U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2011–5149

U.S. Geological Survey National Water-Quality Assessment Program

Simulations of Groundwater Flow and Particle-Tracking 

Analysis in the Zone of Contribution to a Public-Supply Well 

in San Antonio, Texas

NW

Spring

FAULT

EdwardsTrinity aquifer

Trinity 

aquifer

Edwards

aquifer

EDWARDS PLATEAU

Saline

Fresh

Not to scale

Recharge

zone 

Confined zone

BALCONES

FAULT ZONE

Contributing zone

(Catchment area)

NE

SE

Recharge

Discharge

Urban area

Spring Generalized

groundwater

 flow

Generalized conduit system

Upper

confining units

Supply

well
 
Simulations of Groundwater Flow and 

Particle-Tracking Analysis in the Zone of 

Contribution to a Public-Supply Well in San 

Antonio, Texas

By Richard J. Lindgren, Natalie A. Houston, MaryLynn Musgrove, Lynne S. 

Fahlquist, and Leon J. Kauffman

U.S. Geological Survey National Water-Quality Assessment Program

Scientific Investigations Report 2011–5149

U.S. Department of the Interior

U.S. Geological Survey
Suggested citation:

Lindgren, R.J., Houston, N.A., Musgrove, M., Fahlquist, L.S., and Kauffman, L.J., 2011, Simulations of groundwater 

flow and particle-tracking analysis in the zone of contribution to a public-supply well in San Antonio, Texas: U.S. 

Geological Survey Scientific Investigations Report 2011–5149, 93 p.

U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

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Foreword

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scientific information that helps to enhance and protect the overall quality of life and 

that facilitates effective management of water, biological, energy, and mineral resources 

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availability of that water, measured in terms of quantity and quality, even more essential to the 

long-term sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 

1991 to support national, regional, State, and local information needs and decisions related to 

water-quality management and policy (http://water.usgs.gov/nawqa). The NAWQA Program 

is designed to answer: What is the quality of our Nation’s streams and groundwater? How 

are conditions changing over time? How do natural features and human activities affect the 

quality of streams and groundwater, and where are those effects most pronounced? By combining information on water chemistry, physical characteristics, stream habitat, and aquatic life, 

the NAWQA Program aims to provide science-based insights for current and emerging water 

issues and priorities. From 1991 to 2001, the NAWQA Program completed interdisciplinary 

assessments and established a baseline understanding of water-quality conditions in 51 of the 

Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/

studies/study_units.html).

National and regional assessments are ongoing in the second decade (2001–12) of the 

NAWQA Program as 42 of the 51 Study Units are selectively reassessed. These assessments 

extend the findings in the Study Units by determining water-quality status and trends at sites 

that have been consistently monitored for more than a decade, and filling critical gaps in 

characterizing the quality of surface water and groundwater. For example, increased emphasis 

has been placed on assessing the quality of source water and finished water associated with 

many of the Nation’s largest community water systems. During the second decade, NAWQA is 

addressing five national priority topics that build an understanding of how natural features and 

human activities affect water quality, and establish links between sources of contaminants, the 

transport of those contaminants through the hydrologic system, and the potential effects of contaminants on humans and aquatic ecosystems. Included are studies on the fate of agricultural 

chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream 

ecosystems, effects of nutrient enrichment on aquatic ecosystems, and transport of contaminants to public-supply wells. In addition, national syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, trace elements, and aquatic ecology are continuing. 

The USGS aims to disseminate credible, timely, and relevant science information to 

address practical and effective water-resource management and strategies that protect and 

restore water quality. We hope this NAWQA publication will provide you with insights and 

information to meet your needs and will foster increased citizen awareness and involvement in 

the protection and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all 

water-resource issues of interest. External coordination at all levels is critical for cost-effective 

management, regulation, and conservation of our Nation’s water resources. The NAWQA 

Program, therefore, depends on advice and information from other agencies—Federal, State, 

regional, interstate, Tribal, and local—as well as nongovernmental organizations, industry, academia, and other stakeholder groups. Your assistance and suggestions are greatly appreciated.

William H. Werkheiser

USGS Associate Director for Water
 
v

Contents

Abstract ..........................................................................................................................................................1

Introduction ....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................4

Previous Groundwater-Flow Models ................................................................................................4

Description of Study Area ..................................................................................................................6

Methods of Investigation ....................................................................................................................9

Data Collection and Analysis ....................................................................................................9

Development and Application of Groundwater-Flow and Particle-Tracking 

Models ...........................................................................................................................10

Conceptualization of the Edwards Aquifer .............................................................................................18

Geologic Setting .................................................................................................................................18

Hydrogeologic Setting ......................................................................................................................18

Hydrostratigraphy .....................................................................................................................21

Karst Hydrogeology ..................................................................................................................22

Hydraulic Properties ................................................................................................................24

Groundwater-Flow System ......................................................................................................25

Recharge ...........................................................................................................................27

Discharge ..........................................................................................................................28

Simulation of Groundwater Flow ..............................................................................................................30

Model Description .............................................................................................................................30

Model Geometry and Discretization ......................................................................................30

Boundary Conditions and Model Stresses ...........................................................................33

Lateral Boundaries ..........................................................................................................33

Recharge ...........................................................................................................................34

Discharge ..........................................................................................................................36

Hydraulic Properties ................................................................................................................36

Particle-Tracking Simulations ..........................................................................................................38

Model Calibration ...............................................................................................................................40

Parameter Sensitivity ...............................................................................................................41

Parameter Adjustments ...........................................................................................................41

Water-Level Altitudes ...............................................................................................................43

Spring Discharge ......................................................................................................................46

Age-Tracer Concentrations .....................................................................................................46

Model Results .....................................................................................................................................47

Simulated Groundwater Flow .................................................................................................47

Simulated Water Budget .........................................................................................................48

Simulated Zones of Contribution, Areas Contributing Recharge, and Water 

Particle Ages ................................................................................................................49

Supply-Well Vulnerability to Natural and Anthropogenic Contaminants .................................54

Model Uncertainties and Limitations .............................................................................................55

Summary .......................................................................................................................................................57

References Cited .........................................................................................................................................60
vi

Figures

1. Map showing location of regional-scale and local-scale model areas, Edwards 

aquifer segments, and physiographic regions, San Antonio region, Texas ......................3

2. Map showing location of regional-scale and local-scale model areas, 

hydrogeologic zones, and catchment area (upper parts of stream basins that 

contribute recharge) of the Edwards aquifer, San Antonio region, Texas .........................5

3. Map showing local-scale study area and locations of public-supply wells, 

monitoring wells, and tritium observation wells for the local-scale model, San 

Antonio region, Texas ..................................................................................................................7

4. Map showing model grid, boundary conditions, and simulated subzones of the 

recharge zone of the Edwards aquifer for the local-scale model, San Antonio 

region, Texas .................................................................................................................................8

5. Graph showing daily mean water-level altitudes from continuous water-level 

recorders in monitoring wells in the local-scale study area, September 12, 2007, to 

February 9, 2010, San Antonio region, Texas ........................................................................10

6. Map showing local-scale study area and locations of observation wells used to 

monitor water-level altitudes for inclusion in the local-scale model, San Antonio 

region, Texas ...............................................................................................................................11

7. Graphs showing A, annual groundwater withdrawals for San Antonio Water 

System wells, and B, estimated annual groundwater recharge to the Edwards 

aquifer in the local-scale study area, 1969–2009, San Antonio region, Texas ................13

8. Graphs showing measured water-level altitudes in well W38 (Bexar County index 

well, J–17) for A, November 12, 1932, to February 28, 2010, and B, January 1, 2000, 

to February 28, 2010, San Antonio region, Texas ..................................................................14

9. Graphs showing measured water-level altitudes, San Antonio region, Texas. 

A, Well W32, January 24, 2000, to March 3, 2010. B, Well W25, January 24, 2000, to 

July 22, 2009. C, Well W4, January 26, 2000, to February 24, 2010 .....................................16

10. Chart showing correlation of Cretaceous stratigraphic units and hydrogeologic 

units and their relative permeabilities in the San Antonio region, Texas .........................19

11. Map showing thickness and measured potentiometric surface of the Edwards 

aquifer in the local-scale study area, October 27 to November 2, 2001, San Antonio 

region, Texas ...............................................................................................................................20

12. Map showing locations and displacements of faults simulated in the local-scale 

model, San Antonio region, Texas ..........................................................................................21

13. Conceptual diagram showing generalized north to south hydrogeologic section 

and potential paths of groundwater flow for the local-scale study area, San Antonio 

region, Texas ...............................................................................................................................26

14. Map showing locations of groundwater withdrawal wells in the local-scale study 

area, San Antonio region, Texas .............................................................................................29

15. Conceptual diagrams showing generalized hydrogeologic sections and measured 

and simulated tritium concentrations in the local-scale study area, San Antonio 

region, Texas ...............................................................................................................................32

16. Map showing distribution of calibrated horizontal hydraulic conductivity in 

hydrogeologic units 2–4, 6–8, and 10–11 in the local-scale model, San Antonio 

region, Texas ...............................................................................................................................35

17. Map showing distribution of calibrated horizontal hydraulic conductivity in 

hydrogeologic units 5 and 9 in the local-scale model, San Antonio region, Texas ........37

18. Map showing distribution of calibrated horizontal anisotropy in the local-scale 

model, San Antonio region, Texas ..........................................................................................39

19. Graph showing composite sensitivity of the parameters used to calibrate the 

local-scale model, San Antonio region, Texas .....................................................................42
20. Map showing simulated potentiometric surface and water-level residuals for the 

local-scale model, San Antonio region, Texas .....................................................................44

21. Graph showing simulated relative to measured water-level altitudes for the localscale model, steady-state simulation, San Antonio region, Texas ....................................45

22. Graph showing simulated relative to measured tritium concentrations for the localscale model, steady-state simulation, San Antonio region, Texas ....................................47

23. Graph showing simulated relative to measured tritium concentrations in the 

selected public-supply well and monitoring wells for the local-scale model, 

steady-state simulation, San Antonio region, Texas ...........................................................48

24. Schematic diagram showing simulated water-budget components for the localscale model, steady-state simulation, San Antonio region, Texas ....................................49

25. Map showing simulated areas contributing recharge, age of water particles 

derived from simulated particle traveltimes, and particle pathlines for the selected 

public-supply well, San Antonio region, Texas .....................................................................50

26. Map showing simulated areas contributing recharge, age of water particles 

derived from simulated particle traveltimes, and particle pathlines for the 

Zarzamora monitoring wells, San Antonio region, Texas ...................................................51

27. Map showing simulated areas contributing recharge, age of water particles 

derived from simulated particle traveltimes, and particle pathlines for the 

Timberhill monitoring wells, San Antonio region, Texas .....................................................52

28. Graph showing simulated age of water particles reaching the selected publicsupply well, San Antonio region, Texas .................................................................................54

29. Graph showing simulated time series of hypothetical contaminant concentrations 

at the selected public-supply well based on 30 years of contaminant input (at 

relative concentration of 1) in the simulated areas contributing recharge, San 

Antonio region, Texas ................................................................................................................55

Tables

1. Summary of groundwater wells used in the local-scale model, San Antonio region, 

Texas ............................................................................................................................................66

2. Summary of water-level measurements obtained from monitoring and observation 

wells used in the local-scale model, San Antonio region, Texas ......................................69

3. Hydraulic properties for the Edwards aquifer, San Antonio region, Texas ......................71

4. Estimated recharge rates, by recharge subzone, in the local-scale model area 

during 2001, San Antonio region, Texas .................................................................................72

5. Mean daily and mean annual groundwater-withdrawal rates from municipal, 

industrial, irrigation, and livestock wells in the local-scale study area during 2001, 

San Antonio region, Texas .......................................................................................................73

6. Measured and simulated water-level altitudes and springflows and the differences 

between measured and simulated water-level altitudes and springflows (residuals) 

for the local-scale model, steady-state simulation, San Antonio region, Texas .............84

7. Hydrogeologic units used in the local-scale model, San Antonio region, Texas ............87

8. Summary of specified flux by model boundary in the local-scale model, San Antonio 

region, Texas ...............................................................................................................................87

9. Initial and calibrated values for hydraulic conductivity parameters used in the 

local-scale groundwater-flow and particle-tracking simulations, San Antonio 

region, Texas ...............................................................................................................................88

10. Initial and calibrated values for additional parameters used in the local-scale 

groundwater-flow and particle-tracking simulations, San Antonio region, Texas .........89

vii
viii

11. Measured and simulated tritium concentrations and the differences between 

measured and simulated tritium concentrations (residuals) for the local-scale 

model, steady-state simulation, San Antonio region, Texas ..............................................90

12. Simulated annual water budget for the local-scale model, steady-state simulation, 

San Antonio region, Texas .......................................................................................................92

13. Simulated particle ages, minimum, mean, and maximum at monitoring wells and 

at the selected public-supply well, San Antonio region, Texas .........................................93

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2

) 0.0002471 acre 

hectare (ha) 2.471 acre

square hectometer (hm2

) 2.471 acre

square kilometer (km2

) 247.1 acre

square centimeter (cm2

) 0.001076 square foot (ft2)

square meter (m2

) 10.76 square foot (ft2) 

square centimeter (cm2

) 0.1550 square inch (in2) 

square hectometer (hm2

) 0.003861 section (640 acres or 1 square 

mile)

hectare (ha) 0.003861 square mile (mi2

) 

square kilometer (km2

) 0.3861 square mile (mi2)

Volume

cubic meter (m3

) 6.290 barrel (petroleum, 1 barrel = 42 

gal)

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

cubic meter (m3

) 264.2 gallon (gal) 

cubic decimeter (dm3

) 0.2642 gallon (gal) 

cubic meter (m3

) 0.0002642 million gallons (Mgal) 

cubic centimeter (cm3

) 0.06102 cubic inch (in3) 

cubic decimeter (dm3

) 61.02 cubic inch (in3) 
ix

Multiply By To obtain

liter (L) 61.02 cubic inch (in3

) 

cubic decimeter (dm3

) 0.03531 cubic foot (ft3) 

cubic meter (m3

) 35.31 cubic foot (ft3)

cubic meter (m3

) 1.308 cubic yard (yd3) 

cubic kilometer (km3

) 0.2399 cubic mile (mi3) 

cubic meter (m3

) 0.0008107 acre-foot (acre-ft) 

cubic hectometer (hm3

) 810.7 acre-foot (acre-ft) 

Flow rate

cubic meter per second (m3

/s) 70.07 acre-foot per day (acre-ft/d)

cubic meter per minute (m3/min) 0.000811 acre-foot per minute (acre-ft/min)

cubic meter per year (m3

/yr) 0.000811 acre-foot per year (acre-ft/yr) 

cubic hectometer per year (hm3

/

yr)

811.03 acre-foot per year (acre-ft/yr)

meter per second (m/s) 3.281 foot per second (ft/s) 

meter per minute (m/min) 3.281 foot per minute (ft/min) 

meter per hour (m/hr) 3.281 foot per hour (ft/hr)

meter per day (m/d) 3.281 foot per day (ft/d)

meter per year (m/yr) 3.281 foot per year ft/yr) 

cubic meter per second (m3

/s) 35.31 cubic foot per second (ft3/s)

cubic meter per second per 

square kilometer [(m3

/s)/km2]

91.49 cubic foot per second per square 

mile [(ft3/s)/mi2]

cubic meter per day (m3

/d) 35.31 cubic foot per day (ft3/d) 

liter per second (L/s) 15.85 gallon per minute (gal/min) 

cubic meter per day (m3

/d) 264.2 gallon per day (gal/d) 

cubic meter per day per square

kilometer [(m3

/d)/km2]

684.28 gallon per day per square mile 

[(gal/d)/mi2]

cubic meter per second (m3

/s) 22.83 million gallons per day (Mgal/d) 

cubic meter per day per square

kilometer [(m3

/d)/km2]

0.0006844 million gallons per day per square 

mile [(Mgal/d)/mi2]

cubic meter per hour (m3

/h) 39.37 inch per hour (in/h)

centimeter per year (cm/yr) 0.3937 inch per year (in/yr)

millimeter per year (mm/yr) 0.03937 inch per year (in/yr) 

kilometer per hour (km/h) 0.6214 mile per hour (mi/h)

Specific capacity

liter per second per meter 

[(L/s)/m]

4.831 gallon per minute per foot [(gal/

min)/ft]

Hydraulic conductivity

meter per day (m/d) 3.281 foot per day (ft/d) 

Hydraulic gradient

meter per kilometer (m/km) 5.27983 foot per mile (ft/mi) 

Transmissivity*

meter squared per day (m2

/d) 10.76 foot squared per day (ft2/d) 

Application rate

kilograms per hectare per year 

[(kg/ha)/yr]

0.8921 pounds per acre per year 

[(lb/acre)/yr]
x

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88) and to the National Geodetic Vertical Datum of 1929 (NGVD 29) for Bexar County 

index well (J–17).

Altitude, as used in this report, refers to distance above the vertical datum.

*Transmissivity: The standard unit for transmissivity is cubic foot per day per square foot times 

foot of aquifer thickness [(ft3

/d)/ft2]ft. In this report, the mathematically reduced form, foot 

squared per day (ft2/d), is used for convenience.

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 

25°C).

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).
Abstract

In 2006, a public-supply well in San Antonio, Texas, 

was selected for intensive study to assess the vulnerability 

of public-supply wells in the Edwards aquifer to contamination by a variety of compounds. A local-scale, steady-state, 

three-dimensional numerical groundwater-flow model was 

developed and used in this study to evaluate the movement of 

water and solutes from recharge areas to the selected publicsupply well. Particle tracking was used to compute flow paths 

and advective traveltimes throughout the model area and to 

delineate the areas contributing recharge and zone of contribution for the selected public-supply well. 

The local-scale model grid has a finer vertical discretization than do previous regional Edwards aquifer models and 

incorporates refined parameter zones corresponding with 

multiple (10) hydrogeologic units representing the Edwards 

aquifer. In the Edwards aquifer, high matrix porosity and permeability likely are overshadowed by high permeability developed in structurally influenced karstic conduit systems that 

transmit water into, through, and out of the aquifer system. 

The complexity of the aquifer system in the local-scale study 

area is further increased by numerous faults with varying 

vertical displacements. The extensive faulting results in the 

juxtaposition of hydrogeologic units with differing hydraulic 

properties and has appreciable effects on groundwater flow 

in the Edwards aquifer. The local-scale model simulations 

use the MODFLOW Hydrogeologic-Unit Flow Package and 

include two hydrogeologic units with high hydraulic conductivities (one or more orders of magnitude higher than for 

the other simulated hydrogeologic units) that are intended to 

simulate fast flow paths attributable to karst features. The two 

“conduit” hydrogeologic units of the Edwards aquifer represent the lower 8 meters of the leached and collapsed members 

and the Kirschberg evaporite member of the Edwards Group. 

The MODFLOW Horizontal-Flow Barrier Package was used 

to simulate faults in the local-scale model. The assumption 

was made that the degree to which a fault acts as a barrier to 

groundwater flow is proportional to the fault displacement. 

The final calibrated hydraulic-conductance values ranged from 

0.01 to 0.2 per day for fault displacements ranging from 0 to 

more than 100 percent of the total aquifer thickness.

The calibrated steady-state simulation generally reproduces the spatial distribution of measured water-level altitudes. Simulated water-level altitudes were within 9.0 meters 

of measured water-level altitudes at 74 of the 84 wells used as 

targets for the local-scale model for the calibrated steady-state 

simulation. The overall mean absolute difference between 

simulated and measured water-level altitudes is 4.2 meters, 

and the mean algebraic difference is 1.9 meters. The simulated 

springflow for San Antonio Springs was 7.7 percent greater 

and for San Pedro Springs was 4.2 percent less than the 

median measured springflow. Simulated tritium concentrations 

were within 0.14 tritium units of measured tritium concentrations for 11 of the 13 local-scale study tritium observations 

from the 10 local-scale study wells used to calibrate the 

steady-state local-scale model, with a mean absolute difference between simulated and measured tritium concentrations 

of 0.11 tritium units and a mean algebraic difference of -0.04 

tritium units. Simulated tritium concentrations in the selected 

public-supply well during November 2007 were within 0.09 

tritium units of the measured concentrations, with the exception of the shallowest observation from the well. 

The steady-state simulation water budget indicates that 

recharge occurring in the local-scale study area accounts for 

31.8 percent of the sources of water to the Edwards aquifer in 

the local-scale model area and that inflow through the model 

boundaries contributes 68.2 percent. Most of the flow into the 

local-scale model area through the model boundaries occurs 

through the western and southern boundaries, 58.2 and 39.6 

percent, respectively. The largest discharges from the Edwards 

aquifer in the local-scale model area are boundary outflow 

(71.4 percent) and withdrawals by wells (24.9 percent). Most 

of the flow out of the local-scale model area through the 

model boundaries occurs through the southern and eastern 

boundaries, 54.2 and 39.6 percent, respectively. 

The simulated zones of contribution for the selected 

public-supply well, Timberhill well nest, and Zarzamora well 

nest extend to the north, northeast, and northwest from each 

site in the confined zone of the aquifer into the recharge zone, 

where all recharge to the aquifer occurs. The area contributing 

recharge for the selected public-supply well has the greatest 

extent. The area contributing recharge for the Timberhill well 

nest encompasses approximately the western one-half of the 

Simulations of Groundwater Flow and Particle-Tracking 

Analysis in the Zone of Contribution to a Public-Supply 

Well in San Antonio, Texas 

By Richard J. Lindgren, Natalie A. Houston, MaryLynn Musgrove, Lynne S. Fahlquist, and Leon J. Kauffman
2 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

area contributing recharge for the selected public-supply well, 

and that for the Zarzamora well nest encompasses approximately the eastern two-thirds of the area contributing recharge 

for the selected public-supply well.

Simulated particle ages ranged from less than 1 day to 

more than 1,900 years in the 10 local-scale study wells (13 

local-scale study tritium observations) used to calibrate the 

local-scale model. The simulated mean particle ages for the 

tritium observations representing selected well depths (shallow, intermediate, and deep) ranged from 2.5 to 15 years. The 

minimum (youngest) mean particle ages for the selected public-supply well and the Timberhill monitoring wells were for 

the intermediate well depth, while the youngest mean particle 

age for the Zarzamora monitoring wells was for the intermediate and deep well depth. The maximum (oldest) mean particle 

ages for the selected public-supply well and the Zarzamora 

monitoring wells were for the shallow well depth. The mean 

of simulated particle ages for tritium observations representing 

well depths open to the simulated conduit hydrogeologic units 

was 3.8 years, whereas the mean of simulated particle ages for 

tritium observations representing well depths not open to the 

simulated conduit hydrogeologic units was 9.6 years.

The effect of short-circuit pathways, for example karst 

conduits, in the flow system on the movement of young water 

to the selected public-supply well could greatly alter contaminant arrival times compared to what might be expected from 

advection in a system without short circuiting. In a forecasting 

exercise, the simulated concentrations showed rapid initial 

response at the beginning and end of chemical input, followed 

by more gradual response as older water moved through the 

system. The nature of karst groundwater flow, where flow 

predominantly occurs via conduit flow paths, could lead to 

relatively rapid water quality responses to land-use changes. 

Results from the forecasting exercise indicate that timescales 

for change in the quality of water from the selected publicsupply well could be on the order of a few years to decades for 

land-use changes that occur over days to decades, which has 

implications for source-water protection strategies that rely on 

land-use change to achieve water-quality objectives.

Introduction

Groundwater accounts for nearly all of the water supply 

in south-central Texas, and the Edwards aquifer is the principal source. The Edwards aquifer in the Balcones fault zone of 

south-central Texas (fig. 1) is one of the most permeable and 

most productive aquifers in the world (Maclay, 1995). The 

aquifer consists of regionally extensive carbonate rocks that 

crop out within the Edwards Plateau and the Balcones fault 

zone and underlie the Gulf Coastal Plain. Designated a solesource aquifer in the San Antonio and Austin, Tex., regions 

by the U.S. Environmental Protection Agency (2006), the 

aquifer is critical to farming and ranching economies west of 

San Antonio and recreational economies northeast of the city. 

The headwaters of the Comal and San Marcos Rivers consist 

of groundwater discharged from the Comal and San Marcos 

Springs, respectively, that issue from the Edwards aquifer; 

these springs support five federally listed and three candidate 

endangered species (Edwards Aquifer Research and Data 

Center, 2010). Withdrawals from the Edwards aquifer meet the 

water-supply needs of more than 2 million people in the San 

Antonio region. In 2003, water use from the Edwards aquifer 

in Atascosa, Bexar, Comal, Hays, Kinney, Medina, Travis, 

and Uvalde Counties was estimated to be 460.7 million cubic 

meters (m3

) (Texas Water Development Board, 2008). Municipal withdrawals accounted for about 70 percent, and irrigation 

accounts for 27 percent; the remaining 3 percent included 

manufacturing, steam electric power generation, mining, and 

livestock (Texas Water Development Board, 2008). Bexar 

and Uvalde Counties are the largest producers of groundwater 

from the Edwards aquifer in south-central Texas; use in Bexar 

County is mostly municipal, and use in Uvalde County is 

mostly irrigation (Texas Water Development Board, 2008).

Crandall and others (2009, p. 1) explained, “sustainability 

of groundwater quality for public supply requires monitoring 

and understanding of the mechanisms controlling the vulnerability of public-supply wells to contamination.” Burow and 

others (2008, p. 2) wrote, 

Aquifer and public-supply-well vulnerability to contamination is a function of the intrinsic conditions 

of an aquifer, such as depth to water, flow-system 

confinement, recharge rate, horizontal and vertical 

hydraulic conductivity, porosity, pumping rate, and 

geochemical conditions (Focazio and others, 2002). 

Public-supply-well vulnerability is determined 

by assessing aquifer susceptibility and potential 

contaminant sources overlying or within the area 

contributing recharge to the well (Franke and others, 

1998; Focazio and others, 2002). The word ‘contaminant’ is defined as any natural or anthropogenic 

chemical or physical property of the groundwater 

resource in question that could threaten human 

health, interfere with water-treatment practices 

(Focazio and others, 2002), or cause other problems. 

The definition of “contaminant” is the same in this report.

In 2001, the U.S. Geological Survey (USGS) National 

Water-Quality Assessment (NAWQA) Program, as part of a 

broad program to provide an understanding of water-quality 

conditions across the United States, began an intensive study 

to assess the vulnerability of public-supply wells to contamination from a variety of compounds (Eberts and others, 2005). 

As part of the NAWQA Program, the Transport of Anthropogenic and Natural Contaminants (TANC) study is focusing 

on the transport and chemical processes of selected naturally 

occurring and anthropogenic contaminants from urban and 

agricultural sources within that part of the groundwater system 

contributing water to public-supply wells. Eberts and others (2005, p. 1) wrote, “because subsurface processes and 

management practices differ among aquifers and public-water 

systems, public-supply wells in different parts of the Nation 

are not equally vulnerable to contamination, even where 
Introduction 3

Figure 1. Location of regional-scale and local-scale model areas, Edwards aquifer segments, and physiographic regions, San Antonio 

region, Texas.

UNITED STATES

MEXICO

TEXAS

COAHUILA

LLANO COUNTY

BURNET

COUNTY

BLANCO

COUNTY

WILLIAMSON

COUNTY

BASTROP

COUNTY

TRAVIS

 COUNTY

HAYS

COUNTY

COMAL

COUNTY

KENDALL

COUNTY

GILLESPIE

COUNTY

KERR

COUNTY 

EDWARDS COUNTY

REAL

COUNTY 

BANDERA

COUNTY

BEXAR

COUNTY

GUADALUPE

COUNTY

CALDWELL

COUNTY

GONZALES

COUNTY

WILSON

COUNTY

MEDINA COUNTY

UVALDE COUNTY

KINNEY

COUNTY 

MAVERICK

COUNTY 

ZAVALA

COUNTY 

FRIO

COUNTY

ATASCOSA

COUNTY

LA SALLE COUNTY

DIMMIT COUNTY 

Llano Burnet

Fredericksburg

Johnson

City

Dripping

Springs

Georgetown

Round Rock

Austin

Buda Bastrop

Gonzales

Luling

Lockhart

New

Braunfels

San Marcos

Wimberley

Boerne

Bandera

Kerrville

Leakey

Rocksprings

Brackettville

Uvalde

Knippa Hondo

Poteet

San 

Antonio 

Floresville

Pleasanton

Jourdanton

Pearsall

Dilley

La

Pryor

Crystal

City Eagle Pass

Carrizo

Springs

Cotulla

Seguin

Comfort

Blanco

Batesville

Kyle

B A L C O N E S F A U L T Z O N E

Lake

 Travis

Blanco River

Canyon 

Lake

Creek

Medina

Lake

Pedernales

River

San

Marcos

River

Guadalupe

River

Colorado River

Nueces

River

Frio

River

Blanco

Creek

Dry

Frio

River

West

Nueces

River

Medina

River

San Antonio River

Cibolo

Creek

Leona

River

Guadalupe River

Sabinal River

Dry Comal

Seco Creek

Hondo Creek

Colorado River

River Frio

Verd e Cr

RIO

BRAVO

RIO GRANDE

PurgatoryCr

San Pedro Springs

San Antonio Springs

Hueco Springs

Comal Springs

Las Moras Springs

Leona Springs

San Marcos

Springs

Barton

 Springs 

0 10 20 30 KILOMETERS

0 10 20 30 MILES

29°

30°

31°

98°

99°

100°

Base from U.S. Geological Survey and

City of Austin digital data, 2010,

Albers equal area projection, standard parallels

29°30' North and 45°30' North, central meridian 100° West

North American Datum of 1983

G U L F C O A S T A L P L A I N

E D W A R D S P L A T E A U

Hill Country

MAVERICK BASIN

DEVILS RIVER

TREND

SAN MARCOS

PLATFORM

T E X A S

LOCATION MAP

Regional-scale

model boundary 

Local-scale

study area 

Local-scale

model boundary 

EXPLANATION

Regional-scale model area

 Active regional-scale model area—Coincides

 with South-Central Texas regional TANC study

 area (Lindgren and others, 2011) and Edwards

 aquifer segments

 San Antonio segment of the Edwards aquifer

 Barton Springs segment of the Edwards

 aquifer

 Inactive regional-scale model area

Local-scale study area

Local-scale model boundary

Regional-scale model boundary

Depositional province (modified from

 Maclay, 1995, fig. 2)

Boundary of Balcones fault zone

Balcones escarpment (modified from

 Abbott and Woodruff, 1986, fig. 1)

Groundwater divide

Spring

TANC, Transport of anthropogenic and natural contaminants
4 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

similar contaminant sources exist.” The TANC study—which 

is being conducted at multiple locations across the Nation, 

including south-central Texas (Lindgren and others, 2011)—is 

identifying and comparing these important differences in a 

complementary set of aquifer systems, urban settings, and 

public-water systems based on data that were collected and 

analyzed by using consistent methods. To perform this analysis across multiple scales, the TANC study design called for 

regional-scale and local-scale study areas and the development 

of nested numerical groundwater-flow models. The northern 

part of Bexar County in the San Antonio region is one of the 

selected sites for a local-scale comprehensive study, which is 

the subject of this report. Data collection for the local-scale 

study was completed in February 2010. Two regional-scale 

groundwater-flow models, differing only in their hydraulic 

conductivity distributions, were developed for the Edwards 

aquifer in south-central Texas for the regional-scale TANC 

study and were used to estimate areas contributing recharge 

to many public-supply wells (Lindgren and others, 2011). 

A detailed local-scale model within the boundaries of the 

regional-scale models was then developed to simulate groundwater flow within the area contributing recharge to a selected 

public-supply well in the local-scale study area. 

Purpose and Scope

The purpose of this report is to present the dominant processes affecting the vulnerability to contamination of a publicsupply well in the Edwards aquifer in the City of San Antonio 

in northern Bexar County in south-central Texas. This report 

includes a brief description of the design of the local monitoring well network and methods of data collection and analysis. 

Groundwater ages and the distribution of selected constituents 

are used for developing basic interpretations of groundwater 

recharge and discharge patterns and pathways.

This report documents the construction and calibration 

of a local-scale groundwater-flow model. The local-scale 

model incorporates selected hydraulic properties and boundary conditions from previously developed regional-scale 

models developed for the South-Central Texas regional 

TANC study (Lindgren and others, 2011) (fig. 2). The results 

of steady-state simulations of groundwater flow and traveltimes conducted for the local-scale model are also described. 

The steady-state simulations are not intended to exactly 

match transient hydrologic conditions and transport characteristics in the karstic Edwards aquifer system but rather are 

meant to provide insight into the types of processes that are 

important in a system such as this one. The local-scale model 

was used to simulate approximate traveltimes and flow paths 

for potential contaminants and, thereby, address overarching 

NAWQA TANC objectives to (1) assess the effects of natural factors and human activities on contaminant occurrence 

in public-supply wells (PSWs), and (2) provide information 

to managers so they can develop more effective strategies to 

deal with contamination problems affecting selected PSWs 

throughout the United States. 

This report is intended to serve as a foundation for model 

synthesis analyses on which results can be compared between 

this TANC local-scale study area and other TANC study 

units in Connecticut, California, Nebraska, Florida, and New 

Mexico. Results of synthesis analyses and descriptions of 

other TANC study units are not included in this report.

Previous Groundwater-Flow Models

A number of numerical groundwater-flow models have 

been constructed for the San Antonio and (or) Barton Springs 

segments of the Edwards aquifer. Lindgren and others (2009) 

described and evaluated six regional-scale groundwater-flow 

models that are published and generally accepted by the 

water-resources community. Two of the models developed in 

MODFLOW-2000 (Harbaugh and others, 2000)—the Edwards 

aquifer ones (Lindgren and others, 2004; Lindgren, 2006) 

(hereinafter, the “original Edwards aquifer models”)—were 

modified for the South-Central Texas regional TANC study 

(Lindgren and others, 2011) to simulate groundwater flow in 

the South-Central Texas regional TANC study area (fig. 2). 

The original Edwards aquifer models were calibrated for two 

hydraulic conductivity distributions. A numerical groundwater-flow model (hereinafter, the “conduit-flow Edwards 

aquifer model”) of the karstic Edwards aquifer in south-central 

Texas was developed for a study conducted during 2000–3 

on the basis of a conceptualization emphasizing conduit 

development and conduit flow (Lindgren and others, 2004). 

Uncertainties regarding the degree to which conduits pervade 

the Edwards aquifer and influence groundwater flow, as well 

as other uncertainties inherent in simulating conduits, raised 

the question of whether a model based on the conduit-flow 

conceptualization was the optimum model for the Edwards 

aquifer. Accordingly, a model with an alternative hydraulic 

conductivity distribution without conduits was developed in a 

study conducted during 2004–5 (Lindgren, 2006). The hydraulic conductivity distribution for the Edwards aquifer model 

without conduits (hereinafter, the “diffuse-flow Edwards 

aquifer model”) is based primarily on a conceptualization in 

which flow in the aquifer predominantly is through a network 

of numerous small fractures and openings.

The original Edwards aquifer models (Lindgren and 

others, 2004; Lindgren, 2006) were modified for the SouthCentral Texas regional TANC study (Lindgren and others, 

2011) to a finer discretization, both horizontally and vertically, 

and updated to include the 2001–3 time period. Two model 

layers were used to represent the multiple hydrogeologic zones 

that compose the Edwards aquifer, compared to the one model 

layer for the original Edwards aquifer models, and the dimensions of the grid cells were reduced by one-half. The rediscretized regional-scale groundwater-flow models calibrated 

for the South-Central Texas regional TANC study (hereinafter, 

the “rediscretized regional Edwards aquifer models”) cover 

about 41,920 square kilometers (km2

)in south-central Texas 

and consist of 2 layers, 1,400 columns, and 740 rows, with the 

dimensions of the grid cells being uniformly 201.2 meters (m) 
Introduction 5

Figure 2. Location of regional-scale and local-scale model areas, hydrogeologic zones, and catchment area (upper parts of stream 

basins that contribute recharge) of the Edwards aquifer, San Antonio region, Texas.

CATCHMENT AREA

UNITED STATES

MEXICO

TEXAS

COAHUILA

LLANO COUNTY

BURNET

COUNTY

BLANCO

COUNTY

WILLIAMSON

COUNTY

BASTROP

COUNTY

TRAVIS

 COUNTY

HAYS

COUNTY

COMAL

COUNTY

KENDALL

COUNTY

GILLESPIE

COUNTY

KERR

COUNTY 

EDWARDS COUNTY

REAL

COUNTY 

BANDERA

COUNTY

BEXAR

COUNTY

GUADALUPE

COUNTY

CALDWELL

COUNTY

GONZALES

COUNTY

WILSON

COUNTY

MEDINA COUNTY

KINNEY UVALDE COUNTY

COUNTY 

MAVERICK

COUNTY 

ZAVALA

COUNTY 

FRIO

COUNTY

ATASCOSA

COUNTY

LA SALLE COUNTY

DIMMIT COUNTY 

1,000 mg/L

10,000 mg/L

1,000 mg/L

10,000 mg/L

1

2

3 4

5

6

7

8

9

10

NUECES RIVER BASIN SAN ANTONIO RIVER BASIN

GUADALUPE RIVER BASIN

San Pedro Springs

San Antonio Springs

Hueco Springs

Comal Springs

Las Moras Springs

Leona Springs

San Marcos

Springs

Barton

 Springs 

0 10 20 30 KILOMETERS

0 10 20 30 MILES

29°

30°

31°

98°

99°

100°

Base from U.S. Geological Survey and 

City of Austin digital data, 2010,

Albers equal area projection, standard parallels

29°30' North and 45°30' North, central meridian 100° West

North American Datum of 1983

Lake

 Travis

Blanco River

Canyon 

Lake

Creek

Medina

Lake

Pedernales River

San

Marcos

River

Guadalupe

River

Nueces

River

Frio

River

Blanco

Creek

Dry

Frio

River

West

Nueces

River

River

SanAntonio

River

Cibolo

Creek

Leona

River

RIO

BRAVO

Guadalupe River

Sabinal River

Dry Comal

Seco Creek

Hondo Creek

Colorado River

River Frio

Verd e Cr

Salado

Creek

Medina

PurgatoryCr

Onion Creek

Barton Creek

Williamson

Creek

Bear Creek

Slaughter

 Creek

Colorado River

RIO GRANDE

EXPLANATION

Regional-scale model area

 Active regional-scale model area—Coincides

 with South-Central Texas regional TANC

 study area (Lindgren and others, 2011) and

 Edwards aquifer segments

 Recharge zone (outcrop) of the Edwards 

 aquifer (modified from Puente, 1978)

 Freshwater zone of the Edwards aquifer

 Freshwater/saline-water transition zone

 of the Edwards aquifer

Line of equal dissolved solids

 concentration, in milligrams

 per liter (mg/L) (A.L. Schultz,

 consultant, written commun.,

 2000)

Major river basin boundary

Stream basin or contributing

 area boundary

Groundwater divide

Spring

 Inactive regional-scale model

 area and hydrogeologic zones

 Catchment area (underlain by 

 Edwards-Trinity and Trinity

 aquifers)

 Saline zone

Local-scale study area

Local-scale model boundary

Regional-scale model boundary

1,000 mg/L

TANC, Transport of anthropogenic and natural

 contaminants

Stream basin or contributing area

 Nueces-West Nueces River Basin

 Frio-Dry Frio River Basin

 Sabinal River Basin

 Area between Sabinal and Medina River Basins

 (includes Hondo and Seco Creeks)

 Medina River Basin

 Area between Medina River Basin and Cibolo-Dry Comal Creek Basins

 (includes Salado Creek)

 Cibolo and Dry Comal Creek Basins

 Guadalupe River Basin

 Blanco River Basin (includes Blanco River and

 Purgatory Creek)

 Barton Springs segment contributing area (includes Barton,

 Williamson, Slaughter, Bear, and Onion Creeks) 

1

2

3

4

5

6

7

8

9

10
6 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

along rows and columns (Lindgren and others, 2011). The 

rediscretized regional Edwards aquifer models (Lindgren 

and others, 2011) were calibrated by using two different 

hydraulic conductivity distributions, based on conduit flow 

or diffuse flow, as was done for the original Edwards aquifer 

models (Lindgren and others, 2004; Lindgren, 2006). The two 

rediscretized regional Edwards aquifer models are hereinafter referred to as the “conduit-flow rediscretized regional 

Edwards aquifer model” and the “diffuse-flow rediscretized 

regional Edwards aquifer model” when they are discussed 

separately.

The initial boundary conditions and hydraulic properties 

used in the rediscretized regional Edwards aquifer models 

(Lindgren and others, 2011) were the same as those used in the 

original Edwards aquifer models (Lindgren and others, 2004; 

Lindgren, 2006) but were adjusted to conform to the smaller 

grid size in the rediscretized regional Edwards aquifer models. 

The rediscretized regional Edwards aquifer models (both 

the conduit-flow and diffuse-flow models) were calibrated 

for steady-state and transient conditions. Average stresses 

(recharge and pumpage) during 2001, a representative year 

for the recent time period (2000–3), were used to simulate 

steady-state conditions. The transient simulation period for the 

rediscretized regional Edwards aquifer models was 2000–3, 

with 48 monthly stress periods. The steady-state and transient 

simulations for the rediscretized regional Edwards aquifer 

models were calibrated to 2000–3 conditions, primarily by 

using a trial-and-error approach, by varying the simulated 

recharge rates and hydraulic conductivities. The rediscretized 

regional Edwards aquifer models developed for the SouthCentral Texas regional TANC study are discussed in Lindgren 

and others (2011).

Description of Study Area

In 2006, a PSW in San Antonio, Tex., was selected out 

of 39 wells that were sampled for the NAWQA Program’s 

Source Water-Quality Assessment program and the NAWQA 

TANC study in the San Antonio region as the focus of a study 

of processes influencing movement of contaminants between 

recharge areas and the PSW. Water samples from this selected 

public-supply well (hereinafter, the “selected PSW”) were 

initially collected and analyzed in 2004 and 2005 for a wide 

suite of chemical and physical constituents. Results from the 

analyses showed the presence of multiple contaminants, but 

concentrations were below drinking-water standards. The most 

frequently detected chemicals were the pesticide compounds 

atrazine, deethylatrazine, simazine, and prometon and the 

volatile organic compounds chloroform and tetrachloroethylene (PCE). The construction and operational practices of the 

selected PSW are representative of many PSWs that use the 

Edwards aquifer for supplying the water for the population of 

San Antonio, which includes Bexar and Comal Counties. In 

addition, the water purveyor was willing to make available the 

selected PSW, which is one of their primary community watersystem PSWs. The combination of the detected constituents, 

cooperation of the city utility, and typical well construction 

and operational practices prompted the focus on the selected 

PSW for the local-scale study.

The local-scale study area, the focus of this report, is 

in Bexar and Medina Counties in south-central Texas and 

includes the northwestern part of San Antonio (fig. 1). The 

local-scale study area includes about 2,844 km2 and is underlain by the Edwards aquifer. The Edwards aquifer underlies 

much of south-central Texas and provides the water supply 

for more than 2 million people in the San Antonio region. 

The local-scale study area is nested within the regional-scale 

study area, which coincides with the regional-scale model 

area (Lindgren and others, 2011). The local-scale study area 

includes the active area of the local-scale model and a small 

part of the catchment area north of the Edwards aquifer 

recharge zone (fig. 3). The local-scale study area and localscale model boundary were determined by using the rediscretized regional Edwards aquifer models, developed for the 

regional-scale TANC study (Lindgren and others, 2011), to 

identify the areas contributing recharge (ACR) of the selected 

PSW. The local-scale study area boundaries on the west and 

east were placed a short distance beyond the farthest western 

and eastern extents of the ACR of the selected PSW, as simulated by the rediscretized regional Edwards aquifer models, to 

minimize any potential effects of the model boundaries on the 

ACR simulated by the local-scale model. The southern boundary of the local-scale study area approximates the 1,000-milligrams-per-liter (mg/L) dissolved solids concentration line 

(updip boundary of the freshwater/saline-water transition 

zone) (fig. 2). The northern boundary of the local-scale study 

area ranges from less than 1 mile to about 10 miles north of 

the updip limit of the Edwards aquifer recharge zone (fig. 3). 

MODFLOW requires a rectangular area for the model 

grid (fig. 4). The extent of the local-scale study area is less 

than the extent of the local-scale model area because only 

part of the inactive local-scale model area (catchment area) is 

included in the local-scale study area. The active and inactive 

parts of the local-scale model area are shown in figure 4. The 

local-scale model area (fig. 4) is oriented with the regional 

direction of groundwater flow and the major faults in the Balcones fault zone to minimize error in cell-to-cell and boundary 

flows.

The local-scale study area includes part of the Edwards 

Plateau (southern margin of the plateau referred to as the 

“Hill Country”) and the comparatively flat Gulf Coastal Plain, 

which are separated by the Balcones escarpment (fig. 1). The 

Edwards aquifer is part of an aquifer system developed in 

thick and regionally extensive Lower Cretaceous-age carbonates that underlie large parts of Texas (Barker and Ardis, 1996, 

fig. 2). The Edwards aquifer is unconfined adjacent to and in 

the outcrop (recharge zone), where recharge occurs (fig. 2) 

(Puente, 1978). The water table is at depths generally greater 

than 30 m below the streambeds (Hovorka and others, 2004). 

The Edwards aquifer is confined in downdip parts of the Balcones fault zone, including the freshwater zone and the freshwater/saline-water transition zone (fig. 2). Groundwater flow 
Introduction 7

and aquifer properties are appreciably affected by the presence 

of faults and karst dissolution features. Karst features such as 

sinkholes, solution enlargement along fractures and bedding 

planes, caves, and springs are prevalent in the local-scale 

study area. In the outcrop (Edwards aquifer recharge zone), 

karst landforms include shallow, internally drained depressions; depressions of holes in creek bottoms; and small upland 

features such as sinkholes and solution-enlarged fractures 

(Hovorka and others, 2004). In addition, more than 400 caves 

have been inventoried in the Edwards aquifer outcrop (Veni, 

1988; Elliott and Veni, 1994; Clark and Morris, 2011). The 

Edwards aquifer is recharged predominantly through seepage 

from surface streams that flow onto the outcrop of the aquifer. 

Discharge from the aquifer is primarily from withdrawals by 

wells and springflow.

The climate in the local-scale study area is subtropical 

humid (Larkin and Bomar, 1983). Average annual rainfall is 

78.7 centimeters per year (cm/yr) at San Antonio. Months- to 

years-long droughts that strain water supplies and produce 

widespread crop failure commonly are followed by wet 

periods that include torrential rains and flash floods (Bomar, 

1994). A severe drought occurred during 1950–56, when 

rainfall at San Antonio was less than the 30-year (1961–90) 

normal (78.7 cm/yr) during each year of this 7-year span. 

Figure 3. Local-scale study area and locations of public-supply wells, monitoring wells, and tritium observation wells for the localscale model, San Antonio region, Texas.

See inset

below 

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

WQ1 # WQ2

Q12

Q9

Q11

Q18 Q13 Q15 Q14

Q21 Q23

Q24

Q22

Q20

Q16

Q17

Q19

Q30

Q32

Q31 Q35

Q34

Q33

Q26

Q25

Q27

Q28

Q29

Q37

Q36

Q10

Timberhill

well nest 

#

WQ5

WQ4

WQ3

W79

Q8

Q7

Q6

Q5

Q1–Q4

Zarzamora

well nest

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

C A T C H M E N T A R E A C A T C H M E N T A R E A

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

ESpring

Sampling site and number—See table 1

 Public-supply well

 Selected public-supply well

 Monitoring well

 Tritium observation well

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary (modified

 from Puente, 1978)

Freshwater/saline-water interface (1,000 milligrams per

 liter dissolved solids concentration) (A.L. Schultz, consultant,

 written commun., 2000)

EXPLANATION

#

Q6

Q1

WQ3

Q9

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10
Figure 4. Model grid, boundary conditions, and simulated subzones of the recharge zone of the Edwards aquifer for the local-scale model, San Anton

0 5 10 

0 5 10 15 20 

1

20

60

80

100

120

140

160

180

220

240

260

280

20

40

60

80

100

120

140

160

200

220

240

180

Columns

Rows

Hondo Creek

Medina

River

Verde

MedinaLake

Creek

Culebra Creek

Leon

Creek

Medio

Creek

Quihi

Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San 

Sp

1 2

(

A 3

(

A

(B

(B

(B

E

(B(

A

1

2

3

Active local-scale model area Confined zone of Edwards aquifer (or Edwards aquifer not at land surface) Recharge subzone Area between Sabinal and Medina Rivers Medina River Area between Medina River and Cibolo-Dry Comal CreekInactive local-scale model area Inactive local-scale model area included in local-scale study area Inactive local-scale model area not included in local-scale study areaFreshwater/saline-water interface (1,000 milligrams per liter dissolved solids concentration) (A.L. Schultz, consultant, written commun., 2000)Finite-difference gridLocal-scale study area boundaryUrban boundarySpringBoundary condition Specified-flux boundary; inflow from Trinity aquifer through northern boundary of recharge zone Specified-flux boundary; local-scale model boundary fluxes derived from diffuse-flow rediscretized regional Edwards aquifer model

EXPLANATION

Base from U.S. Geological Survey digital data,Texas Centric Mapping System-Albers equal area projectionNorth American Datum of 1983 

99°00'

29°45'

29°30'

29°15'

Hondo Castroville

San

Antonio

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

KENDALL COUNTY

MEDINA COUNTY

BANDERA COUNTY

C A T C H M E N T A R E A C A T C H M E N T A R E A

Area enlarged

Dry Comal Creek

Cibolo Creek

Sabinal River

Medin a River

LLANO

COUNTY

BURNETCOUNTY

BLANCOCOUNTY

WILLIAMSON

COUNTY

BASTROP

COUNTY

TRAVIS

COUNTY

HAYS

COUNTY

COMAL

COUNTY

KENDALL

COUNTY

GILLESPIECOUNTY

KERRCOUNTY 

EDWARDS COUNTY

REALCOUNTY BANDERA

COUNTY

BEXAR

COUNTY

GUADALUPE

COUNTY

CALDWELL

COUNTY

GONZALES

COUNTY

WILSONCOUNTY

MEDINACOUNTY

UVALDECOUNTY

KINNEYCOUNTY 

MAVERICKCOUNTY 

ZAVALACOUNTY 

FRIOCOUNTY

ATASCOSA

COUNTY

LA SALLECOUNTY

DIMMIT COUNTY 

Local-scale

study area 

Local-scale

model boundary 
Introduction 9

During 5 of those years, rainfall was two-thirds or less of the 

30-year normal. Storms can produce rapid runoff and recharge 

to the Edwards aquifer. During the 1970s and 1990s, rainfall in 

the region was generally greater than the 30-year normal rainfall; however, dry years (such as 1975 and 1996) periodically 

resulted in declines of water-level altitudes in the Edwards 

aquifer and below-average springflow.

The local-scale study area encompasses the upper parts 

of the Nueces and San Antonio River Basins (fig. 2). Surface 

water and groundwater in south-central Texas are uniquely 

interrelated. Fahlquist and Ardis (2004, p. 3) noted,

Springs and seeps discharge along impermeable 

zones of the Trinity aquifer in the deeply incised 

stream channels of the Edwards Plateau. These 

springs provide base flow to streams that flow southward and eastward from the plateau. As they flow 

across the highly permeable, fractured and faulted 

carbonate rocks of the Edwards aquifer in the Balcones fault zone, most streams lose all of their base 

flow as recharge to the Edwards aquifer.

Two large springs (San Pedro and San Antonio) issue 

from the confined part of the Edwards aquifer in the localscale study area (fig. 3).

Land use in the local-scale study area correlates with 

physiography. The rugged, thin-soiled terrain of the Edwards 

Plateau is largely undeveloped, and rangeland predominates. 

The flatter, thicker-soiled terrain of the Gulf Coastal Plain 

is better suited to growing crops—primarily hay, sorghum, 

wheat, corn, and oats. In 2001, land use (Homer and others, 

2001) in the local-scale study area, excluding the catchment 

area (north of the recharge zone), was characterized by 35.5 

percent rangeland, 27.9 percent forest, 23.1 percent urban, and 

11.8 percent agriculture; the remainder was water, wetlands, 

or barren land. San Antonio, the principal urban area, includes 

much of Bexar County (fig. 1) and the southeastern part of the 

local-scale study area (fig. 3). 

Methods of Investigation

The methods used for this study were consistent with the 

objectives of the nation-wide NAWQA/TANC study, which 

included the use of similar methods in all six local-scale study 

area investigations. The uses of similar methods of waterquality data collection and analyses, MODFLOW (Harbaugh 

and others, 2000) to simulate groundwater flow, and MODPATH (Pollock, 1994) to simulate the pathlines of water particles in groundwater provide consistency and comparability 

for the TANC local-scale studies (Eberts and others, 2005).

Data Collection and Analysis

A total of six wells were installed during 2007–8 in two 

well nests (with four wells in one well nest and two wells 

in the other nest) oriented along one of the general directions of groundwater flow to the selected PSW based on flow 

directions indicated by the regional-scale model (Lindgren 

and others, 2011). The well nests were Zarzamora (four wells) 

and Timberhill (two wells) (fig. 3, table 1 at end of report). 

The Zarzamora well nest included one well screened in the 

overburden overlying the Edwards aquifer (Zarzamora_OVB; 

W79) and three wells screened in the Edwards aquifer at shallow (Zarzamora_SED; WQ3), intermediate (Zarzamora_IED; 

WQ4), and deep (Zarzamora_DED; WQ5) depths (table 1). 

The Timberhill well nest included two wells screened in the 

Edwards aquifer at intermediate (Timberhill_IED; WQ1) and 

deep (Timberhill_DED; WQ2) depths (table 1). 

Water-level altitudes were measured in all monitoring 

and observation wells during water-quality sampling, and 

water-level recorders were installed in six monitoring wells 

(Zarzamora and Timberhill site wells) to provide water-level 

altitude data that were used to calibrate the groundwater-flow 

model (table 2 at end of report). Groundwater altitudes were 

recorded hourly from January 2008 through February 2010. 

During calibration of the groundwater-flow model, 

measured monthly mean groundwater altitudes (calculated 

from hourly water-level altitudes measured by water-level 

recorders) were compared to simulated monthly groundwater 

altitudes. Hydrographs depicting mean daily water levels from 

September 1, 2007, through March 1, 2010, for the Zarzamora 

and Timberhill monitoring wells are shown in figure 5. Waterlevel altitudes collected for this study are summarized in 

table 2, and all well locations are shown on figure 6.

Groundwater samples analyzed for tritium concentrations 

were collected during 2007–8 from the selected PSW (WZ4), 

from four additional PSWs (WZ2, WZ3, WZ5, and WZ6), and 

from six monitoring wells (Timberhill and Zarzamora well 

nests) (fig. 3, table 1). Groundwater samples included wellhead samples from the PSWs (Q1 [the selected PSW], Q5, Q6, 

Q7, and Q8) and depth-dependent samples from the selected 

PSW (Q2, Q3, and Q4) and the monitoring wells (WQ1, 

WQ2, WQ3, WQ4, and WQ5) (fig. 3, table 1). Geophysical 

and flowmeter logs were collected from the selected PSW 

(Q1) to determine zones of contribution to the wellbore prior 

to sampling. For flow measurements and depth-dependent 

water sample collection, the production pump was removed, 

and a temporary turbine pump was lowered below the existing water-level depth such that the intake was about a meter 

above the bottom of the steel casing in the selected PSW, 

allowing for drawdown and a pumping rate of 2.5–3.2 cubic 

meters per minute (m3/min). This pump was used to stress 

the well to simulate production conditions during the pumped 

flowmeter logging and depth-dependent water sample collection. For comparison purposes, the simulated pumping rate for 

the selected PSW in the local-scale model, representative of 

average conditions during the recent time period (2000–10), is 

10.5 m3/min, about three to four times greater than the pumping rate for the temporary turbine pump. 

Four pumping conditions were logged with the flowmeter: (1) no pumping in the selected PSW or well field (an 

operationally rare occurrence referred to as “ambient 1”); 

(2) no pumping in the selected PSW, but with pumping of 
10 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

nearby well(s) in the well field (“ambient 2”); (3) pumping 

of the selected PSW, with no pumping of additional wells in 

the well field (“moderate”); (4) pumping of the selected PSW, 

with pumping of nearby well(s) in the well field (“normal”). 

“Normal” pumping conditions, with surrounding wells in the 

well field operating under typical pumping schedules (selected 

PSW and nearby PSWs in the well field pumping at total 

discharge rates from approximately 29.4 to 107 m3

/min), 

are likely to be most representative of pumping conditions 

associated with typical well-field production conditions. 

However, as noted in the previous paragraph, the pumping 

rate for the temporary turbine pump used for collecting the 

depth-dependent water samples was much less than the recent 

(2000–10) average pumping rate for the selected PSW.

Depths for sampling (selected on the basis of zones of 

flow within the selected PSW) were (1) shallow (116 m), 

(2) intermediate (131 m), and (3) deep (165 m), which are 

associated with three different Edwards Group stratigraphic 

units, specifically, (1) the cyclic and marine members (undivided), (2) the leached and collapsed members, and (3) the 

Kirschberg evaporite member, respectively. The measured 

tritium concentrations for the selected PSW (one wellhead 

and three depth-dependent samples) for “normal” well-field 

pumping conditions, five of the six Timberhill and Zarzamora 

monitoring wells (excluding well Zarzamora_OVB), and four 

PSWs (WZ2, WZ3, WZ5, and WZ6) were used to calibrate 

the local-scale model. The measured tritium concentration for 

Zarzamora monitoring well Zarzamora_OVB was anomalous 

and thus not used for the local-scale model calibration. 

Development and Application of GroundwaterFlow and Particle-Tracking Models 

A local-scale, steady-state, three-dimensional numerical 

groundwater-flow model was developed and used in this study 

to evaluate the movement of water and solutes from recharge 

areas to the selected PSW. The local-scale model was nested 

within the rediscretized regional Edwards aquifer models used 

for the TANC regional analysis (Lindgren and others, 2011). 

The local-scale model was constructed and run by using 

the USGS finite-difference groundwater flow FORTRAN 

computer-model code MODFLOW-2000 (Harbaugh and others, 2000). Particle pathlines and traveltimes associated with 

simulated particles of water that discharge to wells were determined by using MODPATH version 5.0—the USGS particletracking software (Pollock, 1994). Dispersion, diffusion, 

Figure 5. Daily mean water-level altitudes from continuous water-level recorders in monitoring wells in the local-scale study area, 

September 12, 2007, to February 9, 2010, San Antonio region, Texas. 

9/1/07

11/1/07

1/1/08

3/1/08

5/1/08

7/1/08

9/1/08

11/1/08

1/1/09

3/1/09

5/1/09

7/1/09

9/1/09

11/1/09

1/1/10

3/1/10

Date

Daily mean water-level altitude, in meters above North American Vertical Datum of 1988

195

200

205

210

215

220

Timberhill intermediate well (Timberhill_IED)

Timberhill deep well (Timberhill_DED)

Zarzamora overburden well (Zarzamora_OVB)

Zarzamora shallow well (Zarzamora_SED)

Zarzamora intermediate well (Zarzamora_IED)

Zarzamora deep well (Zarzamora_DED)

EXPLANATION
Introduction 11

adsorption, retardation, degradation, or any other transport 

process affecting the concentrations of contaminant constituents are not included in the MODPATH simulation for determining traveltimes of water. The parameter estimation code 

PEST (acronym for Parameter ESTimation) was used to estimate horizontal and vertical hydraulic conductivities, fault and 

drain hydraulic conductances, and porosity values by using an 

automated nonlinear-estimation technique (Doherty, 2005). 

PEST is a parameter-estimation program that can be used with 

any model that reads its input data from one or a number of 

American Standard Code for Information Interchange (ASCII) 

(text) input files and writes the outcomes of its calculations to 

one or more ASCII output files (Doherty, 2005). This program 

allowed for concentrations of the environmental tracer tritium 

to be used in addition to water-level altitudes and spring 

discharges in estimating the parameters for MODFLOW and 

MODPATH. Groundwater flow and particle-tracking simulations were refined in concert to obtain the best match for simulated water-level altitudes, spring discharges, and groundwater 

age-tracer (tritium) concentrations and to ensure that hydraulic 

parameter estimates were reasonable.

An important part of the local-scale model development 

was the incorporation of the complex hydrogeology of the 

Edwards aquifer into the numerical framework of the model. 

The local-scale model grid has a finer vertical discretization 

than do previous regional Edwards aquifer models (Lindgren 

Figure 6. Local-scale study area and locations of observation wells used to monitor water-level altitudes for inclusion in the localscale model, San Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

W11 W13

W12

W28

W27

W29

W26

W21

W24 W44

W45

W38

W39

W40

W37

W46

W36

W35

W34

W23

W25

W30 W32

W33

W49

W51

W31

W2 W3

W4

W6 W8

W7

W5 W75

W76

W77

W73

W74

W78

W79,WQ4,

WQ3,WQ5

WQ2

WQ1

W1

W14

W18

W15 W9 W10

W16

W43

W17

W20

W19

W22

W50

W42 W41

W48

W47

W70

W53

W54

W55

W67

W52

W69

W68

W62

W66

W65

W72

W59

W56

W60

W61

W71

W57

W58

W63

W64

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

Freshwater/saline-water interface

 (1,000 milligrams per liter dissolved

 solids concentration) (A.L. Schultz,

 consultant, written commun., 2000)

Spring

Water-level observation well in the local-scale

 study area and number—See table 2

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary (modified

 from Puente, 1978)

EXPLANATION

W51
12 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

and others, 2004; Lindgren, 2006) and incorporates refined 

parameter zones corresponding with multiple (10) hydrogeologic units representing the Edwards aquifer. In the Edwards 

aquifer, high matrix porosity and permeability likely are 

overshadowed by high permeability developed in structurally influenced karstic conduit systems that transmit water 

into, through, and out of the aquifer system. The complexity 

of the aquifer system in the local-scale study area is further 

increased by numerous faults with varying vertical displacements. The extensive faulting results in the juxtaposition of 

hydrogeologic units (HGUs) with differing hydraulic properties and has appreciable effects on groundwater flow in the 

Edwards aquifer. The local-scale model simulations use the 

MODFLOW Hydrogeologic-Unit Flow Package (Anderman 

and Hill, 2000) and include two HGUs with high hydraulic 

conductivities (one or more orders of magnitude higher than 

for the other simulated hydrogeologic units) that are intended 

to simulate fast flow paths attributable to karst features. The 

two “conduit” hydrogeologic units of the Edwards aquifer 

represent the lower 8 m of the leached and collapsed members 

and the Kirschberg evaporite member of the Edwards Group. 

The MODFLOW Horizontal-Flow Barrier Package (Harbaugh 

and others, 2000) was used to simulate faults in the local-scale 

model. The assumption was made that the degree to which a 

fault acts as a barrier to groundwater flow is proportional to 

the fault displacement. Steady-state simulation, used for the 

local-scale model, has many applications in hydrologic investigations. It is used to analyze the natural (predevelopment) 

flow system, as well as any new equilibrium conditions that 

have been attained during the course of development (Franke 

and others, 1984, p. 15). Large temporal variations in Edwards 

aquifer groundwater withdrawals (fig. 7A) and groundwater 

recharge amounts (fig. 7B) are common, resulting in large 

changes in water-level altitudes. During periods of drought, 

water-level altitudes decline but recover rapidly in response 

to recharge. Most of the groundwater used for public supply 

is withdrawn near San Antonio, where water-level altitudes in 

well W38 (Bexar County index well, J–17) (fig. 6) have 

varied between a low in 1956 of 186.7 m above the North 

American Vertical Datum of 1988 (NAVD 88) to a high in 

1992 of 214.4 m above NAVD 88 (Hamilton and others, 

2003). Although recurring droughts and floods have caused 

appreciable short-term fluctuations in water-level altitudes, 

long-term hydrographs (about 80 years) indicate no net decline 

(or rise) of water-level altitudes in the San Antonio region 

(fig. 8A).

Average stresses (recharge and pumpage) during 2001 

were used to simulate steady-state conditions for the localscale model. The year 2001 was chosen to represent average, 

equilibrium (steady-state) hydrologic conditions because 

it coincides with the steady-state simulation period for the 

diffuse-flow rediscretized regional Edwards aquifer model 

(Lindgren and others, 2011), which was used to establish 

boundary conditions for the local-scale model. In addition, the year 2001 is representative of average, equilibrium 

(steady-state) hydrologic conditions during a recent time 

period (2000–10). The time period 2000–10 includes (1) a 

typical range of recent groundwater withdrawal rates in the 

local-scale model area and (2) the period of measurement 

for water-level altitudes and tritium concentrations used to 

calibrate the local-scale model. Water-level altitudes used for 

comparison to model output are based on mean water-level 

altitudes measured in wells during 2001 and 2007–10. Tritium 

concentrations used in the local-scale model calibration were 

derived from water samples collected during 2007–8. Groundwater withdrawals by San Antonio Water System (SAWS) 

during 2001 were 219.8 million m3

, compared to mean annual 

groundwater withdrawals during 1969–2009 of 200.4 million 

m3 (San Antonio Water System, 2008; Scott Okland, San Antonio Water System, written commun., 2010). The mean annual 

groundwater withdrawals by SAWS during 1980–2009, a time 

period with groundwater withdrawals generally between about 

175 and 225 million m3 (fig. 7A) and more representative of 

recent groundwater withdrawals, were 217.9 million m3. Mean 

annual groundwater withdrawals by SAWS during 2000–9 

were 222.5 million m3, similar to the groundwater withdrawals 

during 2001 (219.8 million m3) (San Antonio Water System, 

2008; Scott Okland, San Antonio Water System, written 

commun., 2010). 

Rainfall at San Antonio during 2001 was 93.27 cm, somewhat higher than the mean annual rainfall during 2000–10 

of 81.84 cm and the 30-year normal (1971–2000) rainfall of 

83.62 cm (National Oceanic and Atmospheric Administration, 

National Climatic Data Center, 2002). Mean annual rainfall 

at San Antonio during 1969–2009 was 82.89 cm, and during 

1980–2009 it was 80.81 cm. The estimated recharge to the 

Edwards aquifer during 2001 for the three recharge subzones 

(referred to as “stream basin or contributing areas” in figure 2) 

in the local-scale study area was 389.3 million m3 (fig. 7B), 

compared to the mean annual recharge during 2000–9 of 

413.5 million m3 (Edwards Aquifer Authority, 2009). The 

mean annual recharge during 2007–9, the time period for some 

water-level measurement calibration targets and for tritium 

concentration calibration targets associated with short (less 

than 3 years) traveltimes, was 482.5 million m3 (Edwards 

Aquifer Authority, 2009). The mean annual recharge during 

1969–2009 was 386.3 million m3

, and during 1980–2009 was 

378.1 million m3 (Edwards Aquifer Authority, 2009; Richard 

Slattery, U.S. Geological Survey, written commun., 2010). 

The estimated recharge to the Edwards aquifer for the localscale model steady-state calibration (389.3 million m3 during 

2001) might be more representative of long-term (1969–2009; 

1980–2009) hydrologic conditions than of recent shorter term 

(2000–9; 2007–9) hydrologic conditions. However, most of 

the water-level measurement calibration targets were for 2001 

and therefore reflect 2001 hydrologic conditions. 

The attainment of equilibrium, steady-state conditions 

during 2000–10 is indicated by stable average water-level 

altitudes in wells in or near the zone of contribution (ZOC) of 

the selected PSW for the time period, with no apparent longterm increases or decreases in water-level altitudes other than 

seasonal variations and responses to variations in groundwater 
Introduction 13

Figure 7. A, annual groundwater withdrawals for San Antonio Water System wells, and B, estimated annual groundwater recharge to 

the Edwards aquifer in the local-scale study area, 1969–2009, San Antonio region, Texas. 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995

1997199920012003200520072009

Year

196919711973197519771979198119831985198719891991199319951997199920012003200520072009

Year

0

25

50

75

100

125

150

175

200

225

250

275

Groundwater withdrawals, in millions of cubic meters

0

100

200

300

400

500

600

700

800

900

1,000

1,100

1,200

Groundwater recharge, in millions of cubic meters

B

A
14 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Figure 8. Measured water-level altitudes in well W38 (Bexar County index well, J–17) for A, November 12, 1932, to February 28, 2010, 

and B, January 1, 2000, to February 28, 2010, San Antonio region, Texas. 1/1/1932 1/1/1934 1/1/1936 1/1/1938 1/1/1940 1/1/1942 1/1/1944 1/1/1946 1/1/1948 1/1/1950 1/1/1952 1/1/1954 1/1/1956 1/1/1958 1/1/1960 1/1/1962 1/1/1964 1/1/1966 1/1/1968

1/1/19701/1/19721/1/19741/1/19761/1/19781/1/19801/1/19821/1/19841/1/19861/1/19881/1/19901/1/19921/1/19941/1/19961/1/19981/1/20001/1/20021/1/20041/1/20061/1/20081/1/2010

1/1/20007/1/20001/1/20017/1/20011/1/20027/1/20021/1/20037/1/20031/1/20047/1/20041/1/20057/1/20051/1/20067/1/20061/1/20077/1/20071/1/20087/1/20081/1/20097/1/20091/1/20107/1/2010

Date

Date

600

620

640

660

680

700

720

630

640

650

660

670

680

690

700

710

Daily mean water-level altitude, in meters

above National Geodetic Vertical Datum of 19291

Daily mean water-level altitude, in meters

above National Geodetic Vertical Datum of 19291

A. Well W38 (Bexar County index well, J–17)

B. Well W38 (Bexar County index well, J–17)

1

 Source agency reports water-level altitude referenced to sea level

 (Edwards Aquifer Authority, 2009)
Introduction 15

recharge (fig. 9). Measured water-level altitudes from July 

2000 to July 2009 in well W32 indicate an overall decline of 

about 8.0 m, but the pattern of decline is interrupted by higher 

water-level altitudes during 2002, 2004, and 2007, which 

were periods of high groundwater recharge (figs. 7B and 9A). 

For wells W25 and W4, the measured water-level altitudes 

in July 2009 are about the same as in July 2000 (figs. 9B and 

9C, respectively). An overall increasing or decreasing pattern 

in water-level altitudes in the Edwards aquifer is also lacking 

in other parts of the local-scale model area during 2000–10, 

as indicated by the hydrograph for well W38 (Bexar County 

index well, J–17), southeast of the selected PSW (figs. 6 and 

8B). For the three wells in or near the ZOC of the selected 

PSW, the measured water-level altitudes during 2001—the 

time period corresponding with the hydrologic conditions 

used in the local-scale steady-state model calibration—are 

similar to the mean water-level altitudes for the 2000–10 time 

period (fig. 9). The mean measured 2001 water level in well 

W32 was 0.8 m higher than the mean measured water level 

for 2000–10, whereas the mean measured 2001 water-level 

altitudes in wells W25 and W4 were 0.1 and 0.9 m lower, 

respectively, than the corresponding mean measured waterlevel altitudes for 2000–10. The similarity in the mean 

measured water-level altitudes for 2001 and for 2000–10 

indicate that the hydrologic conditions simulated in the localscale model steady-state calibration adequately represent the 

hydrologic conditions for the 2000–10 time period and that 

the model calibration results are representative for water-level 

conditions during 2000–10.

A summary of final steady-state traveltimes for each particle reaching the monitoring wells or the selected PSW was 

obtained from MODPATH and used to describe the distribution of simulated particle ages associated with recharge water 

reaching the wells. A tritium concentration was assigned to 

each particle on the basis of the recharge date (from particle 

ages) and the concentration of tritium in the atmosphere at the 

time of recharge (minus radioactive decay). Biannual historical concentrations of tritium in the atmosphere were derived 

from historical concentrations of tritium measured in rainfall 

at Waco, Tex. (1961–87) and at Vienna, Austria (1961–2006) 

(International Atomic Energy Agency, 2008). Concentrations 

of tritium in precipitation (Michel, 1989) peaked in the 1960s 

and have been generally declining since that time; tritium concentrations were adjusted for radioactive decay to 2009 assuming a half-life of 12.3 years. A flux-weighted average concentration was calculated for each well or particular open interval 

by multiplying the concentration assigned to each particle 

by the amount of recharge associated with that particle and 

summing overall particles reaching a well or particular open 

interval. The calculated tracer concentration is the result of the 

mixture at an observation point (well or particular open interval) of all of the concentrations associated with all of the individual simulated particles with pathlines terminating at that 

observation point. The calculated tracer concentrations derived 

from simulated flow paths and advective traveltimes computed 

by MODPATH were compared with measured concentrations. 

In addition, the mean of MODPATH-computed advective 

traveltimes (simulated mean particle age) at an observation 

point was compared with the apparent groundwater age, which 

was based on an interpretation of tracer concentrations and 

an assumed hydrogeologic conceptual model (Musgrove and 

others, 2011). The apparent groundwater age from tracers can 

be compared to the mean (or central tendency) of particle ages 

for each observation point to provide some indication of how 

plausible both the simulated MODFLOW and geochemical 

apparent groundwater age results are. 

In addition to measured water-level altitudes, the localscale model was calibrated for steady-state conditions by using 

tritium concentrations measured during a 8-month period from 

October 2007 to May 2008. The local-scale steady-state model 

uses average hydrologic conditions during 2001 to approximate the transient hydrologic conditions during the traveltime 

periods from the source areas (recharge zone) to the wells. The 

steady-state velocity represents the average condition over the 

time period that the water particles move from source areas 

(recharge zone) to the wells, so although the exact conditions 

are not represented, the average conditions are such as to give 

reasonable results for the purposes of this study. The steadystate simulations are intended to provide insight into the types 

of processes that are important in karstic aquifer systems and 

are not intended to exactly match transient hydrologic conditions and transport characteristics of the karstic Edwards 

aquifer system. 

The simulated mean particle traveltimes from the source 

area (recharge zone) to the well for wells with measured 

tritium concentrations used as calibration targets ranged from 

about 3 to 15 years. Apparent groundwater ages determined 

for the same wells, derived from tracer concentration data and 

an assumed hydrogeologic conceptual model (Musgrove and 

others, 2011), ranged from about 1 to 40 years. Therefore, 

the entire potential time frame associated with the movement 

of tritium from the source area (recharge zone) to the wells 

(about 40 years; 1969–2009) is not necessarily subject to 

the same hydrologic conditions as those used to calibrate the 

local-scale steady-state model (average stresses during 2001). 

However, as discussed previously in this section, recharge and 

groundwater withdrawals during 2001 were similar to those 

during 1969–2009, and it is likely the hydrologic conditions 

from 2001 used to calibrate the local-scale steady-state model 

were representative of typical 1969–2009 hydrologic conditions. Groundwater withdrawals by SAWS during 2001 were 

9.7 percent higher than mean annual groundwater withdrawals 

during 1969–2009 and only 0.9 percent higher than during 

1980–2009, a time period with groundwater withdrawals 

generally between about 175 and 225 million m3

 and more 

representative of recent groundwater withdrawals (fig. 7A). 

The estimated recharge to the Edwards aquifer during 2001 in 

the local-scale study area (fig. 7B) was only 0.8 percent higher 

than the mean annual recharge during 1969–2009. Also, longterm hydrographs indicate no net decline (or rise) of waterlevel altitudes in the San Antonio region during 1969–2009 

(fig. 8A), indicating a lack of persistent hydrologic patterns 
16 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Figure 9. Measured water-level altitudes, San Antonio region, Texas. A, Well W32, January 24, 2000, to March 3, 2010. B, Well W25, 

January 24, 2000, to July 22, 2009. C, Well W4, January 26, 2000, to February 24, 2010. 1/1/2000 7/1/2000 1/1/2001 7/1/2001 1/1/2002 7/1/2002 1/1/2003 7/1/2003 1/1/2004 7/1/2004 1/1/2005 7/1/2005 1/1/2006 7/1/2006

1/1/20077/1/20071/1/20087/1/20081/1/20097/1/20091/1/2010

Date

185

190

195

200

205

210

195

200

205

210

215

220

215

220

225

230

235

240

245

250

255

Water-level altitude, in meters above North American Vertical Datum of 1988 

A. Well W32

B. Well W25

C. Well W4
Introduction 17

during this time period. The increase in annual groundwater 

withdrawals beginning in about 1980 (fig. 7A) had no apparent effect on equilibrium or average water-level altitudes 

(fig. 8A). The mean measured 2001 water level in well W38 

(Bexar County index well, J–17), located to the southeast 

of the selected PSW, was 1.7 m higher than the mean measured water level for 1969–2009 (7.1 percent of the range in 

measured water-level altitudes during 1969–2009) but was 

within about 0.03 m of the mean measured water level during 

2000–10. The similarity between the mean measured waterlevel altitudes for 2001 and 2000–10 might indicate that the 

local-scale model results are more representative of recent 

hydrologic conditions (2000–10) than they are of hydrologic 

conditions prior to 2000. However, a comparison of the magnitudes of groundwater recharge and withdrawal and of mean 

water-level altitudes for 2001 to those during 2000–10 and 

1969–2009 indicate that hydrologic conditions during 2001 

adequately represent hydrologic conditions during 2000–10 

and 1969–2009 for the purposes of this study. The 2001 

hydrologic conditions may be most representative of recent 

hydrologic conditions (2000–10), but the local-scale model 

simulation results indicate that young water (less than 5 years) 

is a major component of the water reaching wells in the ACR 

of the selected PSW. 

The local-scale steady-state model was used to assess 

the age distribution of water at selected wells and to compute 

particle traveltimes from the source area (recharge zone) to 

the wells. The computed traveltimes were then used to compute simulated tritium concentrations, which were compared 

to measured tritium concentrations. The measured tritium 

concentration at a well is the result of many factors, including radioactive decay of tritium and transient hydrologic 

conditions that vary during the traveltime from the source 

area (recharge zone) to the well. Musgrove and others (2009) 

reported the results for tritium concentrations measured in 

samples collected from shallow unconfined water table wells 

under different hydrologic conditions ranging from relatively 

wet (1998) to relatively dry (2006). For about half of the 

samples, the residence time of the water and the accompanying radioactive decay accounts for the differences in measured 

tritium concentrations between 1998 and 2006. For the other 

half, however, the differences are likely caused by additional 

factors, including the timing of recharge to the aquifer and 

variability in hydrologic conditions (Musgrove and others, 

2009). The local-scale steady-state model developed for this 

study does not account for the potential effects of transient 

hydrologic conditions on the measured tritium concentrations 

at a well. 

The local-scale model was calibrated for steady-state 

conditions by using average hydrologic conditions during 

2001 and tritium concentrations measured over an 8-month 

period from October 2007 through May 2008, with a relatively narrow range of measured tritium concentrations 

(0.51 tritium unit [TU]). An additional 42 tritium concentration values obtained from samples collected during the 1990s 

from 29 wells and not used in the calibration of the model 

were compared to computed tritium concentrations derived 

from the local-scale steady-state model particle-tracking 

results. A greater range of measured tritium concentrations 

(3.70 TU) was measured in the 42 tritium concentrations 

from the 1990s compared to the range of measured tritium 

concentrations (0.51 TU) measured in the samples collected from October 2007 through May 2008. The agreement between the measured and simulated tritium concentrations for the samples collected during the 1990s was 

similar to the agreement between the measured and simulated 

tritium concentrations during 2007–8, indicating that, although 

the entire range of transient hydrologic conditions are not 

equally represented in the local-scale steady-state model, 

the simulated hydrologic conditions and model results are 

applicable for time periods other than the 2007–8 period as 

well. 

The use of steady-state simulations, rather than transient simulations, simplified and facilitated the simulation of 

areas contributing recharge and traveltimes to wells. Reilly 

and Pollock (1995) showed that when the mean traveltime 

is much greater than the cyclical nature of the stresses on a 

system, the steady-state results do not differ appreciably from 

a transient analysis. This conclusion can be expected to hold 

true for the steady-state results presented in this report. The 

simulated steady-state mean traveltimes to wells for this study 

are generally on the order of years, whereas the recharge and 

withdrawal stresses on the Edwards aquifer vary seasonally 

and often daily, and responses in water-level altitudes and 

springflows are often on the order of days. 

The local-scale model was used to simulate the ACR 

and particle traveltimes from the recharge areas to the well 

for the selected PSW and selected nearby PSWs and monitoring wells, including nearby PSWs in the same well field. The 

horizontal and vertical discretization of the model grid of the 

local-scale model resulted in multiple PSWs being located 

in the same horizontal (row, column) grid location for two of 

the three horizontal grid locations encompassing the area of 

the PSW field that includes the selected PSW. The selected 

PSW and two other PSWs are located in row 230, column 264 

of the model grid and are screened across partially overlapping model layers. The starting particle locations for all three 

PSWs in row 230, column 264 of the model grid are vertically 

distributed on each cell face over the open interval of each 

well. Therefore, for model layers where the open intervals of 

the wells overlap, the simulated particle traveltimes and the 

parts of the ACR attributable to the overlapping open intervals 

(model layers) for each of the wells are the same. However, 

because the open intervals (model layers) for the wells are not 

fully coincident, the simulated ACR for the three wells are not 

exactly the same. The dimensions of the grid cells and number 

of model layers were determined on the basis of an acceptable 

balance for particle-tracking purposes and the need to limit the 

total number of cells in the model. A finer grid discretization 

that would eliminate the occurrence of multiple PSWs in the 

same grid cell, or the same horizontal grid location, was not 

feasible. 
18 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Conceptualization of the Edwards 

Aquifer1

The conceptualization of the Edwards aquifer includes a 

description of the geologic and hydrogeologic setting within 

which the aquifer functions. Sedimentary and crystalline rocks 

that range in age from Precambrian to Holocene underlie 

south-central Texas. Four depositional provinces were formed 

during Lower Cretaceous time: the central Texas platform on 

the Edwards Plateau, Maverick Basin, Devils River trend, and 

San Marcos platform (Maclay, 1995) (fig. 1). The Cretaceous 

strata of south-central Texas regionally include two aquifers: 

the Edwards aquifer in the Balcones fault zone and the Trinity 

aquifer in the Hill Country. The Cretaceous rocks composing 

the Edwards aquifer are laterally and vertically heterogeneous, 

with eight aquifer subdivisions defined by Maclay and Small 

(1976, table 1) (fig. 10). 

The altitude of the top of the Edwards aquifer in the 

local-scale study area ranges from about 343 m above NAVD 

88 in the recharge zone in eastern Medina County to about 

640 m below NAVD 88 in the southwestern part of the study 

area. The aquifer thickness ranges from about 129 m in and 

near the recharge zone in Bexar County to about 220 m in the 

confined part of the aquifer in the southwestern part of the 

study area (fig. 11). 

Geologic Setting

The Cretaceous rocks that underlie the local-scale study 

area include shallow-water facies, which consist of sediments 

deposited on tidal flats and sabkhas and of subtidal carbonate 

sediments that accumulated on a carbonate platform. Internal 

depositional cycle boundaries are overlain by rocks consisting 

of near-shore and shallow-water sediments in topographically 

higher parts of the platform grading downdip (seaward) into 

subtidal carbonate rocks. As facies migrated in response to sea 

level variation and sediment aggradation, different depositional facies were superimposed vertically. Three depositional 

provinces were formed in the local-scale study area during 

Lower Cretaceous time: the central Texas platform on the 

Edwards Plateau, Devils River trend, and San Marcos platform 

(Maclay, 1995) (fig. 1). Different depositional facies and different energy conditions associated with carbonate deposition 

were characteristic in each province.

The Devils River trend, the platform margin rimming 

the Maverick Basin, is distinguished by stacked, high-energy 

facies including grainstone, packstone, and rudist patch reefs 

and associated facies. The San Marcos platform was a region 

of less subsidence relative to the other regions where the depositional environment varied through space and time from open 

marine to arid, hot, supratidal flats (Rose, 1972). Dolomite 

and dolomitic limestone are more abundant on the San Marcos 

platform than in the other regions. The dominant carbonate 

1

 This section modified from Lindgren and others (2004, p. 8–27).

textures are massive and burrowed packstone and grainstone; 

collapse breccia, microscale and macroscale structures, calcitized evaporite, and rudist-reef detritus also were identified 

(Rose, 1972; Hovorka and others, 1996). The San Marcos 

platform facies of the Edwards Group have been divided into 

the Kainer and Person Formations (Rose, 1972) (fig. 10). The 

end of the time of formation of the Edwards Group (during the 

Washitan stage) is marked by a period of subaerial erosion and 

karstification (Rose, 1972). The Edwards Group was buried 

by as much as a thousand meters of predominantly deepwater, 

marine-shelf sediments deposited during marine transgression 

that characterized the later Cretaceous globally.

The Edwards aquifer is part of an aquifer system developed in thick and regionally extensive Lower Cretaceous 

carbonates that underlie large areas of Texas. Stratigraphically 

complex facies of the Lower Cretaceous, including sandstones, karstic limestones and dolomites, low permeability 

calcareous marl, and evaporite units, host the Trinity aquifer. 

The upper part of the Trinity aquifer, the Glen Rose Limestone, is overlain by limestone, dolomite, and altered evaporite 

of the Edwards aquifer. The stratigraphically equivalent units 

that compose the Edwards aquifer are the Kainer and Person 

Formations (Edwards Group) and overlying Georgetown Formation in the San Marcos platform (Rose, 1972) and the Devils River Limestone in the Devils River trend (fig. 10). The 

Edwards aquifer is overlain by the Upper Cretaceous Del Rio 

Clay, a thick, regionally distinctive shale that defines the top 

of the Edwards aquifer. Overlying the Del Rio Clay are, from 

oldest to youngest, the Upper Cretaceous Buda Limestone, 

Eagle Ford Group (dominantly shale), and Austin Chalk.

The Balcones fault zone is a system of high-angle normal 

faults with net displacement toward the Gulf of Mexico and 

constitutes the principal structural deformation affecting 

aquifer development. Most of the uplift of the Edwards Plateau along the Balcones fault zone took place in the Miocene 

(Ewing, 1991). This deformation extends from Bracketville, 

Tex., in the west to the east through San Antonio, where it 

bends and extends northeast past Austin, Tex. The underlying Ouachita structural belt provided a pivot between the 

uplifting of the Edwards Plateau and the subsidence of the 

adjacent Gulf Coastal Plain. The gentle southeastward dip of 

Cretaceous strata in the Edwards Plateau and Hill Country is 

interrupted across the Balcones fault zone by a system of en 

echelon faults that generally strike northeastward (Maclay, 

1995). The faulting occurred along the subsurface axis of 

the Ouachita structural belt as a result of extensional forces 

created by the subsidence of basin sediments in the Gulf of 

Mexico (Mace and others, 2000). The vertical displacements 

of these faults vary along the strike of each individual fault. 

Faults of the Balcones fault zone in the local-scale study area 

are shown in figure 12. 

Hydrogeologic Setting

The hydrogeologic setting describes the hydrostratigraphy and karstic nature of the Edwards aquifer, as well as the 
Conceptualization of the Edwards Aquifer 19

Figure 10. Correlation of Cretaceous stratigraphic units and hydrogeologic units and their relative permeabilities in the San Antonio 

region, Texas.

MAVERICK

BASIN1

DEVILS RIVER

TREND1

SAN MARCOS

PLATFORM1

HYDROGEOLOGIC

UNITS

ANACACHO

LIMESTONE

AUSTIN CHALK

EAGLE FORD

GROUP

BUDA

LIMESTONE

UPPER

CONFINING

UNIT

DEL RIO CLAY

UPPER CRETACEOUS

SALMON

PEAK

FORMATION2

DEVILS

RIVER

LIMESTONE2

GEORGETOWN

FORMATION

LOWER CRETACEOUS

Cyclic and

marine members

(undivided)

Leached

member

Collapsed

member

Regional dense

member

Grainstone

member

Dolomitic

member

Basal nodular member

Kirschberg

evaporite

member

PERSON FORMATION3 KAINER FORMATION3

MCKNIGHT

EDWARDS AQUIFER

FORMATION2

WEST NUECES

FORMATION2

TRINITY

AQUIFER

UPPER MEMBER

OF THE GLEN

 ROSE LIMESTONE

LOWER MEMBER

OF THE GLEN

 ROSE LIMESTONE

Aquifer subdivision in the San Marcos platform area4

Hydrogeologic unit numbers used in this report and in the local-scale model

I

II

III

IV

V

VI

VII

VIII

Erosional hiatus 

Very small

Very small

ANACACHO

LIMESTONE

Very small

ANACACHO

LIMESTONE

Very small

Moderate

AUSTIN CHALK Moderate

AUSTIN CHALK Moderate

Very small

EAGLE FORD

GROUP

Very small

EAGLE FORD

GROUP

Very small

Small

BUDA

LIMESTONE Small

BUDA

LIMESTONE Small

Very small

DEL RIO CLAY

Very small

DEL RIO CLAY

Very small

Very small

Very small

Large Small to moderate

Large

Moderate to large

Moderate to large

Very small

Moderate to large

Moderate

Large

Moderate

Moderate

Very small

Very small

Moderate

Small

Small

STRATIGRAPHIC UNITS

Descriptors "very small, small, moderate, and large" refer to relative permeability of stratigraphic units.

.

EDWARDS GROUP

SYSTEM

UPPER

ZONE

MIDDLE

ZONE

DEPOSITIONAL PROVINCE

1 Location shown on figure 1.

2

 Lozo and Smith (1964).

3 Modified from Rose (1972).

4

 Maclay and Small (1984).

GLEN ROSE

LIMESTONE

TRINITY GROUP

GLEN ROSE

LIMESTONE

GLEN ROSE

LIMESTONE

6

11

2

3

4

7

8

10
20 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Figure 11. Thickness and measured potentiometric surface of the Edwards aquifer in the local-scale study area, October 27 to 

November 2, 2001, San Antonio region, Texas.

North-central flow unit

South-central flow unit

Eastern flow unit

Western-southern flow unit

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

225.6

237.8

207.3

243.9

262.2

219.5

213.4

207.3

250.0

256.1

237.8

231.7

231.7

225.6

219.5

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

C A T C H M E N T A R E A C A T C H M E N T A R E A

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

Local-scale study area—Includes active

 local-scale model area and a portion

 of inactive local-scale model area (fig. 4)

 Active local-scale model area, by thickness

 of the the Edwards aquifer, in meters—

 Interval is variable

 129 to 137

 138 to 143

 144 to 147

 148 to 155

 156 to 170

 171 to 182

 183 to 197

 198 to 220

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary E

256.1

EXPLANATION

Edwards aquifer recharge zone (outcrop)

 boundary (modified from Puente, 1978)

Freshwater/saline-water interface (1,000 

 milligrams per liter dissolved solids

 concentration) (A.L. Schultz, consultant,

 written commun., 2000)

Boundary separating flow units (Maclay

 and Land, 1988, fig. 22, table 4)

Water-level contour—Shows altitude at which

 water level would have stood in tightly cased

 wells open to Edwards aquifer. Dashed where

 inferred. Interval is 6.1 meters. Datum is North

 American Vertical Datum of 1988

 (Roberto Esquilin, Edwards Aquifer Authority,

 written commun., 2004)

Generalized direction of groundwater flow

Spring

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10
Conceptualization of the Edwards Aquifer 21

structural and hydrologic features and hydraulic properties that 

influence groundwater flow in the aquifer. The groundwaterflow system and the sources of recharge to and discharge from 

the aquifer also are described.

Hydrostratigraphy

The Cretaceous strata of south-central Texas regionally include two aquifers: the Edwards aquifer in the Balcones fault zone and the Trinity aquifer in the Hill Country. 

The correlation chart (fig. 10) summarizes the relation 

among stratigraphic and hydrogeologic units and combines 

stratigraphic nomenclature with aquifer and confining-unit 

terminology (Lozo and Smith, 1964; Rose, 1972; Maclay and 

Small, 1984). The Trinity aquifer in the Hill Country, composed of sediments of the Trinity Group, has been divided into 

lower, middle, and upper zones (only the middle and upper 

zones are shown in fig. 10) on the basis of hydraulic characteristics of the sediments (Barker and Ardis, 1996; Mace and 

others, 2000). The upper zone of the Trinity aquifer generally 

has lower permeability than does the Edwards aquifer and, 

because of shaley interbeds, has a much lower vertical than 

horizontal permeability (Mace and others, 2000). The degree 

of hydraulic connection between the Trinity and Edwards 

aquifers might be limited in many areas by the relatively 

small permeabilities of the contiguous units (Maclay, 1995). 

Figure 12. Locations and displacements of faults simulated in the local-scale model, San Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

Hondo

Castroville San

Antonio

E

E

San Pedro

 Springs

San Antonio 

Springs

Medina

Lake

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

Freshwater/saline-water interface (1,000 milligrams per

 liter dissolved solids concentration) (A.L. Schultz,

 consultant, written commun., 2000)

Displacement of faults, as percent of total aquifer

 thickness

 0 to 20

 More than 20 to 40

 More than 40 to 60

 More than 60 to 80

 More than 80 to more than 100

Spring

Local-scale study area—Includes active local-scale

 model area and a portion of inactive local-scale

 model area (fig. 4)

 Active local-scale model area

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary

 (modified from Puente, 1978)

EXPLANATION
22 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Conventionally, the lower boundary of the Edwards aquifer is 

defined as the top of the Glen Rose Limestone (fig. 10).

Maclay and Small (1976, table 1) defined eight aquifer 

subdivisions within the Kainer, Person, and Georgetown Formations that compose the Edwards aquifer in the San Marcos 

platform of the Balcones fault zone (fig. 10). The eight aquifer 

subdivisions correspond to eight of the twelve hydrogeologic 

units defined for the local-scale model, discussed later in 

this report in the “Simulation of Groundwater Flow” section. 

Highly permeable intervals are variably distributed throughout units II, III, and VI, with the most permeable parts of 

these units occurring in honeycombed rock (Maclay, 1995). 

Groschen (1996) indicated that units III, VI, and VII transmit most of the groundwater within the San Antonio region. 

However, high-permeability dissolution features have been 

observed in all eight of the aquifer subdivisions. The Edwards 

aquifer contains carbonates that have numerous intervals of 

intercrystalline high porosity, as well as petrophysical properties that make the carbonates subject to development of karst 

conduits (Hovorka and others, 1998). In the San Antonio segment of the aquifer, interaction between lithologies and structure was observed to influence distribution of karst conduits 

(Hovorka and others, 1998).

The Georgetown Formation consists of stratigraphically distinct limestone that overlies and is generally of lower 

porosity and permeability than the Edwards Group. The 

contact is at least locally unconformable, with development of 

pre-Georgetown karst (Rose, 1972). The Georgetown Formation is commonly included within the Edwards aquifer because 

(1) there is no barrier to hydrologic connection between the 

Edwards Group and Georgetown Formation, (2) karst features 

are at least locally developed in the Georgetown Formation, 

and (3) it is difficult to separate the carbonates of the Edwards 

Group consistently from those of the Georgetown Formation 

by using the gamma-ray logs or drillers’ reports commonly 

available for the subsurface (Scanlon and others, 2002).

The thick and regionally extensive shale of the Del Rio 

Clay directly overlies and confines the Edwards aquifer in 

downdip parts of the Balcones fault zone (freshwater and 

freshwater/saline-water transition zones in fig. 2). The high 

clay content and plasticity of the Del Rio Clay indicate that 

it generally functions as an effective barrier to vertical flow 

(Scanlon and others, 2002). The thick shales and marls of the 

Eagle Ford Group additionally confine the Edwards aquifer. 

The confined part of the Edwards aquifer includes, on 

its downdip (gulfward) margin, the freshwater/saline-water 

transition zone (fig. 2). A small part of the freshwater/salinewater transition zone is present in the southwestern corner 

of the local-scale study area (fig. 3). The concentration of 

dissolved solids on the freshwater side of the transition zone 

ranges from about 250 to 300 mg/L (Pavlicek and others, 

1987). The concentration of dissolved solids downdip of the 

transition zone rapidly increases in a gulfward direction to 

more than 250,000 mg/L (Maclay and Land, 1988). The locations of lines of equal concentration of dissolved solids ranging from 1,000 to 100,000 mg/L for the San Antonio segment 

of the Edwards aquifer have been mapped (Schultz, 1992, 

1993, 1994; A.L. Schultz, consultant, written commun., 2000).

Karst Hydrogeology

A karst aquifer is an aquifer developed in soluble rocks 

with a permeability structure dominated by interconnected 

conduits dissolved from the host rock that facilitate the 

circulation of fluid in the downgradient direction wherein the 

permeability structure evolved as a consequence of dissolution 

by the fluid (Huntoon, 1995). An integrated aquifer-wide 

network of solutionally enlarged conduits with rapid flow 

characterizes karst aquifers (Huntoon, 1995; Worthington, 

1999). These networks form tributary systems that discharge 

at springs (Worthington, 2004). Karst aquifers commonly 

are conceptualized as dual-flow systems that compose a 

continuum-flow system with Darcian flow comparable to 

porous media and a discrete conduit network frequently with 

turbulent flow conditions (Birk and others, 2003). Conduits 

having a wide range of spatial and temporal scales are common in karst aquifers. In many carbonate aquifers, the bulk 

of the water is transmitted, for unsaturated flow conditions 

(caves), by turbulent flow in solutionally enlarged conduits 

(Gale, 1984). Aquifer anisotropy and heterogeneity, inherent 

in carbonate aquifer systems, can affect both the direction and 

the velocity of groundwater flow. Fluid flow in karst carbonate aquifers can be highly variable and difficult to measure or 

predict.

Karst was developed contemporaneously with sedimentation at the top of and possibly within the Edwards Group on 

the San Marcos platform, and this karst has created a zone 

of high permeability of unknown continuity at the top of the 

Edwards aquifer (Maclay, 1995; Hovorka and others, 1998). 

Faulting had a critical role in aquifer evolution because it 

(1) increased permeability by forming fracture networks and 

(2) greatly increased hydraulic gradient by uplift of the base 

of the present-day Edwards aquifer to altitudes greater than 

450 m above NAVD 88 in the northwestern part of the localscale study area, whereas at the downdip limit of the aquifer in 

the local-scale study area, the top of the aquifer is about 640 m 

below NAVD 88 at its deepest point. Introduction of freshwater into this heterogeneous and highly permeable carbonate 

rock created an extensive aquifer, which in turn modified the 

rock properties by the self-reinforcing mechanisms of preferential flow through larger aperture pores and preferential dissolution in zones of higher flow, which formed large, interconnected conduits (details of this process are described in Palmer 

[1991]). Epigenic karst theory assumes that karst features are 

produced only during downward or horizontal groundwater movement and are associated with recently recharged or 

meteoric waters and shallow, local flow systems. However, 

Klimchouk (2008) indicated that hypogenic speleogenesis, 

the formation of solution-enlarged permeability structures by 

waters ascending through soluble formations from below, is an 

important and widely occurring factor in karst development. 

Schindel and others (2008) indicate that hypogenic processes 
Conceptualization of the Edwards Aquifer 23

contributed to the formation and structure of the Edwards 

aquifer and the development of karst features. Hypogenic 

processes associated with discharge regimes of regional or 

intermediate flow systems dominated by upward flow likely 

interact with shallower and more local flow systems, supporting various dissolution mechanisms and the development of 

karst features. 

An important factor influencing karst development is 

dissolution at depth. High permeability is developed in the 

confined part of the Edwards aquifer at depths of as much as 

1,200 m below NAVD 88, as well as in the unconfined zone 

(Hovorka and others, 2004). Worthington (2001) demonstrated 

favored conduit development in parts of an aquifer deep below 

the water table, where flow paths are longer than about 3.0 

km, rather than in shallower parts. Stratigraphic control on 

karst formation is evident where caves, soft porous carbonate, 

and terra rossa infills occur preferentially at one horizon. In 

almost all outcrops, caverns have developed preferentially in 

former dolostones. Structural control on karst development 

is also very important. Hovorka and others (1998) described 

solution enlargement along fractures and solution enlargement 

producing caves along faults. Preferential development of 

caves in highly fractured zones adjacent to faults and in dolomitized intervals was observed in the outcrop area. Another 

variable influencing the development of karst is the hydrologic 

setting. Enhancement of matrix permeability is seen regionally 

near the freshwater/saline-water interface (Hovorka and others, 1998). Solution features are abundant in the outcrop area. 

Fractures, solution-enlarged fractures, and caves make up 1–3 

percent of the outcrop area in the San Antonio segment of the 

Edwards aquifer (Hovorka and others, 1998).

Evidence of the karstic nature of the Edwards aquifer 

includes outcrop observations, subsurface data, hydrologic 

information, and tracer test results. Karst landforms in the 

outcrop include large (up to 1.6 km across, but more typically 3–300 m across), shallow, internally drained depressions (Hovorka and others, 2004; fig. 4A, p. 7); depressions 

of holes in creek bottoms; and small, upland features such 

as sinkholes and solution-enlarged fractures. Maclay (1995) 

indicated that fresh fractures in unconfined, freshwater parts 

of the Edwards aquifer outcrop and shallow subcrop evolved 

into cavernous openings near the water table. Hovorka and 

others (1998) reported that in two-dimensional cross section, 

karst features make up 1–5 percent of the area of the outcrop. 

Solution enlargement preferentially developed where faults 

and fractures intersect solution-prone beds. Vertical conduits, 

some filled with terra rosa sediments, are observed in some 

outcrops. Although deep conduits have not been entered by 

humans, the existence of karst in the deep saturated zone is 

known from borehole televiewer images of caves and solutionenlarged fractures, cave textures, and sediments recovered 

in cores, bit drops during well construction, oversize caliper 

logs, and off-scale porosity logs. Hovorka and others (1996) 

reported appreciable areas of coincidence between very 

high porosity and enlarged or off-scale caliper, which likely 

indicates borehole intersection of a cave or solution-enlarged 

bedding plane or fracture. This evidence of karst is found 

throughout the Edwards aquifer and is not focused in any 

particular structural or stratigraphic setting. Maclay and Small 

(1984) indicated that tubular openings or solution channels 

(conduits) probably exist in areas of homogeneous, dense, 

fractured limestone, particularly in the western part of the 

San Antonio region; these tubular openings are aligned along 

fractures and are oriented in the direction of groundwater 

flow. In the Edwards aquifer, measurements by Hovorka and 

others (1998) using several methods also show that about only 

2 percent of the rock volume is occupied by 1.0-cm-scale or 

larger conduits. However, a recent cursory examination of 

geophysical logs and other borehole evaluation data indicated 

that voids 15 cm or larger, interpreted as conduits, were noted 

in 29 percent of the wells analyzed (A.L. Schultz, consultant, 

written commun., 2004). Such voids, typically less than 1.5 

m thick, were detected over a broad area of the San Antonio 

segment of the Edwards aquifer. Halihan and others (2000) 

argue that hydraulic properties indicate that most wells are not 

closely connected to large-aperture conduits with turbulent 

flow. 

Further evidence of flow through karst is the heterogeneous and rapidly responsive nature of water-level variation. 

Water-level altitudes in the aquifer and discharge at springs 

rise rapidly after rainfall and then decline at a variable rate, 

showing drainage from rocks characterized by both conduit and matrix permeability (Atkinson, 1977). Wells close 

together can have different responses to a single recharge 

pulse (Johnson and others, 2002). The response of springs to 

rainfall is rapid. The maximum lag between rainfall and peak 

springflow was 11 days or less at Comal Springs and 9 days or 

less at San Marcos Springs following an intense storm October 

17–19, 1998, centered in Comal County (Tomasko and others, 2001). Similarly, the effects of watering restrictions in 

San Antonio in August 2000 indicate that spring response is 

less than 1 day (Worthington, 2004). Tracer testing in the San 

Antonio segment of the Edwards aquifer has shown rapid 

flow (velocities of 179.8 to 800.1 meters per day (m/d) over 

distances of 0.8 to 4.0 km) from wells to the nearby high-flow 

springs (Ogden and others, 1986; Rothermel and others, 1987; 

Schindel and others, 2002). Rapid transmission of contaminants from several spill sites (Mace and others, 1997; Schindel 

and others, 2002) also indicates the likelihood that conduit 

flow systems are in the San Antonio segment of the Edwards 

aquifer. 

A regionally extensive system of high-permeability 

zones is defined by broad troughs in the potentiometric surface 

(conduit indicators) in the confined zone of the Edwards 

aquifer. Three approximately synoptic water-level maps constructed by Hovorka and others (2004; figs. 7, 8, and 9, p. 20, 

21, and 22, respectively) indicate a wide trough that extends 

westward from central Bexar County to western Medina 

County. This trough is clearly defined in synoptic surveys 

compiled by the Edwards Aquifer Authority (EAA) (Roberto 

Esquilin, Edwards Aquifer Authority, written commun., 

2003; Hovorka and others, 2004; fig. 10, p. 23) and has been 
24 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

recognized as a zone of high transmissivity in previous models 

(Klemt and others, 1979; Maclay and Land, 1988; Painter and 

others, 2002; Lindgren and others, 2004). Worthington (2004) 

conceptualized a dendritic pattern of conduit connection from 

the recharge zone to the confined zone. Maclay and Small 

(1984) hypothesized that solution channels within the Edwards 

aquifer might be oriented parallel to the courses of streams 

recharging the Edwards aquifer and that vertical solution channels are well developed below segments of stream courses in 

the recharge zone. Relatively high porosity and permeability 

in the deepest parts of the aquifer near the freshwater/salinewater interface, anomalously high well yields, and sharp 

chemical gradients indicate that flow might be focused in this 

area. 

Shallow flow paths, close to the water table, commonly 

have been considered the most favored locations for conduits 

(Thrailkill, 1968; Maclay, 1995). However, abundant evidence 

exists for solution activity deep within carbonate aquifers. 

An analysis by Worthington (2004, p. 19) for three possible 

flow paths from the Frio River to Comal Springs indicated 

that “deeper parts of the Edwards aquifer are favored over 

shallower parts for conduit development, even when the 

deep flow path is up to 24 percent longer than the shallow 

flow path.” Grabens and synclines are particularly favorable 

sites for development of conduits, offering the advantages 

of deeper flow paths without the disadvantages of long flow 

paths (Worthington, 2004). Large-scale structural troughs 

with increased flow occur in the Edwards aquifer, and conduit 

development in these is favored. Worthington (2004; fig. 17, 

p. 20) identified nine major structural troughs in the San 

Antonio segment of the Edwards aquifer, including troughs in 

Medina and Bexar Counties.

Hydraulic Properties

Extensive data have been collected on the hydraulic properties of the Edwards aquifer in the San Antonio region. The 

hydraulic properties of primary interest for this report include 

hydraulic conductivity, permeability, anisotropy, and porosity. 

Hydraulic conductivity is a quantitative measure of the ability 

of a material to transmit water and is a property of both the 

medium (aquifer material) and the fluid (Lohman, 1972, p. 6). 

The term “permeability” is commonly used in the extensive 

literature pertaining to the Edwards aquifer (see, for example, 

Hovorka and others, 1996, 1998; Halihan, Mace, and Sharp, 

2000; Mace and Hovorka, 2000). Permeability is used in this 

report (1) for a qualitative description of the ability of materials to transmit water and (2) in relation to aquifer structure, 

for example when referring to matrix, fracture, and conduit 

permeability. 

A qualitative interpretation of the distribution of relative permeability by stratigraphic unit of the Edwards aquifer 

and its confining units is shown in figure 10. These qualitative interpretations of relative permeability are based on field 

observations, stratigraphic studies by Rose (1972), and data 

from test-drilling and geophysical-logging programs (Maclay 

and Small, 1983). For the Edwards aquifer, these estimates 

apply to the confined zone and might not be strictly applicable 

to the unconfined zone. Hydraulic conductivity in the Edwards 

aquifer varies over eight orders of magnitude, and it is multimodal (Hovorka and others, 1998). Matrix, fracture, and 

conduit permeability occur in the Edwards aquifer. The carbonate matrix of the Edwards aquifer is very permeable; 

however, in many intervals, the very high permeabilities 

resulting from conduits and fractures dwarf the matrix 

contribution. In relation to structural position, Hovorka 

and others (1998) found high permeability more frequently 

in the deeper parts of the Edwards aquifer than in the parts 

where the top of the aquifer is higher than about 61 m above 

NAVD 88. Outcrops, which are at the highest altitudes, show 

abundant dissolution features and additional karst features 

that have developed in near-surface settings; however, matrix 

porosity and permeability of outcrop rocks are low relative to 

those in the aquifer. The highest matrix permeability occurs 

in downdip parts of the Edwards aquifer, where mixing of 

freshwater and saline water has maximized dolomite dissolution (Hovorka and others, 1998). High matrix permeability 

is observed on both sides of the freshwater/saline-water 

interface.

Hydraulic conductivity and transmissivity of the Edwards 

aquifer each vary over several orders of magnitude (table 3 at 

end of report). The estimates of mean hydraulic conductivity 

by Hovorka and others (1998) were increased by a minimum 

factor of about 5 if specific-capacity tests with no measurable 

drawdown were included. Mean hydraulic conductivity of 

the confined zone is more than 120 times greater than mean 

hydraulic conductivity in the recharge zone. Based on experimental and theoretical semivariograms (statistically based, 

qualitative functions that characterize spatial continuity of a 

dataset—that is, how quickly values change with changing 

distance and direction in space), Hovorka and others (1998) 

concluded that small-scale variability in hydraulic conductivity is large; even closely spaced measurements might differ 

by a factor of 1,000. The small-scale randomness most likely 

reflects the variable contributions of matrix, fracture, and conduit permeability to the measured average value obtained in 

aquifer tests. Vertical variations in permeability in the Edwards 

aquifer indicate that the entire aquifer is highly permeable, as 

well as highly variable. Structurally influenced cave systems contribute the highest hydraulic conductivities (30.8 to 

32.3 m/d), solution-enhanced fractures and stratigraphically 

controlled karst contribute intermediate values, and the porous 

carbonate matrix contributes hydraulic conductivities of 3.0 × 

10-4 to 30.8 m/d (Hovorka and others, 1998). Matrix permeability accounted for a large fraction of the permeability in 

intervals of low hydraulic conductivity determined from aquifer tests. In intervals of relatively high hydraulic conductivity 

from tests, the matrix contribution was less than 1 percent.

Anisotropy of an aquifer is indicated when the hydraulic 

conductivity shows variations with the direction of measurement at any given point in a geologic formation. Therefore, an 

anisotropic aquifer will have a greater hydraulic conductivity 
Conceptualization of the Edwards Aquifer 25

in one or more directions depending upon geologic and 

hydrologic conditions. Anisotropy either can be intrinsic to the 

geologic material (such as that caused by the platey bedding 

of the components of clayey materials) or can be caused by 

the directional persistence of heterogeneous features, such as 

conduits. Both Hovorka and others (2004; fig. 24, p. 41) and 

Worthington (2004; fig. 21, p. 31) postulate the presence of 

conduits that coincide with major flow paths in the Edwards 

aquifer. Factors that likely influence anisotropy in the aquifer 

also include the presence of barrier faults with large vertical displacements. The disruption of groundwater flow by 

faults might be strongly influenced by major disruptions in 

the lateral continuity of highly permeable strata. The quantitative magnitude of anisotropy of the Edwards aquifer is largely 

unknown. The ratio of anisotropy (ratio of y-direction hydraulic conductivity to x-direction hydraulic conductivity) derived 

from past digital-model analysis ranges from 0:1 (hydraulic 

conductivity in the y-direction is zero, caused, for example, by 

a barrier fault) to 1:1 (aquifer is isotropic) (Maclay and Land, 

1988). The regional maximum directional hydraulic conductivity is aligned parallel with structural features and prevailing 

groundwater flow paths.

The amount and distribution of water in the Edwards 

aquifer are related to the development of porosity and the 

storage characteristics of the aquifer. Hovorka and others 

(1996) estimated that Edwards aquifer porosity varies vertically from lows of 4–12 percent to highs of 20–42 percent, 

with an average for the entire aquifer of 18 percent (table 3). 

Kuniansky and others (2001) found that an effective porosity of 1–3 percent was needed for the karst Edwards aquifer 

system in Texas to match estimated traveltimes derived from 

geochemical mixing models. 

Groundwater-Flow System

Groundwater flow in karst typically includes diffuse 

or matrix flow (slow flow system), flow through fractures, 

and flow through large conduits (fast flow system). Flow in 

conduits is rapid, often turbulent and restricted to discrete 

pathways, whereas flow in the matrix system is more comparable to Darcian flow in porous media (Shuster and White, 

1971). Atkinson and Smart (1981) reported that the presence of turbulent flow in conduits is the definitive characteristic of karst aquifers. Hauwert, Johns, and Sharp (2002), 

Hauwert, Sansom, and others (2002), Schindel and others 

(2002), and Worthington (2004) presented results indicating 

that turbulent flow occurs in conduits in the Edwards aquifer. 

The porous matrix rock can act either as a sink draining water 

from the conduits or as a source supplying the conduits with 

water from the aquifer storage (Bauer and others, 2003). In the 

Edwards aquifer, high matrix porosity and permeability likely 

are overshadowed by high permeability developed in structurally influenced karstic conduit systems that transmit water 

into, through, and out of the aquifer system. The groundwaterflow system of the Edwards aquifer in the San Antonio region 

includes the following components (figs. 2, 13):

1. The catchment area in the Edwards Plateau, where the 

rocks of the Edwards-Trinity and Trinity aquifers 

are exposed and receive direct recharge to the water 

table. Erosion has removed Edwards Group rocks at 

the southern margin of the plateau (Hill Country), 

leaving only the Trinity aquifer present (fig. 13).

2. The recharge zone in the northern and northeastern 

parts of the Balcones fault zone, where streams lose 

flow directly into the unconfined Edwards aquifer 

and where the aquifer receives direct recharge to the 

water table.

3. The confined zone in the southern and southeastern 

part of the Balcones fault zone, which comprises 

the freshwater zone and the freshwater/saline-water 

transition zone.

A potentiometric-surface map for the Edwards aquifer 

based on water-level measurements made during October and 

November 2001 (Roberto Esquilin, Edwards Aquifer Authority, written commun., 2004) (fig. 11). indicates that water that 

entered the catchment area and recharge zone moves from 

unconfined to confined parts of the aquifer through generally southeasterly flow paths. In the confined zone, the water 

moves under low hydraulic gradients through fractured, highly 

transmissive, cavernous strata toward the east and northeast, 

where it is discharged through springs and wells. Regionally 

the hydraulic gradients include (1) a broad, low-gradient part 

of the aquifer in the confined zone in Medina and Bexar Counties and (2) generally steep gradients across the transition from 

the unconfined to confined parts of the Edwards aquifer.

Conduits could be major contributors to flow in the 

Edwards aquifer (Hovorka and others, 2004; Worthington, 

2004). The multimodal hydraulic conductivity distribution of 

the Edwards aquifer (Hovorka and others, 1998) implies that 

the fastest moving water can travel many times faster than the 

largest volume of water. The contribution of matrix permeability to regional-scale hydraulic conductivity likely is minor, 

and most Edwards aquifer water flows through fractures and 

conduits (Hovorka and others, 1998). Both Hovorka and 

others (2004; fig. 24, p. 41) and Worthington (2004; fig. 21, 

p. 31) inferred the presence of conduits and major flow paths 

from central Bexar County to western Medina County, with 

an east-west orientation that indicates structural influence. 

Hovorka and others (2004) postulated a complex of interconnected conduits, with about one-half the segments parallel to 

faults and one-half of them crossing faults at an appreciable 

angle. The presence of conduits and major flow paths also are 

indicated along parts of the freshwater/saline-water interface 

in Medina and western Bexar Counties.

Faults can either increase or decrease permeability (Hovorka and others, 1998). Some of the abundant, interconnected 

fractures in intensely fractured zones adjacent to faults have 

been enlarged, and they might focus flow parallel to faults. 

Where calcite cement fills breccia, cross-fault flow might be 

decreased. Stratigraphic offset of permeable zones along faults 
Figure 13. Generalized north to south hydrogeologic section and potential paths of groundwater flow for the local-scale study area, San Antonio regBarker and Ardis, 1996, plates 1 and 3). 

EDWARDS PLATEAU

HILL COUNTRY

GU

Edwards

Trinity Group

Edwards Group Trinity

Group Del Rio Clay

Eagle Ford Group, Austin 

and overly

Trinity Group

Edwards Group

Hammett Shale

Group

Balcones

escarpment

NOT TO SCALE

Trinity Grou

Edwards aquifer recharge zone

Balcones fault zone

Catchment area

Unconfined

aquifer Confined aquifer

EXPLANATION

Upper confining unitEdwards aquifer Unconfined aquifer Confined aquiferEdwards-Trinity aquiferTrinity aquifer

LimestoneSandUnderlying rock unitsApproximate freshwater/saline- water interfaceGeneralized conduit systemGeneralized direction of groundwater flowFault—Arrows indicate direction of movement

Streamflow

diminishes

to zero 

L a n d s u r f a c e
Conceptualization of the Edwards Aquifer 27

might also decrease the cross-fault flow (Maclay and Small, 

1983, 1984). Holt (1959) observed nearly 30.5 m of head difference across faults in northern Medina County, and George 

(1952) reported head differences of 1.8–7.9 m across segments 

of major faults in unconfined, less-permeable parts of the 

aquifer in Comal County. Maclay (1995) and Groschen (1996) 

characterized flow in the Edwards aquifer as being controlled 

laterally by barrier faults that locally compartmentalize the 

aquifer, especially toward the eastern part of the San Antonio 

segment. Maclay and Land (1988) and Clark and Journey 

(2006) hypothesized that large-throw faults segment the aquifer and divert flow entering the recharge zone on relay ramps 

to the west before flow is redirected toward the east.

Several 4.8- to 11.3-km-long sections of large-throw 

faults are coincident with a steep gradient between the 

confined and unconfined sections of the Edwards aquifer, 

which would indicate that faults or stratigraphic juxtaposition 

limit cross-fault flow. Notches in water-level maps, however, 

indicate that more permeable zones provide connections 

between the recharge zone and the confined aquifer (Hovorka 

and others, 2004). Some areas of steep hydraulic gradient 

are coincident with faults, but in most areas the water-level 

change appears to be gradational rather than sharp. Only at 

large-throw faults is there a transition directly from recharge 

(unconfined) zone to confined zone across a fault boundary. 

Hovorka and others (2004) determined the saturated 

thickness of the San Antonio segment of the Edwards aquifer, 

computed as the water-level altitude minus the altitude of the 

top of the Trinity aquifer (Glen Rose Limestone). The findings indicate that the Edwards Group is saturated over only a 

part of the recharge zone, which indicates that recharge flows 

through the Edwards Group into the upper beds of the underlying Glen Rose Limestone before returning to the Edwards 

Group. Veni (George Veni and Associates, written commun., 

2003) has documented cave patterns in the northern Bexar 

County area, as well as other locations in the Edwards aquifer 

recharge zone, that indicate that the upper part of the Glen 

Rose Limestone is hydrologically connected to the Edwards 

Group. 

Recharge

The Edwards aquifer is recharged through (1) seepage losses in streambeds of surface streams that drain the 

Hill Country, where the streams flow onto the outcrop of the 

Edwards aquifer; (2) infiltration of rainfall on the outcrop 

in interstream areas; (3) subsurface inflow across the updip 

margin of the Balcones fault zone, where the Trinity aquifer is 

laterally adjacent to the downfaulted Edwards aquifer (LBGGuyton Associates, 1995); and (4) movement of water from 

the Trinity aquifer into the overlying Edwards aquifer. The 

primary source of recharge is seepage from streams crossing the outcrop of the Edwards aquifer (hence, the outcrop is 

synonymous with the recharge zone). In the catchment area 

(fig. 2), streams gain water as they flow over low-permeability 

Glen Rose Limestone, which is at the surface over most of the 

catchment area. Streams become predominantly losing streams 

and recharge the Edwards aquifer as they cross the outcrop. 

Reported percentages of the total recharge that occurs as infiltration of rainfall on the outcrop in interstream areas, rather 

than as seepage losses through streambeds, are (1) 15 percent 

for the Barton Springs segment of the Edwards aquifer (Slade 

and others, 1985; Scanlon and others, 2002) and (2) 20 percent 

(Klemt and others, 1979; Thorkildsen and McElhaney, 1992) 

and 40 percent (Maclay and Land, 1988) for the San Antonio 

segment (fig. 1). Major streams that cross the recharge zone 

of the Edwards aquifer in the local-scale study area are the 

Medina River and Hondo and Salado Creeks (fig. 3). 

Water moves from stream channels to the water table of 

the unconfined Edwards aquifer in the recharge zone, where 

the water table is at depths generally greater than 30.5 m 

below the streambeds. All of the base flow from the catchment 

area (fig. 13) and some of the storm runoff of streams crossing 

the recharge zone infiltrate to the unconfined aquifer. Karst 

features and faults occur in the recharge zone and may provide 

pathways for water to move rapidly from land surface to the 

water table. Estimates of the combined recharge to the San 

Antonio segment of the Edwards aquifer from stream seepage 

and infiltration of rainfall range from a low of 53.9 million 

m3

 during 1956 to a high of 3,066.8 million m3 during 1992 

(Hamilton and others, 2003). The long-term (1934–2002) 

mean annual recharge to the Edwards aquifer is 862.2 million 

m3 (median 688.1 million m3) and for 1993–2002 is 979.6 

million m3 (median 710.9 million m3) (Hamilton and others, 2003). Much of the annual flow of the Medina River is 

impounded in Medina Lake (U.S. Army Corps of Engineers, 

1965). Of the volume impounded, about one-half seeps into 

the Edwards aquifer from the lake and its irrigation facilities 

(U.S. Army Corps of Engineers, 1965).

Monthly rates of recharge for the San Antonio segment 

of the Edwards aquifer from seepage losses from streams and 

infiltration of rainfall in the recharge zone are computed from 

records of stream-gaging stations near upstream and downstream limits of the recharge area and from estimated runoff 

in the recharge area (Puente, 1978). Recharge by seepage 

losses from streams in the drainage area of a losing stream is 

computed by subtracting the flow at the downstream station 

from the sum of the flow at the upstream station and estimated 

inflow from adjacent interstream areas. Recharge by infiltration of rainfall is estimated on the basis of unit runoff from 

the catchment area (Puente, 1978). Groundwater evapotranspiration losses are assumed negligible because of the depth of 

the water table below land surface in the recharge zone. The 

recharge subzones present in the local-scale model area are 

(1) 80 percent of the area between the Sabinal and Medina 

Rivers subzone, (2) 100 percent of the Medina River subzone, 

and (3) 69 percent of the area between Medina River and 

Cibolo–Dry Comal Creek subzone (fig. 4). Monthly recharge 

estimates computed by the USGS, by recharge subzone, for 

the local-scale study area for 2001 are shown in table 4 at end 

of report. The percentages of area cited are the area of each 

recharge subzone in the local-scale model area compared to 
28 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

the total area of the recharge subzone (San Antonio segment 

of the Edwards aquifer). The percentages of the total recharge 

contributed by each recharge subzone are 39, 29, and 32 

percent for the area between the Sabinal and Medina Rivers, 

the Medina River, and the area between the Medina River and 

Cibolo–Dry Comal Creek subzones, respectively.

The Edwards aquifer in much of the Balcones fault zone 

is juxtaposed against the Trinity aquifer both at the surface 

and at depth, and the Trinity aquifer likely discharges directly 

into the Edwards aquifer. The volume of water that moves 

laterally from the Trinity aquifer into the Edwards aquifer 

currently (2010) cannot be explicitly measured. A number 

of studies have shown, either through hydraulic or chemical analyses, that groundwater likely flows from the Trinity 

aquifer into the Edwards aquifer (Long, 1962; Klemt and others, 1979; Walker, 1979; Senger and Kreitler, 1984; Slade and 

others, 1985; Maclay and Land, 1988; Waterreus, 1992; Stein, 

1993; Veni, 1994, 1995). Both units are karstic limestones, and 

large caves that cross the contact are interpreted as evidence 

that cross-formational flow occurs through karst systems in at 

least parts of the San Antonio segment of the Edwards aquifer 

(Veni, 1988; Vauter, 1992). Mace and others (2000) indicated 

that groundwater from the Trinity aquifer discharges to the 

south and east in the direction of the Edwards aquifer. The volume of flow from the Trinity aquifer into the Edwards aquifer 

can only be estimated. The available estimates vary, ranging from about 2 percent to 6 percent of total average annual 

recharge to the Edwards aquifer (Woodruff and Abbott, 1986; 

LBG-Guyton Associates, 1995). A flow of about 79.0 million 

cubic meters per year (m3

/yr) from the upper and middle zones 

of the Trinity aquifer in the direction of the Edwards aquifer, 

representing about 9 percent of the average estimated annual 

recharge to the Edwards aquifer, was simulated by Mace and 

others (2000). Lindgren and others (2004) reported simulated 

inflow from the Trinity aquifer into the Edwards aquifer at 

the northern recharge zone boundary for the San Antonio and 

Barton Springs segments of the Edwards aquifer for a steadystate simulation of 49.7 million m3

/yr, about 6.9 percent of the 

simulated recharge to the aquifer. For a transient simulation, 

simulated inflow from the Trinity aquifer ranged from about 

3.4 percent of the total simulated sources to the aquifer during 

a period of above-normal rainfall and recharge to about 39.4 

percent during a period of drought. 

Discharge

Discharge from the Edwards aquifer occurs (1) as 

withdrawals by municipal, industrial, irrigation, and livestock wells and (2) as springflow. Groundwater withdrawals 

by wells have increased with increasing population. From 

1934 through 2002, the lowest estimated annual pumpage 

(withdrawals) for the San Antonio segment of the Edwards 

aquifer was 125.7 million m3 in 1934, and the highest was 

669.1 million m3 in 1989 (Hamilton and others, 2003). 

Springflow from the San Antonio segment averaged 459.2 

million m3

/yr (median 463.6 million m3/yr) for 1934–2002 

(Hamilton and others, 2003). Total annual springflow from the 

Edwards aquifer has varied as much as an order of magnitude 

over the period of record. Springflow totaled 86.1 million m3

in 1956 during the 1950s drought and reached a record high 

of 990.4 million m3 in 1992 (Hamilton and others, 2003). 

Annual total discharge from the San Antonio segment generally has increased since the mid-to-late 1960s. This increase 

largely results from an approximate doubling of the well 

pumpage. 

Thousands of water wells tap the Edwards aquifer in 

the San Antonio region. Annual discharge by wells increased 

steadily at an average annual rate of about 5.6 million m3/yr, 

more than tripling between 1939 and 2000 (Hamilton and 

others, 2003). Estimated annual groundwater withdrawals 

from the Edwards aquifer by wells in the local-scale study 

area during 2001 were 264.1 million m3 (table 5 at end of 

report). Mean daily and mean annual groundwater withdrawal 

rates for wells in the local-scale study area, by water-use 

type, are shown in table 5. Municipal and industrial water 

use account for about 82 percent of annual withdrawals from 

the Edwards aquifer in the local-scale study area (table 5), 

primarily in the San Antonio region in the eastern part of the 

study area. Irrigation accounts for about 17 percent of annual 

groundwater withdrawals in the local-scale study area (table 

5), primarily in Medina County in the western part of the 

study area. The locations of groundwater withdrawal wells 

in the local-scale study area are shown in figure 14. Groundwater withdrawals are primarily from the confined part of the 

Edwards aquifer, with the largest withdrawals in and around 

San Antonio. 

Yields of more than 2.0 million m3/yr (3.8 m3/min) are 

common for wells in the confined freshwater zone of the 

Edwards aquifer (Maclay, 1995). Yields of wells commonly 

are limited more by the capacity of the pumps to discharge 

water than by the productivity of the aquifer. The density of 

wells in the unconfined recharge zone of the aquifer is substantially less than that in the confined zone, and typically the 

yields are smaller. The smaller yields are the result of generally less saturated thickness and hydraulic conductivity in the 

unconfined zone. 

Springs and seeps are the major natural discharge outlets 

for the Edwards aquifer, accounting for nearly all natural 

discharge from the aquifer (Maclay, 1995). San Antonio and 

San Pedro Springs in Bexar County are the largest springs in 

the local-scale study area, with mean flow rates of 0.91 cubic 

meters per second (m3

/s) (28.7 million m3/yr) and 0.24 m3/s 

(7.6 million m3/yr), respectively, during 2001 (Hamilton and 

others, 2003). Groschen (1996) postulated that the locations 

of most major springs in the Edwards aquifer are structurally 

controlled. Groundwater flow is diverted along barrier faults, 

with vertical openings at a few places along faults where 

springs can emerge. Structural constrictions can also facilitate 

the rise of water along faults. San Antonio and San Pedro 

Springs discharge groundwater that rises along a major fault. A 

structural horst near the fault acts as a barrier to groundwater 

flow in a complex graben and diverts flow around its northern 
Conceptualization of the Edwards Aquifer 29

and southern margins, some of which emerges as springflow 

(Maclay, 1995).

Increased pumpage, primarily from wells in San Antonio, 

has resulted in frequent periods of zero discharge from San 

Antonio and San Pedro Springs (Brune, 1975). San Antonio 

Springs has flowed intermittently since 1950—but only during 

periods of relatively high water-level altitudes. Periods of zero 

discharge have been appreciably more frequent and of longer 

duration for San Antonio Springs than for San Pedro Springs. 

Extended periods of zero discharge for San Antonio Springs 

include June 1949 to February 1958, June 1962 to April 1965, 

July 1965 to December 1967, July 1982 to October 1985, June 

1988 to November 1991, and May 1995 to May 1997. In contrast, the only extended period of zero discharge lasting more 

than 1 year for San Pedro Springs was July 1951 to October 

1957. However, the discharge from San Antonio Springs typically is much greater than for San Pedro Springs, for example, 

72.3 million m3

/yr(2.3 m3/s) for San Antonio Springs compared to 12.3 million m3

/yr (0.4 m3/s) for San Pedro Springs in 

2002. The more frequent and longer duration periods of zero 

discharge combined with greater magnitudes of discharge for 

San Antonio Springs relative to San Pedro Springs reflect the 

larger discharge capacity and higher spring orifice altitude for 

San Antonio Springs.

Figure 14. Locations of groundwater withdrawal wells in the local-scale study area, San Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

ESpring

Groundwater-withdrawal well, by water use

 Municipal

 Industrial

 Irrigation

 Stock

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary (modified

 from Puente, 1978)

Freshwater/saline-water interface (1,000 milligrams per liter

 dissolved solids concentration) (A.L. Schultz, consultant,

 written commun., 2000)

EXPLANATION
30 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Simulation of Groundwater Flow

The local-scale groundwater-flow model simulates 

steady-state conditions in the Edwards aquifer that are 

representative of long-term stresses, including recharge and 

pumpage. Average stresses (recharge and pumpage) during 

2001, a representative year for a recent time period (2000–10), 

were used to simulate steady-state conditions, as discussed in 

the “Development and Application of Groundwater Flow and 

Particle-Tracking Models” section of this report. Differences 

between measured and simulated water-level altitudes (residuals) were calculated for 84 wells to compare measured mean 

water-level altitudes to simulated water levels from the model. 

The 84 wells were as follows: (1) the 6 wells installed for the 

TANC local-scale study from 2007 to 2010, (2) 6 wells in the 

vicinity of the selected PSW equipped with water-level recorders from 2007 to 2010 for the TANC local-scale study, and 

(3) 72 monitoring wells measured biannually by EAA during 

2001 (table 6 at end of report). Residuals between measured 

and simulated water-level altitudes are shown in table 6. The 

measured and simulated springflow volumes and their residuals for San Antonio Springs and San Pedro Springs are also 

shown in table 6.

The rediscretized regional Edwards aquifer models 

developed for the regional TANC study (Lindgren and others, 2011) were used to provide initial water-level altitudes, 

groundwater withdrawal rates, recharge rates, selected initial 

hydraulic properties, drain locations, and initial drain hydraulic conductances for the local-scale model. Specified fluxes at 

the lateral boundaries of the local-scale model were derived 

from the simulated flows from the diffuse-flow rediscretized 

regional Edwards aquifer model. The local-scale model grid 

covers about 4,249 km2

 and, like the rediscretized regional 

Edwards aquifer models, is rotated 35 degrees counterclockwise from horizontal. The local-scale model grid has a finer 

vertical discretization than do the rediscretized regional 

Edwards aquifer models and incorporates refined parameter 

zones corresponding with multiple hydrogeologic units. 

The local-scale model simulations also use the MODFLOW 

Hydrogeologic-Unit Flow Package (Anderman and Hill, 

2000) and include two hydrogeologic units that are intended 

to simulate fast flow paths attributable to karst features. The 

selected initial hydraulic properties and initial drain hydraulic 

conductances from the rediscretized regional Edwards aquifer 

models were revised in the local-scale model during model 

calibration. 

Model Description

A description of the local-scale model includes the 

structure and hydraulic properties of the aquifer, the boundary 

conditions imposed, and the stresses on the aquifer. Pertinent hydraulic and hydrologic characteristics of the aquifer 

for appropriate cells within the grid are needed to solve the 

governing partial-differential equation. Specific parameters 

required for the local-scale model include (1) active and inactive cells, (2) elevations of the top and bottom of model layers, 

(3) fault locations and horizontal conductance, (4) horizontal 

hydraulic conductivity, (5) horizontal and vertical anisotropy, (6) boundary fluxes, (7) recharge rates, (8) groundwater 

withdrawal rates, (9) drain elevation and conductance, and 

(10) initial water-level altitudes.

The FORTRAN computer-model code MODFLOW-2000 

(Harbaugh and others, 2000), a modular finite-difference 

groundwater flow code developed by the USGS, was used 

to simulate groundwater flow in the Edwards aquifer. The 

local-scale model uses the Basic, Output Control, Hydrogeologic-Unit Flow, Recharge, Well, Horizontal-Flow Barrier, 

Drain, and Geometric Multigrid (GMG; numerical solver) 

MODFLOW modules, or “packages,” to simulate groundwater 

flow in the Edwards aquifer. The software Groundwater Vistas 

version 5 (Groundwater-vistas.com, A Division of Scientific 

Software Group, Sandy, Utah) was used as a preprocessor and 

postprocessor to facilitate data entry and allow analysis of 

model output (Environmental Simulations, Inc., 2007).

The MODFLOW Hydrogeologic-Unit Flow (HUF) Package (Anderman and Hill, 2000) is an alternative internal flow 

package that allows the vertical geometry of the system hydrogeology to be defined explicitly within the model by using 

hydrogeologic units that can be different from the definition 

of the model layers. The geometry of the hydrogeologic units 

is defined independently of the model layers. For the MODFLOW Groundwater Flow Process, the HUF Package calculates effective hydraulic properties for the model layers on the 

basis of the hydraulic properties of the hydrogeologic units, 

which are defined by using parameters. The hydraulic properties are used to calculate the conductance coefficients and 

other terms needed to solve the groundwater-flow equation. 

The HUF Package supports parameters that are used to define 

the following hydraulic properties, which are listed with their 

parameter type in parentheses: horizontal hydraulic conductivity (HK), horizontal anisotropy (HANI), vertical hydraulic 

conductivity (VK), vertical anisotropy (VANI), specific storage (SS), and specific yield (SY).

Model Geometry and Discretization

The uniformly spaced finite-difference grid used to 

spatially discretize the model area for the local-scale model 

has 300 rows and 350 columns and is rotated 35 degrees 

counterclockwise from horizontal (fig. 4). The dimensions of 

the grid cells are uniformly 201.2 m along rows and columns, 

the same as the dimensions for the rediscretized regional 

Edwards aquifer models (Lindgren and others, 2011). The 

local-scale model grid includes areas beyond the boundaries 

of the recharge zone to the north. Model cells in these areas 

were made inactive (no-flow cells), which resulted in about 

63 percent of the cells in the grid being active. The localscale model has 92 layers, each with a uniform thickness of 

8 m and top and bottom surfaces that dip downward to the 

south and east with a uniform slope, following the general 
Simulation of Groundwater Flow 31

slope of the top of the Edwards aquifer. The layer thickness of 

8 m was chosen as an acceptable trade-off between maximizing the vertical discretization for particle tracking purposes 

and minimizing the total number of cells in the model. The 

local-scale model includes 12 HGUs, whose properties are 

defined by using the HUF Package. The 12 HGUs include 8 

HGUs previously defined for the Edwards aquifer (Maclay, 

1995, fig. 11), 2 HGUs with high hydraulic conductivities (one 

or more orders of magnitude higher than for the other HGUs) 

(“conduit” HGUs), 1 HGU overlying the Edwards aquifer, and 

1 HGU underlying the Edwards aquifer. The geometry of the 

HGUs is defined independently of the model layers, with the 

model-layer geometry superimposed on the defined HGUs. In 

the local-scale model, one to three HGUs are present in each 

active model cell.

The HGUs specified in the local-scale model are shown 

in figure 15 and table 7 at end of report. HGU1 (overburden) represents a composite unit comprised of the geologic 

materials that overlie the Edwards aquifer in the local-scale 

model area. HGU1 ranges in thickness from 0.3 to 759 m, 

where present, and because it is predominantly a confining unit it was not simulated in the rediscretized regional 

Edwards aquifer models (Lindgren and others, 2011). HGU1 

was included in the local-scale model because of horizontal 

hydraulic discontinuities between HGUs in some areas near 

the southern boundary of the recharge zone that result from the 

effects of large-displacement faults. The displacement of these 

faults along some segments exceed the aquifer thickness, in 

some cases lowering the top of the uppermost HGU in one cell 

below the bottom of the lowermost HGU in an adjacent cell, 

thereby creating a hydrogeologically undefined vertical interval (hydraulic discontinuity). HGU2 (Georgetown Formation), 

HGU3 (cyclic and marine members of the Edwards Group), 

HGU4 (leached and collapsed members of the Edwards 

Group), HGU6 (regional dense member of the Edwards 

Group), HGU7 (grainstone member of the Edwards Group), 

HGU8 (Kirschberg evaporate member of the Edwards Group), 

HGU10 (dolomitic member of the Edwards Group), and 

HGU11 (basal nodular member of the Edwards Group) represent the commonly defined stratigraphic units of the Edwards 

aquifer (Maclay, 1995; fig. 11, p. 26) (fig. 10), with differing 

lithologic and hydrologic properties. HGU5 and HGU9 are 

the “conduit” HGUs representing hydrogeologic units with 

high hydraulic conductivities (one or more orders of magnitude higher than for the other HGUs) intended to simulate fast 

flow paths attributable to karst features. HGU12 represents 

the Glen Rose Limestone of the Trinity Group that underlies 

the Edwards Group and has a relatively small permeability 

compared to the permeability of the Edwards aquifer. HGU12 

was included in the local-scale model to prevent unsaturated 

or thinly saturated areas from going dry (simulated water level 

falling below the simulated base of the model layer) in the 

recharge zone. Part of the underlying, lower permeability Glen 

Rose Limestone of the Trinity Group was added to the total 

aquifer thickness in the recharge zone and unconfined areas 

near the recharge zone.

In the HUF Package, HGUs are defined by the top altitude and thickness of each HGU for each row and column in 

the model grid. If an HGU does not occur at a row and column 

location, then the thickness is set to zero. The top altitude for 

HGU1, where present, was specified as land surface altitude. 

HGU1 is absent in the recharge zone, where the Edwards 

aquifer outcrops. HGU7, HGU8, HGU9, HGU10, HGU11, 

and HGU12 occur at land surface at various locations in the 

recharge zone, and for model cells in these areas the top altitudes for the appropriate HGUs are specified as land surface 

altitude. The altitude of the top of the Georgetown Formation 

(HGU2), the uppermost HGU of the Edwards aquifer, was 

derived from available drillers’ logs in the local-scale model 

area. The altitudes of the tops of the remaining nine HGUs 

composing the Edwards Group corresponding to the Edwards 

aquifer (HGU3, HGU4, HGU5, HGU6, HGU7, HGU8, 

HGU9, HGU10, and HGU11) and of HGU12 underlying the 

Edwards aquifer were calculated in a downward progression 

as the top altitude of the overlying HGU minus the thickness 

of the overlying HGU. The thicknesses for HGU1 were calculated as the differences between the altitude of the land surface 

and the altitude of the top of the Georgetown Formation. The 

thicknesses for the HGUs composing the Edwards aquifer, 

other than the conduit HGUs (HGU5 and HGU9) representing 

relatively fast flow paths attributable to karst features, were 

derived from available drillers’ logs in the local-scale model 

area. Groundwater velocities in the conduit HGUs are likely 

appreciably greater than average velocities in the other HGUs. 

Walker (1979) reported that groundwater moving through 

fractured, jointed, or solutioned rocks [conduits] could move 

on the order of 100 m/d compared to velocities of a meter 

per year in other parts of the aquifer. Tracer testing in the San 

Antonio segment of the Edwards aquifer has shown rapid 

flow (velocities of 179.8 to 800.1 m/d over distances of 0.8 

to 4.0 km) from wells to the nearby high flow springs (Ogden 

and others, 1986; Rothermel and others, 1987; Schindel and 

others, 2002). The thicknesses for HGU5 and HGU9 (the 

conduit HGUs) were initially specified as a uniform 3 m but 

were increased to a uniform 8 m during model calibration. 

The thicknesses for HGU12 (Glen Rose Limestone member 

of the Trinity Group corresponding to the Trinity aquifer) were 

obtained from the rediscretized regional Edwards aquifer models (Lindgren and others, 2011). The maximum thicknesses 

range from 8 m for HGU5 and HGU9 to 759 m for HGU1, 

with much of the thickness for HGU1 being unsaturated. The 

maximum thicknesses for the HGUs composing the Edwards 

aquifer, other than HGU5 and HGU9, range from 12 m 

(regional dense member of the Edwards Group corresponding to the Edwards aquifer) to 51 m (leached and collapsed 

members of the Edwards Group corresponding to the Edwards 

aquifer). 

Karst features were incorporated into the local-scale 

model by specifying two comparatively thin (8 m) HGUs with 

large horizontal hydraulic conductivities (initial values of 

152,393 m/d) and low effective porosities (initial dimensionless values of 1.0 × 10-4). The top altitudes and thicknesses for 
32 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

the conduit HGUs (HGU5 and HGU9) were specified so as to 

correspond with the lower 8 m of the leached and collapsed 

members of the Edwards Group for HGU5 and the lower 8 m 

of the Kirschberg evaporite member of the Edwards Group for 

HGU9. Geophysical logging by the USGS in 2008 (Gregory 

Stanton, U.S. Geological Survey, written commun., 2008) in 

the selected PSW and nearby monitoring wells indicated that 

most of the flow and the greatest transmissivities occurred in 

the leached and collapsed members of the Edwards Group and 

the Kirschberg evaporite member of the Edwards Group. The 

large flows and high estimated transmissivities for these intervals are thought to reflect the presence of fast flow paths and 

conduit features, and the conduit HGUs were therefore specified for these approximate intervals. Scant information exists 

regarding hydraulic properties, flow rates, and karst features of 

the Edwards aquifer HGUs other than the geophysical logging 

done in 2008 (Gregory Stanton, U.S. Geological Survey, written commun., 2008). Therefore, the results from the selected 

PSW and nearby monitoring wells were extrapolated throughout the local-scale model area, and the top altitudes and 

thicknesses for the conduit HGUs (HGU5 and HGU9) were 

specified so as to correspond with the lower 8 m of the leached 

and collapsed members and the Kirschberg evaporite member 

of the Edwards Group throughout the local-scale model area. 

The thicknesses of HGU4 (leached and collapsed members of 

the Edwards Group) and HGU8 (Kirschberg evaporite member 

of the Edwards Group) were reduced by 8 m to accommodate 

the inclusion of the conduit HGUs.

Numerous faults with varying vertical displacements 

occur in the local-scale model area. The extensive faulting 

results in the juxtaposition of HGUs with differing hydraulic 

properties and has appreciable effects on groundwater flow 

in the Edwards aquifer. As previously discussed in this section, the displacement of faults along some segments exceeds 

the aquifer thickness, thereby creating a hydrogeologically 

undefined vertical interval (hydraulic discontinuity) in the 

local-scale model. Because the local-scale model uses the 

MODFLOW HUF Package and the geometry of the hydrogeologic units is defined independently of the model layers, different HGUs with differing hydraulic properties are frequently 

Figure 15. Generalized hydrogeologic sections and measured and simulated tritium concentrations in the local-scale study area, San 

Antonio region, Texas.

NORTH

SOUTH

A

HGU1

HGU2

HGU 3

HGU 4

HGU 5 HGU 7

HGU 10

HGU 11

HGU 12

HGU 1

HGU 2

HGU 3

HGU 4 HGU 5

HGU 6 HGU 7 HGU 8

HGU 9 HGU 10

HGU 11

HGUs 6–11

are discontinuous and

undifferentiated

in recharge zone 

HGU 3

HGU 4

HGU 7

HGU 10

HGU 11

HGU 2

HGU 9

HGU 5

HGU 6

HGU 8

HGU 6

HGU 8

HGU 9

Selected public-supply well

Southern boundary

of recharge zone

Northern boundary

of recharge zone 

EXPLANATION

HGU 5

HGU 1

Hydrogeologic unit (HGU) and

 number—See table 7

HGU other than 5 and 9

HGUs 5 and 9 (conduit HGUs representing

 units with a high density of fast flow

 paths attributable to karst features)

Open interval

Simulated water-level altitude

Land-surface altitude

Well

Large displacement fault 
Simulation of Groundwater Flow 33

juxtaposed in adjacent cells in the local-scale model. This 

juxtaposition allows water particles to move between HGUs 

within the same model layer and incorporates the effects of 

faulting in the model geometry. In contrast, when the HGUs 

and model layers coincide, water particles are forced to move 

vertically along a simulated fault interface in order to stay in 

the same model layer. 

The MODFLOW Horizontal-Flow Barrier (HFB) 

Package (Harbaugh and others, 2000) was used to simulate 

faults in the local-scale model (fig. 12). Required parameters 

include the (1) location of the horizontal-flow barrier (fault) 

and (2) hydraulic characteristic of the horizontal-flow barrier 

(fault), a measure of conductance across the fault. Horizontalflow barriers were placed at the boundaries of cells crossed 

by the trace of a fault. Fault locations and fault displacements 

from the rediscretized regional Edwards aquifer models were 

revised and updated in the local-scale study area for inclusion in the local-scale model on the basis of current (2009) 

hydrogeologic and stratigraphic information. The location of 

a fault is specified by the cell locations for the two cells that 

the fault separates. The hydraulic characteristic of the fault is 

an inverse measure of the degree to which it acts as a barrier 

to flow, defined as the fault hydraulic conductivity divided by 

its width. When the assigned value for the hydraulic characteristic of the fault is greater, it acts less as a barrier to flow. 

For the local-scale model, the assumption was made that the 

degree to which a fault acts as a barrier to groundwater flow is 

proportional to the fault displacement, with the hydraulic characteristic of the fault being inversely proportional to the fault 

displacement. Because of the uncertainty of the components 

(fault hydraulic conductivity and fault width) typically used to 

compute the hydraulic characteristic, values for the hydraulic 

characteristic of faults were determined during model calibration. The faults were divided into five categories on the basis 

of their associated fault displacements and a hydraulic characteristic assigned, with categories of greater fault displacements being assigned lower hydraulic-characteristic values. 

The initial hydraulic-characteristic values ranged from 1.0 × 

10-9 to 0.02 per day for fault displacements ranging from 0 to 

more than 100 percent of the total aquifer thickness (fig. 12). 

The hydraulic-characteristic values were varied during model 

calibration until the appropriate simulated barrier effect was 

achieved on the basis of measured water-level altitudes and 

known effects of faults on groundwater-flow directions. 

Boundary Conditions and Model Stresses

Boundary conditions for the local-scale model include 

specified fluxes entering or exiting the model area at the 

boundaries, and stresses include recharge from precipitation, discharge from pumping, and discharge to springs. In 

the local-scale model, specified fluxes are used for boundary 

conditions on all sides and layers of the model, except for layers that are inactive at the model boundary or whose thickness 

includes only HGU1. Water flowing across the boundary into 

HGU1 is assumed to be negligible. Average stresses (recharge 

and pumpage) during 2001, a representative year for the recent 

time period (2000–10), were used to simulate steady-state 

conditions. 

Lateral Boundaries

The local-scale model employs lateral nonzero fluxes 

across boundaries so that the model extent does not have 

to include the natural hydrologic groundwater divides, thus 

allowing the focus of the modeling effort to remain on the 

ACR of the selected PSW. The nonzero fluxes are specified by 

Figure 15. Continued.

WEST EAST

B

S 2.17 (2.06)

I 2.08 (2.09)

D 2.13 (1.99)

D 1.72 (1.82)

I 1.77(1.85)

DS 2.23 (1.88)

DI 1.78 (1.87)

DD 1.90 (1.99)

HGU 11

HGU 10 HGU 9

HGU 8 HGU 7 HGU 6

HGU 5

HGU 4

HGU 3

HGU 2

HGU 1

Selected public-supply well

Zarzamora

monitoring wells Timberhill

monitoring wells

HGU 5

HGU 1

DS 2.23 (1.88)

S 2.17 (2.06)

Hydrogeologic unit (HGU) and

 number—See table 7

HGU other than 5 and 9

HGUs 5 and 9 (conduit HGUs representing

 units with a high density of fast flow paths

 attributable to karst features)

Open interval of monitoring well—S, I, D are sampling

 depths (shallow, intermediate, and deep, respectively);

 first number is measured tritium concentration, in tritium

 units (TU); number in parentheses is simulated tritium

 concentration, in TU; NM indicates no measurement

Open interval of selected public-supply well—

 DS, DI, DD are depth-dependent sampling depths;

 first number is measured tritium concentration, in TU;

 number in parentheses is simulated tritium

 concentration, in TU

Simulated water-level altitude

Land-surface altitude

Well

EXPLANATION

NM
34 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

using the MODFLOW Well Package (Harbaugh and others, 

2000). The northern boundary of the active local-scale model 

corresponds with the physical limits of the Edwards aquifer, 

more specifically with the northern limit of the Edwards aquifer recharge zone (fig. 4). A nonzero flux boundary was used 

for the northern model boundary to account for inflow from 

the adjacent Trinity aquifer. The fluxes from the two-layer 

diffuse-flow rediscretized regional Edwards aquifer model 

were apportioned among the 92 layers of the local-scale model 

on the basis of the cumulative transmissivities of the HGUs 

present in each boundary cell. Therefore, the highest fluxes in 

a vertical sequence of model layers for a given (row, column) 

grid location occur in the layers that contain the HGUs with 

the highest simulated transmissivities (horizontal hydraulic 

conductivity times thickness).

All specified nonzero boundary fluxes for the western, 

southern, and eastern boundaries of the local-scale model 

were derived from the two-layer diffuse-flow rediscretized 

regional Edwards aquifer model. The simulated fluxes from 

the diffuse-flow rediscretized regional Edwards aquifer model 

were used in the local-scale model, rather than from the 

conduit-flow rediscretized regional Edwards aquifer model, 

because of the dominant effect of the simulated conduits on 

simulated groundwater flow in the conduit-flow rediscretized 

regional Edwards aquifer model (Lindgren and others, 2011). 

The distribution of simulated fluxes into the local-scale 

model area is proportional to the simulated hydraulic conductivity in each model cell of the conduit-flow rediscretized 

regional Edwards aquifer model corresponding to model 

boundary cells in the local-scale model. Therefore, a comparatively high proportion of the boundary flux into the local-scale 

model area occurs through model cells of the conduit-flow 

rediscretized regional Edwards aquifer model that coincide 

with simulated conduit cells (Lindgren and others, 2011, 

fig. 9A). The simulated conduits in the conduit-flow rediscretized regional Edwards aquifer model are one cell wide and 

have assigned hydraulic conductivity values two to five orders 

of magnitude greater than the assigned hydraulic conductivity values for the nonconduit model cells. Similarly, for the 

diffuse-flow rediscretized regional Edwards aquifer model, a 

comparatively high proportion of the boundary flux into the 

local-scale model area occurs through cells that coincide with 

simulated high hydraulic conductivity zones (Lindgren and 

others, 2011, fig. 9B). The simulated high hydraulic conductivity zones in the diffuse-flow rediscretized regional Edwards 

aquifer model reduce the effects of uncertainty regarding the 

locations of conduits in the Edwards aquifer and spread the 

distribution of comparatively high boundary fluxes over the 

lateral extent. 

The simulated fluxes from the diffuse-flow rediscretized 

regional Edwards aquifer model include flows into and out 

of the local-scale model area for all three model boundaries. The net boundary flux for the western local-scale model 

boundary is into the local-scale model area (986,034 cubic 

meters per day [m3

/d]), while the net boundary fluxes for the 

eastern and southern local-scale model boundaries are out 

of the local-scale model area (782,013 and 327,430 m3/d, 

respectively) (table 8 at end of report). About 79 percent of the 

inflow through the western local-scale model boundary occurs 

through the boundary cells coinciding with the simulated high 

hydraulic conductivity zones through the center of the confined part of the aquifer and near the northern boundary of the 

freshwater/saline-water transition zone (HK zones 14 and 17) 

(fig. 16). Similarly, about 97 percent of the outflow through 

the eastern local-scale model boundary occurs through the 

boundary cells coinciding with the simulated high hydraulic 

conductivity zones in the southeastern part of the local-scale 

model area (HK zones 13, 16, and 17) (fig. 16). 

For the western, southern, and eastern boundaries of the 

local-scale model, the fluxes from the two-layer diffuse-flow 

rediscretized regional Edwards aquifer model were apportioned among the 92 layers of the local-scale model based 

on the cumulative transmissivities of the HGUs present in 

each boundary cell. Therefore, the highest fluxes in a vertical 

sequence of model layers for a given (row, column) grid location occur in the layers that contain the HGUs with the highest 

simulated transmissivities. Because the simulated conduit 

HGUs have assigned horizontal hydraulic conductivities that 

are at least an order of magnitude higher than for the other 

HGUs, the highest fluxes in a vertical sequence of model layers for a given (row, column) grid location occur in the layers 

that contain the conduit HGUs.

Recharge

Recharge to the Edwards aquifer occurs primarily by 

seepage from streams to the aquifer in the recharge zone 

(fig. 3). Additional recharge is from infiltration of rainfall in 

the interstream areas of the recharge zone. Recharge in the 

local-scale model by seepage from streams and infiltration of 

rainfall was assigned to nine streams (Hondo Creek, Verde 

Creek, Quihi Creek, Medina River, San Geronimo Creek, 

Culebra Creek, Helotes Creek, Leon Creek, and Salado Creek) 

and their interstream areas for three recharge subzones in the 

recharge zone (fig. 4) on the basis of monthly recharge rates 

to the Edwards aquifer for 2001 computed by the USGS and 

published, as annual totals, by the EAA (Hamilton and others, 

2003). The three recharge subzones in the local-scale model 

area are the area between the Sabinal and Medina Rivers, the 

Medina River, and the area between the Medina River and 

Cibolo–Dry Comal Creek (fig. 4). Monthly and annual (2001) 

recharge rates for the recharge subzones simulated in the 

local-scale model are shown in table 4. As for the rediscretized 

regional Edwards aquifer models (Lindgren and others, 2011), 

85 percent of the recharge was applied to streambed cells, 

and the remaining 15 percent was applied to the interstream 

area cells in the local-scale model, on the basis of percentages 

reported in the literature. A specified-flux boundary, simulated 

by using the MODFLOW Recharge Package (Harbaugh and 

others, 2000), was used to represent recharge to the aquifer in 

the recharge zone. No recharge was applied to cells outside the 

recharge zone.
Simulation of Groundwater Flow 35

Figure 16. Distribution of calibrated horizontal hydraulic conductivity in hydrogeologic units 2–4, 6–8, and 10–11 in the local-scale 

model, San Antonio region, Texas.

RAXEB

YTNUOC 

 ANIDEM

YTNUOC

MEDINA COUNTY

BANDERA COUNTY

Hondo

Castroville

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

Hondo

Castroville

San

Antonio

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

1

20

18

23

21

19

17

14

13

17

16

30

32

33

15

22

31

33

31

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

C A T C H M E N T A R E A C A T C H M E N T A R E A

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

 HK30 = 153

 HK31 = 322

 HK32 = 146

 HK33 = 107 

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop)

 boundary (modified from Puente, 1978)

Freshwater/saline-water interface (1,000

 milligrams per liter dissolved solids 

 concentration) (A.L. Schultz, consultant,

 written commun., 2000)

Spring

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area—Horizontal hydraulic conductivity

 (HK) zone number and calibrated HK value, in meters

 per day (table 9)

 Base HK, varies by hydrogeologic unit (table 9)

 HK13 = 6,584

 HK14 = 4,073

 HK15 = 5,863

 HK16 = 5,227

 HK17 = 4,297

 HK18 = 0.35

 HK19 = 2.56

 HK20 = 2.50

 HK21 = 1.59

 HK22 = 2.18

 HK23 = 17.3

EXPLANATION

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

1

15

16

17

18

19

20

21

22

23

30

31

32

33

14

13
36 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Discharge

Discharge from the Edwards aquifer includes withdrawals by wells and springflow. Average withdrawal rates by 

wells for 2001 were the same for both of the rediscretized 

regional Edwards aquifer models (conduit-flow and diffuseflow models), and these rates were distributed spatially within 

the model grid for the local-scale model, on the basis of the 

well locations. The vertical assignment of withdrawals to a 

model layer was done on the basis of the percentage of the 

screened interval in each of the model layers and the transmissivity of the HGUs present in each model layer. Withdrawals 

were separated into four categories according to water use: 

municipal, industrial (includes manufacturing, mining, and 

power generation), irrigation, and livestock (table 5). Municipal withdrawals were provided (1) by well by EAA (Edwards 

Aquifer Authority, 2009) and Bexar Metropolitan Water District and (2) for each of their well fields by SAWS (San Antonio Water System, 2008). Industrial, irrigation, and livestock 

withdrawals were provided by well by EAA (Edwards Aquifer 

Authority, 2009) for most of the model area, but in some areas 

irrigation withdrawals were spatially distributed for the landuse categories of row crops, small grains, and orchards/vineyards. Groundwater withdrawals were simulated by using the 

MODFLOW Well Package (Harbaugh and others, 2000).

Discharge from the Edwards aquifer also includes 

springflow. San Antonio and San Pedro Springs (fig. 3) were 

simulated in the local-scale model and used during model 

calibration in addition to water-level information. The springs 

were simulated in the model by using the MODFLOW Drain 

Package (Harbaugh and others, 2000). The MODFLOW Drain 

Package simulates the effects of features that remove water 

from the aquifer at a rate proportional to (1) the difference 

between the water level in the aquifer and the drain elevation 

and (2) the hydraulic conductance. The hydraulic conductance 

depends on the characteristics of the convergent flow pattern 

toward the drain, as well as on the characteristics of the drain 

itself and its immediate environment (Harbaugh and others, 

2000). The initial drain hydraulic conductances specified 

in the local-scale model were the same as those used in the 

conduit-flow and diffuse-flow rediscretized regional Edwards 

aquifer models (Lindgren and others, 2011) (drain hydraulic 

conductances have the same values in both regional models). 

The initial drain hydraulic conductances for San Antonio and 

San Pedro Springs were 613,100 and 3,066 m2

/d, respectively. 

The drain hydraulic conductances were adjusted during model 

calibration for the local-scale model to match the mean measured values of discharge during 2001 for San Antonio and 

San Pedro Springs to simulated values.

Hydraulic Properties

The aquifer hydraulic properties specified in the localscale model—horizontal hydraulic conductivity and horizontal and vertical anisotropy—were defined by using the 

MODFLOW HUF Package (Anderman and Hill, 2000). The 

MODFLOW HUF Package determines the units that apply 

to each model layer for each row and column and calculates 

model-layer horizontal and vertical conductances internally. 

Characteristics for the model grid are obtained by averaging 

and by using the assumption that the HGUs that occur within 

each model finite-difference cell are virtually horizontal. 

HGUs that pinch out and are discontinuous are defined by 

specifying the top altitude and thickness of HGUs, on the basis 

of defined rows and columns of the finite-difference grid. 

Hydraulic properties are assigned to the HGUs, rather than to 

the model layers, by using parameters (Harbaugh and others, 

2000, p. 12). 

Areal distributions of horizontal hydraulic conductivities 

for the simulated HGUs in the local-scale model are shown in 

figures 16 and 17. The simulated horizontal hydraulic conductivities include a base value that varies by HGU (zone 1 

in figures 16 and 17) and additional zones and values that are 

the same for multiple HGUs (figs. 16 and 17). The initial base 

horizontal hydraulic conductivity for each simulated HGU 

(HK1–HK12 corresponding to HGU1–HGU12) is shown in 

table 9 at end of report. The initial base horizontal hydraulic 

conductivities were based on reported horizontal hydraulic 

conductivities for the Edwards aquifer (table 3) and the relative permeabilities by Maclay (1995; fig. 11, p. 26) for the 

eight hydrogeologic units of the Edwards aquifer (I–VIII on 

fig. 10). The highest permeabilities in Maclay (1995; fig. 11, 

p. 26) are for the cyclic and marine members and the leached 

and collapsed members of the Edwards Group and for the 

Kirschberg evaporite member of the Edwards Group. These 

high permeabilities are consistent with the results of geophysical logging conducted by the USGS in 2008 (Gregory 

Stanton, U.S. Geological Survey, written commun., 2008) 

in the selected PSW and nearby monitoring wells, which 

indicated that most of the flow and the greatest transmissivities occurred in the leached and collapsed members of the 

Edwards Group and the Kirschberg evaporite member of the 

Edwards Group. The base horizontal hydraulic conductivities were adjusted during model calibration for the local-scale 

model to match the measured water-level altitudes and spring 

discharges during 2001 and measured tritium concentrations to 

simulated values.

In addition to the base horizontal hydraulic conductivity for each of the 12 simulated HGUs, with the exception of 

HGU1 and HGU12 there are zones of horizontal hydraulic 

conductivity with assigned values that differ from the base 

value for each HGU (figs. 16 and 17). The appropriate base 

horizontal hydraulic conductivity value is used for the full 

extent of HGU1 (HK1) and HGU12 (HK12). Horizontal 

hydraulic conductivity zones, in addition to the base horizontal hydraulic conductivity zone (zone 1), include (1) zones of 

high horizontal hydraulic conductivity through the center of 

the confined part of the aquifer and near the northern boundary of the freshwater/saline-water transition zone (hereinafter, the “high-K confined zones”) (fig. 16; zones 13–17), (2) 

zones of comparatively high horizontal hydraulic conductivity in the recharge zone underlying streambeds (hereinafter, 
Simulation of Groundwater Flow 37

the “high-K streambed zones”) (fig. 16; zones 30–33), and 

(3) zones of differing horizontal hydraulic conductivity near 

the boundary between the recharge zone and the confined part 

of the Edwards aquifer (hereinafter, the “K transition zones”) 

(fig. 16; zones 18–23) (fig. 17; zones 24–29). The high-K 

confined zones simulated in the local-scale model are derived 

from zones of high horizontal hydraulic conductivity used in 

the diffuse-flow rediscretized regional Edwards aquifer model 

(Lindgren and others, 2011), with minor modifications. The 

high-K confined zones (fig. 16; zones 13–17) are simulated 

for all of the HGUs, except for the two conduit HGUs (HGU5 

and HGU9) and HGU1 and HGU12 (table 9) and extend 

through much of the aquifer thickness. The high-K streambed 

zones are similarly derived from zones of high horizontal 

hydraulic conductivity underlying streambeds used in the 

conduit-flow and diffuse-flow rediscretized regional Edwards 

aquifer models (Lindgren and others, 2011) (zones are the 

same in both regional models), with minor modifications. The 

high-K streambed zones (fig. 16; zones 30–33) are simulated 

for the same HGUs as are the high-K confined zones and also 

Figure 17. Distribution of calibrated horizontal hydraulic conductivity in hydrogeologic units 5 and 9 in the local-scale model, San 

Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

!25

!24

!27

!26

!28

!29

(1

(1

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop)

 boundary (modified from Puente, 1978)

Freshwater/saline-water interface (1,000

 milligrams per liter dissolved solids 

 concentration) (A.L. Schultz, consultant,

 written commun., 2000)

Spring

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area—Horizontal hydraulic conductivity

 (HK) zone number and calibrated HK value, in meters per

 day (table 9)

 Base HK, varies by hydrogeologic unit (table 9)

 HK24 = 515

 HK25 = 4.39

 HK26 = 688

 HK27 = 37.8

 HK28 = 923

 HK29 = 1.52 

 Inactive local-scale model area

EXPLANATION

(1

!

!

!

!

!

!

24

25

26

27

28

29
38 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

are simulated for HGU12 (table 9). The simulated horizontal 

hydraulic conductivities for the high-K confined zones and the 

high-K streambed zones were varied during model calibration 

to match the measured water-level altitudes and spring discharges during 2001 and the measured tritium concentrations 

to simulated values.

The K transition zones have one set of values for all the 

HGUs, except the two conduit HGUs (HGU5 and HGU9) 

and HGU1 and HGU12 (fig. 16). A different set of values 

is used for the conduit HGUs (HGU5 and HGU9) (fig. 17). 

However, the extent of each zone is the same for all the HGUs 

for which they are used (figs. 16–17). The K transition zones 

(figs. 16–17; zones 18–29) have initial horizontal hydraulic 

conductivities that are equal to or less than the base horizontal hydraulic conductivities of the HGUs for which they are 

used and tend to retard flow and maintain higher simulated 

water-level altitudes near the boundary between the recharge 

zone and the confined part of the Edwards aquifer (table 9). 

K transition zones 27 and 28 were assigned initial horizontal 

hydraulic conductivities (parameters HK27 and HK28) that 

were an order of magnitude higher than the initial horizontal 

hydraulic conductivities of the other K transition zones (but 

still much lower than the base horizontal hydraulic conductivities for HGU5 and HGU9). K transition zones 27 and 28 

thereby potentially serve as areas of preferential, fast flow 

paths near the boundary between the recharge zone and the 

confined part of the Edwards aquifer. The simulated horizontal 

hydraulic conductivities for the K transition zones were varied 

during model calibration to match the measured water-level 

altitudes and spring discharges during 2001 and measured 

tritium concentrations to simulated values.

Six zones of horizontal anisotropy are simulated in the 

local-scale model (fig. 18, table 9). The confined part of the 

Edwards aquifer composes one of the horizontal anisotropy 

zones (zone 1), and the remaining five zones are delineated 

in the recharge zone of the aquifer. Maclay and Land (1988) 

hypothesized that large-displacement faults segment the 

aquifer and divert flow entering the recharge zone on relay 

ramps (transfer zone accommodating deformation between 

normal fault segments with similar dip directions [Peacock 

and Sanderson, 1994]) to the west before flow is redirected 

toward the east. Clark and Journey (2006) indicated that relay 

ramps and associated faulting in and near the recharge zone 

in Medina County appear to channel groundwater flow along 

flow paths that move water toward the southwest, rather than 

directly down the formational dip from the recharge zone 

into the confined zone of the aquifer. Similar relay ramps and 

associated faulting likely are present in the recharge zone in 

Bexar County, but the fault displacements in the recharge zone 

in Bexar County are appreciably smaller compared to those 

in Medina County. Because of the departure from downdip 

flow demonstrated by Clark and Journey (2006), an initial 

value of 0.1 was specified for horizontal anisotropy for zone 

2 in the recharge zone in Medina County in the western part 

of the model area (fig. 18, table 9). An initial value of 1.0 was 

specified for horizontal anisotropy for the other five zones, the 

same as was used in the rediscretized regional Edwards aquifer models (Lindgren and others, 2011). Multiple horizontal 

anisotropy zones were specified in the recharge zone to allow 

for variations in horizontal anisotropy between the western 

and eastern parts of the recharge zone and between selected 

high-K streambed zones to potentially better match measured 

water-level altitudes. The simulated horizontal anisotropy 

values were varied during model calibration to match the measured water-level altitudes and spring discharges during 2001 

and measured tritium concentrations to simulated values.

Uniform vertical anisotropy parameters were applied 

to each of the 12 simulated HGUs (table 9). An initial value 

of 10 was specified for the more permeable HGUs (initial 

horizontal hydraulic conductivities greater than or equal to 

91 m/d), while an initial value of 0.1 was specified for the less 

permeable HGUs (initial horizontal hydraulic conductivities 

less than or equal to 3.0 m/d) (table 9). Freeze and Cherry 

(1979) indicated that it is not uncommon for layered heterogeneity to lead to regional vertical anisotropy values on the 

order of 100:1 or larger. However, Snow (1969) showed that 

fractured rocks may behave anisotropically because of the 

directional variations in joint aperture and spacing, and, in this 

case, it is quite common for vertical hydraulic conductivity to 

be greater than horizontal hydraulic conductivity. Fractures 

are common throughout the entire thickness of the Edwards 

aquifer and commonly cross several strata (Maclay and Land, 

1988). These fractures are believed to hydraulically interconnect the permeable strata (Maclay and Land, 1988). Abundant 

fractures adjacent to faults are well connected both laterally 

and vertically by numerous intersecting and crosscutting 

fractures (Hovorka and others, 1998). In the karstic, highly 

faulted Edwards aquifer, fractures, faults, and karst features 

might contribute to vertical hydraulic conductivity being 

greater than horizontal hydraulic conductivity. The simulated 

vertical anisotropy values were varied during model calibration to match the measured water-level altitudes and spring 

discharges during 2001 and measured tritium concentrations to 

simulated values.

Particle-Tracking Simulations

Particle tracking was used to compute flow paths and 

advective traveltimes throughout the model area and to 

delineate the ACR and zones of contribution (ZOCs) for the 

selected PSW and the two monitoring well nests. The ACR 

to a discharging well is defined as the area at the water table 

where recharging water that enters the groundwater-flow 

system will eventually be removed by the well. The ZOC is 

defined as the specific volume of aquifer material bounded 

by outermost flow paths that will recharge a discharging well 

(Focazio and others, 2002). Steady-state conditions were 

assumed and the volume of water associated with individual 

particles of water entering the well were estimated on the 

basis of the simulated distribution of recharge. The recharge 

volumes were combined with estimated input concentrations 

of the age-tracer tritium on the basis of the simulated particle 
Simulation of Groundwater Flow 39

traveltimes to calculate flux-weighted concentrations of the 

tracer reaching the well. The resulting calculated concentrations were compared with measured concentrations to evaluate 

the adequacy of the model to simulate traveltimes and flow 

paths for potential contaminants. 

Particle tracking was performed by using MODPATH, 

which uses cellular volumetric fluxes from a groundwaterflow model and effective porosity to calculate linear velocity 

(Pollock, 1994). The x, y, and z components of linear velocity 

are used to generate a velocity field by using simple linear 

interpolation of the components between adjacent cell faces 

of the finite-difference cells. For steady-state simulations, an 

analytical expression for the flow path in each cell is calculated by direct integration of the velocity components. The 

traveltime calculated by this method represents an average 

traveltime for the advection of a “particle” of water or a 

conservative solute. Dispersion, diffusion, adsorption, retardation, degradation, or any other transport process affecting the 

concentrations of contaminant constituents is not included 

in the MODPATH simulation for determining traveltimes of 

water. The simulated ages of water particles at a well are computed by tracing water particles either backward from the well 

toward the ACR or forward from the ACR to the open-interval 

of the well.

Figure 18. Distribution of calibrated horizontal anisotropy in the local-scale model, San Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

!

! !

!

!

! !

! !

!

!

3 2

4

6

6

6 6

6

6

5

1

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary

 (modified from Puente, 1978)

Freshwater/saline-water interface (1,000

 milligrams per liter dissolved solids

 concentration) (A.L. Schultz, consultant, written

 commun., 2000)

Spring

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area—Horizontal anisotropy (HANI)

 zone number and calibrated HANI value (table 9)

 HANI1 = 1.0

 HANI2 = 0.9

 HANI3 = 0.5

 HANI4 = 1.0

 HANI5 = 0.2

 HANI6 = 1.0 

 Inactive local-scale model area

EXPLANATION

!

!

!

!

!

!

1

3

4

5

6

2
40 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Along with output from the groundwater-flow model, 

MODPATH simulations require effective porosity values to 

calculate groundwater-flow velocities. Initial effective porosity 

values in the local-scale model were based on values reported 

in Hovorka and others (1996), Kuniansky and others (2001), 

and Crandall and others (2009). Uniform effective porosity 

values ranging from 0.0001 to 0.01 were specified for each 

of the 12 HGUs (table 10 at end of report). An initial value 

of 0.01 was specified for the HGUs with comparatively high 

hydraulic conductivities (HGU3, HGU4, HGU7, HGU8, and 

HGU10), other than the two conduit HGUs. An initial value 

of 0.001 was specified for the HGUs with comparatively low 

hydraulic conductivities (HGU1, HGU2, HGU6, HGU11, and 

HGU12). The lowest initial value, 0.0001, was assigned to the 

two conduit HGUs (HGU5 and HGU9). The initial value for 

the HGUs with comparatively high hydraulic conductivities is 

similar to the values reported by Kuniansky and others (2001) 

that were needed for the karstic Edwards aquifer system in 

Texas to match estimated traveltimes derived from geochemical mixing models. The initial value for the two conduit HGUs 

is similar to the value used by Crandall and others (2009) to 

represent karstic model layers containing preferential flow 

path or conduit features. The initial effective porosity values 

were varied during model calibration by using the measured 

age-tracer (tritium) concentrations at the monitoring wells and 

the selected PSW as observations in the nonlinear estimation 

by using PEST. 

In a steady-state model, changes to input porosity values 

do not change the area contributing recharge to a given well. 

Changes to input porosity values, however, will change 

computed traveltimes from recharge areas to discharge areas 

(PSWs) in direct proportion to changes of effective porosity 

because there is an inverse linear relation between groundwater flow velocity and effective porosity and a direct linear relation between traveltime and effective porosity (Heath, 1983, p. 

25). For example, a 1-percent decrease in porosity will result 

in a 1-percent increase in velocity and a 1-percent decrease in 

particle traveltime. 

To calculate concentrations of the age-tracer tritium at the 

selected PSW and monitoring wells for parameter estimation, 

particle tracking was used to obtain a distribution of particle 

ages that were then associated with a local tritium input function (biannual historical concentrations of tritium in the atmosphere). Backward tracking was used in MODPATH to obtain 

the age distributions. MODPATH particle-tracking simulations 

were conducted for the selected PSW for “normal” pumping 

conditions (selected PSW and nearby PSWs in the well field 

pumping), five monitoring wells (Timberhill and Zarzamora), 

and four PSWs. For the monitoring wells, 250 particles for 

each model layer were evenly distributed in a vertical line 

over the open interval of each monitoring well. Particles were 

tracked backward toward the ACR. For the PSWs, 1,000 

particles, vertically distributed on each cell face over the open 

interval of the well based on the simulated flows to the well, 

were tracked using the backward particle tracking mode. Each 

particle is associated with an end point and total traveltime, a 

flow pathline, and traveltime along the flow pathline. In addition, the ACR and the ZOC are mapped from the resultant collection of flow pathlines for the selected PSW and monitoring 

wells. Comparisons between mean simulated particle ages and 

interpreted (apparent) groundwater ages are discussed later 

in the report in the section “Simulated Zones of Contribution, 

Areas Contributing Recharge, and Water Particle Ages.”

Model Calibration

The local-scale model was calibrated for steady-state 

conditions. Average stresses (recharge and pumpage) during 

2001, a representative year for the recent time period (2000–

10), were used to simulate steady-state conditions. The overall 

goodness of fit of the local-scale model to the observation data 

can be evaluated by using summary statistics and graphical 

analyses. The goodness of fit between simulated and measured 

water-level altitudes, simulated and measured springflows, and 

simulated and measured tritium concentrations was quantified 

by using the mean absolute difference, mean algebraic difference, and root mean square (RMS) error. The mean absolute 

difference is the sum of the absolute values of the differences 

divided by the number of observations. The mean algebraic 

difference is the algebraic sum of the differences divided by 

the number of observations. The RMS error is derived from 

the differences between the simulated and measured hydraulic 

heads, as given in Lindgren and others (2004, p. 63, equation 

2). If the ratio of the RMS error to the total head change in the 

modeled area is small, then the error in the head calculations 

is a small part of the overall model response (Anderson and 

Woessner, 1992). 

Groundwater-flow-model and particle-tracking calibration was evaluated by using 84 groundwater-level altitudes 

and 13 tritium concentrations. Overall, 70 parameters were 

used to define the simulation, including those for horizontal 

hydraulic conductivity, horizontal and vertical anisotropy, 

drain hydraulic conductance, fault hydraulic conductance, 

and effective porosity. The local-scale model was calibrated 

by using systematic manual calibration and by using PEST 

(Doherty, 2005), a universal code for sensitivity, calibration (using parameter estimation), and predictive analysis in 

concert with MODFLOW-2000 (Harbaugh and others, 2000) 

and MODPATH (Pollock, 1994). Estimated parameter values 

minimize the sum of squared differences (residuals) between 

observed and simulated values (objective function) to result in 

the best match between measured and simulated water-level 

altitudes, drain (spring) discharges, and age-tracer (tritium) 

concentrations. A uniform weight of 1.0 was applied to the 

water-level observations because the measurement error and 

reliability of all of the measurements was assumed to be 

similar. A uniform weight of 10 was applied to the tritium 

concentration observations when included in conjunction 

with water-level observations in PEST simulations in order to 

make the weighted concentration residuals similar in magnitude to the water-level residuals. The PEST simulations were 

hampered by insensitivity of some parameters (lack of critical 
Simulation of Groundwater Flow 41

observations) and significant correlation between parameters. 

In addition, the PEST simulations including effective porosities as parameters to be estimated resulted in higher residuals 

(differences between measured and simulated values) for both 

hydraulic heads and tritium concentrations than did PEST 

simulations without effective porosities as parameters to be 

estimated. Therefore, hydraulic properties and drain and fault 

hydraulic conductances were estimated first by using systematic manual calibration and PEST simulations, and effective 

porosities were then estimated by using PEST simulations 

including only effective porosities as parameters to be estimated (all other parameters held constant). 

The mean absolute residual for the water-level measurements is 4.2 m and for tritium concentrations is 0.11 tritium 

units (TU). There was a mean algebraic difference of 1.9 m 

for water-level altitudes, with simulated water-level altitudes 

being lower than measured water-level altitudes. There was 

less than a 0.0001 percent discrepancy in the overall water 

budget. Measured and simulated age-tracer (tritium) concentrations matched well enough to indicate a reasonably 

good representation of the porosity and hydraulic parameters. 

Water-level altitudes, spring discharges, and tritium concentrations were used in the calibration of the local-scale model. 

Measured and simulated water-level altitudes, spring discharges, and tritium concentrations are discussed in detail later 

in the report in the Water-Level Altitudes, Spring Discharge, 

and Age-Tracer Concentrations sections, respectively.

Parameter Sensitivity

As described in Haugh (2006, p. 50), “Composite scaled 

sensitivities [unitless values scaled from 0 to 100] can be 

used to compare the importance of different parameters to 

the calculation of model-simulated water levels and flows 

(Hill, 1998). Parameters with greater composite sensitivities 

have greater importance and greater influence on the model 

solution.” The parameters (1) vertical anisotropy for HGU2, 

HGU5, HGU9, and HGU11, (2) horizontal anisotropy for 

HANI zone 5, and (3) horizontal hydraulic conductivity for 

HK zones 15 and 17, with composite sensitivities greater 

than 70, are the most sensitive parameters in the simulation 

compared to those with composite sensitivities less than 70 

(fig. 19). The composite sensitivities cited here and shown 

in figure 19 apply to a mixture of observations and parameters with differing units of measure; therefore, there is no 

particular unit of measure for the PEST-computed composite 

sensitivities. The units of the composite sensitivities computed 

by PEST are specific to the observations and parameters for 

which sensitivities are calculated (Doherty, 2005). Other sensitive parameters are (1) base horizontal hydraulic conductivity 

for HGU6, HGU8, HGU9, and HGU10, (2) horizontal hydraulic conductivity for HK zones 21, 23, and 33, and (3) vertical 

anisotropy for HGU10 at between 50 and 70. Parameters with 

composite sensitivities equal to or less than 10 are effective 

porosities for all HGUs other than HGU9. The composite 

sensitivities for the remaining parameters are between 10 

and 50. The composite sensitivities for the effective porosity 

parameters are small for the PEST simulations with both water 

level and tritium concentration observations because effective porosity has no effect on simulated water-level altitudes. 

However, simulated tritium concentrations are sensitive to 

effective porosity values. The number and location of observations used in the model calibration affect parameter sensitivities and directly control how well parameters can be estimated 

by using parameter estimation (Doherty, 2005).

Parameter Adjustments

The aquifer hydraulic properties specified in the localscale model—horizontal hydraulic conductivity and horizontal 

and vertical anisotropy—were varied during model calibration 

by using systematic manual calibration and PEST simulations 

to minimize the difference between model-computed and measured water-level altitudes, spring discharges, and age-tracer 

(tritium) concentrations. The initial and calibrated values for 

the model parameters are shown in tables 9 and 10.

The calibrated base horizontal hydraulic conductivity 

values were generally similar to the corresponding initial values (table 9). The largest changes were (1) an increase in the 

horizontal hydraulic conductivities for the cyclic and marine 

members (HGU3, HK3), the leached and collapsed members 

(HGU4, HK4), and the Kirschberg evaporite member (HGU8, 

HK8) of the Edwards Group corresponding to the Edwards 

aquifer and (2) a decrease in the horizontal hydraulic conductivities for the lower high-K (conduit) unit (HGU9, HK9) and 

the dolomitic member of the Edwards Group (HGU10, HK10). 

The calibrated horizontal hydraulic conductivity values for 

the high-K confined zones (fig. 16; zones 13–17) and high-K 

streambed zones (fig. 16; zones 30–33) were generally similar 

to the corresponding initial values, except for high-K streambed zone 31, which increased from 152 to 322 m/d (HK31 in 

table 9). For the K transition zones, the largest changes were 

an increase in the horizontal hydraulic conductivities for the 

calibrated horizontal hydraulic conductivity values associated with zones 24, 26, and 28 (HK24, HK26, and HK28 

in table 9), which are superimposed on the base hydraulic 

conductivities of HGUs 5 and 9 (fig. 17), the conduit HGUs 

in the local-scale model representing relatively fast flow paths 

attributable to karst features (fig. 15A, fig 15B). The calibrated 

values for these parameters, however, are still three orders of 

magnitude lower than the calibrated horizontal hydraulic conductivity values for the conduit HGUs. The calibrated horizontal hydraulic conductivity for parameter HK23 also increased 

appreciably compared to the initial value and is greater than 

the calibrated base horizontal hydraulic conductivities for 

HGU2, HGU6, HGU10, and HGU11 (table 9). The increases 

indicate that these zones might be areas of preferential, fast 

flow paths near the boundary between the recharge zone and 

the confined part of the Edwards aquifer. 

The calibrated values for horizontal and vertical anisotropy in many cases differed appreciably from the initial values 

(table 9). The calibrated values for HANI3 and HANI5 were 
42 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Figure 19. Composite sensitivity of the parameters used to calibrate the local-scale model, San Antonio region, Texas.

0 10 20 30 40 50 60 70 80 90 100

Composite sensitivity, no units

Vertical anisotropy for HGU9

Vertical anisotropy for HGU2

Horizontal hydraulic conductivity zone 17

Vertical anisotropy for HGU11

Vertical anisotropy for HGU5

Horizontal anisotropy zone 5

Horizontal hydraulic conductivity zone 15

Base horizontal hydraulic conductivity for HGU6

Vertical anisotropy for HGU10

Horizontal hydraulic conductivity zone 23

Base horizontal hydraulic conductivity for HGU8

Base horizontal hydraulic conductivity for HGU9

Horizontal hydraulic conductivity zone 21

Base horizontal hydraulic conductivity for HGU10

Horizontal hydraulic conductivity zone 33

Vertical anisotropy for HGU4

Base horizontal hydraulic conductivity for HGU1

Base horizontal hydraulic conductivity for HGU3

Horizontal hydraulic conductivity zone 19

Vertical anisotropy for HGU1

Horizontal hydraulic conductivity zone 26

Drain conductance for San Pedro Springs

Horizontal hydraulic conductivity zone 14

Horizontal hydraulic conductivity zone 20

Horizontal hydraulic conductivity zone 31

Base horizontal hydraulic conductivity for HGU12

Horizontal hydraulic conductivity zone 13

Horizontal anisotropy zone 6

Horizontal hydraulic conductivity zone 27

Horizontal anisotropy zone 3

Horizontal hydraulic conductivity zone 28

Horizontal hydraulic conductivity zone 16

Horizontal hydraulic conductivity zone 29

Horizontal hydraulic conductivity zone 32

Base horizontal hydraulic conductivity for HGU7

Base horizontal hydraulic conductivity for HGU2

Horizontal anisotropy zone 2

Vertical anisotropy for HGU6

Base horizontal hydraulic conductivity for HGU11

Vertical anisotropy for HGU3

Vertical anisotropy for HGU8

Horizontal hydraulic conductivity zone 22

Horizontal hydraulic conductivity zone 18

Horizontal hydraulic conductivity zone 25

Horizontal anisotropy zone 1

Base horizontal hydraulic conductivity for HGU5

Horizontal hydraulic conductivity zone 24

Drain conductance for San Antonio Springs

Base horizontal hydraulic conductivity for HGU4

Vertical anisotropy for HGU7

Horizontal anisotropy zone 4

Horizontal hydraulic conductivity zone 30

Effective porosity for HGU9

Vertical anisotropy for HGU12

Effective porosity for HGU5

Effective porosity for HGU1

Effective porosity for HGU4

Effective porosity for HGU10

Effective porosity for HGU6

Effective porosity for HGU8

Effective porosity for HGU3

Effective porosity for HGU11

Effective porosity for HGU7

Effective porosity for HGU12

Effective porosity for HGU2
Simulation of Groundwater Flow 43

less than the initial values by factors of 2 and 5, respectively, 

while the calibrated value for HANI2, in the western part of 

the recharge zone (fig. 18), increased from 0.1 to 0.9. The 

calibrated values for 5 of the 12 vertical anisotropy parameters were similar to the initial values (table 9). The calibrated 

values for vertical anisotropy parameters VANI2, VANI6, 

VANI9, and VANI11 increased by a factor of 2 or more 

compared to the initial values, and for VANI4, VANI7, and 

VANI10 decreased by a factor of 2 or more. The grainstone 

member (HGU7, VANI7) and dolomitic member (HGU10, 

VANI10) of the Edwards Group were changed from an initial 

vertical anisotropy value of 10 to calibrated values of less than 

1.0. Conversely, the basal nodular member (HGU11, VANI11) 

of the Edwards Group was changed from an initial vertical 

anisotropy value of 0.1 to a calibrated value of 5.0 (table 9). 

The drain hydraulic conductances were adjusted during 

the steady-state calibration to match measured springflows 

to simulated springflows. As a result of the steady-state 

calibration, the drain hydraulic conductance for San Antonio 

Springs (DR1) was decreased by about 26 percent, and the 

drain hydraulic conductance for San Pedro Springs (DR2) was 

increased by about 55 percent (table 10).

The hydraulic conductances for the simulated faults were 

adjusted uniformly by vertical displacement category during 

model calibration to match measured water-level altitudes to 

simulated water-level altitudes. The final calibrated hydraulicconductance values ranged from 0.01 to 0.2 per day (table 10) 

for fault displacements ranging from 0 to more than 100 percent of the total aquifer thickness. The hydraulic conductances 

for HFB1, HFB2, and HFB3 were reduced by four to seven 

orders of magnitude compared to the initial values (table 10), 

which were based on the values from the rediscretized 

regional Edwards aquifer models (Lindgren and others, 2011). 

The use of the HUF Package in the local-scale model and 

the resulting juxtaposition of HGUs with differing horizontal 

hydraulic conductivity values in the same model layer might 

impede flow where HGUs with appreciably different horizontal hydraulic conductivities are juxtaposed. In contrast, in the 

rediscretized regional Edwards aquifer models (Lindgren and 

others, 2011), HGUs with differing horizontal hydraulic conductivity values were not juxtaposed, and the simulated faults 

were the primary barriers to flow. 

Effective porosity values were varied during model calibration by using PEST simulations to minimize the difference 

between model-computed and measured age-tracer (tritium) 

concentrations. The low calibrated effective porosities of about 

10-4 (dimensionless) for the conduit HGUs (HGU5, POR5 and 

HGU9, POR9) (table 10) indicate that the flow occurs in only 

a small percentage of the total volume of the aquifer, which is 

consistent with the concept of flow through conduits. The calibrated effective porosities for the cyclic and marine members 

(HGU3, POR3), the leached and collapsed members (HGU4, 

POR4), the grainstone member (HGU7, POR7), and the 

Kirschberg evaporite member (HGU8, POR8) of the Edwards 

Group corresponding to the Edwards aquifer were approximately an order of magnitude lower than the initial values, 

indicating a need to generally increase the particle traveltimes 

in order to better match the measured tritium concentrations. 

The calibrated effective porosities increased by approximately 

an order of magnitude compared to the initial values for the 

Georgetown Formation (HGU2, POR2) and the basal nodular 

member (HGU11, POR11) of the Edwards Group (table 10). 

Water-Level Altitudes

The local-scale model was calibrated by using 72 waterlevel measurements representing mean measured water-level 

altitudes for 2001 and 12 water-level measurements representing mean measured water-level altitudes during 2007–10 

from wells in the vicinity of the selected PSW (table 6). The 

84 wells with water-level measurements are generally open 

to multiple HGUs. Twenty-eight water-level measurements 

were from wells open to two or fewer HGUs (table 6). For 

18 of the wells, the open interval was unknown; these wells 

were assumed to be open to the full saturated thickness of 

the aquifer. There were 27 water-level measurements from 

wells open to the HGUs above the regional dense member 

of the Edwards Group (HGU6), 18 water-level measurements from wells open to the HGUs below the regional dense 

member of the Edwards Group, and 2 water-level measurements from wells open to only the regional dense member of 

the Edwards Group (HGU6) (table 6). The remainder of the 

water-level measurements (37) were from wells open to HGUs 

above and to HGUs below the regional dense member of the 

Edwards Group (table 6). The calibrated steady-state simulation generally reproduces the spatial distribution of measured 

water-level altitudes (fig. 20). Simulated water-level altitudes 

were within 9.0 m of measured water-level altitudes at 74 of 

the 84 wells used as targets for the local-scale model for the 

calibrated steady-state simulation (fig. 20, table 6). The difference between measured and simulated water-level altitudes 

was less than 6.0 m at 64 of the 84 wells and less than 3.0 m 

at 42 of the 84 wells. The overall mean absolute difference 

between simulated and measured water-level altitudes is 4.2 m 

(table 6). The largest differences between measured and simulated water-level altitudes (residuals) occur in the western part 

of the model area and in and near the recharge zone (fig. 20). 

Many of the residuals in the eastern two-thirds of the confined 

zone of the aquifer are less than 1.5 m. The overall RMS error 

is 6.0 m, which represents about 7.5 percent of the total difference in water level-altitudes (head difference) across the 

model area. The simulated water-level altitudes for wells open 

to HGU6 (regional dense member of the Edwards Group) 

and above matched the measured water-level altitudes best 

(mean absolute difference of 3.4 m), while the poorest match 

was for wells open to the HGUs below HGU6 (mean absolute 

difference of 5.1 m). The mean absolute difference for wells 

open to HGUs both above and below HGU6 was intermediate in value, 4.5 m. The mean algebraic difference between 

simulated and measured water-level altitudes, computed as 

the algebraic sum of the differences divided by the number of 

wells, is 1.9 m, indicating that simulated water-level altitudes 
44 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Figure 20. Simulated potentiometric surface and water-level residuals for the local-scale model, San Antonio region, Texas.

C A T C H M E N T A R E A C A T C H M E N T A R E A

Hondo

Castroville San

Antonio

E

E

San Pedro

Springs

San Antonio 

Springs

Hondo Creek

Medina

River

Verde

Medina

Lake

Creek

Salado

Creek

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek

Black Creek

San Francisco Perez Creek

San Geronim o Creek

Helotes Creek

San Antonio

River

!

!

!

!

!

!

!

!

!

! !

!!

!

!

!

!!

!

!

! ! !

!

!

!

!

!

!

!

! !

!

! !

!

!

!

! !

! !

!

!

!

!

!

!

!

! !

!

!

!

!

!

! !

!

!

!

! !

! !

!

! !

!

!

!

!

!

!

! !

!!

!

!

BEXAR COUNTY

MEDINA COUNTY

BANDERA COUNTY

MEDINA COUNTY

0 2.5 5 7.5 MILES 10

0 2.5 5 7.5 KILOMETERS 10

98°30'

98°45' 99°00'

99°15'

29°30'

29°15'

Base from U.S. Geological Survey digital data,

Texas Centric Mapping System-Albers equal area projection

North American Datum of 1983 

E

Freshwater/saline-water interface (1,000 milligrams

 per liter dissolved solids concentration)

 (A.L. Schultz, consultant, written commun., 2000)

Spring

Simulated water-level residual (measured water

 level minus simulated water level), in meters

 -23.0 to -9.1

 -9.0 to -6.1

 -6.0 to -3.1

 -3.0 to 0.0

 0.0 to 3.0

 3.1 to 6.0

 6.1 to 9.0

 9.1 to 18.8

EXPLANATION

Local-scale study area—Includes active local-scale model area

 and a portion of inactive local-scale model area (fig. 4)

 Active local-scale model area—Simulated water-level altitude,

 in meters above North American Vertical Datum of 1988

 203.8 to 207.5

 207.6 to 209.7

 209.8 to 210.2

 210.3 to 212.6

 212.7 to 215.6

 215.7 to 233.2

 233.3 to 283.2

 283.3 to 340.0

 Inactive local-scale model area

Urban area boundary

Local-scale study area boundary

Edwards aquifer recharge zone (outcrop) boundary (modified

 from Puente, 1978)

!

!

!

!

!

!

!

!
Simulation of Groundwater Flow 45

are on an overall basis slightly lower than measured waterlevel altitudes. The graph of simulated relative to measured 

water-level altitudes indicates that simulated water-level 

altitudes are neither consistently greater than, nor consistently 

less than, measured water-level altitudes in the steady-state 

simulation results for the local-scale model (fig. 21). However, as noted earlier in this paragraph, the largest water-level 

residuals (absolute difference) tend to occur in the western 

part of the model area and in and near the recharge zone.

Vertical hydraulic gradients were also analyzed on the 

basis of the measured and simulated water-level altitudes for 

the Timberhill and Zarzamora monitoring well nests. Vertical hydraulic gradients were calculated as the differences 

between the mean daily water-level altitudes during 2007–10 

for the wells screened at varying depths in each well nest. The 

calculated vertical hydraulic gradient for the two Timberhill 

wells, one screened at an intermediate depth (Timberhill_IED) 

and the other screened at a deep depth (Timberhill_DED), 

was 0.2 m, with an upward gradient (table 2). The Zarzamora 

well nest includes four wells screened in the overburden 

(Zarzamora_OVB) and at shallow (Zarzamora_SED), intermediate (Zarzamora_IED), and deep (Zarzamora_DED) depths in 

the Edwards aquifer. The calculated vertical hydraulic gradients between the differing well depths varied from a minimum 

of 0.2 m upward to a maximum of 6.4 m downward (table 2). 

In contrast, the simulated vertical hydraulic gradients, based 

on the simulated water-level altitudes, were all less than 0.003 

m. Probable reasons for the discrepancies between the measured and simulated vertical hydraulic gradients are related to 

model limitations discussed later in the report in the “Model 

Uncertainties and Limitations” section, including the simulation of steady-state, rather than transient, conditions and the 

inherent approximation of the complex hydrogeology at the 

well nest sites. Figure 5 indicates that for most time periods 

the differences in water-level altitudes between the wells in 

a well nest are minimal, with the exception of the Zarzamora 

site overburden well. The larger differences are generally 

transient in nature, likely in response to recharge events or 

pumping changes. Figure 5 also indicates that the direction 

of the vertical gradients between wells varies temporally, 

Figure 21. Simulated relative to measured water-level altitudes for the local-scale model, steady-state simulation, San Antonio region, 

Texas.

180 200 220 240 260 280

Measured water-level altitude, in meters above North American Vertical Datum of 1988

180

200

220

240

260

280

Simulated water-level altitude, in meters above North American Vertical Datum of 1988
46 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

further complicating an assessment of an appropriate representation of the vertical hydraulic gradients for steady-state 

conditions. 

Spring Discharge

The steady-state simulation calibration results for the 

local-scale model include a comparison of simulated springflows with median springflows for 2001. The simulated 

springflow for San Antonio Springs was 7.7 percent greater 

and for San Pedro Springs was 4.2 percent less than the 

median measured springflow (table 6). The RMS error for the 

two springs is 0.05 m3/s, which represents about 6.9 percent of 

the range in the two measured springflows. 

Age-Tracer Concentrations

Simulated age-tracer (tritium) concentrations were generally in good agreement with measured values in wells in the 

model area. Simulated tritium concentrations were within 

0.35 TU of measured tritium concentrations for the 13 tritium 

observations (hereinafter, the “local-scale study tritium observations”) from 10 wells (hereinafter, the “local-scale study 

wells”) used as observations in PEST simulations to calibrate 

the local-scale model (table 11 at end of report). Simulated 

tritium concentrations were within 3.52 TU of measured 

tritium concentrations for an additional 42 tritium observations 

(hereinafter, the “NAWQA tritium observations”) from 29 

wells (hereinafter, the “NAWQA wells”) not used as observations in the PEST simulations (table 11). These measured 

tritium concentrations were not used to calibrate the localscale model because the sample dates in the 1990s and the 

appreciably longer simulated mean particle traveltimes to the 

wells indicate that the hydrologic conditions simulated in the 

local-scale model might be less representative of the hydrologic conditions associated with the NAWQA tritium observations than those associated with the local-scale study tritium 

observations. However, the measurements are useful as an 

indicator of the capability of the local-scale model to simulate 

tritium concentrations in water at wells within the model area, 

in addition to the relatively few and closely spaced local-scale 

study wells. The mean absolute difference between simulated 

and measured tritium concentrations for the NAWQA wells 

is 0.64 TU, and the mean algebraic difference is 0.31 TU 

(table 11). The RMS error is 1.01 TU, which represents about 

27 percent of the range in the measured tritium concentrations for the 42 NAWQA tritium observations. The appreciably higher mean absolute difference for the NAWQA tritium 

observations (0.64 TU) compared to the local-scale study 

tritium observations (0.11 TU) likely reflects the multiple 

sampling dates and resulting greater variability in hydrologic 

conditions for the NAWQA tritium observations. The graph of 

simulated relative to measured tritium concentrations for the 

local-scale study and NAWQA tritium observations indicates 

little bias in the steady-state simulation results, with the data 

points relatively evenly distributed on both sides of the one-toone line (fig. 22). 

The mean absolute difference between simulated and 

measured tritium concentrations for the local-scale study 

wells is 0.11 TU, and the mean algebraic difference is -0.04 

TU (table 11). The mean algebraic difference of -0.04 indicates that positive differences are approximately balanced by 

negative differences and that there is minimal bias in the simulated concentrations, except for possibly a tendency to underestimate tritium concentrations at the higher measured tritium 

concentrations (fig. 23). The RMS error is 0.14 TU, which 

represents about 27 percent of the range in the measured tritium concentrations for the 13 observations. Simulated tritium 

concentrations were within 0.14 TU of measured concentrations for 11 of the 13 local-scale study tritium observations 

(table 11). The largest differences were for the shallow-depth 

observation for the selected PSW (0.35 TU) and the wellhead 

observation for PSW WZ5W (0.25 TU), 

with simulated concentrations that were less than the measured concentrations. The mean absolute differences between 

simulated and measured tritium concentrations, grouped by 

the sampling location (at the wellhead) or sampling depth 

(shallow, intermediate, or deep), are similar among values 

grouped as wellhead, intermediate, or deep observations 

(0.09, 0.06, and 0.11 TU, respectively). The mean absolute 

difference for the shallow grouping (0.23) is higher because 

there are only two observations, and one of the observations 

(WZ4S) had the highest absolute difference (0.35 TU) of the 

13 observations. 

Simulated tritium concentrations in the selected PSW 

during November 2007 were within 0.09 TU of the measured concentrations, with the exception of the shallow depth 

observation (WZ4S) (table 11). The simulated concentrations were higher than the measured concentrations for the 

wellhead, intermediate, and deep depth observations but were 

lower for the shallow depth observation. The vertical pattern 

in the measured tritium concentrations for the depth-dependent 

sampling in the selected PSW has the highest concentration 

for the shallow depth observation, the lowest concentration for 

the intermediate depth observation, and the middle concentration for the deep depth observation (fig. 15B, table 11). The 

simulated concentrations follow the pattern for the intermediate and deep observations but not for the shallow-depth 

observation. The vertical pattern in the measured tritium concentrations observed in the selected PSW is also seen in the 

concentrations for the Zarzamora well nest (fig. 15B, table 11). 

However, for the Zarzamora wells, simulated concentrations 

follow the pattern for the shallow and deep depth observations, but the simulated concentration for the intermediate 

depth observation is greater than the concentrations for the 

other two observations. The measured and simulated concentrations for the Timberhill wells indicate a lower concentration for the deep depth observation than for the intermediate 

depth observation. The meaning of the patterns in the vertical 

distribution of measured tritium concentrations observed in the 

selected PSW and in the Zarzamora and Timberhill well nests 
Simulation of Groundwater Flow 47

is not clear because the differences in measured concentrations 

between the well depth observations might be less than the 

uncertainty in the measurements. 

Poor matches between measured and simulated tritium 

concentrations might be a result of model limitations, such as 

inexact representations of karst features and their placement, 

the assumption of steady-state flow, and the inability of the 

Modpath computer code to account for diffusion and dispersion in the MODPATH simulations. In addition, uncertainty 

exists regarding exactly what depth interval or amount of flow 

to the well each of the tritium concentration observations represents. Poor matches between measured and simulated tritium 

concentrations for the selected PSW might also be attributable to the appreciably higher simulated pumping rate for the 

selected PSW compared to the pumping rate used for collecting depth-dependent samples, as discussed previously in the 

Data Collection and Analysis section. 

Model Results

Model output from the MODFLOW local-scale model 

includes simulated water-level altitudes, cell-by-cell flows and 

water budgets. MODPATH was used to estimate water-particle 

traveltimes and ACR for the selected PSW and monitoring 

wells.

Simulated Groundwater Flow

The simulated potentiometric surface (fig. 20) was generally representative of the measured potentiometric surface 

(fig. 11) in the local-scale model area. The major components of groundwater flow in the local-scale model area are 

(1) from the recharge zone southward into the confined zone 

and (2) from west to east in the confined zone toward the 

major springs (Comal and San Marcos Springs) east of the 

Figure 22. Simulated relative to measured tritium concentrations for the local-scale model, steady-state simulation, San Antonio 

region, Texas.

1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

Measured tritium concentration, in tritium units

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

Simulated tritium concentration, in tritium units

* NAWQA, U.S. Geological Survey National Water-Quality Assessment Program

Local-scale study tritium observation

NAWQA* tritium observation

EXPLANATION
48 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

local-scale model area. Water in the local-scale model flowed 

from the recharge zone toward the south and southeast into 

the confined zone. Water-level altitudes decreased from north 

to south, from north to southeast, and from west to east across 

the local-scale model area and were in generally good agreement with the observed flow directions.

Structures simulated in the local-scale model influencing groundwater flow that tend to restrict flow include largedisplacement faults. The influence of simulated faults on 

flow directions is most evident in northern Medina County. 

In this area, the direction of groundwater flow is affected 

primarily by large-displacement, parallel northeastwardstriking faults (fig. 12) that divert flow toward the southwest. The steep regional slope of the potentiometric surface 

is toward the southeast, but these faults, as local barriers to 

southeastward flow, divert the flow toward the southwest. 

The diversion of flow to the southwest can be seen in measured (fig. 11) and simulated (fig. 20) potentiometric surfaces. Water-level altitudes abruptly change across segments 

of the large-displacement faults in some areas, in particular 

in the western part of the local-scale study area in Medina 

County and in west-central Bexar County (fig. 12). Comparatively large simulated water-level changes across faults are 

indicated in these areas by the coincidence between breaks 

(changes in color) in the simulated zones of water-level altitudes in figure 20 and the traces of large-displacement faults in 

figure 12.

Simulated Water Budget

In addition to water-level altitudes, the water budget for 

the model is computed. A water budget in the context of the 

model is an accounting of inflow to, outflow from, and storage change in the aquifer. For steady-state conditions, inflow 

(sources) to the aquifer equal outflow (discharges) from the 

aquifer. The steady-state simulation water budget indicates 

that recharge occurring in the local-scale study area accounts 

for 31.8 percent of the sources of water to the Edwards aquifer 

in the local-scale model area and that inflow through the 

model boundaries contributes 68.2 percent (table 12 at end 

of report). Most of the flow into the local-scale model area 

through the model boundaries occurs through the western and 

southern boundaries, 58.2 and 39.6 percent, respectively. The 

net flow through the western boundary is into the local-scale 

model area (fig. 24) and constitutes 80.0 percent of the total 

flow (both into and out of the local-scale model area) through 

Figure 23. Simulated relative to measured tritium concentrations in the selected public-supply well and monitoring wells for the localscale model, steady-state simulation, San Antonio region, Texas.

1.5 1.7 1.9 2.1 2.3 2.5

Measured tritium concentration, in tritium units

1.5

1.7

1.9

2.1

2.3

2.5

Simulated tritium concentration, in tritium units

Selected public-supply well

 Wellhead (WZ4W)

 Shallow depth (WZ4S)

 Intermediate depth (WZ4I)

 Deep depth (WZ4D)

Monitoring wells and other public-supply wells

 Wellhead (WZ2W, WZ3W, WZ5W, WZ6W)

 Shallow depth (Zarzamora_SED)

 Intermediate depth (Timberhill_IED,

 Zarzamora_IED)

 Deep depth (Timberhill_DED,

 Zarzamora_DED)

EXPLANATION
Simulation of Groundwater Flow 49

the western boundary (table 8). All of the flow through the 

northern boundary is into the local-scale model area and 

represents flow from the Trinity aquifer into the Edwards 

aquifer (fig. 24, table 12). Flow through the northern boundary constitutes a comparatively small part (1.7 percent) of the 

total boundary inflow under steady-state conditions. A very 

small amount of flow into the local-scale model area also 

occurs through the eastern model boundary in the recharge 

zone. 

The largest discharges from the Edwards aquifer in 

the local-scale model area are boundary outflow (71.4 percent) 

and withdrawals by wells (24.9 percent) (table 12). Most of 

the flow out of the local-scale model area through the model 

boundaries occurs through the southern and eastern boundaries, 54.2 and 39.6 percent, respectively. The net flow through 

the southern boundary is out of the local-scale model area 

(fig. 24) and constitutes only 17.8 percent of the total flow 

(both into and out of the local-scale model area) through the 

southern boundary (table 8). In contrast, the net flow out of the 

eastern boundary (fig. 24, table 12) constitutes most (97.7 percent) of the total flow (both into and out of the local-scale 

model area) through the eastern boundary (table 8). A small 

amount of flow out of the local-scale model area also occurs 

through the western model boundary in the recharge zone. 

Springflow from San Antonio and San Pedro Springs contribute a small amount (3.7 percent) to the total discharge.

Simulated Zones of Contribution, Areas 

Contributing Recharge, and Water Particle Ages

The simulated ZOCs and ACR to the selected PSW, Zarzamora well nest, and Timberhill well nest are shown in figures 25, 26, and 27, respectively. The ZOCs for all three sites 

extend to the north, northeast, and northwest from each site in 

the confined zone of the aquifer into the recharge zone, where 

all recharge to the aquifer occurs. The areal extent of the surficial expression of the simulated ZOC is about 44,040 hectares 

for the selected PSW, about 29,320 hectares for the Zarzamora 

well nest, and about 18,540 hectares for the Timberhill well 

nest. The ACR for each site is restricted to the recharge zone. 

Although the simulated ACR for the selected PSW and nearby 

well nests in San Antonio likely do not represent the true areas 

contributing recharge, they are a useful tool for delineating 

approximate areas that may serve as sources of groundwater 

recharging the wells and potential sources of contaminants 

at the time of recharge. The simulated ACR in figures 25–27 

are represented as networks of model-grid cells, some of 

which are contiguous and others disconnected. The “patchy” 

Figure 24. Simulated water-budget components for the local-scale model, steady-state simulation, San Antonio region, Texas.

Units are cubic meters per year; numbers in parentheses are percentages of total sources or discharges; blue text indicates a source

of water; red text indicates a discharge of water.

FAULT

Approximate downdip limit of freshwater zone

of Edwards aquifer

Confining unit

Edwards aquifer

Net outflow through

eastern boundary:

2.85 x 108

 (41.0)

Net outflow through

southern boundary:

1.20 x 108

 (17.2)

Withdrawals: 2.54 x 108

 (36.4)

Springflow: 3.80 x 107

 (5.4)

Inflow through northern

boundary (from Trinity

aquifer): 1.18 x 107

 (1.7) 

Net inflow through

western boundary:

3.60 x 108

 (51.7)

Recharge from streams on

outcrop and infiltration of rainfall

in recharge zone: 3.25 x 108

 (46.6)

EXPLANATION

Direction of flow
Figure 25. Simulated areas contributing recharge, age of water particles derived from simulated particle traveltimes, and particle pathlines for the sSan Antonio region, Texas.

San Antonio

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek San Geronimo Creek

He

lo

tes

 

Creek

Medina Lake

Medina River

MEDINA COUNTY BANDERA COUNTY

MEDINA COUNTY

BEXAR COUNTY

29°39'29°36'29°33'29°30'29°27'

98°55' 98°50' 98°45' 98°40' 98°35'

Base from U.S. Geological Survey digital data,Texas Centric Mapping System-Albers equal area projectionNorth American Datum of 1983

C A T C H M E N T A R E A C A T C H M E N T A R E A

Active local-scale model area Areas contributing recharge (discontinuous network of model-grid cells), by particle traveltimes, in years 0.00 to 1.99 2.00 to 4.99 5.00 to 9.99 10.00 to 49.99 >50.00Inactive local-scale model area

Local-scale study area boundaryUrban area boundarySouthern boundary of Edwards aquifer recharge zone (outcrop) (modified from Puente, 1978)Simulated particle pathline for selected public-supply well (Areal extent of the particle pathlines bounded by the outer- most particle pathlines represents the surficial expression of the zone of contribution)Selected public-supply well (Q1–Q4, table 11)

EXPLANATION

Local-scale

study area

0 1.75 3.5 5.25 7 MILES0 1.75 3.5 5.25 7 KILOMETERS
Figure 26. Simulated areas contributing recharge, age of water particles derived from simulated particle traveltimes, and particle pathlines for the ZSan Antonio region, Texas.

San Antonio

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek San Geronimo Creek

He

lo

tes

 

Creek

Medina Lake

Medina River

MEDINA COUNTY BANDERA COUNTY

MEDINA COUNTY

BEXAR COUNTY

29°39'29°36'29°33'29°30'29°27'

98°55' 98°50' 98°45' 98°40' 98°35'

Base from U.S. Geological Survey digital data,Texas Centric Mapping System-Albers equal area projectionNorth American Datum of 1983

C A T C H M E N T A R E A C A T C H M E N T A R E A

Local-scale

study area

0 1.75 3.5 5.25 7 MILES0 1.75 3.5 5.25 7 KILOMETERS

Active local-scale model area Areas contributing recharge (discontinuous network of model-grid cells), by particle traveltimes, in years 0.00 to 1.99 2.00 to 4.99 5.00 to 9.99 10.00 to 49.99 >50.00Inactive local-scale model area

Local-scale study area boundaryUrban area boundarySouthern boundary of Edwards aquifer recharge zone (outcrop) (modified from Puente, 1978)Simulated particle pathline for Zarzamora monitoring well (Areal extent of the particle pathlines bounded by the outer- most particle pathlines represents the surficial expression of the zone of contribution)Zarzamora monitoring wells (WQ3–WQ5, table 11)

EXPLANATION
Figure 27. Simulated areas contributing recharge, age of water particles derived from simulated particle traveltimes, and particle pathlines for the TSan Antonio region, Texas.

San Antonio

Culebra

Creek

Leon Creek

Medio Creek

Quihi Creek San Geronimo Creek

He

lo

tes

 

Creek

Medina Lake

Medina River

MEDINA COUNTY BANDERA COUNTY

MEDINA COUNTY

BEXAR COUNTY

29°39'29°36'29°33'29°30'29°27'

98°55' 98°50' 98°45' 98°40' 98°35'

Base from U.S. Geological Survey digital data,Texas Centric Mapping System-Albers equal area projectionNorth American Datum of 1983

C A T C H M E N T A R E A C A T C H M E N T A R E A

Local-scale

study area

0 1.75 3.5 5.25 7 MILES0 1.75 3.5 5.25 7 KILOMETERS

Active local-scale model area Areas contributing recharge (discontinuous network of model-grid cells), by particle traveltimes, in years 0.00 to 1.99 2.00 to 4.99 5.00 to 9.99 10.00 to 49.99 >50.00Inactive local-scale model area

Local-scale study area boundaryUrban area boundarySouthern boundary of Edwards aquifer recharge zone (outcrop) (modified from Puente, 1978)Simulated particle pathline for Timberhill monitoring well (Areal extent of the particle pathlines bounded by the outer- most particle pathlines represents the surficial expression of the zone of contribution)Timberhill monitoring wells (WQ1–WQ2, table 11)

EXPLANATION
Simulation of Groundwater Flow 53

(discontinuous) appearance of the ACR probably represents 

different simulated flow paths of water particles traversing 

different HGUs with widely differing hydraulic conductivities 

and effective porosities. The “patchy” (discontinuous) appearance of the ACR is likely particularly affected by the extent 

to which the flow paths of water particles traverse the two 

conduit HGUs (HGU5 and HGU9) with comparatively high 

hydraulic conductivities, low effective porosities, and rapid 

flow.

The ACR to the selected PSW, Zarzamora well nest, and 

Timberhill well nest differ in their extent and cumulative area 

(total area of the discontinuous network of model grid cells) 

(figs. 25, 26, and 27, respectively). The ACR for the selected 

PSW has the greatest extent, from the San Antonio River on 

the east to the Medina River on the west, and the largest cumulative area, about 12,240 hectares. The ACR for the Timberhill 

well nest (located northwest of the selected PSW) has the least 

extent, encompassing approximately the western one-half 

of the ACR for the selected PSW, and the smallest cumulative area, about 6,210 hectares. The ACR for the Zarzamora 

well nest (northeast of the selected PSW) is intermediate in 

its extent and cumulative area, encompassing approximately 

the eastern two-thirds of the ACR for the selected PSW and 

covering an area of about 11,670 hectares. The extent of the 

ACR for the Zarzamora well nest is appreciably smaller than 

that for the selected PSW, but the cumulative areas for the 

two sites (selected PSW and Zarzamora well nest) are similar 

(11,670 and 12,240 hectares, respectively). This is because the 

simulated endpoint locations of water particles contributing 

water to the Zarzamora well nest occur within a smaller area 

and are more dense (less scattered) than those for the selected 

PSW (figs. 25 and 26). The ACR for the selected PSW has 

the greatest extent because the simulated particle endpoints 

include the flow contribution for the entire open interval of 

the well (simulated for the wellhead sampling), whereas the 

screened intervals for the Timberhill and Zarzamora wells are 

much shorter (3–4.5 m) and the simulated particle endpoints 

include the flow contribution for only two (Timberhill well 

nest) or three (Zarzamora well nest) depth intervals. In addition, the selected PSW is actively withdrawing water, creating 

flow towards the well, whereas the Timberhill and Zarzamora 

wells are monitoring wells with no groundwater withdrawals. 

Simulated particle ages ranged from less than 1 day 

to more than 1,900 years in the 10 local-scale study wells 

(13 local-scale study tritium observations) used to calibrate 

the local-scale model (table 13 at end of report). Simulated 

particle ages ranged from less than 1 day to more than 14,000 

years in the 29 NAWQA wells (42 NAWQA tritium observations) (table 13). The simulated particle ages for the localscale study tritium observations representing selected well 

depths (shallow, intermediate, and deep) ranged from less than 

1 day to 621 years. The minimum (youngest) particle ages for 

the selected PSW and the Zarzamora well nest were for the 

deep well depth, while the youngest particle age for the Timberhill well nest was for the intermediate well depth (table 13). 

The maximum (oldest) particle age for the Zarzamora well 

nest was for the shallow well depth, while the oldest particle 

age for the selected PSW and the Timberhill well nest was 

for the deep well depth. The wellhead or composite mean 

particle ages in the 10 local-scale study wells (13 local-scale 

study tritium observations) ranged from 3.7 to 7.6 years and 

was youngest for the Timberhill well nest and oldest for the 

Zarzamora well nest (table 13). The mean particle age in the 

29 NAWQA wells (42 NAWQA tritium observations) was 

42 years, about 2.8 times greater than the maximum mean 

particle age for the 10 local-scale study wells in the vicinity of 

the selected PSW (table 13). The reason for the greater mean 

particle age for the NAWQA wells may be that some of the 

wells receive contributions of water (simulated particles) with 

longer flow paths, and therefore presumably older age, than do 

the 10 local-scale study wells. 

The simulated mean particle ages for the tritium observations representing selected well depths (shallow, intermediate, 

and deep) ranged from 2.5 to 15 years. The minimum (youngest) mean particle ages for the selected PSW and the Timberhill well nest were for the intermediate well depth, while 

the youngest mean particle age for the Zarzamora well nest 

was for the intermediate and deep well depths (table 13). The 

maximum (oldest) mean particle ages for the selected PSW 

and the Zarzamora well nest were for the shallow well depth. 

The likely reason that the maximum (oldest) mean particle 

ages for the selected PSW and the Zarzamora well nest were 

for the shallow well depth is that the shallow well depth (sampling depth) lies above the simulated conduit HGUs (HGU5 

and HGU9), thereby lessening the contribution from the low 

effective porosity HGUs and fast flow paths. The mean of 

simulated particle ages for tritium observations representing 

well depths open to the conduit HGUs was 3.8 years, whereas 

the mean of simulated particle ages for tritium observations 

representing well depths not open to the conduit HGUs was 

9.6 years. The vertical pattern in the simulated particle ages 

for the depth-dependent sampling in the selected PSW follows 

the same pattern as for the measured tritium concentrations 

(tables 11 and 13). The shallow-depth observation has the 

highest measured concentration and maximum (oldest) simulated mean particle age, the intermediate depth observation has 

the lowest (youngest) measured concentration and minimum 

simulated mean particle age, and the deep depth observation 

has an intermediate measured concentration and simulated 

mean particle age. 

Apparent groundwater ages were available for 10 of the 

13 local-scale study tritium observations used to calibrate the 

local-scale model. The apparent groundwater ages, derived 

from concentrations of the geochemical tracer tritium, ranged 

from 0.8 to 41.3 years (table 13) (Musgrove and others, 2011). 

The simulated particle ages and apparent groundwater ages 

shown in table 13 represent pumping conditions with the test 

well (selected PSW, WZ4W) and the other wells in the well 

field pumping. The apparent groundwater ages are greater 

(older) than the simulated particle ages, with the exception of 

the deep depth observation for the Zarzamora well nest and 

the wellhead and shallow observations for the selected PSW 
54 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

(WZ4W). The greatest differences between the simulated 

particle ages and the apparent groundwater ages are for the 

Timberhill well nest observations, where apparent groundwater ages were much older than the simulated particle ages. A 

likely reason for this discrepancy is that geophysical logging 

and flow measurements made at the selected PSW and the 

Zarzamora and Timberhill well nests indicated less permeable, 

tighter material and less hydraulic connection with nearby 

pumping wells for the Timberhill well nest site than was the 

case for the selected PSW and the Zarzamora well nest sites. 

These site-specific hydraulic properties (that is, at the Timberhill well nest site) are not represented in the local-scale model 

because of the comparatively large model cell size (201.2 m 

on a side) and general lack of detailed hydrogeologic information other than at the three sites investigated for the TANC 

local-scale study. The simulated particle ages and the apparent 

groundwater ages indicate an inverse relation between age 

and depth below land surface (decreasing age with increasing 

depth below land surface) for the Zarzamora well nest. Also, 

both the simulated particle ages and the apparent groundwater ages indicate older ages for the wellhead observations for 

wells WZ2W and WZ3W than for the wellhead observations 

for well WZ6W and the selected PSW (WZ4W).

Supply-Well Vulnerability to Natural and 

Anthropogenic Contaminants

Like many karst aquifers, high porosity and permeability 

and rapid flow of recharging surface water through conduits, 

with little to no filtration, render the Edwards aquifer highly 

susceptible to contamination. Constituents of concern in the 

Edwards aquifer for the long-term sustainability of the groundwater resource include organic contaminants and the nutrient 

nitrate (NO3) (Musgrove and others, 2011). Measured concentrations of organic contaminants and NO3

 are currently low 

relative to levels of regulation. Nonetheless, the dominance 

of very young groundwater in the local-scale study area and 

specifically that reaching the selected PSW and other PSWs 

in the well field indicates that the aquifer and water supply are 

vulnerable to contamination. Although changes in pumping 

conditions might change the distribution of groundwater flow 

paths contributing water to the well field, under all pumping 

conditions the majority of the groundwater was young and, as 

such, is susceptible to anthropogenic contaminants (Musgrove 

and others, 2011).

The simulated age distribution for contributing-area 

water particles reaching the selected PSW ranged from less 

than 1 to 342 years, with a mean of 4.4 years. Particle-tracking 

(MODPATH) results indicate that 99 percent of the selected 

PSW water was less than 50 years old and that 88 percent of 

the water was less than 5 years old (fig. 28). Younger water 

(less than 50 years old) is more likely to be affected by human 

activities, and if present, most anthropogenic contaminants 

would be present in younger water. These model results 

concur with the conceptual understanding that a large fraction 

of water in the aquifer, and particularly in the selected PSW, 

is young (less than 50 years old). Water samples from the 

selected PSW, other wells in the well field, and other PSWs 

completed in the Edwards aquifer contain detectable concentrations of a small number of some pesticides and VOCs 

(Musgrove and others, 2011). Natural attenuation processes 

are also likely to be limited in flow systems with young 

groundwater, in particular for conditions or contaminants 

where degradation processes are slow (Chapelle and Bradley, 

1999; McMahon and others, 2008) such as the case in this 

oxic aquifer. In flow systems with a higher fraction of olderage water (that is more than 50 years old), that fraction could 

dilute anthropogenic contaminant concentrations when waters 

of different ages mix within the aquifer and the open borehole 

of a PSW (Osenbrück and others, 2006). 

In a model-forecasting exercise, slug inputs of a hypothetical contaminant were used to examine the range in lag 

times, dilution, and degradation that might be expected at the 

selected PSW (Musgrove and others, 2011). Results of this 

exercise might be representative of a rapid land-use change 

overlying the contributing area of a PSW in the local-scale 

study area and might represent how quickly the aquifer 

responds to mitigation. The hypothetical contaminant was 

introduced over the ACR for the selected PSW continuously 

for 30 years. Each ACR (recharge zone) cell was loaded with 

a relative contaminant concentration of 1 (that is, relative to 

a background concentration of 0). After 30 years, the contaminant input returned to zero. The hypothetical response 

at the PSW is illustrated in figure 29 for (1) a simulation 

with no contaminant degradation and (2) a simulation with 

Figure 28. Simulated age of water particles reaching the 

selected public-supply well, San Antonio region, Texas.

Simulated water particle traveltime, in years

<0.5 0.5 to <2 2–4.9 5–9.9 10–19.9 20–50 51–100 >100

0

10

20

30

40

50

Proportion of flow to public-supply well, in percent
Simulation of Groundwater Flow 55

contaminant degradation at a first-order reaction kinetics 

degradation rate of 0.1 per year (10 percent per year). For both 

responses (curves in fig. 29), concentrations at the selected 

PSW began to rise within 1 year after loading began and rose 

quickly to reach 50 percent of peak concentration in 3 (with 

nondegradation) or 4 years (with degradation). The nondegradation curve continued to rise rapidly until about 5 years, 

when 77 percent of peak concentration was reached. Concentrations continued to rise for both curves until peak concentrations were reached at the end of the input period of 30 years. 

Maximum concentrations were 98 percent of input for the 

nondegradation curve and 73 percent of input for the withdegradation curve. Once the input was stopped after 30 years, 

both simulations responded with a rapid drop in concentration. Concentration decreased to about 50 percent of input in 

3 years in the nondegradation simulation and in a little more 

than 2 years for the with-degradation simulation. Concentration decreased to 25 percent of input in 5 years (nondegradation) and in less than 4 years (with degradation). Although 

peak concentrations dropped quickly after input ceased, 32 

and 12 years were required, respectively, to flush 99 percent 

of the hypothetical contaminant and achieve near background 

conditions (Musgrove and others, 2011). 

Lag times would be expected to be shorter for wells with 

large fractions of young water (McMahon and others, 2008), 

such as observed for this study, than for wells with smaller 

fractions of young water. The effect of short-circuit pathways, 

for example karst conduits, in the flow system on the movement of young water to the selected PSW could greatly alter 

contaminant arrival times compared to what might be expected 

from advection in a system without short circuiting. This 

observation is particularly valid for karst such as the Edwards 

aquifer: numerous voids are present in wells completed in 

this aquifer, including the selected PSW. In the forecasting 

exercise, the simulated concentrations showed rapid initial 

response at the beginning and end of chemical input, followed 

by more gradual response as older water moved through the 

system. The nature of karst groundwater flow, where flow 

predominantly occurs via conduit flow paths, could lead to 

relatively rapid water quality responses to land-use changes. 

The forecasting exercise did not consider chemical storage and transit times in the unsaturated zone, dispersion/diffusion, or transient flow conditions in the aquifer, which might 

yield substantially different results (Musgrove and others, 

2011). Transient conditions in the flow system could result in 

more complex ACR and groundwater age distributions than 

were assessed here and should be considered in future studies 

(Franke and others, 1998; Rock and Kupfersberger, 2002). 

Spatial variability in input, which would likely have considerable effect on concentrations and movement of contaminants, 

also was not considered. The spatial component of land-use 

change is also important because the complex distribution 

of particle traveltimes within the ACR strongly influences 

contaminant arrival times and degradation reaction progress. 

Results from this forecasting exercise and other similar exercises (McMahon and others, 2008) indicate that timescales for 

change in the quality of water from the selected PSW could 

be on the order of a few years to decades for land-use changes 

that occur over days to decades, which has implications for 

source-water protection strategies that rely on land-use change 

to achieve water-quality objectives. 

Model Uncertainties and Limitations

An understanding of model limitations is essential to 

appropriately use groundwater-flow and particle-tracking 

simulation results. The accuracy of groundwater-flow models is limited by simplification of complexities within the 

flow system, by space and time discretization effects, and by 

assumptions made in the formulation of the governing flow 

equations. Model accuracy also is limited by cell size, number 

and representation of layers, accuracy of boundary conditions, 

accuracy and availability of data on hydraulic properties, accuracy of groundwater withdrawal and groundwater recharge 

estimates, historical data for calibration, parameter sensitivity, and the interpolations and extrapolations that are inherent 

in using data in a model. In addition, a combination of input 

values to the model different from those used in the calibrated 

simulations could produce the same result; the solution is not 

unique.

Models solve for average conditions within each cell, 

the parameters for which are interpreted or extrapolated from 

measurements and estimated during calibration. The relatively 

coarse grid cell size (201.2 m on a side) of the local-scale 

model does not fully incorporate the complex hydrogeology of 

the karstic Edwards aquifer. Hydrogeologic units often have 

Figure 29. Simulated time series of hypothetical contaminant 

concentrations at the selected public-supply well based on 30 

years of contaminant input (at relative concentration of 1) in the 

simulated areas contributing recharge, San Antonio region, 

Texas.

0 10 20 30 40 50 60 70 80

Elapsed time, in years

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Relative contaminant concentration

Input

period

No degradation

With degradation (0.1)

EXPLANATION
56 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

characteristics, such as being thin or pinching out or being 

faulted and discontinuous, that make them difficult or impossible to represent with any model. Scant information exists 

regarding hydraulic properties, flow rates, and karst features 

of the Edwards aquifer HGUs other than the geophysical logging conducted by the USGS in 2008 (Gregory Stanton, U.S. 

Geological Survey, written commun., 2008) in the selected 

PSW and nearby monitoring wells. Therefore, the results from 

the selected PSW and nearby monitoring wells were extrapolated throughout the local-scale model area. In addition, in 

the local-scale model the overburden is simulated as a single 

HGU with uniform hydraulic properties representing multiple 

geologic units. The boundary conditions for the local-scale 

model are derived from the regional-scale model. To the extent 

that the regional model may contain errors in representing the 

flow system in the local-scale model domain, the boundary 

conditions used in the local-scale model also could be a source 

of model error.

Additional uncertainties and limitations apply in regard 

to the MODPATH particle-tracking simulations. The assumed 

local-scale model boundary conditions may affect the age 

distribution of particles entering the simulated wells and the 

simulated ACR. A small portion of those particles were found 

to originate from the northern model boundary itself, indicating that the complete ACR to wells might not be delineated. 

However, the effects of particles originating from the northern 

model boundary itself are likely minimal because the inflow 

through the northern model boundary is only about 1 percent 

of the total sources of water to the aquifer. The relatively 

coarse discretization of the model grid might also affect the 

simulated ACR for the selected PSW. The selected PSW and 

two other PSWs are all located in row 230, column 264 of 

the model grid and are screened across partially overlapping 

model layers. Because the model grid cells (one row, column 

location but multiple model layers) containing the selected 

PSW contain two other PSWs, the simulated ACR for the 

selected PSW may be more representative of the combined 

ACR for the three PSWs than specifically for the selected 

PSW alone. Dispersion, diffusion, adsorption, retardation, 

degradation, or any other transport process affecting the concentrations of contaminant constituents is not included in the 

MODPATH simulation for determining traveltimes of water. 

Estimates of groundwater traveltimes and ACR can be in error 

if the effects of dispersion and mixing on age-tracer (tritium) 

concentrations are ignored. Advection-dispersion transport 

simulations would likely yield larger ACR than would advective particle-tracking simulations because the effects of dispersion caused by aquifer heterogeneity would be included.

It is assumed for a steady-state model that the system 

is in equilibrium. Water-level hydrographs indicate that 

this generally is the case in the local-scale model area over 

time. Long-term hydrographs (about 80 years) indicate no 

net decline (or rise) of water-level altitudes in the San Antonio region. Average stresses (recharge and pumpage) during 2001 were used to simulate steady-state conditions for 

the local-scale model. Errors related to this assumption of 

steady-state could be notable, and consideration should be 

taken in interpreting model results and analyses that depend 

on model output, particularly for the particle-tracking results. 

For steady-state simulations, an analytical expression for the 

flow path in each cell is calculated by direct integration of the 

velocity components. The traveltime calculated by this method 

represents an average traveltime for the advection of a “particle” of water or a conservative solute. 

The entire potential timeframe associated with the movement of tritium from the source area (recharge zone) to the 

wells (about 40 years; 1969–2009) is not necessarily subject 

to the same hydrologic conditions as those used to calibrate 

the local-scale steady-state model (average stresses during 

2001). The similarity between the mean measured waterlevel altitudes for 2001 and 2000–10 might indicate that the 

local-scale model results are more representative of recent 

hydrologic conditions (2000–10) than they are of hydrologic 

conditions longer ago. Apparent groundwater ages in a karst 

system such as the Edwards aquifer reflect mixtures of water 

that likely vary temporally as a result of changes in hydrologic 

conditions; therefore, a one-time sampling (or narrow window 

of sampling time) might not provide representative apparent 

groundwater ages (Musgrove and others, 2009). Variability in 

hydrologic conditions and the transient nature of the Edwards 

aquifer likely do influence measured tritium concentrations 

and apparent groundwater ages, and these transient effects 

are not accounted for in the local-scale steady-state model. 

However, a large dataset of historical tritium values that 

would be necessary to quantitatively account for transient 

effects on tritium concentrations is not available for the 

Edwards aquifer. 

Variability in hydrologic conditions and transient effects 

not accounted for in the local-scale steady-state model include 

cyclic hydrologic conditions that are similar in length to 

mean particle traveltimes or mean particle traveltimes that are 

shorter than the duration of cyclic hydrologic conditions. The 

simulated steady-state mean traveltimes to wells in the ACR to 

the selected PSW for this study are generally less than 5 years. 

The effects of long-term cyclic hydrologic conditions that 

occur over multiple years, such as droughts, on traveltimes to 

wells is largely unknown for the Edwards aquifer because of 

a lack of applicable age-tracer data and is beyond the scope of 

this study. Fast flow paths (conduits) have been documented 

by dye-tracing experiments in the Edwards aquifer and are 

simulated in the local-scale steady-state model that result in 

short traveltimes of less than 1 year for a small portion of the 

water particles reaching a well. In addition, there are likely 

fast flow paths not represented in the local-scale model which 

cause more variation in the traveltime distributions and locations of ACR than would be computed by either steady-state 

or transient simulations. Traveltimes of particles through the 

fast flow paths are unlikely to be appreciably affected by longterm hydrologic cycles but may be affected by seasonal or 

shorter term cycles. However, as previously stated in the section “Development and Application of Groundwater Flow and 

Particle-Tracking Models,” the steady-state simulations are not 
Summary 57

intended to exactly match transient hydrologic conditions and 

transport characteristics in the karstic Edwards aquifer system 

but rather are meant to be used as a tool to better understand 

the movement of contaminants to PSWs. The effects of storage, not accounted for in steady-state simulations, on traveltimes are likely to be minimal because the water released from 

storage is ultimately derived from recharge and is not a different source of water (Leon Kauffman, U.S. Geological Survey, 

written commun., 2008); that is, the water released from 

storage is derived from recharge, with an age corresponding to 

the time that recharge occurred, not a new source of water that 

would have a different age.

A comparison between simulated particle ages and apparent groundwater ages might be more uncertain for the karstic 

Edwards aquifer than for other types of aquifers for a number 

of reasons. Hydrogeologically, groundwater in the Edwards 

aquifer undergoes appreciable mixing. Also, the apparent ages 

themselves are an interpretation of tracer concentrations, and 

that interpretation is based on some assumed hydrogeologic 

conceptual model. The apparent ages used for comparison 

with the simulated particle ages for this study are based on 

a piston-flow geochemical model, which may not be a valid 

model for karst aquifers (Musgrove and others, 2011). This 

is further indicated by a lack of good correlation between the 

age-tracer (tritium) and other independent geochemical tracers 

that provide insight into the relative residence time of water 

in the aquifer. Additional information on the mean apparent 

age of groundwater derived from age-tracer concentrations is 

discussed in Musgrove and others (2009) and Musgrove and 

others (2011).

Results from the local-scale model described herein 

should be interpreted generally and are best suited for comparative analysis rather than for prediction at this location. 

The local-scale model was developed to portray and test 

the conceptual understanding of the aquifer system. The 

model was not expected to reproduce the natural system or 

transient hydrologic conditions in detail but was intended to 

represent its dominant characteristics. This is especially true 

in aquifers with karst features where there is an extreme difference in aquifer properties at scales much smaller than the 

minimum representation in the numerical model. Although the 

simulated ACR for the selected PSW and nearby well nests in 

San Antonio likely do not represent the true areas contributing 

recharge, they are a useful tool for delineating approximate 

areas that may serve as sources of groundwater recharging 

the wells and potential sources of contaminants at the time of 

recharge. 

Summary 

In 2006, a public-supply well (PSW) in San Antonio, 

Tex., was selected for intensive study to assess the vulnerability of PSWs in the Edwards aquifer to contamination by 

a variety of compounds. The construction and operational 

practices of this PSW (hereinafter, the “selected PSW”) are 

representative of many PSWs that use the Edwards aquifer 

for supplying the population of San Antonio, which includes 

Bexar and Comal Counties. A total of six wells were installed 

in 2007–8 in two nests (with four wells in one nest and two 

wells in the other nest) oriented along one of the general 

directions of groundwater flow to the selected PSW to support a detailed analysis of physical and chemical conditions 

and processes affecting the water chemistry of the selected 

PSW. A local-scale, steady-state, three-dimensional numerical 

groundwater-flow model was developed and used in this study 

to evaluate the movement of water and solutes from recharge 

areas to the selected PSW. The uniformly spaced finitedifference grid used to spatially discretize the model area for 

the local-scale model has 300 rows and 350 columns and is 

rotated 35 degrees counterclockwise from horizontal. The 

dimensions of the grid cells are uniformly 201.2 m along rows 

and columns. The local-scale model has 92 layers, each with a 

uniform thickness of 8 m and top and bottom surfaces that dip 

downward to the south and east with a uniform slope, following the general slope of the top of the Edwards aquifer. The 

local-scale model includes 12 hydrogeologic units (HGUs), 

whose properties are defined by using the MODFLOW 

Hydrogeologic-Unit Flow (HUF) Package. The geometry of 

the HGUs is defined independently of the model layers, with 

the model-layer geometry being superimposed on the defined 

HGUs. In the local-scale model, one to three HGUs are present in each active model cell. HGU5 and HGU9 (“conduit” 

HGUs) represent hydrogeologic units with high hydraulic 

conductivities (one or more orders of magnitude higher than 

for the other HGUs) and low effective porosities (10-4) that 

are intended to simulate fast flow paths attributable to karst 

features. 

Numerous faults with varying vertical displacements 

occur in the local-scale model area. The extensive faulting 

results in the juxtaposition of HGUs with differing hydraulic 

properties and has appreciable effects on groundwater flow in 

the Edwards aquifer. The use of the MODFLOW HUF Package results in different HGUs with differing hydraulic properties being frequently juxtaposed in adjacent cells in the localscale model, allowing water particles to move between HGUs 

within the same model layer. The MODFLOW HorizontalFlow Barrier (HFB) Package was used to explicitly simulate 

faults in the local-scale model. 

Boundary conditions for the local-scale model include 

specified fluxes entering or exiting the model area at the 

boundaries. In the local-scale model, specified fluxes are 

used for boundary conditions on all sides and layers of the 

model, except for layers that are inactive at the model boundary or whose thickness includes only HGU1. Water flowing 

across the boundary into HGU1 is assumed to be negligible. 

A nonzero flux boundary was used for the northern model 

boundary to account for inflow from the adjacent Trinity 

aquifer. The fluxes from an existing two-layer diffuse-flow 

rediscretized regional Edwards aquifer model were apportioned among the 92 layers of the local-scale model on the 
58 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

basis of the cumulative transmissivities of the HGUs present 

in each boundary cell. The net boundary flux for the western 

local-scale model boundary is into the local-scale model area 

(986,034 cubic meters per day [m3/d]), while the net boundary 

fluxes for the eastern and southern local-scale model boundaries are out of the local-scale model area (782,013 and 327,430 

m3/d, respectively). 

Stresses simulated in the local-scale model include 

recharge from precipitation, discharge from pumping, and 

discharge to springs. Recharge to the Edwards aquifer occurs 

primarily by seepage from streams to the aquifer in the 

recharge zone. Additional recharge is from infiltration of rainfall in the interstream areas of the recharge zone. Eighty-five 

percent of the recharge was applied to streambed cells, and the 

remaining 15 percent was applied to the interstream area cells. 

No recharge was applied to cells outside the recharge zone. 

Discharge from the Edwards aquifer includes withdrawals by 

wells and springflow. Average withdrawal rates by wells for 

2001 were distributed spatially within the model grid for the 

local-scale model on the basis of the well locations. The vertical assignment of withdrawals to a model layer was done on 

the basis of the percentage of the screened interval in each of 

the model layers and the transmissivity of the HGUs present in 

each model layer. The springs were simulated in the model by 

using the MODFLOW Drain Package. 

The aquifer hydraulic properties specified in the localscale model—horizontal hydraulic conductivity and horizontal 

and vertical anisotropy—were defined by using the MODFLOW HUF Package. The simulated horizontal hydraulic conductivities for the local-scale model include a base horizontal 

hydraulic conductivity that varies by HGU and additional 

zones and values of horizontal hydraulic conductivity that are 

the same for multiple HGUs. Horizontal hydraulic conductivity zones, in addition to the base horizontal hydraulic conductivity zone (zone 1), include (1) zones of high horizontal 

hydraulic conductivity through the center of the confined part 

of the aquifer and near the northern boundary of the freshwater/saline-water transition zone, (2) zones of comparatively 

high horizontal hydraulic conductivity in the recharge zone 

underlying streambeds, and (3) zones of differing horizontal hydraulic conductivity near the boundary between the 

recharge zone and the confined part of the Edwards aquifer. Six zones of horizontal anisotropy are simulated in the 

local-scale model. The confined part of the Edwards aquifer 

composes one of the horizontal anisotropy zones, and five of 

the zones are delineated in the recharge zone of the aquifer. 

Uniform vertical anisotropy values were applied to each of the 

12 simulated HGUs.

Particle tracking was performed by using MODPATH 

and was used to compute flow paths and advective traveltimes 

throughout the model area and to delineate the areas contributing recharge (ACR) and zones of contribution (ZOCs) for the 

selected PSW and the two monitoring well nests (Timberhill 

and Zarzamora). Calculated flux-weighted concentrations 

of the age-tracer tritium reaching the well were compared 

with measured concentrations to evaluate the adequacy of 

the local-scale model to simulate traveltimes and flow paths 

for potential contaminants. To calculate concentrations of the 

age-tracer tritium at the selected PSW and monitoring wells, 

particle tracking was used to obtain a distribution of particle 

ages that were then associated with a local tritium input function. A backward-tracking approach was used in MODPATH 

to obtain the particle-age distributions. Along with output 

from the local-scale model, the MODPATH simulations 

required effective porosity values to calculate groundwaterflow velocities. Changes to input effective porosity values 

change computed traveltimes from recharge areas to discharge 

areas (PSWs) in direct proportion to changes in effective 

porosity. Initial values of 0.01 for the HGUs with comparatively high hydraulic conductivities, 0.001 for the HGUs with 

comparatively low hydraulic conductivities, and 0.0001 for the 

two simulated conduit HGUs were specified in the local-scale 

model. 

The local-scale model was calibrated for steady-state 

conditions. Average stresses (recharge and pumpage) during 

2001, a representative year for the recent time period (2000–

10), were used to simulate steady-state conditions. Groundwater-flow-model and particle-tracking calibration was 

evaluated by using 84 groundwater-level altitudes and 13 

tritium concentrations. Overall, 70 parameters were used to 

define the simulation, including those for horizontal hydraulic 

conductivity, horizontal and vertical anisotropy, drain and fault 

hydraulic conductances, and effective porosity. The local-scale 

model was calibrated by using systematic manual calibration and by using the parameter-estimation code PEST. The 

parameters (1) vertical anisotropy for HGU2, HGU5, HGU9, 

and HGU11, (2) horizontal anisotropy for HANI zone 5, and 

(3) horizontal hydraulic conductivity for HK zones 15 and 17, 

with PEST-computed composite sensitivities greater than 70 

(no units), are the most sensitive parameters in the simulation. 

Parameters with composite sensitivities equal to or less than 

10 (no units) are effective porosities for all HGUs other than 

HGU9.

Model parameter values were varied during model 

calibration by using systematic manual calibration and 

PEST simulations to minimize the difference between modelcomputed and measured water-level altitudes, spring discharges, and age-tracer (tritium) concentrations. As a result 

of the steady-state calibration, the drain hydraulic conductance for San Antonio Springs was decreased by about 26 

percent, and the drain hydraulic conductance for San Pedro 

Springs was increased by about 55 percent. The hydraulic 

conductances for HFB1, HFB2, and HFB3 were reduced by 

four to seven orders of magnitude compared to the initial 

values. The low calibrated effective porosities of about 10-4

(dimensionless) for the conduit HGUs indicate that the flow 

occurs in only a small percentage of the total volume of the 

aquifer, which is consistent with the concept of flow through 

conduits. 

The calibrated steady-state simulation generally 

reproduces the spatial distribution of measured water-level 

altitudes. Simulated water-level altitudes were within 9.0 m 
Summary 59

of measured water-level altitudes at 74 of the 84 wells used as 

targets for the local-scale model for the calibrated steady-state 

simulation and was less than 3.0 m at 42 of the 84 wells. The 

overall mean absolute difference between simulated and measured water-level altitudes is 4.2 m. The mean algebraic difference between simulated and measured water-level altitudes is 

1.9 m, indicating that simulated water-level altitudes are on 

an overall basis slightly lower than measured water-level 

altitudes. The simulated springflow for San Antonio Springs 

was 7.7 percent greater and for San Pedro Spring was 4.2 percent less than the median measured springflow.

Simulated age-tracer (tritium) concentrations were generally in good agreement with measured values in wells in the 

model area. Simulated tritium concentrations were within 

0.35 tritium units (TU) of measured tritium concentrations 

for the 13 tritium observations (hereinafter, the “local-scale 

study tritium observations”) from 10 wells (hereinafter, the 

“local-scale study wells”) used as observations in PEST simulations to calibrate the local-scale model. Simulated tritium 

concentrations were within 3.52 TU of measured tritium 

concentrations for an additional 42 tritium observations 

(hereinafter, the “NAWQA tritium observations”) from 29 

NAWQA wells (hereinafter, the “NAWQA wells”) not 

used as observations in the PEST simulations. The mean 

absolute difference between simulated and measured tritium 

concentrations for the local-scale study wells is 0.11 TU, 

and the mean algebraic difference is -0.04 TU. Simulated 

tritium concentrations were within 0.14 TU of measured 

concentrations for 11 of the 13 local-scale study tritium 

observations. The mean absolute differences between simulated and measured tritium concentrations, grouped by the 

sampling location (at the wellhead) or sampling depth (shallow, intermediate, or deep), are similar among values grouped 

as wellhead, intermediate, or deep observations (0.09, 0.06, 

and 0.11 TU, respectively) but are higher for the shallow 

grouping (0.23). Simulated tritium concentrations in the 

selected PSW during November 2007 were within 0.09 TU 

of the measured concentrations, with the exception of the 

shallow-depth observation. The vertical pattern in the measured tritium concentrations for the depth-dependent sampling 

in the selected PSW has the highest concentration for the 

shallow-depth observation, the lowest concentration for the 

intermediate-depth observation, and the middle concentration 

for the deep-depth observation. The simulated concentrations 

follow the pattern for the intermediate and deep observations but not for the shallow-depth observation. Poor matches 

between measured and simulated tritium concentrations might 

be a result of model limitations, such as inexact representations of karst features and their placement and the assumption 

of steady-state flow.

The simulated potentiometric surface was generally 

representative of the measured potentiometric surface in the 

local-scale model area. Water in the local-scale model flowed 

from the recharge zone toward the south and southeast into 

the confined zone. Water-level altitudes decreased from north 

to south, from north to southeast, and from west to east across 

the local-scale model area, and were in generally good agreement with the observed flow directions. Comparatively large 

simulated water-level changes coincide with the locations of 

large-displacement faults in the western part of the local-scale 

study area and in west-central Bexar County, consistent with 

measured water-level altitudes. 

The steady-state simulation water budget indicates that 

recharge occurring in the local-scale study area accounts for 

31.8 percent of the sources of water to the Edwards aquifer 

in the local-scale model area and that inflow through the 

model boundaries contributes 68.2 percent. Most of the flow 

into the local-scale model area through the model boundaries occurs through the western and southern boundaries, 

58.2 and 39.6 percent, respectively. The largest discharges 

from the Edwards aquifer in the local-scale model area 

are boundary outflow (71.4 percent) and withdrawals by 

wells (24.9 percent). Most of the flow out of the local-scale 

model area through the model boundaries occurs through 

the southern and eastern boundaries, 54.2 and 39.6 percent, 

respectively. Springflow from San Antonio and San Pedro 

Springs contribute a small amount (3.7 percent) to the total 

discharge.

The simulated ZOCs for the selected PSW, Timberhill 

well nest, and Zarzamora well nest extend to the north, northeast, and northwest from each site in the confined zone of the 

aquifer into the recharge zone. The “patchy” (discontinuous) 

appearance of the ACR probably represents different simulated flow paths of water particles traversing different HGUs 

with widely differing hydraulic conductivities and effective 

porosities. The ACR for the selected PSW has the greatest 

extent, from the San Antonio River on the east to the Medina 

River on the west. The ACR for the Timberhill well nest 

(located northwest of the selected PSW) has the least extent, 

encompassing approximately the western one-half of the ACR 

for the selected PSW. The ACR for the Zarzamora well nest 

(located northeast of the selected PSW) is intermediate in its 

extent, encompassing approximately the eastern two-thirds of 

the ACR for the selected PSW.

Simulated particle ages ranged from less than 1 day 

to more than 1,900 years in the 10 local-scale study wells 

(13 local-scale study tritium observations). Simulated particle 

ages ranged from less than 1 day to more than 14,000 years 

in the 29 NAWQA wells (42 NAWQA tritium observations). 

The simulated particle ages for the local-scale study tritium 

observations representing selected well depths (shallow, intermediate, and deep) ranged from less than 1 day to 621 years. 

The minimum (youngest) particle ages for the selected PSW 

and the Zarzamora well nest were for the deep well depth, 

while the youngest particle age for the Timberhill well nest 

was for the intermediate well depth. The maximum (oldest) 

particle age for the Zarzamora well nest was for the shallow 

well depth, while the oldest particle ages for the selected PSW 

and the Timberhill well nest were for the deep well depth. The 

wellhead or composite mean particle ages in the 10 local-scale 

study wells (13 local-scale study tritium observations) ranged 

from 3.7 to 7.6 years and was youngest for the Timberhill well 
60 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

nest and oldest for the Zarzamora well nest. The mean particle 

age in the 29 NAWQA wells (42 NAWQA tritium observations) was 42 years, about 2.8 times greater than the maximum 

mean particle age for the 10 local-scale study wells.

The simulated mean particle ages for the tritium observations representing selected well depths (shallow, intermediate, 

and deep) ranged from 2.5 to 15 years. The minimum (youngest) mean particle ages for the selected PSW and the Timberhill well nest were for the intermediate well depth, while the 

youngest mean particle age for the Zarzamora well nest was 

for the intermediate and deep well depths. The maximum 

(oldest) mean particle ages for the selected PSW and the 

Zarzamora well nest were for the shallow well depth. The 

mean of simulated particle ages for tritium observations representing well depths open to the conduit HGUs was 3.8 years, 

whereas the mean of simulated particle ages for tritium observations representing well depths not open to the conduit HGUs 

was 9.6 years.

In a model-forecasting exercise, slug inputs of a hypothetical contaminant were used to examine the range in lag 

times, dilution, and degradation that might be expected at the 

selected PSW. The hypothetical contaminant was introduced 

over the ACR for the selected PSW continuously for 30 years, 

and simulations with no contaminant degradation and with 

contaminant degradation at a first-order reaction kinetics 

degradation rate of 0.1 per year (10 percent per year) were 

conducted. For both simulations, concentrations at the selected 

PSW began to rise within 1 year after loading began and rose 

quickly to reach 50 percent of peak concentration in 3 (with 

nondegradation) or 4 years (with degradation). Concentrations 

continued to rise for both simulations until peak concentrations were reached at the end of the input period of 30 years. 

Once the input was stopped after 30 years, both simulations 

responded with a rapid drop in concentration. However, 32 

and 12 years were required for the nondegradation and withdegradation simulations, respectively, to flush 99 percent of 

the hypothetical contaminant and achieve near background 

conditions. 

The effect of short-circuit pathways, for example karst 

conduits, in the flow system on the movement of young 

water to the selected PSW could greatly alter contaminant 

arrival times compared to what might be expected from advection in a system without short circuiting. In the forecasting 

exercise, the simulated concentrations showed rapid initial 

response at the beginning and end of chemical input, followed 

by more gradual response as older water moved through the 

system. The nature of karst groundwater flow, where flow 

predominantly occurs via conduit flow paths, could lead to 

relatively rapid water quality responses to land-use changes. 

Results from the forecasting exercise and other similar 

exercises indicate that timescales for change in the quality of 

water from the selected PSW could be on the order of a few 

years to decades for land-use changes that occur over days to 

decades, which has implications for source-water protection 

strategies that rely on land-use change to achieve water-quality 

objectives.

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66 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 1. Summary of groundwater wells used in the local-scale model, San Antonio region, Texas.—Continued 

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 

is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is 

Glen Rose (Trinity Group); WZ4W is wellhead sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate 

depth-dependent sampling interval for well WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; 

WZ6W is wellhead sample for well WZ6; WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3]

Well or 

sample name

Well or sample 

identifier

Hydrogeologic unit 

number(s)

Land surface altitude

(meters)

Depth to top 

of open interval

(meters)

Well depth

(meters)

6827307 W1 11 301 58 82

6827401 W2 4–10 313 54 129

6827517 W3 7–8 303 66 92

6827609 W4 8–10 294 58 80

6827610 W5 4–6 278 45 73

6827611 W6 4 293 58 79

6827612 W7 3–4 291 57 78

6828113 W8 7–8 310 76 98

6828210 W9 2–3 300 61 86

6828211 W10 10–12 297 67 91

6828313 W11 12 291 60 91

6828314 W12 7–8 273 52 73

6828315 W13 12 288 58 85

6828406 W14 6–8 299 68 93

6828407 W15 7–8 305 73 94

6828512 W16 6–12 290 0 122

6828515 W17 6 297 75 93

6828516 W18 6–7 290 62 92

6828518 W19 6 281 55 80

6828519 W20 6–7 281 55 85

6828608 W21 3–11 262 53 152

6828609 W22 5–7 280 61 79

6828909 W23 3–11 238 128 264

6828920 W24 1 280 76 110

6828921 W25 3–11 250 113 261

6829103 W26 1–10 291 30 167

6829112 W27 6–9 272 49 79

6829113 W28 1 272 49 73

6829418 W29 1 253 34 55

6835106 W30 3–11 292 88 232

6835202 W31 1–3 259 43 87

6836103 W32 1–11 275 104 251

6836130 W33 3–11 271 119 242

6836206 W34 2–7 228 164 228

6836502 W35 2–11 209 220 371

6836901 W36 2–4 193 248 267

6837103 W37 3–11 223 178 306

6837203 W38 1–6 222 212 266

6837304 W39 1 213 222 221

6837524 W40 1 198 256 272

6843402 W41 1–10 213 511 651

Table 1
Table 1 67

Table 1. Summary of groundwater wells used in the local-scale model, San Antonio region, Texas.—Continued 

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 

is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is 

Glen Rose (Trinity Group); WZ4W is wellhead sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate 

depth-dependent sampling interval for well WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; 

WZ6W is wellhead sample for well WZ6; WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3]

Well or 

sample name

Well or sample 

identifier

Hydrogeologic unit 

number(s)

Land surface altitude

(meters)

Depth to top 

of open interval

(meters)

Well depth

(meters)

6843606 W42 1 187 475 478

68285AA W43 1–11 270 Unknown Unknown

68299BB W44 3–11 221 Unknown Unknown

68299CC W45 3–11 220 Unknown Unknown

68377AA W46 3–11 192 Unknown Unknown

68431AA W47 1–11 220 Unknown Unknown

68437AA W48 1–11 194 Unknown Unknown

6826802 W49 3–5 305 241 299

6833604 W50 1–3 259 18 195

6834506 W51 3–11 320 137 285

6841301 W52 3–4 231 193 216

6842106 W53 1–4 236 165 226

6842112 W54 3 234 349 352

6842502 W55 2–4 223 340 392

6939504 W56 1 312 26 199

6939801 W57 1–4 292 185 263

6939901 W58 6–11 285 201 328

6940101 W59 2–11 310 Unknown Unknown

6940102 W60 1–10 295 0 170

6940404 W61 1–8 285 61 161

6940901 W62 4 269 340 371

6947301 W63 1–6 279 305 460

6947306 W64 1–7 271 369 457

6948102 W65 4–10 264 391 504

6948303 W66 7–10 305 445 500

68339AA W67 4–11 235 Unknown Unknown

68415AA W68 1–11 290 Unknown Unknown

68416AA W69 1–11 293 Unknown Unknown

68422AA W70 1–8 236 Unknown Unknown

69396AA W71 1–10 308 Unknown Unknown

69489AA W72 1–7 243 Unknown Unknown

YMCA W73 3–10 270 Unknown Unknown

Graham W74 1–11 261 Unknown Unknown

Lockhill W75 9–11 280 107 166

Abe Lincoln W76 2–11 276 Unknown Unknown

Propane Depot W77 1–10 265 Unknown Unknown

Salazar W78 1–11 251 Unknown 41

Zarzamora_OVB W79 1 258 62 77

Timberhill_IED WQ1 4–6 242 146 155

Timberhill_DED WQ2 8–10 242 197 200

Zarzamora_SED WQ3 3 258 102 105
68 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 1. Summary of groundwater wells used in the local-scale model, San Antonio region, Texas.—Continued 

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 

is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is 

Glen Rose (Trinity Group); WZ4W is wellhead sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate 

depth-dependent sampling interval for well WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; 

WZ6W is wellhead sample for well WZ6; WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3]

Well or 

sample name

Well or sample 

identifier

Hydrogeologic unit 

number(s)

Land surface altitude

(meters)

Depth to top 

of open interval

(meters)

Well depth

(meters)

Zarzamora_IED WQ4 4 258 121 127

Zarzamora_DED WQ5 7–8 258 179 182

WZ4W Q1 2–11 271 98 249

WZ4S Q2 3 271 98 249

WZ4I Q3 4–5 271 98 249

WZ4D Q4 8–9 271 98 249

WZ5W Q5 4–11 275 123 240

WZ6W Q6 4–11 276 122 250

WZ2W Q7 2–11 277 104 251

WZ3W Q8 2–11 271 98 246

Parkwood Park Q9 4–6 273 45 70

Indian Meadows Q10 6–7 289 62 92

Lockhill-S-PO Q11 1 297 75 93

DeZavala PO Q12 7–8 298 68 93

Helotes Q13 6–8 304 66 91

Bluestone Q14 3–4 293 57 78

Western Oak Q15 7–10 293 58 80

Huebner at Olmos Q16 6 280 55 85

VJ Beckwith Q17 7–8 305 73 94

Roadrunner Way Q18 2–4 294 58 79

Shavano Woods Q19 10–11 294 55 80

SP-Cliffside Q20 6 282 55 80

Babcock Firestation Q21 10–11 303 58 82

SP-Fawn Drive Q22 10–11 297 67 91

UTSA at Regency Q23 6–7 309 76 98

Lockhill S (at 1604) Q24 1–3 301 61 86

Landrum Q25 1–4 290 55 98

O. Martin Q26 4–8 318 32 87

Wiemers Q27 1–10 330 2 122

Lehmberg Q28 1–10 336 Unknown 109

Walthour Q29 12 379 98 130

Shavano Park (no. 6) Q30 11–12 293 83 148

34th St Sta Q31 1–11 208 155 380

Lockhill-Selma Q32 3–5 258 161 195

Fohn Farms Q33 2–7 285 74 158

Bendele, Ken Q34 5–7 277 157 172

SanPedro Springs 4D Q35 2–11 201 NA NA

Medina JHS Q36 1–7 231 106 414

Yancy #3 Q37 2–10 320 355 450
Table 2 69

Table 2. Summary of water-level measurements obtained from monitoring and observation wells used in the local-scale model, San 

Antonio region, Texas.—Continued

Well 

name

Well 

identifier

Date of measurement Number

of days

Water-level altitude

(meters)

Start date End date Mean Minimum Maximum

6827307 W1 2/12/2001 7/23/2001 2 245.7 245.7 245.7

6827401 W2 7/24/2001 10/29/2001 2 241.2 239.2 243.3

6827517 W3 2/12/2001 10/29/2001 3 238.0 236.2 240.8

6827609 W4 2/12/2001 10/29/2001 3 232.7 231.3 234.0

6827610 W5 2/12/2001 7/23/2001 2 223.5 223.0 224.0

6827611 W6 2/12/2001 10/29/2001 3 232.7 229.7 235.8

6827612 W7 2/12/2001 10/29/2001 3 230.6 228.7 232.2

6828113 W8 2/12/2001 10/29/2001 3 243.1 240.8 245.0

6828210 W9 2/12/2001 10/29/2001 3 240.0 236.5 245.6

6828211 W10 2/12/2001 10/29/2001 3 227.1 225.6 230.0

6828313 W11 2/12/2001 11/1/2001 2 226.0 225.6 226.5

6828314 W12 2/12/2001 10/29/2001 3 220.7 219.2 223.1

6828315 W13 2/12/2001 10/29/2001 3 223.9 219.2 227.2

6828406 W14 2/12/2001 10/29/2001 3 223.1 220.3 224.8

6828407 W15 7/23/2001 10/29/2001 2 224.3 219.9 228.7

6828512 W16 2/12/2001 10/29/2001 3 232.8 230.7 233.9

6828515 W17 2/12/2001 10/29/2001 2 218.5 217.3 219.7

6828516 W18 2/12/2001 10/29/2001 3 226.9 226.8 227.1

6828518 W19 2/12/2001 7/23/2001 2 218.1 216.6 219.6

6828519 W20 7/23/2001 10/29/2001 2 218.3 217.5 219.2

6828608 W21 2/12/2001 11/1/2001 3 215.7 209.5 221.3

6828609 W22 2/12/2001 11/1/2001 3 218.5 215.8 220.6

6828909 W23 2/15/2001 10/30/2001 3 205.4 200.9 208.6

6828920 W24 2/12/2001 10/31/2001 3 208.0 203.4 210.6

6828921 W25 2/15/2001 10/30/2001 3 205.9 201.4 209.1

6829103 W26 2/12/2001 10/31/2001 3 214.2 213.4 215.1

6829112 W27 2/12/2001 10/29/2001 3 220.0 217.0 222.2

6829113 W28 2/12/2001 10/29/2001 3 220.3 217.9 222.2

6829418 W29 2/12/2001 10/29/2001 3 215.9 215.1 217.1

6835106 W30 2/15/2001 10/29/2001 3 205.7 194.4 215.3

6835202 W31 7/26/2001 10/29/2001 2 210.5 207.9 213.1

6836103 W32 2/16/2001 10/29/2001 2 202.9 199.7 206.0

6836130 W33 7/26/2001 10/29/2001 2 201.3 199.9 202.7

6836206 W34 2/15/2001 10/29/2001 3 206.1 202.1 209.0

6836502 W35 2/15/2001 7/26/2001 2 205.7 202.3 209.1

6836901 W36 2/14/2001 10/31/2001 3 205.8 203.0 208.0

6837103 W37 2/15/2001 10/30/2001 3 205.1 200.6 208.3

6837203 W38 2/12/2001 10/31/2001 3 204.6 200.7 207.4

6837304 W39 2/13/2001 11/1/2001 3 202.1 200.4 205.1

6837524 W40 2/13/2001 11/1/2001 3 205.1 200.8 208.0

6843402 W41 2/14/2001 10/31/2001 3 206.8 202.5 209.8

6843606 W42 2/14/2001 10/31/2001 3 209.2 203.8 212.9

Table 2
70 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 2. Summary of water-level measurements obtained from monitoring and observation wells used in the local-scale model, San 

Antonio region, Texas.—Continued

Well 

name

Well 

identifier

Date of measurement Number

of days

Water-level altitude

(meters)

Start date End date Mean Minimum Maximum

68285AA W43 2/12/2001 11/1/2001 3 184.8 182.6 186.4

68299BB W44 2/12/2001 10/31/2001 3 203.5 199.8 206.0

68299CC W45 2/12/2001 10/31/2001 2 204.0 201.8 206.2

68377AA W46 2/13/2001 11/1/2001 3 197.1 193.4 199.9

68431AA W47 2/14/2001 10/31/2001 3 209.8 205.6 212.8

68437AA W48 2/14/2001 10/31/2001 3 203.8 198.9 208.5

6826802 W49 2/12/2001 10/31/2001 3 236.7 230.9 242.7

6833604 W50 2/12/2001 10/30/2001 3 215.6 211.8 218.5

6834506 W51 2/15/2001 10/29/2001 3 212.6 208.7 215.6

6841301 W52 2/12/2001 10/30/2001 3 213.4 209.8 216.1

6842106 W53 2/13/2001 10/29/2001 3 213.5 209.1 216.7

6842112 W54 2/12/2001 10/29/2001 3 209.9 208.6 210.6

6842502 W55 2/12/2001 10/30/2001 3 211.5 207.4 214.5

6939504 W56 2/14/2001 11/2/2001 3 262.7 261.8 263.3

6939801 W57 2/14/2001 11/2/2001 3 230.0 227.3 232.0

6939901 W58 2/14/2001 11/2/2001 3 228.1 225.2 230.3

6940101 W59 2/14/2001 11/2/2001 3 264.9 263.9 265.8

6940102 W60 2/14/2001 11/2/2001 3 253.1 252.2 254.0

6940404 W61 2/14/2001 11/2/2001 2 236.9 236.1 237.8

6940901 W62 2/14/2001 10/30/2001 3 218.3 214.8 220.9

6947301 W63 2/12/2001 11/2/2001 3 219.6 215.6 223.3

6947306 W64 2/12/2001 10/31/2001 3 218.9 215.4 221.5

6948102 W65 2/12/2001 11/1/2001 3 218.7 215.2 221.1

6948303 W66 2/13/2001 11/2/2001 3 213.9 210.3 217.9

68339AA W67 2/12/2001 10/30/2001 3 214.6 210.8 217.2

68415AA W68 2/13/2001 10/29/2001 3 214.3 210.3 217.2

68416AA W69 2/14/2001 10/29/2001 3 213.0 208.9 216.0

68422AA W70 2/12/2001 10/30/2001 3 211.5 207.4 214.4

69396AA W71 2/14/2001 11/2/2001 3 241.9 241.2 243.0

69489AA W72 2/13/2001 11/2/2001 3 223.5 220.4 226.0

YMCA W73 5/10/2007 1/31/2010 662 218.5 206.7 238.8

Graham W74 6/14/2007 2/9/2010 873 217.8 204.9 235.8

Lockhill W75 5/4/2007 2/9/2010 937 228.8 217.5 239.2

Abe Lincoln W76 6/20/2007 5/12/2009 673 214.8 203.7 226.3

Propane Depot W77 5/14/2007 1/15/2010 887 209.6 197.6 224.1

Salazar W78 5/15/2007 6/8/2007 25 213.2 212.2 214.1

Zarzamora_OVB W79 10/17/2008 2/9/2010 762 212.7 209.3 219.6

Timberhill_IED WQ1 10/17/2008 2/3/2010 462 204.7 198.0 211.1

Timberhill_DED WQ2 10/17/2008 2/3/2010 462 204.9 198.2 210.0

Zarzamora_SED WQ3 10/17/2008 2/9/2010 619 206.3 197.5 215.0

Zarzamora_IED WQ4 10/17/2008 2/9/2010 552 207.6 198.2 215.5

Zarzamora_DED WQ5 9/12/2007 11/30/2009 627 207.8 197.7 219.6
Table 3 71

Table 3

Table 3. Hydraulic properties for the Edwards aquifer, San Antonio region, Texas.

[m-1, per meter; m/d, meters per day; m2/d, meters squared per day; NA, no reported value]

Source

Horizontal hydraulic 

conductivity

(m/d)

Transmissivity

(m2

/d)

Specific yield

(dimensionless)

Storativity

(units vary)

Porosity

(percent)

Garza (1968) Freshwater confined zone: 

92,900–185,800

Maclay and Land (1988)

(based on numerical modeling results)

As much as 13,500 Freshwater confined zone: 

generally 39,950–204,380 

but may be as much as 

900,000 

Recharge zone: generally 

<39,950 

Freshwater/saline-water 

transition zone: as low 

as 12

NA NA NA

Hovorka and others (1996) NA NA NA NA Varies vertically 

from lows of 

4–12 percent to 

highs of 20–42 

percent. Mean 

for entire aquifer 

of 18 percent

Hovorka and others (1998) 3.0x10-4-3.0x104

Recharge zone: 

Mean of 0.085

Freshwater confined 

zone:

Mean of 10.4

Aquifer as a whole:

Mean of 3.4

Aquifer matrix: 

Mean of 0.03

9.3x10-3-9.29x105 NA NA NA

Kuniansky and others (2001)

(based on numerical modeling results)

NA NA NA NA Used 1–3 percent to match 

estimated 

traveltimes 

derived from 

geochemical 

mixing models

Lindgren and others (2004)

(based on numerical modeling results)

.3–2,239 

Conduit cells: 

305–91,440

NA 0.005–.15 Specific storage:

1.6x10-6-1.6x10-5 m-1

NA

Lindgren (2006) (based 

on numerical modeling 

results)

.9–15,240 NA NA NA NA

Maclay and Rettman (1973);

Klemt and others (1979);

Maclay and Small (1984);

Maclay and Land (1988)

NA NA .025–.20 NA NA

Sieh (1975); 

Klemt and others (1979);

Maclay and Small (1984);

Hovorka and others (1993)

NA NA NA Storage coefficient 

(dimensionless):

1x10-5-8x10-4

NA
Table 4. Estimated recharge rates, by recharge subzone, in the local-scale model area during 2001, San Antonio region, Texas. [Monthly recharge rates have been estimated by the U.S. Geological Survey for the San Antonio segment of the Edwards aquifer since 1934. Streambed recharge is 85 percent of recharge occurs in the interstream areas and is 15 percent of the total recharge. The local-scale model area includes 80 percent of the diffuse area of the area between Sabinal and and 69 percent of the diffuse area of the area between Medina River and Cibolo-Dry Comal Creek recharge subzone. The local-scale model includes the whole area (100 percent) Medina River recharge subzone. Annual totals are in cubic meters per year]

Month-Year

Estimated recharge rate 

(cubic meters per month)

Recharge subzone

Area between Sabinal and Medina River Medina River Area between Medina River an

Streambed Subzone diffuse Subzone total

Localscale

model 

area

diffuse

Localscale 

model 

area

total

Streambed Subzone diffuse Subzone total Streambed Subzone diffuse Subzon

total

January-01 18,742,214 3,307,450 22,049,663 2,645,960 21,388,173 6,186,729 1,091,776 7,278,505 10,473,645 1,848,162 12,321,

February-01 12,457,528 2,198,387 14,655,916 1,758,710 14,216,238 6,711,028 1,184,299 7,895,327 13,722,768 2,421,665 16,144,

March-01 22,436,299 3,959,511 26,395,810 3,167,609 25,603,908 7,445,047 1,313,832 8,758,879 16,261,907 2,869,615 19,131,

April-01 9,702,746 1,712,249 11,414,995 1,369,799 11,072,545 9,122,804 1,609,907 10,732,710 10,338,079 1,824,367 12,162,

May-01 22,833,533 4,029,318 26,862,851 3,223,455 26,056,987 9,619,839 1,697,619 11,317,458 8,581,385 1,514,362 10,095,

June-01 5,297,442 934,843 6,232,285 747,874 6,045,316 7,549,907 1,332,336 8,882,243 1,756,147 309,908 2,066,

July-01 2,985,484 526,850 3,512,334 421,480 3,406,964 6,870,415 1,212,426 8,082,841 1,468,692 259,181 1,727,

August-01 4,518,841 797,605 5,316,446 638,084 5,156,925 6,085,015 1,073,826 7,158,841 0 0 

September-01 7,134,168 1,258,835 8,393,003 1,007,068 8,141,236 8,650,318 1,526,636 10,176,953 7,934,647 1,400,232 9,334,

October-01 2,987,888 527,406 3,515,294 421,925 3,409,813 6,711,028 1,184,299 7,895,327 8,638,277 1,524,402 10,162,

November-01 17,877,007 3,154,766 21,031,773 2,523,813 20,400,819 9,489,196 1,674,673 11,163,869 13,654,743 2,409,661 16,064,

December-01 3,193,273 563,519 3,756,792 450,815 3,644,089 9,880,940 1,743,695 11,624,636 13,625,467 2,404,494 16,029,

Annual 130,166,424 22,970,739 153,137,163 18,376,591 148,543,015 94,322,265 16,645,323 110,967,589 106,455,757 18,786,049 125,241,
Table 5 73

Table 5

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00269-005 MUN 178 54 17,386 6,346,037

BE00269-006 MUN 170 52 17,386 6,346,037

BE00269-007 MUN 164 50 17,386 6,346,037

BE00269-008 MUN 162 49 17,386 6,346,037

BE00269-094 MUN 169 51 15,182 5,541,480

BE00269-095 MUN 170 52 15,182 5,541,480

BE00269-096 MUN 178 54 15,182 5,541,480

BE00269-097 MUN 173 53 15,182 5,541,480

BE00269-098 MUN 171 52 15,182 5,541,480

BE00269-099 MUN 161 49 15,182 5,541,480

BE00269-072 MUN 161 49 13,671 4,989,898

BE00149-001 MUN 137 42 13,058 4,766,276

BE00269-080 MUN 119 36 12,932 4,720,132

BE00269-045 MUN 106 32 10,261 3,745,371

BE00269-046 MUN 110 34 10,261 3,745,371

BE00269-047 MUN 107 33 10,261 3,745,371

BE00269-048 MUN 99 30 10,261 3,745,371

BE00269-101 MUN 106 32 10,261 3,745,371

BE00269-903 MUN 96 29 10,261 3,745,371

BE00269-902 MUN 116 35 8,894 3,246,135

BE00269-032 MUN 29 9 8,864 3,235,251

BE00269-049 MUN 50 15 8,512 3,106,976

BE00269-050 MUN 49 15 8,512 3,106,976

BE00269-051 MUN 58 18 8,512 3,106,976

BE00149-002 MUN 99 30 6,811 2,485,876

BE00269-052 MUN -88 -27 6,785 2,476,485

BE00269-053 MUN -44 -14 6,785 2,476,485

BE00269-054 MUN -43 -13 6,785 2,476,485

BE00269-055 MUN -45 -14 6,785 2,476,485

BE00269-056 MUN -43 -13 6,785 2,476,485

BE00269-057 MUN -46 -14 6,785 2,476,485

BE00269-027 MUN -96 -29 6,668 2,433,921

BE00269-028 MUN -3 -1 6,668 2,433,921

BE00227-024 MUN 133 41 6,093 2,224,056

BE00058-003 MUN 65 20 5,419 1,977,830

BE00239-001 MUN -130 -40 5,243 1,913,827

BE00269-089 MUN 94 29 5,227 1,907,799

BE00227-017 MUN 96 29 5,154 1,881,388

BE00269-020 MUN 48 15 5,084 1,855,712

BE00269-021 MUN 42 13 5,084 1,855,712
74 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00269-022 MUN 47 14 5,084 1,855,712

BE00269-024 MUN 56 17 5,084 1,855,712

BE00269-025 MUN 48 15 5,084 1,855,712

BE00269-102 MUN 44 13 5,084 1,855,712

BE00269-014 MUN -97 -30 5,077 1,852,991

BE00269-015 MUN -80 -25 5,077 1,852,991

BE00269-016 MUN 30 9 4,939 1,802,847

BE00269-087 MUN 189 58 4,651 1,697,506

BE00269-085 MUN 79 24 4,569 1,667,575

BE00151-006 MUN -240 -73 4,429 1,616,466

BE00227-004 MUN -79 -24 4,309 1,572,900

BE00269-084 MUN 64 19 3,333 1,216,669

BE00269-074 MUN 159 48 3,295 1,202,675

BE00227-020 MUN 87 26 3,138 1,145,315

BE00269-001 MUN -8 -2 2,554 932,035

BE00269-002 MUN -13 -4 2,554 932,035

BE00269-003 MUN -19 -6 2,554 932,035

BE00269-004 MUN -7 -2 2,554 932,035

BE00026-002 MUN 126 38 2,443 891,807

BE00227-023 MUN 86 26 2,339 853,647

BE00173-002 MUN -359 -110 2,301 839,949

BE00269-039 MUN -47 -14 2,131 777,683

BE00269-040 MUN -215 -65 2,131 777,683

BE00269-041 MUN -214 -65 2,131 777,683

BE00269-044 MUN 60 18 2,115 771,982

BE00109G-001 MUN -37 -11 2,053 749,355

BE00012-002 MUN -9 -3 2,001 730,437

ME00318-001 MUN -81 -25 1,946 710,309

BE00227-003 MUN -83 -25 1,892 690,639

BE00173-001 MUN -326 -99 1,740 635,237

ME00411-002 MUN -436 -133 1,731 631,863

BE00276-007 MUN 184 56 1,724 629,096

BE00151-003 MUN -133 -41 1,650 602,280

BE00269-093 MUN 135 41 1,604 585,400

BE00269-033 MUN -130 -40 1,563 570,629

BE00269-034 MUN -132 -40 1,563 570,629

BE00026-001 MUN 136 42 1,556 568,103

BE00227-032 MUN -10 -3 1,506 549,682

ME00302-002 MUN -373 -114 1,474 538,037

BE00227-019 MUN 157 48 1,434 523,383
Table 5 75

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00151-001 MUN -198 -60 1,389 506,903

BE00151-005 MUN -110 -34 1,296 472,958

BE00269-086 MUN 180 55 1,191 434,580

BE00269-901 MUN 42 13 1,191 434,580

ME00537-003 MUN 9 3 1,171 427,521

BE00151-008 MUN -120 -37 1,136 414,693

BE00109G-003 MUN -105 -32 1,101 401,804

BE00227-021 MUN 84 26 1,101 401,716

BE00269-019 MUN 137 42 1,089 397,653

BE00269-018 MUN 139 42 1,056 385,602

BE00227-036 MUN 178 54 1,021 372,682

BE00269-073 MUN 144 44 976 356,060

BE00276-008 MUN 186 57 941 343,346

BE00058-001 MUN 134 41 938 342,238

ME00318-002 MUN -88 -27 795 290,333

BE00058-005 MUN 119 36 735 268,371

BE00151-009 MUN -120 -37 727 265,231

ME00322-002 MUN -127 -39 668 243,923

ME00537-002 MUN 39 12 658 240,174

BE00021-001 MUN -292 -89 635 231,948

BE00227-029 MUN 165 50 603 219,929

BE00151-002 MUN -194 -59 502 183,281

ME00537-001 MUN 18 5 483 176,258

BE00151-007 MUN -225 -69 460 168,081

ME00411-001 MUN -463 -141 455 166,217

ME00576-001 MUN -435 -133 438 159,943

ME00576-002 MUN -392 -120 436 158,964

BE00227-038 MUN 149 45 428 156,289

BE00227-039 MUN 103 31 366 133,426

ME00302-004 MUN -360 -110 320 116,745

BE00205-002 MUN 191 58 301 109,845

BE00229-001 MUN 169 52 292 106,725

BE00151-004 MUN -150 -46 290 105,890

BE00227-008 MUN -94 -29 290 105,806

ME00406-001 MUN -206 -63 284 103,799

BE00052-002 MUN 58 18 263 96,047

ME00406-002 MUN -205 -63 238 87,024

BE00227-042 MUN 60 18 211 77,177

BE00052-003 MUN 57 17 192 70,166

ME00527AL1-002 MUN -114 -35 131 47,805
76 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

ME00564-002 MUN -122 -37 131 47,805

ME00330-001 MUN -81 -25 130 47,414

BE00052-001 MUN 59 18 127 46,416

BE00227-030 MUN 165 50 120 43,792

ME00527AL1-001 MUN -114 -35 117 42,843

ME00564-001 MUN -124 -38 117 42,843

BE00058-006 MUN 114 35 112 40,939

BE00227-031 MUN 54 16 109 39,670

ME00311-001 MUN -136 -41 108 39,550

ME00484-001 MUN 51 16 100 36,415

ME00483-001 MUN 85 26 99 36,162

ME00379-001 MUN 52 16 99 36,030

ME00380-001 MUN -14 -4 97 35,238

BE00288-001 MUN 118 36 80 29,348

BE00227-045 MUN 47 14 80 29,277

BE00270-001 MUN 73 22 73 26,660

BE00227-917 MUN 161 49 72 26,343

BE00276-006 MUN 211 64 60 22,052

BE00058-002 MUN 82 25 60 21,861

BE00227-018 MUN 109 33 54 19,752

BE00292-001 MUN 77 23 44 15,937

ME00302-003 MUN -360 -110 42 15,352

BE00227-033 MUN -8 -3 35 12,731

BE00236-001 MUN 105 32 27 9,842

ME00311-002 MUN -134 -41 25 9,109

BE00186-001 MUN 210 64 24 8,652

BE00013-002 MUN 181 55 20 7,404

BE00270-004 MUN -23 -7 20 7,349

ME00373-001 MUN 41 13 20 7,256

BE00227-022 MUN 43 13 19 7,102

BE00227-907 MUN 180 55 16 5,997

BE00004-001 MUN -66 -20 16 5,961

ME00566-001 MUN 51 15 8 2,818

BE00013-001 MUN 180 55 6 2,106

ME00456-001 MUN 98 30 5 1,889

BE00229-002 MUN 127 39 5 1,765

BE00270-002 MUN 71 22 4 1,585

BE00058-004 MUN 85 26 3 1,096

BE00091-001 MUN 199 61 3 1,016

BE00099A-001 MUN 183 56 1 310
Table 5 77

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00010-002 MUN -26 -8 1 214

ME00322-001 MUN -127 -39 0 155

BE00270-008 MUN 171 52 0.0 14

BE00010-001 MUN -28 -9 0.00 0

Subtotal 546,808 199,585,063

BE00043-003 IND -41 -13 8,257 3,013,644

BE00079-001 IND 197 60 7,337 2,678,109

BE00079-002 IND 201 61 5,513 2,012,249

BE00043-002 IND -56 -17 3,989 1,456,030

BE00053L1-001 IND 27 8 2,886 1,053,253

BE00043-001 IND -94 -29 1,862 679,642

BE00089-002 IND 74 23 1,664 607,222

BE00214-002 IND 183 56 1,575 574,895

BE00178-001 IND -8 -2 1,045 381,279

BE00214-001 IND 190 58 818 298,402

BE00234-001 IND -60 -18 782 285,608

BE00195AA-001 IND 27 8 736 268,766

BE00206-001 IND -7 -2 491 179,162

BE00119-003 IND -54 -16 464 169,515

BE00089-001 IND 88 27 443 161,751

BE00130-002 IND -6 -2 418 152,732

BE00092-001 IND -32 -10 337 122,856

BE00076-002 IND 46 14 302 110,163

BE00168-001 IND -60 -18 291 106,331

BE00123-001 IND 88 27 275 100,444

BE00132-001 IND -250 -76 272 99,199

BE00043-004 IND -62 -19 245 89,490

ME00471-001 IND 109 33 234 85,488

BE00078-001 IND -10 -3 226 82,662

ME00346-001 IND -74 -23 222 80,936

BE00178-005 IND 36 11 218 79,507

BE00111-001 IND -58 -18 197 72,086

BE00123-002 IND 88 27 192 69,920

BE00191-001 IND 61 19 184 67,061

BE00164-002 IND 171 52 173 63,016

BE00077-001 IND 125 38 169 61,563

BE00076-001 IND 43 13 144 52,417

BE00164-001 IND 171 52 134 48,997

BE00143-001 IND 186 57 94 34,304

BE00152-001 IND 208 63 90 32,748
78 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00089-003 IND 91 28 87 31,602

ME00597-001 IND -46 -14 70 25,641

BE00038-001 IND -53 -16 69 25,027

BE00266-001 IND 156 47 66 24,072

BE00016-001 IND -55 -17 65 23,898

BE00119-001 IND -54 -16 58 21,275

ME00493AA-001 IND 190 58 56 20,261

BE00174-001 IND -273 -83 54 19,825

BE00208-002 IND 4 1 49 17,801

BE00062-001 IND -56 -17 44 15,952

BE00113A-001 IND 180 55 41 15,051

BE00206-002 IND -35 -11 39 14,367

BE00199-001 IND 212 65 37 13,400

BE00095-001 IND 36 11 34 12,551

BE00017-002 IND 205 62 33 12,064

BE00017-001 IND 205 62 25 8,994

BE00141-001 IND 15 5 19 6,808

BE00070-001 IND -12 -4 9 3,396

BE00238-001 IND -25 -8 4 1,429

BE00111-002 IND -55 -17 4 1,382

BE00220-001 IND 79 24 4 1,338

BE00084-001 IND 92 28 4 1,317

BE00244-001 IND 30 9 3 1,152

BE00208-003 IND 4 1 2 851

BE00282-001 IND 196 60 2 815

BE00208-001 IND 4 1 2 792

BE00175-001 IND 66 20 0 97

Subtotal 43,158 15,752,608

BE00314-001 IRR -269 -82 3,592 1,311,100

ME00320-001 IRR -141 -43 3,378 1,233,089

BE00113-001 IRR -326 -99 3,340 1,218,955

ME00343-001 IRR 185 56 2,818 1,028,532

ME00358-001 IRR 74 22 2,745 1,001,813

ME00349-003 IRR 235 72 2,739 999,575

ME00391-001 IRR 153 47 2,668 973,773

ME00515-001 IRR -40 -12 2,432 887,810

ME00325-001 IRR -65 -20 2,413 880,656

ME00325-002 IRR -75 -23 1,963 716,672

BE00056-001 IRR -286 -87 1,953 712,941

ME00415-001 IRR -124 -38 1,946 710,457
Table 5 79

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

ME00414-001 IRR 36 11 1,878 685,615

BE00128-001 IRR 182 55 1,837 670,603

ME00323-001 IRR -57 -17 1,819 664,028

ME00507-001 IRR -116 -35 1,654 603,640

BE00055-001 IRR -286 -87 1,647 601,156

ME00342-001 IRR 47 14 1,613 588,874

BE00224-001 IRR -318 -97 1,566 571,577

ME00402-001 IRR -39 -12 1,450 529,116

ME00352-001 IRR 2 1 1,448 528,396

ME00534-001 IRR -183 -56 1,429 521,664

ME00371-001 IRR 48 15 1,427 520,796

ME00455-001 IRR 32 10 1,392 507,984

ME00409-001 IRR 74 23 1,354 494,339

ME00408-001 IRR 78 24 1,327 484,402

ME00353-001 IRR -112 -34 1,324 483,175

ME00521-001 IRR 78 24 1,279 467,013

BE00150-002 IRR 30 9 1,243 453,723

ME00467-001 IRR 61 19 1,242 453,351

BE00225-001 IRR -46 -14 1,218 444,656

ME00599-001 IRR 26 8 1,176 429,101

BE00209-001 IRR -329 -100 1,147 418,573

BE00207-004 IRR -29 -9 1,134 414,091

ME00443-001 IRR 44 13 1,100 401,418

ME00514-001 IRR 18 6 1,092 398,487

BE00207-003 IRR -23 -7 1,075 392,524

ME00321-001 IRR -137 -42 1,039 379,210

ME00448-001 IRR 141 43 1,027 374,695

ME00347-001 IRR 5 2 998 364,410

ME00348-001 IRR 27 8 969 353,837

ME00344-001 IRR 24 7 953 347,776

BE00041-001 IRR -275 -84 942 343,851

ME00301-001 IRR 91 28 940 343,145

ME00538-001 IRR 129 39 930 339,578

ME00368-001 IRR 91 28 919 335,355

BE00009-001 IRR -63 -19 912 332,992

BE00134-001 IRR 69 21 887 323,906

ME00526-001 IRR 90 27 883 322,224

ME00535-001 IRR 41 12 866 315,979

AT00903-001 IRR -386 -118 860 313,749

ME00602-001 IRR 36 11 845 308,283
80 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00207-005 IRR -29 -9 842 307,355

ME00447-001 IRR 37 11 827 301,918

ME00533-001 IRR 57 17 808 294,800

ME00357-001 IRR -93 -28 785 286,547

ME00404-001 IRR 137 42 765 279,152

ME00432-001 IRR 80 24 750 273,767

BE00061-003 IRR -48 -14 728 265,800

ME00310-001 IRR 70 21 728 265,800

ME00396-001 IRR -328 -100 728 265,800

ME00529-001 IRR 93 28 728 265,800

BE00039-001 IRR -282 -86 724 264,367

BE00129-001 IRR -299 -91 709 258,641

BE00030-001 IRR -284 -86 708 258,522

BE00061-002 IRR 40 12 701 255,864

ME00334-001 IRR -433 -132 681 248,411

ME00487-001 IRR -108 -33 681 248,411

ME00519-001 IRR 180 55 681 248,411

ME00335-001 IRR -41 -13 661 241,111

ME00512-001 IRR 38 12 646 235,742

ME00397-001 IRR 37 11 640 233,507

BE00061-001 IRR 40 12 619 226,054

ME00604-001 IRR 38 12 619 226,054

ME00544-001 IRR -122 -37 611 223,190

ME00303-001 IRR -44 -14 606 221,086

ME00324-001 IRR 52 16 606 221,086

ME00422-001 IRR -111 -34 601 219,546

ME00606-001 IRR 55 17 595 217,059

ME00431-001 IRR 163 50 585 213,634

BE00042-001 IRR -333 -102 575 209,957

BE00155-001 IRR -294 -90 571 208,589

ME00455A-001 IRR 32 10 570 207,903

ME00354-003 IRR 181 55 567 206,934

BE00161-001 IRR -334 -102 565 206,181

ME00309-001 IRR 45 14 565 206,181

BE00073-002 IRR -42 -13 563 205,416

BE00275-001 IRR -46 -14 553 201,755

BE00048-001 IRR -318 -97 519 189,391

ME00556-001 IRR 37 11 509 185,720

ME00516-001 IRR 36 11 504 183,824

ME00362-001 IRR -98 -30 483 176,372
Table 5 81

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

BE00032-001 IRR -310 -94 482 176,042

BE00011-001 IRR -281 -86 479 174,790

ME00557-001 IRR 55 17 463 168,910

ME00525-001 IRR 80 24 456 166,316

ME00562-001 IRR -138 -42 453 165,320

ME00574-001 IRR -62 -19 451 164,555

BE00211-001 IRR -328 -100 441 161,043

BE00067-002 IRR -241 -73 440 160,424

BE00082-001 IRR -27 -8 430 157,089

ME00363-001 IRR 39 12 424 154,860

ME00369-001 IRR -302 -92 409 149,303

ME00367-001 IRR 42 13 402 146,563

ME00565-001 IRR 19 6 401 146,528

ME00539-001 IRR 116 35 391 142,588

BE00162-001 IRR 123 37 383 139,814

BE00201-001 IRR 105 32 359 130,892

ME00336-001 IRR -55 -17 344 125,706

BE00233-001 IRR -83 -25 340 124,278

ME00442-001 IRR -274 -84 315 115,139

ME00407-001 IRR -78 -24 309 112,891

BE00046-004 IRR -50 -15 308 112,356

ME00583-001 IRR -36 -11 304 111,040

ME00555-001 IRR 52 16 301 109,959

BE00065-001 IRR 103 31 301 109,697

ME00388-001 IRR -81 -25 299 109,301

ME00319-001 IRR 164 50 289 105,575

BE00240-001 IRR -89 -27 286 104,305

ME00350-001 IRR -94 -29 283 103,406

BE00060-001 IRR -39 -12 282 102,924

ME00312-001 IRR 50 15 275 100,511

BE00101-001 IRR -173 -53 275 100,358

ME00300-001 IRR -83 -25 267 97,526

BE00139-001 IRR -315 -96 263 95,951

ME00364-001 IRR 80 24 259 94,620

BE00064-001 IRR -233 -71 259 94,434

ME00354-001 IRR 175 53 252 92,131

ME00575-001 IRR -68 -21 249 90,837

BE00067-003 IRR -241 -73 242 88,511

ME00538-002 IRR 147 45 237 86,447

BE00067-001 IRR -241 -73 222 80,898
82 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

ME00389-001 IRR 66 20 213 77,629

BE00197-001 IRR 33 10 202 73,810

ME00476-001 IRR -503 -153 191 69,555

BE00046-010 IRR -64 -19 184 67,071

ME00365-001 IRR -205 -63 177 64,587

ME00518-001 IRR -93 -28 172 62,600

ME00378-001 IRR -41 -13 166 60,712

BE00060-002 IRR -45 -14 164 59,795

ME00316-001 IRR 152 46 163 59,619

BE00312-001 IRR -236 -72 162 59,112

BE00040-001 IRR 33 10 157 57,135

ME00568-001 IRR 52 16 151 54,978

BE00192-001 IRR -335 -102 149 54,561

BE00071A-001 IRR 90 27 148 54,099

ME00349-002 IRR 235 72 143 52,340

ME00415-002 IRR -128 -39 136 49,682

ME00570-001 IRR -116 -35 128 46,768

BE00181-001 IRR 124 38 125 45,542

ME00384-001 IRR 119 36 122 44,551

BE00267-001 IRR -331 -101 118 42,975

ME00339-001 IRR 34 10 106 38,628

BE00150-001 IRR 36 11 98 35,647

BE00207-001 IRR -15 -5 85 30,897

ME00404-002 IRR -112 -34 83 30,189

ME00561-001 IRR 39 12 75 27,325

BE00315-001 IRR -36 -11 68 24,841

BE00182-001 IRR 121 37 65 23,719

ME00469-001 IRR 89 27 65 23,599

BE00207-002 IRR -16 -5 64 23,452

BE00022-001 IRR -265 -81 61 22,362

BE00046-007 IRR -66 -20 61 22,357

ME00354-002 IRR 178 54 55 20,124

ME00579-001 IRR -106 -32 53 19,483

ME00523-001 IRR -28 -9 48 17,438

ME00382-001 IRR 55 17 48 17,351

BE00046-008 IRR -66 -20 41 14,905

BE00197-002 IRR -33 -10 40 14,619

BE00024-001 IRR -332 -101 35 12,769

ME00308-001 IRR 5 1 30 10,982

ME00540-001 IRR -108 -33 27 9,754
Table 5 83

Table 5. Mean daily and mean annual groundwater-withdrawal rates from municipal, industrial, irrigation, and livestock wells in the 

local-scale study area during 2001, San Antonio region, Texas.—Continued

[Locations of wells are shown in figure 14; MUN, municipal well; IND, industrial well; IRR, irrigation well; STK, livestock well. Withdrawal rates provided by 

San Antonio Water System (2008), Bexar Metropolitan Water District, and Edwards Aquifer Authority (2009)]

Well 

number

Water use

type

Altitude of top of 

open interval

(meters)

Altitude of bottom 

of open interval

(meters)

Withdrawal rate

(cubic meters per day)

Withdrawal rate

(cubic meters per year)

ME00573-001 IRR -122 -37 26 9,566

BE00187-001 IRR 103 31 23 8,334

BE00020-001 IRR -324 -99 21 7,627

ME00572-001 IRR 23 7 18 6,716

BE00035-001 IRR -241 -73 13 4,898

BE00053-001 IRR 7 2 12 4,227

ME00315-001 IRR -91 -28 9 3,289

BE00247-001 IRR 34 10 8 2,931

BE00115-001 IRR 133 40 7 2,484

BE00097A-001 IRR -61 -18 6 2,142

BE00034-001 IRR 120 37 4 1,555

BE00093-001 IRR -36 -11 3 1,238

BE00156-001 IRR 119 36 3 1,172

ME00510-001 IRR 39 12 2 646

BE00118-001 IRR -293 -89 1 362.7

BE00274-001 IRR -260 -79 1 248.4

BE00198-001 IRR 196 60 0 165.1

BE00172-001 IRR 124 38 0.1 36.59

BE00046-006 IRR -66 -20 0.0 7.44

BE00046-011 IRR -64 -19 0.0 7.44

Subtotal 124,896.9 45,587,377

BE00027-001 STK 71 22 7,763 2,833,675

BE00027-002 STK 71 22 940 343,190

Subtotal 8,704 3,176,865

Total 723,567 264,101,914
84 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 6

Table 6. Measured and simulated water-level altitudes and springflows and the differences between measured and simulated waterlevel altitudes and springflows (residuals) for the local-scale model, steady-state simulation, San Antonio region, Texas.—Continued

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 is 

upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is Glen 

Rose (Trinity Group); Measured value is the mean hydraulic head or springflow measured during 2001. Difference or residual is the measured water level or 

springflow minus the simulated water level or springflow. m, meters; m3/s, cubic meters per second; RMS, root mean square]

Well 

name

Well 

identifier

Hydrogeologic unit

number(s)

Water-level altitude 

(m)

Difference

(m)

Measured

value

Simulated 

value

Algebraic 

difference

Absolute value 

of difference

6827307 W1 11 245.7 241.8 3.9 3.9

6827401 W2 4–10 241.2 235.0 6.3 6.3

6827517 W3 7–8 238.0 244.3 -6.2 6.2

6827609 W4 8–10 232.7 232.9 -.2 .2

6827610 W5 4–6 223.5 215.0 8.5 8.5

6827611 W6 4 232.7 229.6 3.1 3.1

6827612 W7 3–4 230.6 228.7 1.8 1.8

6828113 W8 7–8 243.1 241.9 1.2 1.2

6828210 W9 2–3 240.0 240.9 -.9 .9

6828211 W10 10–12 227.1 227.7 -.6 .6

6828313 W11 12 226.0 226.5 -.4 .4

6828314 W12 7–8 220.7 219.3 1.3 1.3

6828315 W13 12 223.9 226.1 -2.2 2.2

6828406 W14 6–8 223.1 219.3 3.8 3.8

6828407 W15 7–8 224.3 227.3 -3.0 3.0

6828512 W16 6–12 232.8 226.4 6.4 6.4

6828515 W17 6 218.5 211.0 7.5 7.5

6828516 W18 6–7 226.9 215.5 11.4 11.4

6828518 W19 6 218.1 216.3 1.8 1.8

6828519 W20 6–7 218.3 213.1 5.2 5.2

6828608 W21 3–11 215.7 213.7 2.0 2.0

6828609 W22 5–7 218.5 222.1 -3.7 3.7

6828909 W23 3–11 205.4 206.7 -1.3 1.3

6828920 W24 1 208.0 206.2 1.8 1.8

6828921 W25 3–11 205.9 206.8 -.8 .8

6829103 W26 1–10 214.2 212.2 2.0 2.0

6829112 W27 6–9 220.0 214.4 5.6 5.6

6829113 W28 1 220.3 212.3 8.1 8.1

6829418 W29 1 215.9 207.8 8.1 8.1

6835106 W30 3–11 205.7 210.4 -4.8 4.8

6835202 W31 1–3 210.5 209.8 .7 .7

6836103 W32 1–11 202.9 207.1 -4.3 4.3

6836130 W33 3–11 201.3 206.3 -5.0 5.0

6836206 W34 2–7 206.1 205.9 .2 .2

6836502 W35 2–11 205.7 206.9 -1.3 1.3

6836901 W36 2–4 205.8 207.0 -1.2 1.2

6837103 W37 3–11 205.1 205.3 -.3 .3

6837203 W38 1–6 204.6 205.4 -.9 .9
Table 6 85

Table 6. Measured and simulated water-level altitudes and springflows and the differences between measured and simulated waterlevel altitudes and springflows (residuals) for the local-scale model, steady-state simulation, San Antonio region, Texas.—Continued

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 is 

upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is Glen 

Rose (Trinity Group); Measured value is the mean hydraulic head or springflow measured during 2001. Difference or residual is the measured water level or 

springflow minus the simulated water level or springflow. m, meters; m3/s, cubic meters per second; RMS, root mean square]

Well 

name

Well 

identifier

Hydrogeologic unit

number(s)

Water-level altitude 

(m)

Difference

(m)

Measured

value

Simulated 

value

Algebraic 

difference

Absolute value 

of difference

6837304 W39 1 202.1 204.9 -2.8 2.8

6837524 W40 1 205.1 206.6 -1.5 1.5

6843402 W41 1–10 206.8 209.6 -2.8 2.8

6843606 W42 1 209.2 209.5 -.3 .3

68285AA W43 1–11 184.8 207.9 -23.0 23.0

68299BB W44 3–11 203.5 204.1 -.6 .6

68299CC W45 3–11 204.0 204.1 -.1 .1

68377AA W46 3–11 197.1 207.0 -9.9 9.9

68431AA W47 1–11 209.8 209.0 .8 .8

68437AA W48 1–11 203.8 209.6 -5.9 5.9

6826802 W49 3–5 236.7 222.3 14.4 14.4

6833604 W50 1–3 215.6 212.7 2.9 2.9

6834506 W51 3–11 212.6 212.5 .1 .1

6841301 W52 3–4 213.4 212.6 .9 .9

6842106 W53 1–4 213.5 212.5 1.0 1.0

6842112 W54 3 209.9 209.9 0 0

6842502 W55 2–4 211.5 209.7 1.8 1.8

6939504 W56 1 262.7 253.6 9.1 9.1

6939801 W57 1–4 230.0 220.3 9.7 9.7

6939901 W58 6–11 228.1 220.2 7.9 7.9

6940101 W59 2–11 264.9 264.6 .3 .3

6940102 W60 1–10 253.1 243.1 10.0 10.0

6940404 W61 1–8 236.9 220.7 16.2 16.2

6940901 W62 4 218.3 215.4 2.9 2.9

6947301 W63 1–6 219.6 215.8 3.8 3.8

6947306 W64 1–7 218.9 215.8 3.1 3.1

6948102 W65 4–10 218.7 215.7 3.0 3.0

6948303 W66 7–10 213.9 215.5 -1.6 1.6

68339AA W67 4–11 214.6 212.6 1.9 1.9

68415AA W68 1–11 214.3 210.0 4.3 4.3

68416AA W69 1–11 213.0 209.9 3.1 3.1

68422AA W70 1–8 211.5 210.0 1.5 1.5

69396AA W71 1–10 241.9 238.5 3.3 3.3

69489AA W72 1–7 223.5 212.7 10.8 10.8

YMCA W73 3–10 219.2 210.6 8.7 8.7

Graham W74 1–11 218.2 210.6 7.7 7.7

Lockhill W75 9–11 228.5 209.7 18.8 18.8

Abe Lincoln W76 2–11 214.4 209.0 5.4 5.4
86 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 6. Measured and simulated water-level altitudes and springflows and the differences between measured and simulated waterlevel altitudes and springflows (residuals) for the local-scale model, steady-state simulation, San Antonio region, Texas.—Continued

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 is 

upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is Glen 

Rose (Trinity Group); Measured value is the mean hydraulic head or springflow measured during 2001. Difference or residual is the measured water level or 

springflow minus the simulated water level or springflow. m, meters; m3/s, cubic meters per second; RMS, root mean square]

Well 

name

Well 

identifier

Hydrogeologic unit

number(s)

Water-level altitude 

(m)

Difference

(m)

Measured

value

Simulated 

value

Algebraic 

difference

Absolute value 

of difference

Propane Depot W77 1–10 209.7 208.8 0.9 0.9

Salazar W78 1–11 213.3 208.0 5.4 5.4

Zarzamora_

OVB

W79 1 212.9 207.2 5.7 5.7

Timberhill_IED WQ1 4–6 205.0 208.2 -3.2 3.2

Timberhill_

DED

WQ2 8–10 205.1 208.2 -3.1 3.1

Zarzamora_SED WQ3 3 206.5 207.2 -.7 .7

Zarzamora_IED WQ4 4 207.4 207.2 .2 .2

Zarzamora_

DED

WQ5 7–8 206.1 207.2 -1.1 1.1

Mean 1.9 4.2

RMS error 6.0

Spring 

name

Spring 

identifier

Hydrogeologic unit

number(s)

Springflow (m3

/s)

Measured value Simulated value Residual

San Antonio DR1 2–11 0.91 0.98 -0.07

San Pedro DR2 2–11 .24 .23 .01

RMS error .05
Table 8 87

Table 8

Table 7. Hydrogeologic units used in the local-scale model, San Antonio region, Texas.

[Thickness of hydrogeologic unit number 1 (overburden) is computed as the difference between land surface altitude and the altitude of the top of the uppermost 

unit of the Edwards aquifer (hydrogeologic units 2–11) present at a location; much of the thickness is unsaturated]

Hydrogeologic 

unit

Hydrogeologic 

unit number

Thickness

(meters) Number of active

model cells

Minimum Mean Maximum

overburden 1 0.3 281 759 55,778

Georgetown 2 .6 7 21 57,333

cyclic and marine 3 8 21 40 57,333

leached and collapsed 4 8 25 51 57,333

upper high K (conduit) 5 8 8 8 57,333

regional dense 6 3 7 12 57,906

grainstone 7 10 17 44 57,906

Kirschberg evaporite 8 2 10 20 57,906

lower high K (conduit) 9 8 8 8 57,906

dolomitic 10 13 36 44 57,906

basal nodular 11 13 17 26 65,869

Glen Rose (Trinity Group) 12 3 139 291 13,492

Table 8. Summary of specified flux by model boundary in the local-scale model, San Antonio region, Texas.

[Subtotal is the sum of the flows for the western, southern, and eastern model boundaries. Total is the sum of the flows for the northern, western, southern, and 

eastern model boundaries. Negative flow indicates flow out of the local-scale model area. The net flows from this table are shown in figure 24, adjusted for the 

different units of measure used in figure 24 (cubic meters per year)]

Flow

direction

Specified flux by model boundary, in cubic meters per day

Northern Western Southern Eastern Subtotal Total

Inflow 32,385 1,108,927 754,201 9,190 1,872,318 1,904,703

Outflow 0 -122,893 -1,081,631 -791,203 -1,995,727 -1,995,727

Net flow 32,385 986,034 -327,430 -782,013 -123,409 -91,024
88 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 9

ParameterHydrogeologic

unit number Initial value Calibrated value

HK1 1 3.0 12.1

HK2 2 3.0 2.84

HK3 3 152 497

HK4 4 152 497

HK5 5 152,393 152,393

HK6 6 3.0 2.92

HK7 7 91 83.5

HK8 8 152 256

HK9 9 152,393 115,818

HK10 10 91 9.14

HK11 11 3.0 5.39

HK12 12 1.5 5.76

HK13 2–4, 6–8, 10–11 4,572 6,584

HK14 2–4, 6–8, 10–11 3,810 4,073

HK15 2–4, 6–8, 10–11 3,048 5,863

HK16 2–4, 6–8, 10–11 3,048 5,227

HK17 2–4, 6–8, 10–11 3,048 4,297

HK18 2–4, 6–8, 10–11 1.5 .35

HK19 2–4, 6–8, 10–11 1.5 2.56

HK20 2–4, 6–8, 10–11 1.5 2.50

HK21 2–4, 6–8, 10–11 3.0 1.59

HK22 2–4, 6–8, 10–11 3.0 2.18

HK23 2–4, 6–8, 10–11 3.0 17.3

HK24 5, 9 3.0 515

HK25 5, 9 3.0 4.39

HK26 5, 9 3.0 688

ParameterHydrogeologic

unit number Initial value Calibrated value

HK27 5, 9 30 37.8

HK28 5, 9 30 923

HK29 5, 9 3.0 1.52

HK30 2–4, 6–8, 10–12 152 153

HK31 2–4, 6–8, 10–12 152 322

HK32 2–4, 6–8, 10–12 152 146

HK33 2–4, 6–8, 10–12 152 107

HANI1 All 1.0 1.0

HANI2 All .1 .9

HANI3 All 1.0 .5

HANI4 All 1.0 1.0

HANI5 All 1.0 .2

HANI6 All 1.0 1.0

VANI1 1 .1 .1

VANI2 2 .1 .2

VANI3 3 10 17.03495

VANI4 4 10 1.0

VANI5 5 10 10

VANI6 6 .1 .2

VANI7 7 10 .55224

VANI8 8 10 15.7668

VANI9 9 10 53.50458

VANI10 10 10 .5

VANI11 11 .1 5.0

VANI12 12 .1 .28165

Table 9. Initial and calibrated values for hydraulic conductivity parameters used in the local-scale groundwater-flow and particletracking simulations, San Antonio region, Texas.

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 is 

upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is Glen 

Rose (Trinity Group); HK, horizontal hydraulic conductivity; HANI, horizontal anisotropy; VANI, vertical anisotropy; HK1 to HK12 are base horizontal hydraulic conductivity values referred to in text and figures 16–17; horizontal aisotropy is the ratio of hydraulic conductivity along columns to hydraulic conductivity 

along rows; vertical anisotropy is the ratio of horizontal to vertical hydraulic conductivity; horizontal hydraulic conductivity is in meters per day; horizontal 

anisotropy and vertical anisotropy are dimensionless] 
Table 10 89

Table 10

Table 10. Initial and calibrated values for additional parameters 

used in the local-scale groundwater-flow and particle-tracking 

simulations, San Antonio region, Texas.

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is 

overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is 

Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal 

nodular, 12 is Glen Rose (Trinity Group); DR1, drain conductance for San 

Antonio Springs; DR2, drain conductance for San Pedro Springs; HFB1–

HFB5, hydraulic conductance for fault reaches 1–5; POR1–POR12, effective 

porosity for hydrogeologic units 1–12; drain conductance is in meters squared 

per day; fault conductance is per day; effective porosity is dimensionless]

Parameter

Hydrogeologic unit 

number

Initial value Calibrated value

DR1 2–11 613,100 455,210

DR2 2–11 3,066 4,738

HFB1 All .000000001 .01

HFB2 All .00000001 .1

HFB3 All .00001 .1

HFB4 All .01 .1

HFB5 All .02 .2

POR1 1 .001 .002909

POR2 2 .001 .009217

POR3 3 .01 .001795

POR4 4 .01 .003944

POR5 5 .0001 .0005373

POR6 6 .001 .0009396

POR7 7 .01 .005700

POR8 8 .01 .001914

POR9 9 .0001 .00009296

POR10 10 .01 .01255

POR11 11 .001 .01241

POR12 12 .001 .008111
90 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 11

Table 11. Measured and simulated tritium concentrations and the differences between measured and simulated tritium concentrations 

(residuals) for the local-scale model, steady-state simulation, San Antonio region, Texas.—Continued

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 

is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is 

Glen Rose (Trinity Group); WZ4W is wellhead sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate 

depth-dependent sampling interval for well WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; 

WZ6W is wellhead sample for well WZ6; WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3. RMS, root mean square]

Well or

sample name

Well or 

sample 

identifier

Sample

date

Hydrogeologic

unit

number(s)

Concentration

(tritium units)

Difference

(tritium units)

Measured

value

Simulated 

value

Algebraic

difference

Absolute 

value of 

difference

Local-scale study wells

Timberhill_IED WQ1 5/6/2008 4–6 1.77 1.85 0.08 0.08

Timberhill_DED WQ2 5/7/2008 8–10 1.72 1.82 .10 .10

Zarzamora_SED WQ3 10/31/2007 3 2.17 2.06 -.11 .11

Zarzamora_IED WQ4 10/30/2007 4 2.08 2.09 .01 .01

Zarzamora_DED WQ5 11/1/2007 7–8 2.13 1.99 -.14 .14

WZ4W Q1 11/16/2007 2–11 1.88 1.92 .04 .04

WZ4S Q2 11/16/2007 3 2.23 1.88 -.35 .35

WZ4I Q3 11/15/2007 4–5 1.78 1.87 .09 .09

WZ4D Q4 11/15/2007 8–9 1.90 1.99 .09 .09

WZ5W Q5 11/29/2007 4–11 2.18 1.93 -.25 .25

WZ6W Q6 11/28/2007 4–11 1.91 1.93 .02 .02

WZ2W Q7 11/29/2007 2–11 2.08 1.99 -.09 .09

WZ3W Q8 11/28/2007 2–11 2.05 1.99 -.06 .06

Mean -.04 .11

RMS error .14

NAWQA wells

Parkwood Park Q9 12/10/1998 4–6 3.32 3.21 -.11 .11

9/11/2006 2.10 2.21 .11 .11

Indian Meadows Q10 8/30/2006 6–7 2.60 1.79 -.81 .81

Lockhill-S-PO Q11 11/6/1998 1 1.19 3.24 2.05 2.05

8/30/2006 2.10 1.91 -.19 .19

DeZavala PO Q12 11/6/1998 7–8 3.01 2.87 -.14 .14

9/6/2006 1.82 1.80 -.02 .02

Helotes Q13 9/1/2006 6–8 1.69 1.89 .20 .20

Bluestone Q14 9/5/2006 3–4 2.01 1.94 -.07 .07

Western Oak Q15 11/10/1998 7–10 3.70 3.09 -.61 .61

9/5/2006 2.32 1.94 -.38 .38

Huebner at Olmos Q16 11/14/1998 6 3.32 2.89 -.43 .43

8/29/2006 1.82 1.74 -.08 .08

VJ Beckwith Q17 11/13/1998 7–8 2.92 3.11 .19 .19

9/11/2006 1.60 1.94 .34 .34

Roadrunner Way Q18 11/12/1998 2–4 3.51 3.49 -.02 .02

9/6/2006 1.69 2.13 .44 .44

Shavano Woods Q19 12/8/1998 10–11 3.01 3.09 .08 .08

8/31/2006 1.69 1.76 .07 .07
Table 11 91

Table 11. Measured and simulated tritium concentrations and the differences between measured and simulated tritium concentrations 

(residuals) for the local-scale model, steady-state simulation, San Antonio region, Texas.—Continued

[Hydrogeologic unit numbers refer to hydrogeologic units as follows: 1 is overburden, 2 is Georgetown, 3 is cyclic and marine, 4 is leached and collapsed, 5 

is upper high K (conduit), 6 is regional dense, 7 is grainstone, 8 is Kirschberg evaporite, 9 is lower high K (conduit), 10 is dolomitic, 11 is basal nodular, 12 is 

Glen Rose (Trinity Group); WZ4W is wellhead sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate 

depth-dependent sampling interval for well WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; 

WZ6W is wellhead sample for well WZ6; WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3. RMS, root mean square]

Well or

sample name

Well or 

sample 

identifier

Sample

date

Hydrogeologic

unit

number(s)

Concentration

(tritium units)

Difference

(tritium units)

Measured

value

Simulated 

value

Algebraic

difference

Absolute 

value of 

difference

SP-Cliffside Q20 12/11/1998 6 2.01 3.25 1.24 1.24

8/24/2006 2.19 1.74 -.45 .45

Babcock Firestation Q21 10/23/1998 10–11 4.61 3.09 -1.52 1.52

9/7/2006 2.51 1.94 -.57 .57

SP-Fawn Drive Q22 11/14/1998 10–11 2.82 3.46 .64 .64

8/24/2006 1.16 1.77 .61 .61

UTSA at Regency Q23 11/12/1998 6–7 3.10 3.16 .06 .06

9/7/2006 2.10 1.73 -.37 .37

Lockhill S (at 1604) Q24 10/26/1998 1–3 2.70 2.81 .11 .11

9/12/2006 1.91 1.70 -.21 .21

Landrum Q25 8/22/1996 1–4 4.01 4.29 .28 .28

O. Martin Q26 7/24/1996 4–8 3.13 3.55 .42 .42

Wiemers Q27 7/22/1996 1–10 2.82 3.87 1.05 1.05

Lehmberg Q28 8/1/1996 1–10 1.19 3.81 2.62 2.62

Walthour Q29 7/23/1996 12 4.39 3.80 -.59 .59

Shavano Park (no. 6) Q30 8/6/1996 11–12 1.19 3.96 2.77 2.77

34th St Sta Q31 6/26/1997 1–11 2.70 3.51 .81 .81

Lockhill-Selma Q32 7/7/1997 3–5 3.92 3.62 -.30 .30

Fohn Farms Q33 7/8/1997 2–7 0.91 4.43 3.52 3.52

Bendele, Ken Q34 7/9/1997 5–7 3.20 3.87 .67 .67

SanPedro Springs 4D Q35 7/9/1997 2–11 2.51 2.82 .31 .31

Medina JHS Q36 7/10/1997 1–7 2.92 3.28 .36 .36

Yancy #3 Q37 7/15/1997 2–10 3.92 4.97 1.05 1.05

Mean .31 .64

RMS error 1.01
92 Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well

Table 12

Table 12. Simulated annual water budget for the local-scale model, steady-state simulation, San Antonio region, Texas.

[Recharge includes leakage from streams through streambeds and infiltration of precipitation in interstream areas. Boundary inflow includes inflow through 

specified-flow boundary condition cells at the northern, western, southern, and eastern model boundaries. m3/yr, cubic meters per year]

Detailed water budget

Budget 

component

Flow rate

(m3

/yr)

Percent 

of budget 

component

Percent 

of total 

sources or 

discharges

Source

Recharge 324,890,616 100.0 31.8

Boundary inflow

North 11,820,540 1.7 1.2

West 404,758,389 58.2 39.7

East 3,354,189 .5 .3

South 275,283,477 39.6 27.0

Subtotal 695,216,596 100.0 68.2

Total sources 1,020,107,211 100.0 100.0

Discharge

Withdrawals (pumpage) 253,706,023 100.0 24.9

Springflow 37,961,345 100.0 3.7

Boundary outflow

West 44,855,919 6.2 4.4

East 288,789,091 39.6 28.3

South 394,795,483 54.2 38.7

Subtotal 728,440,493 100.0 71.4

Total discharges 1,020,107,861 100.0 100.0

Water budget with net boundary flows 

Budget

component

Flow rate

(m3

/yr)

Percent of

budget

component

Percent 

of total 

sources or 

discharges

Source

Recharge 324,890,616 100.0 46.6

Net boundary inflow

North 11,820,540 3.2 1.7

West 359,902,470 96.8 51.7

Subtotal 371,723,010 100.0 53.4

Total sources 696,613,626 100.0 100.0

Discharge

Withdrawals (pumpage) 253,706,023 100.0 36.4

Springflow 37,961,345 100.0 5.4

Net boundary outflow

East 285,434,902 70.5 41.0

South 119,512,006 29.5 17.2

Subtotal 404,946,908 100.0 58.2

Total discharges 696,614,276 100.0 100.0
Table 13 93

Table 13

Table 13. Simulated particle ages, minimum, mean, and maximum at monitoring wells and at the selected public-supply well, San 

Antonio region, Texas.

[Simulated particle ages and measured apparent groundwater ages are for pumping conditions with the well field and test well (WZ4) pumping; measured 

apparent groundwater age is based on 3H/3He tracer and piston-flow model (Musgrove and others, 2011); ages in years, except where noted. WZ4W is wellhead 

sample for well WZ4; WZ4S is shallow depth-dependent sampling interval for well WZ4; WZ4I is intermediate depth-dependent sampling interval for well 

WZ4; WZ4D is deep depth-dependent sampling interval for well WZ4; WZ5W is wellhead sample for well WZ5; WZ6W is wellhead sample for well WZ6; 

WZ2W is wellhead sample for well WZ2; WZ3W is wellhead sample for well WZ3. Composite refers to all the particles at all the wells (screened at varying 

depths) for the Timberhill or the Zarzamora well nests. The mean simulated particle ages highlighted in yellow are older than the corresponding measured apparent groundwater ages. The minimum, maximum, and mean simulated particle ages for the NAWQA wells are the composite values for all particles for the 29 

NAWQA wells with tritium observations used in this study. <, less than; NA, not applicable; NM, unable to determine an age (Musgrove and others, 2011)]

Well or

sample name

Well or sample 

identifier

Simulated particle age Measured apparent 

Minimum Maximum Mean groundwater age

Timberhill_IED WQ1 0.3 92 2.5 41.3

Timberhill_DED WQ2 .5 621 4.9 31.6

Composite .3 621 3.7

Zarzamora_SED WQ3 3.7 145 15 27.5

Zarzamora_IED WQ4 1.1 24 3.7 11.5

Zarzamora_DED WQ5 .8 16 3.7 1.3

Composite .8 145 7.6

WZ4W Q1 <1 day 342 4.4 3.4

WZ4S Q2 .4 244 4.9 .8

WZ4I Q3 .4 25 2.7 NM

WZ4D Q4 <1 day 342 4.3 NM

WZ5W Q5 <1 day 342 4.5 NM

WZ6W Q6 <1 day 342 4.5 16.6

WZ2W Q7 .2 1,968 7.2 18.2

WZ3W Q8 .2 1,968 7.2 18.4

NAWQA NA <1 day 14,767 42 NA

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Lindgren and others—Simulations of Groundwater Flow and Particle-Tracking Analysis in the Zone of Contribution to a Public-Supply Well—SIR 2011–5149

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