Further models were analysed to determine the influence of site drainage

conditions on ground movement. In this case, 30% and zero runoff corrections were

considered. A lower surface runoff is associated with greater availability of water for

infiltration. Hence, poor drainage conditions will create greater ground movements.

Compared to the 60% runoff considered in VB1, 30% and zero runoff increase the

maximum observed ground movement by 20% and 45%, respectively.

The 1D models were also used to determine the ground movement due to predicted

climate conditions. In this case, 4 years of wet and dry climate conditions were

forecasted for 2015-2018 using past climate data. These climate data sets were used to

analyse 1D models from 1945 to 2018. The model results from a forecasted wet climate

condition suggest that the ongoing settling trend will terminate due to wet conditions

and the ground conditions will be similar to those experienced in 2011. However, 4

years of wet climate conditions is not sufficient to allow the grounds to fully recover

from the moisture deficit caused by the millennium drought period. However, in actual

condition, cracks allow rainwater to move deep into the soil and accelerate the wetting

process. Therefore, in actual condition, a further recovery could have been observed by

such 4 years of above average rainfall. The model results from a forecasted dry climate

condition showed that a dry period will drag the soils back to a drought condition at the

end of 2018. The changes in ground movement in the Fawkner site due to these

different climate conditions are smaller than in Braybrook. This is due to the shallower

and less reactive soil profile in Fawkner.

260

Moreover, long-term climate predictions were also considered using 1D models.

Reported climate predictions suggest an ongoing drying with an increase in temperature

and a decrease in rainfall. These changes were applied to a data set of typical average

climate conditions over 50 years. Model predictions suggest that both Braybrook and

Fawkner soils will experience a moisture deficit due to an ongoing drying compared to

the typical average condition. At the end of the 50-year period, Braybrook will

experience an additional 12 mm settlement, whereas Fawkner will experience half of

that.

The 2D model developed in Vadose/w software was used to determine the soil moisture

changes in the lateral direction. A perfectly flexible cover was introduced into the 2D

model to investigate the soil moisture changes beneath the cover due to climate

influences on an adjacent open area. The results of this model (2DVB1) were also

useful in identifying changes in ‘e’ distance due to different climate conditions. The ‘e’

distances obtained from these models were compared with those of the AS2870 method.

The model predictions suggested that the millennium drought has created an increase of

15% to 20% in ‘e’ distances. Since the AS2870 method produced the same ys for the

1945-1995 and 1945-2009 periods, the change in ‘e’ distance was not captured using

this method.

Changes in soil mound shapes beneath cover slabs were also investigated using the 2D

model results. To observe edge heave and edge settlement conditions, two periods of the

most extreme wet and dry climate conditions were identified: 1983-1992 and 1992-2010

respectively. Then, two different models were analysed for climate conditions in these

periods. The moisture predictions of these models were used in a one-dimensional soil

column in the FLAC model to determine the ground movement at several discrete

points along the distance from the axis of symmetry. ys values were also calculated

based on the AS2870 method using characteristic suction profiles at these discrete

points. Considering mound profiles in both edge heave and edge settlement conditions,

the calculations based on the AS2870 method are in strong agreement with the FLAC

model predictions. However, the FLAC model predictions showed a steep slope in

mound profiles near the edge of the slab. This is possibly because the one-dimensional

soil column in the FLAC model does not consider the shear effects between adjacent

soils. The shear interaction in adjacent soils will reduce sudden high deflection of

261

discrete points and hence produce a smooth mound profile. A full 2D model in FLAC

will overcome this issue; however, development of the 2D model in FLAC is yet to be

completed and is beyond the scope of this thesis.

Further analyses in the 2D models in Vadose/w software were performed to observe the

effects of abnormal moisture sources on soil moisture changes. A cover slab was

modelled with adjacent soils dipping towards it. The sloping ground creates runoff

towards the slab edge and increases the water available for infiltration. This model

(2DVB4_S) was analysed for 1945 to 2012 and then compared with the control model

(2DVB1). The predictions indicated that the sloping ground significantly increased the

soil moisture at the edge of the slab. In fact, during the wet period in 2010 and 2011, the

characteristic suction at the slab edge was 0.45 pF lower in the sloping ground case

compared to the control model.

262

8. CONCLUSIONS AND FUTURE WORK

8.1 OVERVIEW OF THE STUDY

Prior investigations have suggested that the Victorian climate has changed over the last

few decades. In addition, back-to-back extreme climate events were observed in the

recent past and more of these events are expected in the future. These changes affect the

soil moisture conditions and have a severe impact on volume changes in expansive

soils. Recent media reports and anecdotal evidence suggest that a large number of

houses were damaged as a result of footing movements which may have been caused by

climate related soil moisture changes. Hence, it is timely that the consideration of

climate influence and the procedure of estimating ground movement in the standard of

residential footing design are reviewed.

The procedure outlined in the AS2870 for calculating characteristic ground movement

was investigated, with a particular emphasis on climate influences. A field site was

established to monitor the expansive soil behaviour. A site in Braybrook, which is in the

Western suburbs of Melbourne, was selected for field monitoring. Braybrook has a

consistent profile of extremely reactive basaltic clays. The purpose of the field site was

to collect a comprehensive dataset of soil properties and monitor soil moisture changes

and the subsequent ground movement over several seasons. A one dimensional finite

element model using Vadose/w software was developed to investigate the soil moisture

changes in response to climate conditions. The finite element model was based on the

measured expansive soil properties of Braybrook site and the climate data collected

from a nearby weather station to define boundary condition of the model. The model

was validated against the soil moisture data collected from the Braybrook site

monitoring. The model was then extended to a two dimensional model to observe the

moisture changes in soil beneath cover slabs due to climate influences on adjacent open

ground. These models were used to analyse the soil moisture changes due to long-term

climate conditions including recent extreme events. Furthermore, the soil moisture

changes in response to various climate scenarios were examined. The soil moisture

predictions were used as the input to another model developed by another researcher

using FLAC3D as a part of this comprehensive research study. The FLAC3D model

was developed to predict the ground movements due to the changes in soil moisture

263

conditions. The development of the FLAC3D model is out of the scope of this PhD

thesis however, the soil moisture and ground movement predictions are discussed in this

thesis. The model predictions of moisture and suction changes and ground movements

due to different climate conditions were compared with the estimations based on the

AS2870 method.

8.2 SUMMARY OF CONCLUSIONS

8.2.1 Ground movement, climate changes and TMI

The estimation of ground movement in footing design is dependent on factors affecting

the volume change behaviour of expansive soils, such as degree of reactivity of the soil

and amount of moisture change. The moisture changes in soil are created by several

sources including climate condition and manmade causes.

The method of estimating ground movement in the AS2870 provides a simplified

approach to obtain ys value of an undeveloped site for the purpose of site classification.

This method uses Iss to account for the degree of reactivity of soils. AS2870 considers

soil moisture changes by means of idealized suction profile which is defined using ∆U

and Hs. The standard procedure allows for correlation of Hs with the climate condition

of the area using the TMI. The depth of bedrock and water table affect the Hs. The

Standard provides a single ΔU value (1.2 pF) for all parts of Australia, irrespective of

the climate or site condition.

There are certain weaknesses in AS2870 in estimating ground movement one of which

is the lack of definition of the basis of TMI assumed in the Standard. Several methods

are available to calculate the TMI and each method can produce different values. Four

methods for calculating TMI were presented in Chapter 3 and their results compared,

Since each TMI calculation method produces different values, the correlation between

TMI and Hs generates different values for the same climate condition. This can result in

different footing designs. It was found that the method noted as “Method 1” produces

the closest results to those in AS2870.

In addition, the use of different averaging periods for TMI also produces different

values. Specifically, the more years used in the average calculation, the lesser the

sensitivity to isolated extreme weather events, such as droughts. The long-term average

264

TMI is appropriate to reflect long-term trends. However, for the residential footing

design, this averaging period must be considered together with more soil specific

parameters. Furthermore, it was found that the TMI largely depends on rainfall and,

hence, linear correlations were observed between annual rainfall and TMI variations in

most of cities in Victoria. The influence of the other climate components, such as

evaporation and relative humidity are not critical in determining soil moisture changes.

Furthermore, the climate zone map given in the Standard was developed based on

climate data from 1940-1960. However, in Australia, there has been a change in the

climate over the last few decades. The TMI trend of the last 50 years is clearly showing

the ongoing drying. If the same trend continues, it means that the TMI will also reduce.

The drying trend is forecasted by climate models such as that by CSIRO. Irrespective of

the TMI calculation method, it appears that there is an ongoing drying in the Victorian

climate. The modifications to AS2870 in the 2011 edition captured the changes of TMI

due to the drying effect experienced in the last 25 years. However, this may not be

sufficient to capture ongoing changes predicted for the future. Moreover, the values of

Hs and ΔU have not been updated in the Standard to reflect the recent changes and

possible future changes.

The findings presented in Chapter 3 also highlight an issue in estimating the degree of

reactivity of soil in terms of Iss. The shrink swell test, which is used to determine Iss, is

recommended in AS2870 to assess soil reactivity. The corresponding standard of the

test (AS1289) specifies Iss as a constant for a given soil type. In this research, soils

collected from different sites at different times of the year were tested and a number of

Iss values were obtained for the same soil. The results indicated that the Iss increases

with increasing in situ moisture. Even though the experimental data is limited, this

suggests the dependency of Iss on in situ moisture content, which is in contrast to the

assumptions outlined in the AS1289.7.1.1. Specifically, it can result in different footing

designs for a particular site, when the soils are tested at different times of the year.

Hence, Iss values should be reported with the initial moisture content of the soil and the

results considered in relation to the site climatic conditions.

265

8.2.2 Characterization of typical basaltic clay in Western Melbourne

As part of the research study described in this thesis, a field site was established to

collect the required data related to expansive soils in Melbourne. A comprehensive data

set was developed for the typical basaltic clay soils as found in Braybrook, located in

West Melbourne.

The data set consists of basic soil properties and some specific expansive soil

parameters. The basic properties include Atterberg limits, linear shrinkage, specific

gravity and clay content. The plastic limit of Braybrook clay varies from 20 to 25 %

while the liquid limit varies from 70 to 80%. Based on these results, the Braybrook soil

was categorised as CH type in the Unified soil classification. The linear shrinkage

varies by approximately 20% and the clay content of soils below 0.5 m is about 45%.

The clay content of the surface layer is less than that of deep soils, which reflects the

presence of silts and organic matter in the top soil. All of these properties are consistent

in the soils below the surface layer. The bedrock was not encountered in the Braybrook

site, even though the boreholes were cored down to 4.5 m.

In addition to the basic soil properties, some specific properties were investigated to

classify the site and examine the behaviour of expansive soils. The shrink swell index

was calculated to vary from 4 to 6% and, based on this index, the Braybrook was

classified as an extremely reactive site. However, X-Ray Diffraction tests revealed that

there was more than 50% of Quartz in the mineral composition of Braybrook clay.

However, Braybrook soils have less than 10% of sand. Hence, this Quartz content could

represent fine sediments, which have clay size and silt size minerals. Importantly, there

is more than 30% of Montmorillonite in the mineral composition in Braybrook clay,

which is the primary cause of the expansiveness.

In addition to the clay mineralogy, the hydraulic conductivity and SWCC functions

were developed for Braybrook soils to use in the prediction models. Matric suction and

volumetric moisture contents were employed which provided the coordinates of the

SWCC. Hyprop, WP4C and filter papers were used to measure the suctions values at

different moisture levels. Osmotic suction obtained from the filter paper method was

used to convert total suctions into matric suction measured from WP4C. A correlation

was developed between volumetric and gravimetric moisture contents of Braybrook

266

soils. This correlation was used to obtain volumetric moistures from measured

gravimetric moistures corresponding to WP4C and filter paper suctions. Since the

Braybrook site has a constant soil profile throughout the depth, the SWCC functions are

assumed to be similar in deep soils. However, the presence of organic matter caused a

different SWCC for the surface soils.

The saturated hydraulic conductivity of surface soils was found in the range of 10-7 m/s.

The hydraulic conductivities were reduced in deeper soils due to a higher clay content

and density. The saturated hydraulic conductivities of deeper soils were in the range of

10-9 m/s. Hydraulic conductivity functions of unsaturated soils were developed using

these values and SWCCs.

This unique data set is beneficial for both practitioners and researchers. It provides the

characteristics of typical basaltic clay found in West Melbourne, which are useful in site

classification and modelling.

8.2.3 Field monitoring of expansive soil behaviour

The field monitoring of a typical expansive soil site was performed in this study to

collect the data required to calibrate and validate the prediction models. The soil

moisture changes were monitored using neutron probe technique and the corresponding

ground movements were monitored using magnetic extensometers. Paving blocks were

placed at several locations to monitor the ground movement using a surveying level.

The neutron probe reads the number of neutrons that react with soil moisture during

measurements. Therefore, in this study, a calibration equation was developed between

neutron counts and volumetric moisture content. The calibration equation, which has

0.86 coefficient of determination, provides the corresponding volumetric moisture

content to the neutron count measurements. The field monitoring continued regularly

from April 10th, 2013 to March 25th, 2015. Seasonal moisture variations were observed

at three locations over the two-year period. All three locations showed similar moisture

profiles at deeper depths. However, there were some differences in near surface

measurements possibly due to local effects such as slope differences, potholes and grass

cover changes. The soil moisture changes were observed up to 1.25 m over the

monitoring period. The most significant changes were observed in the top 0.75 m soils.

Moisture contents of near surface soils followed the rainfall pattern with a certain time

267

lag. The seasonal heave and settlements were observed in three magmatic extensometers

located next to the neutron probe access tubes. Similar to the moisture changes, most of

the movements occurred in the top soil layers. The maximum seasonal ground

movement was in the range of 40-50 mm.

8.2.4 Finite element modelling approach of expansive soil and climate

interaction

The expansive soil properties and the data collected from regular monitoring were used

to develop finite element model using Vadose/w to predict soil moisture changes due to

climate conditions. The model requires specifying SWCC, hydraulic conductivity,

thermal conductivity and the specific heat capacity of the soil. The thermal properties

had a minimal impact on soil moisture changes, as suggested by sensitivity analysis.

Therefore, thermal conductivity and specific heat capacity were obtained from a site

close to Braybrook described in the literature. The soil properties were defined to a

depth of 6 m deep soil column to represent the soil profile. The climate boundary was

specified at the top surface and it includes daily inputs of rainfall, evaporation, relative

humidity, wind and temperature. These climate components were collected from

Essendon airport - a weather station close to the Braybrook site. The no-flow boundary

was defined at the bottom to simulate the effect of bedrock.

This model was analysed for the two-year period of field monitoring from 2013 to 2015.

The model predicts soil moisture and suction profiles as daily outputs. These predictions

were compared with the neutron moisture measurements. The results showed a good

agreement between soil moisture predictions and field measurements and hence the

model was considered as validated.

In order to study the soil moisture beneath a flexible cover, the 1D model was extended

to a 2D model. The observations of homogeneous soil in Braybrook soil suggest that the

lateral hydraulic conductivity, which is the only additional parameter required in the 2D

model, is similar to the hydraulic conductivity in the vertical direction. The results at

open area exposed to climate effects in the 2D model showed same moisture changes as

1D model for the period of field monitoring. However, the results of mound shapes

obtained from 2D models depend on the assumptions of lateral hydraulic conductivity.

The sensitivity analysis of the input parameters revealed that soil moisture changes are

268

mostly affected by the SWCC of soils followed by the hydraulic conductivity. A 20%

change in SWCC and hydraulic conductivity resulted in 22% and 2% change in soil

moisture, respectively, at 0.3 m below the surface. Rainfall is the most critical climate

component in changing soil moistures. The responses of the models to vegetation

effects and pooling situations were also considered. Grass covers prevent the

evaporation and increase the water available for the infiltration. Therefore, both grass

covers and pooling effects significantly increase the soil moisture.

The effect of cracks was not included in these models. The presence of cracks can

significantly change the moisture content of soils even at deeper depths. The cracks

allow rainwater to infiltrate and hence increase the moisture content of deep soils.

Therefore, in actual conditions during the rainy days of summer, the moisture may

increase abruptly. This is not captured in the models described in this thesis.

8.2.5 Prediction of ground movement due to several site conditions and

climate scenarios

The finite element models were used to investigate the soil moisture, suction and

ground movement due to long term climate conditions. In addition to the Braybrook

site, Fawkner - another reactive soil site in Melbourne - was considered. Fawkner has a

shallower soil profile and less reactive soils compared to Braybrook. The long-term

climate data taken from Essendon airport weather station were considered in the

analyses as Braybrook and Fawkner sites are close to each other. The model results

were considered for a period starting 50 years before the severe millennium drought.

The total period was divided in three based on the millennium drought; pre drought

(1945-1995), millennium drought (1996-2010) and the wet period after the drought

(2011-2012).

The predictions of the models developed in Vadose/w software were used to obtain ΔU

and Hs values in different periods. The corresponding ground movements were

calculated using the AS2870 method. In addition, the model results were fed into a one-

dimensional soil column developed in FLAC-3D software to predict ground movement.

The predictions suggest that during 1945-1995, ΔU and Hs of Braybrook were 1.3 pF

and 3.0 m, respectively. Deep-seated moisture change was observed in Braybrook

because of the deeper soil profile. The 1D model was modified to determine these

269

parameters if Braybrook had a shallower soil profile with bedrock at 3 m, which is the

general condition of basaltic soil sites in West Melbourne. However, the modified

model results suggested only a small reduction of Hs (2.7 m). ΔU appears to be a

dependent on climate conditions and properties of top soils.

Even though the climate conditions are the same in both Fawkner and Braybrook, the

Fawkner site had ΔU of 1.5 pF and Hs of 1.8m during 1945-1995. This is due to the

shallower soil profile in Fawkner. Further, the hydraulic conductivities of Fawkner soils

below the top layer are lower compared to Braybrook. Therefore, moisture flow is

restricted through deeper soils, which creates higher fluctuations in top soils and hence

higher ∆U.

Both Braybrook and Fawkner sites showed an additional increase of ΔU of 0.2 pF at the

end of the millennium drought that resulted in additional ground movement. The FLAC

model showed that the millennium drought produced the greatest ground movement

(settlement) during the past 70 years. In fact, the model results suggest that the

millennium drought created a 15-20% increase in the ground movement compared to

the pre-drought period. AS2870 provides a method to calculate ys for an undeveloped

site experiencing normal climate condition. Therefore, isolated extreme climate

conditions may not be captured in the AS2870 approach. Consequently, the impact of

the millennium drought would not have been captured in its estimation of the surface

movement, which depends on average TMI over a long period. However, when the TMI

was calculated in 25 year blocks instead of 50 year period, the impact of the drought

was reflected in the calculated ground movements.

A surface runoff correction of 60% (typical value for urban residential area) was used in

the prediction models. However, the effect of different site drainage condition on soil

moisture and ground movement was also investigated. A lower surface runoff results in

more water available for infiltration. Hence, poor drainage condition will create higher

ground movements. Compared to the 60% runoff correction considered, 30% and zero

runoff corrections will increase the maximum observed ground movement by 20 and

45% respectively.

Further, the validated model was used to determine the ground movement due to future

climate scenarios. In this case, 4 years of wet and dry climate conditions were

270

artificially forecasted for the period 2015-2018 using past climate data. These climate

data sets were used to analyse the 1D model from 1945 to 2018. The model results in

both Braybrook and Fawkner suggested that the ongoing settling trend would terminate

and the ground will reach a similar condition to that experienced in 2011. However, 4

years of wet climate condition is not sufficient to allow the grounds to completely

recover from the moisture deficit caused by millennium drought. However, in actual

condition, cracks allow rainwater to move deep into the soil, and accelerate the wetting

process. Therefore, in actual condition, a further recovery could have been observed by

such four years of above average rainfall.

Long-term climate predictions were also considered using the 1D models. A set of

climate data representing typical average climate condition was considered. It was

modified to integrate the ongoing drying trend reported by climate predictions

(Austroads, 2004). Models predictions suggest that both Braybrook and Fawkner soils

would experience a moisture deficit due to ongoing drying compared to the typical

average condition. At the end of 50 year period, Braybrook would experience an

additional 12 mm settlement whereas Fawkner would experience half of that.

The 2D model developed in Vadose/w software was used to determine the soil moisture

changes in the lateral direction. A perfectly flexible cover was introduced in the 2D

model to investigate the soil moisture changes beneath the cover due to climate

influences on an adjacent open area. The 2D model was used to determine the changes

in soil mound shapes beneath a flexible cover. To observe the highest edge heave and

edge settlement conditions, two periods of the worst wet and dry climate condition were

identified;1983-1992 and 1992-2010, respectively. Then, two different models were

analysed for climate conditions in these periods. The soil moisture predictions were

used in the FLAC model to determine the ground movement at several discrete

locations measured from the axis of symmetry. The ys values were also calculated based

on the AS2870 method using characteristic suction profiles at these discrete locations.

Considering mound profiles in both edge heave and edge settlement conditions, the

calculations based on AS2870 method are in strong agreement with the FLAC model

predictions. The model results suggest that this approach is effective in predicting

mound shapes for slabs placed at different times (i.e., slabs constructed during wet or

dry periods).

271

Additional analyses using the 2D models were performed to observe the effects of

abnormal moisture sources on soil moisture changes. The condition of a cover slab with

adjacent surface slope towards it was modelled. The sloping ground creates a runoff

towards the slab edge and increases the water available for infiltration. The predictions

indicated that this case resulted in a significantly wet condition in soils at the edge of

the slab. In fact, during the wet period in 2010 and 2011, the characteristic suction at the

slab edge is 0.45 pF lower in sloping ground case compared to the control model with

no slopes. .

In conclusion, the models developed in this study provide a comprehensive and versatile

approach to investigate soil moisture and ground movement due to different climate and

manmade conditions. They can be used not only to obtain ΔU and Hs but also to

determine variation in ground movement and mound shapes. Consequently, correlations

of the ground movement induced by various climate scenarios can be established using

further investigations of different soil types. These models will therefore greatly assist

the development of design tools for the footings of light structures.

8.3 RECOMMENDATIONS FOR FUTURE WORK

Even though, the research described in this thesis is a part of a comprehensive group

research programme, there were some limitations in the study, which opens various

paths for future research.

The models developed in this study were validated only for the Braybrook site for a

period of 2 years. However, more analysis is required, including different sites with

various soils and site conditions. Further analysis is essential for the provision of

generalized conclusions in expansive soil behaviour in response to the changes in

climate conditions.

The Vadose/w model developed in this study considers a crack free soil profile.

However, most of the clay soils experience cracking during dry weather conditions. In

fact, there were more than 1 m deep cracks observed in Braybrook site during the

summer. This condition can result in sudden increments of the moisture contents at deep

soils due to infiltration of runoff water through the cracks. It can affect the depth of soil

moisture change. Moreover, the cracks can reduce the vertical soil movement due to

272

availability of space to volume changes in the lateral direction. The cracking of soils

depends on various factors, including the climate, soil type and the local effects. Hence

it is difficult to generalize the way of crack propagation. However, since the cracks can

impact Hs and ys values, adopting the cracking behaviour in models could be effective

in designing residential structures on expansive soils.

In addition, the differential equations used in the Vadose/w model are limited only for

the “No snow” condition in climate. Hence, modifications must be employed

accordingly to use this model in analysing soil moisture changes in alpine areas.

Furthermore, the Vadose/w model only considers the effect of vegetation in terms of

grass cover. In most cases, grass covers reduce the amount of solar radiation available

on soil surface. This reduces the evaporation resulting in an increment in soil moisture.

Importantly, the effect of tree roots is different from grass covers. Tree roots absorb

moisture from deep soils and reduce the soil moistures. Therefore, the soil experiences

additional deficits and settlement due to trees. This phenomenon has been a common

cause for differential settlements in houses with trees in the influential zone. The

influence of trees must be considered in reference to a structure which is affected by

various factors, including the soil type, distance from the structure, type of tree canopy

and distribution of roots. The model developed in this study can be extended in future

research to include the influence of trees.

In addition to the potential advancements in the Vadose/w model, the development of

the 2D FLAC model is also an area for future research. The development of the 2D

FLAC modal began as part of this comprehensive research program but is yet to be

finalized. The 2D FLAC model overcomes the issues of neglecting shear effects of

adjacent soils in the 1D FLAC model when estimating ground movement profiles. The

2D FLAC model will predict the ground movement underneath cover slabs and,

therefore, will be highly useful in estimating mound shapes of slabs placed at different

times and exposed to different climate scenarios.

Apart from the possible upgrades to the models, the results of the model described in

this thesis can be utilized into a standard procedure. Since this model can produce soil

moisture and ground movement due to different climate conditions, they can be

categorized into a rationalized form. For example, the climate conditions could be

273

classified based on the severity of the extreme events and the prediction scenarios. The

severities can be categorized based on return periods. Then, the influence of those

climate events on footing design parameters can be specified for use in design

guidelines, for example changes in ΔU, Hs and ys based on the severity of extreme

events. This will allow footing designers to obtain relevant parameters based on the

expectable climate conditions, quality and financial feasibility of the construction rather

than depending solely on the past climate conditions. For, example; if a home owner

desires a house which can withstand severe climate events, the model can be employed

to obtain ground movements for climate conditions with appropriate extreme events.

However, such designs may require higher construction cost. Moreover, such a

procedure requires model predictions from a number of expansive soil sites.

274

9. REFERENCES

ACA. 2012. A Current Affair Channel 9 [Online]. http://aca.ninemsn.com.au/investigations/8424660/homes-cracking-under-pressure [Accessed 01-03- 2012].

AITCHISON, G. D. 1965. Moisture Equilibria and Moisture Change in Soils Beneath Covered Areas. Statement of the Review Panel, Engineering Concepts of Moisture Equilibria and Moisture Change in Soils. Butterworths, Sydney.

AITCHISON, G. D. & HOLMES, J. W. 1953. Aspects of Swelling in the Soil Profile. Australian Journal of applied Science, 4, 244.

AITCHISON, G. D. & RICHARDS, B. G. 1965. A Broad scale Study of Moisture Conditions in Pavement Subgrades throughout Australia. Part 1 - 4. Butterworths, Sydney.

AL-RAWAS, A. A. & GOOSEN, M. F. A. 2006. Expansive Soils: Recent Advances in Characterization and Treatment, Taylor & Francis.

ALONSO, E. E., GENS, A. & JOSA, A. 1990. A constitutive model for partially saturated soils. Geotechnique, 40, 405 –430.

ALONSO, E. E., VAUNAT, J. & GENS, A. 1999. Modelling the mechanical behaviour of expansive clays. Engineering Geology, 54, 173–183.

ALTMEYER, W. T. 1955. Discussion of Engineering properties of expansive clays. Proceedins ASCE, 81(separate No. 658).

AS1289.3.1.1 2009. Methods for testing soils for engineering purposes. Soil classification tests - Determination of the liquid limit of a soil - four point Casagrande method. Sydney, Australia.: Standards Association of Australia.

AS1289.3.2.1 2009. Methods for testing soils for engineering purposes. Soil classification tests - Determination of the plastic limit of a soil - Standard method. Sydney, Australia.: Standards Association of Australia.

AS1289.3.4.1 2008. Methods for testing soils for engineering purposes. Soil classification tests - Determination of the linear shrinkage of a soil - Standard method. Sydney, Australia.: Standards Association of Australia.

AS1289.7.1.1 2003. Methods for testing soils for engineering purposes. Determination of the shrinkage index of a soil; shrink swell index. Sydney, Australia.: Standards Association of Australia.

AS2870 1986. Residential slabs and footings. Sydney, Australia.: Standards Associatiion of Australia.

AS2870 1996. Residential slabs and footings - Construction. Sydney, Australia.: Standards Associatiion of Australia.

AS2870 2011. Residential slabs and footings. Sydney, Australia: Standards Association of Australia.

ASTM-D422 2007. Standard Test Method for Particle-Size Analysis of Soils. D422 - 63. ASTM International.

ASTM-D854 2010. Standard Test Methods for Specific Gravity of Soil Solids by Water Pycnometer. D854. ASTM International.

ASTM-D2487 2011. Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System). D854. ASTM International.

ASTM-D4943 2008. Standard Test Method for Shrinkage Factors of Soils by the Wax Method. D4943. ASTM International.

http://aca.ninemsn.com.au/investigations/8424660/homes-cracking-under-pressure

http://aca.ninemsn.com.au/investigations/8424660/homes-cracking-under-pressure

275

ASTM-D5084 2003. Standard Test Methods for Measurement of Hydraulic Conductivity of Saturated Porous Materials Using a Flexible Wall Permeameter. D5084 - 03. ASTM International.

ASTM-D5298 2003. Standard Test Method for Measurement of Soil Potential (Suction) Using Filter Paper. D5298. ASTM International.

ASTM-D6836 2008. Standard Test Methods for Determination of the Soil Water Chararcteristic Curve for Desorption Using a Hanging Column, Pressure Extractor, Chilled Mirror Hygrometer, and/or Centrifuge. D6836. ASTM International.

ATWELL, B. J., KRIEDEMANN, P. E. & TURNBULL, C. G. N. 1999. Plants in Action - Adaptation in Nature, Performance in Cultivation [Online]. Macmillan Education Australia Pty Ltd, Melbourne, Australia: http://plantsinaction.science.uq.edu.au/edition1/. [Accessed 25-02- 2015].

AUSTROADS 2004. Impact of Climate Change on Road Infrastructure. Sydney, Australia.

BANDYOPADHYAY, S. S. 1981. Prediction of Swelling Potential for Natural Soils. Journal of the Geotechnical Engineering Division, 107, 658-661.

BARNETT, I. C. & KINGSLAND, R. I. 1999. Assignment of AS2870 Soil Suction Change Profile Parameters to TMI Derived Climate Zones For NSW. Australian Geomechanics, 34, 25-31.

BARRY-MACAULAY, D., BOUAZZA, A. & SINGH, R. 2011. Study of Thermal Properties of a Basaltic Clay. Geo-Frontiers 2011.

BARRY-MACAULAY, D., BOUAZZA, A., SINGH, R. M., WANG, B. & RANJITH, P. G. 2013. Thermal conductivity of soils and rocks from the Melbourne (Australia) region. Engineering Geology, 164, 131-138.

BELCHER, D. J., SACK, H. S. & CUYKENDALL, T. R. 1950. The measurement of soil moisture and density by neutron and gamma-ray scattering, Indianapolis, Civil Aeronautics Administration, Technical Development and Evaluation Center.

BENSON, C. H. & TRAST, J. M. 1995. Hydraulic Conductivity of Thirteen Compacted Clays. Clays and Clay Minerals, 43, 669-681.

BIDDLE, G. 2001. Tree Root Damage to Buildings. Expansive Clay Soils and Vegetative Influence on Shallow Foundations.

BIDDLE, P. G. 1983. Patterns of soil drying and moisture deficit in the vicinity of trees on clay soils. Géotechnique, 33, 107-126.

BIDDLE, P. G. 1998. Tree root damage to buildings, Wantage, UK, Willowmead Publishing Ltd.

BOM 2012. Special Climate Statement 38. National Climate Centre: Bureau of Meteorology, Australia.

BOM. 2015a. Average annual, seasonal and monthly rainfall [Online]. http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp?period=an&area=vc#maps. [Accessed 01-09- 2015].

BOM. 2015b. Victoria in 2014: Another very warm year with very dry conditions in the west [Online]. Bureau of Meteorology http://www.bom.gov.au/climate/current/annual/vic/summary.shtml. [Accessed 20-07- 2015].

BRIAUD, J.-L. 2013. Laboratory Tests. Geotechnical Engineering. John Wiley & Sons, Inc.

http://plantsinaction.science.uq.edu.au/edition1/

http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp?period=an&area=vc#maps

http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp?period=an&area=vc#maps

http://www.bom.gov.au/climate/current/annual/vic/summary.shtml

276

BULUT, R. 2001. Finite Element Method Analysis of Slabs on Elastic Half Space Expansive Soil Foundations. PhD, Texas A & M University.

BULUT, R., LYTTON, R. L. & WRAY, W. K. 2001. Soil Suction Measurements by Filter Paper. In: VIPULANANDAN, C., ADDISON, M. B. & HANSEN, M. (eds.) Expansive Clay Soils and Vegetative Influence on Shallow Foundations. Houston, Texas, United States: ASCE Geotechnical Special Publication.

BURNETT, A. 1995. A quantitative X-ray diffraction technique for analyzing sedimentary rocks and soils. Journal of testing and evaluation, 23, 111-118.

CAMERON, D. A. 1977. Parameters for the design of residential slabs and strip footing. MEng, Victoria Institutes of Colleges (Swinburne College of Technology).

CAMERON, D. A. 1989. Tests for reactivity and prediction of ground movement, Canberra, AUSTRALIE, Institution of Engineers.

CAMERON, D. A. 2001. The extent of soil desiccation near trees in a semi-arid environment. Geotechnical & Geological Engineering, 19, 357-370.

CAMERON, D. A. & WALSH, P. F. 1984. The prediction of moisture induced foundation movements using the instability index. Australian Geomechanics, 8, 5-11.

CHAN, D., KODIKARA, J., GOULD, S., RANJITH, P., CHOI, X. S. K. & DAVIS, P. Data analysis and laboratory investigation of the behaviour of pipes buried in reactive clay. Proceedings of 10th Australia New Zealand Conference on Geomechanics - Common Ground 2007, 21st-24th October 2007 Brisbane, Australia. 206-211.

CHAN, D., RAJEEV, P., GALLAGE, C. & KODIKARA, J. Regional field measurement of soil moisture content with neutron probe. Proceedings of The Seventeenth Southeast Asian Geotechnical Conference, 2010. Taiwan Geotechnical Society/Southeast Asian Geotechnical Society, 92-95.

CHAN, D. C. C. 2014. A study of pipe-soil-climate interaction of buried water and gas pipes. PhD, Monash University.

CHAN, I. & MOSTYN, G. 2008. Climate Factors for AS2870 for the Metropolitan Sydney Area. Australian Geomechanics, 43, 17-28.

CHANASYK, D. S. & NAETH, M. A. 1996. Field measurement of soil moisture using neutron probes. Canadian Journal of Soil Science, 76, 317-323.

CHAO, K. C. 2007. Design Principles for Foundations on Expansive Soils. Ph.D, Colorado State University.

CHEN, F. H. 1988. Foundations on expansive soils, Elsevier. CLARKE, D. & SMETHURST, J. A. 2010. Effects of climate change on cycles of

wetting and drying in engineered clay slopes in England. Quarterly Journal of Engineering Geology and Hydrogeology, 43, 473-486.

CORBITT, R. A. 1999. Standard handbook of environmental engineering, New York McGraw-Hill.

COVAR, A. P. & LYTTON, R. L. 2001. Estimating Soil Swelling Behavior Using Soil Classification Properties. Expansive Clay Soils and Vegetative Influence on Shallow Foundations.

CRICHTON, A. J. 1974. Towards a Rational and Echonomical Design Method for Residential Slabs. MEng, Swinburne College of Technology, Melbourne.

CRONEY, D. & COLEMAN, J. D. 1961. Pore Pressure and Suction in Soils. Conference on Pore Pressure and Suction in Soils. Butterworths, London.

277

CUTLER, D. F. & RICHARDSON, I. B. K. 1981. Tree roots and buildings, London, Construction Press.

D.G.FREDLUND 1975. Engineering Properties of Regina Clay. Seminar on Shallow Foundations on Expansive Clays. Regina, Saskatchewan, Canada.

DAHLHAUS, P. G. & O'ROUKE, M. The Newer Volcanics. In: PECK, W. A., NEILSON, J. L. & OLDS, R. J., eds. Engineering Geology of Melbourne: Proceedings of the Seminar on Engineering Geology of Melbourne, 16 September 1992 Melbourne, Victoria, Australia. A.A. Balkema.

DARCY, H. Les Fontaines Publiques de la Ville de Dijon. 1856 Dalmont, Paris. 590-594.

DAS, B. M. 1998. Principles of Geotechnical Engineering, Boston, Mass, PWS Publishing.

DECAGON 2010. WP4C Dewpoint PotentiaMeter Manual. Operator’s Manual - Version 2. Pullman WA, USA: Decagon Devices, Inc.

DECAGON. 2012. WP4C Dewpoint Potentiameter [Online]. http://www.decagon.com/products/environmental-instruments/water-potential-instruments/wp4c-dewpoint-potentiameter/. [Accessed 05-24- 2012].

DELANEY, M., ALLMAN, M. & SLOAN, S. A Network of Field Sites for Reactive Soil Monitoring in the Newcastle-Hunter Region. Proceedings of the 7th. ANZ Conference in Geomechanics., 1996 Adelaide. 381-387.

DELANEY, M. G., LI, J. & FITYUS, S. G. 2005. Field Monitoring of Expansive Soil Behaviour in the Newcastle-Hunter Region. Australian Geomechanics, 40, 3-14.

DINGMAN, S. L. 2002. Physical Hydrology, Prentice Hall. DRISCOLL, R. 1984. A Review of British Experience of Expansive Clay Problems.

Fifth International Conference on Expansive Soils Adelaide, South Australia. EDLEFSEN, N. & ANDERSON, A. 1943. Thermodynamics of soil moisture.

Hilgardia, 15, 31-298. EVETT, S. R., HOWELL, T. A., STEINER, J. L. & CRESAP, J. L. 1993.

Evapotranspiration by soil water balance using TDR and neutron scattering. Management of Irrigation and Drainage Systems, Irrigation and Drainage Div./ASCE, 914-921.

FATAHI, B. 2007. Modelling of Influence of Matric Suction Induced by Native Vegetation on Sub-soil Improvement. PhD, University of Wollongong.

FITYUS, S., CAMERON, D. A. & WALSH, P. F. 2005. The Shrink-swell Test. Geotechnical Testing Journal, 28.

FITYUS, S. G., SMITH, D. W. & ALLMAN, M. A. 2004. Expansive Soil Test Site Near Newcastle. Journal of Geotechnical and Geoenvironmental Engineering, 130, 686-695.

FITYUS, S. G., WALSH, P. F. & KLEEMAN, P. W. 1998. The influence of climate as expressed by the Thornthwaite index on the design depth of moisture change of clay soils in the Hunter Valley. Conference on geotechnical engineering and engineering geology in the Hunter Valley. Springwood, Australia.

FOX, E. 2000. A Climate Based Design Depth of Moisture Change Map of Queensland and the Use of Such Maps to Classify Sites Under AS2870-1996. Australian Geomechanics, 35, 53-60.

FRATTA, D., AGUETTANT, J. & ROUSSEL-SMITH, L. 2007. Introduction to Soil Mechanics Laboratory Testing, New York, Taylor & Francis Group.

http://www.decagon.com/products/environmental-instruments/water-potential-instruments/wp4c-dewpoint-potentiameter/

http://www.decagon.com/products/environmental-instruments/water-potential-instruments/wp4c-dewpoint-potentiameter/

278

FREDLUND, D. G. 2000. The 1999 R.M. Hardy Lecture: The Implementation of Unsaturated Soil Mechanics into Geotechnical Engineering. Canadian Geotechnical Journal, 37, 963 – 986.

FREDLUND, D. G. & RAHARDJO, H. 1993. Soil Mechanics for Unsaturated Soils, John Wiley & Sons.

FREDLUND, D. G., RAHARDJO, H. & FREDLUND, M. D. 2012. Unsaturated Soil Mechanics in Engineering Practice, Hoboken, New Jersey, John Wiley and Sons.

FREDLUND, D. G. & VU, H. Q. 2003. Numerical Modelling of Swelling and Shrinking soils around slabs-on-ground. Proceeding of Post-Tensioning Institute Annual Technical Conference. Huntington Beach, CA, USA.

FREDLUND, D. G. & XING, A. 1994. Equations for the soil-water characteristic curve. Canadian Geotechnical Journal, 31, 521-532.

FREDLUND, D. G., XING, A. & HUANG, S. 1994. Predicting the permeability function for unsaturated soils using the soil-water characteristic curve. Canadian Geotechnical Journal, 31, 533-546.

FU, X., SHAO, M., LU, D. & WANG, H. 2011. Soil water characteristic curve measurement without bulk density changes and its implications in the estimation of soil hydraulic properties. Geoderma, 167–168, 1-8.

GALLERIES. 2014. The clay mineral group [Online]. http://www.galleries.com/clays_group. [Accessed 03-11- 2014].

GEO-SLOPE. 2013. Software tools for geotechnical solutions [Online]. http://www.geo-slope.com/. [Accessed 01-04- 2013].

GIKAS, V. & SAKELLARIOU, M. 2008. Settlement analysis of the Mornos earth dam (Greece): Evidence from numerical modeling and geodetic monitoring. Engineering Structures, 30, 3074-3081.

GOLAIT, Y. S. & WAKHARE, A. S. Unit Swell Potential Concept for Expansive Soils and its Simple Evaluation. Proceedings 8th Australia New Zealand Conference on Geomechanics, 1999 Barton. Australian Geomechanics Society, 171-177.

GOLDBERG, R. N. 1981. Evaluated activity and osmotic coefficients for aqueous solutions: thirty-six uni-bivalent electrolytes. Journal of Physical and Chemical Reference Data, 10, 671-764.

GOLDBERG, R. N. & NUTTALL, R. L. 1978. Evaluated activity and osmotic coefficients for aqueous solutions: The alkaline earth metal halides. Journal of Physical and Chemical Reference Data, 7, 263-310.

GRAY, C. W. & ALLBROOK, R. 2002. Relationships between shrinkage indices and soil properties in some New Zealand soils. Geoderma, 108, 287-299.

GUGGENHEIM, S. & MARTIN, R. T. 1995. Definition of clay and clay mineral. Journal report of the AIPEA nomenclature and CMS nomenclature committees. Clays and Clay Minerals.

HAMER, W. J. & WU, Y.-C. 1972. Osmotic Coefficients and Mean Activity Coefficients of Uni-univalent Electrolytes in Water at 25[degree]C. Journal of Physical and Chemical Reference Data, 1, 1047-1100.

HAMILTON, J. J. 1969. EFFECTS OF ENVIRONMENT ON THE PERFORMANCE OF SHALLOW FOUNDATIONS. Canadian Geotechnical Journal, 6, 65-80.

HANNAM, P. 2015. World headed for an El Nino and it could be a big one, scientists say [Online]. http://www.smh.com.au/environment/weather/world-headed-for-an-el-nino-and-it-could-be-a-big-one-scientists-say-20150507-ggw8bo.html. [Accessed 22-05- 2015].

http://www.galleries.com/clays_group

http://www.geo-slope.com/

http://www.smh.com.au/environment/weather/world-headed-for-an-el-nino-and-it-could-be-a-big-one-scientists-say-20150507-ggw8bo.html

http://www.smh.com.au/environment/weather/world-headed-for-an-el-nino-and-it-could-be-a-big-one-scientists-say-20150507-ggw8bo.html

279

HAZELTON, P. A. & MURPHY, B. W. 2007. Interpreting Soil Test Results: What Do All the Numbers Mean?, CSIRO Publishing.

HMA. 2013. Model 4700: Magnetic Extensometer [Online]. http://www.geotechsystems.com.au/products/s4000/4700.php. [Accessed 20-09- 2012].

HMA. 2014. Model 4000: Borehole Rod Extensometers [Online]. http://www.geotechsystems.com.au/products/s4000/4000.php. [Accessed 23-04- 2015].

HOLLAND, J. E. & LAWRANCE, C. E. 1980. Seasonal Heave of Austrahan Clay Soils. Proceedigns of 4th Intemational Conference on Expansive Soils. Denver, CO.

HOLLAND, J. E., PITT, W. G., LAWRANCE, C. E. & CIMINO, D. J. 1980. The Behavior and Design of Housing Slabs on Expansive Soils. Proceedigns of 4th Intemational Conference on Expansive Soils. Denver, CO.

HOLLAND., J. E. 1978. Residential Slab Research - Recent Findings, Swinburne College Press, Melbourne.

HOLLAND., J. E., CAMERON., D. A. & WASHUSEN., J. A. 1975. Residential Raft Slabs, Swinburne College of Technology, Hawthorn, Victoria.

HOLTZ, W. G. 1959. Expansive clays-properties and problems. Quarterly of the Colorado School of Mine, 54, 89-125.

HOLTZ, W. G. & GIBBS, H. J. 1956. Engineering properties of expansive clays. Transactions ASCE, 121, 641-677.

HUGHES, L. 2003. Climate change and Australia: Trends, projections and impacts. Austral Ecology, 28, 423–443.

HUNG, V. Q. 2002. Uncoupled and coupled solutions of volume change problems in expansive soils. PhD, University of Saskatchewan.

HUPET, F. & VANCLOOSTER, M. 2002. Intraseasonal dynamics of soil moisture variability within a small agricultural maize cropped field. Journal of Hydrology, 261, 86-101.

JENNINGS, J. E., FIRTH, R. A., RALPH, T. K. & NAGAR, N. 1973. An improved method for predicting heave using the oedometer test. Proceedings of the 3rd International Conference on Expansive Soils. Haifa, Israel.

JENNINGS, J. E. B. & KNIGHT, K. 1957. The Prediction of Total Heave From the Double Oedometer Test. Proc. Symposium on Expansive Clays. Johannesburg: South African Institute Civil Engineers.

JEWELL, S. A. & MITCHELL, P. W. 2009. The Thornthwaite Moisture Index and Seasonal Soil Movement in Adelaide. Australian Geomechanics Journal, 41, 59-68.

JONES, E. W., KOH, Y., TIVER, B. & WONG, M. 2009. Modelling the behaviour of unsaturated, saline clay for geotechnical design. School of Civil Environment and Mining Engineering,: University of Adelaide, Australia.

KARUNARATHNE, A. M. A. N., GAD, E. F., SIVANERUPAN, S. & WILSON, J. L. Review of Residential Footing Design on Expansive Soil in Australia. In: SAMALI, B., ATTARD, M. M. & SONG, C., eds. 22nd Australasian Conference on the Mechanics of Structures and Materials, 11-14 December 2012 Sydney, NSW. Taylor & Francis Group, 575-579.

KARUNARATHNE, A. M. A. N., GAD, E. F., SIVANERUPAN, S. & WILSON, J. L. 2013. Review of Residential Footing Design on Expansive Soil in Australia. In: SAMALI, B., ATTARD, M. M. & SONG, C. (eds.) 22nd Australasian

http://www.geotechsystems.com.au/products/s4000/4700.php

http://www.geotechsystems.com.au/products/s4000/4000.php

280

Conference on the Mechanics of Structures and Materials. Sydney: Taylor & Francis.

KARUNARATHNE, A. M. A. N., SIVANERUPAN, S., GAD, E. F., DISFANI, M. M., RAJEEV, P., WILSON, J. L. & LI, J. 2014. Field and laboratory investigation of an expansive soil site in Melbourne. Australian Geomechanics, 49, 85-93.

KAY, N. 1990. Use of the liquid limit for characterisation of expansive soils. Civil Engineering Transactions, Institution of Engineers, Australia., 32, 151-156.

KEIM, B. D. 2010. THE LASTING SCIENTIFIC IMPACT OF THE THORNTHWAITE WATER–BALANCE MODEL. Geographical Review, 100, 295-300.

KODIKARA, J., RAJEEV, P., CHAN, D. & GALLAGE, C. 2013. Soil moisture monitoring at the field scale using neutron probe. Canadian Geotechnical Journal, 51, 332-345.

KOVÁCS, G. 1981. Seepage Hydraulics. Developments in Water Science 10. Elsevier Science Publishers: Amsterdam.

KRAHN, J. & FREDLUND, D. G. 1972. On toatal, matric and osmotic suction. Soil Science, 114, 339-348.

LANG, A. 1967. Osmotic coefficients and water potentials of sodium chloride solutions from 0 to 40 0C. Australian Journal of Chemistry, 20, 2017-2023.

LEAO, S. & OSMAN, N. Y. TMI for urban resilience: Measuring and mapping long-term climate change effects on soil moisture. In: ROWLEY, S., ONG, R. & MARKKANEN, S., eds. 7th Australasian Housing Researchers’ Conference, 2013 Fremantle, WA, Australia

LEONG, E., HE, L. & RAHARDJO, H. 2002. Factors Affecting the Filter Paper Method for Total and Matric Suction Measurements. Geotechnical Testing Journal, 25, 322-333.

LEONG, E. C., TRIPATHY, S. & RAHARDJO., R. 2003. Total suction measurement of unsaturated soils with a device using the chilled-mirror dew-point technique. Geotechnique, 53, 173 –182

LI, J., SMITH, D., FITYUS, S. & SHENG, D. 2003a. Numerical Analysis of Neutron Moisture Probe Measurements. International Journal of Geomechanics, 3, 11-20.

LI, J., SMITH, D. W. & FITYUS, S. G. 2003b. The effect of a gap between the access tube and the soil during neutron probe measurements. Soil Research, 41, 151-164.

LI, J. & SUN, X. 2015. Evaluation of Changes of the Thornthwaite Moisture Index in Victoria. Australian Geomechanics, 50, 39-49.

LIKOS, W. J. 2000. Total suction-moisture content characteristics for expansive soils. Ph. D, Colorado School of Mines.

LIKOS, W. J. 2004. Measurement of crystalline swelling in expansive clay. Geotechnical Testing Journal, 27, 540-546.

LIU, G., NG, C. & WANG, Z. 2005. Observed Performance of a Deep Multistrutted Excavation in Shanghai Soft Clays. Journal of Geotechnical and Geoenvironmental Engineering, 131, 1004-1013.

LOPES, D., MCMANUS, K. J. & OSMAN, N. 2003. The effect of Thornthwaite Moisture Index changes on ground movements in expansive soils in Victoria, Australia. In: EFFERSON, I. & FROST, M. (eds.) Proceedings of the International Conference on Problematic Soils. Nottingham, England: CI-Premier

281

LOPES, D. & OSMAN, N. Y. 2010. Changes Of Thornthwaite's Total Moisture Indices In Victoria From 1948-2007 And The Effect On Seasonal Foundation Movements. Australian Geomechanics, 45, 37-48.

LOWE, P. R. 1977. An approximating polynomial for the computation of saturation vapour pressure. Journal of Applied Meteorology, 16, 100-103.

LU, N. & GRIFFITHS, D. 2004. Profiles of Steady-State Suction Stress in Unsaturated Soils. Journal of Geotechnical and Geoenvironmental Engineering, 130, 1063-1076.

LU, N. & KAYA, M. 2014. Power Law for Elastic Moduli of Unsaturated Soil. Journal of Geotechnical and Geoenvironmental Engineering, 140, 46-56.

LYTTON, R., AUBENY, C. & BULUT, R. 2004. Design Procedure for Pavements on Expansive Soils. FHWA/TX-05/0-4518-1 Vol. 1. Texas Transportation Institute: The Texas A&M University System.

LYTTON, R. L. 1970a. Analysis for Design of Foundations on Expansive Clay. Geomechanics Journal, 29-37.

LYTTON, R. L. 1970b. Design Criteria for Residential Slabs and Grillage Rafts on Reactive Clay. Melbourne, Australia: Division of Applied Mechanics, CSIRO.

LYTTON, R. L. & WOODBURN, J. A. 1985. Design and Performance of Mat Foundations on Expansive Clay. Golden Jubilee of the International Society for Soil Mechanics and Foundation Engineering: Commemorative Volume. Institution of Engineers, Australia.

MANN, A. 2003. The identification of road sections in Victoria displaying roughness caused by expansive soils. MSc, Swinburne University of Technology.

MAPS. 2015. Energy and Earth Resources - Earth resources online store [Online]. http://dpistore.efirst.com.au/categories.asp?cID=4. [Accessed 09-02- 2015].

MATHER, J. R. 1974. Climatology: fundamentals and applications, McGraw-Hill, USA.

MATHER, J. R. 1978. The climatic water budget in environmental analysis, Lexington, US, Lexington Books.

MATYAS, E. L. & RADHAKRISHNA, H. S. 1968. Volume Change Characteristics of Partially Saturated Soils. Geotechnique, 18, 432 –448.

MCKEEN, R. G. & JOHNSON, L. D. 1990. Climate-Controlled Soil Design Parameters for Mat Foundations. Journal of Geotechnical Engineering, 116, 1073-1094.

MCMANUS, K., LOPES, D. & OSMAN, N. Y. 2004. The Effect of Thronthwaite Moisture Index Changes on Ground Movement Predictions in Australian Soils. 9th Australia-New Zealand Conference on Geomechanics. Auckland.

MITCHELL, P. 1984a. A Simple Method of Design of Shallow Footings on Expansive Soil In: INSTITUTION OF ENGINEERS, A. A. G. S. S. A. G. (ed.) Fifth International Conference on Expansive Soils. Adelaide, South Australia: Barton, A.C.T. : The Institution.

MITCHELL, P. W. 1979. The Structural Analysis of Footings on Expansive Soil. Newton: Kenneth W.G. Smith & Associates.

MITCHELL, P. W. The Concepts Defining the Rate of Swell of Expansive Soils. 4th International Conference on Expansive Soils, 1980 Denver. 106-116.

MITCHELL, P. W. 1984b. The Design of Shallow Footings on Expansive Soil. University of Adelaide.

MITCHELL, P. W. 2008. Footing Design for Residential Type Structures in Arid Climates. Australian Geomechanics Journal, 43, 51-68.

http://dpistore.efirst.com.au/categories.asp?cID=4

282

MITCHELL, P. W. & AVALLE, D. L. 1984. A Technique to Predict Expansive Soil Movements. Fifth International Conference on Expansive Soils Adelaide, South Australia.

MORRIS, P. O. & GRAY, W. J. 1976. Moisture conditions under roads in the Australian environment. In: GRAY, W. J., NATIONAL ASSOCIATION OF AUSTRALIAN STATE ROAD AUTHORITIES, C., MAINTENANCE PRACTICES, C. & SYMPOSIUM ON SUB-SOIL, D. (eds.) Research report ARR ; no. 69. Vermont South, Vic: Australian Road Research Board.

MURPHY, B. F. & TIMBAL, B. 2008. A review of recent climate variability and climate change in southeastern Australia. International Journal of Climatology, 28, 859-879.

MURRAY, E. J. & SIVAKUMAR, V. 2010. Unsaturated Soils: A Fundamental Interpretation of Soil Behaviour, John Wiley & Sons.

NELSON, J. D., CHAO, K. C., OVERTON, D. D. & NELSON, E. J. 2015. Nature of Expansive Soils. Foundation Engineering for Expansive Soils. John Wiley & Sons, Inc.

NELSON, J. D. & MILLER, D. J. 1992. Expansive soils: problems and practice in foundation and pavement engineering, John Wiley & Sons Inc.

NELSON, J. D., OVERTON, D. D. & DURKEE, D. B. Depth of Wetting and the Active Zone. Shallow Foundation and Soil Properties Committee Sessions at ASCE Civil Engineering, 2001 Houston, Texas, United States. American Society of Civil Engineers, 95-109.

NELSON, J. D., OVERTON, D. O. & CHAO, K. C. 2003. Design of Foundations for Light Structures on Expansive Soils. California Geotechnical Engineers Association Annual Conference. Carmel, California.

NG, C. W. W. & MENZIES, B. 2007. Advanced Unsaturated Soil Mechanics and Engineering, London, Taylor and Francis.

NIXON, P. R. & LAWLESS, G. P. 1960. Detection of deeply penetrating rain water with neutron-scattering moisture meter. Transactions of the American Society of Agricultural Engineers, 3.

NWS. 2010. The Hydrologic Cycle [Online]. National Weather Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce.: http://www.srh.noaa.gov/jetstream/atmos/hydro.htm. [Accessed 05-10- 2012].

PENMAN, H. L. 1948. Natural Evaporation from Open Water, Bare Soil and Grass. Proceedings of the Royal Society of London - Series A, Mathematical and Physical Sciences, 193, 120-145.

PEREIRA, J. H. F. 1996. Numerical analysis of the mechanical behavior of collapsing earth dams during first reservoir filling. Ph.D, University of Saskatchewan.

PHILP, M. & TAYLOR, M. 2012. Beyond Agriculture - Exploring the application of the Thornthwaite Moisture Index to infrastructure and possibilities for climate change adaptation [Online]. http://www.nccarf.edu.au/settlements-infrastructure/content/beyond-agriculture-exploring-application-thornthwaite-moisture-index-infrastructure-and. [Accessed 13-01- 2014].

PITT, W. G. 1982. Correlation Between the Real Behaviour and the Theoretical Design of Residential Raft Slabs MEng, Swinburne Institute of Technology, Melbourne.

PTI 2004. Design of Post-tensioned Slabs-on-ground, Post Tensioning Institute. RAHARDJO, H. & LEONG, E. Suction Measurements. In: MILLER, G. A., ZAPATA,

C. E., HOUSTON, S. L. & FREDLUND, D. G., eds. Fourth International

http://www.srh.noaa.gov/jetstream/atmos/hydro.htm

http://www.nccarf.edu.au/settlements-infrastructure/content/beyond-agriculture-exploring-application-thornthwaite-moisture-index-infrastructure-and



283

Conference on Unsaturated Soils, April 2-6, 2006 Carefree, Arizona, United States. American Society of Civil Engineers, 81-104.

RAJEEV, P., CHAN, D. & KODIKARA, J. 2012. Ground–atmosphere interaction modelling for long-term prediction of soil moisture and temperature. Canadian Geotechnical Journal, 49, 1059-1073.

RAJEEV, P. & KODIKARA, J. 2011. Numerical analysis of an experimental pipe buried in swelling soil. Computers and Geotechnics, 38, 897-904.

RANGANATHAM, B. V. & SATYANARAYANA, B. 1965. A rational method of predicting swelling potential for compacted expansive clays. International Conference on Soil Mechanics and Foundation Engineering. Montrial, Canada.

REN, G. & LI, J. 2010. Monitoring In Situ Soil Moisture Variations of Expansive Clay Using Neutron Probes. Deep Foundations and Geotechnical In Situ Testing.

RICHARDS, B. G. 1965. Measurement of the Free Energy of Soil Moisture by the Psychrometric Technique Using Thermistors. In: AITCHISON, G. D. (ed.) Moisture Equilibria and Moisture Changes in Soils Beneath Covered Areas. Butterworths, Sydney.

RICHARDS, B. G., PETER, P. & EMERSON, W. W. 1983. The effects of vegetation on the swelling and shrinking of soils in Australia. Geotechnique, 33, 127–139.

RUSSAM, K. & COLEMAN, J. D. 1961. The Effect of Climatic Factors on Subgrade Moisture Conditions. Geotechnique, 3, 22-28.

SAMUELS, S. G. & CHENEY, J. E. Long-term heave of a building on clay due to tree removal. Proceedings of Conference on Settlement of Structures, 1975 Cambridge. Pentech Press, London 212-220.

SATTLER, P. J. & FREDLUND, D. G. 1991. Numerical modelling of vertical ground movements in expansive, soils. Canadian Geotechnical Journal, 28, 189-199.

SCHOFIELD, R. K. The pF of the Water in Soil. Transactions, 3 "d International Congress of Soil Science, 1935. 37-48.

SEED, H. B., WOODWARD, R. J. & LUNDGREN, R. 1962. Prediction of Swelling Potential for compacted clays. ASCE. Soil Mechanics and Foundation Division.

SHROFF, A. V. 2003. Soil Mechanics and Geotechnical Engineering, Taylor & Francis.

SKEMPTON, A. W. 1953. The colloidal “Activity” of clays. Proceedings of the 3rd International Conference of Soil Mechanics and Founda-tion Engineering.

SMITH, J. B., SCHNEIDER, S. H., OPPENHEIMER, M., YOHE, G. W., HARE, W., MASTRANDREA, M. D., PATWARDHAN, A., BURTON, I., CORFEE-MORLOT, J., MAGADZA, C. H. D., FÜSSEL, H.-M., PITTOCK, A. B., RAHMAN, A., SUAREZ, A. & VAN YPERSELE, J.-P. 2009. Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) “reasons for concern”. Proceedings of the National Academy of Sciences, 106, 4133-4137.

SMITH, R. 1993. Estimating soil movements in new Areas. Seminar - Extending the Code beyond Residential Slabs and Footings. The Institution of Engineers, Australia.

SRIDHARAN, A. 1999. Volume change behaviour of expansive soils. International Symposium on Problematic Soils. Sendai, Japan.

STATISTICS, A. B. O. 2012. GEOGRAPHIC DISTRIBUTION OF THE POPULATION [Online]. http://www.abs.gov.au/ausstats/[email protected]/Lookup/by%20Subject/1301.0~2012~

http://www.abs.gov.au/ausstats/[email protected]/Lookup/by%20Subject/1301.0~2012~Main%20Features~Geographic%20distribution%20of%20the%20population~49

284

Main%20Features~Geographic%20distribution%20of%20the%20population~49. [Accessed 01-09- 2012].

SVOFFICE. 2015. SVOffice 2009 Software - Soil vision [Online]. http://www.soilvision.com/subdomains/svoffice.com/. [Accessed 06-04- 2015].

TADANIER, R. & NGUYEN, V. 1984. Index Properties of Expansive Soils in New South Wales. Fifth International Conference on Expansive Soils. Adelaide, South Australia: Institution of Engineers Australia.

THE-AGE. 2011. Owners find homes are cracking under pressure [Online]. http://www.domain.com.au/news/owners-find-homes-are-cracking-under-pressure-20111221-1p5or/. [Accessed 27-02- 2012].

THE-AGE. 2014a. Thousands of suburban home owners facing financial ruin [Online]. http://www.theage.com.au/victoria/thousands-of-suburban-home-owners-facing-financial-ruin-20140607-39q4z.html. [Accessed 10-06- 2014].

THE-AGE. 2014b. When a dream home turns into a nightmare [Online]. http://www.theage.com.au/victoria/when-a-dream-home-turns-into-a-nightmare-20140607-39q50.html. [Accessed 21-07- 2014].

THOMAS, D. E. 1967. Geology of the Melbourne District, Victoria, Mines Department Melbourne, Victoria, Australia.

THORNTHWAITE, C. W. 1948. An Approach Toward a Rational Classification of Climate. Soil Science, 66, 77.

THORNTHWAITE, C. W. 1952. The water balance in arid and semiarid climates. Proceding of International Symposium on Desert research. Jerusalem: Research Council of Israel, Special Publication No. 2.

THORNTHWAITE, C. W. & MATHER, J. R. 1955. The Water Balance. Publications in Climatology. Centerton, New Jersey: Laboratory of Climatology, Drexel Institute of Technology.

THORNTHWAITE, C. W. & MATHER, J. R. 1957. Instructions and Tables for Computing Potential Evapotranspiration and the Water Balance. Publications in Climatology. Centerton, New Jersey: Laboratory of Climatology, Drexel Institute of Technology

TODD, D. K. 1980. Groundwater Hydrology, New York., John Wiley & Sons. TUCKER, B. M. 1955. SOME APPLICATIONS OF CLIMATIC ANALYSIS. In:

CSIRO (ed.) Division of Soils. Adelade: CSIRO. UMS. 2013. HYPROP - Laboratory evaporation method for the determination of pF-

curves and unsaturated conductivity [Online]. http://www.ums-muc.de/en/products/soil_laboratory/hyprop.html. [Accessed 08-29- 2013].

VADOSE 2013. Vadose Zone modeling with VADOSE/W, Calgary, Alberta, Canada, Geo-Slope International Ltd.

VAN GENUCHTEN, M. T. 1980. A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils. Soil Sci. Soc. Am. J., 44, 892-898.

VU, H. Q. & FREDLUND, D. G. 2004. The prediction of one-, two-, and three-dimensional heave in expansive soils. Canadian Geotechnical Journal, 41, 713-737.

WALSH, P. F. 1975. The Design of Residential Slabs on Ground. Division of Building Research, C.S.I.R.O. Melbourne, Australia.

WALSH, P. F. 1978. The Analysis of Stiffened Rafts on Expansive Clays. Division of Building Research, C.S.I.R.O. Melbourne, Australia.



http://www.soilvision.com/subdomains/svoffice.com/

http://www.domain.com.au/news/owners-find-homes-are-cracking-under-pressure-20111221-1p5or/

http://www.domain.com.au/news/owners-find-homes-are-cracking-under-pressure-20111221-1p5or/

http://www.theage.com.au/victoria/thousands-of-suburban-home-owners-facing-financial-ruin-20140607-39q4z.html

http://www.theage.com.au/victoria/thousands-of-suburban-home-owners-facing-financial-ruin-20140607-39q4z.html

http://www.theage.com.au/victoria/when-a-dream-home-turns-into-a-nightmare-20140607-39q50.html

http://www.theage.com.au/victoria/when-a-dream-home-turns-into-a-nightmare-20140607-39q50.html

http://www.ums-muc.de/en/products/soil_laboratory/hyprop.html

http://www.ums-muc.de/en/products/soil_laboratory/hyprop.html

285

WALSH, P. F. & CAMERON, D. A. 1997. The design of residential slabs and footings, Standards Australia.

WARD, A. L. & WITTMAN, R. S. 2009. Calibration of a neutron hydroprobe for moisture measurements in small diameter steel-cased boreholes. Pacific Northwest National Laboratory.

WASHUSEN, J. A. 1977. The Behaviour of Experimental Rafts Slabs on Expansive Clay Soils in the Melbourne Area. MEng, Swinburne College of Technology, Melbourne.

WAYLLACE, A. 2008. Volume change and swelling pressure of expansive clay in the crystalline swelling regime. PhD, University of Missouri.

WIJEYESEKERA, D. C., O'CONNOR, K. & SALMON, D. E. 2001. Design and performance of a compacted clay barrier through a landfill. Engineering Geology, 60, 295-305.

WILSON, G. W. 1990. Soil evaporative fluxes for geotechnical engineering problems. Ph.D, University of Saskatchewan.

WRAY, W. K. 1978. Development of a Design Procedure for Residential and Light Commercial Slabs-on-ground Constructed Over Expansive Soils. PhD, Texas A&M University.

WRAY, W. K. 1997. Using Soil Suction to Estimate Differential Soil Shrink or Heave. Proc. Unsaturated Soil Engineering Practice. Geotechnical Special Publication No. 68: ASCE.

WRAY, W. K. Mass transfer in Unsaturated Soils: A Review of Theory and Practices. Proceedings of the 2nd International Conference on Unsaturated Soils, 1998 Beijing, China. 99-155.

WRAY, W. K. 2005. Three-Dimensional Model for Moisture and Volume Changes Prediction in Expansive Soils. Journal of Geotechnical and Geoenvironmental Engineering, 131, 311-324.

YOSHIDA, R. T., FREDLUND, D. G. & HAMILTON, J. J. 1983. The prediction of total heave of a slab-on-grade floor on Regina clay. Canadian Geotechnical Journal, 20, 69-81.

ZASLAVSKY, D. & ROGOWSKI, A. S. 1969. Hydrologic and Morphologic Implications of Anisotropy and Infiltration in Soil Profile Development. Soil Science Society of America Journal, 33, 594-599.

A_1

10. APPENDICES

A: HYPROP MEASUREMENTS OF BRAYBROOK SOIL

Depth 0 – 0.3 meters

HYPROP TEST RESULTS SHEET

SITE: Braybrook DEPTH: 0-0.3 m

SAMPLE DATE : 1/05/2014 TEST DATE : 23/09/2014

INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 371.5 g

Hyprop data corrected data

Matric Suction

(pF)

Moisture content

from Hyprop

(%)

Water volume (cm3)


content (%)

Matric Suction

(kPa)

Corrected Volumetric moisture content

1.14 52.51 130.75 35.19 1.38 0.5012 1.16 52.50 130.72 35.18 1.44 0.5011 1.21 52.48 130.68 35.17 1.63 0.5010 1.22 52.51 130.75 35.19 1.67 0.5012 1.28 52.47 130.65 35.16 1.91 0.5009 1.33 52.44 130.58 35.15 2.16 0.5007 1.38 52.41 130.51 35.13 2.40 0.5006 1.43 52.37 130.41 35.10 2.71 0.5003 1.48 52.33 130.31 35.07 3.02 0.5001 1.51 52.29 130.20 35.04 3.21 0.4998 1.53 52.25 130.10 35.02 3.36 0.4995 1.54 52.20 129.97 34.98 3.50 0.4992 1.56 52.13 129.79 34.93 3.65 0.4988 1.58 52.06 129.62 34.89 3.81 0.4983 1.60 52.02 129.52 34.86 4.01 0.4981 1.63 51.98 129.42 34.83 4.24 0.4978 1.65 51.93 129.32 34.81 4.43 0.4976 1.66 51.89 129.21 34.78 4.59 0.4973 1.68 51.84 129.08 34.74 4.79 0.4969 1.70 51.80 128.98 34.71 4.98 0.4967 1.71 51.76 128.87 34.69 5.14 0.4964 1.73 51.70 128.74 34.65 5.33 0.4961 1.73 51.21 127.51 34.32 5.37 0.4929 1.75 51.66 128.64 34.62 5.56 0.4958 1.75 51.13 127.31 34.27 5.58 0.4924 1.77 51.59 128.47 34.58 5.82 0.4954 1.77 51.05 127.11 34.21 5.89 0.4919

A_2

1.78 51.29 127.72 34.38 6.01 0.4935 1.79 51.52 128.30 34.53 6.14 0.4950 1.80 50.95 126.87 34.15 6.27 0.4913 1.80 50.86 126.63 34.08 6.37 0.4907 1.81 51.44 128.09 34.48 6.47 0.4944 1.82 50.76 126.40 34.02 6.56 0.4901 1.83 51.37 127.92 34.43 6.73 0.4940 1.85 50.67 126.16 33.96 7.00 0.4894 1.86 50.57 125.92 33.89 7.24 0.4888 1.88 50.46 125.65 33.82 7.50 0.4881 1.89 50.35 125.38 33.75 7.69 0.4874 1.90 50.26 125.15 33.68 7.93 0.4868 1.91 50.17 124.91 33.62 8.15 0.4862 1.92 50.06 124.64 33.55 8.39 0.4855 1.93 49.95 124.37 33.48 8.61 0.4848 1.95 49.85 124.14 33.41 8.85 0.4841 1.96 49.75 123.87 33.34 9.10 0.4834 1.97 49.64 123.60 33.27 9.33 0.4827 1.98 49.53 123.33 33.20 9.57 0.4820 1.99 49.42 123.07 33.12 9.84 0.4813 2.01 49.30 122.76 33.04 10.12 0.4805 2.02 49.20 122.50 32.97 10.40 0.4798 2.03 49.07 122.20 32.89 10.69 0.4790 2.04 48.95 121.90 32.81 10.94 0.4782 2.05 48.83 121.60 32.73 11.22 0.4774 2.05 48.58 120.96 32.56 11.30 0.4757 2.06 48.71 121.30 32.65 11.40 0.4766 2.06 48.46 120.66 32.48 11.48 0.4748 2.08 48.34 120.36 32.40 12.08 0.4740 2.10 48.21 120.03 32.31 12.59 0.4731 2.12 48.06 119.67 32.21 13.06 0.4721 2.12 47.94 119.37 32.13 13.12 0.4713 2.13 47.81 119.04 32.04 13.46 0.4704 2.14 47.24 117.62 31.66 13.74 0.4665 2.15 47.66 118.67 31.94 14.19 0.4694 2.15 47.38 117.98 31.75 14.26 0.4675 2.16 47.51 118.31 31.84 14.45 0.4684 2.17 47.09 117.26 31.56 14.76 0.4655 2.22 46.95 116.90 31.46 16.71 0.4645 2.24 46.81 116.57 31.37 17.54 0.4636 2.26 46.67 116.21 31.28 18.24 0.4626 2.28 46.52 115.85 31.18 18.88 0.4615 2.29 46.37 115.45 31.07 19.50 0.4604 2.30 46.24 115.13 30.99 20.14 0.4595 2.32 46.09 114.77 30.89 20.70 0.4585 2.33 45.93 114.38 30.78 21.33 0.4574 2.33 45.78 113.98 30.68 21.63 0.4563 2.35 45.63 113.63 30.58 22.23 0.4553 2.37 45.48 113.24 30.48 23.28 0.4541 2.38 45.32 112.85 30.37 24.10 0.4530 2.40 45.18 112.49 30.28 24.95 0.4520

A_3

2.41 45.02 112.10 30.17 25.70 0.4509 2.42 44.85 111.68 30.06 26.49 0.4497 2.44 44.68 111.26 29.95 27.29 0.4485 2.45 44.51 110.84 29.83 28.12 0.4472 2.46 44.33 110.39 29.71 28.97 0.4459 2.48 44.15 109.94 29.59 29.92 0.4446 2.49 43.98 109.52 29.48 30.83 0.4434 2.50 43.80 109.07 29.36 31.77 0.4421 2.52 43.62 108.62 29.24 32.81 0.4407 2.53 43.46 108.21 29.12 33.81 0.4395 2.54 43.30 107.83 29.02 34.91 0.4384 2.56 43.14 107.41 28.91 36.06 0.4371 2.57 42.98 107.03 28.81 37.15 0.4360 2.58 42.82 106.61 28.70 38.28 0.4348 2.60 42.65 106.20 28.58 39.45 0.4335 2.61 42.47 105.76 28.46 40.74 0.4322 2.62 42.29 105.31 28.35 41.98 0.4308 2.64 42.12 104.87 28.23 43.35 0.4295 2.65 41.94 104.43 28.11 44.77 0.4282 2.67 41.77 104.02 28.00 46.34 0.4269 2.68 41.60 103.58 27.88 47.86 0.4256 2.69 41.42 103.14 27.76 49.55 0.4242

Depth 0.3 – 0.8 meters


SITE: Braybrook DEPTH: 0.5 m



Hyprop data Corrected data

Matric Suction

(pF)

Moisture content

from Hyprop

(%)

Water volume (cm3)


content (%)

Matric Suction

(kPa)


0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147

A_4

0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 1.82 51.43 128.06 36.67 6.64 0.5147 1.80 51.41 128.01 36.66 6.35 0.5145 1.76 51.39 127.96 36.64 5.70 0.5144 1.68 51.37 127.91 36.63 4.73 0.5143 1.51 51.36 127.89 36.62 3.25 0.5142 0.25 51.44 128.09 36.68 0.18 0.5147 1.50 51.31 127.76 36.59 3.14 0.5139 1.68 51.28 127.69 36.57 4.80 0.5137 1.78 51.26 127.64 36.55 5.96 0.5136 1.84 51.24 127.59 36.54 6.93 0.5134 1.89 51.20 127.49 36.51 7.78 0.5132 1.93 51.17 127.41 36.49 8.57 0.5130 1.97 51.14 127.34 36.47 9.29 0.5128 2.00 51.11 127.26 36.44 9.98 0.5126 2.03 51.07 127.16 36.42 10.67 0.5124 2.05 51.03 127.06 36.39 11.27 0.5121 2.07 51.00 126.99 36.37 11.86 0.5119 2.10 50.96 126.89 36.34 12.45 0.5117 2.12 50.93 126.82 36.32 13.12 0.5115 2.14 50.88 126.69 36.28 13.84 0.5111 2.16 50.83 126.57 36.24 14.35 0.5108 2.17 50.79 126.47 36.22 14.76 0.5106 2.18 50.75 126.37 36.19 15.21 0.5103 2.20 50.70 126.24 36.15 15.74 0.5100 2.21 50.65 126.12 36.12 16.14 0.5097 2.22 50.60 125.99 36.08 16.52 0.5093 2.23 50.55 125.87 36.05 16.94 0.5090 2.24 50.49 125.72 36.00 17.30 0.5086 2.25 50.43 125.57 35.96 17.66 0.5082 2.25 50.38 125.45 35.92 17.95 0.5079 2.26 50.32 125.30 35.88 18.20 0.5075 2.27 50.26 125.15 35.84 18.54 0.5071 2.28 50.21 125.02 35.80 18.97 0.5068 2.29 50.14 124.85 35.75 19.45 0.5064 2.30 50.08 124.70 35.71 19.91 0.5060 2.31 50.01 124.52 35.66 20.37 0.5055 2.32 49.95 124.38 35.62 20.80 0.5051 2.33 49.88 124.20 35.57 21.23 0.5046 2.34 49.81 124.03 35.52 21.68 0.5042 2.34 49.74 123.85 35.47 22.08 0.5037 2.35 49.66 123.65 35.41 22.54 0.5032 2.36 49.60 123.50 35.37 22.96 0.5028 2.37 49.53 123.33 35.32 23.44 0.5023 2.38 49.45 123.13 35.26 23.88 0.5018

A_5

2.39 49.37 122.93 35.20 24.38 0.5013 2.40 49.30 122.76 35.15 24.89 0.5008 2.40 49.22 122.56 35.10 25.35 0.5003 2.41 49.15 122.38 35.05 25.82 0.4998 2.42 49.07 122.18 34.99 26.24 0.4993 2.43 48.98 121.96 34.93 26.73 0.4987 2.43 48.90 121.76 34.87 27.16 0.4981 2.44 48.82 121.56 34.81 27.67 0.4976 2.45 48.74 121.36 34.75 28.18 0.4971 2.46 48.65 121.14 34.69 28.64 0.4965 2.47 48.57 120.94 34.63 29.17 0.4959 2.47 48.48 120.72 34.57 29.65 0.4953 2.48 48.39 120.49 34.50 30.20 0.4947 2.49 48.30 120.27 34.44 30.69 0.4941 2.50 48.20 120.02 34.37 31.26 0.4934 2.50 48.12 119.82 34.31 31.70 0.4929 2.51 48.03 119.59 34.25 32.21 0.4923 2.52 47.93 119.35 34.18 32.73 0.4916 2.52 47.85 119.15 34.12 33.19 0.4910 2.53 47.75 118.90 34.05 33.73 0.4903 2.54 47.66 118.67 33.98 34.36 0.4897 2.54 47.57 118.45 33.92 34.99 0.4891 2.55 47.47 118.20 33.85 35.73 0.4884 2.56 47.37 117.95 33.78 36.39 0.4877 2.57 47.27 117.70 33.71 37.07 0.4870 2.58 47.17 117.45 33.63 37.84 0.4863 2.59 47.07 117.20 33.56 38.55 0.4856 2.59 46.97 116.96 33.49 39.26 0.4849

2.601 46.87 116.71 33.42 39.90 0.4842 2.608 46.77 116.46 33.35 40.55 0.4835 2.616 46.67 116.21 33.28 41.30 0.4828 2.623 46.57 115.96 33.21 41.98 0.4821 2.631 46.48 115.74 33.14 42.76 0.4815 2.642 46.38 115.49 33.07 43.85 0.4808 2.654 46.28 115.24 33.00 45.08 0.4801 2.665 46.18 114.99 32.93 46.24 0.4794 2.676 46.08 114.74 32.86 47.42 0.4787 2.688 45.98 114.49 32.79 48.75 0.4780 2.701 45.88 114.24 32.72 50.23 0.4772 2.713 45.77 113.97 32.64 51.64 0.4765 2.725 45.67 113.72 32.57 53.09 0.4757 2.738 45.56 113.44 32.49 54.70 0.4750

A_6







Matric Suction

(pF)

Moisture content

from Hyprop

(%)

Water volume (cm3)


content (%)

Matric Suction

(kPa)


1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.77 52.91 131.75 38.09 5.82 0.5270 1.92 52.89 131.70 38.07 8.24 0.5268 2.00 52.87 131.65 38.06 10.07 0.5267 2.06 52.85 131.60 38.04 11.53 0.5266 2.10 52.83 131.55 38.03 12.47 0.5265 2.12 52.80 131.47 38.01 13.15 0.5263 2.14 52.78 131.42 37.99 13.71 0.5262 2.15 52.75 131.35 37.97 14.16 0.5260 2.16 52.72 131.27 37.95 14.52 0.5258 2.17 52.69 131.20 37.93 14.89 0.5256 2.18 52.66 131.12 37.91 15.21 0.5254 2.19 52.63 131.05 37.89 15.42 0.5253 2.19 52.59 130.95 37.86 15.35 0.5250 2.18 52.55 130.85 37.83 15.24 0.5248 2.19 52.51 130.75 37.80 15.35 0.5245 2.19 52.48 130.68 37.78 15.49 0.5243 2.20 52.43 130.55 37.74 15.67 0.5240 2.20 52.38 130.43 37.71 15.92 0.5237 2.21 52.35 130.35 37.68 16.26 0.5235 2.22 52.30 130.23 37.65 16.60 0.5232 2.23 52.24 130.08 37.61 16.83 0.5228 2.23 52.19 129.95 37.57 17.14 0.5225

A_7

2.24 52.14 129.83 37.53 17.50 0.5222 2.25 52.09 129.70 37.50 17.86 0.5219 2.27 52.04 129.58 37.46 18.54 0.5216 2.29 51.98 129.43 37.42 19.28 0.5212 2.30 51.92 129.28 37.38 19.86 0.5208 2.31 51.87 129.16 37.34 20.28 0.5205 2.31 51.81 129.01 37.30 20.61 0.5202 2.32 51.73 128.81 37.24 20.94 0.5196 2.33 51.67 128.66 37.20 21.28 0.5193 2.33 51.61 128.51 37.15 21.53 0.5189 2.34 51.55 128.36 37.11 21.88 0.5185 2.35 51.48 128.19 37.06 22.18 0.5181 2.35 51.41 128.01 37.01 22.44 0.5176 2.36 51.33 127.81 36.95 22.86 0.5171 2.37 51.27 127.66 36.91 23.23 0.5167 2.37 51.19 127.46 36.85 23.55 0.5162 2.38 51.11 127.26 36.79 23.93 0.5157 2.39 51.04 127.09 36.74 24.38 0.5153 2.40 50.96 126.89 36.68 24.89 0.5148 2.40 50.89 126.72 36.63 25.35 0.5143 2.41 50.81 126.52 36.58 25.88 0.5138 2.42 50.73 126.32 36.52 26.42 0.5133 2.43 50.65 126.12 36.46 26.98 0.5128 2.44 50.56 125.89 36.40 27.54 0.5122 2.45 50.48 125.70 36.34 28.12 0.5117 2.46 50.40 125.50 36.28 28.58 0.5112 2.46 50.31 125.27 36.22 28.51 0.5106 2.45 50.22 125.05 36.15 27.99 0.5100 2.45 50.13 124.82 36.09 27.93 0.5094 2.45 50.04 124.60 36.02 28.05 0.5088 2.45 49.94 124.35 35.95 28.38 0.5082 2.46 49.84 124.10 35.88 29.04 0.5075 2.47 49.74 123.85 35.81 29.72 0.5068 2.48 49.64 123.60 35.73 30.41 0.5062 2.49 49.54 123.35 35.66 31.12 0.5055 2.50 49.45 123.13 35.60 31.84 0.5049 2.52 49.35 122.88 35.53 32.73 0.5043 2.52 49.25 122.63 35.45 33.42 0.5036 2.53 49.15 122.38 35.38 34.04 0.5029 2.54 49.05 122.13 35.31 34.43 0.5023 2.54 48.95 121.89 35.24 34.83 0.5016 2.55 48.85 121.64 35.17 35.65 0.5009 2.56 48.75 121.39 35.09 36.48 0.5003 2.57 48.65 121.14 35.02 37.33 0.4996 2.58 48.55 120.89 34.95 38.19 0.4989 2.59 48.45 120.64 34.88 39.08 0.4982 2.60 48.34 120.37 34.80 39.90 0.4975 2.61 48.23 120.09 34.72 40.74 0.4967 2.62 48.12 119.82 34.64 41.30 0.4960 2.62 48.01 119.54 34.56 41.21 0.4952 2.62 47.90 119.27 34.48 41.30 0.4945

A_8

2.62 47.80 119.02 34.41 41.88 0.4938 2.63 47.69 118.75 34.33 42.46 0.4930 2.63 47.60 118.52 34.27 42.95 0.4924 2.64 47.51 118.30 34.20 43.55 0.4918

2.648 47.42 118.08 34.14 44.46 0.4912 2.657 47.32 117.83 34.06 45.39 0.4905 2.666 47.23 117.60 34.00 46.34 0.4899 2.677 47.13 117.35 33.93 47.53 0.4892 2.687 47.04 117.13 33.86 48.64 0.4885 2.698 46.95 116.91 33.80 49.89 0.4879 2.708 46.86 116.68 33.73 51.05 0.4873 2.719 46.76 116.43 33.66 52.36 0.4866

2.73 46.67 116.21 33.60 53.70 0.4860 2.742 46.58 115.98 33.53 55.21 0.4853 2.752 46.48 115.74 33.46 56.49 0.4846 2.763 46.39 115.51 33.39 57.94 0.4840 2.774 46.3 115.29 33.33 59.43 0.4833 2.788 46.2 115.04 33.26 61.38 0.4826







Matric Suction

(pF)

Moisture content

from Hyprop

(%)

Water volume (cm3)


content (%)

Matric Suction

(kPa)


1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.60 52.44 130.58 37.65 3.94 0.5232 1.79 52.42 130.53 37.64 6.17 0.5231 1.89 52.41 130.50 37.63 7.83 0.5230 1.96 52.40 130.48 37.62 9.10 0.5230 2.00 52.39 130.45 37.62 10.09 0.5229 2.04 52.38 130.43 37.61 10.86 0.5229 2.06 52.36 130.38 37.59 11.51 0.5227 2.08 52.35 130.35 37.59 11.99 0.5227

A_9

2.09 52.33 130.30 37.57 12.42 0.5226 2.11 52.31 130.25 37.56 12.79 0.5224 2.12 52.28 130.18 37.54 13.03 0.5222 2.12 52.26 130.13 37.52 13.15 0.5221 2.12 52.23 130.05 37.50 13.27 0.5219 2.13 52.20 129.98 37.48 13.40 0.5217 2.13 52.17 129.90 37.46 13.49 0.5216 2.13 52.14 129.83 37.44 13.61 0.5214 2.14 52.11 129.75 37.41 13.87 0.5212 2.15 52.08 129.68 37.39 14.09 0.5210 2.15 52.05 129.60 37.37 14.26 0.5208 2.16 52.01 129.50 37.34 14.29 0.5206 2.15 51.97 129.41 37.31 14.16 0.5203 2.15 51.94 129.33 37.29 14.06 0.5201 2.15 51.90 129.23 37.26 14.16 0.5199 2.16 51.86 129.13 37.24 14.45 0.5196 2.17 51.82 129.03 37.21 14.89 0.5194 2.19 51.77 128.91 37.17 15.38 0.5191 2.20 51.73 128.81 37.14 15.85 0.5188 2.22 51.68 128.68 37.11 16.41 0.5185 2.23 51.63 128.56 37.07 16.98 0.5182 2.24 51.58 128.43 37.03 17.46 0.5179 2.25 51.53 128.31 37.00 17.91 0.5175 2.26 51.47 128.16 36.96 18.32 0.5172 2.27 51.42 128.04 36.92 18.71 0.5168 2.28 51.36 127.89 36.88 19.14 0.5165 2.29 51.31 127.76 36.84 19.68 0.5161 2.31 51.25 127.61 36.80 20.28 0.5158 2.32 51.18 127.44 36.75 20.84 0.5153 2.33 51.13 127.31 36.71 21.33 0.5150 2.34 51.07 127.16 36.67 21.73 0.5146 2.34 51.00 126.99 36.62 22.03 0.5142 2.35 50.93 126.82 36.57 22.39 0.5137 2.36 50.86 126.64 36.52 22.70 0.5133 2.36 50.79 126.47 36.47 22.96 0.5128 2.37 50.72 126.29 36.42 23.28 0.5124 2.37 50.65 126.12 36.37 23.55 0.5119 2.38 50.57 125.92 36.31 23.88 0.5114 2.38 50.50 125.75 36.26 24.21 0.5109 2.39 50.42 125.55 36.20 24.55 0.5104 2.40 50.34 125.35 36.14 24.89 0.5099 2.40 50.27 125.17 36.09 25.23 0.5095 2.41 50.19 124.97 36.04 25.53 0.5089 2.41 50.11 124.77 35.98 25.88 0.5084 2.42 50.03 124.57 35.92 26.30 0.5079 2.43 49.94 124.35 35.86 26.67 0.5073 2.43 49.86 124.15 35.80 27.16 0.5068 2.44 49.77 123.93 35.73 27.61 0.5062 2.45 49.68 123.70 35.67 27.99 0.5056 2.45 49.60 123.50 35.61 28.44 0.5051 2.46 49.51 123.28 35.55 28.91 0.5045

A_10

2.47 49.43 123.08 35.49 29.38 0.5039 2.48 49.34 122.86 35.43 29.92 0.5033 2.48 49.25 122.63 35.36 30.41 0.5027 2.49 49.16 122.41 35.30 30.97 0.5021 2.50 49.07 122.18 35.23 31.55 0.5015 2.51 48.98 121.96 35.17 32.14 0.5009 2.52 48.90 121.76 35.11 32.73 0.5004 2.52 48.81 121.54 35.05 33.34 0.4998 2.53 48.72 121.31 34.98 34.04 0.4992 2.54 48.63 121.09 34.92 34.75 0.4986 2.55 48.53 120.84 34.84 35.56 0.4979 2.56 48.44 120.62 34.78 36.31 0.4973 2.57 48.34 120.37 34.71 37.15 0.4966 2.58 48.24 120.12 34.64 38.02 0.4960 2.59 48.14 119.87 34.56 38.90 0.4953 2.60 48.03 119.59 34.49 39.90 0.4945 2.61 47.93 119.35 34.41 40.93 0.4938 2.62 47.82 119.07 34.33 41.88 0.4931 2.63 47.73 118.85 34.27 42.85 0.4925 2.64 47.63 118.60 34.20 43.85 0.4918 2.65 47.53 118.35 34.13 44.98 0.4911 2.66 47.43 118.10 34.05 45.81 0.4904 2.67 47.34 117.88 33.99 46.77 0.4898

2.682 47.25 117.65 33.93 48.08 0.4891 2.694 47.15 117.40 33.85 49.43 0.4885 2.706 47.06 117.18 33.79 50.82 0.4878 2.719 46.96 116.93 33.72 52.36 0.4871 2.733 46.86 116.68 33.65 54.08 0.4864 2.746 46.76 116.43 33.57 55.72 0.4857

2.76 46.66 116.18 33.50 57.54 0.4850 2.774 46.56 115.93 33.43 59.43 0.4843 2.788 46.46 115.69 33.36 61.38 0.4836 2.802 46.36 115.44 33.29 63.39 0.4829 2.817 46.25 115.16 33.21 65.61 0.4821 2.832 46.14 114.89 33.13 67.92 0.4814 2.847 46.04 114.64 33.06 70.31 0.4806

A_11







Matric Suction

(pF)

Moisture content

from Hyprop

(%)

Water volume (cm3)


content (%)

Matric Suction

(kPa)


1.47 47.52 118.33 35.86808 2.94 0.5074 1.60 47.51 118.31 35.86 3.94 0.5074 1.89 47.51 118.29 35.86 7.82 0.5073 2.00 47.51 118.29 35.86 9.89 0.5073 2.04 47.50 118.28 35.85 11.07 0.5073 2.07 47.49 118.26 35.85 11.72 0.5072 2.08 47.49 118.24 35.84 12.11 0.5072 2.09 47.48 118.23 35.84 12.42 0.5071 2.10 47.42 118.07 35.79 12.56 0.5067 2.11 47.46 118.17 35.82 12.74 0.5070 2.11 47.47 118.19 35.83 12.76 0.5070 2.12 47.39 118.00 35.77 13.06 0.5065 2.13 47.38 117.97 35.76 13.34 0.5064 2.13 47.36 117.93 35.75 13.58 0.5063 2.14 47.35 117.90 35.74 13.87 0.5062 2.15 47.33 117.85 35.72 14.16 0.5061 2.16 47.31 117.80 35.71 14.42 0.5059 2.17 47.29 117.76 35.70 14.69 0.5058 2.17 47.27 117.71 35.68 14.96 0.5057 2.18 47.25 117.66 35.67 15.24 0.5055 2.19 47.23 117.61 35.65 15.56 0.5054 2.20 47.21 117.56 35.63 15.85 0.5053 2.21 47.19 117.50 35.62 16.18 0.5051 2.22 47.16 117.43 35.60 16.48 0.5049 2.23 47.14 117.38 35.58 16.83 0.5048 2.23 47.11 117.31 35.56 17.14 0.5046 2.24 47.09 117.24 35.54 17.50 0.5044 2.25 47.06 117.17 35.52 17.86 0.5042 2.26 47.02 117.09 35.49 18.20 0.5040 2.27 47.00 117.02 35.47 18.58 0.5038 2.28 46.96 116.93 35.44 18.97 0.5035

A_12

2.29 46.93 116.86 35.42 19.32 0.5033 2.29 46.90 116.77 35.40 19.68 0.5031 2.30 46.86 116.69 35.37 20.09 0.5028 2.31 46.83 116.62 35.35 20.46 0.5026 2.32 46.80 116.53 35.32 20.84 0.5024 2.33 46.76 116.44 35.30 21.23 0.5021 2.34 46.72 116.34 35.26 21.63 0.5018 2.34 46.69 116.25 35.24 22.03 0.5016 2.35 46.64 116.14 35.21 22.44 0.5013 2.36 46.61 116.06 35.18 22.86 0.5011 2.37 46.57 115.95 35.15 23.28 0.5008 2.37 46.52 115.84 35.11 23.71 0.5005 2.38 46.48 115.74 35.08 24.15 0.5002 2.39 46.43 115.61 35.05 24.60 0.4998 2.40 46.39 115.51 35.01 25.06 0.4995 2.41 46.34 115.38 34.98 25.59 0.4991 2.42 46.28 115.24 34.93 26.12 0.4987 2.43 46.22 115.10 34.89 26.67 0.4983 2.43 46.17 114.96 34.85 27.16 0.4979 2.44 46.12 114.83 34.81 27.67 0.4976 2.45 46.05 114.67 34.76 28.18 0.4971 2.46 45.99 114.53 34.72 28.71 0.4967 2.47 45.94 114.38 34.67 29.31 0.4963 2.48 45.88 114.24 34.63 29.92 0.4959 2.48 45.82 114.09 34.58 30.48 0.4955 2.49 45.76 113.93 34.54 30.97 0.4950 2.50 45.70 113.79 34.49 31.55 0.4946 2.51 45.64 113.64 34.45 32.14 0.4942 2.51 45.57 113.48 34.40 32.73 0.4937 2.52 45.50 113.30 34.34 33.34 0.4932 2.53 45.44 113.15 34.30 33.96 0.4927 2.54 45.38 112.99 34.25 34.59 0.4923 2.55 45.30 112.81 34.19 35.32 0.4917 2.56 45.24 112.64 34.14 36.06 0.4913 2.57 45.17 112.48 34.09 36.81 0.4908 2.57 45.10 112.29 34.04 37.58 0.4902 2.58 45.02 112.11 33.98 38.37 0.4897 2.59 44.95 111.92 33.93 39.17 0.4892 2.60 44.87 111.74 33.87 39.99 0.4886 2.61 44.79 111.53 33.81 40.93 0.4880 2.62 44.71 111.33 33.75 41.88 0.4874 2.63 44.63 111.12 33.68 42.85 0.4868 2.64 44.55 110.92 33.62 43.85 0.4862 2.65 44.47 110.73 33.57 44.87 0.4857 2.66 44.38 110.51 33.50 46.03 0.4850 2.67 44.29 110.28 33.43 47.10 0.4843 2.68 44.20 110.06 33.36 48.31 0.4836 2.70 44.11 109.83 33.29 49.55 0.4830 2.71 44.03 109.62 33.23 50.93 0.4824 2.72 43.93 109.40 33.16 52.24 0.4817 2.73 43.84 109.17 33.09 53.70 0.4810

A_13

2.74 43.75 108.94 33.02 55.34 0.4803 2.76 43.66 108.71 32.95 56.89 0.4796 2.77 43.56 108.46 32.88 58.75 0.4789 2.78 43.46 108.21 32.80 60.67 0.4781

B_1

B: WP4C MEASUREMENTS OF BRAYBROOK SOIL

Depth 0 – 0.3 meters

WP4C TEST RESULTS SHEET

SITE: Braybrook DEPTH: 0-0.3 m


GMC Total

Suction (pF)


Matric suction (Kpa)

VMC

0.2241 4.23 700.00

998.24 0.36 0.1866 4.38 1698.83 0.31 0.0864 5.89 76924.71 0.16





GMC Total

Suction (pF)



VMC

0.2090 4.59 3190.45 0.3387 0.1607 4.89 7062.47 0.2734 0.1583 5.09 11602.69 0.2700 0.1352 5.18 14435.61 0.2367 0.1344 5.26 700 17497.01 0.2355 0.1186 5.44 26842.29 0.2118 0.1110 5.56 35607.81 0.2001 0.1106 5.60 39110.72 0.1995 0.0978 5.75 55534.13 0.1793 0.0917 5.95 88425.09 0.1695

B_2





GMC Total

Suction (pF)



VMC

0.2090 4.59 2790.45 0.3387 0.2167 4.62 3068.69 0.3487 0.1920 4.76 4654.40 0.3163 0.1883 4.80 5209.57 0.3114 0.1879 4.86 1100 6144.36 0.3108 0.1607 4.89 6662.47 0.2734 0.1583 5.09 11202.69 0.2700 0.1352 5.18 14035.61 0.2367 0.1344 5.26 17097.01 0.2355 0.1186 5.44 26442.29 0.2118 0.1110 5.56 35207.81 0.2001 0.1106 5.60 38710.72 0.1995 0.0978 5.75 55134.13 0.1793 0.0921 5.95 88025.09 0.1701

B_3





GMC Total

Suction (pF)



VMC

0.2494 4.28 805.46 0.3896 0.2480 4.32 989.30 0.3880 0.2494 4.34 1087.76 0.3896 0.2387 4.35 1100 1138.72 0.3765 0.2413 4.39 1354.71 0.3796 0.2309 4.42 1530.27 0.3667 0.1903 4.71 4028.61 0.3140 0.1438 5.16 13354.4 0.2493 0.1093 5.56 35207.81 0.1975





GMC Total

Suction (pF)



VMC

0.23 4.58

2500

1301.89 0.37 0.21 4.68 2286.30 0.34 0.27 4.49 590.30 0.41 0.24 4.59 1390.45 0.37 0.11 5.65 45173.68 0.18

C_1

C: FILTER PAPER SUCTION MEASUREMENTS OF BRAYBROOK SOIL


FILTER PAPER TEST RESULTS SHEET

SITE: Braybrook

DEPTH: 0.5 m TEST NO: 1

Test Started: 15/07/2014 Test Finished: 7/08/2014

Moisture content of the sample (%) 23.01 VMC 0.3669

Suction type

Cold tare

mass (g)

Cold tare + wet filter paper (g)

Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])

Suction converted into kPa

Total 25.4049 25.5658 25.5296 25.401 25.12 3.37 2346.46 Matric 13.7186 13.8282 13.8012 13.715 27.15 3.21 1630.47 Osmotic suction (kPa) 716

DEPTH: 0.5 m

TEST NO: 2



Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])



C_2

DEPTH: 0.5 m TEST NO: 3

Test Started: 27/06/2014 Test Finished: 14/07/2014 Moisture content of the sample (%) 29.05 VMC 0.4387

Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])





SITE: Braybrook

DEPTH: 1.0-1.5 m

TEST NO: 1



Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])



C_3



SITE: Braybrook

DEPTH: 1.5-2.0 m

TEST NO: 1



Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])


Total 13.9589 14.118 14.0846 13.9534 21.27 3.67 4682.07 Matric 13.5377 13.699 13.6604 13.5314 25.04 3.38 2379.47 Osmotic suction (kPa) 2302.59

DEPTH: 1.5-2.0 m

TEST NO: 2


Moisture content of the sample(%) 23.15 VMC 0.3687

Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])



C_4

DEPTH: 1.5-2.0 m

TEST NO: 3


Moisture content of the sample(%) 23.45 VMC 0.3725

Suction type

Cold tare

mass (g)


Hot tare +

dry filter paper

(g)

Hot tare

mass (g)

Filter paper water

content (%)

Suction from

standard ASTM D5298

(log[kPa])



D_1

D: SATURATED HYDRAULIC CONDUCTIVITY MEASUREMENTS OF BRAYBROOK SOIL


Type of Material Undisturbed clay soil Depth (m) 0.0-0.4 Location Braybrook Date Sampled 24/07/2014 Tested by Aruna Karunarathne Date Tested 30/10/2014

Material Specification Saturation Duration 24 hrs

Curing Duration 24 hrs

Sample Diameter (mm) 50.00

Reading Duration 48 hrs Water Temperature 20 (°C) Sample Area (cm2) 19.63

Epoxy Curing 24 hrs Flow direction Downward Sample height (cm) 10.60 Water density at test temperature (gr/cm3) 0.9982071

Readings

No Time after starting test (sec)

Reading Q (cm3)

Time (sec)

q (cm3/sec)

Top Pressure (kPa)


Δ h (cm) i=Δh/L k

(m/sec) k (m/day)

1 90000 127.94 13.59 3600 0.0037736 410.4 407.9 24.48 2.31 8.32E-07 7.19E-02 2 93600 141.52 12.44 3600 0.003455 410.4 407.9 24.48 2.31 7.62E-07 6.58E-02 3 97200 153.96 12.58 3600 0.0034942 410.4 407.9 24.48 2.31 7.71E-07 6.66E-02 4 100800 166.54 12.35 3600 0.0034292 410.4 407.9 24.48 2.31 7.56E-07 6.53E-02 6 104400 178.88 12.15 3600 0.0033747 410.4 407.9 24.48 2.31 7.44E-07 6.43E-02 7 108000 191.03 3600 410.4 407.9 24.48 2.31

Average value 7.73E-07 6.68E-02

D_2








Readings


Reading Q (cm3)

Time (sec)

q (cm3/sec)

Top Pressure (kPa)


Δ h (cm) i=Δh/L k (m/sec) k

(m/day)

1 7200 2.41 0.878 1800 0.0004878 535 533 19.58 2.062 1.21E-07 1.04E-02 2 9000 3.288 0.937 1800 0.0005206 535 533 19.58 2.062 1.29E-07 1.11E-02 3 10800 4.225 1.039 1800 0.0005772 535 533 19.58 2.062 1.43E-07 1.23E-02 4 12600 5.264 1.248 1800 0.0006933 535 533 19.58 2.062 1.71E-07 1.48E-02 5 14400 6.512 1.317 1800 0.0007317 535 533 19.58 2.062 1.81E-07 1.56E-02 6 16200 7.829 1.32 1800 0.0007333 535 533 19.58 2.062 1.81E-07 1.57E-02 7 18000 9.149 1.276 1800 0.0007089 535 533 19.58 2.062 1.75E-07 1.51E-02 8 19800 10.425 1800 535 533 19.58 2.062


D_3








Readings


Reading Q (cm3)

Time (sec)

q (cm3/sec)

Top Pressure (kPa)


Δ h (cm) i=Δh/L k (m/sec) k (m/day)

1 39600 0.821 0.025 1800 1.389E-05 520 518 19.58 2.201 3.21E-09 2.78E-04 2 41400 0.846 0.027 1800 0.000015 520 518 19.58 2.201 3.47E-09 3.00E-04 3 43200 0.873 0.027 1800 0.000015 520 518 19.58 2.201 3.47E-09 3.00E-04 4 45000 0.9 0.025 1800 1.389E-05 520 518 19.58 2.201 3.21E-09 2.78E-04 5 46800 0.925 0.026 1801 1.444E-05 520 518 19.58 2.201 3.34E-09 2.89E-04 6 48600 0.951 0.03 1800 1.667E-05 520 518 19.58 2.201 3.86E-09 3.33E-04 7 50400 0.981 1800 520 518 19.58 2.201


D_4








Readings


Reading Q (cm3)

Time (sec)

q (cm3/sec)

Top Pressure (kPa)


Δ h (cm) i=Δh/L k (m/sec) k (m/day)

1 97200 2.870 0.069 3600 1.916E-05 408.0 405.5 24.48102913 2.185806172 4.47E-09 3.86E-04 2 100800 2.939 0.022 3600 6.111E-06 408.0 405.5 24.48102913 2.185806172 1.42E-09 1.23E-04 3 104400 2.961 0.021 3600 5.833E-06 408.0 405.5 24.48102913 2.185806172 1.36E-09 1.17E-04 4 108000 2.982 0.019 3600 5.278E-06 408.0 405.5 24.48102913 2.185806172 1.23E-09 1.06E-04 5 111600 3.001 0.023 3600 6.389E-06 408.0 405.5 24.48102913 2.185806172 1.49E-09 1.29E-04 6 115200 3.024 3600 408.0 405.5 24.48102913 2.185806172


E_1

E: MODEL CALIBRATION DATA

ACTUAL MEASUREMENTS

Location CN1 – Volumetric moisture contents from Neutron probe

Depth from GL (m)

CN1 10/04/2

013

CN1 20/06/2

013

CN1 21/08/2

013

CN1 21/10/2

013

CN1 11/12/2

013

CN1 29/01/2

014

CN1 26/02/2

014

CN1 1/04/20

14

CN1 1/05/20

14

CN1 5/06/20

14

CN1 8/07/20

14

CN1 12/11/2

014

CN1 25/03/2

015

-0.35 0.33 0.41 0.43 0.44 0.43 0.30 0.28 0.27 0.36 0.36 0.37 0.34 0.35 -0.6 0.34 0.39 0.42 0.41 0.41 0.35 0.34 0.32 0.33 0.33 0.33 0.35 0.35 -0.85 0.36 0.36 0.38 0.38 0.38 0.37 0.36 0.35 0.35 0.34 0.34 0.34 0.35 -1.1 0.34 0.34 0.35 0.34 0.35 0.35 0.35 0.35 0.34 0.34 0.34 0.34 0.35 -1.35 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 -1.6 0.37 0.36 0.36 0.37 0.37 0.36 0.37 0.36 0.36 0.36 0.36 0.36 0.37 -1.85 0.37 0.36 0.36 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.36 -2.1 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 -2.35 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 -2.6 0.37 0.38 0.37 0.37 0.38 0.37 0.38 0.37 0.37 0.37 0.37 0.38 0.38 -2.85 0.37 0.38 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.37 0.37 0.38 0.38

E_2

Location CN2– Volumetric moisture contents from Neutron probe

Depth from GL (m)

CN2 10/04/2

013

CN2 20/06/2

013

CN2 21/08/2

013

CN2 21/10/2

013

CN2 11/12/2

013

CN2 29/01/2

014

CN2 26/02/2

014

CN2 1/04/20

14

CN2 1/05/20

14

CN2 5/06/20

14

CN2 8/07/20

14

CN2 12/11/2

014

CN2 25/03/2

015

10/04/2013

20/06/2013

21/08/2013

21/10/2013

11/12/2013

29/01/2014

26/02/2014

1/04/2014

1/05/2014

5/06/2014

8/07/2014

12/11/2014

25/03/2015

-0.35 0.33 0.32 0.36 0.36 0.36 0.22 0.21 0.21 0.27 0.27 0.28 0.24 0.29 -0.6 0.33 0.37 0.39 0.40 0.40 0.34 0.33 0.33 0.34 0.34 0.34 0.37 0.38 -0.85 0.36 0.37 0.40 0.40 0.40 0.38 0.35 0.34 0.36 0.36 0.36 0.38 0.38 -1.1 0.37 0.35 0.40 0.35 0.36 0.36 0.35 0.35 0.35 0.36 0.35 0.36 0.36 -1.35 0.37 0.36 0.35 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37 -1.6 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37 -1.85 0.38 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.38 0.37 0.38 0.38 -2.1 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37 0.38 0.38 -2.35 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37 0.38 0.38 -2.6 0.38 0.37 0.37 0.37 0.38 0.38 0.37 0.37 0.38 0.38 0.37 0.39 0.39 -2.85 0.38 0.37 0.38 0.37 0.38 0.38 0.37 0.37 0.38 0.38 0.37 0.39 0.39

E_3

Average of locations CN1 and CN2– Volumetric moisture contents from Neutron probe

Depth from GL (m)

10/04/2013

20/06/2013

21/08/2013

21/10/2013

11/12/2013

29/01/2014

26/02/2014

1/04/2014

1/05/2014

5/06/2014

8/07/2014

12/11/2014

25/03/2015

-0.35 0.33 0.36 0.39 0.40 0.39 0.26 0.25 0.24 0.32 0.31 0.32 0.29 0.32 -0.6 0.33 0.38 0.40 0.41 0.41 0.34 0.33 0.33 0.34 0.34 0.34 0.36 0.37

-0.85 0.36 0.37 0.39 0.39 0.39 0.38 0.35 0.35 0.35 0.35 0.35 0.36 0.36 -1.1 0.35 0.34 0.37 0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.34 0.35 0.35

-1.35 0.37 0.36 0.35 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 -1.6 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37

-1.85 0.37 0.36 0.36 0.37 0.36 0.36 0.36 0.36 0.37 0.37 0.37 0.37 0.37 -2.1 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37

-2.35 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.38 -2.6 0.38 0.38 0.37 0.37 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.38 0.38

-2.85 0.38 0.38 0.38 0.37 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.38 0.38

E_4

MODEL PREDICTIONS – Volumetric moisture contents

Y (m) Model

10/04/2013

Model 20/06/2

013

Model 21/08/2

013

Model 21/10/2

013

Model 11/12/2

013

Model 29/01/2

014

Model 26/02/2

014

Model 01/04/2

014

Model 01/05/2

014

Model 05/06/2

014

Model 08/07/2

014

Model 12/11/2

014

Model 25/03/2

015

-4.00 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.90 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.80 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.70 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.60 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.50 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.40 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.30 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.20 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.10 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-3.00 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.90 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.80 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.70 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.60 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.50 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.40 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

-2.30 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.37

-2.20 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37

-2.10 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-2.00 0.38 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

E_5

-1.90 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.80 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.70 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.60 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.50 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.40 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.30 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37

-1.20 0.37 0.37 0.37 0.37 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37

-1.10 0.37 0.36 0.37 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.36

-1.00 0.36 0.36 0.37 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.36 0.36

-0.90 0.36 0.35 0.39 0.39 0.39 0.38 0.37 0.37 0.36 0.36 0.36 0.36 0.35

-0.80 0.33 0.35 0.41 0.39 0.38 0.37 0.36 0.35 0.35 0.35 0.35 0.35 0.33

-0.70 0.33 0.35 0.41 0.39 0.38 0.36 0.35 0.34 0.34 0.34 0.34 0.34 0.32

-0.60 0.33 0.37 0.41 0.39 0.38 0.36 0.35 0.34 0.34 0.34 0.34 0.34 0.31

-0.50 0.33 0.38 0.41 0.39 0.37 0.35 0.34 0.33 0.34 0.34 0.34 0.34 0.31

-0.40 0.34 0.40 0.40 0.39 0.37 0.35 0.34 0.32 0.34 0.33 0.34 0.33 0.30

-0.30 0.33 0.39 0.38 0.36 0.35 0.32 0.31 0.30 0.32 0.31 0.32 0.31 0.28

-0.20 0.33 0.37 0.35 0.33 0.34 0.29 0.28 0.27 0.30 0.29 0.30 0.28 0.25

-0.10 0.32 0.38 0.33 0.29 0.35 0.24 0.23 0.24 0.30 0.32 0.29 0.24 0.21

0.00 0.27 0.38 0.30 0.17 0.32 0.10 0.14 0.14 0.29 0.36 0.26 0.13 0.15

E_6

Figures – Volumetric moisture content profiles obtained from Neutron probe

measurements and model

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 10/04/2013 CN1 - 10/04/2013 CN2 - 10/04/2013

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

) Model - 20/06/2013 CN1 - 20/06/2013 CN2 - 20/06/2013

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 21/10/2013 CN1 - 21/10/2013 CN2 - 21/10/2013

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 21/08/2013 CN1 - 21/08/2013 CN2 - 21/08/2013

E_7

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 11/12/2013 CN1 - 11/12/2013 CN2 - 11/12/2013

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 29/01/2014 CN1 - 29/01/2014 CN2 - 29/01/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 26/02/2014 CN1 - 26/02/2014 CN2 - 26/02/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 1/04/2014 CN1 - 01/04/2014 CN2 - 01/04/2014

E_8

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 5/06/2014 CN1 - 05/06/2014 CN2 - 05/06/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 1/05/2014 CN1 - 01/05/2014 CN2 - 01/05/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 12/11/2014 CN1 - 12/11/2014 CN2 - 12/11/2014

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 8/07/2014 CN1 - 08/07/2014 CN2 - 08/07/2014

E_9

0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

-4

-3

-2

-1

0


Dep

th (m

)

Model - 25/03/2015 CN1 - 25/03/2015 CN2 - 25/03/2015

Date post:	27-Mar-2020
Category:	Documents
Upload:	others
View:	0 times
Download:	0 times

Investigation of expansive soil for design of light ...Investigation of Expansive Soil for Design of...

Documents