Groundwater Availability Modeling (GAM) for the Dockum Aquifer · groundwater flow models...

Groundwater Availability Modeling (GAM) for the

Dockum Aquifer

GAM Stakeholder TrainingOctober 22, 2008

Workshop Agenda

1. Introduction2. Modeling Overview

– Modeling Protocol and Practice

– MODFLOW– Groundwater Vistas (GV)

3. Dockum GAM Review– Technical Overview– Data and Model Inputs

4. Break5. Modeling Demonstration

– The GV Interface– Transient/Predictive

Model Exercise(s)

Workshop Goals

Provide an introduction to groundwater modeling, MODFLOW, and GV

Review the development of the Dockum GAM

Provide information on model input and associated data sources

Provide insight into the utility and applicability of the GAM

1. Introduction

Workshop Expectations

To gain an appreciation of the expertise required to use the GAM

To gain an understanding as to the potential applicability of the GAM

To gain some understanding of the limitations of the GAM

To acquire the ability to make minor modifications to the model via PMWIN

1. Introduction

The GAM Truth

If you want to run these models – seek professional help

“It is very easy for me to calculate the positions of Sun, Moon and any planet, but I cannot calculate the positions of water particles as they move through the earth.” Galileo

1. Introduction

GAM Objectives

Develop realistic and scientifically accurate groundwater flow models representing the physical characteristics of the aquifer and incorporating the relevant processes

The models are designed as tools to help GWCD, RWPGs, and individuals assess groundwater availability

Stakeholder participation is important to ensure that the model is accepted as a valid model of the aquifer

1. Introduction

GAM Model Specifications

Three dimensional (MODFLOW-2000)

Regional scale (1000’s of mi2)

Grid spacing of 1 square mile

Include Groundwater/surface water interaction (Stream routing, Prudic 1988)

Properly implement recharge

Stress periods as small as 1 year

Calibrate to within 10% of head drop

1. Introduction

Schematic of Modeling PeriodsPre-development

(Steady-State) Post-developmentCalibration(Transient)

1950 1980 1997

Observed Water LevelModel Water Level

2050

Prediction

Steady-state and transient calibration periods represent different hydrologic conditions

1900

Wat

er E

leva

tion

in W

ell

Modeling Overview

Modeling Protocol & Practice MODFLOW GV – Groundwater Vistas

2. Modeling Overview

Definition of a Model

Domenico (1972) defined a model as a representation of reality that attempts to explain the behavior of some aspect of it and is always less complex than the system it represents

Wang & Anderson (1982) defined a model as a tool designed to represent a simplified version of reality


GW Models in Water Resources

GW Models have been used in water resources in response to 4 basic issues.

Impact on neighboring resources

Conjunctive use issues (SW-GW)

GW mining & resource depletion on practical time scales (regional resource issues)

Water quality issues


GW Models in Water Resources

Regional-scale models typically are used to address management as an institutional issue

Local-scale models typically are used to address management as an operational issue


Define model objectives

Data compilation and analysis

Conceptual model

CALIBRATION

Reporting

Future WaterStrategies

Comparison with

field data

Model design

Field data

Field data

*Includes sensitivity

analysis

Modeling Protocol

Transient*

Steady State*


Prediction

Modeling References

Anderson & Woessner “Applied GW Modeling”

ASTM D5447 “Standard Guide for Application of a Ground-Water Model to a Site-Specific Problem”

“Fundamentals of Ground-Water Modeling”, U.S. EPA

Faust & Mercer: “GW Modeling: Numerical Models”

Mercer & Faust: “GW Modeling: An Overview”


Conceptual Model

Identify relevant processes and physical elements controlling GW flow in the aquifer:– Geologic Framework– Hydrologic Framework– Hydraulic Properties– Sources & Sinks (Water Budget)

Determine Data Deficiencies

Conceptual model dictates how you translate “real world” to Mathematical Model


To be Considered in Code Selection

Simulates Relevant Physical/Chemical Processes

Public-Domain vs. Proprietary

Thorough Testing for Intended Use

Complete Documentation


Model Design

Translate Conceptual Model to Mathematical Counterparts

Procedure– Grid Design (Numerical)– Define Hydraulic Properties– Boundary & Initial Conditions


Grid Design – Typical Drivers

Dimensionality (1D,2D,3D)– Vertical Gradients– Multiple Aquifers– Partially Penetrating Wells

Number of Grid Cells– Run Time– Computer Memory

Regular vs. Irregular Node Spacings– Design Time– Accuracy in Areas of Interest


Grid Design – When to use a Regular (constant dimension) Grid

Regional Studies (e.g. USGS RASA, GAM)

Preliminary Analyses

Models Where Area of Interest May Change

High Resolution Models Where Memory is Not a Concern

GAM grid defined to be 1 mile square


Model Grid Example

Source: USGS Fact Sheet FS-127-97


Model Inputs

Hydrostratigraphic Surfaces for each Layer

Hydraulic Properties:– Hydraulic Conductivity– Storativity (transient)

Hydraulic heads

Recharge

Stream Flow (headwater flows, initial C)

Pumpage


Boundary Conditions

Boundary Condition is a constraint put on the active grid to characterize interaction between the modeled area and its environment

Types:– Specified Head (Dirichlet – Type 1)– Specified Flux (Neumann – Type 2)– Head-Dependent Flux or Mixed (Cauchy- Type 3)

Determination:– Based on Natural Hydrogeologic Boundaries– Analyze Impact of Artificial Boundaries


Boundary Conditions

Boundary conditions may be static or transient

Recharge or wells – Specified flow

GHB, Reservoir, Stream – Head dependent flow

Vertical or lower boundaries – specified flow @ zero = no flow


Modeling Approaches

MODEL

HeadsSpring FlowStream Flow

Hydraulic ConductivityStorativityBoundary Conditions


Model Calibration

Process used to produce agreement between observed and simulated data through adjustment of independent variables

Typical variables adjusted are hydraulic conductivity, storativity, and recharge



Model Calibration

Types:– Trial-and-Error– Automated or inverse– Stochastic

Procedures:– Select Calibration Targets– Select Calibration Metrics– Adjust Boundary Conditions/Properties– Analyze Errors


Model Calibration

Steady-state calibration– Assumes that the hydrologic system is static over

the time frame of interest– Q in = Q out; No storage effects

Transient calibration– Assumes that dependent variables change with time

in response to changing stresses (recharge, pumping, stage, boundaries)


Sensitivity Analysis

A sensitivity analysis is a formal means of quantifying the effect of changes in model inputs on model outputs

Provides a means of identifying parameters which are:– Important– Correlated

Most common method is the one-off-method


Verification

Simulation period where the model is run in a forward mode (ie without adjustment of parameters) to see how the model agrees with observations

The more variable stresses the better the verification period

Acceptable verification doesn’t insure accuracy; does enhance model validity


Prediction

Once the model meets the calibration metrics, it can be used for prediction.

The basis behind model predictions is the assumption that:– The past is the key to the future.

Predictive accuracy depends on– Validity of modeled processes– Accuracy of props. and boundaries– Knowledge of hydraulic conditions– Reliability of estimates of system stresses


Reporting


Prediction

Field data

Conceptual model

Prediction – Post Audits

Post-audits have demonstrated that models are moderately reliable and are uncertain

As approximations to reality, models can, and should, always be improved – (updated)

A primary value of a model, regardless of the predictive accuracy, is it allows for a disciplined format for the improvement of the understanding of an aquifer (Konikow, 1995)


Calibration Challenges

Uniqueness of calibration

Over-Calibration

2. Calibration Challenges & Approach

Model Uniqueness (Similarity Solutions)

Models are inherently non-unique, that is multiple combinations of parameters and stresses can produce similar aquifer conditions.

The ramification of this is:– A good match to observed data does not guarantee

an accurate model

Modeling Approach to Deal with Uniqueness

To reduce the impact of non-uniqueness:a) Calibrate to multiple hydrologic conditionsb) Calibrate with parameters consistent with

measured valuesc) Calibrate to multiple performance measures


(a) Calibrate to Multiple Hydrologic Conditions

CALIBRATION

Transient*

Prediction

*Includes sensitivity analysis

Steady State* Comparison with

field data

The calibration approachiterates between the steady-stateand the transient calibrations to reach a consistent set of physical parameters that match both setsof observation.


(b) Calibrate with parameters consistent with measured values

Because of the uniqueness issues, you must consider some parameters known

On super-regional models such as the GAM, scale issues related to measured data and how they relate to the model result in difficulties


(c) Calibrate using multiple targets and performance measures

Heads (SS and transient)– Distributions– Time series– Scatter plots– Statistics (RMS, MAE, ME)

Stream aquifer interaction– Stream flow rates– Gain loss estimates

Flow balance (qualitative)

Don’t calibrate better than target error (see next slide)

300

350

400

450

500

550

600

650

700

750

800

300 350 400 450 500 550 600 650 700 750 800

Measured Head (ft)

Sim

ulat

ed H

ead

(ft)

5.0

2

1 1

ism

n

ihh

nRMS


Over Calibration

One must strive to not over-calibrate (tweak) a model; that is:– Over parameterize lacking data support– Adjust parameters to bring model agreement

below performance measure uncertainty– In the GAM model, head is the primary

performance measure and we have estimated errors associated with heads to be on the order of at least 30 feet


Calibration and Prediction

Freyberg published a study on calibration and prediction (GW, 1988, Vol. 26, No. 3)

Nine modeling teams using same data

Best model prediction came from the model with the least estimated parameters and with inferior local fits

Good calibration may not equal good prediction

Best calibrated model yielded poorest prediction


MODFLOW (is a Code)

Developed by the United States Geological Survey

Three-dimensional, finite difference groundwater flow CODE


MODFLOW Version History

Various USGS research codes; Trescott (1975), and others

MODFLOW (1984)– McDonald and Harbaugh, 1986 (Fortran 66)

MODFLOW (1988)– McDonald and Harbaugh, 1988 (Fortran 77)

MODFLOW96 (1996)– Harbaugh and McDonald, 1996

MODFLOW2000 (2000)– Harbaugh et al (2000)


MODFLOW Packages

Original Packages (88)– Basic– Block-Centered Flow– Recharge– Evapotranspiration– River– Well– Drain– General Head Boundary– Output Control– SIP/SOR Solvers

Add on Packages (2000)– Block-Centered Flow 2 .. 6– Discretization– PCG/PCG2, GMG Solvers– Horizontal Flow Barrier (HFB)– Compaction (IBS)– Time-variant C.H. (CHD)– Stream Routing (STR)– Transient Leakage (TLK)– Direct solver (DE4)– Various user add ons

Subroutines are called modulesGroups of subroutines representing a “process” are packages


MODFLOW Advantages

Handles the basic processes

Well documented

Testing is documented – courts accept

Public domain – non-proprietary

Most widely used model– USGS had 12,261 downloads of MODFLOW in 2000

Multiple utility programs and Graphical User Interfaces (GUIs) available


MODFLOW Processes

Important for GAM– Confined/unconfined GW

flow– Recharge/ET– Horizontal flow barriers– Wells– Streams– Drains (springs)– Reservoirs



After McDonald & Harbaugh, 1988

Example of a MODFLOW GridNote – Regular Grid

Row

>

Column >



Vertical DiscretizationShould have physical significance


Assignment of Properties

Properties can be assigned on a gridCell basis as below

Properties can be assigned in zones as above


Example of an IBOUNDArray (Basic package)for a Single Layer


These cellsBecome inactive

Single Layer example of conceptualizing aModel grid and assigning boundary conditions


MODFLOW in simplest terms

MODFLOW calculates flow in 3 dimensions using a finite difference (FD) approach

The GW flow FD equation form follows from the application of the continuity equation which stipulates that:– The sum of all flows into and out of a cell at a given

time step must equal the rate of change of storage within the cell


Steady-state, One Dimensional Flow Darcy’s Law – One cell

Where:●

K = hydraulic conductivity

●

A = area normal to Flow

●

h = head●

L = length


Darcy’s Law Can be Rewritten

Where C is equal to the hydraulic conductance (L3/T L)

Q = C (h2 – h1)

C = K A / LMODFLOW uses hydraulic conductance to

calculate flow rates using Darcy’s Law


Vertical Conductance - Vcont

Simply stated – Vcont is the interval conductance divided by the area (plan view)

MODFLOW uses Vcont (also known as leakance) to calculate vertical flow


Wells in MODFLOW-2000

MODFLOW-2000 does not have a wellbore submodel– Therefore, simulated heads are representative of the

grid volume

Well rates are specified by row, column, layer (r,c,l)

Multiple wells can be assigned one grid cell

Wells are specified in the well package (.wel)


Stream Routing

Use MODFLOW Stream Routing Package (Prudic, 1988)

Stream stages are calculated using Manning’s equation

Stream-routing package routes surface water and calculates stream/aquifer interaction (gaining/losing)

Input headwater flow rate, stream conductance, stream dimensions, and Manning’s n parameter


Stream Routing Package

Stream reaches (each cell is an individual reach) and segments must be numbered


Head Dependent Flow Boundaries

General head boundaries

Reservoirs

River cells

Stream cells

Drains


Head-dependent Boundaries

Head difference

Head dependentBoundaries alwaysRequire input of the

ConductanceC = K A / L


Specified-flow Boundaries

Wells

Recharge

Evapotranspiration ET (hybrid – head dependent)


MODFLOW Interfaces

PMWIN– Academic, commercially available

Groundwater Modeling System (GMS)– DOD, commercially available

Groundwater Vistas (GV)– Private, commercially available

Visual MODFLOW– Private, commercially available


GV – Groundwater Vistas

Windows graphical user interface for 3-D groundwater flow and transport modeling. Developed by Environmental Simulations Incorporated.

Authors:Jim Rumbaugh and Doug Rumbaugh

http://www.groundwater-vistas.com

http://www.groundwatermodels.com


GV Capabilities

Offers a Windows based interface for developing MODFLOW models and for using the family of MODFLOW codes

Imports existing standard MODFLOW models

Supports all standard packages

Allows many options for data input: ArcView shapefiles, AutoCAD DXF files, SURFER files, and ASCII files

Allows for telescopic grid refinement

Some degree of checking of input prior to execution

Offers a wide variety of analysis techniques for viewing simulation results


GV Requirements

Pentium or better

Windows 95/98/2000/NT 4.0/XP/Vistas

16 MB RAM (32 Recommended)

GAM model– Requires at least 128 MB RAM– 2 GB or better disk space


GV Interface 2. Modeling Overview

-29,700,203

-23,100,158

-16,500,113

-9,900,068

-3,300,023

3,300,023

9,900,068

16,500,113

23,100,158

29,700,203

1.0 3,690.07,379.011,068.014,757.018,446.022,135.025,824.029,513.033,202.036,891.0

Time

Top Inflow

Stream Inflow

Storage Inflow

Recharge Inflow

Top Outflow

Well Outflow

Drain Outflow

Stream Outflow

Storage Outflow

Total Inflow

Total Outflow

Error

Mass Balance Summary for Layer 3

1,956.8

2,586.9

3,217.0

3,847.1

4,477.2

5,107.3

1,956.8 2,586.9 3,217.0 3,847.1 4,477.2 5,107.3

Observed Value

Layer 2

Layer 3

Observed vs. Computed Target Values

Dockum GAM Review

Technical Overview–

Emphasis on Data and Model Inputs

3. Dockum GAM Review

Model Area F

ile: 2

_01_

stud

y_ar

ea.m

xd

Source: N/A

Dockum Aquifer Study Area

0 50 100

Miles

−State Line

Study_Area

Model Boundary

Downdip Aquifer Limit

County Boundaries

Study Area Model Domain

Lea

Eddy

Chaves

Pecos

Union

Quay

Colfax

Reeves

Culberson

Ellis

DeBaca

Harding

Curry

Texas

San Miguel

Roosevelt

Irion

Mora

Crockett

Hall

Hale

Dallam

Gaines

Jeff Davis

Upton

Hartley

King

Kent

Oldham Gray

Lynn

Beaver

Caddo

Guadalupe

FloydLamb

Terry

Coke

Andrews

Ector

Major

Knox

Kiowa

Mills

Clay

Nolan

Ward

Jones

Potter

Cottle

Taylor

Brown

Custer

Motley

Reagan

Blaine

Young

Dewey

Garza

Martin

Fisher

Coleman

Llano

Baylor

Moore

Archer

Scurry

Tom Green

Castro

Cimarron

Bailey

Deaf SmithDonley

Crane

Runnels

Carson

Concho

Crosby

Schleicher

Washita

Borden

Haskell

Tillman

Erath

Randall

Sterling

Woods

Foard

BriscoeParmer

MitchellHoward

Menard

Roberts

Woodward

Mason

San Saba

Midland

DickensHockley

Swisher

Winkler

Greer

Dawson

Wheeler

Harper

Jack

Eastland

Lubbock

Hemphill

Alfalfa

McCulloch

Roger Mills

Ochiltree

Loving

Wilbarger

HansfordSherman

Callahan

Yoakum

Jackson

Cotton

Comanche

Beckham

Lipscomb

Stephens

Stonewall

Cochran

Armstrong

Glasscock

Comanche

Wichita

Hutchinson

Shackelford Palo Pinto

Childress

Sutton

Harmon

Hardeman

Kimble

Collingsworth

Throckmorton

Burnet

Lampasas

Terrell

coln

Hamilto

Canadia

Kingfis

BrewsterPresidio

ero

Gra

Garf

Steph

File

: 2_0

2_do

ckum

_aqu

ifer.m

xd

Source: Online: Texas Water Development Board, Aug 2006

State Line

Model Boundary


County Boundaries

Dockum AquiferOutcrop

Downdip

−0 25 50

Miles

River Basins and Topography

Major River Basins Topography

State Line

Model Boundary


County Boundaries

River Basins

Canadian River Basin

Red River Basin

Brazos River Basin

Colorado River Basin

File

: 2_1

0_riv

er_b

asin

s.m

xd

Source: Online: Texas Water Development Board, June 2006; New Mexico Resource GIS Program, June 2006

Rio Grande River Basin0 25 50

Miles

−

File

: 2_1

3_to

po.m

xd

Source: Online: USGS, Aug 2006

State Line

Model Boundary


County Boundaries

Land Surface Elevation(ft-MSL)1,406 - 1,5001,501 - 2,0002,001 - 2,5002,501 - 3,0003,001 - 3,5003,501 - 4,0004,001 - 4,5004,501 - 5,0005,001 - 5,5005,501 - 6,0006,001 - 6,5006,501 - 7,0007,001 - 7,5007,501 - 8,0008,001 - 8,5008,501 - 9,000

0 25 50

Miles

−

Geology

Stratigraphic Units Overlying Aquifers

Ogallala/Alluvium

Cretaceous-age Sediments (not continuous)

Upper Dockum

Cooper Canyon Formation

Trujillo Sandstone

Lower Dockum

Tecovas Formation

Santa Rosa Sandstone

Permian-age Sediments

Lea

Eddy

Chaves

Pecos

Quay

Union

Colfax

Reeves

Culberson

Ellis

DeBaca

Harding

Curry

San Miguel

Crockett

Roosevelt

Mora

Irion

Hall

Texas

Jeff Davis

Hale

Dallam

Gaines

Upton

Hartley

King

Kent

Oldham Gray

Guadalupe

Lynn

Caddo

FloydLamb

Terry

Coke

Andrews

Ector

Beaver

Major

Knox

Kiowa

Mills

Llano

Nolan

Ward

Jones

Potter

Clay

Cottle

Taylor

Brown

Custer

Motley

Reagan

Blaine

Young

Dewey

Garza

Martin

Fisher

Coleman

Baylor

Moore

Archer

Scurry

Tom Green

Castro

Bailey

Deaf Smith Donley

Crane

Runnels

Carson

Concho

Crosby

Mason

Schleicher

Washita

Cimarron

Borden

Haskell

Tillman

Randall

Sterling

Foard

BriscoeParmer

MitchellHoward

Menard

Roberts

Woodward

San Saba

Erath

Midland

DickensHockley

Swisher

Winkler

Greer

Dawson

Wheeler

Woods

Eastland

Lubbock

Hemphill

McCulloch

Roger Mills

Ochiltree

Loving

Wilbarger

HansfordSherman

Callahan

JackYoakum

Jackson

Beckham

Lipscomb

Comanche

Stephens

HarperAlfalfa

Cotton

Stonewall

Cochran

Armstrong

Glasscock

Sutton

Wichita

Comanche

Hutchinson

Hardeman

KimbleTerrell

Shackelford

Childress

Collingsworth

Harmon

Throckmorton

Burnet

Lincoln

Hamilton

Canadian

Presidio Brewster

Otero

File

: Fig

.4.1

_Aqu

ifers

_Dire

ctly

_Ove

rlayi

ng_D

ocku

m

Source: Adapted from Texas Water Development Board, Dec 2006

−

Model BoundaryAquifer Downdip LimitState LineCounties

Aquifer NameDockum Group OutcropOgallalaEdwards-Trinity (High Plains)Pecos ValleyEdwards-Trinity (Plateau) - OutcropEdwards-Trinity (Plateau) - SubcropRita Blanca

0 30 60Miles

Model Flow Conceptualization

Undifferentiated Permian

Upper Dockum

Lower Dockum

Ogallala

Cretaceous

Upper Dockum

Lower Dockum

General Head BoundaryRecharge (Precipitation)Discharge (ET, Springs)Discharge via PumpingSurface Water-Aquifer InteractionCross-Formational FlowNo-Flow Boundary

AquiferOutcrop

Aquifer Outcrop

NW SE

Ogallala/Younger

Model Grid

1 square mile grid blocks212 columns422 rows3 layers150,548 active cells

Schematic of Modeling PeriodsPre-development

(Steady-State) Post-development Calibration(Transient)

1950 1980 1997

Observed Water LevelModel Water Level

Model Input – Supporting Data

Hydrostratigraphic

surfaces for each layerHydraulic properties

–

Hydraulic Conductivity–

Storativity

(transient)

Water LevelsRechargeETStream FlowPumpage

All model data, source and derived, was delivered to the TWDB and will be available to the public

Dockum Thickness

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File

: 4.2

.5_l

ower

_thi

ckne

ss.m

xd

Source: McGowen et al. (1977)

State Line

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−0 25 50

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Upper DockumThickness

(feet)20 - 100101 - 200201 - 300301 - 400401 - 500501 - 600601 - 700701 - 800801 - 900901 - 1,0001,001 - 1,1001,101 - 1,200

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File

: 4.2

.3_l

ower

_thi

ckne

ss.m

xd

Source: McGowen et al. (1977)

State Line

Model Boundary


County Boundaries

! McGowen Control Points

−0 25 50

Miles

Lower DockumThickness

(feet)50 - 100101 - 200201 - 300301 - 400401 - 500501 - 600601 - 700701 - 800801 - 900901 - 1,0001,001 - 1,1001,101 - 1,2001,201 - 1,3001,301 - 1,400

Upper Dockum Lower Dockum

Horizontal Hydraulic Conductivity – KH


0 25 50

Miles

Upper Dockum Calibrated Horizontal

Hydraulic Conductivity (ft/d)

0.01 - 0.03

0.03 - 0.1

0.1 - 0.3

0.3 - 1

1 - 3

3 - 10

Active Boundary

State Line

County Boundaries

Inactive Cells

Active Boundary

State Line

County Boundaries

Inactive Cells

0 30 60

Miles

Lower Dockum Calibrated Horizontal

Hydraulic Conductivity (ft/d)

0.01 - 0.030.03 - 0.10.1 - 0.30.3 - 11 - 33 - 10

Vertical Hydraulic Conductivity – KV


Active Boundary

State Line

County Boundaries

Inactive Cells

0 25 50

Miles

Upper DockumVertical

HydraulicConductivity

(ft/d)2.5e-4 - 3.0e-4

3.0e-4 - 3.5e-4

3.5e-4 - 4.0e-4

4.0e-4 - 4.5e-4

4.5e-4 - 5.0e-4

5.0e-4 - 1.0e-3

1.0e-3 - 5.0e-3

Active Boundary

State Line

County Boundaries

Inactive Cells (layer3)

0 25 50

Miles

Lower DockumVertical

HydraulicConductivity

(ft/d)2.5e-4 - 3.0e-4

3.0e-4 - 3.5e-4

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4.0e-4 - 4.5e-4

4.5e-4 - 5.0e-4

5.0e-4 - 1.0e-3

1.0e-3 - 5.0e-3

StorativityUpper Dockum Lower Dockum

Active Boundary

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0 25 50

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Storativity in Upper Dockum

1e4 - 3e-4

3e-4 - 1e-3

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3e-3 - 1e-2

1e-2 - 3e-2

Active Boundary

State Line

County Boundaries

0 25 50

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Storativity in Lower Dockum

1e-4 - 3e-4

3e-4 - 1e-3

1e-3 - 3e-3

3e-3 - 1e-2

1e-2 - 3e-2

General Head Boundary

19971980

Surface Water Boundary ConditionsUpper Dockum Lower Dockum

Recharge Rate Estimates

County/Area Land use Aquifer Recharge (in/yr) Technique Reference Dockum Aquifer – Colorado River outcrop area All of the Colorado River outcrop area - Predevelopment Grassland and shrubland Dockum 0.08 SZ chloride mass

balance This report

Sandy areas (Nolan and eastern Mitchell counties) - Predevelopment Grassland and shrubland Dockum 0.22 SZ chloride mass

balance This report

All of the Colorado River outcrop area Dockum 0.08 to 0.2 UZ numerical

modeling Scanlon et al. (2003)

Western Scurry and Mitchell counties Grassland and shrubland Dockum <0.01 SZ chloride mass balance This report

Scurry County - Predevelopment Dockum 0.02 to 0.04 Water budget on playas This report

All of the Colorado River Outcrop area - Postdevelopment Dockum 2.2 regional water level

rise This report

Sandy areas (Nolan and eastern Mitchell counties) - Postdevelopment Cropland Dockum

Geom. Average = 1.7Median = 1.6

Range = 0 to 4.3

linear water level rises in individual wells

This report

County/Area Land use Aquifer Recharge (inch/yr) Technique ReferenceDockum Aquifer – Canadian River outcrop area All of the Canadian River outcrop area- Predevelopment and Postdevelopment

Grassland and shrubland Dockum 0.17 SZ chloride mass balance This report

All of the Canadian River outcrop area Dockum <0.08 UZ numerical

modeling Scanlon et al. (2003)

Dockum Aquifer – high TDS outcrop area Howard, Borden and Garza counties - Predevelopment Grassland and shrubland Dockum <0.01 SZ chloride mass

balance This report

Predevelopment Recharge

Recharge was estimated on limited points (80) using:

The correlation of estimated recharge to physical parameters was tested, however, no obvious correlation was found

A significance analysis (t-test) was conducted to determine whether average recharge rates should be divided into regions; no significant difference existed

Recharge rates were weighted as a power function of the local topography and normalized to conserve total recharge

Power coefficient adjusted until maximum recharge rate was reasonable (~0.5 in/yr)

GW

P

ClClPR

Modern Recharge

Analysis of regional water-level rise was conducted–

Colorado River outcrop rise indicates 2.2 in/yr effective recharge–

Canadian River outcrop indicates no appreciable rise–

includes recovery, stream loss, land-use impacts, return flow

For non-pumped, interstream wells with linear water table rise:–

Recharge = ∆h/Sy∆t

where median = 1.6 in/yr–

Already have 0.15 in/yr historical recharge

Added 1.45 in/yr to cropland areas–

Only added within Colorado River outcrop–

Added to cells by percent cropland within cell

Recharge Distribution

ModernPredevelopment

Aquifer Discharge Through Pumping

Point Source Data–

Municipal, power, mining, manufacturing

Non-Point Source Data–

Irrigation, livestock, county-other (domestic)

Historical (1980-1997)–

TWDB water use survey database

Uses of Water (1980 – 1997 Average)

Irrigation69%

Municpal13%

Livestock6%

Rural Domestic4%

Mining7%

Manufacturing0.5%

Power0.5%

1980 – 1997 Pumpage

0

5000

10000

15000

20000

25000

30000

35000

40000

4500019

80

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

Year

Pum

page

(afy

) STKRDPWRMUNMINMFGIRR

Pumpage (AFY)

1980 1997

Active Boundary

State Line

County Boundaries

0 25 50

Miles

Pumpage in Lower Dockum

in 1980 (AFY)0 - 11 - 33 - 1010 - 3030 - 100100 - 300300 - 10001000 - 3000

Active Boundary

State Line

County Boundaries

0 25 50

Miles

Pumpage in Lower Dockum in 1997 (AFY)

0 - 11 - 33 - 1010 - 3030 - 100100 - 300300 - 10001000 - 3000

Calibration Approach

Define model objectives

Data compilation and analysis

Conceptual model

CALIBRATION

Reporting


Comparison with

field data

Model design

Field data

Field data

*Includes sensitivity

analysis

Transient*

Steady State*

Prediction

Model Evaluation

Model results compared to observed data–

Observed water levels

–

Stream flow Model results evaluated against literature

data–

Recharge

–

Hydraulic conductivitiesModel results evaluated against

conceptual model–

Flow from overlying aquifer

Model Calibration

Calibration required:–

Reducing Kh

of the upper and lower Dockum

by factor of 0.2

–

Reducing Kv

of the upper and lower Dockum

by factor of 0.5

–

Reducing streambed conductances

by a factor of 0.1

Upper Dockum Calibration – Predevelopment

(a)

2500

3000

3500

4000

4500

5000

2500 3000 3500 4000 4500 5000

Observed (ft)

Sim

ulat

ed (f

t)

!(#*!(

!( !( #* #*!( #* #*

#* #*

!(

#*#*

#* !(

#*

!(

!(!(

#*

!( !(

!(

#*36

00

3400

38004000

3200

4200

3000

2800

4400

4600

2600

4800

3000

Active Boundary

State Line

County Boundaries

−0 25 50

Miles

Simulated head in Upper Dockum in

Steady-state Model (ft)

ContoursDry Cells

Residuals!( -300 to -100!( -100 to -30!( -30 to -10!( -10 to 0#* 0 to 10#* 10 to 30#* 30 to 100#* 100 to 300

count 29RMSE 99.8 ftMAE 76.3 ftME 16.1 ftMin E -223.0 ftMax E 185.6 ft

Range 2403.6 ftRMSE/Range 4.15%MAE/Range 3.17%ME/Range 0.67%

Lower Dockum Calibration – Predevelopment

(a)

2000

2500

3000

3500

4000

4500

2000 2500 3000 3500 4000 4500Observed (ft)

Sim

ulat

ed (f

t)



#*!(

#*#* #*#* #*

#*

#* #*#*#* #*#*!(#*

#*!(#*#* !(!( !(#*#* #*!( #*

!(#*

#* #*#*#* #*#*!(#*#*#* #*

#* !(

#*#* !(#* #*#*#*#*!(#* #*#*#*#*#*!(#*!(!(!(#*#*!(#*#*!(#*#*#*!(!(#*#*#*#*!(!(!(!(!(!(#*!(!(#*#*!(#*#*!( #*#* #* #*#*!( #*#*!(

#*!(#*#*#*#*!(

!(!(!( !(

!(#*#*

!( #*#*#*#*!(#*!(#*!( #*#*#*#*#*!(

!(!(!(#* !( !( !(!(!(#* #*!( !(#* #*#*!(#*#*#* !(#*!( #*#* !(#* !(!(!( !(

#*!(

#* !( #*!( !(

#*!(

#* #*#* !( !(

#*!(

#*

3800

4000

420046004800

5000

5200

5400

600064

00

3600

3400

3200

2200

2600

3000

4400 2800

2400

2800300032

00

2400

2600

2400

2200

2400

3600

2600

2400

3800

4200

2600

4200

2400

3200

2800

Active Boundary

State Line

County Boundaries

−0 25 50

Miles

Simulated head in Lower Dockum in

Steady-state Model (ft)

ContoursDry Cells

Residuals!( -300 to -100!( -100 to -30!( -30 to -10!( -10 to 0#* 0 to 10#* 10 to 30#* 30 to 100#* 100 to 300

Upper Dockum Calibration – Transient



(a)

2500

3000

3500

4000

4500

5000

2500 3000 3500 4000 4500 5000Observed (ft)

Sim

ulat

ed (f

t)

Active Boundary

State Line

County Boundaries

0 25 50

Miles

Mean Residuals in Upper Dockum

in Transient model (ft)

-1000 to -300-300 to -100-100 to -30-30 to -10-10 to 00 to 1010 to 3030 to 100100 to 300300 to 1000

Lower Dockum Calibration – Transient

(a)

1500

2000

2500

3000

3500

4000

4500

1500 2000 2500 3000 3500 4000 4500Observed (ft)

Sim

ulat

ed (f

t)



Active Boundary

State Line

County Boundaries

0 25 50

Miles

Mean Residuals in Lower Dockum

in Transient model (ft)

-1000 to -300-300 to -100-100 to -30-30 to -10-10 to 00 to 1010 to 3030 to 100100 to 300300 to 1000

Subcrop Randall 1015901

3512

3532

3552

3572

3592

3612

3632

3652

3672

3692

3712

1980 1985 1990 1995 2000Year

Head

(ft

Subcrop Randall 1016102

3608

3618

3628

3638

3648

3658

3668

3678

3688

3698

3708

1980 1985 1990 1995 2000Year

Head

(ft

Upper Dockum Hydrographs

Outcrop Deaf 908301

4007

4017

4027

4037

4047

4057

4067

4077

4087

4097

4107

1980 1985 1990 1995 2000Year

Hea

d (ft

Subcrop Deaf 1001601

4044

4054

4064

4074

4084

4094

4104

4114

4124

4134

4144

1980 1985 1990 1995 2000Year

Hea

d (ft

Outcrop Hartley 726101

3200

3220

3240

3260

3280

3300

3320

3340

3360

3380

3400

1980 1985 1990 1995 2000Year

Head

(ft

Subcrop Armstrong 1105101

3170

3180

3190

3200

3210

3220

3230

3240

3250

3260

3270

1980 1985 1990 1995 2000Year

Hea

d (ft

Lower Dockum Hydrographs

Outcrop Mitchell 2934805

2105

2115

2125

2135

2145

2155

2165

2175

2185

2195

2205

1980 1985 1990 1995 2000Year

Head

(ft

Outcrop Scurry 2925707

2128

2138

2148

2158

2168

2178

2188

2198

2208

2218

2228

1980 1985 1990 1995 2000Year

Hea

d (ft

Subcrop Motley 2201915

2546

2556

2566

2576

2586

2596

2606

2616

2626

2636

2646

1980 1985 1990 1995 2000Year

Head

(ft

Subcrop Winkler 4623701

2655

2665

2675

2685

2695

2705

2715

2725

2735

2745

2755

1980 1985 1990 1995 2000Year

Head

(ft

Stream Gain/loss

19971990

Stream Results

Miles

0 10 20

Borden

Garza

Kent

Scurry

NolanMitchell

Sterling

Howard

Fisher

CrosbyDickens

Dawson

Lynn

Glasscock Coke

Stream-FlowStudy Number(s)

37-3942-4445-4852

08123720

08123800

08117995

0811

9500

08120700

08121000

Aquifer Downdip Limit

County Boundaries

Dockum Aquifer

Fresh-Water Outcrop

High-TDS Outcrop

Downdip

Model Boundary

Streamflow-Gaging Station08123720

Slade et al., 2002

-300

-250

-200

-150

-100

-50

0

50

100

150

200

Studies 37,38,39 Studies45,46,47,48

Study 42

Studies 43,44,52

Gai

n/Lo

ss (A

FY/m

ile)

Simulated

Study A

Study B

Study C

Study D

Comparison with Steady-State Model

Spring Flow

19971990

ET Flow

19971990

Flow into Top of Dockum

Active Boundary

State Line

County Boundaries

0 25 50

Miles

Flow into Dockum in Steady-state

Model (AFY)-300 to 100-100 tp -30-30 to -10-10 to 00 to 1010 to 3030 to 100100 to 300

Active Boundary

State Line

County Boundaries

−0 25 50

Miles

Flow into Dockum in Transient Model (AFY)

-300 to -100-100 to -30-30 to -10-10 to 00 to 1010 to 3030 to 100100 to 300

1997Predevelopment

Sensitivity Analysis

-15

-10

-5

0

5

10

15

0.4 0.6 0.8 1 1.2 1.4 1.6

Fraction of Base Value

Mea

n He

ad D

iffer

ence

(ft) Kh-all

Kh-OgallalaKh-Upper-DockumKh-Lower-DockumKv-allKv-OgallalaKv-Upper-DockumKv-Lower-Dockum

Example: Effect of Hydraulic Parameters on Lower Dockum

Heads

Conclusions

GAM for Dockum Aquifer:–

Incorporated all relevant features, data on aquifer properties, recharge estimates, and pumpage

–

Calibrated to specifications: steady-state (prior to 1950) transient conditions (1980-1997)

–

Required some adjustment of properties during transient calibration (not beyond measured data)

Data Models

background

Consistent methodology for storage of GAM data

Facilitates future improvements or modifications of current work

Available to the general public as an addition to the final reports

Data Models basic structure

srcdata

– contains the source and some derived data used to generate the model input data sets

pumpage

– contains tools for generating pumpage inputs along with output tables

Modflow

– contains all of the actual model input and output data files

Data Models srcdata

-

examples

Boundary

– geopolitical boundaries

Climate

– climatic data

Conservation

– natural and ecological boundaries

Geology

– subsurface geology, outcrop delineation

Geomorphology

– physiography and elevation

Geophysics

– well logs

Model*– model inputs and results on the model grid

Recharge

– direct and irrigation recharge

Soil

– STATSGO data, runoff numbers

SubsurfaceHydro

– pumping rates, hydraulic

conductivities, water levels, hydrographs

SurfaceHydro

– streamflows, stream/aquifer

interaction, springflows

Transportation

– roads

Data Models modflow

mf2k•

Input –

ASCII input data sets for running modflow

from the command line•

Output –

All output data sets

vistas•

Data sets for running the models from groundwater vistas interface along with output

postprocessors•

layerMB.pl

–

calculates layer water budgets

•

countyMB.pl

–

calculates budgets by county or GCD

Limitations & Applicability of the GAM

The GAM is a tool capable of being used to make groundwater availability assessments on a regional scale

The model is well suited for studying institutional water resource issues

The model would likely require refinement to study operational issues for a specific project

The GAM allows regional consideration of interference between resource strategies

Limitations & Applicability of the GAM

The GAM scale of application is for areas of many square miles.– The GAM produces water levels representative of

large volumes of aquifer (e.g., 5,280 ft X 5,280 ft X100 ft aquifer thickness)

The GAM is not capable of predicting aquifer responses at particular point such as a particular well – The model is well suited for refinement to address

local-scale, operational water resource questions.

Model Grid Scale

Lea

Eddy

Chaves

Pecos

Union

Quay

Colfax

Culberson

Reeves

Mora

San Miguel

Ellis

DeBaca

Harding

Guadalupe

Texas

Curry

Roosevelt

Irion

Hall

Crockett

Lincoln

Hale

Dallam

Gaines

Jeff Davis

Upton

Hartley

King

Kent

Beaver

Oldham Gray

Lynn

FloydLamb

Terry

Coke

Andrews

Ector

Knox

Kiowa

Nolan

Ward

Jones

Potter

Cottle

Taylor

Brown

Custer

Motley

Reagan

Young

Dewey

Garza

Martin

Fisher

Coleman

Baylor

Cimarron

Moore

Scurry

Archer

Tom Green

Castro

Bailey

Deaf Smith

Mills

Donley

Crane

Runnels

Carson

Concho

Crosby

Llano

Woods

Schleicher

Washita

Borden

Haskell

Tillman

Randall

Sterling

Foard

BriscoeParmer

MitchellHoward

Menard

Roberts

Woodward

Major

Midland

San Saba

DickensHockley

Swisher

Harper

Winkler

Mason

Greer

Dawson

Wheeler

EastlandOtero

Lubbock

Hemphill

McCulloch

Roger Mills

Ochiltree

Loving

Wilbarger

HansfordSherman

Callahan

Yoakum

Jackson

Beckham

Lipscomb

Stephens

Blaine

Stonewall

Cochran

Armstrong

Glasscock

Wichita

Hutchinson

Shackelford

Childress

Harmon

Hardeman

Comanche

Sutton Kimble

udspeth

Caddo

Collingsworth

Throckmorton

Comanche

Alfalfa

Cotton

Terrell

Palo Pi

Taos

Era

Presidio Brewster

Lampa

Cla

Ham

LegendActive boundary

State Line

County Boundaries

Model grid

0 25 50

Miles

Scurry County

Dockum Model Limitations

Limitations of supporting data– Limited head targets spatially and temporally– Limited Stream/aquifer gain loss estimates– Limited data quantifying x-formational flow– Limited hydraulic property data in areas

Assumptions– GHB used to describe overlying aquifers– Spatial variation in recharge– Lack of temporal variation in recharge– No flow to underlying formations

Dockum Model Limitations (continued)

Model applicability– Regional scale

Applicable at scale of tens of miles

– Annual stress period

Not applicable to seasonal trends

– Low TDS regions

MODFLOW does not account for density- dependant flow in high TDS regions

Dockum Model Limitations (continued)

Model applicability– Surface water/groundwater coupling

The model does not provide a rigorous solution to surface water modeling for GAMs

– Water-quality issues

Only a preliminary assessment of water quality is conducted for the GAMs

Future Improvements

Additional supporting data– Water-level monitoring in areas with sparse

measurements– Recharge studies– Long-term surface water/groundwater studies– Additional study of structure– Additional estimates of flow from overlying

aquifers– Additional data describing seasonal trends

Future Implementation Improvements

Account for density-dependant flow– If simulations are to include development of high TDS

portion aquifer, a different simulator (e.g., SEAWAT) may be warranted

Account for flow to underlying units– If water-level data become available to describe

conditions in underlying Permian formation, could add a fourth model layer

Grid Refinement– If local effects of a small portion of the aquifer are to

be modeled, a local-scale model with a refined grid should be considered

Dockum GAM 4th Stakeholder Training Seminar

October 22, 2008

Sign-in Sheet

Name Affiliation

Melanie Barnes LWV

Jim Conkwright HPWD

Harvey Everheart Mesa UWCD

John Ewing INTERA

Michelle Guelker Lone Wolf GCD

Ian Jones TWDB

Steve Walthour North Plains GCD

Bruce Blalack City of Lubbock

Emmett Autrey City of Amarillo

Ferrel Wheeler Garza Co. U&FWCD

Aubrey Spear City of Lubbock

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