U.S. Department of the Interior

U.S. Geological Survey

Professional Paper 1737–A

National Water-Quality Assessment Program 

Hydrogeologic Settings and Ground-Water Flow 

Simulations for Regional Studies of the Transport 

of Anthropogenic and Natural Contaminants

to Public-Supply Wells—

Studies Begun in 2001

Hydrogeologic Settings and Ground-Water 

Flow Simulations for Regional Studies of 

the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—

Studies Begun in 2001

Edited by Suzanne S. Paschke

National Water-Quality Assessment Program

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Paschke, Suzanne S., ed., 2007, Hydrogeologic settings and ground-water flow simulations for regional studies of the 

transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 2001: U.S. Geological 

Survey, Professional Paper 1737–A, 244 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with accurate and 

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

facilitates effective management of water, biological, energy, and mineral resources (http://

www.usgs.gov/). Information on the quality of the Nation’s water resources is critical to assuring the long-term availability of water that is safe for drinking and recreation and suitable for 

industry, irrigation, and habitat for fish and wildlife. Population growth and increasing demands 

for multiple water uses make water availability, now 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, and local information needs and decisions related to water-quality 

management and policy (http://water.usgs.gov/nawqa). Shaped by and coordinated with ongoing efforts of other Federal, State, and local agencies, the NAWQA Program is designed to 

answer: What is the condition of our Nation’s streams and ground water? How are the conditions changing over time? How do natural features and human activities affect the quality 

of streams and ground water, 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 1991–2001, the NAWQA Program completed interdisciplinary assessments in 51 of the 

Nation’s major river basins and aquifer systems, referred to as Study Units (http://water.usgs.

gov/nawqa/studyu.html). Baseline conditions were established for comparison to future assessments, and long-term monitoring was initiated in many of the basins. During the next decade, 

42 of the 51 Study Units will be reassessed so that 10 years of comparable monitoring data 

will be available to determine trends at many of the Nation’s streams and aquifers. The next 10 

years of study also will fill in critical gaps in characterizing water-quality conditions, enhance 

understanding of factors that 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.

The USGS aims to disseminate credible, timely, and relevant science information to inform 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 waterresource issues of interest. External coordination at all levels is critical for a fully integrated 

understanding of watersheds and 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, interstate, Tribal, and local—as well as nongovernmental organizations, industry, academia, and other stakeholder groups. Your assistance and 

suggestions are greatly appreciated.

Robert M. Hirsch

Associate Director for Water

v

Contents

Section 1.

Overview of Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells, by S.S. Paschke, L.J. Kauffman, S.M. Eberts, 

and S.R. Hinkle

Section 2.

Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley 

Regional Study Area, Utah, by B.J. Stolp

Section 3.

Hydrogeologic Settings and Ground-Water Flow Simulations of the Eagle Valley 

and Spanish Springs Valley Regional Study Areas, Nevada, by D.H. Schaefer, 

J.M. Green, and M.R. Rosen

Section 4.

Hydrogeologic Setting and Ground-Water Flow Simulations of the San Joaquin Valley 

Regional Study Area, California, by S.P. Phillips, K.R. Burow, D.L. Rewis, J.J. Shelton, and 

Bryant Jurgens

Section 5.

Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay 

Regional Study Area, Florida, by C.A. Crandall

Section 6.

Hydrogeologic Setting and Ground-Water Flow Simulations of the Pomperaug River 

Basin Regional Study Area, Connecticut, by F.P. Lyford, Carl S. Carlson, Craig J. Brown, 

and J. Jeffrey Starn

Section 7.

Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River 

Basin Regional Study Area, Ohio, by R.A. Sheets

Section 8.

Hydrogeologic Setting and Ground-Water Flow Simulations of the Eastern High Plains 

Regional Study Area, Nebraska, by M.K. Landon and M.J. Turco

Appendix 1.

Database Dictionary for the Study of Anthropogenic and Natural Contaminants
vi

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 (ft2) 

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

liter (L) 0.2642 gallon (gal)

cubic meter (m3) 264.2 gallon (gal) 

cubic meter (m3) 0.0002642 million gallons (Mgal) 

cubic centimeter (cm3) 0.06102 cubic inch (in3) 

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 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)

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

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

Conversion Factors, Datum, Abbreviations, and 

Definitions
vii

Multiply By To obtain

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

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) 

Overview of Regional Studies of the 

Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells

By Suzanne S. Paschke, Leon J. Kauffman, Sandra M. Eberts, and 

Stephen R. Hinkle

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 1 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Paschke, S.S., Kauffman, L.J., Eberts, S.M., and Hinkle, S.R., 2007, Overview of regional studies of the transport of 

anthropogenic and natural contaminants to public-supply wells, section 1 of Paschke, S.S., ed., Hydrogeologic 

settings and ground-water flow simulations for regional studies of the transport of anthropogenic and natural 

contaminants to public-supply wells—studies begun in 2001: Reston, Va., U.S. Geological Survey Professional 

Paper 1737–A, pp. 1–1 –1–18.
iii

Contents

Abstract...................................................................................................................................................... 1–1

Introduction................................................................................................................................................ 1–1

Purpose and Scope ......................................................................................................................... 1–2

Study Area Locations...................................................................................................................... 1–2

Basin and Range Basin-Fill Aquifers................................................................................... 1–5

Central Valley Aquifer System.............................................................................................. 1–5

Floridan Aquifer System ........................................................................................................ 1–7

Glacial Aquifer System .......................................................................................................... 1–8

High Plains Aquifer................................................................................................................. 1–9

Methods...................................................................................................................................................... 1–9

Retrospective Data Compilation.................................................................................................. 1–10

Source Water-Quality Assessment Sample Collection........................................................... 1–10

Ground-Water Flow Simulation ................................................................................................... 1–10

Oxidation-Reduction and pH Classification and Mapping...................................................... 1–12

Database Development ................................................................................................................ 1–14

References Cited..................................................................................................................................... 1–14

Figures

Maps showing:

1.1. The 19 principal aquifers selected as the primary focus of 

ground-water studies during Cycle II of the National Water-Quality 

Assessment program............................................................................................... 1–4

1.2. Locations of principal aquifers, National Water-Quality Assessment

program study-unit boundaries, and 2001-start regional study areas

for the transport of anthropogenic and natural contaminants. ...................... 1–6

1.3. Schematic diagram of area contributing recharge and zone of contribution for a 

single discharging well in a simplified hypothetical ground-water system. .......... 1–11

Tables

1.1. The 19 principal aquifers selected as the primary focus of ground-water studies

during Cycle II of the National Water-Quality Assessment Program ........................ 1–3

1.2. Effects of weak sinks on the determination of contributing areas........................... 1–12

1.3. Oxidation-reduction classification scheme ................................................................. 1–13

Overview of Regional Studies of the Transport of 

Anthropogenic and Natural Contaminants to 

Public-Supply Wells

By Suzanne S. Paschke, Leon J. Kauffman, Sandra M. Eberts, and Stephen R. Hinkle

Abstract

This study of the Transport of Anthropogenic and Natural 

Contaminants to public-supply wells (TANC study) is being 

conducted as part of the U.S. Geological Survey National 

Water Quality Assessment (NAWQA) Program and was 

designed to increase understanding of the most important 

factors to consider in ground-water vulnerability assessments. 

The seven TANC studies that began in 2001 used retrospective 

data and ground-water flow models to evaluate hydrogeologic 

variables that affect aquifer susceptibility and vulnerability at 

a regional scale. Ground-water flow characteristics, regional 

water budgets, pumping-well information, and water-quality 

data were compiled from existing data and used to develop 

conceptual models of ground-water conditions for each 

study area. Steady-state regional ground-water flow models 

were used to represent the conceptual models, and advective 

particle-tracking simulations were used to compute areas contributing recharge and traveltimes from recharge to selected 

public-supply wells. Retrospective data and modeling results 

were tabulated into a relational database for future analysis. 

Seven study areas were selected to evaluate a range of hydrogeologic settings and management practices across the Nation: 

the Salt Lake Valley, Utah; the Eagle Valley and Spanish 

Springs Valley, Nevada; the San Joaquin Valley, California; 

the Northern Tampa Bay region, Florida; the Pomperaug River 

Basin, Connecticut; the Great Miami River Basin, Ohio; and 

the Eastern High Plains, Nebraska. This Professional Paper 

Chapter presents the hydrogeologic settings and documents 

the ground-water flow models for each of the NAWQA TANC 

regional study areas that began work in 2001. Methods used 

to compile retrospective data, determine contributing areas 

of public-supply wells, and characterize oxidation-reduction 

(redox) conditions also are presented. This Professional Paper 

Chapter provides the foundation for future susceptibility and 

vulnerability analyses in the TANC study areas and comparisons among regional aquifer systems. The report is organized 

in sections. In addition to the introductory section (Section 1) 

are seven sections that present the hydrogeologic characterization and ground-water flow model documentation for each 

TANC regional study area (Sections 2 through 8). Abstracts 

in Sections 2 through 8 provide summaries and major findings 

for each regional study area. 

Introduction

About one-third of the population of the United States 

obtains drinking water from public-supply systems that rely 

on ground water causing concern for the quality of ground 

water pumped by public-supply wells (Franke and others, 

1998). The occurrence and concentration of anthropogenic and 

natural contaminants in public-supply wells is controlled by 

many factors intrinsic and extrinsic to a ground-water system. 

Aquifer and public-supply well susceptibility to contamination is determined by the intrinsic conditions of an aquifer 

such as depth to water, flow-system confinement, recharge 

rate, hydraulic conductivity, and porosity (Focazio and others, 

2002). Factors extrinsic to the aquifer include land use and 

the presence and location of potential contaminant sources 

overlying or within the area contributing recharge to a publicsupply well. Aquifer vulnerability is determined by considering both the intrinsic and extrinsic factors affecting water 

quality (Focazio and others, 2002). This study of the Transport 

of Anthropogenic and Natural Contaminants to supply wells 

(TANC) also considers public-supply well pumping rates and 

aquifer geochemical conditions when determining aquifer 

vulnerability. 

The TANC study is part of the U.S. Geological Survey 

National Water-Quality Assessment (NAWQA) Program. The 

long-term goals of the NAWQA Program are to describe the 

status and trends in the quality of a large representative part 

of the Nation’s surface- and ground-water resources and to 

provide a sound, scientific understanding of the major natural 

and human factors affecting the quality of those resources 

(Gilliom and others, 1995). The first cycle (Cycle I) of the 

NAWQA Program was implemented from 1991 to 2000, and 

a second investigative cycle (Cycle II) began in 2001. During Cycle II (2001 to 2011), 42 NAWQA study units will be 
1–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

revisited in three groups of 14 on a rotational schedule. Each 

group is intensively studied for 4 years, followed by 6 years of 

low-intensity assessment. The primary emphasis of Cycle II 

is to assess long-term trends in water quality and to improve 

understanding of the factors and processes governing water 

quality. The TANC study is one of several Cycle II NAWQA 

studies designed to aid understanding of our Nation’s water 

quality. 

Purpose and Scope

The TANC study was designed to increase understanding 

of anthropogenic and natural contaminants detected in publicsupply wells in support of ground-water susceptibility and vulnerability assessments by examining answers to the question: 

“What are the primary anthropogenic and natural contaminant 

sources, aquifer processes, and well characteristics that control 

the transport and transformation of contaminants along flow 

paths to public-supply wells in representative water-supply 

aquifers?”

Seven TANC studies began in 2001 using retrospective 

data and ground-water flow models to evaluate hydrogeologic 

variables that affect aquifer susceptibility and vulnerability at 

a regional scale. Ground-water flow characteristics, regional 

water budgets, pumping-well information, and water-quality 

data were compiled from existing data and used to develop 

conceptual models of ground-water conditions for each study 

area. Steady-state regional ground-water flow models were 

used to represent the conceptual models, and advective particle-tracking simulations were used to compute areas contributing recharge and traveltimes from recharge to selected publicsupply wells. Retrospective data, ground-water traveltimes 

from recharge to discharge areas, oxidation-reduction (redox) 

conditions along flow paths, and the presence of potential contaminant sources in areas contributing recharge to public-supply wells were tabulated into a relational database for future 

use in analyzing aquifer vulnerability. The 5-year period from 

1997 to 2001 was selected for data compilation and modeling 

exercises in order to facilitate comparisons among study areas 

and to use large recently collected water-quality data sets.

The purpose of this report is to present the hydrogeologic 

settings, including regional redox and pH conditions, of the 

seven NAWQA TANC regional study areas that began work 

in 2001. The report also documents the ground-water flow 

models for each regional study area. This report provides the 

foundation for further susceptibility and vulnerability analyses 

in the TANC study areas, comparisons among regional aquifer 

systems, and future local-scale field and modeling investigations. The report is organized into sections. In addition to this 

introductory section (Section 1), there are seven sections that 

present the hydrogeologic characterization and ground-water 

flow model documentation for each TANC regional study 

area (Sections 2 through 8). Abstracts in Sections 2 through 8 

provide summaries and major findings for each regional study 

area. 

Study Area Locations

The U.S. Geological Survey has identified 62 principal aquifers in the United States (Miller, 1999). A principal 

aquifer is defined as a regionally extensive aquifer or aquifer 

system that has potential to be used as a source of potable 

water (U.S. Geological Survey, 2003; Maupin and Barber, 

2005). An aquifer is a geologic formation, a group of formations, or a part of a formation that contains sufficient saturated 

permeable material to yield significant amounts of water to 

wells and springs. Aquifers are often combined into aquifer 

systems. The NAWQA Program has designated 19 of the 

Nation’s 62 principal aquifers as the primary focus of Cycle 

II studies by considering the factors of aquifer areal extent, 

water use for drinking-water supply, lithology, and widespread 

geographic coverage of the United States (table 1.1). The 19 

principal aquifers account for about 75 percent of the water 

used for domestic plus public drinking-water supply in the 

United States in 1990 (Lapham and others, 2005) and provide 

a good spatial coverage of aquifer systems across the country 

(fig 1.1). 

Aquifers in different parts of the Nation differ in their 

susceptibility and vulnerability to contamination because of 

varying hydrogeologic settings and ground-water management 

practices. Of the NAWQA Cycle II study units that began 

investigations in 2001, 7 regional study areas located in 5 of 

the 19 principal aquifers were selected for TANC studies to 

evaluate a range of hydrogeologic conditions and management 

practices (fig. 1.2). Additional areas will be selected for TANC 

studies as NAWQA Cycle II proceeds through its rotational 

schedule. The NAWQA TANC 2001-start regional study areas 

and their associated principal aquifers are: 

•	 Salt Lake Valley, Utah, in the Basin and Range basinfill aquifers,

•	 Eagle Valley and Spanish Springs Valley, Nevada, in 

the Basin and Range basin-fill aquifers,

•	 San Joaquin Valley, California, in the Central Valley 

aquifer system,

•	 Northern Tampa Bay, Florida, in the Floridan aquifer 

system, 

•	 Pomperaug River Basin, Connecticut, in the glacial 

aquifer system,

•	 Great Miami River Basin, Ohio, in the glacial aquifer 

system, and 

•	 Eastern High Plains, Nebraska, in the High Plains 

aquifer.

A hydrogeologic description of each TANC 2001-start 

regional study area and its associated principal aquifer follows 

with additional details of each study provided in subsequent 

sections of this report.
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–3

Table 1.1. The 19 principal aquifers selected as the primary focus of ground-water studies during Cycle II of the National WaterQuality Assessment Program. 

[km2, square kilometers; Mm3/d, millions of cubic meters per day; NAWQA, National Water-Quality Assessment Program]

Principal aquifer or aquifers

Primary 

lithologies of the 

principal aquifer

Approximate 

area of 

principal aquifer

(km2)

Number of 

NAWQA Cycle II 

study units overlying principal 

aquifer

Principal aquifer 

rank by 2000 

drinking-water 

use1

Estimated withdrawals for public 

supply3 (Mm3/d)

Glacial aquifer system Sand and gravel 2,470,655 18 1 7.38

Mississippi Embayment—Texas Coastal 

Uplands aquifer system 

Semiconsolidated 

sandstone

511,191 7 8 2.74

Cambrian-Ordovician aquifer system Sandstone 459,722 5 10 2.23

High Plains aquifer Sand and gravel 457,594 4 14 1.47

Basin and Range basin-fill and carbonate 

aquifers 

Sand and gravel, 

carbonates

423,513 4 4 4.09

Floridan aquifer system and overlying 

Surficial aquifer system2

Carbonate 292,088 5 3 5.89

Coastal Lowlands aquifer system Semiconsolidated 

sandstone

255,975 4 5 3.82

Piedmont and Blue Ridge aquifers Carbonate and 

crystalline

227,449 8 24 0.42

Edwards-Trinity aquifer system Sandstone and 

carbonate

194,439 2 12 1.56

New England crystalline-rock aquifers Crystalline 183,158 4 31 0.28

North Atlantic Coastal Plain aquifer 

system (NACPAS)3

Semiconsolidated 

sandstone

114,542 4 7 3.00

Columbia Plateau basin-fill and 

basaltic-rock aquifers 

Sand and gravel, 

basalt

112,811 1 18 0.84

Central Valley aquifer system Sand and gravel 52,633 2 6 3.18

California Coastal basins aquifers Sand and gravel 26,367 1 2 6.0

Denver Basin aquifer system Sandstone 17,595 1 49 0.10

Hawaiian volcanic-rock aquifers Basalt 16,691 1 16 0.92

Biscayne aquifer Carbonate 9,259 1 9 2.64

Snake River basin-fill and 

basaltic-rock aquifers

Sand and gravel, 

basalt

5,060 1 23 0.57

1

Rank 1 is largest water use; use was estimated for 62 principal aquifers. 

2

Includes that part of the Coastal Plain surficial aquifer that overlies the Floridan. 

3

From Maupin and Barber, 2005
1–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 1.1. The 19 principal aquifers selected as the primary focus of ground-water studies during Cycle II of the National Water-Quality Assessment program.

EXPLANATION

Glacial aquifer systemMississippi embayment-Texas Coastal Uplands aquifer systemCambrian-Ordovician aquifer system—Darker color indicates buried portionHigh Plains aquiferBasin and Range basin-fill and carbonate aquifersFloridan aquifer system—Darker color indicates buried portionCoastal Lowlands aquifer systemPiedmont and Blue Ridge aquifersEdwards-Trinity aquifer systemNew England crystalline-rock aquifers

Surficial aquifer systemNorth Atlantic Coastal Plain aquifer systemColumbia Plateau basin-fill and basaltic-rock aquifersCentral Valley aquifer systemCalifornia Coastal basin aquifersDenver Basin aquifer systemHawaiian volcanic-rock aquifersBiscayne aquiferSnake River basin-fill and basaltic-rock aquifers

Modified from National Atlas—Principal Aquifers, 2003
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–5

Basin and Range Basin-Fill Aquifers

The Basin and Range basin-fill aquifers are a primary 

source of water in the arid West extending through about 

423,513 square kilometers (km2) of the Southwestern United 

States and underlying most of Nevada and parts of eastern 

California, southern Oregon and Idaho, western Utah, southern 

Arizona, and southwestern New Mexico (fig. 1.2). The Basin 

and Range basin-fill aquifers are thick deposits of alluvial 

materials in valleys bounded by bedrock mountain ranges. 

Basin fill primarily consists of unconsolidated to moderately 

consolidated, poorly- to well-sorted beds of gravel, sand, silt, 

and clay deposited on alluvial fans, pediments, flood plains, 

and playas. Basin-fill thickness is not well known in some 

basins but ranges from about 305 to 1,525 m in many basins 

and may exceed 3,050 m in a few deep basins in Utah and 

south-central Arizona (Robson and Banta, 1995).

Recharge to the Basin and Range basin-fill aquifers 

primarily is derived from stream runoff (mountain-front 

recharge) and subsurface flow (mountain-block recharge) 

from mountains surrounding the basins (Robson and Banta, 

1995). The generally arid climate of the area causes almost 

all precipitation in the basins and most of the precipitation 

in the mountains to be lost to evapotranspiration; only about 

5 percent of precipitation recharges the basin-fill aquifers 

(Robson and Banta, 1995). In extensively developed parts 

of the aquifers, agricultural and urban irrigation return flow 

percolates into the basin fill and ultimately recharges the 

aquifers. Discharge from the aquifers is by evapotranspiration, 

discharge to streams and springs, underflow, interbasin flow, 

and withdrawal by wells (Robson and Banta, 1995; Planert 

and Williams, 1995). Basin-fill aquifers generally are not 

connected to other basins although underflow and interbasin 

flow can be significant components of recharge or discharge 

in some basins where the surrounding bedrock is composed of 

cavernous carbonate rocks (Robson and Banta, 1995; Planert 

and Williams, 1995). Ground-water withdrawal from wells 

is the largest component of discharge from Basin and Range 

basin-fill aquifers and supplies water for agricultural irrigation 

and public water supply (Robson and Banta, 1995). Evapotranspiration is the largest natural component of ground-water 

discharge and can decrease when the water table is lowered by 

ground-water withdrawal (Robson and Banta, 1995). Although 

agricultural irrigation is still a principal ground-water use in 

the area, population increases since the 1960s have decreased 

the percentage of ground water used for irrigation and 

increased the percentage of ground water used for public water 

supply (Robson and Banta, 1995).

Ground water in the basin-fill aquifers generally is of 

suitable chemical quality for most uses; most ground water 

has a dissolved-solids concentration of less than 1,000 milligrams per liter (mg/L). However, the dissolved-solids concentration of water in parts of some basins can be as large as 

300,000 mg/L (Robson and Banta, 1995). Water that has small 

dissolved-solids concentration generally is present near the 

margins of the basins, where recharge from the nearby mountains enters the aquifers; and water with larger dissolved-solids 

concentrations is present in topographically low parts of some 

basins, where ground water is discharged by evaporation and 

transpiration (Robson and Banta, 1995). In basins that have no 

discharge by underflow or streamflow, salts can accumulate 

over long periods of time in the fine-grained sediments near 

the center of the basin or can form extensive surface deposits 

of salt, such as the salt flats of the Great Salt Lake Desert in 

western Utah (Robson and Banta, 1995). 

The Salt Lake Valley and Eagle Valley and Spanish 

Springs Valley regional study areas, which are within the 

Basin and Range basin-fill aquifers, are characterized by the 

occurrence of ground water in deep sediment-filled graben basins between mountain ranges. The Salt Lake Valley 

regional study area encompasses the Great Salt Lake Valley west of the Wasatch Range where ground water is used 

extensively for water supply in and around Salt Lake City, 

Utah. The basin-fill aquifer of the Salt Lake Valley study area 

is unconfined on the valley margins and transitions to confined 

conditions near the center of the valley where an overlying 

confining layer is present. Section 2 of this report presents the 

hydrogeologic setting, model setup, and modeling results for 

the Salt Lake Valley regional study area. 

The Eagle Valley and Spanish Springs Valley regional 

study includes two alluvial basins—Eagle Valley near Carson 

City, Nevada, in the Carson River basin, and Spanish Springs 

Valley north of Sparks, Nevada, in the Truckee River basin. 

Rapid urban development in both the Eagle Valley and the 

Spanish Springs Valley regional study areas has resulted in 

reliance on ground water for water supply. Differing population stresses and rates of ground-water movement make the 

two study areas unique. The Eagle Valley is more urbanized and receives more recharge from precipitation than the 

Spanish Springs Valley. Section 3 of this report presents the 

hydrogeologic setting, model setup, and modeling results for 

the Eagle Valley and Spanish Springs regional study areas.

Central Valley Aquifer System

The Central Valley aquifer system of California (fig. 1.2) 

contains the largest basin-fill aquifer system in the Western 

United States. The Central Valley is one of the most important agricultural areas in the World, having more than 28,000 

km2 of agricultural land under irrigation in 1995 (Planert and 

Williams, 1995). During 1985, crop irrigation accounted for 

96 percent of the surface water and 89 percent of the ground 

water withdrawn in the Central Valley (Planert and Williams, 

1995).

The Central Valley is in a structural trough about 644 km 

long and from 32 to 113 km wide and extends over more than 

52,633 km2 (Planert and Williams, 1995). The trough is filled 

by marine and continental sediments up to 10 km thick (Gronberg and others, 1998), which form an important aquifer system. The Central Valley is bounded on the west by the Coast 

Ranges and on the east by the Cascade Range and the Sierra 

Nevada. The valley floor, which consists primarily of alluvial 
1–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

4

3 2

8

7

6

5

San JoaquinTulare Basins

Nevada Basin and Range

(southern unit)

Nevada Basin and Range

(northern unit)

Great Salt

Lake Basins

High Plains

Regional GroundWater Study

White River-Great and

Little Miami River Basin

Georgia-Florida

Coastal Plain

Drainages

Connecticut,

Housatonic,

and Thames

River Basins

EXPLANATION

Principal aquifers Basin and Range basin-fill and carbonate aquifers Central Valley aquifer system Floridan aquifer system—Darker color indicates buried portion Glacial aquifer system High Plains aquiferNAWQA study-unit boundaryRegional study areas—Number indicates section number in this report. 2—Salt Lake Valley, Utah 3—Eagle Valley and Spanish Springs Valley, Nevada 4—San Joaquin Valley, California 5—Northern Tampa Bay, Florida 6—Pomperaug River Basin, Connecticut 7—Great Miami River Basin, Ohio 8—Eastern High Plains, Nebraska

4

Figure 1.2. Locations of principal aquifers, National Water-Quality Assessment program study-unit boundaries, and 2001-start regional study areas for the transport of anthropogenic and natural contaminants.
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–7

and flood-plain deposits of the major rivers, is relatively flat 

to gently rolling and is generally below an altitude of 152 m. 

The Sacramento River drains the northern end of the Central 

Valley, and the San Joaquin River drains much of the middle 

one-third. The two rivers join in the Sacramento-San Joaquin 

Delta and empty into the upper end of San Francisco Bay. The 

southern end of the valley is occupied by the Tulare Basin, in 

which drainage is internal and the inflowing water is removed 

by evapotranspiration (Gronberg and others, 1998). 

The climate of the Central Valley is Mediterranean and 

Steppe, characterized by hot summers and mild winters with 

about 85 percent of the precipitation falling from November 

to April (Planert and Williams, 1995). Annual precipitation 

decreases from north to south, with an average of about 58.4 

cm in the northern part of the Sacramento Valley to about 15.2 

cm in the southern part of the San Joaquin Valley (Planert and 

Williams, 1995). Runoff from the Coast Ranges is principally 

on the western slopes to the Pacific Ocean.

Under natural conditions, ground water in the Central 

Valley aquifer system flowed from areas of higher altitude at 

the valley margins toward rivers and marshes near the valley axis (Davis and others, 1959). The aquifer was recharged 

primarily by streams emanating from the Cascade Range 

and the Sierra Nevada (average of 30.5 cm/yr) (Planert and 

Williams, 1995). Ground water that was not evaporated or 

transpired by plants discharged either into the Sacramento and 

the San Joaquin Rivers or into the Tulare Basin, from which 

it was eventually removed by evaporation or transpiration. 

By the early 1960s, intensive ground-water development for 

agricultural irrigation had substantially lowered water levels 

and altered ground-water flow patterns in the Central Valley aquifer system (Planert and Williams, 1995). The most 

striking effect of development on water levels was in the San 

Joaquin Valley, where water-level declines in the confined part 

of the aquifer system were locally more than 122 m (Planert 

and Williams, 1995). Large withdrawals from deep wells in 

the San Joaquin Valley diverted ground-water flow toward the 

wells and away from the San Joaquin River and reversed vertical hydraulic gradients over much of the San Joaquin Valley 

to the point that water in the upper unconfined aquifer leaked 

downward into the lower confined aquifer (Planert and Williams, 1995). Well construction also affected vertical flow in 

the valley as many deep wells were perforated across confining units, allowing unrestricted vertical flow through the well 

bores. Ground-water withdrawals have decreased since the late 

1960s as additional surface water was imported to the valley 

(Planert and Williams, 1995).

Water quality in the Central Valley aquifer system is 

affected by natural geologic and hydrologic factors as well as 

agricultural land use. The thickness of aquifers saturated with 

freshwater (water with less than 1,000 mg/L dissolved solids) 

varies greatly within the basin, but in general, freshwater is 

contained in continental fluvial deposits, and dissolved-solids 

concentrations increase with depth (Gronberg and others, 

1998). Selenium, nitrate, and pesticide concentrations are 

elevated in ground water of some areas of the Central Valley 

as the result of agricultural irrigation. The pesticide dibromochloropropane (DBCP) is particularly problematic and is 

present in ground water in every county in the San Joaquin 

Valley (Planert and Williams, 1995).

The San Joaquin Valley regional study area is located in 

the northeastern San Joaquin Valley and centered around the 

city of Modesto, California, which relies heavily on ground 

water for public water supply. The study area is about 2,700 

km2 in area, bounded on the west by the San Joaquin River, on 

the north by the Stanislaus River, on the south by the Merced 

River, and on the east by the Sierra Nevada foothills. The San 

Joaquin Valley occupies the southern two-thirds of the Central 

Valley principal aquifer system. Unconfined ground water 

is present in the Pleistocene sediments of the San Joaquin 

Valley above a thick confining unit known as the Corcoran 

Clay member of the Tulare Formation. Confined ground water 

occurs primarily in Pleistocene and Tertiary sediments below 

the Corcoran Clay. Section 4 of this report presents the hydrogeologic setting, model setup, and modeling results for the San 

Joaquin Valley regional study area.

Floridan Aquifer System

The Floridan aquifer system, one of the most productive aquifers in the World, underlies an area of about 292,088 

km2 in southern Alabama, southeastern Georgia, southern 

South Carolina, and all of Florida (Miller, 1990). The Floridan 

aquifer system provides water for several large cities, including Savannah and Brunswick in Georgia and Jacksonville, 

Gainsville, Tallahassee, Orlando, Tampa, and St. Petersburg 

in Florida. An average of about 15,230,000 m3/d of freshwater 

was withdrawn from the Floridan aquifer system for all purposes during the year 2000 (Marella and Berndt, 2005). 

A thick sequence of carbonate rocks (limestone and dolomite) of Tertiary age constitutes the Floridan aquifer system 

(Miller, 1990). In most places, the system can be divided into 

the Upper and Lower Floridan aquifers, separated by a less 

permeable confining unit (Miller, 1986). Because it is a prolific aquifer with acceptable water quality, the Upper Floridan 

is the primary water supply for the area, and its geology and 

hydraulic properties have been extensively studied. The Upper 

Floridan is highly permeable in most places and includes 

the Suwannee and Ocala Limestones and the upper part of 

the Avon Park Formation (Miller, 1986). Where the Tampa 

Limestone is highly permeable, it also is included in the Upper 

Floridan; however, aquifer-system boundaries do not necessarily conform to formational boundaries (Miller, 1990). In most 

areas, the limestones are highly fractured and dissolved to 

form secondary porosity and karst features. Sinkholes, springs, 

and conduits are numerous in the Floridan aquifer in northern 

and central Florida. The Floridan aquifer system generally 

thickens seaward from a thin edge near its northern limit to 

about 914 m in thickness in southern Florida (Miller, 1986).

Prior to extensive ground-water development in the 

1960s, ground water generally moved coastward from the 

outcrop area of the aquifer in Georgia and South Carolina 
1–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

and outward in all directions from a potentiometric high in 

central Florida. Although recharge to the aquifer takes place 

throughout more than one-half of its area, recharge tends to 

be concentrated in outcrop areas and at potentiometric highs. 

Recharge rates range from less than 2.54 cm/yr to more than 

51 cm/yr depending on local geologic and hydrologic conditions (Miller, 1990). Before development, nearly 90 percent of 

the discharge from the Floridan aquifer system was to springs 

and streams supplying base flow to the Suwannee, Flint, Sante 

Fe, Withlacoochee, Hillsborough, and other rivers, which are 

important water supply and recreational resources (Bush and 

Johnson, 1988). The Floridan aquifer also discharged to offshore springs both on the Gulf of Mexico and Atlantic Ocean 

sides of the northern part of peninsular Florida (Bush and 

Johnson, 1988).

Following development of the Upper Floridan aquifer, 

deep cones of depression developed near some major pumping centers, regional water-level declines were noted in some 

areas, and predevelopment potentiometric gradients were 

reversed in some coastal areas, creating the potential for 

encroachment of saltwater from the Gulf of Mexico (Miller, 

1990). However, the major characteristics of the predevelopment flow system have not been greatly altered, and the 

dominant form of discharge remains springflow and discharge 

to streams (Miller, 1990).

Water quality and dissolved-solids concentrations of 

water in the Floridan aquifer system are related to (1) the 

ground-water flow system and (2) the proximity to saltwater. 

Water in the Floridan aquifer system is predominantly calcium-bicarbonate type water with dissolved-solids concentrations ranging from 10 to 30,000 mg/L and averaging 250 mg/L 

(Katz, 1992). In places where the aquifer system is unconfined 

or thinly confined, large volumes of water move quickly in and 

out of the aquifer system, and dissolved-solids concentrations 

are generally less than 250 mg/L (Katz, 1992). In areas where 

the aquifer system is confined, water travels along longer flow 

paths and has greater dissolved-solids concentrations. Near the 

east and west coasts of Florida, and locally in coastal areas of 

South Carolina and Georgia, large dissolved-solids concentrations result from mixing of fresh ground water with deeper 

saltwater that migrates into the aquifer from the ocean (Miller, 

1990). 

The Northern Tampa Bay regional study area is located in 

west-central peninsular Florida in the Tampa Bay metropolitan 

area. The study area overlies the karst Floridan aquifer system 

of the Southeastern United States. This study area was chosen 

because of the extensive water use from the Floridan aquifer 

system, because the aquifer is shallow, susceptible, and vulnerable to contamination, and because it represents a range of 

hydrogeologic and land-use conditions found throughout areas 

overlying the Floridan aquifer system. The Tampa Bay metropolitan area relies heavily on the Floridan aquifer system for 

drinking water, and the Floridan aquifer system is the primary 

source of water for domestic, irrigation, and industrial supplies. The study area includes public water-supply systems for 

the cities of Tampa, St. Petersburg, and Clearwater, Florida, 

and numerous smaller cities. Section 5 of this report compares 

the study area characteristics to those of the Floridan principal 

aquifer system and presents the hydrogeologic setting, model 

setup, and modeling results for the Northern Tampa Bay 

regional study area.

Glacial Aquifer System

The glacial aquifer system is present in 21 States from 

Maine to Washington, and covers more than 27 percent or 

approximately 2.5 billion km2 of the continental United States 

(fig. 1.2) (U.S. Geological Survey, 2003). The glacial sand and 

gravel aquifers were ranked first in withdrawals for domestic 

plus public drinking-water supply among the approximately 

62 principal aquifers in the United States.

The glacial aquifer system is generally composed of 

unconsolidated sand, gravel, and clay commonly deposited as 

individual valley-fill deposits of outwash and ice-contact materials in bedrock valleys when large continental glaciers covered parts of Canada and the northern United States between 

approximately 1.6 million and 10,000 years ago (Olcott, 

1995). The glacial sand and gravel deposits range from a few 

meters to more than 300 m in thickness and are highly heterogeneous across the North-Central and Northeastern United 

States. The glacial sand and gravel aquifers are generally 

unconfined and in hydraulic connection with valley streams 

and are the most productive aquifers throughout the glaciated 

area of the country. The glacial aquifer system in the Northeastern United States is located in humid climatic regions with 

precipitation ranging from 91 to 127 cm/yr (Randall, 1996), 

and ground-water recharge is primarily from local precipitation and stream runoff from surrounding bedrock uplands. The 

bedrock surrounding glacial aquifers is usually less permeable 

than the valley-fill sediments, and ground-water underflow 

from bedrock uplands is minimal (Randall, 2001). Groundwater discharge in the glacial aquifers is generally to streams 

and wells with ground-water pumping accounting for about 15 

percent of ground-water discharge (Morrissey, 1983).

Ground-water quality in the glacial aquifers is generally 

characterized as calcium-bicarbonate type water with dissolved-solids concentrations less than 150 mg/L and pH values 

in the range of 6 to 8 (Rogers, 1989). However, water quality 

varies regionally, depending on ground-water flow conditions, 

valley-fill sediment size, and sediment source area (Randall, 

2001). Source area of glacial deposits determines the mineral 

composition of valley-fill deposits, and rock/water interaction and changing redox conditions in an aquifer can mobilize 

many constituents that affect natural water quality (Warner 

and Arnold, 2006). For example, high iron concentrations are 

detected in some parts of glacial aquifers where geochemical 

reducing conditions cause dissolution of iron oxides present 

in sediment. The glacial aquifer system also is vulnerable to 

anthropogenic contaminants such as nitrates and pesticides 

in agricultural areas because of the unconfined ground-water 

flow conditions and short ground-water flow paths.
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–9

The Pomperaug River Basin and Great Miami River 

Basin regional study areas are both within the glacial aquifer 

system. The Pomperaug River Basin study area is located in 

west-central Connecticut and represents glacial aquifers in 

the Northeastern United States. Characteristics of the aquifer 

system selected for this study are similar to many valley-fillaquifer systems in the Eastern Hills and Valley Fills hydrophysiographic region (Randall, 2001), which encompasses 

much of the most populated parts of New England, northern 

New Jersey, and eastern New York. Public water supply in the 

Pomperaug River Basin is obtained from ground water in the 

glacial valley-fill aquifer. Section 6 of this report presents the 

hydrogeologic setting, model setup, and modeling results for 

the Pomperaug River Basin regional study area.

The Great Miami River Basin regional study area is in 

the east-central portion of the White River-Great and Little 

Miami River Basin NAWQA study unit and is centered on the 

city of Dayton, Ohio. Ground water in the study area occurs 

in the valley-fill glacial aquifer underlying the Great Miami 

River, and the study area represents the glacial aquifer system 

in the North-Central United States. The glacial aquifer in the 

study area is heavily used by industry and municipalities, and 

pumping often causes induced infiltration from nearby rivers 

or artificial recharge lagoons. Section 7 of this report presents 

the hydrogeologic setting, model setup, and modeling results 

for the Great Miami River Basin regional study area.

High Plains Aquifer

The High Plains aquifer underlies 457,594 km2 in parts 

of eight States (fig. 1.2) and is primarily composed of Tertiary 

sand and gravel deposits of the Ogallala Formation (Gutentag 

and others, 1984). Ground water also occurs in Quaternary 

sand and gravel deposits overlying the Ogallala Formation in 

some areas. Approximately 27 percent of the irrigated land in 

the United States is in the High Plains, and about 30 percent 

of the ground water used for irrigation in the United States is 

pumped from the High Plains aquifer (Dennehy, 2000). The 

High Plains aquifer also provides drinking water to 82 percent 

of the 2.3 million people (1990 census) who live within the 

aquifer boundary. 

The Ogallala Formation, which underlies about 80 percent of the High Plains, is the principal geologic unit forming the aquifer. The Ogallala Formation is a heterogeneous 

sequence of gravel, sand, silt, and clay deposited by braided 

streams flowing eastward from the ancestral Rocky Mountains 

during the Tertiary period. Younger unconsolidated alluvial 

deposits of Quaternary age in hydraulic connection with the 

Tertiary deposits make up the High Plains aquifer in eastern 

and central Nebraska and Kansas. These Quaternary alluvial 

deposits are derived from erosion and redeposition of sediments from the Ogallala Formation (Gutentag and others, 

1984). The Quaternary alluvial deposits directly overlie the 

Ogallala Formation in many areas of the High Plains.

Regionally, the High Plains aquifer is considered an 

unconfined aquifer, but confined conditions can exist locally 

(Gutentag and others, 1984). The average saturated thickness 

of the aquifer is about 61 m with a maximum of about 366 

m (Gutentag and others, 1984; McGuire and others, 2003). 

Pumping from more than 130,000 wells (Sharon Qi, U.S. Geological Survey, oral commun., 2004) is the largest component 

of ground-water discharge. Ground water generally flows from 

west to east and discharges naturally to streams and springs 

and by evapotranspiration in areas where the water table is 

near land surface. Irrigation return flows, precipitation, and 

seepage from canals and reservoirs are the principal sources 

of recharge to the aquifer (Luckey and others, 1986; Dennehy 

and others, 2002). Substantial pumping of the High Plains 

aquifer for irrigation since the 1940s has resulted in waterlevel declines of nearly 46 m in some parts of the aquifer 

(McGuire and others, 2003). 

Ground-water quality in the High Plains aquifer is characterized as calcium- bicarbonate type water with dissolvedsolids concentrations generally less than 500 mg/L (Dennehy 

and others, 2002). Ground water is generally oxidized with 

dissolved-oxygen concentrations greater than 5.4 mg/L and 

pH ranges from 7 to 8 (Dennehy and others, 2002). Naturally 

occurring constituents in the ground-water system, which are 

derived from the water interaction with the sedimentary materials and are considered contaminants, include salinity, iron, 

manganese, fluoride, radon, uranium, and arsenic (Dennehy 

and others, 2002). Anthropogenic contaminants are the results 

of agricultural practices and include nitrate, pesticides, salinity, and carbon tetrachloride (Dennehy and others, 2002).

The Eastern High Plains regional study area is near 

York, Nebraska, in the eastern part of the High Plains aquifer. 

Ground water in the Eastern High Plains study area is present 

in Quaternary sand and gravel deposits, is used extensively 

for public water supply by the city of York, Nebraska, and is 

vulnerable to contamination because of the shallow depth to 

water and high permeability. Section 8 of this report presents 

the hydrogeologic setting, model setup, and modeling results 

for the Eastern High Plains regional study area.

Methods

The TANC regional studies consisted of implementing 

the following tasks:

•	 Compilation of retrospective water-quality, well-construction, water-use, and geologic data.

•	 Collection of ground-water samples from publicsupply wells in each study area in association with the 

NAWQA Source Water-Quality Assessment (SWQA) 

project.

•	 Development of a steady-state regional ground-water 

flow model to represent conditions for 1997–2001.

•	 Use of the regional ground-water flow model and 

advective particle tracking to compute the extent of the 
1–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

steady-state contributing recharge area and the zone 

of contribution for as many as 15 public-supply wells 

within each quartile of pumping for each modeled 

study area.

•	 Mapping of regional redox and pH conditions using the 

retrospective and newly collected SWQA water-quality 

data.

•	 Development of a TANC database to store retrospective 

data and modeling results.

The following sections present details of each task.

Retrospective Data Compilation

Existing water-quality, well-construction, water-use, and 

geologic data were compiled for each study area from the 

U.S. Geological Survey National Water Information System 

(NWIS), the U.S. Environmental Protection Agency STORET 

database, and State and local agencies. Data compilation 

focused on information for public-supply wells, but information from monitoring and domestic wells was included where 

available. Parameters within each data set were cross-checked 

and stored in a consistent manner to allow the data to be 

jointly evaluated. To support understanding of recent waterquality and water-use conditions, the period 1997–2001 was 

selected as the focus for the water-quality and water-use data 

compilation. If more than one water-quality analysis was available for a well, the most recent and complete analysis for the 

period 1997–2001 was saved in the database developed for the 

TANC study (discussed in “Database Development” section). 

In some instances, a well was not sampled for all water-quality 

parameters on any given date, and for these cases, the complete analysis stored in the database is a composite of the most 

recent analysis for each parameter.

Source Water-Quality Assessment Sample 

Collection

NAWQA Source Water-Quality Assessments (SWQA) 

consisted of sampling public-supply wells. In 2003 and 2004, 

SWQA studies were implemented in 10 NAWQA study units 

including the 7 TANC regional study areas discussed in this 

report. Between 8 and 31 public-supply wells were sampled 

in each study area, and samples were analyzed for a suite of 

natural and anthropogenic constituents including major ions 

(Fishman, M.J., and Friedman, 1989), nutrients (Fishman, 

1993), trace elements (Faires, 1993; Garbarino and others, 

2006), volatile-organic compounds (Connor and others, 1998; 

Rose and Sandstrom, 2003), pesticides (Zaugg and others, 

1995; Furlong and others, 2001; Sandstrom and others, 2001), 

and waste-water compounds (Zaugg and others, 2002). Results 

from the SWQA sampling are stored in the U.S. Geological Survey NWIS database (http://waterdata.usgs.gov/nwis,

accessed January 31, 2007) and the NAWQA Data Warehouse 

(http://infotrek.er.usgs.gov/travers/f?p=NAWQA:HOME:9108

424999420775073, accessed January 31, 2007).

Ground-Water Flow Simulation

As a process-based tool for understanding ground-water 

vulnerability, a steady-state ground-water flow model was 

developed or updated from existing models for each TANC 

regional study area. Ground-water flow was simulated using 

the U.S. Geological Survey’s modular finite-difference 

ground-water flow simulation code MODFLOW-2000 

(Harbaugh and others, 2000; Hill and others, 2000). Models 

were calibrated following the guidelines of Hill (1998) using 

water-budget estimates and water-level data for the period 

1997–2001 to facilitate comparisons of modeling results 

among study areas. Steady-state regional models and the 

particle-tracking program MODPATH (Pollock, 1994) were 

used to delineate areas contributing recharge and to compute 

advective traveltime through the aquifers for as many as 143 

public-supply wells within each study area. For study areas 

with more than 60 public-supply wells, at least 15 public-supply wells were selected for particle tracking from each quartile 

percentage of pumping. Model conceptualization, boundary 

conditions, calibration, and particle-tracking simulations for 

each regional study area are presented in Sections 2 through 7 

of this report.

MODPATH uses the cell-by-cell flow values calculated 

by MODFLOW to calculate the ground-water flow velocity 

distribution throughout the ground-water system, which is 

then used to determine flow paths of water particles moving 

through the aquifer (Pollock, 1994). Traveltimes along flow 

paths are computed by MODPATH using the magnitude of the 

cell-by-cell flows, porosity of the aquifer, and the model cell 

dimensions. MODPATH calculates advective ground-water 

flow only; the effects of mechanical dispersion and chemical reaction on ground-water transport are not included in the 

analysis. 

Particle-tracking simulations can outline the aquifer 

area contributing recharge to a pumping well and the aquifer 

volume composing the zone of contribution to a pumping well 

(fig. 1.3). The “area contributing recharge” is defined as the 

surface area of the ground-water system that delineates the 

location of water entering the ground-water system that eventually flows to the well and discharges. This area must provide 

an amount of recharge that balances the amount of water 

being discharged from the well (Franke and others, 1998). 

Thus, lower areal recharge rates result in larger contributing 

areas (Franke and others, 1998). The “zone of contribution” is 

the three-dimensional volumetric part of the aquifer through 

which ground water flows to the discharging well from the 

area contributing recharge. If the zone of contribution intercepts a surface-water body, the area contributing recharge is 

reduced and its size is a function of areal recharge rate and 

surface-water leakage (Franke and others, 1998). Depending 

on the screen placement of the well and local ground-water 
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–11

Figure 1.3. Area contributing recharge and zone of contribution for a single discharging well in a simplified hypothetical ground-water 

system.

General direction of ground-water flow

Lower bounding flowpath

Upper bounding flowpath

Screened

interval

Discharging

well

A R E A L R E C H A R G E 

W at er table

Z O N E

O F C O N T R I B U T I O N

A R E A L E X T E N T Z O N E O F C O N T R I B U T I O N

AREA CONTRIBUTING RECHARGE

flow conditions, the area contributing recharge to a well does 

not necessarily have to include the location of the well. The 

vertical projection of the zone of contribution to the land 

surface is termed the “areal extent of the zone of contribution” 

(USGS Office of Ground Water Technical Memorandum No. 

2003.02, http://water.usgs.gov/admin/memo/GW/gw03.02.

html, accessed June 15, 2004). Zones of contribution and their 

areal extents will always include the location of the well.

Because of the regional scale of the models used in this 

study, special consideration was given to the treatment of 

weak sinks in the determination of contributing areas. A weak 

sink is a model cell (representing a well, for example) with 

an insufficient discharge rate to capture all ground-water flow 

entering the cell; thus, some of the flow leaves the cell across 

one or more cell faces. Particle flow paths calculated for a 

weak-sink cell cannot be uniquely defined because it is impossible to know whether a specific water particle discharges to 

the weak sink or passes through the cell (Spitz, 2001). 

Weak sinks cause problems with associating a given 

amount of water with each particle. MODPATH offers three 

options for dealing with weak sinks. Particles can be stopped 

when they reach a weak sink, allowed to pass through weak 

sinks, or stopped if the percentage of flow entering the model 

cell that is captured by the weak sink exceeds a user-supplied 

threshold (Pollock, 1994). Table 1.2 shows the effects of the 

first two options. Effects of the third option would be some 

combination of the other two options.

The approach of grid refinement described by Spitz 

(2001) was used in TANC particle-tracking simulations to better represent particle movement through weak sinks (see discussions on weak sinks in preceding paragraphs and table 1.2). 

The grid-refinement approach creates a MODFLOW model 

of the weak-sink cell (fine model) so the cell containing the 

well becomes a strong sink. The boundaries of this fine model 

are set to a constant flux equal to the flow across each face 

as simulated in the original (coarse) model. The FORTRAN 

programs described by Spitz (2001) were altered to allow particles to be transferred from the coarse model to the fine model 

(to allow for forward particle tracking) and to allow the fine 

model to represent multiple layers from the coarse model (for 

the case where a well screen spans several model layers). 

A forward particle-tracking approach was used in the 

MODPATH simulations together with a grid-refinement 

program (Spitz, 2001) to delineate areas contributing recharge 

to public-supply wells (see discussions on weak sinks and 

grid-refinement approach). Particles were started on modelboundary cell faces for cells representing sources of water, 

forward tracked along path lines, and then were stopped when 
1–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

they reached a weak-sink cell. A fine model was constructed 

for each weak sink cell, particles were transferred from the 

coarse model to the fine model and tracked through the model, 

and then the particles that did not terminate in the fine model 

were transferred back to the coarse model. The remaining 

particles then were forward tracked again in the coarse model. 

This process was repeated until all particles reached a strong 

sink either in the coarse model or one of the fine models. 

MODPATH simulations of areas contributing recharge were 

initially run by starting particles on every boundary cell face 

of the model with a positive flux of water and tracking particles as previously described. For the final calculation of areas 

contributing recharge, the particle density for each well was 

adjusted so that between 100 and 1,500 particles were used to 

represent the contributing area. 

Contributing area results were used to create GIS datasets, which were subsequently used to determine a variety of 

attributes for each contributing area. The starting locations 

of particles on a given model-cell face were evenly distributed so a flow could be assigned to each particle equal to the 

total flow associated with the face divided by the number of 

particles started on the face. A traveltime also was associated 

with each particle. For particles associated with recharge from 

irrigation and(or) precipitation, properties of the landscape 

(data on land use, census, soils, and potential contaminant 

sources) were assigned to the particles. Path-line information 

was combined with descriptions of redox conditions, pH, and 

geology to determine the environments “experienced” by each 

particle on the way to the well. To determine average statistics 

for the entire contributing area, the properties for each particle 

were weighted by the percentage of the total flow to the well 

that they represented. A full list of the attributes calculated for 

the contributing areas is presented in Appendix 1. 

Table 1.2. Effects of weak sinks on the determination of contributing areas.

Water particles stop at weak sink Water particles pass through weak sink

Forward 

tracking

First weak sinks encountered can have 

too many particles, resulting in areas 

contributing recharge that are too large. 

Sinks (weak or strong) farther along the 

flow path may intercept too few particles, 

resulting in areas contributing recharge 

that are too small.

No particles associated with weak sink cells. 

Too many particles reach strong sinks, 

resulting in areas contributing recharge 

that are too large. Particles passing 

through weak sinks effectively lose flow.

Backward 

tracking

Difficulty in assigning starting particles for weak sinks. Particles that pass back through 

weak sinks are effectively gaining flow; the resulting area contributing recharge will be 

too large.

Oxidation-Reduction and pH Classification and 

Mapping

The oxidation-reduction (redox) state of ground water is 

an important geochemical control on the solubility and mobility of anthropogenic contaminants and naturally occurring 

trace elements. In aquifers where redox chemistry controls 

chemical reactions in the system, it is sometimes possible to 

define redox zones where a dominant redox couple controls 

the redox potential of the system (Domenico and Schwartz, 

1990). Numerous studies have deduced redox conditions in 

ground water on the basis of concentrations of electron acceptors, intermediate products, and accumulations of final products from terminal electron-accepting processes. However, 

the lack of an electron acceptor or final product accumulation 

does not always define the distribution of redox processes and 

is an admitted limitation of inferring redox state from redox 

indicator species. For example, a decrease in sulfate concentration and an increase in sulfide concentration would indicate 

a sulfate-reducing redox zone. However, a decrease in sulfate 

concentration may not be observed during sulfate reduction 

if there is a continuous source of sulfate to a system such as 

gypsum dissolution (Plummer and others, 1990). Similarly, an 

increase in sulfide concentration may not be observed if metal 

sulfides are precipitated during sulfate reduction. The measurement of hydrogen concentrations in ground water can be 

used in conjunction with patterns of electron-acceptor consumption and final-product accumulation to more accurately 

identify the distribution of terminal electron-accepting processes in ground-water systems (Chapelle and others, 1995). 

The TANC regional studies inferred aquifer redox conditions by using concentrations of redox-indicator species from 

the retrospective water-quality data. A redox-classification 

system was developed as discussed below, and a “redox environment consistent with redox indicator species” was assigned 

to each well location based on concentrations of dissolved 

oxygen, nitrate, manganese, iron, and sulfate (table 1.3). The 
Overview of Regional Studies of the Transport of Anthropogenic and Natural Contaminants to Public-Supply Wells 1–13

Table 1.3. Oxidation-reduction classification scheme.

[DO, dissolved oxygen; NO3, nitrate; Mn, manganese; Fe, iron; SO4, sulfate; mg/L, milligrams per liter; mg N/L, 

milligrams nitrogen per liter: μg/L, micrograms per liter; >, greater than; ≤, less than or equal to; —, not applicable]

Redox category assigned—

consistent with indicator

species concentrations

Redox indicator species significance level

DO

0.5 mg/L

NO3

0.5 mg N/L

Mn

50 μg/L

Fe

100 μg/L

SO4

4 mg/L

Oxygen reduction > > ≤ ≤ —

Nitrate reduction ≤ > ≤ ≤ —

Manganese reduction ≤ ≤ > ≤ —

Iron reduction with high sulfate ≤ ≤ > > >

Iron reduction with low sulfate ≤ ≤ > > ≤

discussed above. Furthermore, the assumption is made that 

oxidized forms of manganese and iron are available in the 

aquifer matrix so that manganese and iron are available for 

reduction. No assumptions are made about initial sulfate 

concentrations. In this classification system, oxygen-, nitrate-, 

and manganese-reducing conditions do not depend on sulfate 

concentrations. This allowance arises from the expectation that 

sulfate concentrations in recharge water commonly may be 

either greater than or less than the significance level for sulfate. However, the assumption is made that by the time redox 

conditions progress to iron-reducing conditions, sulfate will 

have become available from either recharge area sources or 

from various aquifer sources (e.g. Hem, 1985). This assumption facilitates the creation of high-sulfate and low-sulfate 

iron-reducing conditions. 

Examples of how the redox classification system was 

applied follow. If dissolved-oxygen and nitrate concentrations were greater than their respective significance levels, and 

manganese and iron concentrations were less than or equal 

to their respective significance levels, a redox classification 

was assigned consistent with oxygen reduction. If dissolvedoxygen, manganese, and iron concentrations were less than or 

equal to their respective significance levels, and nitrate concentration was greater than its respective significance level, a 

redox classification was assigned consistent with nitrate reduction. For the case of dissolved-oxygen, nitrate, and iron concentrations less than or equal to their respective significance 

levels, and manganese concentration greater than its respective 

significance level, a redox classification was assigned consistent with manganese reduction. With dissolved-oxygen and 

nitrate concentrations less than or equal to their respective significance levels, and manganese, iron, and sulfate concentrations greater than their respective significance levels, a redox 

classification was assigned consistent with iron reduction, high 

sulfate. Similar water, but with sulfate concentrations less than 

or equal to its significance level, would be assigned a redox 

classification consistent with iron reduction, low sulfate. If 

TANC redox classification system used five general categories 

to assign redox conditions to individual wells in the TANC 

regional study areas:

•	 Conditions consistent with oxygen reduction

•	 Conditions consistent with nitrate reduction

•	 Conditions consistent with manganese reduction

•	 Conditions consistent with iron reduction with high 

sulfate

•	 Conditions consistent with iron reduction with low 

sulfate

Concentration data for these redox-indicator species were 

commonly available in the retrospective data, and concentration significance levels were used to infer redox conditions for 

each well location. Hydrogen data were generally not available 

in the regional retrospective data set. Concentration significance levels for the redox-indicator species followed those 

presented by Chapelle and others (1995) for dissolved oxygen 

and nitrate, the Geological Survey of Sweden (http://www.

internat.environ.se/index.php3?main=/documents/legal/assess/

assedoc/gndwdoc/aqui.htm, accessed June 15, 2004) for manganese and iron, and Chapelle and others (2002) for sulfate. 

The sulfate significance level (4 mg/L) was chosen because 

Chapelle and others (2002) suggested the threshold sulfate 

concentration for sulfate reduction may be on the order of 4 

mg/L. Thus, once iron-reducing conditions have been achieved 

and sulfate concentrations drop below 4 mg/L, geochemical 

conditions likely have progressed well into, if not beyond, 

sulfate reduction. Such highly-reducing conditions may or 

may not correspond to methanogenic conditions, but likely 

do represent a low energy state that may have significance in 

geochemical investigations. 

For this redox classification system, the assumption 

is made that recharge water contains dissolved oxygen and 

nitrate at concentrations greater than the significance levels 
1–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

more than one redox category was assigned to a sample, the 

sample was categorized as having a “mixed” redox state.

Redox conditions were mapped at a regional scale using 

the redox categories assigned to each well, and the maps were 

discretized using the MODFLOW model grids to calculate 

traveltime through various redox environments. A wide range 

of available redox data and redox conditions was observed 

among TANC study areas, and the redox classification was 

reduced to two categories in the final particle-tracking analysis: 1) conditions consistent with oxygen or nitrate reduction, 

and 2) conditions consistent with manganese or iron reduction. The redox classification using retrospective data proved 

effective for delineating regional redox patterns in all study 

areas except the Northern Tampa Bay. Redox zones were 

not mapped for the Northern Tampa Bay regional study area 

because complex ground-water flow patterns in this karst aquifer resulted in no discernable redox pattern. 

The pH of ground water can be another important 

geochemical control on the mobility of naturally occurring 

trace elements and anthropogenic contaminants. For example, 

the adsorption of trace elements onto iron oxides is often a 

pH-dependent reaction. For the TANC regional study areas, 

ground-water pH values were grouped into two categories: pH 

values less than 8 (circumneutral), and pH greater than 8 (high 

pH). A pH of 8 was chosen, in part, on the basis of the zero 

point of charge for iron oxide being roughly 8 (Stumm and 

Morgan, 1981).

Database Development

To conduct a more process-oriented national assessment of the susceptibility and vulnerability of aquifers and 

public-supply wells than has been previously possible and 

to complement earlier work such as the U.S. Environmental 

Protection Agency’s review of contaminant occurrence in 

public-water systems (U.S. Environmental Protection Agency, 

1999), TANC data and results were organized using relationaldatabase software. Information in the TANC database includes 

retrospective water-quality data, well-construction data, wateruse data, geologic data, SWQA water-quality data, groundwater flow model and particle-tracking results, potential 

contaminant sources within the area contributing recharge of 

selected public-supply wells, and geochemical classifications 

of redox and pH. Many of the data-field definitions in the 

TANC database follow those in the U.S. Geological Survey 

NWIS database. However, several additional data tables and 

fields were added to accommodate modeling results, which 

cannot be stored in NWIS. The TANC database structure is 

such that additional tables can be added as data collection and 

analyses proceed.

The database currently (2006) consists of 10 data tables 

generally linked by a combination of NAWQA TANC Study 

Unit code and U.S. Geological Survey Site Identification (ID) 

number, which forms a unique identification number assigned 

to each well location. Appendix 1 contains data dictionaries for the TANC data tables. The TANC_STUDIES table 

contains summary information about each TANC study area 

such as its start date, overall location, area, and general aquifer 

characteristics. The SITES table contains information specific 

to each sampling location such as U.S. Geological Survey Site 

ID, local station name, location, altitude, and site use, and 

the WELL_INFO table contains well-completion details. The 

RESULTS_RGNL table contains water-quality analysis results 

for the regional study areas, and the PARAMETERS table 

contains parameter-code definitions for the RESULTS_RGNL 

table. The PUMPING_RGNL table stores information about 

all pumping centers simulated in each of the TANC regional 

ground-water flow models. Four tables contain ground-water 

particle-tracking results and geochemical interpretations. The 

ANCILLARY table includes the geochemical interpretations 

of redox conditions as previously discussed in the “Redox and 

pH Classification and Mapping” section. The CAREASUM_

RGNL table contains contributing area and traveltime information for each well calculated from the regional ground-water flow models, as previously discussed in the “Ground-Water 

Flow Simulation” section, and the CAREARDXPH_RGNL 

table contains tabulations of ground-water traveltime through 

redox and pH zones. The CAREASRCE_RGNL table contains 

a tabulation of the land use, population density, and potential 

contaminant sources overlying contributing areas.

At the completion of initial data compilation (2003), 

nearly 196,000 water-quality records from 2,242 sampling 

locations were included in the TANC database; 129 of these 

locations had new water-quality data collected as part of the 

NAWQA SWQA project. Contributing areas were calculated 

for 405 public-supply wells, and water-quality data were 

stored in the TANC database for 321 of the 405 public-supply 

wells with calculated contributing areas.

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37 p.

Hydrogeologic Setting and Ground-Water 

Flow Simulations of the Salt Lake Valley 

Regional Study Area, Utah

By Bernard J. Stolp

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 2 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

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natural hazards, and the environment:

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Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Stolp, B.J., 2007, Hydrogeologic setting and ground-water flow simulations of the Salt Lake Valley Regional Study 

Area, Utah, section 2 of Paschke, S.S., ed., Hydrogeologic settings and ground-water flow simulations for regional 

studies of the transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 2001: 

Reston, Va., U.S. Geological Survey Professional Paper 1737–A, pp. 2–1 – 2–22.
iii

Contents

Abstract...................................................................................................................................................... 2–1

Introduction................................................................................................................................................ 2–1

Purpose and Scope ......................................................................................................................... 2–1

Study Area Description................................................................................................................... 2–4

Topography and Climate ........................................................................................................ 2–6

Surface-Water Hydrology ..................................................................................................... 2–6

Land Use................................................................................................................................... 2–6

Water Use ................................................................................................................................ 2–6

Conceptual Understanding of the Ground-Water System................................................................. 2–6

Geology.............................................................................................................................................. 2–6

Ground-Water Occurrence and Flow........................................................................................... 2–7

Aquifer Hydraulic Properties ......................................................................................................... 2–9

Water Budget ................................................................................................................................... 2–9

Recharge.................................................................................................................................. 2–9

Discharge............................................................................................................................... 2–10

Ground-Water Quality ................................................................................................................... 2–11

Ground-Water Flow Simulations .......................................................................................................... 2–11

Modeled Area and Spatial Discretization.................................................................................. 2–11

Boundary Conditions and Model Stresses................................................................................ 2–14

Recharge................................................................................................................................ 2–14

Discharge............................................................................................................................... 2–14

Model Calibration and Sensitivity ............................................................................................... 2–16

Model-Computed Hydraulic Heads ................................................................................... 2–16

Model-Computed Water Budget........................................................................................ 2–16

Simulation of Areas Contributing Recharge to Wells .............................................................. 2–17

Limitations and Appropriate Use of the Model......................................................................... 2–17

References Cited..................................................................................................................................... 2–22

Figures

Maps showing:

2.1. Location of the Salt Lake Valley regional study area within the

Basin and Range basin-fill aquifers. .....................................................................2–2

2.2. Topography, hydrologic features, and location of publicsupply wells, Salt Lake Valley regional study area, Utah.................................2–3

2.3. Generalized block diagram showing the basin-fill ground-water flow system, 

Salt Lake Valley regional study area, Utah..................................................................... 2–7

Maps showing:

2.4. Elevation of model-computed basin-fill aquifer potentiometric surface 

for 1997–2001 average conditions, Salt Lake Valley regional study area, 

Utah. ............................................................................................................................2–8
iv

2.5. Generalized oxidation-reduction classification zones, Salt Lake Valley 

regional study area, Utah...................................................................................... 2–12

2.6. Ground-water flow model grid and selected boundary conditions, 

Salt Lake Valley regional study area, Utah........................................................ 2–13

2.7. Distribution of basin-fill aquifer transmissivity for the calibrated groundwater flow model, Salt Lake Valley regional study area, Utah...................... 2–18

2.8. Water-level observation well locations and head residuals, 

Salt Lake Valley regional study area, Utah........................................................ 2–19

Graphs showing

2.9. Relation between model-computed and measured hydraulic head, 

Salt Lake Valley regional study area, Utah........................................................2–20

2.10. Relation between head residual and measured hydraulic head, 

Salt Lake Valley regional study area, Utah........................................................2–20

2.11. Map showing model-computed areas contributing recharge to

public-supply wells, Salt Lake Valley regional study area, Utah. ............................. 2–21

Tables

2.1. Summary of hydrogeologic and ground-water quality characteristics for 

the Basin and Range basin-fill aquifers and the Salt Lake Valley regional 

study area, Utah.................................................................................................................. 2–4

2.2. Model-computed water budget for 1997–2001 average conditions, 

Salt Lake Valley regional study area, Utah................................................................... 2–15
Hydrogeologic Setting and Ground-Water Flow Simulation 

of the Salt Lake Valley Regional Study Area, Utah

By Bernard J. Stolp

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated in the Salt Lake Valley, 

Utah, as part of the U.S. Geological Survey National WaterQuality Assessment Program. The valley-fill aquifer in the 

Salt Lake Valley regional study area is representative of the 

Basin and Range basin-fill aquifers, is an important source of 

water for agricultural irrigation and public water supply, and 

is susceptible and vulnerable to contamination. An existing 

seven-layer, transient ground-water flow model of the Salt 

Lake Valley was converted to a steady-state model representative of average conditions for the period 1997–2001. The 

steady-state model and advective particle-tracking simulations were used to compute ground-water flow paths, areas 

contributing recharge, and traveltimes from recharge areas for 

94 wells. Model results indicate recharge from the surrounding mountain block (43.8 percent of inflow) and precipitation 

plus irrigation (39.5 percent of inflow) provide the majority of 

ground-water inflow to the study area. Inflow from rivers and 

canals provides the remaining inflow. Ground-water discharge 

is primarily to wells (49.4 percent of outflow) and the Jordan 

River (28.3 percent of outflow) with the remainder of groundwater outflow going to evapotranspiration, springs, drains, and 

the Great Salt Lake. The model-computed areas contributing 

recharge reached to the edges of the modeled area indicating mountain-front and mountain-block recharge from the 

Wasatch Range on the east and the Oquirrh Mountains on the 

west contributes water to public-supply wells in the Salt Lake 

Valley study area. The simulated median traveltime for ground 

water to flow from its recharge point to a well ranged from 5 

to 780 years. The longest traveltimes are associated with contributing areas for wells on the west side of Salt Lake Valley.

Introduction

The Salt Lake Valley regional study area for the transport 

of anthropogenic and natural contaminants to public-supply 

wells (TANC) study is on the western edge of the 37,500-km2

Great Salt Lake Basins study unit of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) program 

(fig. 2.1). The Salt Lake Valley is located west of the Wasatch 

Range (fig. 2.2) and is the metropolitan and industrial center 

of the State of Utah. Ground water exists in the unconsolidated 

and semiconsolidated basin-fill materials of the valley and 

is used extensively for water supply in and around Salt Lake 

City, Utah.

Purpose and Scope

The purpose of this Professional Paper section is to present the hydrogeologic setting of the Salt Lake Valley regional 

study area. The section also documents a steady-state regional 

ground-water flow model for the study area. Ground-water 

flow characteristics, pumping-well information, and waterquality data were compiled from existing data to develop a 

conceptual understanding of ground-water conditions in the 

study area. A seven-layer transient ground-water flow model 

of the Salt Lake Valley basin-fill aquifer was converted to a 

steady-state model to represent average conditions for the 

period from 1997 to 2001. The 5-year period 1997–2001 

was selected for data compilation and modeling exercises 

for all TANC regional study areas to facilitate future comparisons between study areas. The steady-state ground-water 

flow model and associated particle tracking were used to 

simulate advective ground-water flow paths and to delineate 

areas contributing recharge to selected public-supply wells. 

Ground-water traveltimes from recharge to public-supply 

wells, oxidation-reduction (redox) conditions along flow 

paths, and presence of potential contaminant sources in areas 

contributing recharge were tabulated into a relational database 

described in Section 1 of this Professional Paper. This section 

provides the foundation for future ground-water susceptibility 

and vulnerability analyses of the study area and comparisons 

among regional aquifer systems.
2–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 2.1. Location of the Salt Lake Valley regional study area within the Basin and Range basin-fill aquifers.

N E W

M E X I C O

Great

Salt

Lake

A R I Z O N A

U T A H COLORADO

N E V A D A

C A L I F O R N I A

O R E G O N

I D A H O

W Y O M I N G

P A C I F I C

O C E A N

M E X I C O

Gulf of

California

Salt Lake City

Phoenix

San Diego

Los Angeles

Las Vegas

Sacramento

Reno

122° 121° 120° 119° 118° 117° 116° 115° 114° 113° 112° 111° 110° 109° 108° 107° 106° 

43° 

42° 

41° 

40° 

39° 

38° 

37° 

36° 

35° 

34° 

33° 

32° 

31° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 50 100 150 200 kilometers

0 50 100 miles

EXPLANATION

Salt Lake Valley regional study area

Basin and Range aquifer

USGS NAWQA study unit—Great Salt Lake Basins
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–3

Figure 2.2. Topography, hydrologic features, and location of public-supply wells, Salt Lake Valley regional study area, Utah.

65

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River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS

0 5 10 MILES

EXPLANATION

Land elevation, in meters above sea level

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley

Fault

Public-supply well

3600

3200

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2400

2000

1600

1200

800

400

0
2–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Study Area Description

The Salt Lake Valley regional study area is located in the 

Basin and Range basin-fill aquifers, which are ranked fourth in 

total water use of the 62 principal aquifers in the United States 

(Maupin and Barber, 2005). The Salt Lake Valley regional 

study area is representative of the Basin and Range basin-fill 

aquifers (table 2.1) with ground water occurring in the basinfill deposits of the valley.

Table 2.1. Summary of hydrogeologic and ground-water-quality characteristics for the Basin and Range basin-fill aquifers and the 

Salt Lake Valley regional study area, Utah.

[m, meters; cm/yr, centimeters per year; hm3/yr; cubic hectometers per year; m2/d, squared meters per day; m3/d, cubic meters per day; m/d, meters per day; 

ET, evapotranspiration; mg/L, milligrams per liter]

Characteristic Basin and Range basin-fill aquifers Salt Lake Valley regional study area

Geography

Topography Altitude ranges from about 46m at Yuma, Arizona 

to over 3,048 m at the crest of some mountain 

ranges (Robson and Banta, 1995). 

Valley floor altitude slopes from 1,280 m near Great 

Salt Lake to about 1,580 m on the foothills of 

Wasatch and Oquirrh Mountains. 

Climate Arid to semi-arid climate. Precipitation ranges from 

10 to 20 cm/yr in basins and 40 to 76 cm/yr in 

mountains (Robson and Banta, 1995).

Semi-arid climate. Precipitation in valley ranges from 

30 cm/yr to almost 50 cm/yr. Precipitation exceeds 

130 cm/yr in surrounding mountains.

Surface-water hydrology Streams drain from surrounding mountains into 

basins. Basins generally slope toward a central 

depression with a main drainage that is dry most 

of the time. Many basins have playas in their 

lowest depressions. 

Ground-water discharge to streams can occur in 

basin depressions. (Planert and Williams, 1995)

Jordan River is the major stream in Salt Lake 

Valley with tributaries originating in the Wasatch 

Mountains. Diversions on Jordon River supply 

irrigation water. Small streams originating in 

Oquirrh Mountains infiltrate before reaching the 

Jordan River.

Land use Undeveloped basins are unused, grazing, and rural 

residential. Developed basins are urban, suburban 

and agricultural.

Urban, suburban, rural residential, and agricultural.

Water use Ground-water withdrawals from wells supply 

water for agricultural irrigation and municipal 

use. Population increases since the 1960’s have 

increased the percentage of water being used for 

municipal supply.

Approximately 70 percent of total water use is from 

ground water and 30 percent from surface water. 

Total ground-water withdrawal estimated for 

1997–2001 is about 500,000 m3/d with 30 percent 

applied to household use and 70 percent applied to 

lawn and agricultural irrigation.

Geology

Surficial geology Tertiary and Quaternary unconsolidated to 

moderately consolidated fluvial gravel, sand, silt 

and clay basin-fill deposits include alluvial fans, 

flood plain deposits, and playas. (Robson and 

Banta, 1995; Planert and Williams, 1995)

Tertiary and Quaternary unconsolidated fluvial basinfill sediments consist of gravel, sand, silt, clay, 

tuff, and lava interbedded with lacustrine deposits 

of historical Lake Bonneville.

Bedrock geology Mountains surrounding basins are composed of 

Paleozoic to Tertiary bedrock formations. Tertiary 

volcanic and metamorphic rocks are in general 

impermeable. Paleozoic and Mesozoic carbonate 

rocks are cavernous allowing inter-basin flow in 

some areas. (Robson and Banta, 1995; Planert 

and Williams, 1995) 

Wasatch Mountains east of Salt Lake Valley are 

composed of Paleozoic and Precambrian quartzites 

and crystalline rocks. Oquirrh Mountains west of 

Salt Lake Valley are composed of Tertiary volcanic 

rocks and associated sulfide mineralization.
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–5

Characteristic Basin and Range basin-fill aquifers Salt Lake Valley regional study area

Ground-water hydrology

Aquifer conditions Unconfined basin-fill aquifers surrounded by 

relatively impermeable bedrock mountains and 

foothills. Basin ground-water flow systems are 

generally isolated and not connected with other 

basins except in some locations where basins are 

hydraulically connected via cavernous carbonate 

bedrock.

Unconfined basin-fill aquifer along basin margins, 

which transitions to confined basin-fill aquifer 

under the central and northern parts of Salt Lake 

Valley because of the shallow confining layer. 

Confined aquifer is composed of interbedded 

clays, silts, sands, and gravels. Ground-water flow 

is from valley margins toward central and northern 

valley and upward toward discharge area along the 

Jordan River.

Hydraulic properties Transmissivity ranges from less than 93 m2/d to 

greater than 2,790 m2/d. In general, alluvial fan 

deposits near basin margins are more conductive 

than flood plain and lacustrine deposits near basin 

centers. (Robson and Banta, 1995; Planert and 

Williams, 1995)

Transmissivity ranges from less than 930 m2/d 

to more than 4,600 m2/d (Lambert, 1995a). 

Horizontal hydraulic conductivity ranges from 

3.05 X 10-4 to 19.8 m/d (Thiros, 1992). Vertical 

hydraulic conductivity ranges from 1.6 X 10-5 to 

6.1 X 10-3 m/d (Thiros, 1992).

Ground-water budget Recharge to basin fill deposits is from surfacewater runoff in mountains where precipitation 

is highest. Ground-water discharges naturally 

as evapotranspiration (ET) to playas and stream 

channels in basin depressions. Ground-water 

withdrawal from wells is largest component 

of discharge from Basin and Range aquifers. 

(Robson and Banta, 1995)

Recharge to basin fill is from subsurface inflow 

from surrounding mountains, local precipitation, 

seepage from streams, and infiltration from 

irrigation. Discharge is to streams (Jordan River), 

wells, ET, springs, drains, and the Great Salt Lake. 

Ground-water quality

Water quality varies between basins. Dissolved 

solids can range from less than 500 mg/L to over 

35,000 mg/L. Generally, low-dissolved solids, 

oxic water occurs near recharge areas of basin 

margins. High-dissolved solids anoxic water 

occurs with depth or near basin centers and playa 

lakes (Robson and Banta, 1995; Planert and 

Williams, 1995).

Dissolved solids are lowest along the eastern basin 

margins (200 to 500 mg/L) where calciumbicarbonate type water dominates. Dissolved solids 

along the western margin ranges from 400 to 

1,100 mg/L, and the water type is calcium-sulfate 

because mountains west of valley are volcanic 

rocks with sulfide mineralization. Dissolved solids 

concentrations increase and water type transitions 

to sodium-chloride from south to north in the 

valley. Water near valley margins is generally oxic 

with redox conditions transitioning to anoxic near 

the valley center.

Table 2.1. Summary of hydrogeologic and ground-water-quality characteristics for the Basin and Range basin-fill aquifers and the 

Salt Lake Valley regional study area, Utah.—Continued

[m, meters; cm/yr, centimeters per year; hm3/yr; cubic hectometers per year; m2/d, squared meters per day; m3/d, cubic meters per day; m/d, meters per day; 

ET, evapotranspiration; mg/L, milligrams per liter]
2–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Topography and Climate

The Salt Lake Valley is almost 1,300 km2 in area, trends 

from south to north, and terminates on its northern end at the 

Great Salt Lake. The Wasatch Range bounds the valley on the 

east, and the Oquirrh and Traverse Mountains bound the valley 

on the west-southwest (fig. 2.2). The valley floor slopes gradually up from an elevation of 1,280 m near Great Salt Lake 

to about 1,580 m on the foothills of the Wasatch Range and 

Oquirrh and Traverse Mountains. Elevations in the Wasatch 

Range exceed 3,300 m. The Oquirrh and Traverse Mountains 

are not as extensive as the Wasatch Range, and the upper 

elevations are around 2,900 m.

The Salt Lake Valley is classified as semiarid, and average annual precipitation ranges from about 35 cm/yr in the 

northwest and central parts of Salt Lake Valley to about 60 

cm/yr along the foothills of the Wasatch Range (Prism Group, 

Oregon State University, 2006). Precipitation in the surrounding mountain areas can exceed 130 cm/yr and occurs mainly 

as snowfall during the winter months. March and April are 

the wettest months of the year. Average daytime temperatures 

range from 33.6 ̊C in July to 3.1 ̊C in January.

Surface-Water Hydrology

The major stream in the Salt Lake Valley is the Jordan 

River (fig. 2.2), which flows north along the axis of the valley and discharges to the Great Salt Lake. Flow in the Jordan 

River is diverted through seven major canals as it enters the 

south end of Salt Lake Valley to feed an extensive surfacewater irrigation system. The Jordan River has seven major tributaries, all of which originate in the Wasatch Range. Several 

small streams originate in the Oquirrh and Traverse Mountains 

but none reach the Jordan River.

Land Use

Land in the Salt Lake Valley was historically used for 

agriculture, which included grazing, orchards, dry farming, 

and irrigated cultivation. As population grew and commercial 

activities increased, agricultural lands have slowly converted 

to residential and commercial use. The population in Salt 

Lake Valley more than doubled between 1963 and 2001. As of 

2002, land use in the valley is categorized as 39 percent residential, 29 percent commercial/industrial, 21 percent water/

riparian/idle, and 11 percent agricultural (Utah Department of 

Natural Resources, 2003).

Water Use

Most water use in the Salt Lake Valley in 2000 was for 

domestic purposes. An estimated 30 percent of the domestic 

water supply goes toward household uses, and about 70 percent of the domestic water supply is used for lawn watering. 

About 70 percent of the domestic water supply is from surface 

water, and the remaining 30 percent comes from public-supply 

wells located throughout the valley (Lawrence Spangler, U.S. 

Geological Survey, written commun., September 2005) 

(fig. 2.2).

Conceptual Understanding of the 

Ground-Water System

The hydrogeology of the Salt Lake Valley has been 

closely scrutinized since the middle of the 20th century 

(Marine and Price, 1964; Hely and others, 1971; Waddell and 

others, 1987; Thiros, 1992 and 1995; and Lambert, 1995a). 

Those discussions, particularly Lambert (1995a), are paraphrased and summarized in the following sections.

Geology

The ground-water system underlying the Salt Lake Valley 

exists in unconsolidated and semiconsolidated basin-fill material. The source of basin fill is the surrounding mountains. The 

depositional basin was created by a downward rotation of the 

consolidated-rock base of the valley relative to the Wasatch 

Range. The thickness of the unconsolidated basin fill averages 

about 600 m and in some places exceeds 1,200 m.

The basin-fill material consists mostly of Tertiary- and 

Quaternary-age clay, silt, sand, gravel, tuff, and lava. The 

depositional history of these sediments is extremely complex 

(Marine and Price, 1964). In the late Pleistocene (10,000 to 

25,000 years ago), changes in regional climate and topography 

created conditions that led to numerous cycles of inundation and subsequent desiccation of the Salt Lake Valley by a 

series of ancient lakes. The most extensive and recent ancient 

lake was Lake Bonneville. As the valley filled with water, 

lacustrine and deltaic depositional mechanisms dominated. 

As lakes dried, these sediments were reworked and redeposited by stream erosion. Previously inundated areas were 

eroded and received stream-channel and flood-plain deposits. 

Alluvial fans formed along the mountain fronts at canyon 

mouths; glacial and mud-rock flow deposits also were laid 

down at the valley margins. As lakes reappeared and filled 

the valley, lacustrine deposition again predominated. These 

cyclic changes in the depositional environment resulted in the 

interlayered lacustrine, alluvial, and glacial sediments that 

compose the basin fill. Generally, coarse-grained sediments 

are common near the mountains, and finer grained sediments 

are dominant in the low-lying areas in the central and northern 

parts of the valley.

The consolidated rock of the Wasatch Range consists 

mainly of Precambrian and Paleozoic quartzites, tillites, and 

carbonates. Where the range borders the southeastern Salt 

Lake Valley, the consolidated rock is Tertiary-age quartz monzonite. The Oquirrh and Traverse Mountains consist of Paleo-
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–7

zoic-age quartzite and limestone. Volcanism occurred during 

the Oligocene Period and resulted in sulfide mineralization.

Ground-Water Occurrence and Flow

A generalized conceptual model of the saturated basinfill material consists of (1) a confined aquifer underlying 

the central and northern parts of the Salt Lake Valley that 

transitions to unconfined conditions along the margins of the 

valley (hereinafter called the basin-fill aquifer), (2) a shallow 

confining layer that overlies the basin-fill aquifer in the center 

of the valley, and (3) shallow, unconfined ground water above 

the shallow confining layer (fig. 2.3). The basin-fill aquifer is 

composed of interbedded clay, silt, sand, and gravel and exists 

within the discontinuous and interconnected lenses of sand 

and gravel. The confining layer is composed of finer grained, 

lower permeability materials than the underlying basin-fill 

aquifer. The top of the shallow confining layer generally lies 

within 30 m of land surface. Along the margins of the valley, the higher energy depositional environment deposited 

coarse-grained sediment, and the ground-water system in these 

areas is conceptualized as a single, deeper unconfined aquifer 

without vertical stratification. Ground water is withdrawn from 

wells completed in both the confined basin-fill aquifer beneath 

the shallow confining layer and the unconfined basin-fill aquifer near the margins of the valley.

The Salt Lake Valley basin-fill aquifer exists primarily 

in the Quaternary-age basin-fill material that ranges from 0 to 

600 m thick. Quaternary-age material generally overlies relatively impermeable, semiconsolidated sediments of Tertiary 

and pre-Tertiary age (Arnow and others, 1970, p. D257). In 

scattered areas, the Tertiary-age basin fill is more permeable 

and yields small amounts of ground water to wells. Where the 

Tertiary-age sediments yield water, they are considered part of 

the basin-fill aquifer.

Ground water flows laterally from the primary recharge 

areas at the valley margins to the center and northern parts 

of the valley (fig. 2.4). An upward gradient is established 

between the confined aquifer and the unconfined aquifer as 

water moves laterally beneath the confining layer. In the central part of the valley, ground water flows upward in the confined aquifer, through the overlying confining layer and into 

the shallow unconfined aquifer. From the shallow unconfined 

aquifer, water discharges primarily into the Jordan River, to 

drains, and is used by riparian vegetation, or evaporates at land 

surface. Ground water along the valley margins is generally 30 

Figure 2.3. Basin-fill ground-water flow system, Salt Lake Valley regional study area, Utah.

Deeper confined aquifer

Perched

water table

Deeper

unconfined

aquifer

Shallow

aquifer

Water level in

shallow aquifer

Water level

in deeper

confined aquifer

Confining layer

Not to scale

Water level in deeper

unconfined aquifer

Modified from Hely and others, 1971

Discharge

area

Secondary recharge area

Primary

recharge

area Precipitation Precipitation

Fault

EXPLANATION

Principal aquifer

 Coarse-grained deposits

 Fine-grained deposits

Basin-fill deposits of Tertiary age

Consolidated rock

Ground-water flow direction
2–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 2.4. Elevation of model-computed basin-fill aquifer potentiometric surface for 1997–2001 average conditions, Salt 

Lake Valley regional study area, Utah.

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Mill Creek

Big

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Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS After Lambert, 1995a, fig. 25

0 5 10 MILES

EXPLANATION

Potentiometric contour—Model-computed line of equal steady-state 

 potentiometric surface, in meters. Contour interval is 50 meters. 

 Datum is sea level

Approximate direction of horizontal ground-water flow

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley

1350
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–9

to 100 m below land surface. In the central and northern areas, 

water levels are usually 3 to 6 m below land surface.

Aquifer Hydraulic Properties

Hydraulic properties of aquifer materials were determined using a number of standard techniques that include 

(1) ground-water gradients and discharge, (2) slug tests, (3) 

laboratory testing of core samples, (4) aquifer tests, and (5) 

specific-capacity data. Generally, these methods test only 

small intervals and volumes of the aquifer, and quantification 

commonly produces results that vary over several orders of 

magnitude. This range of aquifer hydraulic properties is not 

surprising and reflects the complex depositional history of the 

Salt Lake Valley.

Horizontal hydraulic conductivity for the shallow unconfined aquifer is estimated to range from 9.1 X 10–4 to 19.8 m/d 

(Thiros, 1995), and horizontal hydraulic conductivity for the 

confining layer is estimated to range from 1.2 X 10–4 to 0.7 

m/d (S.A. Thiros, U.S. Geological Survey, written commun., 

1993). Vertical hydraulic conductivity of the shallow confining layer ranges from 1.6 X 10–5 to 0.3 m/d (Hely and others, 

1971; Waddell and others, 1987; Thiros, 1992; Thiros, 1995). 

Transmissivity of the basin-fill aquifer is estimated to range 

from less than 930 to more than 4,600 m2/d (Lambert, 1995a). 

Hydraulic conductivity, which equals transmissivity divided 

by saturated thickness of the aquifer, was given an upper 

limit of 70 m/d on the basis of reported hydrologic properties 

for aquifers of the Basin and Range Province (Bedinger and 

others, 1986). Vertical hydraulic conductivity of the basin-fill 

aquifer is estimated to range from 0.003 to 1.5 m/d (Lambert, 

1995a, p. 17 and fig. 8).

Storage-coefficient values in confined zones of the Salt 

Lake Valley are estimated to range from 1 X 10–3 to less than 1 

X 10–4 (Hely and others, 1971). The range of probable storagecoefficient values for confined zones of the basin-fill aquifer 

was assumed also to apply to the storage-coefficient value of 

the shallow confining layer. Hely and others (1971) estimated 

that specific yield of the shallow unconfined aquifer ranges 

from 0.10 to 0.20 and that specific yield of unconfined basinfill aquifer near the basin margins has an upper limit of 0.3.

Water Budget

Recharge to the ground-water system in the Salt Lake 

Valley is primarily from (1) subsurface inflow from consolidated rock at the margins of the valley; (2) infiltration of 

precipitation on the valley floor; (3) seepage from streams 

and canals; and (4) infiltration from commercial crop fields, 

lawns, and gardens. Discharge occurs to (1) streams and 

canals, (2) pumping and flowing wells, (3) evapotranspiration, 

(4) springs, (5) drains, and (5) Great Salt Lake. Recharge and 

discharge quantities were originally estimated by Hely and 

others (1971) for conditions during 1964 through 1968. Since 

then, components of the water budget have been reevaluated because of additional data collection and interpretation 

(Herbert and others, 1985; Waddell and others, 1987; Lambert, 

1995a). The conceptual water budget presented here is a combination of previously estimated water budgets and scaling of 

water-budget components determined from the 1969–91 transient ground-water flow model calibration (Lambert, 1995a, 

p. 21) to 1997–2001 conditions on the basis of precipitation 

and streamflow ratios. Given the various timeframes, the complexity of the ground-water system, and the density of available data, individual components of the budget are probably 

only accurate to within +/– 25 percent. Conceding these limitations, the conceptual budget described here is presented as a 

1997–2001 average and is considered a steady-state portrayal 

because ground-water pumping rates and climatic conditions 

were relatively stable for the time period.

Recharge

The movement of ground water from the fractures, joints, 

and pore space of the mountain block into the adjacent basin 

fill (mountain-block recharge) recharges the aquifer at an 

estimated rate of approximately 402,000 m3/d for 1997–2001. 

This rate was computed using a long-term average water 

balance for the mountains and measured hydraulic gradients 

at the margins of the valley. It is scaled to 1997–2001 conditions by using the ratio of 1997–2001 average Wasatch Range 

precipitation to the long-term average Wasatch Range precipitation. Inflow is distributed along the mountain front on 

the basis of the inferred relative permeability of the different 

consolidated rock units (Hely and others, 1971, table 21; 

Waddell and others, 1987, table 1).

Recharge from infiltration of precipitation on the valley 

floor was estimated to be about 257,000 m3/d for 1997–2001. 

The 1997–2001 recharge rate is scaled from a long-term 

estimate by using the ratio of average 1997–2001 precipitation 

rate to the long-term precipitation rate in the Salt Lake Valley. 

The long-term estimate was derived by subtracting the sum of 

surface runoff and precipitation consumed by evapotranspiration from the total precipitation falling on the valley (Hely 

and others, 1971, table 21; Waddell and others, 1987, table 1; 

Lambert, 1995a, table 5).

Mountain-front recharge occurs where mountain streams 

enter the Salt Lake Valley and lose surface water to the coarser 

grained basin-fill material at the canyon mouths. Ground water 

moving laterally through the channel fill beneath the streams 

(underflow) also contributes recharge to adjoining basin-fill 

material at canyon mouths. In addition, recharge from underflow occurs where the Jordan River enters the southern end 

of the Salt Lake Valley. On the basis of data collected by 

Hely and others (1971, p. 123 and table 5) and modifications 

by Lambert (1995a, table 5), the annual recharge rate from 

streams and underflow for 1997–2001 is estimated to be about 

60,800 m3/d. Surface-water seepage losses were established 

from data collected at multiple streamflow-gaging stations on 

individual streams. Estimates of underflow were determined 

using Darcy’s law. In addition to streams, there is also seep-
2–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

age from the major irrigation canals in the valley. On the basis 

of gain/loss measurements made in 1983 (Herbert and others, 

1985), recharge from the canals is estimated at about 94,500 

m3/d. Total recharge from streams and canals is estimated as 

155,300 m3/d.

Infiltration from agricultural irrigation return flow during 

1997–2001 was estimated to be about 108,000 m3/d on the 

basis of historical estimates (Hely and others, 1971, p. 126) 

and modifications by Lambert (1995a, p. 37). Infiltration from 

irrigation of lawns and gardens is estimated to be about 33,700 

m3/d (Lambert, 1995a, p. 33). Historical estimates (Hely 

and others, 1971) assumed recharge rates that were about 

30 percent of the applied irrigation water and were based on 

generalized field-application efficiency rates and a series of 

site-specific farm studies. The more recent recharge estimates 

are close to 15 percent of the applied irrigation water (Lambert, 1995a).

Discharge

The largest component of natural discharge from the 

aquifer system in the Salt Lake Valley is seepage to the Jordan 

River and the lower reaches of its principal tributaries. Based 

on records from an extensive streamflow-gaging network, 

Hely and others (1971, p. 83 and 136) estimated annual 

ground-water discharge from the confined part of the basin-fill 

aquifer to the Jordan River and its tributaries to be 500,000 

m3/d. The average rate of ground-water discharge to canals in 

the valley is estimated as 33,700 m3/d and is based on gain/

loss measurements made by Herbert and others (1985) and 

adjusted to average climatic conditions by Waddell and others 

(1987, p. 27). The relation between the aquifer and streams/

canals in the central parts of the valley has been fairly stable 

over time, and the previous analysis of discharge is likely a 

reasonable estimate of discharge for 1997–2001.

Ground water is withdrawn from wells in the Salt Lake 

Valley for the purposes of public supply, irrigation, industrial, 

and domestic/stock uses. The average withdrawal for all these 

purposes for 1997–2001 is estimated as 500,000 m3/d for the 

Salt Lake Valley regional study area. Withdrawals for publicsupply, irrigation, and industrial uses is estimated as about 

399,000 m3/d and is based on annual withdrawal compilations 

made by the U.S. Geological Survey. The remaining withdrawals, 101,000 m3

/d, are from thousands of small domestic 

and stock wells scattered throughout the valley and were 

estimated by Hely and others (1971, p. 140) for the period 

1964–68. The domestic/stock withdrawal estimate for 1964-

1968 also was used for the period 1997–2001 because it was 

beyond the scope of this study to inventory all domestic and 

stock wells in the valley. Some verification of the domestic/

stock withdrawals was made in 1992 by examining the number 

of recorded water rights for domestic and stock uses (Utah 

Department of Natural Resources, Division of Water Rights, 

written commun., 1992) and results indicate that the 1964–68 

estimate is reasonable for 1997–2001.

Initial estimates of evapotranspiration in the Salt Lake 

Valley were based on the assumption that evapotranspiration 

occurred in areas where the average depth to ground water is 

less than 5 m (Hely and others, 1971, p. 179). To determine 

an evapotranspiration rate, the area of shallow ground water 

was divided into five major land categories: bare ground, 

cultivated land, urban land, waterfowl-management land, and 

areas of phreatophytes. The phreatophyte area was further 

subdivided by plant group. Each land category and plant group 

was assigned a maximum evapotranspiration rate (Hely and 

others, 1971, p. 179; Blaney and Criddle, 1962). The multiplication of area and rate (adjusted to compensate for an average 

depth to ground water) resulted in an evapotranspiration rate 

of 203,000 m3/d for 1964–1968. Revised evapotranspiration 

estimates made initially by Waddell and others (1987, p. 29), 

and later by Lambert (1995a, p. 36), resulted in evapotranspiration rates about 40 percent less than that presumed by Hely 

and others (1971). The revised evapotranspiration estimates 

were made by simulating ground-water flow in the valley-fill 

aquifer of Salt Lake Valley and matching model-computed and 

measured water levels for the shallow unconfined portion of 

the aquifer. On the basis of the last stress period of the transient calibration by Lambert (1995a, p. 37), which incorporates land-use changes in Salt Lake Valley from 1968 to 1991, 

the average evapotranspiration rate estimated for 1997–2001 is 

109,000 m3/d.

Discharge to springs in the Salt Lake Valley from the 

basin-fill aquifer was originally estimated by Hely and others 

(1971) on the basis of springflow water-rights records. For 

the present modeling study, the 1964–1968 estimates of Hely 

and others (1971) are used to estimate a spring discharge rate 

of about 64,110 m3/d for 1997–2001. The estimate assumes 

springflows have been relatively stable over time because the 

springs are located near the valley margins and are generally 

not affected by pumping.

Ground-water discharge from the shallow unconfined 

aquifer to surface drains is known to occur near the Great Salt 

Lake and to buried storm drains in Salt Lake City. Data are 

available to quantify flow to the surface drains near the Great 

Salt Lake, and a rate of 17,000 m3/d was estimated by Hely 

and others (1971 p. 136). The discharge rate to buried drains 

in the Salt Lake City area is not known. However, a steady 

discharge to and from storm drains has been observed by the 

employees of the Salt Lake City Department of Public Utilities 

(Charles H. Call, Jr., oral commun., 1992) and is assumed 

by them to be seepage from shallow ground water. Lambert 

(1995a) simulated 33,700 m3/d of discharge to surface and 

buried drains during steady-state simulation, and for lack of 

additional information, this is the rate assumed for 1997–2001.

Ground-water discharge to Great Salt Lake has been 

calculated by applying Darcy’s law along an arbitrary line parallel to and near the shore of Great Salt Lake (Mower, 1968, 

p. D71; Hely and others, 1971, p. 136; and Waddell and 

others, 1987, p. 29). The average discharge rate from previous computations is about 11,800 m3

/d, and this same rate is 
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–11

assumed for 1997–2001. Discharge to the Great Salt Lake is 

less than 1 percent of the Salt Lake Valley water budget.

Ground-Water Quality

General ground-water quality in the Salt Lake Valley has 

identifiable trends along east- west and south-north transects. 

Dissolved-solids concentrations in ground water are lowest 

along the margins of the valley where most recharge occurs. 

Along the eastern margin, dissolved-solids concentrations 

typically range from 200 to 500 mg/L, and the dominant ions 

are calcium and bicarbonate. On the western margin, dissolved-solids concentrations are in the range of 400 to 1,100 

mg/L, and the dominant ions are calcium, magnesium, and sulfate. The difference in water quality between the eastern and 

western parts of the valley can be explained by rock type in the 

recharge source area. Recharge on the eastern valley margin 

originates in the Wasatch Range, which is predominantly composed of crystalline rock and quartzites, and recharge on the 

western valley margin originates in the Oquirrh and Traverse 

mountains, which are predominantly composed of Tertiary-age 

volcanic rocks and associated sulfide mineralization.

Dissolved-solids concentrations increase and the dominant ions become sodium and chloride as ground water flows 

from south to north in the Salt Lake Valley. As ground-water 

residence time increases from south to north, there is more 

time for ground water to interact with the basin-fill materials 

and dissolved-solids concentrations increase. Vertically, the 

best quality water is at intermediate depths within the basin-fill 

aquifer. Water in the shallow unconfined aquifer and deeper in 

the basin-fill aquifer have the highest dissolved-solids concentrations.

Oxidation-reduction zones within the Salt Lake Valley 

(fig. 2.5) have been conceptualized on the basis of recharge 

and discharge areas using existing water-quality data. The 

basin-fill aquifer is spatially divided into three areas with 

respect to recharge/discharge processes (Anderson and others, 1994): (1) the primary recharge area, (2) the secondary 

recharge area, and (3) the discharge area. These areas are 

delineated on the basis of lithology reported on drillers’ logs 

and vertical hydraulic-gradient information.

The primary recharge area exists along the valley margins 

where coarse-grained sediments dominate the basin fill and 

the vertical hydraulic gradient is downward. Fresh oxygenated 

water recharges the aquifer in these areas, and ground water 

is assumed oxygen reducing (oxic). The secondary recharge 

area occurs where layers of fine-grained sediment are present, but the vertical gradient is still downward. The secondary 

recharge area is adjacent to and downgradient from the primary recharge area, although a small amount of recharge from 

land surface does occur. Because ground water in the secondary recharge area has a longer residence time than that in the 

primary recharge area, the secondary recharge area is conceptualized as a transition zone between oxic and iron-reducing 

(anoxic) conditions. The discharge zone is defined by extensive fine-grained layering within the aquifer and vertically 

upward gradients. No recharge occurs in the discharge zone 

and ground water in these areas has experienced the longest 

travel and residence times, so it is assumed that all dissolved 

oxygen has been consumed and ground water is iron-reducing 

in the discharge zone.

Ground-Water Flow Simulations

The modular ground-water flow simulation code 

MODFLOW-2000 (Harbaugh and others, 2000) was used to 

simulate a steady-state condition based on the annual average 

conditions for the 5-year period from 1997 through 2001. A 

previously calibrated transient model, which was constructed 

and calibrated to 1968 steady-state and 1969–91 transientstate conditions by Lambert (1995a), was used by this study to 

simulate a steady-state stress period representing 1997–2001 

average conditions. This study modified specified-flux terms 

of the Lambert (1995a) model defining (1) inflow from 

consolidated rock, (2) infiltration of precipitation, (3) inflow 

from streams, and (4) discharge to pumping wells to reflect 

1997–2001 average values. Aquifer parameters of hydraulic 

conductivity and transmissivity were not recalibrated by this 

modeling exercise. The steady-state model is considered a 

reasonable approximation of ground-water flow conditions for 

1997–2001 because ground-water pumping rates and climatic 

conditions were relatively stable for the time period.

Modeled Area and Spatial Discretization

The model grid covers 1,152 km2 of the Salt Lake Valley 

and is subdivided into 94 rows, 62 columns (fig. 2.6) and 7 

layers. Each model cell represents 0.32 km2 of surface area. 

The shallow unconfined aquifer is represented by model layer 

1, and the shallow confining layer is represented by model 

layer 2. The thicknesses of model layers 1 and 2 vary spatially 

and roughly represent the estimated depth and thickness of the 

shallow unconfined aquifer and the underlying shallow confining layer, respectively. Layers 1 and 2 are both simulated 

as convertible between confined and unconfined conditions 

depending on the elevation of hydraulic head computed by 

the model. The basin-fill aquifer is simulated by model layers 

3 through 7. Layer 3 defines the areal extent of the model 

domain and is simulated as convertible between confined 

and unconfined conditions. Model layers 4 to 7 represent 

deep sediments of the basin-fill aquifer and are simulated as 

confined. Model layers 3 to 5 are each 46 m thick, and model 

layer 6 is 61 m thick. Model layer 7 ranges in thickness from 

61 m to more than 460 m. The term “vertical column,” as used 

in this report, is the set of model cells with the same row and 

column index.
2–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 2.5. Generalized oxidation-reduction classification zones, Salt Lake Valley regional study area, Utah.

65

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89 190

90

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U I R

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H

M O U N T A I N S

T R A V E R S E

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River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS

0 5 10 MILES

EXPLANATION

Discharge area, iron-reduction conditions assumed

Primary recharge area, oxygen-reduction conditions assumed

Secondary recharge area, oxygen-reduction and iron-reduction conditions assumed

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–13

Figure 2.6. Ground-water flow model grid and selected boundary conditions, Salt Lake Valley regional study area, Utah.

65

80

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89 190

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River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS Modified from Lambert, 1995a

0 5 10 MILES

EXPLANATION

Head-dependent flux—Used to simulate surface-water/ground-water interaction 

 along streams, mountain-block recharge from the Oquirrh Mountains, and 

 ground-water discharge to drains and springs

Specified-flux boundary—Used to simulate mountain-block recharge, surface-water/

 ground-water interaction along streams and canals, and discharge from springs

Constant-head cells along Great Salt Lake

Model grid

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley
2–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Boundary Conditions and Model Stresses

Boundary conditions assigned to the numerical solution are mathematical equations that represent flow at surface 

boundaries and internal sources and sinks. Boundary types 

and the specified amounts of recharge and discharge were 

assigned to reflect the conceptual analysis of the ground-water 

flow system (table 2.2). Four distinct boundary types are used 

to simulate recharge, discharge, and the spatial extent of the 

Salt Lake Valley ground-water system. They are (1) no flow, 

(2) specified flux, (3) head-dependent flux, and (4) constant 

head. A no-flow boundary simulates an impermeable hydrologic boundary. Unless specifically noted, the horizontal and 

vertical extent of the model domain is set by no-flow boundaries. A specified-flux boundary allows a specified rate of flow 

across a boundary as a function of location and time. A headdependent boundary allows the flow rate across the boundary 

surface to change in response to changes in water level in the 

aquifer adjacent to the boundary. Constant-head boundaries fix 

the water level in a cell, and flows to or from adjacent cells are 

computed on the basis of that water level.

 No-flow boundaries are assigned at the base of the 

modeled area. The base corresponds to the contact between 

consolidated rock of pre-Tertiary age and basin-fill material or to a depth within the basin fill below which sediments 

were assumed not to contribute substantially to the basin-fill 

ground-water flow system. The northern border of the modeled area approximates a flow line and was treated as a noflow boundary.

Recharge

Mountain-block recharge from the consolidated rock of 

the Wasatch Range and the Oquirrh Mountains is simulated 

using specified-flux cells with the MODFLOW Well package placed at the lateral edges of the model domain in layers 

3 or 4 (Lambert, 1995a, fig. 9; fig. 6). Some mountain-block 

recharge occurs at the northern end of the Oquirrh Mountains, 

and that portion is simulated using MODFLOW General-head 

cells (Lambert, 1995a, fig. 15). The amount of specified flow 

from mountain-block recharge, which is the conceptualized 

amount minus the Oquirrh Mountains inflow, is set at 401,918 

m3/d (table 2.2).

Recharge from precipitation on the valley floor is 

simulated as a specified flux using the MODFLOW Recharge 

package over the entire modeled area except in areas of dense 

commercial and residential development (Lambert, 1995a). In 

dense commercial and residential areas, it is assumed that precipitation was collected as runoff in drain systems and routed 

directly to surface-water bodies. The total simulated amount 

of precipitation recharge (256,712 m3/d) is adjusted from the 

conceptualized amount of precipitation recharge (257,000 

m3/d) to account for the dense commercial and residential 

area. The MODFLOW Recharge package applies recharge to 

the uppermost active cells in a vertical column of cells. The 

total recharge is spatially distributed across the model grid 

on the basis of mean annual precipitation isohyets (Hely and 

others, 1971).

Specified-flux cells using the MODFLOW Recharge 

package also are used to simulate mountain-front recharge 

from streams at and near where they enter the Salt Lake Valley 

from the mountains (Lambert, 1995a, fig. 12) and underflow 

recharge through stream-channel fill where the Jordan River 

enters the Salt Lake Valley. The boundaries are placed in the 

uppermost active cell of the model grid that corresponds to 

the location of the stream. This recharge encompasses the 

major streams that flow out of the Wasatch Range. Simulated recharge from the streams draining the Wasatch Range 

is 54,000 m3/d, and lateral subsurface flow associated with 

the Jordan River is set at 6,850 m3/d. Recharge from the five 

canals that traverse the west and east sides of the valley is 

simulated using the MODFLOW Well package to specify 

flux. Ground-water recharge from canals is simulated approximately 94,500 m3

/d.

Recharge from irrigation of fields, lawns, and gardens is 

simulated as a specified flux using the MODFLOW Recharge 

package. The cells where the recharge is applied correspond 

either to irrigated land use or residential land use (lawns and 

gardens). Recharge was distributed on the basis of the percentage of cell area that represents irrigated fields or residential 

land and the irrigation recharge is added to the precipitation 

recharge. The recharge amount for commercial fields is about 

108,200 m3/d (19.5 cm/yr), and for residential areas the rate is 

about 33,700 m3/d (5.5 cm/yr) (Lambert, 1995a, p. 33 and 42).

Discharge

Discharge to streams is simulated as head-dependent 

boundaries using the MODFLOW River package along the 

length of the Jordan River and the lower reaches of three of 

the Wasatch Range streams (Lambert, 1995a, fig. 15; fig. 6). 

The boundary cells are in model layer 1 and follow the course 

of the streams. Riverbed altitude and length were determined 

from 1:24,000 U.S. Geological Survey topographic maps. Riverbed width and thickness were not measured; it was assumed 

that the riverbed thickness is one tenth of the riverbed width. 

Hydraulic conductivities of the riverbed range from 0.03 to 3.0 

m/d and were determined during model calibration (Lambert, 

1995a).

Discharge to canals is simulated as a specified flux using 

the MODFLOW Well package for four of the major canals in 

the Salt Lake Valley where ground-water discharge has been 

measured (Herbert and others, 1985). The boundaries are in 

the uppermost active cell of the vertical columns that correspond to the canal locations (Lambert, 1995a, fig. 12).

Public-supply, irrigation, and industrial wells that withdrew more than 170 m3

/d for the period 1997–2001 are simulated in the ground-water flow model. The wells are simulated 

as specified-flux cells using the MODFLOW Well package 

located in model cells corresponding to actual well locations. 
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–15

Discharge is disseminated vertically to the appropriate model 

layer on the basis of well depth and the depth of well-casing 

perforations (Lambert, 1995a, p. 27). All simulated wells withdraw water from model layers 3 to 7. The discharge quantity 

associated with individual wells is based on annual-withdrawal 

data reported by the water user and compiled by the U.S. 

Geological Survey and the Utah Division of Water Rights. 

The steady-state model simulates the average withdrawals for 

1997–2001, and the total simulated withdrawal in the model is 

398,630 m3/d.

The model also simulates withdrawals from domestic 

and stock wells. These small-diameter wells are represented 

as specified-flux cells using the MODFLOW Well package in 

model layer 3. Areal distribution of withdrawal was determined from individual locations recorded by the Utah Department of Natural Resources, Division of Water Rights (Lambert, 1995a, p. 28). Simulated withdrawals from domestic and 

stock wells are 101,370 m3/d.

Evapotranspiration (ET) is simulated as head-dependent 

flux boundaries using the MODFLOW ET package. The 

boundary is placed at cells in model layer 1 that correspond 

to the areas of shallow ground water in the Salt Lake Valley 

(Lambert, 1995a, fig. 15). The extinction-depth value assigned 

to the boundary is 4.6 m (Lambert, 1995a). As a generalization, the presence of phreatophytes is limited to areas of the 

valley where the water table is within 4.6 m of land surface. To 

capture the variability in water use by different plant species, 

the evapotranspiration area was subdivided into five major 

land-use categories. Each category is assigned a maximum 

evapotranspiration rate. The rate was adjusted to a finalized 

value during model calibration by Lambert (1995a, p. 36).

Six major freshwater springs exist in the Salt Lake Valley, 

and they are simulated as specified-flux boundaries using the 

MODFLOW Well package. The boundaries are assigned to 

model layer 3 and correspond to the locations of the springs 

(Lambert, 1995a, fig. 12). Total specified spring discharge is 

64,110 m3/d.

Surface drains near Great Salt Lake and buried drains 

beneath commercial and residential areas in Salt Lake City are 

simulated using MODFLOW Drain cells placed in model layer 

1 at the location of actual drains. Drain altitudes were specified to be 3.0 m less than land-surface altitude. Drain conductance was not measured, and initial values were arbitrarily 

selected. Drain conductance was adjusted during model calibration by Lambert (1995a, p. 36) to simulate a conceptually 

reasonable amount of ground-water discharge (23,562 m3/d).

The hydrologic connection between the basin-fill aquifers and Great Salt Lake is simulated with a constant-head 

boundary (fig. 2.6). The boundary is in model layer 1 along 

the northwestern border of the model domain at cells that 

represent the shore of Great Salt Lake (Lambert, 1995a, fig. 

15). The water level assigned to the constant-head boundary 

is 1,280 m, which is the approximate average historical water 

level of the lake.

Table 2.2. Model-computed water budget for 1997–2001 average conditions, Salt Lake Valley 

regional study area, Utah.

[m3/d, cubic meters per day]

Water-budget component

Specified

flow

(m3/d)

Computed

flow

(m3/d)

Total flow

(m3/d)

Percentage 

of inflow or 

outflow

Model inflow (recharge)

Mountain-block recharge 401,918 40,548 442,466 43.8

Precipitation 256,712 256,712 25.4

Irrigation return flow 141,918 141,918 14.1

Mountain-front recharge, rivers, and canals 155,342 13,425 168,767 16.7

TOTAL INFLOW 1,009,863 100

Model outflow (discharge)

Jordan River 287,123 287,123 28.3

Wells

Public supply, irrigation, and industrial 398,630 398,630 39.4

Domestic and stock 101,370 101,370 10.0

Evapotranspiration 104,658 104,658 10.3

Springs and drains 64,110 23,562 87,671 8.7

Canals 30,411 30,411 3.0

Great Salt Lake 3,288 3,288 0.3

TOTAL OUTFLOW 1,013,151 100
2–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Model Calibration and Sensitivity

The model used to simulate the average conditions for 

1997–2001 was calibrated to 1968 steady-state and 1969–91 

transient conditions by Lambert (1995a). The model was 

calibrated by manually adjusting calibration variables (primarily transmissivity) within a prescribed range until a reasonable 

match between model-computed and observed conditions was 

achieved. A complete discussion of the calibration process 

is given in Lambert (1995a). Final values of transmissivity assigned to the basin-fill aquifer by Lambert (1995a) are 

shown in figure 2.7 and represent the sum of transmissivity 

values for the basin-fill aquifer (model layers 3 to 7). Calibrated aquifer hydraulic properties presented by Lambert 

(1995a) were not altered during the present modeling exercise.

As part of the model calibration by Lambert (1995a), a 

sensitivity analysis was done to determine the response of the 

model to changes in selected parameters. Calibration parameters were independently adjusted and the effects of these 

adjustments on simulated water levels and flow rates were 

noted. Generally, the calibrated model is more sensitive to 

decreasing parameter values than to increasing values. Specifically, the model is most sensitive to decreasing horizontal 

hydraulic conductivity in model layer 1; decreasing conductivity caused substantial increases in water levels in model 

layer 1. The model is relatively insensitive to (1) increasing 

vertical leakance within model layers 1 to 3, (2) decreasing or 

increasing vertical leakance within model layers 3 to 7, and (3) 

increasing riverbed conductance (Lambert, 1995a).

Model-Computed Hydraulic Heads

The ability of the ground-water flow model to simulate 

the 1997–2001 average conditions was judged by comparing 

model-computed and measured water levels at 45 wells for 

the same time period. Measured levels are an average of the 

February, March, and April 1997–2001 available water-level 

data for the well. The overall goodness of fit of the model to 

the observation data was evaluated using summary measures 

and graphical analyses. The root-mean-squared error (RMSE), 

the range of head and residuals, the standard deviation, and 

the standard-mean error of the residuals (SME) were used to 

evaluate the model calibration. The RMSE is a measure of the 

variance of the residuals and was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of wells used in the computation. If the ratio of the RMSE 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).

The SME was calculated as:

where (hmeas – hsim) is the standard deviation of the residuals.

A simple method of assessing model fit is to plot the 

model-computed hydraulic head values against the measured 

observations. For a perfect fit, all points should fall on the 1:1 

diagonal line. Figure 2.8 shows the locations of water-level 

measurements and the spatial distribution of head residuals 

and indicates a random spatial distribution of the residuals. 

A plot of the model-computed heads against the measured 

hydraulic heads for the Salt Lake Valley regional ground-water 

flow model (fig. 2.9) indicates reasonable model fit. The mean 

residual for the entire model is 3.91 m, and residuals range 

from –18.3 m to 38.4 m. The RMSE for the entire model is 

10.7 m, which is about 6 percent of the 183-m range of head 

observations in the model, and the head residuals appear to be 

randomly distributed at all values of measured head (fig. 2.10). 

The standard deviation of the residuals is 10.1 m, and the SME 

is 1.58 m. The results of these comparisons indicate a reasonable match between model-computed and measured water 

levels for 1997–2001 average conditions.

Model-Computed Water Budget

The model-computed water budget for 1997–2001 average conditions in the Salt Lake Valley regional study area is 

presented in table 2.2. Many of the water-budget components 

simulated by the model were specified values and some 

components were computed by the model. Mountain-block 

recharge (43.8 percent of inflow) and recharge from precipitation and irrigation (39.5 percent of inflow) were the primary 

sources of recharge to the basin-fill aquifer. Recharge from 

mountain-front recharge, streams, and canals provided the 

remaining 16.7 percent of ground-water inflow. Discharge to 

wells (49.4 percent of outflow) and to the Jordan River (28.3 

percent of outflow) were the primary ground-water outflows 

from the Salt Lake Valley. Model-computed ground-water discharge to the Jordan River was less than the conceptual model 

estimate, but, in general, the model-computed water budget is 

in reasonable agreement with the conceptual estimates of flow 

discussed in the Water Budget section of this chapter.
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–17

Simulation of Areas Contributing Recharge to 

Wells

The steady-state regional flow model was used to estimate areas contributing recharge and zones of contribution 

for 94 wells in the Salt Lake Valley using the MODPATH 

(Pollock, 1994) particle-tracking post processor and methods 

outlined in Section 1 of this Professional Paper. The modelcomputed areas contributing recharge represent advective 

ground-water flow and do not account for mechanical dispersion. Advection-dispersion transport simulations would 

likely yield larger areas contributing recharge than advective 

particle-tracking simulations because the effects of dispersion 

caused by aquifer heterogeneity would be included.

Along with flux output from the models, the MODPATH 

simulations require effective porosity values to calculate 

ground-water flow velocities. An effective porosity value of 

0.4 was assigned to model layers 1 and 2, and an effective 

porosity value of 0.3 was assigned to model layers 3 to 7 based 

on estimates from Lambert (1995b, p. 21).

The simulated contributing areas can be summarized as 

long and narrow and truncating at specified-flux boundaries at 

the edges of the model domain (fig. 2.11). This summarization 

holds true regardless of the pumping rate at individual wells. 

The shape of the contributing areas is controlled mainly by 

the recharge being simulated primarily along the edges of the 

model domain, which is a direct reflection of the conceptualization of the ground-water system. Truncation of contributing areas at model boundaries indicates mountain-front and 

mountain-block recharge from the Wasatch Range and Oquirrh 

Mountains is contributing water to public-supply wells in the 

Salt Lake Valley.

The simulated median traveltime for water to move from 

its recharge point to a well ranges from 5 to 780 years based 

on particle-tracking estimates from MODPATH. The longest 

traveltimes are associated with contributing areas for wells on 

the west side of the Salt Lake Valley.

Limitations and Appropriate Use of the Model

The ground-water flow model for the Salt Lake Valley 

regional study area was designed to evaluate the water budget 

for 1997–2001 and to delineate areas contributing recharge to 

public-supply wells. Sources of error in the model may include 

the steady-state flow assumption and errors in the conceptual model of the system, hydraulic properties, and boundary 

conditions.

The assumption of steady-state conditions for the Salt 

Lake Valley regional model is reasonable for the time period 

of study because sources of recharge and discharge were 

relatively stable from 1997 to 2001. However, model calibration parameters were taken from an existing model and were 

not specifically calibrated to match water levels and flow rates 

during 1997-2001. Further calibration for transient conditions 

may be needed to accurately represent temporal changes in the 

system.

Measured water levels, historical water-level changes, 

and simulated discharge to the Jordan River were not accurately simulated in all areas of the model domain. However, a 

reasonable match was obtained between simulated and measured hydrologic conditions for the study area.

Sensitivity analysis indicates that increasing vertical 

hydraulic conductivity relative to calibrated estimates within 

reasonable limits does not substantially affect model results. 

Vertical gradients and flows simulated in the model are controlled, in part, by the vertical hydraulic conductivity incorporated in model input. The uncertainty of the final estimates 

of vertical hydraulic conductivity of the basin fill (and thus, 

vertical leakance between model layers) should be noted when 

evaluating simulation results.

The simulation of mountain-block recharge to the basinfill aquifer is greatly simplified. In the physical system, flow 

from the consolidated-rock aquifer to the basin-fill aquifer is 

controlled by the difference in water level between the two 

aquifers. The head-dependent nature of flow between the 

two aquifers is not accounted for in the model other than at 

the northern end of the Oquirrh Mountains. Large declines 

in basin-fill hydraulic heads near the margins of the valley 

may increase inflow from consolidated rock, and because the 

model represents mountain-block recharge using constant-flux 

boundaries, changes in mountain-block flux resulting from 

drawdown in the basin fill are not simulated.

Computed areas contributing recharge and traveltimes 

through zones of contribution are based on a calibrated 

model and estimated effective porosity values. In a steadystate model, changes to input porosity values do not change 

the area contributing recharge to a given well. Changes to 

input porosity values will change computed traveltimes from 

recharge to discharge areas in direct proportion to changes of 

porosity because there is an inverse linear relation between 

ground-water flow velocity and effective porosity and a direct 

linear relation between traveltime and effective porosity. For 

example, a one-percent decrease in porosity will result in a 

one-percent increase in velocity and a one-percent decrease 

in particle traveltime. There are no available porosity data for 

this study area, so a reasonable estimated value was chosen. 

A detailed sensitivity analysis of porosity distributions was 

beyond the scope of this study, although future work could 

compare simulated ground-water traveltimes to ground-water 

ages to more thoroughly evaluate effective porosity values.
2–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 2.7. Distribution of basin-fill aquifer transmissivity for the calibrated ground-water flow model, Salt Lake Valley 

regional study area, Utah.

65

80

15

215

80

201

15

89 190

90

15

O

Q

U I R

R

H

M

O

U

N

T A I N

S

W

A

S

A

T

C

H

M O U N T A I N S

T R A V E R S E

R

A

N

G

E

River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS

0 5 10 MILES

EXPLANATION

Transmissivity, in meters squared per day

 28 to 650

 930 to 1,400

 1,860 to 3,720

 4,650 to 5,570

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–19

Figure 2.8. Water-level observation well locations and head residuals, Salt Lake Valley regional study area, Utah.

65

80

15

215

80

201

15

89 190

90

15

O

Q

U I R

R

H

M

O

U

N

T A I N

S

W

A

S

A

T

C

H

M O U N T A I N S

T R A V E R S E

R

A

N

G

E

River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

1.4

0.9 2.5 –4.7

5.8 0

10

–0.2 6.4

16

1.9

2.5

2.5

22

–18

5.5

20 –6.3

6.2

–5.7

0.1

–13

6.6

6.7

7.4 –0.1

12

19

0.7

4.2 –13

–3.9

3.8

0.2

–10 8.3

38 5.9

4.6

3.4

1.1

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS

0 5 10 MILES

EXPLANATION

Extent of active cells in model layer 3

Approximate extent of basin-fill deposits in Salt Lake Valley

Observation well—Number is head residual, in meters –4.7
2–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 2.9. Relation between model-computed and measured 

hydraulic head, Salt Lake Valley regional study area, Utah.

Figure 2.10. Relation between head residual and measured 

hydraulic head, Salt Lake Valley regional study area, Utah.

The Salt Lake Valley regional ground-water-flow model 

uses previously calibrated aquifer properties and boundary 

conditions and provides a reasonable representation of average 

ground-water flow conditions for 1997–2000. The model is 

suitable for evaluating regional water budgets and ground-water flow paths in the study area for the time period of interest 

but may not be suitable for long-term predictive simulations. 

This regional model provides a useful tool to evaluate aquifer 

vulnerability at a regional scale, to facilitate comparisons of 

ground-water traveltime between regional aquifer systems, and 

to guide future detailed investigations in the study area.

1:1 line

1,250

1,275

1,300

1,325

1,350

1,375

1,400

1,425

1,450

1,475

1,500

Model-computed head elevation, in meters

Measured head elevation, in meters

1,250 1,275 1,300 1,325 1,350 1,375 1,400 1,425 1,450 1,475 1,500

–25

–20

–15

–10

–5

0

5

10

15

20

25

30

35

40

45

Head residual, in meters

Measured head elevation, in meters

1,250 1,275 1,300 1,325 1,350 1,375 1,400 1,425 1,450 1,475 1,500
Hydrogeologic Setting and Ground-Water Flow Simulations of the Salt Lake Valley Regional Study Area, Utah 2–21

Figure 2.11. Model-computed areas contributing recharge to public-supply wells, Salt Lake Valley regional study area, Utah.

65

80

15

215

80

201

15

89 190

90

15

O

Q

U I R

R

H

M

O

U

N

T A I N

S

W

A

S

A

T

C

H

M O U N T A I N S

T R A V E R S E

R

A

N

G

E

River

Jordan

Creek City

Butte

Creek

Red

Emigration

Creek

Parleys

Creek

Mill Creek

Big

Creek

Cottonwood

Little Creek

Cottonwood

Butterfield

Creek

Rose

Creek

Creek

Bingham

Barneys Creek

Coon Creek

Tailings pond

G R E A T

S A L T

L A K E

S A L T L A K E

C I T Y

DAVIS COUNTY

SALT LAKE COUNTY SALT LAKE COUNTY TOOLE COUNTY

SALT LAKE COUNTY

UTAH COUNTY

UTAH COUNTY

WASATCH COUNTY

SALT LAKE COUNTY

SUMMIT COUNTY

SALT LAKE COUNTY

DAVIS COUNTY MORGAN COUNTY

40° 30'

40° 45'

112° 15' 112° 00' 111° 45'

Base from U.S. Geological Survey digital data,

Universal Transverse Mercator projection,

Zone 12, North American Datum of 1983

0 5 10 15 20 KILOMETERS

0 5 10 MILES

EXPLANATION

Area contributing recharge

 First quartile of pumping (highest 25 percent of pumping rates)

 Second quartile (50 to 75 percent of maximum pumping rate)

 Third quartile (25 to 50 percent of maximum pumping rate)

 Fourth quartile (lowest 25 percent of pumping rates)

Pathlines

Extent of active cells in model layer 3

Urban area

Approximate extent of basin-fill deposits in Salt Lake Valley

Wells with model-computed contributing areas

 First quartile

 Second quartile

 Third quartile 

 Fourth quartile

Other wells
2–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

References Cited

Anderson, P.B., Susong, D.D., Wold, S.R., Heilweil, V.M., and 

Baskin, R.L., 1994, Hydrogeology of recharge areas and 

water quality of the principal aquifers along the Wasatch 

Front and adjacent areas, Utah: U.S. Geological Survey 

Water-Resources Investigations Report 93–4221, 74 p.

Anderson, M.P., and Woessner, W.W., 1992, Applied groundwater modeling: Academic Press, Inc., New York, 381 p.

Arnow, Ted, Van Horn, Richard, and LaPray, Reed, 1970, 

The pre-Quaternary surface in the Jordan Valley, Utah, in

Geological Survey Research 1970: U.S. Geological Survey 

Professional Paper 700–D, p. D257–D261.

Blaney, H.F., and Criddle, W.D., 1962, Determining consumptive use and irrigation requirements: U.S. Agricultural 

Research Service Technical Bulletin 1275, 59 p.

Bedinger, M.S., Langer, W.H., and Reed, J.E., 1986, Synthesis of hydraulic properties of rocks in the Basin and Range 

Province, southwestern United States: U.S. Geological 

Survey Water-Supply Paper 2310, p. 35–43.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. 

Geological Survey Open-File Report 00–92, 121 p.

Hely, A.G., Mower, R.W., and Harr, C.A., 1971, Water 

resources of Salt Lake County, Utah: Utah Department of 

Natural Resources Technical Publication no. 31, 244 p.

Herbert, L.R., Cruff, R.W., and Waddell, K.M., 1985, Seepage study of six canals in Salt Lake County, Utah, 1982–83: 

Utah Department of Natural Resources Technical Publication no. 82, 95 p.

Lambert, P.M., 1995a, Numerical simulation of ground water 

flow in basin-fill material in Salt Lake Valley, Utah: Utah 

Department of Natural Resources Technical Publication 

no. 110–B, 58 p.

Lambert, P.M., 1995b, Particle–tracking analysis of timerelated capture zones for selected public-supply wells 

in Salt Lake Valley, Utah: Utah Department of Natural 

Resources Technical Publication no. 110–C, 36 p.

Marine, I.W., and Price, Don, 1964, Geology and groundwater resources of the Jordan Valley, Utah: Utah Geological 

and Mineralogical Survey Bulletin 7, 68 p.

Maupin, M.A., and Barber, N.L., 2005, Estimated withdrawals from principal aquifers in the United States, 2000: U.S. 

Geological Survey Circular 1279, 47 p.

Mower, R.W., 1968, Ground-water discharge toward Great 

Salt Lake through valley fill in the Jordan Valley, Utah, in 

Geological Survey Research 1968: U.S. Geological Survey 

Professional Paper 600–D, p. D71–D74.

Pollock, D.W., 1994, User’s guide for MODPATH/MODPATH-PLOT, Version 3—A particle tracking post-processing package for MODFLOW, the U.S. Geological Survey 

finite-difference ground-water flow model: U.S. Geological Survey Open-File Report 94-464, accessed June 15, 

2004, at http://water.usgs.gov/nrp/gwsoftware/modpath41/

modpath41.html

Planert, Michael, and Williams, J.S., 1995, Ground Water 

Atlas of the United States—California and Nevada: U.S. 

Geological Survey Hydrologic Atlas 730–B.

PRISM Group, Oregon State University, 2006, Prism products matrix, accessed Feb. 7, 2007, at http://www.ocs.

oregonstate.edu/prism/products/matrix.phtml?vartype=ppt

&view=maps

Robson, S.G., and Banta, E.R., 1995, Ground Water Atlas of 

the United States—Arizona, Colorado, New Mexico, and 

Utah: U.S. Geological Survey Hydrologic Atlas 730–C.

Thiros, S.A., 1992, Selected hydrologic data for Salt Lake 

Valley, Utah, 1990–92, with emphasis on data from the shallow unconfined aquifer and confining layers: U.S. Geological Survey Open-File Report 92–640, duplicated as Utah 

Hydrologic-Data Report no. 49, 44 p.

Thiros, S.A., 1995, Chemical composition of ground water, 

hydrologic properties of basin-fill material, and groundwater movement in Salt Lake Valley, Utah: Utah Department of Natural Resources Technical Publication no. 

110–A.

Utah Department of Natural Resources, Division of Water 

Resources, 2003, Agricultural land-use program, AgricultauralUrbanLandUse2003.shp: accessed Sept. 22, 2005, at 

URL http://agrc.utah.gov/agrc_sgid/sgidlib/sgid024_

agriculturalurbanlanduse2003.htm

Waddell, K.M., Seiler, R.L., Santini, Melissa, and Solomon, 

D.K., 1987, Ground-water conditions in Salt Lake Valley, 

Utah, 1969–83, and predicted effects of increased withdrawals from wells: Utah Department of Natural Resources 

Technical Publication no. 87, 69 p.
Hydrogeologic Settings and Ground-Water 

Flow Simulations of the Eagle Valley and 

Spanish Springs Valley Regional Study 

Areas, Nevada

By Donald H. Schaefer, Jena M. Green, and Michael R. Rosen

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 3 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report. 

Suggested citation:

Schaeffer, D.H., and Rosen, M.R., 2007, Hydrogeologic settings and ground-water flow simulations of the Eagle Valley and Spanish Springs Regional Study Areas, Nevada, section 3 of Paschke, S.S., ed., Hydrogeologic settings and 

ground-water flow simulations for regional studies of the transport of anthropogenic and natural contaminants to 

public-supply wells—studies begun in 2001: Reston, Va., U.S. Geological Survey Professional Paper 1737–A, 

pp. 3–1 – 3–33
iii

Contents

Abstract...................................................................................................................................................... 3–1

Introduction................................................................................................................................................ 3–1

Purpose and Scope ......................................................................................................................... 3–1

Study Area Description................................................................................................................... 3–3

Topography and Climate ........................................................................................................ 3–3

Surface-Water Hydrology ..................................................................................................... 3–3

Land Use................................................................................................................................... 3–8

Water Use ................................................................................................................................ 3–8

Conceptual Understanding of the Ground-Water System................................................................. 3–8

Geology.............................................................................................................................................. 3–8

Ground-Water Occurrence and Flow......................................................................................... 3–10

Aquifer Hydraulic Conductivity.................................................................................................... 3–10

Water Budget ................................................................................................................................. 3–11

Ground-Water Quality ................................................................................................................... 3–13

Ground-Water Flow Simulations .......................................................................................................... 3–16

Modeled Areas and Spatial Discretizations.............................................................................. 3–16

Boundary Conditions..................................................................................................................... 3–16

Recharge................................................................................................................................ 3–16

Discharge............................................................................................................................... 3–17

Aquifer Hydraulic Conductivity.................................................................................................... 3–17

Model Calibration........................................................................................................................... 3–25

Model-Computed Hydraulic Heads ................................................................................... 3–25

Model-Computed Water Budget........................................................................................ 3–27

Simulation of Areas Contributing Recharge to Public-Supply Wells .................................... 3–28

Limitations and Appropriate Use of the Model......................................................................... 3–28

References Cited..................................................................................................................................... 3–32

Figures

Maps showing:

3.1. Location of the Eagle Valley and Spanish Springs Valley regional 

study areas within the Basin and Range basin-fill aquifers. ...........................3–2

3.2A. Topography, hydrologic features, and locations of public-supply wells, 

Eagle Valley regional study area, Nevada. ..........................................................3–6

3.2B. Topography, hydrologic features, and locations of public-supply wells,

Spanish Springs Valley regional study area, Nevada. ......................................3–7

Generalized block diagrams showing:

3.3A. Basin-fill ground-water flow system of the Eagle Valley regional study area, 

Nevada........................................................................................................................3–9

3.3B. Basin-fill ground-water flow system of the Spanish Springs Valley 

regional study area, Nevada. .................................................................................3–9
iv

Maps showing:

3.4A. Basin-fill aquifer potentiometric surface and oxidation-reduction 

classification zones, Eagle Valley regional study area, Nevada...................3–14

3.4B. Basin-fill aquifer potentiometric surface and oxidation-reduction 

classification zones, Spanish Springs Valley regional 

study area, Nevada. ............................................................................................... 3–15

3.5A. Ground-water flow model grid, boundary conditions, and location 

of public-supply wells, Eagle Valley regional study area, Nevada...............3–18

3.5B. Ground-water flow model grid, boundary conditions, and location 

of public-supply wells, Spanish Springs Valley regional 

study area, Nevada. ...............................................................................................3–19

3.6A. Distribution of hydraulic conductivity for model layer 1, 

Eagle Valley regional study area, Nevada. ........................................................3–20

3.6B. Distribution of hydraulic conductivity for model layer 2, 

Eagle Valley regional study area, Nevada. ........................................................3–21

3.7A. Distribution of hydraulic conductivity for model layer 1, 

Spanish Springs Valley regional study area, Nevada. ....................................3–22

3.7B. Distribution of hydraulic conductivity for model layer 2, 

Spanish Springs Valley regional study area, Nevada. ....................................3–23

3.7C. Distribution of hydraulic conductivity for model layer 3, 

Spanish Springs Valley regional study area, Nevada. ....................................3–24

Graphs showing:

3.8A. Relation between residual head and measured hydraulic head, 

Eagle Valley regional study area, Nevada. ........................................................3–26

3.8B. Relation between residual head and measured hydraulic head, 

Spanish Springs Valley regional study area, Nevada. ....................................3–26

Maps showing:

3.9A. Model-computed areas contributing recharge to public-supply wells, 

Eagle Valley regional study area, Nevada. ....................................................... 3–30

3.9B. Model-computed areas contributing recharge to public-supply wells, 

Spanish Springs Valley regional study area, Nevada. ....................................3–31

Tables

3.1. Summary of hydrogeologic and ground-water quality characteristics for

 the Basin and Range basin-fill aquifers and the Eagle Valley and Spanish 

Springs Valley regional study areas, Nevada................................................................ 3–4

3.2. Average ground-water pumping rates for public-supply wells, 1997– 2001, 

Eagle Valley regional study area, Nevada.................................................................... 3–12

3.3. Average ground-water pumping rates for public-supply wells, 1997– 2001, 

Spanish Springs Valley regional study area, Nevada................................................. 3–13

3.4. Model-computed water budget for 1997–2001 average conditions, 

Eagle Valley regional study area, Nevada.................................................................... 3–27

3.5. Model-computed water budget for 1997–2001 average conditions, 

Spanish Springs Valley regional study area, Nevada................................................. 3–27
Hydrogeologic Settings and Ground-Water Flow 

Simulations of the Eagle Valley and Spanish Springs 

Valley Regional Study Areas, Nevada

By Donald H. Schaefer, Jena M. Green, and Michael R. Rosen

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated in the Eagle and Spanish 

Springs Valleys, Nevada, as part of the U.S. Geological Survey 

National Water-Quality Assessment Program. The valley-fill 

aquifers in the Eagle and Spanish Springs Valleys regional 

study areas are representative of the Basin and Range basinfill aquifers, are important sources of water for agricultural 

irrigation and public water supply, and are susceptible and 

vulnerable to contamination. Three-dimensional, steady-state 

ground-water flow models were developed for the Basin and 

Range basin-fill aquifers in each of the valleys and calibrated 

to average conditions for the period from 1997 to 2001. The 

calibrated models and advective particle-tracking simulations were used to compute ground-water flow paths, areas 

contributing recharge, and traveltimes from recharge areas 

for public-supply wells. The Eagle Valley ground-water flow 

model is a two-layer, steady-state finite-difference model 

modified from a previous finite-element model of the basin, 

and the Spanish Springs Valley ground-water flow model is 

a three-layer, steady-state finite-difference model modified 

from a previous two-layer finite-difference model of the basin. 

Modeling results for the Eagle Valley indicate ground-water 

recharge is primarily from streams flowing into the basin from 

the surrounding mountains (mountain-front recharge) and 

from subsurface flow from the adjacent mountains (mountain-block recharge); ground-water discharge is primarily to 

public-supply wells and evapotranspiration. Modeling results 

for the Spanish Springs Valley indicate ground-water recharge 

is primarily from precipitation, irrigation, and canal leakage; 

ground-water discharge is primarily to public-supply wells 

and evapotranspiration. Particle-tracking simulations for all 

20 public-supply wells in Eagle Valley indicate that areas 

contributing recharge extend from the pumping wells in the 

valley to areas of mountain-block and mountain-front recharge 

along the edges of the basin with traveltimes from recharge 

areas on the order of 30 to 50 years. Particle-tracking results 

for all eight public-supply wells in Spanish Springs Valley 

were similar to those in the Eagle Valley with areas contributing recharge extending to the mountain front but with slightly 

greater traveltimes on the order of 50 to 100 years. In both the 

Eagle and Spanish Springs Valley models, areas contributing 

recharge extended to the general-head boundary cells along 

the mountain-front boundary of the alluvial aquifer indicating 

mountain-front and mountain-block recharge are important 

sources of water for the public-supply wells.

Introduction

Two regional study areas within the Nevada Basin and 

Range study unit of the U.S. Geological Survey National 

Water-Quality Assessment (NAWQA) Program were included 

in the study of the transport of anthropogenic and natural 

contaminants to public-supply wells (TANC). The first TANC 

regional study area is Eagle Valley, which includes Carson City and is part of the Carson River Basin. The second 

TANC regional study area is Spanish Springs Valley, north of 

Sparks, which is in the Truckee River Basin. The study areas 

are within the Basin and Range basin-fill aquifers, which are 

important water sources for agricultural irrigation and drinking-water supply throughout the region (fig. 3.1).

Purpose and Scope

The purpose of this Professional Paper section is to 

present the hydrogeologic setting of the Eagle Valley and 

Spanish Springs Valley regional study areas. The section also 

documents the setup and calibration of steady-state regional 

ground-water flow models for the study areas. Ground-water 

flow characteristics, pumping-well information, and waterquality data were compiled from existing data to develop a 

conceptual understanding of ground-water conditions in the 

study area. A two-layer steady-state ground-water flow model 

of the Eagle Valley basin-fill aquifer and a three-layer steadystate ground-water flow model of the Spanish Springs Valley 

basin-fill aquifer were developed and calibrated to average 

conditions for the period from 1997 to 2001. The 5-year 
3–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.1. Location of the Eagle Valley and Spanish Springs Valley regional study areas within the Basin and Range basin-fill 

aquifers.

N E W

M E X I C O

Great

Salt

Lake

A R I Z O N A

U T A H COLORADO

N E V A D A

C A L I F O R N I A

O R E G O N

I D A H O

W Y O M I N G

P A C I F I C

O C E A N

M E X I C O

Gulf of

California

Salt Lake City

Phoenix

San Diego

Los Angeles

Las

Vegas

Sacramento

Reno-Sparks

Carson City

Spanish

Springs

Valley

Eagle Valley

122° 121° 120° 119° 118° 117° 116° 115° 114° 113° 112° 111° 110° 109° 108° 107° 106° 

43° 

42° 

41° 

40° 

39° 

38° 

37° 

36° 

35° 

34° 

33° 

32° 

31° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 50 100 150 200 kilometers

0 50 100 miles

EXPLANATION

Eagle Valley and Spanish Springs Valley regional study areas

Basin and Range aquifer

USGS NAWQA study unit—Nevada Basin and Range
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–3

period 1997–2001 was selected for data compilation and modeling exercises for all TANC regional study areas to facilitate future comparisons between study areas. The calibrated 

ground-water flow models and associated particle tracking 

were used to simulate advective ground-water flow paths and 

to delineate areas contributing recharge to selected public-supply wells. Ground-water traveltimes from recharge to publicsupply wells, oxidation-reduction (redox) conditions along 

flow paths, and presence of potential contaminant sources in 

areas contributing recharge were tabulated into a relational 

database as described in Section 1 of this Professional Paper. 

This section provides the foundation for future ground-water 

susceptibility and vulnerability analyses of the study areas and 

comparisons among regional aquifers.

Study Area Description

The Nevada Basin and Range NAWQA study unit 

includes the Truckee and Carson River Basins in northwestern 

Nevada and northeastern California and the Las Vegas Valley 

area in southeastern Nevada (fig. 3.1). These two areas represent many of the diverse environments found in the Basin and 

Range physiographic province, which is characterized by high 

mountains surrounding valleys underlain by thick, unconsolidated deposits (Covay and others, 1996). The Nevada Basin 

and Range study unit is located in the Basin and Range basinfill aquifers, which are ranked fourth in total water use of the 

62 principal aquifers in the United States (Maupin and Barber, 

2005). The study areas were chosen because the aquifers are 

used extensively for public water supply, are susceptible and 

vulnerable to contamination, and are representative of the 

Basin and Range basin-fill principal aquifer (table 3.1).

Two study areas within the Nevada Basin and Range 

study unit were included in the TANC regional study. The first 

regional study area is the Eagle Valley, which includes Carson 

City and is part of the Carson River Basin (fig. 3.2A). The 

population of Carson City is greater than 50,000 (U.S. Census 

Bureau, 2003), and the area has experienced a steady population increase since the 1970s. The second regional study area 

is the Spanish Springs Valley, north of Sparks, which is in the 

Truckee River Basin (fig. 3.2B). The population of the Spanish 

Springs Valley has grown substantially since the early 1980s, 

and this growth has affected water quality in the basin (Seiler 

and others, 1999). The two areas were chosen for TANC 

regional studies because they have similar hydrologic and geologic characteristics, different rates of population increase, and 

different potential sources of ground-water contaminants.

Topography and Climate

The Eagle Valley is a semiarid basin in the west-central 

part of Nevada. The valley is bordered on the west by the Carson Range of the Sierra Nevada, on the north by the Virginia 

Range, on the east by Prison Hill and the Pine Nut Mountains 

and on the south by Carson Valley (fig. 3.2A). The floor of the 

Eagle Valley averages about 1,433 m above NAVD88, and the 

summit of Prison Hill is about 1,737 m. The Virginia Range 

is about 2,438 m in altitude; and the Carson Range is greater 

than 2,804 m in altitude (Maurer and others, 1996).

The Spanish Springs Valley is bounded on the west by 

Hungry Ridge and its unnamed southern extension with summits approaching 1,829 m. The northern boundary separating 

the Spanish Springs Valley from Warm Springs Valley is a 

narrow (less than 805 m) topographic divide lying between 

bedrock outcrops of the Hungry Ridge and the Pah Rah Range 

to the east (Berger and others, 1997). The southern boundary 

is bedrock and includes a low alluvial divide where an agricultural ditch (the Orr Ditch) enters and an agricultural drain (the 

North Truckee drain) exits the study area.

Climate in both valleys is similar, although the differing 

western boundaries (higher Carson Range and lower Hungry 

Ridge) affect precipitation in the valleys. Annual precipitation on the floor of the Eagle Valley averages about 25.4 cm 

(Arteaga and Durbin, 1979). Average annual precipitation 

along the crest of the Carson Range is about 96.5 cm. The Virginia Range receives much less precipitation than the Carson 

Range: average annual precipitation is slightly more than 35.6 

cm (Arteaga and Durbin, 1979). In both ranges, most precipitation falls as rain or snow during November through April. 

Snow in the Carson Range accumulates to several meters during most winters and melts in early spring to early summer.

Average annual precipitation on the floor of the Spanish 

Springs Valley is generally less than 20.0 cm. The surrounding 

mountains receive 22.9 to 27.9 cm of precipitation in an average year, and as much as 33.0 cm of precipitation may fall in 

the higher altitudes of the Pah Rah Range (VanDenburgh and 

others, 1973).

Surface-Water Hydrology

One large river, the Carson River, crosses the Eagle Valley, and several streams discharge into the Carson River within 

the valley (fig. 3.2A). The Carson River acts as both a recharge 

and discharge boundary to the ground-water system on the 

south and east sides of the basin. The annual mean flow in the 

Carson River is 11.7 cubic meters per second (m3/s) at the Carson City gage and 14.2 m3

/s, 11.3 km downstream at the Deer 

Run Road gage (periods of record 1940–2001 and 1979–2001, 

respectively (U.S. Geological Survey, 1939–00 and 1978–00). 

Streams in Ash and Kings Canyons drain the eastern flank of 

the Carson Range west of Carson City and provide perennial 

flow into the Eagle Valley during most years. The stream in 

Vicee Canyon flows downstream from the canyon mouth only 

during severe storms or during spring snowmelt in years with 

above-normal precipitation. The only other perennial stream is 

Clear Creek, which has the largest drainage area (40 km2) of 

any stream entering the Eagle Valley. The remaining streams 

entering Eagle Valley are ephemeral, flowing only occasionally onto the valley floor.

Surface water in the Spanish Springs Valley consists 

almost entirely of Truckee River water imported by way of the 
3–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 3.1. Summary of hydrogeologic and ground-water-quality characteristics for the Basin and Range basin-fill aquifers and the 

Eagle and Spanish Springs Valleys regional study areas, Nevada.

[m, meters; cm/yr, centimeters per year; m2/d, squared meters per day; m/d, meters per day; ET, evapotranspiration; mg/L, milligrams per liter]

Characteristic Basin and Range basin-fill aquifers Eagle and Spanish Springs Valleys

regional study areas

Geography

Topography Altitude ranges from about 46 m at Yuma, Arizona to 

more than 3,048 m at the crest of some mountain 

ranges (Robson and Banta, 1995). 

 Eagle Valley floor altitude ranges from 1,410 m to 

1,460 m.

Spanish Springs Valley floor ranges from about 

1,356 m to 1,450 m.

Climate Arid to semi-arid climate. Precipitation ranges from 

10 to 20 cm/yr in basins and 40 to 76 cm/yr in 

mountains (Robson and Banta, 1995).

Arid climate. Eagle Valley floor precipitation 

is about 25.4 cm/yr with up to 96.5 cm/yr 

precipitation in surrounding mountains. Spanish 

Springs Valley floor precipitation is less than 20.0 

cm/yr with up to 33.0 cm/yr in Pah Rah Range.

Surface-water hydrology Streams drain from surrounding mountains into 

basins. Basins generally slope toward a central 

depression with a main drainage that is dry most 

of the time. Many basins have playas in their 

lowest depressions. 

Ground-water discharge to streams can occur in 

basin depressions. (Planert and Williams, 1995)

Carson River crosses south and east sides of Eagle 

Valley and is a recharge and discharge boundary. 

Spanish Springs Valley contains no natural 

streams, although the Orr Ditch, which imports 

irrigation water, crosses the valley. 

Land use Undeveloped basins are unused, grazing, and rural 

residential. Developed basins are urban, suburban 

and agricultural.

Eagle Valley—Urban, suburban, and rural 

residential.

Spanish Springs Valley—Urban, suburban, rural 

residential, agricultural.

Water use Ground-water withdrawals from wells supply 

water for agricultural irrigation and municipal 

use. Population increases since the 1960’s have 

increased the percentage of water being used for 

municipal supply.

Eagle Valley—Approximately 30 percent of public 

supply provided by ground water and 70 percent 

provided by surface water.

Spanish Springs Valley—Similar to Eagle Valley 

but with some agricultural irrigation ground-water 

use.

Geology

Surficial geology Tertiary and Quaternary unconsolidated to 

moderately consolidated fluvial gravel, sand, silt 

and clay basin-fill deposits include alluvial fans, 

flood plain deposits, and playas. (Robson and 

Banta, 1995; Planert and Williams, 1995)

Eagle Valley—Tertiary and Quaternary 

unconsolidated fluvial basin-fill sediment up to 

610 m in thickness. Sediments are coarse grained 

near the basin margins and finer grained near the 

basin center.

Spanish Springs Valley—Similar to Eagle Valley 

with greater variation in basin-fill thickness.

Bedrock geology Mountains surrounding basins are composed of 

Paleozoic to Tertiary bedrock formations. Tertiary 

volcanic and metamorphic rocks are in general 

impermeable. Paleozoic and Mesozoic carbonate 

rocks are cavernous allowing inter-basin flow in 

some areas. (Robson and Banta, 1995; Planert and 

Williams, 1995) 

Eagle Valley—Carson Range west of Eagle Valley is 

composed of Mesozoic granitic and metamorphic 

rocks overlain by Tertiary volcanic rocks.

Spanish Springs Valley—Surrounding ranges are 

composed of Mesozoic granitic and metamorphic 

rocks overlain by Tertiary volcanic rocks.
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–5

Characteristic Basin and Range basin-fill aquifers Eagle and Spanish Springs Valleys

regional study areas

Ground-water hydrology

Aquifer conditions Unconfined basin-fill aquifers surrounded by 

relatively impermeable bedrock mountains and 

foothills. Basin ground-water flow systems are 

generally isolated and not connected with other 

basins except in some locations where basins are 

hydraulically connected via cavernous carbonate 

bedrock.

Eagle Valley—Unconfined basin-fill aquifer 

surrounded by bedrock mountains. Recharge 

originates as precipitation in the mountains. 

Ground-water flow is generally eastward across 

the valley because there is greater precipitation in 

the Carson Range to the west.

Spanish Springs Valley—Unconfined basin-fill 

aquifer surrounded by bedrock mountains. 

Hydraulic properties Transmissivity ranges from less than 93 m2/d to 

greater than 2,790 m2/d. In general, alluvial fan 

deposits near basin margins are more conductive 

than flood plain and lacustrine deposits near basin 

centers. (Robson and Banta, 1995; Planert and 

Williams, 1995)

Eagle Valley—Transmissivity ranges from 42 to 

77 m2/d (Johnson and others, 1996). Hydraulic 

conductivity ranges from 0.12 to 1.6 m/d for basin 

fill (Arteaga, 1986).

Spanish Springs Valley—Hydraulic conductivity 

ranges from 0.15 to 3.6 m/d (Berger and others, 

1997). 

Ground-water budget Recharge to basin fill deposits is from surfacewater runoff in mountains where precipitation 

is highest. Ground-water discharges naturally 

as evapotranspiration (ET) to playas and stream 

channels in basin depressions. Ground-water 

withdrawal from wells is largest component of 

discharge from Basin and Range aquifers. (Robson 

and Banta, 1995)

Eagle Valley—Recharge to basin fill is from 

surface-water runoff in mountains. Runoff from 

Carson Range is largest component of recharge. 

Discharge to ET, base flow to Eagle Valley Creek, 

and municipal pumping wells. Pumping has 

decreased ET.

Spanish Springs Valley—Less precipitation than 

Eagle Valley. Recharge is from imported surface 

water and local precipitation. Discharge is to ET, 

ground-water underflow, and pumping wells.

Ground-water quality

Water quality varies between basins. Dissolved solids 

can range from less than 500 mg/L to over 35,000 

mg/L. Generally, low-dissolved solids, oxic water 

occurs near recharge areas of basin margins. Highdissolved solids anoxic water occurs with depth 

or near basin centers and playa lakes (Robson and 

Banta, 1995; Planert and Williams, 1995).

Eagle Valley and Spanish Springs Valley exhibit 

similar water quality of calcium-bicarbonate type 

water. Dissolved solids range from 100 to more 

than 3,000 mg/L and averages 250 mg/L. Eagle 

Valley pH range is 6.5 to more than 8. Spanish 

Springs pH generally is greater than 8. Eagle 

Valley redox conditions are generally oxic with 

some iron and manganese reducing conditions 

near basin center. Spanish Springs Valley is 

predominantly oxic.

Table 3.1. Summary of hydrogeologic and ground-water-quality characteristics for the Basin and Range basin-fill aquifers and the 

Eagle and Spanish Springs Valleys regional study areas, Nevada.—Continued

[m, meters; cm/yr, centimeters per year; m2/d, squared meters per day; m/d, meters per day; ET, evapotranspiration; mg/L, milligrams per liter]
3–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.2A. Topography, hydrologic features, and locations of public-supply wells, Eagle Valley regional study area, 

Nevada.

Deer Run Road gage

Carson City gage

395

50

395

50

C

A

R

S

O

N

R

A

N

G

E

V I R G I N I A R A N G E

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Washoe Lake

Marlette

Lake

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 55' 119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Land elevation, in meters above sea level

Extent of active model cells

Hydrographic-area boundary

Golf course

Public-supply well

Stream gage

3600

3200

2800

2400

2000

1600

1200

800

400

0
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–7

Figure 3.2B. Topography, hydrologic features, and locations of public-supply wells, Spanish Springs Valley regional study 

area, Nevada.

80

395

80

445

445

Spanish

Springs

Peak

W A R M

S P R I N G S

V A L L E

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

T R U C K E E M E A D O W S

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

Truckee

R E N O River

S P A R K S

WASHOE COUNTY

STOREY COUNTY

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Land elevation, in meters above sea level

3600

3200

2800

2400

2000

1600

1200

800

400

0

Extent of active model cells

Hydrographic-area boundary

Public-supply well
3–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Orr Ditch, which is used to support agriculture in the southern 

part of the valley (fig. 3.2B). Several dry channels throughout the study area, however, indicate sufficient precipitation 

occasionally falls to produce runoff from surrounding mountains. The Orr Ditch has delivered water from the Truckee 

River through the southern boundary of the valley since 1878 

(Berger and others, 1997). The ditch is unlined throughout its 

11.2-km length in the valley and has numerous take-out gates 

to smaller ditches used for flood irrigation and stock watering. 

The North Truckee Drain originates near the center of the irrigated lands within the area encompassed by the Orr Ditch. The 

drain conveys unused irrigation water and, to a lesser extent, 

ground-water discharge out of the study area.

Land Use

Land use in the Eagle Valley slowly changed from unused 

scrubland to urban and residential development over the past 

several decades. The population of Carson City was estimated 

at 35,000 in 1979 and was more than 50,000 by 2001 (U.S. 

Census Bureau, 2003). The initial city limits slowly expanded 

in all directions as urban development progressed, and little 

land in the valley is currently (2006) used for pasture or agriculture.

Development in the Spanish Springs Valley was virtually nonexistent before about 1960, except for a small number 

of agricultural homesteads in the southern part of the valley. 

Based on comparison of aerial photographs taken in 1956, 

1977, and 1994 and assessor parcel maps, general agricultural land use within the area serviced by the Orr Ditch has 

remained relatively unchanged, although some acreage has 

been developed in the southwest part of the valley. Urban 

growth and development in the Spanish Springs Valley 

increased sharply after 1979 when the population increased 

from less than 800 in 1979 to more than 4,000 in 1990 (Berger 

and others, 1997). Most subdivisions are located around the 

northern perimeter of the Orr Ditch with smaller subdivisions 

in the southern part of the valley. Individual homes also are 

scattered in the northern part of the basin in and adjacent to 

the surrounding mountains.

Water Use

Water use in the Eagle Valley is primarily for domestic purposes and is supplied though public water systems. 

Ground-water pumping provides about 30 percent of the 

public water supply, and surface-water sources supply the 

remaining 70 percent (Welch, 1994). Lesser amounts of water 

are provided by domestic wells. Very little water is used for 

agriculture or manufacturing. Most of the homes in the Eagle 

Valley are served by a wastewater-treatment plant that exports 

effluent out of the basin.

The Spanish Springs Valley has water-use characteristics 

similar to those in the Eagle Valley, although there is slightly 

more agricultural water use in the Spanish Springs Valley. 

As of 1994, more than 3,000 subdivision houses had water 

supplied by a public utility; however, nearly 1,000 of these 

received water from a supplier outside of the valley (Berger 

and others, 1997). Of the total number of houses with public water supply, 1,600 have septic systems and about 1,400 

are served by wastewater-treatment facilities located outside 

the basin. Nearly 200 houses had domestic wells with septic 

systems. Although no new septic systems are allowed in the 

basin, there are now approximately 2,300 parcels with septic 

systems in Spanish Springs Valley (Rosen and others, 2006).

Conceptual Understanding of the 

Ground-Water System

Unconfined to confined ground water is present in the 

Eagle Valley Quaternary basin-fill sediments and the surrounding bedrock, although most wells are completed in the basinfill deposits (fig. 3.3A). Ground-water recharge originates as 

precipitation in the surrounding mountains, and ground water 

generally flows eastward through the Eagle Valley basin-fill 

sediments because there is greater precipitation at higher 

altitudes, especially in the Carson Range (Worts and Malmberg, 1966; Arteaga, 1986; Maurer and Fisher, 1988). Prior 

to ground-water development in Eagle Valley, ground water 

discharged by evapotranspiration through phreatophytes and 

pasture grasses and by subsurface flow to the Carson River 

flood plain. Ground-water pumping, mostly for municipal 

supply, has diverted ground water that would have historically 

discharged through phreatophytes or flowed eastward to the 

Carson River flood plain.

Similar to Eagle Valley, ground water in the Spanish 

Springs Valley is present in the Quaternary basin-fill alluvial 

sediments and the surrounding bedrock both under water-table 

and confined conditions. However, in contrast to Eagle Valley, 

ground-water recharge in the Spanish Springs Valley is derived 

from imported surface water and precipitation falling within 

the drainage basin (fig. 3.3B). Ground water flows generally 

in an eastward direction toward the North Truckee Drain, 

irrigated areas, and areas of evapotranspiration (Berger and 

others, 1997).

Geology

The mountains surrounding the Eagle Valley consist of 

Mesozoic granitic and metamorphic rocks overlain by Tertiary 

volcanic rocks (Welch, 1994). The mountains were uplifted 

and the valley floor was lowered relative to the mountains by 

extensional tectonics, forming a basin that is partly filled with 

Quaternary sediments eroded from the surrounding mountains. In this chapter, the consolidated rocks exposed in the 

mountains and buried beneath the sediments in the valley are 

collectively called bedrock; the sediments in the valley are collectively called basin-fill sediments. The basin-fill sediments 
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–9

Precipitation

Basin-fill sediments

Fault

Bedrock

Recharge

Runoff

Spring

Not to scale

Well

Interbedded fine-grained deposits

Orr Ditch

North Truckee Drain

Septic tanks

Fields Water table

Bedrock

Highway 445 Irrigation

return flow

Transmission

losses

Applied

surface water

Ground-water

withdrawal

North

West

EXPLANATION

Ground-water flow direction

Surface-water flow direction

Infiltration of imported surface water

Evapotranspiration

T

Precipitation

Fault

Fault

Basin-fill sediments

Weathered and fractured bedrock

Bedrock

East

South

Municipal

pumping

Infiltration

from lawns

Infiltration from

golf-courses

Infiltration

from streamflow

Evapotranspiration

from pastures

Infiltration

from diversions

Infiltration

from runoff

Carson Hot Springs

Runoff

Carson

City Municipal

diversion

Evapotranspiration

from pheatophytes

Subsurface

flow to

Carson

River

Subsurface flow through

weathered bedrock

Not to scale

EXPLANATION

Ground-water flow direction

Infiltration

Evapotranspiration

Figure 3.3A. Basin-fill ground-water flow system of the Eagle Valley 

regional study area, Nevada.

Figure 3.3B. Basin-fill ground-water flow system of the Spanish Springs Valley 

regional study area, Nevada.
3–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

consist primarily of poorly sorted sands and gravels with small 

boulders and intervening clay layers. Basin-fill sediments 

are generally coarse grained near the base of the mountains 

and finer grained near the center of the valley. The basin-fill 

sediments are estimated to be about 366 m thick 2.4 km west 

of Lone Mountain, about 122 to 244 m thick beneath the 

northeastern and southern parts of the Eagle Valley, and about 

610 m thick about 1.6 km northwest of Prison Hill (Arteaga, 

1986). In general, the deepest part of the alluvial basin is in 

the center of the Eagle Valley.

The geologic setting of the Spanish Springs Valley is 

similar to that of the Eagle Valley, consisting of basin-fill 

sediments surrounded by mountains composed of Mesozoic 

granitic and metamorphic rocks overlain by Tertiary volcanic 

rocks (Berger and others, 1997). For purposes of this report, 

the major geologic units identified in the Spanish Springs 

Valley were subdivided into two general groups on the basis of 

their hydrogeologic properties: (1) consolidated igneous and 

metamorphic bedrock, which commonly has low porosity and 

permeability except where fractured, and (2) basin fill, which 

is highly porous and transmits water readily. The structural 

depression occupied by the Spanish Springs Valley is filled 

in part by interbedded deposits of sand, gravel, clay, and silt 

derived primarily from adjacent mountains. These deposits 

form the basin-fill aquifer, which is bounded and underlain by 

consolidated rock. The areal extent of the basin-fill aquifer is 

approximated by the contact between consolidated rock and 

basin fill along the periphery of the valley floor. Total surface 

area of basin fill is about 88 km2, or almost 43 percent of the 

total drainage area of Spanish Springs Valley (Berger and 

others, 1997). On the north, an alluvium-covered topographic 

divide exists between the Spanish Springs and Warm Springs 

Valley. At the southern boundary of the study area the saturated basin fill in the Spanish Springs Valley may be continuous with saturated basin fill of Truckee Meadows (fig. 3.2B). 

This boundary, which is not a topographic divide, is underlain 

by consolidated rock at depths of less than 6 m. Basin fill 

also occupies the structurally controlled Dry Lakes area in 

the southeast part of the Pah Rah Range (Berger and others, 

1997).

Wells drilled in the Spanish Springs Valley range in depth 

from several meters to more than 240 m, and most wells are 

completed in basin fill (Berger and others, 1997). Discrepancies in basin-fill thickness reported on drillers’ logs for several 

wells limit the use of these logs to estimate areal distribution 

of basin-fill thickness. Basin-fill sediments are thickest along a 

northeast-trending trough close to the mountain front of Hungry Ridge, where depth to bedrock reaches a maximum value 

of about 305 m (Berger and others, 1997). In general, the 

greatest depth to bedrock is beneath the west part of the Spanish Springs Valley, and the basin-fill sediments thin toward the 

east. In the southern part of the valley, depth to bedrock is less 

than 30 m, and basin-fill sediments thin toward the southern 

boundary (Berger and others, 1997).

Ground-Water Occurrence and Flow

In the northern part of the Eagle Valley, ground water 

flows eastward and southeastward beneath the topographic 

divide into Dayton Valley (fig. 3.4A) (Worts and Malmberg, 

1966; Arteaga, 1986; Maurer, 1997). In the southern part of 

the Eagle Valley, some ground water flows northeastward 

around the northern end of Prison Hill and southeastward 

beneath the topographic divide into the Carson Valley (Worts 

and Malmberg, 1966; Arteaga, 1986). Figure 3.4A shows the 

potentiometric surface for 2001 as simulated in the upper layer 

of the Eagle Valley model.

Ground water flows both north and south from the 

ground-water divide that has developed beneath the center of 

the Spanish Springs Valley (fig. 3.4B). Ground water flows 

south out of the valley through the basin fill and probably 

through fractured bedrock to Truckee Meadows. Ground water 

also flows from the ground-water divide toward the northern 

part of the study area. Geochemical data from a municipal 

well, which is screened in more than 37 m of saturated basin 

fill, indicates the source of ground water is a mixture of local 

recharge and water from the Truckee River. Stable isotope 

and chlorofluorocarbon data (Berger and others, 1997) support the conclusion that imported Truckee River water moves 

northward from the Orr Ditch. Figure 3.4B shows the potentiometric surface for 2001 as simulated in the upper layer of the 

Spanish Springs Valley model.

Aquifer Hydraulic Conductivity

The hydraulic conductivity and transmissivity of basinfill sediments in the Eagle Valley have been estimated by 

Arteaga (1986), Johnson and others (1996), and Maurer and 

others (1996). Values of hydraulic conductivity reported by 

Arteaga (1986) ranged from 0.12 to 1.6 m/d. Transmissivities of 42, 45, and 77 m2

/d for three wells were reported by 

Johnson and others (1996). Dividing transmissivity values by 

aquifer saturated thickness in the perforated interval of the 

respective wells results in hydraulic conductivities of 0.98, 

0.91, and 0.98 m/d, respectively. Maurer and others (1996) 

estimated hydraulic conductivities of lithologic units in the 

Eagle Valley basin-fill sediments and in fractured and weathered bedrock from correlations between slug-test analyses and 

borehole resistivity logs. In the basin-fill sediments, hydraulic 

conductivity ranged from 0.006 to 0.027 m/d for clay and 

from 10 to 14 m/d for sand and gravel (Maurer and others, 

1996). Hydraulic conductivity of weathered and unweathered 

granitic bedrock closed fractures ranged from 0.02 to 0.28 

m/d, whereas hydraulic conductivity of open-fractured metamorphic rocks was up to 18 m/d (Maurer and others, 1996) 

indicating that metamorphic rocks with open fractures can 

be more permeable than basin-fill sediments and weathered 

granitic rocks.
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–11

In the Spanish Springs Valley, hydraulic conductivity was 

calculated from several aquifer tests completed in the upper 

100 m of saturated basin fill and ranged from 0.15 to about 

3.6 m/d (Berger and others, 1997). Analyses of geophysical 

and lithologic logs and grain-size distributions collected from 

observation wells drilled as part of the study by Berger and 

others (1997) and Washoe County (1993) provided additional 

qualitative estimates of the ability of the basin-fill aquifer to 

transmit water. In general, basin fill derived from volcanic 

rocks tends to be dominated by fine-grained deposits resulting in an overall lower hydraulic conductivity than basin fill 

derived from granitic bedrock, which is dominated by sand 

and gravel. Hydraulic conductivity in the deepest part of the 

basin fill is unknown but is probably less than that of the upper 

100 m owing to sediment compaction and induration. The distribution of hydraulic conductivity within the basin-fill aquifer 

was refined during ground-water flow model calibration, as 

discussed in the section “Ground-Water Flow Modeling.”

Water Budget

Historical recharge estimates for the Eagle Valley were 

based on precipitation data. Original estimates of recharge to 

Eagle Valley (Worts and Malmberg, 1966) used an empirical 

relation between altitude, precipitation, and recharge (Maxey 

and Eakin, 1949) to estimate ground-water recharge to basins 

in eastern Nevada. Worts and Malmberg (1966) estimated 

29,300 m3/d (15 cm/yr over the modeled area of 71 km2) of 

potential recharge to the Eagle Valley in 1965. A subsequent 

recharge estimate of 18,900 m3/d (9.7 cm/yr over the modeled 

area) for the period 1967–77 was made for Eagle Valley using 

a relation between precipitation and surface runoff from Clear 

Creek and creeks in Ash and Kings Canyons (Arteaga and 

Durbin, 1979).

Sources of recharge and inflow to the Eagle Valley 

considered by this study include subsurface inflow from the 

mountains (mountain-block recharge); infiltration of streamflow from Clear, Kings Canyon, and Ash Canyon Creeks and 

ephemeral streams (mountain-front recharge); infiltration of 

precipitation; infiltration of lawn and golf course irrigation; 

and effluent from septic tanks. Estimates of inflow made for 

1997–2001 conditions were made from inflow estimates for 

the period 1995–1998 (Maurer and Thodal, 2000), which were 

wet years. Average annual precipitation from the two periods was used to scale the 1995–1998 inflow estimates to the 

period 1997–2001. Mountain-block recharge was estimated to 

be about 15,600 m3/d for 1995–98 (Maurer and Thodal, 2000) 

and about 12,900 m3/d for 1997–2001 average conditions, 

and mountain-front recharge from infiltration of streamflow 

was about 11,800 m3/d during 1995–98 (Maurer and Thodal, 

2000) and about 8,800 m3/d for 1997–2001 average conditions. Recharge from precipitation on open areas of the valley 

floor ranged from 110 to 300 m3/d (0.06 to 0.15 cm/yr over the 

modeled area) for 1997–2001 average conditions. Recharge 

from lawn irrigation is estimated to range from 3,300 to 

8,200 m3/d for 1995–98 (Maurer and Thodal, 2000) and from 

about 2,700 to 7,700 m3/d for 1997–2001 average conditions. 

Recharge from irrigation of golf courses with treated effluent 

is about 2,000 m3/d (Maurer and Thodal, 2000). An estimated 

900 septic tanks were functioning in the Eagle Valley in 1997 

with an estimated use and infiltration rate of 0.95 m3/d per 

tank for a total of about 855 m3/d. (Leanna Stevens, Carson 

City Public Utilities Department, oral and written communs., 

1998). Summing the recharge components results in a total 

recharge estimate from sources on the valley floor (excluding mountain-block recharge) ranging from 18,000 to 23,200 

m3/d (9.3 to 12 cm/yr over the modeled area) for 1995–98 

(Maurer and Thodal, 2000) and from about 14,500 to 19,600 

m3/d (7.5 to 10.1 cm/yr over the modeled area) for 1997–2001 

average conditions. Estimates for the total for all sources of 

ground-water recharge and subsurface inflow to the Eagle 

Valley basin-fill aquifer range from approximately 27,400 to 

32,500 m3/d for 1997–2001. Estimates of ground- water-budget components are probably within 20 percent of their actual 

values. Water-budget components of greatest uncertainty are 

subsurface inflow, recharge from ephemeral streamflow, and 

recharge from lawn irrigation.

Ground water in the basin-fill aquifer of the Eagle Valley is discharged by evapotranspiration from bare soil and 

plants, by pumping, and to base flow of Eagle Valley Creek 

and unnamed creeks. In 1964, about 20 km2 near the center 

of the valley were covered with phreatophytes (plants that 

use ground water) and pasture grasses (Worts and Malmberg, 

1966, p. 27). Since that time, many acres of phreatophytes 

and pasture grasses have been replaced by urban and residential development. Based on indirect evidence, phreatophytes 

covered about 4.4 km2 in 1997. In addition, ground-water 

pumping has caused water levels to decline, further reducing the amount of ground water discharged by phreatophytes. 

Since 1964, ground-water discharge to public-supply wells has 

increased and discharge by evapotranspiration has decreased. 

For this study, evapotranspiration within the Eagle Valley 

was estimated as about 15,100 m3/d based on output from the 

ground-water flow model and a known acreage where evapotranspiration occurs. Ground-water pumping was 25,397 m3

/d 

from 1997 to 2001 (table 3.2). Where the water table is close 

to land surface, ground water also discharges as seepage to 

Eagle Valley Creek and two unnamed creeks and as evapotranspiration from phreatophytes. Base flow in Eagle Valley 

Creek averaged 21 m3/d for 1997–2001 (U.S. Geological Survey, 1997–01). Estimated total ground-water discharge for the 

Eagle Valley basin-fill aquifer is approximately 47,900 m3/d 

with about 15,100 m3/d going to evapotranspiration, 25,400 

m3/d going to pumping, and 7,400 m3/d going to surface-water 

base flow based on ground-water flow model results.
3–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 3.2. Average ground-water pumping rates for publicsupply wells, 1997–2001, Eagle Valley regional study area, Nevada 

(Nevada State Engineer’s office, written commun., 2001).

[m3/d, cubic meters per day]

Well Pumping rate

(m3/d)

3 1,740

4 723

5 970

6 2,301

7 668

8 1,397

9 882

10 3,123

11 1,175

24 2,219

33 277

34 932

38 879

40 1,937

43 1,537

44 408

45 1,504

46 2,408

47 304

48 0

Total, all wells 25,397

Sources of ground-water recharge and inflow to the Spanish Springs Valley considered by this study include infiltration 

from the Orr Ditch (canal leakage), infiltration of precipitation, subsurface inflow from the surrounding mountains 

(mountain-block recharge), infiltration of water from lawn irrigation, and effluent from septic tanks. Ground-water recharge 

from precipitation takes place in or adjacent to the mountains 

in the Spanish Springs Valley through weathered or fractured 

bedrock or when intermittent runoff infiltrates dry channel 

deposits (fig. 3.3B). Precipitation that falls on the valley floor 

is considered a negligible source of recharge, although some 

recharge may be generated during heavy and localized rain 

showers. In eastern and western parts of the valley, ground 

water in basin-fill deposits generally flows toward the center 

of the basin, away from recharge-source areas in the mountains. Potential recharge, generated from nearly 11,800 m3

/d of 

annual precipitation (Berger and others, 1997) estimated to fall 

within the topographically closed Dry Lakes area (fig. 3.2B), 

may enter the basin fill at depth through fractures within the 

Pah Rah Range along the southeastern part of the study area.

Berger and others (1997) estimated anthropogenic 

sources of recharge to the Spanish Springs Valley on the basis 

of the amount of ground-water recycled from municipal and 

domestic uses. Water applied to outdoor lawn and shrub watering is mostly consumed by evapotranspiration and was considered an insignificant contributor to ground-water recharge 

(Berger and others, 1997). Recharge from septic systems 

(indoor uses) was estimated as 75 percent of the total amount 

of water delivered to the household during winter months, 

when outdoor watering is at a minimum. This monthly volume 

of water was assumed constant and was prorated over an 

entire year to arrive at an annual estimate of recharge from 

septic systems, which was approximately 1,600 m3/d for 1994 

(Berger and others, 1997). In Spanish Springs Valley, based on 

field and empirical techniques, total recharge from all sources 

is estimated at about 14,800 m3/d (Berger and others, 1997). 

An estimated 54 percent of recharge is from canal leakage 

from the Orr Ditch (Truckee River water that is diverted into 

the Spanish Springs Valley) with the remainder coming from 

mountain-block recharge, infiltration of precipitation, infiltration from lawn irrigation, and septic-tank effluent.

Prior to urban development and ground-water withdrawal 

for water supply, evapotranspiration was the principal mechanism of ground-water discharge from Spanish Springs Valley. 

In areas where the water table is less than one meter below 

land surface, ground water can be discharged by evaporation. 

Under natural conditions, bare-soil evaporation in the Spanish Springs Valley probably took place in the area surrounding the springs, where the water table is near land surface. 

Transpiration by phreatophytes has been documented in other 

arid basins in Nevada to consume relatively large quantities of 

ground water (Robinson, 1970; Harrill, 1973, table 9; Berger, 

1995, p. 35). Rush and Glancy (1967) estimated about 7.7 km2

of phreatophytes discharged nearly 3,000 m3/d of ground water 

by evapotranspiration under natural conditions in the Spanish 

Springs Valley (conditions without the Orr Ditch). Berger and 

others (1997) estimated 1,200 m3/d of ground-water discharge 

from areas surrounding the Orr Ditch. The total estimate of 

ground-water discharge by evapotranspiration in Spanish 

Springs Valley is about 8,400 m3/d.

Similar to the Eagle Valley, ground-water discharge to 

public-supply wells has increased and discharge by evapotranspiration has decreased as urban development occurred in 

the Spanish Springs Valley. Average 1997–2001 ground-water 

pumping rates for public-supply wells in the Spanish Springs 

Valley are listed in table 3.3 and total approximately 4,850 

m3/d.
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–13

Table 3.3. Average ground-water pumping rates for publicsupply wells, 1997–2001, Spanish Springs Valley regional study 

area, Nevada, Nevada (Nevada State Engineer’s office, written 

commun., 2001).

[m3/d, cubic meters per day]

Well name Pumping rate

(m3/d)

DS1 838

DS2 27

DS3 1,458

DS4 540

SC2 975

SC3 121

SC4 581

SC5 310

Total 4,850

Ground-Water Quality

The ground-water quality of the Eagle Valley and Spanish 

Springs Valley is similar, although there is considerable variability in the major-ion composition of both areas. Calcium 

and sodium are the predominant cations, and bicarbonate and 

sulfate are the predominant anions, although most ground 

water is dominated by calcium and bicarbonate. Dissolvedsolids concentrations range from approximately 100 mg/L to 

more than 3,000 mg/L with a median of about 250 mg/L. The 

pH within the Eagle Valley Basin ranges from approximately 

6.5 to greater than 8 pH units, and the pH of the Spanish 

Springs Valley ground water is more basic than Eagle Valley ground water, with most values greater than 8 pH units 

(Welch, 1994; Christian Kropf, Washoe County Department of 

Water Resources, written commun., 2001).

Oxidation-reduction (redox) conditions in Eagle Valley 

tend to follow trends that are controlled by the mountain-front 

and mountain-block recharge (fig. 3.4A). The most oxygenated ground water occurs around the edges of the basin near 

the mountain recharge areas, regardless of depth, and less 

oxygenated water is located near the center of the basin. Some 

areas near the basin center exhibit conditions consistent with 

manganese- and iron-reducing redox conditions, but oxygen 

and nitrate-reducing conditions predominate in the basin. 

Depth-related trends in redox conditions are not apparent in 

the Eagle Valley.

The Spanish Springs Valley aquifer is dominantly oxygen 

reducing (fig. 3.4B), although there are relatively few available water-quality analyses for redox classification. Two wells 

exhibited concentrations consistent with iron-reducing conditions, but these wells are completed in fractured bedrock and 

are probably not related to the redox conditions in the basinfill aquifer (Christian Kropf, Washoe County Department of 

Water Resources, written commun., 2001).

Subsurface outflow from Spanish Springs Valley to the 

Truckee Meadows was estimated between 330 and 500 m3/d 

(Cohen and Loeltz, 1964, p. 23; Rush and Glancy, 1967). 

These investigators evaluated subsurface outflow through the 

basin fill and did not attempt to estimate flow volumes through 

fractured bedrock. However, subsurface flow to the Truckee 

Meadows probably moves through fractured or weathered bedrock, as indicated from stable isotope data (Berger and others 

1997, p. 48). Total discharge from the Spanish Springs Valley 

from evapotranspiration, pumping, and subsurface outflow is 

estimated at about 13,750 m3/d.
3–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.4A. Basin-fill aquifer potentiometric surface and oxidation-reduction classification zones, Eagle Valley regional 

study area, Nevada.

395

50

395

50

1460

1440

1420

1420

1420

1430

1450

1440

1430

1450

1410

1400

1400

1410

1410

1420

1420

1440

1430

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson

River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Oxygen reduction

Nitrate reduction

Manganese reduction

Iron reduction with high sulfate

Direction of ground-water flow

Line of equal potentiometric-surface elevation, 1997–2001.

 Contour interval 5 meters. Datum is sea level.

Extent of active model cells

1420
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–15

Figure 3.4B. Basin-fill aquifer potentiometric surface and oxidation-reduction classification zones, Spanish Springs Valley 

regional study area, Nevada.

395

445

445

1360

1360

1380

1400

1360

1340

1380

1400

1420

1360

1340

1370

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Oxygen reduction

Nitrate reduction

Manganese reduction

Iron reduction with high sulfate

1360

Direction of ground-water flow

Line of equal potentiometric-surface elevation, 1997–2001.

 Contour interval 10 meters. Datum is sea level.

Extent of active model cells
3–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Ground-Water Flow Simulations

The modular ground-water flow simulation code MODFLOW-2000 (Harbaugh and others, 2000) was used to construct steady-state finite-difference ground-water flow models 

for the Eagle and Spanish Springs Valleys representing average conditions for the 5-year period from 1997 to 2001. Both 

models were modified from previously existing models and 

recalibrated to average conditions for 1997–2001. The following sections present details of the modeled areas, model input, 

model calibration, and particle-tracking simulations.

Modeled Areas and Spatial Discretizations

The Eagle Valley model simulates ground-water flow 

in the basin-fill deposits. The modeled area covers the entire 

valley floor of approximately 70 km2 where basin-fill deposits 

are exposed at the surface, and the model perimeter coincides 

with the horizontal extent of the basin-fill aquifer. The model 

grid (fig. 3.5A) contains 186 rows and 130 columns with grid 

cells 76 m on a side. The model contains 48,360 cells of which 

24,356 cells are active. Vertically, the model is discretized into 

two layers. The top layer (layer 1) represents coarse-grained 

alluvial material in the upper 30 m of the basin fill, and layer 

2 represents the underlying coarse-grained alluvial material. 

Layer 2 thickness extends to the base of basin-fill sediments as 

determined from gravity and seismic surveys (Arteaga, 1986) 

ranging from 50 to 2,160 m. Both layers are simulated as 

confined. The intervening fine-grained confining layer is simulated by a vertical leakance coefficient, which allows some 

flow between the two coarse-grained layers. The Eagle Valley 

MODFLOW finite-difference model was converted from a 

finite-element model constructed in the late 1970s (Arteaga, 

1986) by overlaying the finite-difference grid on the finite-element mesh and interpolating the hydrologic properties to the 

finite-difference grid.

The Spanish Springs Valley finite-difference groundwater flow model used for this study was originally developed by Berger and others (1997) and later modified by the 

Washoe County Department of Water Resources (Wyn Ross, 

Washoe County Department of Water Resources, written commun., 2003). The original Spanish Springs Valley model grid 

contained 37 rows, 28 columns, and 2 layers that divided the 

saturated basin fill into discrete three-dimensional model cells. 

Variable node spacing was used to provide higher resolution 

in areas of concentrated ground-water recharge and discharge 

related to the importation of Truckee River water. Model-cell 

size ranged from a minimum of 62,500 m2 (250 m by 250 m) 

to a maximum of 250,000 m2 (500 m by 500 m). Of the 1,036 

cells in each model layer, 625 were active in layer 1 and 282 

were active in layer 2. The top 100 m of saturated basin fill 

was represented as unconfined by layer 1, and the processes 

of ground-water recharge and discharge were simulated in 

layer 1. Layer 2 extended from the bottom of layer 1 to the 

top of consolidated bedrock, functioning as a conduit for deep 

flow and as a reservoir of stored water. Layer 2 was simulated 

as convertible from confined to unconfined, which allowed 

conversion to unconfined conditions if water levels dropped 

below the bottom of layer 1. The original Spanish Springs 

Valley model (Berger and others, 1997) was slightly altered by 

Washoe County Department of Water Resources to facilitate 

their management of ground-water resources in the valley 

(Wyn Ross, Washoe County Department of Water Resources, 

written commun., 2003). The altered model now contains 

71 rows, 35 columns, and 3 layers (fig. 3.5B). The grid cells 

throughout the entire model are now 250 m on a side. The 

altered model contains 7,455 model cells of which 2,917 are 

active. Layer 3 represents a basalt layer at depth penetrated by 

several newer supply wells on the east side of the valley. The 

altered model provides better coverage of the modeled area 

especially for the purposes of this study.

Boundary Conditions

Model stresses for both modeled areas include areal 

recharge from precipitation and irrigation, subsurface recharge 

from the surrounding mountains (mountain-block recharge), 

recharge from and discharge to streams, discharge to evapotranspiration, and discharge to pumping wells.

Recharge

Recharge boundaries in the Eagle Valley model consist of 

recharge cells to simulate precipitation and irrigation recharge 

to the land surface, general-head boundary cells to simulate 

mountain-block recharge, and river cells to simulate surfacewater infiltration (fig. 3.5A). The MODFLOW General-Head 

package is used to simulate the edges of the model where 

basin-fill deposits lie adjacent to consolidated bedrock and 

mountain-block recharge of winter snow contributes significant recharge to the basin. General-head cells are located in 

layer 1, although some mountain-block recharge may occur 

at greater depths. Precipitation recharge is insignificant in the 

Eagle Valley, but the MODFLOW Recharge package is used to 

simulate small amounts of lawn and golf course irrigation with 

rates on the order of 7.3 cm/yr. The MODFLOW River package cells are used to represent recharge from surface-water 

flow in the Carson River, and Clear Canyon, Ash Canyon, and 

Kings Canyon Creeks.

In the Spanish Springs Valley model, ground-water 

recharge from septic systems, precipitation, and imported surface water were simulated in the model as assigned recharge 

rates based on either empirical estimates or measured quantities. Recharge rates from precipitation and septic systems were 

assumed constant. Mountain-block recharge was simulated 

using 18 recharge nodes. Recharge nodes and rates for the 

model are shown in figure 3.5B. Recharge from septic systems 

and irrigation return flows were simulated using well nodes 

with a positive discharge. For cells containing a domestic well 

(discharge) and a septic system (recharge), values of domestic 
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–17

pumping were input to the model as the net difference between 

well discharge and septic-system recharge.

Discharge

Discharge boundaries in the Eagle Valley model included 

evapotranspiration discharge, river discharge, and public-supply well pumping (fig. 3.5A). Evapotranspiration (ET) was 

the primary discharge component and was simulated using the 

MODFLOW ET package. Evapotranspiration was simulated 

as a linear function of depth computed from a maximum rate, 

which was decreased linearly to the depth at which evapotranspiration is assumed to cease (the evapotranspiration 

extinction depth). An evapotranspiration extinction depth of 

12 m was used in the model and provided a reasonable calculation of evapotranspiration, which generally was simulated 

for the center portion of the basin where evapotranspiration 

historically occurred. Discharge to rivers and creeks in the valley was represented using the MODFLOW River package (319 

river cells) and public-supply well pumping was represented 

using the MODFLOW Well package (20 well cells). Average pumping rates for 1997–2001 for public-supply wells in 

Carson City were used as model input (table 3.2).

The Spanish Springs Valley model also included discharge by evapotranspiration. Ground-water discharge by 

evapotranspiration was specified in model layer 1 as headdependent flow boundaries using the ET package and was 

assigned to selected active cells on the basis of plant distribution from field observations. In Spanish Springs Valley, evapotranspiration is limited to the area encompassed by the Orr 

Ditch and along the outside of the Orr Ditch near the central 

and southeast part of the valley. Inside the area encompassed 

by the Orr Ditch, the depth to water is shallow and vegetation consists of meadow grasses and alfalfa separated by large 

areas of bare soil (fig. 3.5B). A maximum evapotranspiration 

rate of 0.005 m/d at land surface and an extinction depth of 

3 m were used to simulate evapotranspiration inside the area of 

the Orr Ditch. Assuming evapotranspiration is at a maximum 

when depth to ground water is 1 m, the maximum evapotranspiration rate used in the model for the area outside the Orr 

Ditch was 5 X 10–4 m/d and the extinction depth was 10 m.

In the Spanish Spring model, the simulation of groundwater discharge to domestic and public-supply wells was 

accomplished using the MODFLOW Well package. Average 

pumping rates for 1997–2001 for the eight public-supply wells 

in the Spanish Springs Valley were input to the model (table 

3.3).

Aquifer Hydraulic Conductivity

Aquifer properties used in the Eagle Valley model were 

taken from the original model done in the late 1970s (Arteaga, 

1986). The transmissivity values used by that model ranged 

from 1 to 940 m2/d in layer 1 and from 5 to 11,600 m2/d in 

layer 2. The areal distribution of transmissivity and hydraulic 

conductivity values coincides in general with grain size of 

the alluvial deposits. In layer 1, the coarser, more conductive 

deposits tend to be near creeks coming from the mountainous 

areas surrounding the valley (fig. 3.6A). The finer, less conductive deposits tend to be in the center of the valley. For layer 1, 

the aquifer thickness was held constant at 30 m; hydraulic conductivity ranged from 0.01 to 9.4 m/d with an average value 

of approximately 0.3 m/d. In general, layer 2 was simulated 

as coarser grained and as more transmissive than layer 1 (fig. 

3.6B). Hydraulic conductivity of layer 2 ranged from 0.009 to 

47.2 m/d with an average value of approximately 2 m/day.

In the Spanish Springs Valley model, transmissivity 

values determined from several aquifer tests were used to 

calculate hydraulic conductivities, which ranged from 0.5 to 

about 4 m/d (Berger and others, 1997). Figure 3.7A shows the 

hydraulic-conductivity distribution for layer 1 where values 

ranged from less than 0.01 to 15 m/d. Figure 3.7B shows the 

hydraulic-conductivity distribution for layer 2 where values 

ranged from less than 0.01 to 5 m/d, and figure 3.7C shows 

the hydraulic-conductivity distribution of layer 3 where values 

also varied from less than 0.01 to 5 m/d.
3–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.5A. Ground-water flow model grid, boundary conditions, and location of public-supply wells, Eagle Valley regional 

study area, Nevada.

395

50

395

50

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson

River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Evapotranspiration cells

River cells

General-head boundary

Model grid

Extent of active model cells

Public-supply well
Figure 3.5B. Ground-water flow model grid, boundary conditions, and location of public-supply wells, Spanish Springs 

Valley regional study area, Nevada.

395

445

445

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Evapotranspiration cells

Drain cells

General-head boundary

Model grid

Extent of active model cells

Public-supply well

Simulated ground-water recharge rate, in centimeters per day

 0.0003173

 0.001569

 0.001926

 0.002642

 0.007196

Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–19
3–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.6A. Distribution of hydraulic conductivity for model layer 1, Eagle Valley regional study area, Nevada.

395

50

395

50

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson

River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Hydraulic conductivity, in meters per day

 0.01 to 0.16

 0.161 to 0.350

 0.351 to 0.550

 0.551 to 0.850

 0.851 to 1.20

 1.201 to 1.85

 1.851 to 9.41

Extent of active model cells
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–21

Figure 3.6B. Distribution of hydraulic conductivity for model layer 2, Eagle Valley regional study area, Nevada.

395

50

395

50

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson

River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Hydraulic conductivity, in meters per day

 0.009 to 6.10

 6.11 to 12.2

 12.3 to 19.8

 19.9 to 27.4

 27.5 to 33.5

 33.6 to 39.6

 39.7 to 47.2

Extent of active model cells
3–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.7A. Distribution of hydraulic conductivity for model layer 1, Spanish Springs Valley regional study area, Nevada.

395

445

445

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Hydraulic conductivity, in meters per day

 Less than 0.01

 0.011 to 0.03

 0.031 to 0.09

 0.091 to 0.5

 0.051 to 1.0

 1.1 to 5.0

 5.1 to 15.0

Extent of active model cells
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–23

Figure 3.7B. Distribution of hydraulic conductivity for model layer 2, Spanish Springs Valley regional study area, Nevada.

395

445

445

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Hydraulic conductivity, in meters per day

 Less than 0.01

 0.011 to 0.03

 0.031 to 0.09

 0.091 to 0.5

 0.051 to 1.0

 1.1 to 5.0

Extent of active model cells
3–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.7C. Distribution of hydraulic conductivity for model layer 3, Spanish Springs Valley regional study area, Nevada.

395

445

445

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Hydraulic conductivity, in meters per day

 Less than 0.01

 0.011 to 0.03

 0.031 to 0.09

 0.091 to 0.5

 0.051 to 1.0

 1.1 to 5.0

Extent of active model cells
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–25

Model Calibration

Both the Eagle Valley and Spanish Springs Valley steadystate models were calibrated by comparing model-computed 

hydraulic heads to measured hydraulic heads for 1997–2001. 

Hydraulic conductivity and recharge values were manually 

adjusted within a prescribed range until a reasonable match 

was obtained between model-computed and measured hydraulic heads. There were no surface-water flow data available for 

use in model calibration.

The overall goodness of fit of the model to the observation data was evaluated using summary measures and graphical analyses. The root-mean-squared error (RMSE), the range 

of head and residuals, the standard deviation, and the standardmean error of the residuals (SME) were used to evaluate the 

model calibration. The RMSE is a measure of the variance of 

the residuals and was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of observations used in the 

computation. If the ratio of the RMSE 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).

The SME was calculated as:

where σ(hmeas – hsim) is the standard deviation of the residuals.

Model-Computed Hydraulic Heads

The model-computed hydraulic heads compared favorably with measured hydraulic heads for the Eagle Valley 

model. The average residual was 0.14 m and residuals ranged 

from 13.6 to -18.6 m with the largest errors occurring along 

the model boundary representing the contact between the 

basin fill and mountain front. The standard deviation of the 

residuals is 5.77 m, and the SME is 0.58 m. The root-meansquared error (RMSE) for the entire model was 5.7 m, which 

is approximately 6 percent of the 99-m range of measured 

hydraulic head. Measured hydraulic heads ranged from 1,397 

to 1,496 m above NAVD88 and were similar to model-computed hydraulic heads, which ranged from 1,407 to 1,489 m 

above NAVD88. Figure 3.8A shows the relation between the 

residual head calculated as the difference between model-computed and measured hydraulic heads for both model layers and 

indicates the head residuals appear to be randomly distributed 

about zero at all values of measured head.

For the Spanish Springs Valley model, model-computed hydraulic heads also compare favorably with measured hydraulic heads. The average residual was 2.96 m and 

residuals ranged from -2.58 to 9.38 m with the largest errors 

generally occurring along the model boundary representing 

the contact between the basin fill and mountain front. The 

standard deviation of the residuals is 3.14 m, and the SME is 

0.55 m. The RMSE for the entire model was 4.28 m, which 

is approximately 9 percent of the 50-m range of measured 

hydraulic head. Measured hydraulic heads ranged from 1,351 

to 1,401 m above NAVD88 and were similar to model-computed hydraulic heads, which ranged from 1,352 to 1,396 m 

above NAVD88. Figure 3.8B shows the relation between the 

residual head calculated as the difference between model-computed and measured hydraulic heads for model layers 1 and 2 

and indicates residuals are greatest in areas of highest hydraulic head.
3–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.8A. Relation between residual head and measured hydraulic head, Eagle Valley regional study area, Nevada.

Figure 3.8B. Relation between residual head and measured hydraulic head, Spanish Springs Valley regional study area, Nevada.

–25

–20

–15

–10

–5

0

5

10

15

20

Head residual, in meters

Measured head elevation, in meters

1,380 1,400 1,420 1,440 1,460 1,480 1,500 1,520

EXPLANATION

Layer 1 Layer 2

–4

–2

0

2

4

6

8

10

Head residual, in meters

Measured head elevation, in meters

1,340 1,350 1,360 1,370 1,380 1,390 1,400 1,410

EXPLANATION

Layer 1 Layer 2
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–27

Model-Computed Water Budget

The model-computed water budget for the Eagle Valley 

model is presented in table 3.4, and the model-computed water 

budget for the Spanish Springs Valley model is presented in 

table 3.5. In the Eagle Valley, infiltration of streamflow from 

the surrounding mountains (mountain-front recharge—62.9 

percent of inflow) and mountain-block recharge (28.1 percent of inflow) were the primary sources of recharge to the 

basin-fill aquifer. Recharge from precipitation and irrigation 

provided 9 percent of the ground-water inflow. Discharge 

to public-supply wells (52.9 percent of outflow) and evapotranspiration (31.9 percent of outflow) were the primary 

Table 3.5. Model-computed water budget for 1997–2001 average 

conditions, Spanish Springs Valley regional study area, Nevada.

[m3/d, cubic hectometers per year]

Water-budget component Flow

(m3/d)

Percentage of 

inflow or outflow

Model inflow

Canal leakage 6,400 42.7

Precipitation and lawn 

irrigation

5,900 39.3

Mountain-block recharge 2,000 13.3

Head-dependent boundaries 700 4.7

TOTAL INFLOW 15,000 100

Model outflow

Evapotranspiration 8,400 56.0

Wells 5,200 34.7

Head-dependent boundaries 1,100 7.3

Streams 300 2.0

TOTAL OUTFLOW 15,000 100

Table 3.4. Model-computed water budget for 1997–2001 average 

conditions, Eagle Valley regional study area, Nevada.

[m3/d, cubic hectometers per year]

Water-budget component Flow

(m3/d)

Percentage of 

inflow or outflow

Model inflow

Streams (mountain front 

recharge)

30,200 62.9

Mountain-block recharge 13,500 28.1

Precipitation, lawn and 

golf course watering 4,300 9.0

TOTAL INFLOW 48,000 100

Model outflow

Wells 25,400 52.9

Evapotranspiration 15,300 31.9

Streams 7,300 15.2

TOTAL OUTFLOW 48,000 100

ground-water outflows from the Eagle Valley. In the Spanish 

Spring Valley, canal leakage from the Orr Ditch (42.7 percent 

of inflow) and precipitation and irrigation (39.3 percent of 

inflow) were the primary sources of recharge to the basin-fill 

aquifer. Mountain-block recharge accounted for 13.3 percent of the ground-water inflow. Similar to the Eagle Valley, 

discharge to evapotranspiration (56 percent of outflow) and 

public-supply wells (34.7 percent of outflow) were the primary 

ground-water outflows from the Spanish Springs Valley. In 

general, both budgets compare fairly well with the conceptual 

water budgets discussed in the Water Budget section of this 

section.
3–28 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Simulation of Areas Contributing Recharge to 

Public-Supply Wells

The calibrated steady-state regional flow models were 

used to estimate areas contributing recharge and zones of 

contribution for public-supply wells using the MODPATH 

(Pollock, 1994) particle-tracking post processor and methods 

outlined in Section 1 of this Professional Paper. The modelcomputed areas contributing recharge represent advective 

ground-water flow and do not account for mechanical dispersion. Advection-dispersion transport simulations would 

likely yield larger areas contributing recharge than advective 

particle-tracking simulations because the effects of dispersion 

caused by aquifer heterogeneity would be included.

Along with flux output from the models, the MODPATH 

simulations require effective porosity values to calculate 

ground-water flow velocities. There are no porosity data 

available for the study areas, so a reasonable porosity value of 

0.15 from the literature (Fetter, 2001) was used for all layers 

in both the Eagle Valley and Spanish Springs Valley particletracking simulations.

 Particle-tracking simulations were used to outline areas 

contributing recharge for all 20 public-supply wells in the 

Eagle Valley. Areas contributing recharge are irregular in 

shape and extend to the mountain front on the north and west 

sides of the valley because a large amount of water enters the 

model as mountain-front or mountain-block recharge (fig. 

3.9A). Traveltimes from recharge areas to public-supply wells 

were on the order of 5 to 140 years.

Particle-tracking simulations for the eight public-supply 

wells in the Spanish Springs Valley provided results similar 

to those for the Eagle Valley. In general, areas contributing 

recharge were along the mountain front on the east and west 

sides of the valley (fig. 3.9B). Traveltimes from recharge to 

discharge areas were somewhat longer in the Spanish Springs 

Valley than in the Eagle Valley, ranging from 10 to 2,600 

years.

The areas contributing recharge in both the Eagle and 

Spanish Springs Valleys models extend to the general-head 

boundary cells along the mountain-front boundary of the 

alluvial aquifer indicating mountain-front and mountain-block 

recharge are the primary source of water for the public-supply 

wells.

Limitations and Appropriate Use of the Model

The ground-water flow models for the Eagle Valley and 

Spanish Springs Valley regional study areas were designed to 

evaluate the water budgets and delineate contributing areas to 

public-supply wells for hydrologic conditions in 1997–2001. 

A numerical ground-water model is a simplification of a physical system, and the intent in developing these regional models 

was not to reproduce every detail of the natural systems, but 

rather to portray their general characteristics. Sources of error 

in the model may include the steady-state flow assumption and 

errors in the conceptual model of the system, hydraulic properties, and boundary conditions.

The assumption of steady-state conditions for these 

models is a source of model uncertainty because the steadystate model may not be representative of ground-water flow 

conditions as time progresses and there were limited waterlevel data with which to evaluate long-term water-level trends. 

As water continues to be pumped from public-supply wells, 

water may be removed from aquifer storage especially in this 

arid climate where recharge is limited. The result may be a 

considerable delay before land-use practices in contributing 

areas delineated by this analysis could actually affect water 

quality in supply wells.

In some cases, model data were derived from sparse data 

or data of questionable quality (for example some drillers’ 

logs) or by empirical methods that are inherently uncertain 

(such as estimating recharge as a percentage of precipitation). 

Other properties of the system had to be estimated without 

observation or measurement (for example, hydraulic properties 

of deep basin fill) and are another source of model uncertainty.

Although substantial information exists on some system 

stresses (for example, public-supply pumping), others such 

as evapotranspiration rates and septic-system recharge were 

estimated from literature values. It was not possible to identify 

the uncertainties, or the magnitude of the uncertainties, in the 

model data sets that contributed to the lack of complete agreement between simulated and measured hydraulic heads and 

ultimately to limitations of the results.

 Computed areas contributing recharge and traveltimes 

through zones of contribution are based on a calibrated 

model and estimated effective porosity values. In a steady-
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–29

state model, changes to input porosity values do not change 

the area contributing recharge to a given well. Changes to 

input porosity values will change computed traveltimes from 

recharge to discharge areas in direct proportion to changes of 

porosity because there is an inverse linear relation between 

ground-water flow velocity and effective porosity and a direct 

linear relation between traveltime and effective porosity. For 

example, a one-percent decrease in porosity will result in a 

one-percent increase in velocity and a one-percent decrease 

in particle traveltime. There are no available porosity data for 

these study areas, so a reasonable estimated values were used. 

A detailed sensitivity analysis of porosity distributions was 

beyond the scope of this study, although future work could 

compare simulated ground-water traveltimes to ground-water 

ages to more thoroughly evaluate effective porosity values.

Despite their limitations, the Eagle Valley and Spanish Springs Valley regional ground-water flow models use 

justifiable aquifer properties and boundary conditions and 

provide reasonable representations of average ground-water 

flow conditions for 1997-2000. The models are suitable for 

evaluating regional water budgets and ground-water flow paths 

in the study area for the time period of interest but may not be 

suitable for long-term predictive simulations. These regional 

models provide useful tools to evaluate aquifer vulnerability 

at a regional scale, to facilitate comparisons of ground-water 

traveltime between regional aquifer systems, and to guide 

future detailed investigations in the study areas.
3–30 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 3.9A. Model-computed areas contributing recharge to public-supply wells, Eagle Valley regional study area, Nevada.

395

50

395

50

Lone

Mountain

Prison

Hill

P I N E

N U

T

M O

U

N

T A I N

S

C A R S O N

V A L L E Y

E A G L E

V A L L E Y

Vicee

Canyon

Creek

Hobart

Lake

Ash

Canyon

North Kings Canyon Creek

Kings Canyon

Creek

Clear

Creek

Eagle

Valley

Creek

Carson

River

Carson

River

C A R S O N

C I T Y

DOUGLAS COUNTY

CARSON CITY

WASHOE COUNTY

CARSON CITY

LYON COUNTY

CARSON CITY

39° 10'

39° 05'

119° 50' 119° 45' 119° 40'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Areas contributing recharge

Urban area

Model grid

Extent of active model cells

Public-supply well
Hydrogeologic Settings, Ground-Water Flow Simulations of the Eagle Valley and Spanish Springs Valley, Nevada 3–31

Figure 3.9B. Model-computed areas contributing recharge to public-supply wells, Spanish Springs Valley regional study 

area, Nevada.

395

445

445

Spanish

Springs

Peak

P A H R A H R A N G E

S P A

N I S H

S P R I N

G

S

V A L L E

Y

D R Y

L A K E S

Spring

area

Sugarloaf

Peak

H U N G R Y

R I D G E

H U N G R Y

V A L L E Y

Spanish Springs Canyon

North

Truckee

Drain

Orr

Ditch

S P A R K S

39° 40'

39° 35'

119° 45' 119° 40' 119° 35'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 96° West, 

North American Datum of 1983

0

0 2 4 MILES

2 4 6 8 KILOMETERS

EXPLANATION

Areas contributing recharge

Urban area

Model grid

Extent of active model cells

Public-supply well
3–32 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

References Cited

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Valley ground-water basin, west-central Nevada: Nevada 

Division of Water Resources Bulletin 45, 53 p.

Arteaga, F.E., and Durbin, T.J., 1979, Development of a relation for steady-state pumping rate for Eagle Valley groundwater basin, Nevada: U.S. Geological Survey Open-File 

Report 79–261, 44 p.

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mine dewatering in Desert Valley, Humboldt and Pershing 

Counties, northwestern Nevada, 1962–91: U.S. Geological 

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79 p.

Berger, D.L., Ross, W.C., Thodal, C.E., and Robledo, A.R., 

1997, Hydrogeology and simulated effects of urban 

development on water resources of Spanish Springs Valley, 

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Cohen, P., and Loeltz, O.J., 1964, Evaluation of hydrogeology 

and hydrogeochemistry of Truckee Meadows area, Washoe 

County, Nevada: U.S. Geological Survey Water-Supply 

Paper 1779–S, 62 p.

Covay, K.J., Banks, J.M., Bevans, H.E., and Watkins, S.A., 

1996, Environmental and hydrologic settings of the Las 

Vegas Valley area and the Carson and Truckee River Basins, 

Nevada and California: U.S. Geological Survey WaterResources Investigations Report 96–4087, 72 p.

Fetter, C.W., 2001, Applied hydrogeology (4th ed.) Prentice 

Hall, Upper Saddle River, New Jersey.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. 

Geological Survey Open-File Report 00–92, 121 p.

Harrill, J.R., 1973, Evaluation of the water resources of Lemmon Valley, Washoe County, Nevada, with emphasis on 

effects of ground-water development to 1971: Nevada Division of Water Resources, Bulletin 42, 130 p.

Johnson, K.L., Ball, G.W., Jr., and Harrigan, W.A., 1996, 

Carson City well completion report amendment, Silver Oak, 

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Geological Survey Circular 1279, 47 p.

Maurer, D.K., 1997, Hydrology and ground-water budgets of 

the Dayton Valley Hydrographic Area, west-central Nevada: 

U.S. Geological Survey Water-Resources Investigations 

Report 97–4123, 89 p.

Maurer, D.K., Berger, D.L., and Prudic, D.E., 1996, Subsurface flow to Eagle Valley from Vicee, Ash, and Kings 

Canyons, Carson City, Nevada, estimated from Darcy’s Law 

and the chloride-balance method: U.S. Geological Survey 

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99–4289, 46 p.

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8, 59 p.

Planert, Michael, and Williams, J.S., 1995, Ground Water 

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Geological Survey Hydrologic Atlas HA 730–B.

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finite-difference ground-water flow model: U.S. Geological 

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12 p.
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brief water-resources appraisal of the Truckee River Basin, 

western Nevada: Nevada Division of Water Resources, 

Reconnaissance Report 57, 122 p.

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well construction, August–October 1993, Reno, Nevada: 

Washoe County Department of Public Works, Utility Division, 19 p. and appendix.

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Carson and Eagle Valleys, western Nevada and eastern California, U.S. Geological Survey Open-File Report 93–33, 

99 p.

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Department of Conservation and Natural Resources Reconnaissance Report 39, 55 p.

Hydrogeologic Setting and Ground-Water 

Flow Simulations of the San Joaquin Valley 

Regional Study Area, California

By Steven P. Phillips, Karen R. Burow, Diane L. Rewis, Jennifer Shelton, and 

Bryant Jurgens

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 4 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
Suggested citation:

Phillips, S.P., Burow, K.R., Rewis, D.L., Shelton, J., and Jurgens, B., 2007, Hydrogeologic settings and ground-water 

flow simulations of the San Joaquin Valley Regional Study Area, California, section 4 of Paschke, S.S., ed., Hydrogeologic settings and ground-water flow simulations for regional studies of the transport of anthropogenic and natural 

contaminants to public-supply wells—studies begun in 2001: Reston, Va., U.S. Geological Survey Professional Paper 

1737–A, pp. 4–1 – 4–31.

U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report. 
iii

Contents

Abstract...................................................................................................................................................... 4–1

Introduction................................................................................................................................................ 4–1

Purpose and Scope ......................................................................................................................... 4–1

Study Area Description................................................................................................................... 4–3

Topography and Climate ........................................................................................................ 4–3

Surface-Water Hydrology ..................................................................................................... 4–3

Land Use................................................................................................................................... 4–3

Water Use ................................................................................................................................ 4–3

Conceptual Understanding of the Ground-Water System................................................................. 4–5

Geology.............................................................................................................................................. 4–5

Ground-Water Occurrence and Flow........................................................................................... 4–7

Aquifer Hydraulic Conductivity...................................................................................................... 4–7

Water Budget ................................................................................................................................. 4–12

Ground-Water Quality ................................................................................................................... 4–13

Ground-Water Flow Simulations .......................................................................................................... 4–18

Modeled Area and Spatial Discretization.................................................................................. 4–18

Boundary Conditions and Model Stresses................................................................................ 4–18

Aquifer Hydraulic Properties ....................................................................................................... 4–20

Model Calibration and Sensitivity ............................................................................................... 4–20

Model-Computed Hydraulic Heads ................................................................................... 4–22

Model-Computed Water Budget........................................................................................ 4–26

Simulation of Areas Contributing Recharge to Public-Supply Wells .................................... 4–26

Particle-Tracking Simulations............................................................................................. 4–26

Public-Supply Well Contributing Areas............................................................................. 4–28

Limitations and Appropriate Use of the Model......................................................................... 4–28

References Cited..................................................................................................................................... 4–30

Figures

Maps showing:

4.1. Location of the San Joaquin Valley regional study area within the 

Central Valley aquifer system.................................................................................4–2

4.2. Topography, hydrologic features, and location of public-supply wells, 

San Joaquin Valley regional study area, California ...........................................4–4

4.3. Physiographic provinces and selected geologic units, 

San Joaquin Valley regional study area, California. ..........................................4–6

4.4 Generalized A) map and B) hydrogeologic section showing regional

ground-water flow near Modesto, California................................................................. 4–8

4.5. Map showing measured hydraulic-head elevations in the unconfined to 

semi-confined aquifer for spring 2000, San Joaquin Valley regional 

study area, California. ........................................................................................................ 4–9
iv

4.6. Graph showing measured hydraulic-head elevations from November 1969 

to November 2000 for selected irrigation wells, San Joaquin Valley 

regional study area, California. ...................................................................................... 4–10

Maps showing:

4.7. Percentage of coarse-grained texture for model layer 4, 

San Joaquin Valley regional study area, California ......................................... 4–11

4.8. Ground-water flow model subareas used for water-budget calculations, 

San Joaquin Valley regional study area, California .........................................4–14

4.9. Water-year 2000 estimated recharge rates for model subareas, 

San Joaquin Valley regional study area, California. ........................................4–15

4.10 Water-year 2000 estimated ground-water pumping rates for model

subareas, San Joaquin Valley regional study area, California ......................4–16

4.11. Conceptual diagram of oxidation-reduction conditions near 

Modesto, California.......................................................................................................... 4–17

4.12 Map showing ground-water flow modeled area and boundary 

conditions San Joaquin Valley regional study area, California ................................ 4–19

Graphs showing:

4.13 Frequency of estimated horizontal hydraulic conductivity (Kh)

and estimated vertical hydraulic condivivity (Kv) for the eastern

and western alluvial fans, San Joaquin Valley regional study area,

California ...................................................................................................................4–21

4.14. Ground-water flow model calibration results, San Joaquin Valley 

regional study area, California. .....................................................................4–23–24

4.15. Map showing spatial distribution of hydraulic-head residuals, 

San Joaquin Valley regional study area, California.................................................... 4–25

Graphs showing:

4.16. Relation between head residual and measured hydraulic head, 

San Joaquin Valley regional study area, California. ........................................4–26

4.17. Relation between model-computed and measured hydraulic head, 

San Joaquin Valley regional study area, California. ........................................4–26

4.18. Map showing model-computed areas contributing recharge for 15 

public-supply wells in top quartile of pumping, San Joaquin Valley 

regional study area, California....................................................................................... 4–29

Tables

4.1. Summary of water-budget components for water-year 2000 in the 

Modesto area, San Joaquin Valley regional study area, California......................... 4–12 

4.2. Model-computed water budget for water-year 2000, San Joaquin Valley 

regional study area, California. ...................................................................................... 4–27

4.3. Effective porosity values, by percentage of coarse-grained texture, used for 

MODPATH simulations, San Joaquin Valley regional study area, California.......... 4–27
Hydrogeologic Setting and Ground-Water Flow 

Simulations of the San Joaquin Valley Regional

Study Area, California

By Steven P. Phillips, Karen R. Burow, Diane L. Rewis, Jennifer Shelton, and Bryant Jurgens

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated in the northeastern part 

of the San Joaquin Valley near Modesto, California, as part of 

the U.S. Geological Survey National Water-Quality Assessment Program. The basin-fill aquifer system in the San Joaquin Valley regional study area is representative of the Central 

Valley aquifer system, is used extensively for agricultural 

irrigation and public water supply, and is susceptible and vulnerable to contamination. The Central Valley aquifer system 

in the study area consists of an unconfined to semi-confined 

aquifer in the upper sediments of the basin above and east of 

the Corcoran Clay confining unit. A confined aquifer occurs 

beneath the Corcoran Clay. Irrigation and public-supply wells 

are completed in both the unconfined and confined aquifers, 

and pumping in the valley has altered the natural ground-water 

flow patterns. A 16-layer, steady-state ground-water flow 

model of the basin-fill aquifer in an area around Modesto, 

California, was developed and calibrated to water-year 2000 

conditions. The calibrated model and advective particle-tracking simulations were used to compute areas contributing 

recharge and traveltimes from recharge areas for 60 publicsupply wells. Model results indicate agricultural irrigation 

return flow (41.5 percent of inflow) and precipitation (29.3 

percent of inflow) provide most of the ground-water inflow, 

whereas the majority of ground-water discharge is to pumping 

wells (54.2 percent of outflow) and evapotranspiration (11.9 

percent of outflow). Particle-tracking results indicate the areas 

contributing recharge to wells generally extend upgradient 

to the northeast of Modesto beyond the extent of the Corcoran Clay. Minimum traveltime from the water table to a well 

ranges from 3 to 141 years with a median of about 20 years, 

and maximum traveltime ranges from 18 to more than 1,600 

years with a median of 107 years on the basis of particle-tracking results.

Introduction

The San Joaquin Valley regional study area for the transport of anthropogenic and natural contaminants to public-supply wells (TANC) is in the San Joaquin Valley near Modesto, 

California, and is part of the San Joaquin-Tulare Basins study 

unit of the U.S. Geological Survey National Water-Quality 

Assessment (NAWQA) Program (fig. 4.1).

Purpose and Scope

The purpose of this Professional Paper section is to 

present the hydrogeologic setting of the San Joaquin Valley 

regional study area. The section also documents the setup 

and calibration of a steady-state regional ground-water flow 

model for the study area. Ground-water flow characteristics, 

pumping-well information, and water-quality data were compiled from existing data to develop a conceptual understanding of ground-water conditions in the study area. A 16-layer 

steady-state ground-water flow model of the basin-fill aquifer 

in an area around Modesto, California, was developed and 

calibrated to ground-water flow conditions for the water-year 

2000. The water-year 2000 was assumed to represent average conditions for the period from 1997 to 2001. The 5-year 

period 1997–2001 was selected for data compilation and 

modeling exercises for all TANC regional study areas to facilitate future comparisons between study areas. The calibrated 

ground-water flow model and associated particle tracking were 

used to simulate advective ground-water flow paths and to 

delineate areas contributing recharge to selected public-supply 

wells. Ground-water traveltimes from recharge to publicsupply wells, oxidation-reduction (redox) conditions along 

flow paths, and presence of potential contaminant sources in 

areas contributing recharge were tabulated into a relational 

database as described in Section 1 of this Professional Paper. 

This section provides the foundation for future ground-water 

susceptibility and vulnerability analyses of the study area and 

comparisons among regional aquifer systems.
4–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4.1. Location of the San Joaquin Valley regional study area within the Central Valley aquifer system.

C A L I F O R N I A

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Los Angeles

Sacramento

Reno

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San Francisco

Bakersfield

126° 125° 124° 123° 122° 121° 120° 119° 118° 117° 116° 

42° 

41° 

40° 

39° 

38° 

37° 

36° 

35° 

34° 

33° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 50 100 150 200 kilometers

0 50 100 miles

EXPLANATION

San Joaquin Valley regional study area

Central Valley aquifer system

USGS NAWQA study unit—San Joaquin-Tulare Basins

San Joaquin Valley
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–3

Study Area Description

The San Joaquin Valley regional study area is about 2,700 

square kilometers (km2) centered on the city of Modesto, 

California, in the San Joaquin Valley. The San Joaquin Valley 

composes the southern two-thirds of the Central Valley aquifer 

system of California (fig. 4.1), which is ranked second in total 

water use of the 62 principal aquifers in the United States 

(Maupin and Barber, 2005).

Cities in the San Joaquin Valley are among those with 

the highest growth rates in the Nation, resulting in a gradual 

urbanization of adjacent farmlands. In Stanislaus County, the 

estimated population in 2000 was more than 446,000 people, 

an increase of 20 percent since 1990 (U.S. Census Bureau, 

2002). Although more than 90 percent of the 1995 water 

demands in this region were for irrigation, approximately 

one-half of the demand for municipal and industrial supply is 

met by ground water. The increasing population and periods of 

drought are expected to increase reliance on ground water.

Topography and Climate

The San Joaquin Valley regional study area is bounded on 

the west by the San Joaquin River, on the north by the Stanislaus River, on the south by the Merced River, and on the east 

by the Sierra Nevada foothills (fig. 4.2). The Sierra Nevada 

rise east of the valley to an elevation of more than 4,200 m; 

the Coast Ranges, of moderate elevations, form the western 

edge of the valley. Surface topography in the study area slopes 

downward from the Sierra Nevada foothills to the San Joaquin 

River with gradients ranging from less than 1 m/km near the 

river to about 5 m/km near the foothills (fig. 4.2). The climate 

is semiarid, characterized by hot summers and mild winters, 

with rainfall (averaging 31.5 cm annually from 1931–1997 

[National Oceanic and Atmospheric Administration, 2005]) 

during late fall through early spring.

Surface-Water Hydrology

The San Joaquin River is the central drainage for the 

northern San Joaquin Valley; it is the only major surface-water 

outlet from the valley draining out through San Francisco Bay. 

The southern San Joaquin Valley is a hydrologically closed 

basin. The water quality of the San Joaquin River is of critical 

interest because it flows into the Sacramento-San Joaquin 

Delta, a key source of drinking water for southern California 

and irrigation water for the western San Joaquin Valley. The 

Stanislaus, Tuolumne, and Merced Rivers drain the Sierra 

Nevada and are tributaries to the San Joaquin River in the 

study area.

All rivers in the study area have been significantly modified from their natural state. Each has multiple reservoirs for 

irrigation and power generation, which effectively delays 

discharge of large amounts of snowmelt runoff. Imprinted 

over this hydrology is an extensive network of canals used to 

deliver water for irrigation (fig. 4.2).

Land Use

Agriculture is the primary land use, covering more than 

65 percent of the study area, and most of the agricultural 

land is irrigated. The primary crops are almonds, walnuts, 

peaches, grapes, grain, corn, pasture, and alfalfa. The towns 

of Modesto, Turlock, and a number of smaller urban areas 

composed about 6 percent of the study area in 2000, and the 

remaining 29 percent of the study area was natural vegetation 

near the foothills and in riparian areas (Burow and others, 

2004).

Water Use

Agricultural irrigation supplied by surface water and 

ground water accounted for about 95 percent of the total water 

use in 2000 (Burow and others, 2004). Surface-water supplies 

originate primarily from a series of reservoirs in the Sierra 

Nevada foothills, are managed by irrigation districts, and are 

delivered to agricultural users through hundreds of kilometers 

of lined canals.

Irrigation districts and private agricultural users pump 

ground water for irrigation. Some districts also pump ground 

water to lower the water table in areas where it has risen too 

close to the land surface to support agriculture without active 

management. Private agricultural ground-water pumping is not 

measured in the study area but is estimated as about 32 percent 

of total agricultural water use in the study area in 2000.

Urban water demand is met by a combination of surfacewater and ground-water supplies. Before 1995, the City of 

Modesto, the largest urban area, used ground water exclusively 

for public supply. In 1994, a surface-water treatment plant 

was completed, which, in 2000, provided about one-half of 

Modesto’s municipal and industrial water supplies (Burow and 

others, 2004). Data from all of the urban areas, as a whole, 

indicate that about 55 percent of the urban water requirement 

was met with ground water in 2000 (Burow and others, 2004).

Based on local drillers’ logs, about 60 percent of wells in 

the study area are for domestic use, followed by about 27 percent for irrigation, 4 percent for public supply, and 9 percent 

for test, stock, industrial, and other uses (Burow and others, 

2004). Well depths range from 7 to 368 m below land surface, 

with a median depth of 59 m. In general, domestic wells tap 

shallow parts of the aquifer, whereas irrigation and public-supply wells are screened in deeper zones. The wells generally are 

distributed throughout the region, though fewer wells exist in 

the older sediments and terraces east of Modesto and Turlock 

and along the San Joaquin River. The deepest wells generally 

are in the older sediments in the eastern part of the study area, 

and the shallowest wells generally are in the western part and 

along the rivers. Additional clusters of deep wells are in the 

urban areas (fig. 4.2).
4–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4.2. Topography, hydrologic features, and location of public-supply wells, San Joaquin Valley regional study area, 

California.

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River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

37° 15'

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Land elevation, in meters above sea level

Extent of model grid

Extent of Corcoran Clay—Hachures point toward clay

Public-supply well

3600

3200

2800

2400

2000

1600

1200

800

400

0
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–5

Conceptual Understanding of the 

Ground-Water System

The aquifers in the San Joaquin Valley TANC regional 

study area are composed of Tertiary and Quaternary alluvial 

deposits shed from the surrounding Sierra Nevada and Coast 

Ranges. The basin-fill is composed of coalescing alluvial 

fans, which tend to be coarse grained near the mountains and 

finer grained toward the center of the basin. The Corcoran 

Clay, correlated to the Corcoran Clay Member of the Tulare 

Formation south of the study area, is a lacustrine clay deposit 

that separates the basin-fill deposits into an upper unconfined 

aquifer and a lower confined aquifer throughout much of the 

study area. Under natural conditions, ground-water recharge 

occurred in the upper parts of the alluvial fans where stream 

valleys enter the basin, and ground water discharged to the San 

Joaquin River and surrounding marshlands. However, groundwater pumping in the valley for agricultural irrigation and 

public water supply has altered ground-water flow patterns. 

Water flowing laterally toward the center of the basin may be 

pumped, applied as irrigation, recharge the aquifer, then be 

pumped and reapplied at the surface several times as it moves 

toward the San Joaquin River. Ground-water quality is influenced by recharge from the surrounding mountain streams and 

irrigated agriculture.

Geology

The Central Valley of California is a northwest-trending 

structural trough filled with Tertiary and Cretaceous continental and marine sediments up to 10 km thick (Gronberg and 

others, 1998; Bartow, 1991). The Sierra Nevada Range lies 

on the eastern side of the valley and is composed primarily of 

pre-Tertiary granitic rocks. In the northern San Joaquin Valley, 

the Sierra Nevada Range is separated from the Central Valley 

by a foothill belt of marine and metavolcanic rocks. The Coast 

Ranges lie on the western side of the valley and are a complex 

assemblage of rocks, including marine and continental sediments of Cretaceous to Quaternary age (Gronberg and others, 

1998).

The San Joaquin Valley can be divided into three physiographic regions (fig. 4.3): the western alluvial fans, the eastern 

alluvial fans, and the basin (Gronberg and others, 1998) 

Alluvial fan deposits on both sides of the valley are composed 

predominantly of coarse-grained sediments near the head of 

each fan that become finer grained toward the valley trough. 

The sediments in the eastern alluvial fan region generally are 

more permeable than sediments in the western alluvial fan 

region because sediment-source rocks and watershed characteristics are different between the two areas. The basin region 

is composed of continental (shallow) and marine (deeper) 

sediments that are overlain by fine-grained, moderately to 

densely compacted clays. These low-permeability deposits 

restrict the downward movement of water.

Consolidated rocks and deposits exposed along the 

margin of the valley floor include Tertiary and Quaternary 

continental deposits, Cretaceous and Tertiary marine sedimentary rocks, and the pre-Tertiary Sierra Nevada basement 

complex (Piper and others, 1939; Davis and others, 1959). 

Most unconsolidated deposits in the study area are contained 

within the Pliocene-Pleistocene Laguna (not mapped at the 

surface in study area), Turlock Lake, Riverbank, and Modesto 

Formations, with minor amounts of Holocene stream-channel 

and flood-basin deposits (fig. 4.3) (Arkley, 1962, 1964; Davis 

and Hall, 1959). The Turlock Lake, Riverbank, and Modesto 

Formations form a sequence of overlapping terrace and alluvial fan systems (Marchand and Allwardt, 1981) indicating 

cycles of alluviation, soil formation, and channel incision that 

were influenced by climatic fluctuations and resultant glacial 

stages in the Sierra Nevada (Bartow, 1991).

The Corcoran Clay Member of the Tulare Formation is 

a lacustrine deposit that is a key subsurface feature in the San 

Joaquin Valley. Page (1986) mapped the areal extent of this 

regional confining unit based on a limited number of well 

logs and geophysical logs. Additional lithologic data recently 

were used to modify the extent of this prominent unit in the 

study area (Burow and others, 2004). The eastern extent of the 

Corcoran Clay roughly parallels the San Joaquin River valley 

axis (fig. 4.3). The Corcoran Clay ranges in depth from 28 to 

85 m below land surface and in thickness from 0 to 57 m in 

the study area.

The Mehrten Formation is tapped by wells in the eastern part of the study area. The Mehrten Formation reflects a 

change in lithology and texture from overlying sediments of 

primarily unconsolidated coarse-grained sediments of arkosic 

composition to Mehrten Formation sediments of primarily 

consolidated sediments of volcanic-derived mafic materials 

(Burow and others, 2004). The Mehrten Formation outcrops in 

the eastern part of the study area and lies at depths of at least 

120 m below land surface beneath Modesto.
4–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 3. Physiographic provinces and selected geologic units, San Joaquin Valley regional study area, California.

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River

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River

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Lake

Modesto

Reservoir

Dry Creek

MODESTO

TURLOCK

RIVERBANK

OAKDALE

WATERFORD

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STANISLAUS

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F A N S

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F A N S

B A S I N 37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 5 10 15 20 25 30 KILOMETERS

0 5 10 15 MILES

EXPLANATION

Geologic unit

 Dunes

 Alluvium and dredge tailings

 Stream-channel and flood-basin deposits 

 Nonmarine terrace deposits

 Stream-channel and flood-basin deposits

 Modesto Formation

 Riverbank Formation

 Turlock Lake Formation

 Mehrten Formation

 Valley Springs Formation

 Ione Formation

 Ultrabasic intrusive rocks

Urban

Physiographic region boundary

Extent of Corcoran Clay—

 Hachures point toward clay

Holocene Extent of model grid

Pleistocene

Pliocene

Miocene

Eocene

Pre-Cretaceous

QUATERNARY TERTIARY

CENOZOIC

MESOZOIC
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–7

Ground-Water Occurrence and Flow

Ground water in the study area is present in the unconfined to semi-confined aquifer above and east of the Corcoran 

Clay and in the confined aquifer beneath the Corcoran Clay. 

The unconfined to semiconfined aquifer above the Corcoran 

Clay ranges in thickness from about 40 to 70 m. The unconfined to semiconfined aquifer east of the Corcoran Clay is 

composed primarily of alluvial sediments but includes the 

upper part of the Mehrten Formation, which is more consolidated than the overlying formations. Coarse-grained gravel 

and sand layers present in the upper part of the Mehrten are 

tapped by irrigation and public-supply wells. The confined 

aquifer is composed of alluvial sediments and upper Mehrten Formation sediments from beneath the Corcoran Clay to 

the lowermost freshwater. The contribution of ground water 

from the consolidated rocks beneath the primary aquifers was 

assumed negligible and was not considered for this study.

Under natural conditions, ground water was primarily 

recharged at the upper parts of the alluvial fans where the 

major streams enter the valley (fig. 4.4). Ground-water flow 

followed the southwest slope of the basement complex and the 

dip of the overlying sedimentary deposits toward the southwest in the direction of the valley trough. Artesian conditions 

near the San Joaquin River indicated discharge to the river and 

surrounding marshlands (Davis and others, 1959).

Ground-water resource development in the basin changed 

ground-water flow patterns. Pumping for agricultural irrigation and agricultural irrigation return flows are much greater 

than natural recharge and discharge and caused an increase in 

vertical flow in the system (fig. 4.4) (Page and Balding, 1973; 

Londquist, 1981). Ground-water flow direction for 2000 is 

generally toward the southwest and is somewhat similar to the 

predevelopment flow regime (fig. 4.5). However, ground water 

moving along a lateral flow path may be extracted by wells 

and applied at the surface several times before reaching the 

valley trough (fig. 4.4), at which point it may cross to the other 

side of the valley rather than discharge to the river because of 

pumping on the west side of the valley. South of the Tuolumne 

River is a centrally located ground-water-flow divide, east of 

which water flows northeastward toward irrigation wells in 

an agricultural area with no surface-water supplies. West of 

the flow divide, water flows southwestward toward the valley 

trough (fig. 4.5).

The western part of the study area along the San Joaquin 

River is an area of ground-water discharge where the water 

table is within 3 m of the land surface. Ground-water pumping 

is used in this area to keep the water table from affecting crop 

roots. Depth to the water table increases eastward, particularly 

south of the Tuolumne River, where depths can exceed 40 m.

Long-term water levels measured in selected wells representing the unconfined to semi-confined aquifer near the city 

of Modesto indicate water levels generally decreased in the 

Modesto area until the early 1990s (fig. 4.6). This hydraulichead decrease likely was caused by increased urban development and associated public-supply pumping punctuated by 

drought conditions in 1976 and 1987–92. A series of wet years 

in the early 1990s and completion of a surface-water treatment 

plant in 1994, which provided an additional source of publicsupply and industrial water, resulted in a recovery of groundwater levels near Modesto.

Aquifer Hydraulic Conductivity

The hydraulic properties of the aquifer system were 

estimated for this study based on the distribution of sediment 

texture and through calibration of the ground-water flow 

model. The texture distribution was estimated using the general approach of Laudon and Belitz (1991), which made use of 

drillers’ logs and geophysical logs.

To facilitate this texture-based approach, a database was 

constructed as part of a cooperative effort between the U.S. 

Geological Survey and the Modesto Irrigation District to organize information on well construction and subsurface lithology in the study area (Burow and others, 2004). About 10,000 

drillers’ logs were examined. Because sediment descriptions 

on drillers’ logs can be ambiguous and widely variable, a 

rating scheme was developed to select a subset of about 3,500 

logs for use in this study. In addition to lithologic data, the 

database contains well-construction information, which was 

used to vertically distribute ground-water pumping in the flow 

model.

To visualize subsurface sediment-texture distributions 

and provide a heterogeneous hydraulic-conductivity field for 

the flow model, the primary texture of sediments in the study 

area was characterized using a geostatistical approach (Burow 

and others, 2004). Lithologic descriptions in the database were 

expressed as a percentage of coarse-grained sediment. These 

percentages were then interpolated within each layer of the 

model grid (using kriging), providing an estimated distribution of sediment texture. The estimated texture distribution for 

model layer 4 (above the Corcoran Clay) is shown in figure 

4.7. The estimated texture distributions are reasonably constrained in the model layers above the Corcoran Clay and in 

some areas where the deepest wells penetrate the sub-Corcoran part of the system. In deeper parts of the aquifer system, 

where no data were available, the texture value in the lowest 

layer estimated was duplicated in all underlying model cells.
4–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 4. Regional ground-water flow near Modesto, California.

Not to scale

Regional ground-water flow

Municipal pumpage

Agricultural irrigation pumping

Agricultural

irrigation pumping

Irrigation return-flow recharge

Urban recharge

Irrigation return-flow recharge

Agriculture surface-water

deliveries

Discharge

to river

Local return flow

Local return flow

Local return flow

River

Southwest

Northeast

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Base from U.S. Geological Survey 

digital data, Albers equal-area 

projection, standard parallels

29° 30' North and 45° 30' North, 

central meridian 120° West,

North American Datum of 1983

0 10 20 30 KILOMETERS

0 10 20 MILES

37° 45'

37° 30'

121° 15' 121°00' 120° 45' 120° 30'

Tuolumne

River

EXPLANATION

San Joaquin Valley map (left)

 Basin-fill deposits

 Alluvial fans

 Consolidated rocks

 Generalized covergent lateral flow toward basin

Conceptual diagram (below)

 Flood-plain deposits

 Fluvially deposited alluvial fan deposits

 Confining unit (Corcoran Clay)

 More consolidated deposits

 Consolidated rocks

 Water table

 Ground-water flow direction

 Surface-water inflow

 Ground-water withdrawals

 Ground-water recharge

 Wells with typical screening locations

Convergent flow toward basin, laterally driven (below left) overlain with

pumping and reapplication of irrigation water, vertically driven (below)
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–9

Figure 4. 5. Measured hydraulic-head elevations in the unconfined to semi-confined aquifer for spring 2000, 

San Joaquin Valley regional study area, California.

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

3S/8E-18C1

3S/9E-8D1

3S/10E-8D1

15

20

25

30

40

35

30

25

15

15

20

25

30

20

25

30

30

25

20

15

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Physiographic region

 Basin

 Eastern alluvial fans

 Western alluvial fans

Urban

Line of equal water-level elevation, in meters—Interval 5 meters. 

 Dashed where approximately located. Hachures indicate depression. 

 Datum is sea level

Extent of model grid

Extent of Corcoran Clay—Hachures point toward clay

Wells used to contour water-level elevation, in meters

Wells with long-term measured water levels (figure 4.6)

35

3S/10E-8D1
4–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 6. Measured hydraulic-head elevations from November 1969 to November 2000 for selected irrigation wells, San Joaquin 

Valley regional study area, California. Well locations shown on figure 4.5.

0

25 (82)

20 (65)

15 (49)

10 (33)

5 (16)

30 (98)

35 (115)

Water-level elevation, in meters

(feet in parentheses)

Measured head elevation, in meters

11/1/1969 11/1/1974 11/1/1979 11/1/1984 11/1/1989 11/1/1994 11/1/1999

EXPLANATION

Well 3S/10E-8D1 Well 3S/9E-8D1 Well 3S/8E-18C
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–11

Figure 4. 7. Percentage of coarse-grained texture for model layer 4, San Joaquin Valley regional study area, California

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Percentage of coarse-grained texture

 90 to 100 percent

 80 to 90 percent

 70 to 80 percent

 60 to 70 percent

 50 to 60 percent

 40 to 50 percent

 30 to 40 percent

 20 to 30 percent

 10 to 20 percent

 0 to 10 percent

Physiographic region

 Basin

 Eastern alluvial fans

 Western alluvial fans

Urban

Extent of model grid

Extent of Corcoran Clay—Hachures point toward clay
4–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 4.1 Summary of water-budget components for water-year 2000 in the Modesto area, San Joaquin Valley regional study area, 

California.

[m2, square meters; m3, cubic meters]

Water-budget subarea

Irrigation demand Surface-water deliveries

Irrigated cropped 

area, including 

double and 

intercropped area 

(m2)

Crop demand 

(m3)

Irrigation demand 

(m3)

Surface-water 

deliveries (m3)

Agricultural 

ground-water 

pumpage 

deliveries (m3)

Eastside Water District (EWD) 214,781,896 192,159,808 240,199,759 — —

Merced Irrigation District (MER) 134,263,686 118,920,445 188,762,611 85,184,253 2,563,052

Merquin Community Water District 

(MERQ) 29,744,731 28,761,456 45,653,105 21,909,708 —

Modesto Irrigation District (MID) 252,669,587 236,308,482 375,092,829 172,897,795 25,894,607

Oakdale Irrigation District (OID) 206,238,419 209,521,576 261,901,970 302,202,485 10,274,903

South San Joaquin Irrigation District 

(SSJID) 127,848,622 119,424,314 189,562,403 157,031,625 —

Stevinson Water District (SWD) 14,464,212 13,809,833 21,920,370 10,654,212 —

Turlock Irrigation District (TID) 603,293,199 529,757,589 840,885,063 554,268,926 94,771,341

Foothills (FOOT) — — — — —

Reservoirs (RES) — — — — —

Riparian and miscellaneous 

agricultural areas (RIP) 182,577,869 158,586,562 251,724,701 208,025,236 —

Urban (URB) — — — 38,102,384 —

 TOTAL 1,765,882,221 1,607,250,065 2,415,702,811 1,550,276,623 133,503,903

1

 Negative pumpage resulted from excess delivery for calculated crop demand. Pumpage was set to zero in the model.

Water Budget

A water-budget approach was used to estimate groundwater pumping and recharge from infiltration of rainfall and 

irrigation return flow for water-year 2000 (October 1, 1999, 

through September 30, 2000). Surface water and ground water 

are used for irrigation in the agricultural areas. Surface-water 

delivery data were available for most of the water-budget 

subareas, although private pumping records generally were 

not. Therefore, the water budget was critical for estimating 

ground-water use in agricultural areas and was important for 

estimating areal recharge throughout the model area.

The water budget was derived by dividing the basin into 

subareas for which surface-water deliveries could be obtained 

or estimated. A separate water budget was calculated for each 

of the resulting 47 subareas, which were then grouped into 12 

model subareas (table 4.1) (fig. 4.8), which included agricultural and urban settings, foothill areas, riparian areas with 

natural vegetation and(or) crops, and reservoirs.

A land-use approach (Burow and others, 2004) was 

used to estimate the water budget for subareas containing 

primarily nonurban land use. The area of each crop or other 

vegetation type was determined, a daily crop demand was 

calculated based on crop or vegetation type and climate, and 

a daily irrigation demand was estimated for each subarea. 

The irrigation demand was met by a combination of surfacewater deliveries, ground water pumped by irrigation districts, 

and private ground-water pumping. The total reported or 

estimated monthly surface-water and ground-water deliveries 

were subtracted from the estimated monthly irrigation demand 

to determine the monthly unmet irrigation demand. Private 

ground-water pumping was then assumed to be the source of 

unmet irrigation demand.

The consumptive use of applied water, or irrigation efficiency, was estimated at about 63 percent for most of the study 

area on the basis of irrigation methods used and estimates in 

subareas with relatively high surface-water deliveries and few 

known wells. Irrigation efficiency was assumed greater (80 

percent) in the older fan deposits in the foothill areas, where 

the sediments are more indurated and modern and efficient 

irrigation methods are more commonly used (Burow and others, 2004).

Recharge in the urban areas was estimated using the 

minimum month method to determine indoor and outdoor 
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–13

and ground-water pumpage Recharge

Private 

agricultural 

ground-water 

pumpage (m3)

Urban 

ground-water 

pumpage (m3)

Total 

ground-water 

pumpage (m3)

Recharge from 

urban water 

distribution 

lines (m3)

Recharge from 

irrigation (m3)

Recharge from 

precipitation (m3)

Total recharge 

(m3)

240,199,759 — 240,199,759 — 48,039,952 62,028,511 110,068,463

101,015,306 1,858,512 105,436,870 — 69,842,166 37,207,316 107,049,482

23,743,397 — 23,743,397 — 16,891,649 10,573,559 27,465,208

176,300,427 11,636,020 213,831,054 — 138,784,347 66,807,374 205,591,721

1

 –50,575,417 3,591,759 1 –36,708,755 — 52,380,394 58,648,959 111,029,353

32,530,778 2,107,287 34,638,065 — 70,138,089 33,885,822 104,023,911

11,266,159 — 11,266,159 — 8,110,537 6,738,661 14,849,198

206,059,686 33,568,641 334,399,669 — 311,127,473 161,236,620 472,364,093

— — — — — 61,362,021 61,362,021

— — — — — 4,995,484 4,995,484

43,699,465 — 43,699,465 — 93,138,139 69,747,688 162,885,828

— 47,182,527 47,182,527 4,101,222 18,455,497 9,858,789 32,415,508

784,239,561 99,944,746 1,017,688,210 4,101,222 826,908,243 583,090,805 1,414,100,270

water use (California Department of Water Resources, 1994). 

Ten percent of the estimated outdoor use was subtracted from 

the total to account for leakage from water distribution lines 

(California Department of Water Resources, 1994). Fifty 

percent of the remaining outdoor water use was assumed to be 

consumptive use for landscape irrigation or runoff to streams, 

and the remainder of outdoor use was assumed to be urban 

recharge (Burow and others, 2004).

The average areal recharge rate for the study area is about 

54 cm/yr, which includes recharge from precipitation and 

irrigation return flow, with the highest recharge rates occurring in the agricultural areas in the western part of the study 

area and along the rivers in the eastern part (fig. 4.9). The 

lowest recharge rates were in the foothills and the urban areas. 

Similarly, the highest pumping rates were in the agricultural 

areas in the western part of the study area (fig. 4.10). The 

relatively high rates of pumping and recharge in the western 

agricultural areas are related to the irrigation efficiency and 

supplemental pumping required to manage the shallow water 

table. No information was available regarding pumping rates 

from domestic wells. Although domestic wells are common in 

the study area, they were assumed to represent an insignificant 

percentage of the water budget and were not included.

Ground-Water Quality

Ground-water quality in the study area is influenced by 

recharge from streams and surface water imported through 

canals. This recharge can infiltrate from irrigated fields to 

the water table and by regional ground-water flow from the 

alluvial fans on the east and west sides of the valley toward 

the axial trough (Davis and others, 1959; Bertoldi and others, 

1991). Ground water on the east side of the San Joaquin River 

is fairly uniform in composition, consisting of predominantly 

sodium-calcium-bicarbonate or calcium-sodium-bicarbonate type water (Davis and Hall, 1959), and has generally low 

dissolved-solids concentrations (less than 500 mg/L). Groundwater quality east of the San Joaquin River reflects recharge 

of water originating in the granitic Sierra Nevada to the east 

(Page, 1973; Bertoldi and others, 1991). Ground water on 

the west side of the San Joaquin River is predominantly of 
4–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 8. Ground-water flow model subareas used for water-budget calculations, San Joaquin Valley regional study 

area, California.

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

FOOT-NS

OID-N

OID-S FOOT-NT

SSJID

WOODRES

MID-1

MODRES

TLRES

MER-N

FOOT-NM

TID-8

MID-2

MID-3

MID-4

URB-M

URB-C TID-2 TID-1

TID-9

EWD TID-10

TID-5

TID-7

TID-3

TID-2

MID-8

MID-6

MID-7

MID-5

TID-6 TID-11

TID-12

TID-13 TID-14 TID-17

TID-16

TID-15 MER-S

SWD

MERQ

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Model subareas

 Eastside Water District (EWD)

 Merced Irrigation District (MER)

 Merquin Community Water District (MERQ)

 Modesto Irrigation District (MID)

 Oakdale Irrigation District (OID)

 South San Joaquin Irrigation District (SSJID)

 Stevinson Water District (SWD)

 Turlock Irrigation District (TID)

 Foothills (FOOT)

 Reservoirs

 Riparian and miscellaneous agricultural areas

 Urban

Extent of model grid

Inactive model cells
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–15

Figure 4. 9. Water-year 2000 estimated recharge rates for model subareas, San Joaquin Valley regional study area, 

California.

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

FOOT-NS

OID-N

OID-S FOOT-NT

SSJID

WOODRES

MID-1

MODRES

TLRES

MER-N

FOOT-NM

TID-8

MID-2

MID-3

MID-4

URB-M

URB-C TID-2 TID-1

TID-9

EWD TID-10

TID-5

TID-7

TID-3

TID-2

MID-8

MID-6

MID-7

MID-5

TID-6 TID-11

TID-12

TID-13 TID-14 TID-17

TID-16

TID-15 MER-S

SWD

MERQ

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Recharge rate, in meters per year (feet per year in parentheses)

 0.23 to 0.36 (0.75 to 1.2)

 0.37 to 0.50 (1.2 to 1.6)

 0.51 to 0.63 (1.7 to 2.1)

 0.64 to 0.76 (2.1 to 2.5)

Extent of model grid

Inactive model cells
4–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 10. Water-year 2000 estimated ground-water pumping rates for model subareas, San Joaquin Valley regional 

study area, California.

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

FOOT-NS

OID-N

OID-S FOOT-NT

SSJID

WOODRES

MID-1

MODRES

TLRES

MER-N

FOOT-NM

TID-8

MID-2

MID-3

MID-4

URB-M

URB-C TID-2 TID-1

TID-9

EWD TID-10

TID-5

TID-7

TID-3

TID-2

MID-8

MID-6

MID-7

MID-5

TID-6 TID-11

TID-12

TID-13 TID-14 TID-17

TID-16

TID-15 MER-S

SWD

MERQ

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Pumping rate, in meters per year (feet per year in parentheses)

 0 to 0.25 (0 to 0.8)

 0.26 to 0.50 (0.8 to 1.6)

 0.51 to 0.75 (1.7 to 2.5)

 0.76 to 1.0 (2.5 to 3.3)

Extent of model grid

Inactive model cells
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–17

calcium-sulfate or calcium-bicarbonate type water with dissolved-solids concentrations ranging from 500 to 1,500 mg/L 

(Davis and others, 1959; Bertoldi and others, 1991), likely 

reflecting recharge of water originating in the marine and 

continental sedimentary rocks of the Coast Ranges to the west 

(Davis and Hall, 1959). Because the axial trough has been the 

discharge area in the past, ground water in this area is derived 

from a combination of water from the east and west sides of 

the valley and varies widely in composition with depth.

The water chemistry is further influenced by an increase 

in reducing conditions and cation-exchange processes as the 

water moves through the sediments (Bertoldi and others, 

1991). Ground water beneath the alluvial fans in the valley 

area is largely oxidizing, whereas ground water beneath the 

axial trough and in discharge areas adjacent to streams typically is geochemically reduced (Gronberg and others, 1998; 

fig. 4.11). Geochemically reduced water is likely associated with relatively fine-grained sediments of higher organic 

content, longer residence times of water reaching natural 

discharge areas, and confined portions of the aquifer. Concentrations of oxidation-reduction- sensitive (redox) species 

in retrospective ground-water quality data for the study area 

were used to delineate regional redox patterns. Because of the 

limited spatial coverage of suitable water-quality samples and 

the dominantly oxygenated conditions in the aquifer, most 

of the study area was mapped as conditions consistent with 

oxygen and nitrate reduction. Areas of manganese reduction 

and iron reduction with high sulfate were mapped along the 

axial trough and deep in the more consolidated sediments and 

confined parts of the aquifer beneath the alluvial fans.

Agricultural water use is the largest nonpoint source of 

water-quality degradation in the San Joaquin Valley. Irrigation 

has become the major source of recharge to the ground-water 

system and can contain elevated concentrations of dissolved 

solids, nutrients, pesticides, and in some areas, trace elements 

(Gronberg and others, 1998).

Figure 4. 11. Conceptual diagram of oxidation-reduction conditions near Modesto, California.

Not to scale

Regional ground-water flow

Discharge

to river

Local return flow

Local return flow

Local return flow

River

Southwest Northeast Pumping Pumping Pumping

EXPLANATION

Flood-plain deposits

Fluvially deposited alluvial fan deposits

Confining unit (Corcoran Clay)

More consolidated deposits

Consolidated rocks

Water table

Ground-water flow and oxidation-reduction conditions

 Oxygen and/or nitrate reduction—Prevails in shallow part of aquifer as pumping and recharge from surrounding agriculture create local-flow cells

 Iron reduction—Commonly occurs in discharge zones as long as paths terminate and residence time, organic mater, and nutrients increase

 Variably-reduced conditions—Occur in deeper parts of the aquifer as ground water migrates downward and flows laterally

Wells with typical screening locations
4–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Ground-Water Flow Simulations

A steady-state model of ground-water flow in the study 

area was developed using MODFLOW-2000 (Harbaugh and 

others, 2000) to estimate aquifer-system properties, delineate 

areas contributing recharge to public-supply wells in Modesto, 

and support future local modeling efforts. The model represents the water-year 2000 when the ground-water system was 

in a quasi-steady-state condition. Measured hydraulic heads 

in the study area indicate much of the system has been at 

equilibrium for many years (fig. 4.6), particularly the areas 

with a shallow water table downgradient from Modesto and 

Turlock. The two areas where hydraulic heads have recently 

changed are Modesto and the agricultural area upgradient 

from Turlock. Water levels recovered rapidly with importation 

of surface water to the Modesto area in 1995, but the recovery slowed greatly by 2000. Upslope from Turlock, hydraulic 

heads have declined for about 2 decades due to increased 

ground-water use associated with new agricultural development. Although water-level data for this area are sparse, they 

indicate hydraulic heads continue to decline, albeit slowly. 

Transient conditions cannot be taken into account in a steadystate simulation; therefore, some model error is to be expected 

in these areas.

Modeled Area and Spatial Discretization

The modeled area for the San Joaquin Valley regional 

study area extends from the Stanislaus River on the north to 

the Merced River on the south and bounded on the east by 

the Sierra Nevada foothills and the west by the San Joaquin 

River. The model grid is oriented parallel to the valley axis, 

37 degrees west of due north (fig. 4.12). The modeled area 

extends 61.2 km along the valley axis from north of the Stanislaus River to south of the Merced River and 54.8 km from 

the Coast Ranges to the Sierra Nevada foothills. The model 

grid is 137 columns and 153 rows and is uniformly spaced; 

each model cell is 400 m by 400 m in size.

Sixteen model layers were used to represent the geologic 

materials in the study area with model layers designed as a 

series of wedges to represent the regional dip of the sediments. 

The uppermost layer was a constant thickness of 10 m. Layers 

2 through 7 represent the unconfined aquifer above and east of 

the Corcoran Clay. The thicknesses of layers 2 through 7 were 

assigned as a percentage of the thickness of materials between 

layer 1 and the top of the Corcoran Clay (10, 10, 15, 20, 20, 

and 25 percent of that thickness, respectively) and ranged from 

1.9 to 18.8 m in thickness. Layer 8 represents the Corcoran 

Clay, where present, and its specified thickness and presence 

varies spatially as determined from analysis of drillers’ and 

geophysical logs. A minimum thickness of 10 m was specified 

for layer 8 where the Corcoran Clay was not present. Layers 9 through 16 represent the confined aquifer beneath the 

Corcoran Clay, and thickness of layers 9–16 was assigned as 

a percentage of the thickness of materials between the bottom 

of the Corcoran Clay and the bottom of the model. Layers 9 

through 13 were assigned 10 percent of the total thickness, 

layers 14 and 15 were assigned 15 percent of the thickness, 

and layer 16 was assigned 20 percent of the total thickness. 

Layer thickness below the Corcoran Clay ranged from 17 

to 80 m. The bottom of the model was an artificial surface 

loosely representing topographic variability and the general 

dip of the Corcoran Clay. The total thickness of the wedgeshaped model ranges from about 230 to 430 m.

Boundary Conditions and Model Stresses

Lateral boundary conditions in the model were no-flow 

along the Sierra Nevada foothills and general-head elsewhere. 

The general-head boundaries (fig. 4.12) were specified at a 

distance of 400 m using a water-level contour map (fig. 4.5) 

and hydraulic-conductivity estimates for each cell along the 

boundary. The northwestern and southeastern edges of the 

model grid were located beyond the Stanislaus and Merced 

Rivers, respectively, to include these rivers in the modeled 

area. The southwestern model boundary was coincident with 

the San Joaquin River, and all cells west of the river were 

inactive. These general-head boundaries allow for cross-valley flow beneath the San Joaquin River, which is known to 

occur (Belitz and Phillips, 1995; Phillips and others, 1991), 

and provide reasonable boundary conditions in the northwest 

and southeast where no identified hydrologic boundaries exist 

within a reasonable distance of the study area.

The upper model boundary was simulated as the water 

table, and the lower model boundary was simulated as noflow. The lower model boundary was arbitrarily located far 

below the deepest wells, and significant vertical flow in the 

lowest model layer is unlikely.

Model stresses included recharge from irrigation return 

flow; infiltration of precipitation, reservoir leakage, and 

inflow from rivers; and discharge from ground-water pumping, outflow to rivers, and evaporation from the shallow water 

table. Irrigation return flow, infiltration of precipitation, and 

private-agricultural pumping rates were all determined in the 

water-budget analysis. The two recharge terms were summed 

for each water-budget subarea and distributed evenly to the 

uppermost active model layer within each subarea. Privateagricultural pumping was distributed laterally within waterbudget subareas assuming an average well spacing of 1,200 m 

(3 cells). Wells with measured pumping rates (those supplying 

urban areas or operated by irrigation districts) were placed in 

the model at their actual locations. The vertical distribution of 

private-agricultural pumping was estimated using the average 

screened interval of irrigation wells in each subarea (using 

the texture data base). Given this average screened interval, 

the total pumping per well was distributed to the model layers 

within this interval on the basis of effective transmissivity of 

these layers. The vertical distribution of measured pumping 

was distributed using the actual screened intervals (or those of 

nearby wells of the same type).
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–19

Figure 4.12. Ground-water flow modeled area and boundary conditions, San Joaquin Valley regional study area, 

California.

5

120

205

4

580

99

108

120

5

99

N

E

V

A

D

A

S

I

E

R

R

A

C E N

T R A

L

V A

L

L

E

Y

C

O

A

S

T

R

A

N

G

E

San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Boundary conditions

 General-head boundary representing river-aquifer interaction

 Specified recharge from river

 General-head boundary representing lateral subsurface flow

 General-head boundary representing river-aquifer interaction and lateral subsurface flow

 Inactive cells

Extent of model grid

Physiographic region

 Basin

 Eastern alluvial fans

 Western alluvial fans
4–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

The interaction of ground water and surface water is 

poorly understood in the study area but is incorporated in the 

model as reservoir leakage and gaining and losing reaches of 

the four rivers. There are three significant reservoirs along 

the northeastern model boundary: Woodward and Modesto 

Reservoirs and Turlock Lake (fig. 4.2). These reservoirs are 

approximately equal in size, and information on leakage rates 

was available only for the Modesto Reservoir. Results from a 

recent short-term study conducted by the Modesto Irrigation 

District, which manages the reservoir, indicate a leakage rate 

of about 67,600 to 84,500 m3/d (Modesto Irrigation District, 

oral commun., 2001). Leakage rates for the other two reservoirs were assumed to be the same as those for the Modesto 

Reservoir. The MODFLOW-2000 Reservoir package (Fenske 

and others, 1996) was used to simulate the reservoirs, which 

requires specification of reservoir stage and information for 

calculating the hydraulic conductance of the reservoir bottom. The stage was estimated from U.S. Geological Survey 

7.5-minute topographic maps, and the hydraulic conductance 

terms were adjusted to approximate the assumed leakage 

rate (the total reservoir leakage in the calibrated model was 

207,000 m3/d).

The four rivers in the study area were represented in 

the model as a combination of general-head and specifiedflux cells. General-head cells were used where the river was 

directly connected to the water table, which allowed flow into 

and out of the river. The head term was estimated from streamgage data and topography, and the conductance was calculated 

using the estimated vertical hydraulic conductivity by cell, 

the river width, and an assumed riverbed thickness of 1 m. 

Recharge from the river was specified as a flux where the river 

was disconnected from the water table. This value (0.005 m/d 

per river cell) was impossible to estimate with the available 

data, and its calibration was poorly constrained.

Bare-soil evaporation from the water table was simulated 

where the water table was within 2.1 m of the land surface. 

The maximum evaporation rate was 1.6 m/yr at the land 

surface, and decreased linearly to zero at 2.1 m below land 

surface.

Aquifer Hydraulic Properties

A method of parameter estimation based on sediment 

texture, which was used successfully in the development of a 

transient three-dimensional ground-water flow model of the 

central western San Joaquin Valley (Belitz and Phillips, 1995; 

Phillips and Belitz, 1991), was adapted for use in this study. 

This method uses the estimated sediment texture (as percentage of coarse-grained sediments) for each model cell and several user-specified values of hydraulic conductivity to generate 

horizontal and vertical hydraulic conductivities throughout the 

model domain.

The hydraulic-conductivity values specified for the model 

include that of the Corcoran Clay (Kcorc) and of the coarsegrained (Kcoarse) and fine-grained (Kfine) lithologic end members 

of the remaining materials. In the modeled area, the remaining materials were divided into two lithologic subareas during 

model calibration: the eastern alluvial fans upslope of the 

Modesto Formation (fig. 4.3) and everywhere else. Horizontal 

hydraulic conductivity (Kh) was calculated for each cell in 

these subareas using the arithmetic mean:

 (eq. 4.1)

where Fcoarse is the fraction of coarse-grained sediment in a 

cell, and Ffine is the fraction of fine-grained sediment in a cell.

Vertical hydraulic conductivity between model layers (Kv) 

either was set to Kcorc, if the Corcoran Clay was present within 

one of the layers, or was calculated using the geometric mean:

 (eq. 4.2)

where Fcoarsev is the fraction of coarse-grained sediment 

between layer midpoints, and Ffinev is the fraction of finegrained sediment between layer midpoints.

The calibrated value (see next section) of Kcorc was 4 X 

10-3 m/d and that for Kfine was 4 X 10-4 m/d. The calibrated 

value of Kcoarse varied by lithologic subarea: 24 m/d for the 

older fan deposits and 235 m/d for the remaining area. The 

resulting values of Kh and Kv are summarized in figure 4.13. 

The distributions of Kh and Kv are the same as those for the 

sediment texture for the appropriate depth intervals (for example, the distribution of Kh

 in layer 4 is shown in figure 4.7).

Model Calibration and Sensitivity

Model calibration consisted primarily of a systematic 

application of the parameter estimation method. Kcoarse and 

Kfine were varied systematically for a given value of Kcorc, 

which was adjusted to roughly match vertical gradients across 

the Corcoran Clay. Model-computed hydraulic heads were 

compared to measured water levels in 51 wells representing 

various parts of the aquifer system. The resulting error distributions constrained the parameter set.

Model-computed and measured hydraulic heads were 

compared in four areas within the model. The low-lying area 

where the water table is shallow was represented by 17 wells. 

The intermediate-depth zone between the water table and the 

Corcoran clay and the deep zone below the Corcoran were 

represented by six wells each. The area east of the extent of 

the Corcoran was represented by 22 wells.

Two statistics were used to quantify model error:

 (eq. 4.3)
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–21

Figure 4. 13. Frequency of estimated horizontal hydraulic conductivity (Kh) and estimated vertical hydraulic conductivity (Kv) for 

the eastern and western alluvial fans, San Joaquin Valley regional study area, California.

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Frequency

Hydraulic conductivity values, in meters per day

5 10 15 20 25

50 100 150 200 250

50 100 150 200 250

0

Frequency

Hydraulic conductivity values, in meters per day

HORIZONTAL HYDRAULIC CONDUCTIVITY VERTICAL HYDRAULIC CONDUCTIVITY

0.001 0.01 0.1 1.0 10.0 100.0 1,000.0

0.001 0.01 0.1 1.0 10.0 100.0 1,000.0

0.001 0.01 0.1 1.0 10.0 100.0 1,000.0

Eastern fan area

0

5,000

10,000

15,000

20,000

25,000

30,000

0

5,000

10,000

15,000

20,000

25,000

30,000

Frequency

Hydraulic conductivity values, in meters per day

Frequency

Hydraulic conductivity values, in meters per day

Western fan area above Corcoran Clay

0

10,000

20,000

30,000

40,000

50,000

60,000

0

10,000

20,000

30,000

40,000

50,000

60,000

Frequency

Hydraulic conductivity values, in meters per day

Frequency

Hydraulic conductivity values, in meters per day

Western fan area below Corcoran Clay
4–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

 (eq. 4.4)

where RMSE is root-mean-square error, hmeas is measured 

hydraulic head, hsim is model-computed hydraulic head, 

(hmeas – hsim) is the head residual, i is the summation index, n

is the number of measurements, and BIAS is the sum of the 

residuals. The RMSE is a measure of error magnitude, and 

BIAS indicates whether model-computed hydraulic heads were 

higher or lower than measured hydraulic heads.

Model-computed and measured vertical hydraulic gradients also were compared during model calibration. Measured 

gradients were calculated using water levels from nearby 

wells screened at different depths in three areas within the 

model: from the water table to the intermediate-depth zone 

above the Corcoran (three well pairs), across the Corcoran 

(three well pairs), and the area east of the Corcoran extent 

(five well pairs). RMSE and BIAS were calculated for vertical 

gradients in the same way as for hydraulic head by replacing 

the simulated and measured heads in equations 4.3 and 4.4 

with the model-computed and measured vertical hydraulic 

gradients (change in model-computed or measured hydraulic 

head divided by the vertical distance between the midpoints of 

model layers or screened intervals, respectively).

The RMSE and BIAS calculations were used to estimate 

the values of Kcoarse and Kfine that generated the best-fit parameter distribution for the conceptual model described herein. 

RMSE and BIAS values were calculated for 100 simulations 

representing Kcoarse values ranging from 60 to 300 m/d and Kfine

values ranging from 3 X 10–4 to 1 m/d. Results from the 100 

simulations were plotted as error surfaces describing model 

fit with respect to hydraulic heads and gradients for various 

parts of the aquifer system (fig. 4.14). Each plot in figure 4.14 

shows contoured RMSE and BIAS for hydraulic heads and vertical gradients in a specific part of the aquifer system. Lines of 

minimum RMSE and BIAS were drawn where possible. Note 

the model is numerically stable over a wide range of parameter 

values, but numerical stability decreased with lower values of 

Kcoarse and Kfine. Pervasive numerical instability was assumed an 

indication that such parameter combinations are unlikely to be 

representative of this aquifer system.

The RMSE and BIAS values shown in figure 4.14, 

considered as a whole, constrain Kcoarse and Kfine to the lower 

left-hand region of the plot and indicate relatively high values 

of Kcoarse and low values of Kfine provide the best model fit for 

the given conceptual model. The fact that most of the plots do 

not contain lines of minimum RMSE and zero BIAS, and that 

these lines are not coincident where they do coexist, indicates 

there is some degree of error in the conceptual model and (or) 

the calibration criteria. Future modeling efforts can focus on 

reducing these errors, but current results indicate that Kcoarse

and Kfine values of about 235 and 4 X 10–4 m/d, respectively, 

generate the best-fit parameter distribution (Kcorc was 4 X 10–3

m/d).

A hydraulic conductivity of 235 m/d is within the typical 

range for well-sorted gravel, and a hydraulic conductivity of 

4 X 10–4 m/d is indicative of clay (Fetter, 1994). Both lithologies are common in the study area and represent the lithologic 

end members. Permeameter tests of cores from the Corcoran 

Clay indicate vertical hydraulic conductivities ranging from 1 

X 10–6 to 3 X 10–6 m/d (Page, 1977). Previous investigations, 

however, indicate wells screened across the Corcoran Clay 

provide direct vertical connection between the unconfined and 

confined aquifers and have increased the vertical hydraulic 

conductivity by orders of magnitude (Williamson and others, 

1989; Belitz and Phillips, 1995), which is consistent with the 

calibrated value of Kcorc from this study.

Model-Computed Hydraulic Heads

The simulated water table closely resembles that depicted 

in figure 4.5. In the area overlying the Corcoran Clay, modelcomputed hydraulic heads in the area with a shallow water 

table closely match measured heads with an average residual 

of 0.92 m and RMSE of 1.9 m (fig. 4.15). Water levels in wells 

east of the Corcoran Clay extent that represent the unconfined 

aquifer also are simulated reasonably well with an average residual of -1.5 m and RMSE of 3.6 m, although there is 

an apparent increase in residuals with increasing measured 

hydraulic head for the unconfined aquifer east of the Corcoran 

Clay extent (fig. 4.16). In general, the residuals are randomly 

distributed around zero for the entire modeled area (fig. 4.16).

A simple method of assessing overall model fit is to plot 

the model-computed hydraulic head values against the measured observations. For a perfect fit, all points should fall on 

the 1:1 diagonal line. Figure 4.17 presents a plot of the modelcomputed heads as compared to measured hydraulic heads 

for the San Joaquin Valley regional study area and indicates 

reasonable model fit. The average residual for the entire model 

is -0.9 m with a standard deviation of 3.67 m, and residuals 

range from -10.5 m to 6.0 m (range of 16.5 m). The RMSE for 

the entire model is 3.75 m, which is about 10 percent of the 

range of head observations in the model (37.7 m).

Measured hydraulic heads in the Modesto area include 

those in four clusters of piezometers installed for this study 

(Phillips and others, 2007). The piezometers that represent the 

water table range in depth from 11 to 14 m, and the deepest 

piezometer in each cluster ranges from 102 to 108 m deep. 

The shallow and deep water levels were closely simulated, 

with an average error of 0.78 m and 0.35 m, respectively. Consequently, the downward vertical gradient, which features an 

average head difference of 4.4 m, also was simulated well.

Model-computed hydraulic heads between the water 

table and the Corcoran Clay were greater than the measured 

heads by an average of 1.8 m. Coupled with the generally low 

simulated water table, simulated downward gradients above 

the Corcoran are, on average, too low. Model-computed heads 

below the Corcoran were generally greater than measured 
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–23

Figure 4. 14. Ground-water flow model calibration results, San Joaquin Valley regional study area, California. (Continued on next 

page.)

–15

6

5

4

30

0

7

60

90

5

4

3

23

18

13

30

8

7

40

–12

1.7

–15

1.7

2.2

2.7

3.2

–20

–25

–30

–35

2.48 –40

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Shallow water table above Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Water table east of Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Between water table and Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Below Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

EXPLANATION

Line of equal root mean square error between model-computed and measured heads

Line of minimum root mean square error between model-computed and measured head

Line of equal bias between model-computed and measured heads

Parameter combinations simulated and for which error was calculated

Parameter combinations for which model was numerically unstable

Calibrated end-member hydraulic conductivities

1.7

–15
4–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 14. Ground-water flow model calibration results, San Joaquin Valley regional study area, California.—Continued

0.050

0.052

0.057

0

–0.03

–0.06

0.135

0.140

0.145

0.150

0.34

0.37

0.40

0.43

0.063

0.065

0.067

0.12

0.14

0.16

0.18

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

East of Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Above Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

2.48

2.40

2.32

2.24

2.17

2.09

2.01

1.93

1.86

1.78

Log hydraulic conductivity, coarse-grained end member

Across Corcoran Clay

–3.52 –3.13 –2.74 –2.35 –1.96 –1.56 –1.17 –0.78 –0.39 0

Log hydraulic conductivity, fine-grained member

EXPLANATION

Line of equal root mean square error between model-computed and measured heads

Line of minimum root mean square error between model-computed and measured head

Line of equal bias between model-computed and measured heads

Parameter combinations simulated and for which error was calculated

Parameter combinations for which model was numerically unstable

Calibrated end-member hydraulic conductivities

1.7

–15
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–25

Figure 4. 15. Spatial distribution of hydraulic-head residuals, San Joaquin Valley regional study area, California.

5

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San

Joaquin

River

Stanislaus

River

Tuolumne

River

Merced

River

Turlock

Lake

Modesto

Reservoir

Woodward

Reservoir

STOCKTON

MODESTO

TURLOCK

MERCED

SAN JOAQUIN

STANISLAUS

STANISLAUS

TUOLUMNE

STANISLAUS

MERCED

SANTA CLARA

STANILAUS

MERCED

MARIPOSA

STANISLAUS

CALAVERAS

37° 45'

37° 30'

121° 15' 121° 00' 120° 45' 120° 30'

37° 15'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Physiographic region

 Basin

 Eastern alluvial fans

 Western alluvial fans

Urban

Inactive model cells

Extent of model grid

Extent of Corcoran Clay—

 Hachures point toward clay

Model-computed as compared to measured hydraulic heads

 Location

 Water table

 Between water table and Corcoran Clay

 Below Corcoran Clay

 Model-computed residuals—Difference between model-

 computed and measured head

 Less than 3 meters

 3 to 6 meters

 6.1 to 10.5 meters

 Relative difference

 Model-computed head greater than measured water level

 Model-computed head lower than measured water level
4–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 4. 16. Relation between head residual and measured 

hydraulic head, San Joaquin Valley regional study area, California.

Figure 4. 17. Relation between model-computed and measured 

hydraulic head, San Joaquin Valley regional study area, California.

heads by an average of 4 m, but the gradient across the Corcoran is simulated reasonably well in the four locations where 

measurements were available.

Model-Computed Water Budget

Many of the water-budget components simulated by the 

model were specified values. Areal recharge, which was dominated by agricultural irrigation and precipitation, accounted 

for about 71 percent of the total recharge (table 4.2). Leakage 

from reservoirs contributed about 4 percent of the water, and 

net inflow (inflow minus outflow) from rivers also contributed 

about 4 percent of the water. Pumping from wells, primarily for agricultural purposes, accounted for about 54 percent 

of the total discharge. About 12 percent of the discharge 

was bare-soil evaporation from the shallow water table. The 

remainder of the model-computed water budget was flow 

through the lateral head-dependent boundaries, which was a 

net outflow of about 13 percent. Details of the simulated water 

budget are listed in table 4.2.

Simulation of Areas Contributing Recharge to 

Public-Supply Wells

The ground-water flow model was used to simulate 

capture zones for 60 public-supply wells to aid understanding 

of the flow system and to elucidate connections between land 

use and the chemistry of water discharging from public-supply wells. Water extracted from these wells followed various 

pathways through the aquifer system and is an amalgamation 

of water that may vary widely in age and origin. Particle tracking was used to approximate the pathway of water particles, 

associated ages, and points where these particles first entered 

the aquifer, hereinafter referred to collectively as “the contributing area.” The various land uses overlying the contributing 

area may be associated with different chemical inputs to the 

aquifer, which may ultimately reach the public-supply well.

Particle-Tracking Simulations

Sixty public-supply wells with a range of pumping rates 

were selected for particle-tracking analysis. Pumping rates 

for 109 wells that supplied the city of Modesto during wateryear 2000 were available, and 15 wells from each quartile of 

pumping rate were selected for particle-tracking analysis. The 

pumping rates ranged from 131 to 13,381 m3/d, and the total 

water extracted from the 60 wells represents about 60 percent 

of the 57 million cubic meters the city pumped during wateryear 2000.

Particle-tracking software, MODPATH (Pollock, 1994), 

was used in conjunction with flux output from the flow model 

to calculate flow paths and traveltimes for water particles 

traveling from the contributing area, through the aquifer 

system, and to the wells. The model-computed areas contrib-

–12

–10

–8

–6

–4

–2

0

2

4

6

8

Head residual, in meters

Measured head elevation, in meters

0 5 10 15 20 25 30 35 40 45 50

EXPLANATION

Shallow water table above Corcoran Clay

Between ater table and Corcoran Clay

Below Corcoran Clay

Water table east of Corcoran Clay

1:1 line

0

5

10

15

20

25

30

35

40

45

50

Model-computed head elevation, in meters

Measured head elevation, in meters

0 5 10 15 20 25 30 35 40 45 50
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–27

Table 4.2. Model-computed water budget for water-year 2000, San Joaquin Valley regional study 

area, California.

[m3/d, cubic meters per day; —, not applicable]

Water-budget component

Specified

flow

(m3/d)

Computed

flow

(m3/d)

Total flow

(m3/d)

Percentage 

of inflow or 

outflow

Model inflow

Agricultural irrigation return flow 2,267,000 — 2,267,000 41.5

Precipitation 1,598,000 — 1,598,000 29.3

Rivers 500,000 25,000 525,000 9.6

Reservoir leakage — 207,000 207,000 3.8

Pipe leakage, urban 11,000 — 11,000 0.2

Flow through lateral boundaries

Northwest — 102,000 102,000 1.9

Southeast — 162,000 162,000 3.0

Southwest — 584,000 584,000 10.7

TOTAL INFLOW 5,456,000 100

Model outflow

Wells

Agricultural 2,732,000 — 2,732,000

Public supply 274,000 — 274,000

Total (smaller due to dry cells in upper

part of some well screens) 

2,955,000 — 2,955,000 54.2

Evaporation from shallow water table — 651,000 651,000 11.9

Rivers — 310,000 310,000 5.7

Flow through lateral boundaries

Northwest — 952,000 952,000 17.5

Southeast — 103,000 103,000 1.9

Southwest — 480,000 480,000 8.8

TOTAL OUTFLOW 5,452,000 100

uting recharge represent advective ground-water flow and do 

not account for mechanical dispersion. Advection-dispersion 

transport simulations would likely yield larger areas contributing recharge than advective particle-tracking simulations 

because the effects of dispersion caused by aquifer heterogeneity would be included.

Effective porosity was the only hydraulic parameter 

entered into the MODPATH input files. Effective porosity values were assigned on the basis of percentage of coarse-grained 

texture in each model cell (table 4.3). The porosity values are 

based on literature values for different geologic/textural materials (Domenico and Schwartz, 1990) and previous work in 

similar geologic formations in the eastern San Joaquin Valley 

(Burow and others, 1999).

Table 4.3. Effective porosity values, by percentage of coarsegrained texture, used for MODPATH simulations, San Joaquin 

Valley regional study area, California.

[>, greater than; <=, less than or equal to]

Textural material Percentage coarse 

material Effective porosity

Gravel > 75 0.25

Coarse sand 51–75 0.28

Fine sand 26–50 0.32

Silt and clay <= 25 0.35
4–28 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Public-Supply Well Contributing Areas

Fifteen wells in each quartile of pumping in the Modesto 

area were selected to delineate areas contributing recharge 

and compute traveltimes. The resulting contributing areas 

for the 15 wells in the top quartile pumping rate (fig. 4.18) 

tend to overlap and generally extend to the northeast of 

Modesto beyond the extent of the Corcoran Clay. The size 

of the contributing areas generally is a function of the pumping rate, whereas the shape is influenced by geologic setting 

and well-construction characteristics. The ground-water flow 

model incorporates the spatial interpolation model of percentage of coarse-grained texture; therefore, the contributing areas 

reflect, to a degree, the heterogeneous deposits that are characteristic of these dominantly fluvial sediments. This approach 

results in uniquely shaped contributing areas that generally do 

not resemble the tear-shaped areas one would expect in a more 

homogeneous setting.

Differing well characteristics also account for variability in contributing areas. Shallow wells, which tend to have 

lower production rates, generally have small contributing areas 

close to the wells. Traveltimes to shallow wells are relatively 

short. The larger contributing areas and longer flow paths 

(and traveltimes) are associated with higher producing wells. 

These high-producing wells tend to have the longest screened 

intervals and are relatively deep. Consequently, the contributing areas from these wells commonly have two components: 

a local area, which may be offset from the well, that represents the source of water flowing to the upper portion of the 

screened interval; and a distant area that represents the source 

of water flowing to the lower portion of the screened interval. For example, Well 51 in the northwest part of Modesto 

has a contributing recharge area immediately east of the well 

that contributes to the upper portion of the screened interval 

and a small contributing recharge area more than 6 km to the 

northeast that contributes to the lower portion of the screened 

interval.

The minimum traveltime from the water table to the well 

for all 60 wells ranges from 3 to 141 years with a median of 

about 20 years. The maximum traveltime ranges from 18 years 

to more than 1,600 years with a median of 107 years. The 

zones of contribution outlined by pathlines for the 60 publicsupply wells occupy more than 143 km2

 within the modeled 

area. Agricultural and urban land uses dominate in most of the 

area contributing recharge to public-supply wells.

Limitations and Appropriate Use of the Model

The ground-water flow model for the San Joaquin Valley 

regional study area was designed to estimate aquifer-system 

properties, to delineate contributing areas to public-supply 

wells in Modesto, to help guide data collection, and to support 

future local modeling efforts. Limitations of the ground-water 

flow model, assumptions made during model development, 

and results of model calibration and sensitivity analysis all 

are factors that constrain the appropriate use of the model and 

highlight potential future improvements.

A ground-water flow model is a means for portraying 

and testing a conceptual understanding of a system. Because 

ground-water flow systems are inherently complex, simplifying assumptions were made in developing this model (Anderson and Woessner, 1992). Models solve for average conditions 

within each cell, the parameters for which are interpolated 

or extrapolated from measurements and(or) estimated during calibration. In light of this, the intent in developing the 

ground-water flow model was not to reproduce every detail of 

the natural system, but rather to portray its general characteristics.

Water-level hydrographs indicate the ground-water 

system in the study area approximated steady-state equilibrium for water-year 2000 (fig. 4.6); however, the data are not 

conclusive. Long-term hydrographs are not available for some 

areas, including the southeastern part of the model area, where 

hydraulic heads may have been changing with time. Errors 

related to this assumption can be substantial, and care must be 

taken in interpreting model results and analyses that depend on 

model output, including particle tracking.

Some of the boundary conditions of the model are poorly 

constrained, which may be a source of model error. The lateral 

boundary along the San Joaquin River is based on sparse data, 

and the spatial distribution of hydraulic head below the river 

is poorly understood. Similarly, there is little information on 

river/aquifer interaction in the study area, and none regarding 

the hydraulic conductivity of riverbed sediments. Simulation 

results indicate that fluxes across these poorly constrained 

boundaries (table 4.2) make up a small part of the water budget; however, these boundaries may be more important in the 

real system.

The accuracy of model results is related strongly to the 

quality and spatial distribution of input data, and of measurements of system state (for example, measured hydraulic heads) 

for comparison with simulation results during model calibration. The Modesto area is the only region of the ground-water 

flow model that has high-quality input data (particularly 

pumping by well) coupled with a good distribution of measured hydraulic heads. The stresses in other areas of the model 

are a combination of measured values and those estimated 

from the water-budget analysis. Accordingly, the user should 

have higher confidence in simulation results in the Modesto 

area than in other areas of the model.

The interpolation of sediment texture data within model 

layers, or two dimensions, may artificially decrease the vertical connectivity of coarse-grained materials in the aquifer system. This potential shortcoming in the parameter-estimation 

procedure used for the ground-water flow model may affect 

simulated particle pathways and associated analyses. Applying 

a three-dimensional interpolation method may provide a significant improvement over the current parameter distribution.

Computed areas contributing recharge and traveltimes 

through zones of contribution are based on a calibrated model 
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–29

Figure 4. 18. Model-computed areas contributing recharge for 15 public-supply wells in top quartile of pumping, 

San Joaquin Valley regional study area, California.

99

132

108

219

132

Stanislaus

River

Tuolumne

River

MODESTO

RIVERBANK

OAKDALE

SAN JOAQUIN

STANISLAUS

37° 45'

37° 40'

121° 5' 121° 00' 120° 55' 120° 50'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 120° West,

North American Datum of 1983

0 1 2 3 4 5 6 7 8 9 10 KILOMETERS

0 1 2 3 4 5 MILES

EXPLANATION

Physiographic region

 Basin

 Eastern alluvial fans

Urban

Extent of Corcoran Clay—Hachures point to clay

Area contributing recharge to public-supply wells

Pathlines outlining zones of contribution to public-supply wells

 Well 285

 Well 45

 Well 211

 Well 47

 Well 41

Wells selected for contributing-area analysis

 Well 32

 Well 37

 Well 25

 Well 46

 Well 39

 Well 43

 Well 48

 Well 33

 Well 51

 Well 16
4–30 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

and estimated effective porosity values. 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 will change computed traveltimes from recharge 

to discharge areas in direct proportion to changes of porosity 

because there is an inverse linear relation between ground-water flow velocity and effective porosity and a direct linear relation between traveltime and effective porosity. For example, 

a one-percent decrease in porosity will result in a one-percent 

increase in velocity and a one-percent decrease in particle 

traveltime. A detailed sensitivity analysis of porosity distributions was beyond the scope of this study, although future work 

could compare simulated ground-water traveltimes to groundwater ages to more thoroughly evaluate effective porosity 

values.

The San Joaquin Valley regional ground-water flow 

model uses justifiable aquifer properties and boundary conditions and provides a reasonable representation of groundwater flow conditions in the study area for the year 2000. The 

model is suitable for evaluating regional water budgets and 

ground-water flow paths in the study area for the time period 

of interest but may not be suitable for long-term predictive 

simulations. This regional model provides a useful tool to 

evaluate aquifer vulnerability at a regional scale, to facilitate 

comparisons of ground-water traveltime between regional 

aquifer systems, and to guide future detailed investigations in 

the study area.

References Cited

Anderson, M.P. and Woessner, W.W., 1992, Applied groundwater modeling—Simulation of flow and advective transport: San Diego, California, Academic Press, Inc., 381 p.

Arkley, R.J., 1962, Soil survey of Merced area, California: 

U.S. Department of Agriculture, Soil Conservation Service, 

Soil Survey series 1950, no. 7, 131 p., 101 pls.

Arkley, R.J., 1964, Soil survey, eastern Stanislaus area, California: U.S. Department of Agriculture, Soil Conservation 

Service, Soil Survey series 1957, no. 20, 160 p.

Bartow, J.A., 1991, The Cenozoic evolution of the San Joaquin 

Valley, California: U.S. Geological Survey Professional 

Paper 1501, 40 p.

Belitz, Kenneth, and Phillips, S.P., 1995, Alternative to 

agricultural drains in California’s San Joaquin Valley—

Results of a regional-scale hydrogeologic approach: Water 

Resources Research, v. 31, no. 8, p. 1845–1862.

Bertoldi, G.L., Johnston, R.H., and Evenson, K.D., 1991, 

Ground water in the Central Valley, California—A summary 

report: U.S. Geological Survey Professional Paper 1401–A, 

44 p.

Burow, K.R., Panshin, S.Y., Dubrovsky, N.M., VanBrocklin, David, and Fogg, G.E., 1999, Evaluation of processes 

affecting 1,2-dibromo-3-chloropropane (DBCP) concentrations in ground water in the eastern San Joaquin Valley, 

California, analysis of chemical data and ground-water flow 

and transport simulations: U.S. Geological Survey WaterResources Investigations Report 99–4059, 57 p.

Burow, K.R., Shelton, J.L., Hevesi, J.A., and Weissmann, 

G.S., 2004, Hydrogeologic characterization of the Modesto 

area, San Joaquin Valley, California: U.S. Geological Survey Scientific Investigations Report 2004–5232, 54p.

California Department of Water Resources, 1994, Urban 

water use in California: California Department of Water 

Resources, Bulletin 166–4, 48 p. plus appendixes.

Davis, G.H., Green, J.H., Olmsted, F.H., and Brown, D.W., 

1959, Ground-water conditions and storage capacity in the 

San Joaquin Valley, California: U.S. Geological Survey 

Water-Supply Paper 1469, 287 p.

Davis, S.N. and Hall, F.R., 1959, Water quality of eastern 

Stanislaus and northern Merced counties, California: Palo 

Alto, California, Stanford University Publications, Geological Sciences, v. 6, no. 1, 112 p.

Domenico, P.A., and Schwartz, F.W., 1990, Physical and 

chemical hydrogeology: New York, John Wiley and Sons, 

824 p.

Fenske, J.P., Leake, S.A., and Prudic, D.E., 1996, Documentation of a computer program (RES1) to simulate leakage 

from reservoirs using the modular finite-difference groundwater flow model (MODFLOW): U.S. Geological Survey 

Open-File Report 96–364, 51 p.

Fetter, C.W., 1994, Applied hydrogeology: New York, Macmillan College Publishing Company, 691 p.

Gronberg, J.M., Dubrovsky, N.M., Kratzer, C.K., Domagalski, 

J.L., Brown, L.R., and Burow, K.R., 1998, Environmental 

setting of the San Joaquin-Tulare Basins, California: U.S. 

Geological Survey Water-Resources Investigations Report 

97–4205, 45 p.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. 

Geological Survey Open-File Report 00–92, 121 p.

Laudon, Julie, and Belitz, Kenneth, 1991, Texture and depositional history of late Pleistocene-Holocene alluvium in the 

central part of the western San Joaquin Valley, California: 

Bulletin of the Association of Engineering Geologists, v. 28, 

no. 1, p. 73–88.
Hydrogeologic Settings and Ground-Water Flow Simulations of the San Joaquin Valley Regional Study Area, California 4–31

Londquist, C.J., 1981, Digital model of the unconsolidated 

aquifer system in the Modesto Area, Stanislaus and San 

Joaquin counties, California: U.S. Geological Survey WaterResources Investigations Report 81–12, 36 p.

Marchand, D.E., and Allwardt, A., 1981, Late Cenozoic stratigraphic units, San Joaquin-Tulare Basins, California: U.S. 

Geological Survey Bulletin 1470, 70 p.

Maupin, M.A., and Barber, N.L., 2005, Estimated withdrawals from principal aquifers in the United States, 2000: U.S. 

Geological Survey Circular 1279, 47 p.

National Oceanic and Atmospheric Administration, 2005, Precipitation records for California, Web page accessed Nov. 

14, 2005, at http://lwf.ncdc.noaa.gov/oa/pub/data/coopprecip/california.txt.

 Page, R.W., 1973, Base of fresh ground water (approximately 

3,000 micromhos) in the San Joaquin Valley, California: 

U.S. Geological Survey Hydrologic Investigations Atlas 

HA–489.

Page, R.W., 1977, Guide for data collection to calibrate a 

predictive digital ground-water model of the unconfined 

aquifer in and near the city of Modesto, California: U.S. 

Geological Survey Water-Resources Investigations Report 

76–41, 46 p.

Page, R.W., 1986, Geology of the fresh ground-water basin of 

the Central Valley, California, with texture maps and sections: U.S. Geological Survey Professional Paper 1401–C, 

54 p.

Page, R.W., and Balding, G.O., 1973, Geology and quality 

of water in the Modesto-Merced area, San Joaquin Valley, 

California: U.S. Geological Survey Water-Resources Investigations Report 73–6, 85 p.

Phillips, S.P., Beard, Sherrill, and Gilliom, R.J., 1991, Quantity and quality of ground-water inflow to the San Joaquin 

River, California: U.S. Geological Survey Water-Resources 

Investigations Report 91–4019, 64 p.

Phillips, S.P. and Belitz, Kenneth, 1991, Calibration of a 

texture-based model of a ground-water flow system, western 

San Joaquin Valley, California: Ground Water, v. 29, no. 5, 

p. 702-715.

Phillips, S.P., Green, C.T., Burow, K.R., Shelton, J.L., and 

Rewis, D.L., 2007, Simulation of multiscale ground-water 

flow in part of the northeastern San Joaquin Valley, California: US Geological Survey Scientific Investigations Report 

2007–5009, 43 p.

Piper, A.M., Gale, H.S., Thomas, H.E., and Robinson, T.W., 

1939, Geology and ground-water hydrology of the Mokelumne area, California: U.S. Geological Survey Water-Supply Paper 780, 230 p.

Pollock, D.W., 1994, User’s guide for MODPATH/MODPATH-PLOT, Version 3—A particle tracking post-processing package for MODFLOW, the U.S. Geological Survey 

finite-difference ground-water flow model: U.S. Geological 

Survey Open-File Report 94–464, accessed Feb. 6, 2007 

at http://water.usgs.gov/nrp/gwsoftware/modpath41/modpath41.html

U.S. Census Bureau, 2002, State and county quickfacts, for 

1990 and 2000: Web page accessed April 26, 2002, at 

http://quickfacts.census.gov/qfd/states/06/06099lk.html.

 Williamson, A.K., Prudic, D.E., and Swain, L.A., 1989, 

Ground-water flow in the Central Valley, California: U.S. 

Geological Survey Professional Paper 1401–D, 127 p.

Hydrogeologic Setting and Ground-Water 

Flow Simulations of the Northern Tampa 

Bay Regional Study Area, Florida

By Christy Crandall

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 5 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
Suggested citation:

Crandall, C., 2007, Hydrogeologic settings and ground-water flow simulation of the Northern Tampa Bay Regional 

Study Area, Florida, section 5 of Paschke, S.S., ed., Hydrogeologic settings and ground-water flow simulations for 

regional studies of the transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 

2001: Reston, Va., U.S. Geological Survey Professional Paper 1737–A, pp. 5–1 – 5–30.

U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report. 
iii

Contents

Abstract...................................................................................................................................................... 5–1

Introduction................................................................................................................................................ 5–1

Purpose and Scope ......................................................................................................................... 5–1

Study Area Description................................................................................................................... 5–3

Topography and Climate ........................................................................................................ 5–3

Surface-Water Hydrology ..................................................................................................... 5–3

Land Use................................................................................................................................... 5–3

Water Use ................................................................................................................................ 5–3

Conceptual Understanding of the Ground-Water System................................................................. 5–7

Geology.............................................................................................................................................. 5–7

Ground-Water Occurrence and Flow........................................................................................... 5–7

Surficial Aquifer System........................................................................................................ 5–7

Floridan Aquifer System ........................................................................................................ 5–9

Aquifer Hydraulic Properties ......................................................................................................... 5–9

Water Budget ................................................................................................................................. 5–11

Ground-Water Quality ................................................................................................................... 5–11

Ground-Water Flow Simulations .......................................................................................................... 5–13

Modeled Area and Spatial Discretization.................................................................................. 5–13

Boundary Conditions..................................................................................................................... 5–13

Model Stresses .............................................................................................................................. 5–15

Recharge................................................................................................................................ 5–15

Pumping.................................................................................................................................. 5–15

Rivers. .................................................................................................................................... 5–15

Drains. .................................................................................................................................... 5–15

Aquifer Properties.......................................................................................................................... 5–15

Model Calibration and Sensitivity ............................................................................................... 5–19

Model-Computed Hydraulic Heads ................................................................................... 5–19

Model-Computed Discharge and Recharge .................................................................... 5–23

Model-Computed Water Budget........................................................................................ 5–23

Simulation of Areas Contributing Recharge to Wells .............................................................. 5–27

Limitations and Appropriate Use of the Model......................................................................... 5–27

References Cited..................................................................................................................................... 5–29

Figures

Maps showing:

5.1. Location of the Northern Tampa Bay regional study area within the 

Floridan aquifer system...........................................................................................5–2

5.2. Topography, hydrologic features, and locations of public-supply wells, 

Northern Tampa Bay regional study area, Florida.............................................5–6

5.3. Generalized hydrologic section showing conceptual ground-water flow and 

geochemical conditions, Northern Tampa Bay regional study area, Florida. .......... 5–7
iv

Maps showing:

5.4. Year-2000 potentiometric surface and thickness of the Floridan 

aquifer, Northern Tampa Bay regional study area, Florida............................5–10

5.5. Oxidation-reduction classification, Northern Tampa Bay regional 

study area, Florida..................................................................................................5–12

5.6. Ground-water flow model grid and boundary conditions, 

Northern Tampa Bay regional study area, Florida...........................................5–14

5.7. Distribution of hydraulic conductivity for model layer 1, 

Northern Tampa Bay regional study area, Florida...........................................5–16

5.8. Distribution of vertical leakance values assigned between model 

layers 1 and 2, Northern Tampa Bay regional study area, Florida................5–17

5.9. Distribution of transmissivity values assigned to the Floridan 

aquifer (model layers 2, 3, and 4), Northern Tampa Bay regional 

study area, Florida..................................................................................................5–18

5.10. Ground-water flow model calibrated recharge rates,

Northern Tampa Bay regional study area, Florida. ..........................................5–20

5.11A. Distribution of model-computed hydraulic heads for the surficial

aquifer system (model layer 1), Northern Tampa Bay regional study

area, Florida.............................................................................................................5–21

5.11B. Distribution of model-computed hydraulic heads for the uppermost 

Floridan aquifer system (model layer 2), Northern Tampa Bay regional 

study area, Florida..................................................................................................5–22

Graphs showing:

5.12A. Relation between model-computed and measured hydraulic head 

for model layer 1, Northern Tampa Bay regional study area, Florida. .........5–23

5.12B. Relation between model-computed and measured hydraulic head 

for model layer 2, Northern Tampa Bay Regional study area, Florida. ........5–23

5.13. Map showing distribution of head residuals for model layers 1 and 2, 

Northern Tampa Bay regional study area, Florida. ..................................................... 5–24

Graphs showing:

5.14A. Probability distribution of head residuals for model layer 1, 

Northern Tampa Bay regional study area, Florida...........................................5–25

5.14B. Probability distribution of head residuals for model layer 2, 

Northern Tampa Bay regional study area, Florida...........................................5–25

Maps showing:

5.15. Model-computed ground-water inflows and outflows, 

Northern Tampa Bay regional study area, Florida. ..........................................5–26

5.16. Model-computed areas contributing recharge for selected publicsupply wells, Northern Tampa Bay regional study area, Florida. .................5–28

Tables

5.1. Summary of hydrogeologic and ground-water quality characteristics 

for the Floridan aquifer system and the Northern Tampa Bay regional

study area, Florida. ............................................................................................................. 5–4

5.2. Geology, hydrogeology, and water-use characteristics, 

Northern Tampa Bay regional study area, Florida. ....................................................... 5–8

5.3. Model-computed water budget for year 2000, Northern Tampa Bay 

regional study area, Florida. ........................................................................................... 5–25
Hydrogeologic Setting and Ground-Water Flow 

Simulations of the Northern Tampa Bay Regional

Study Area, Florida

By Christy Crandall

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated for part of the Floridan 

aquifer system in the vicinity of Tampa Bay, Florida, as part of 

the U.S. Geological Survey National Water-Quality Assessment Program. The aquifer system in the Northern Tampa 

Bay regional study area is representative of the karst Floridan 

aquifer system throughout the Southeastern United States, is 

used extensively for public water supply, and is susceptible 

and vulnerable to contamination. The aquifer system in the 

study area is composed of an unconfined surficial aquifer of 

sandy deposits underlain by the karst limestone of the Floridan 

aquifer system. The two aquifers are separated by an intermediate confining zone in some parts of the study area creating 

confined and unconfined conditions in the Floridan aquifer 

system. An existing two-layer, steady-state ground-water flow 

model of the study area was modified to include a finer model 

grid, two additional layers, and additional boundary conditions 

and was recalibrated to year-2000 conditions. The calibrated 

ground-water flow model and advective particle-tracking 

simulations were used to compute ground-water flow paths, 

areas contributing recharge, and traveltimes from recharge 

areas to public-supply wells. Model results indicate precipitation recharge (55.4 percent of inflow) and lateral ground-water 

flow (35.1 percent of inflow) provide most of the groundwater inflow. Ground-water discharge is to the Gulf of Mexico 

and Tampa Bay (38 percent of outflow), wells (29.1 percent 

of outflow), and springs and streams (32.7 percent of outflow). Particle-tracking results indicate minimum traveltimes 

to public-supply wells ranged from 0.7 to 233 years with an 

average minimum traveltime of 19 years. Maximum computed 

traveltimes ranged from 32 to 1,875 years and averaged 600 

years. On average, only 3 percent of the flow to a publicsupply well was less than 10 years old, about 36 percent of 

the flow to a public-supply well was less than 50 years old, 

and about 80 percent of the flow to a public-supply well was 

less than 200 years old. Simulated traveltimes are probably 

much longer than actual travel times in the aquifer because the 

regional ground-water flow model does not accurately represent flow through local karst dissolution features.

Introduction

The Northern Tampa Bay regional study area for the 

transport of anthropogenic and natural contaminants (TANC) 

study overlies the karst Floridan aquifer system in west-central 

peninsular Florida in the Tampa Bay metropolitan area (fig. 

5.1). The Floridan aquifer system underlies the Georgia-Florida Coastal Plain drainages National Water-Quality Assessment (NAWQA) study unit and much of the southeastern coast 

of the United States (fig. 5.1)

Purpose and Scope

The purpose of this Professional Paper section is to 

present the hydrogeologic setting of the Northern Tampa Bay 

TANC regional study area. The section also documents the 

setup and recalibration of a steady-state regional ground-water 

flow model for the study area. Ground-water flow characteristics, pumping-well information, and water-quality data were 

compiled from existing data to develop a conceptual understanding of ground-water conditions in the study area. An 

existing ground-water flow model of the area (Yobbi, 2000) 

was modified to include a finer model grid, two additional layers, and additional boundary conditions and was recalibrated 

to year-2000 conditions. The year 2000 was assumed to represent average conditions for the period from 1997 to 2001. The 

5-year period 1997–2001 was selected for data compilation 

and modeling exercises for all TANC regional study areas to 

facilitate future comparisons between study areas. The updated 

ground-water flow model and associated particle tracking were 

used to simulate advective ground-water flow paths and to 

delineate areas contributing recharge to selected public-supply 

wells. Ground-water traveltimes from recharge to publicsupply wells and presence of potential contaminant sources 
5–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.1. Location of the Northern Tampa Bay regional study area within the Floridan aquifer system.

T E N N E S S E E

A T L A N T I C

O

C

E

A

N

G U L F

O F

M E X I C O

N O R T H C A R O L I N A

S O U T H

C A R O L I N A

A L A B A M A G E O R G I A

M I S

S I S

S I P

P I

F L O R I D A

B A H A M A

S

Lake

Okeechobee

Miami

Tampa

St.

Petersburg

Orlando

Jacksonville Tallahassee Pensacola

Mobile

Birmingham

Atlanta

Savannah

Charleston

Raleigh

Chattanooga

Nashville

89° 88° 87° 86° 85° 84° 83° 82° 81° 80° 79° 78° 77° 76° 75° 

36° 

35° 

34° 

33° 

32° 

31° 

30° 

29° 

28° 

27° 

26° 

25° 

24° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

Modified from Miller, 1986

0 50 100 150 200 kilometers

0 50 100 miles

EXPLANATION

Northern Tampa Bay regional study area

Floridan aquifer system

 Confined

 Semiconfined

 Unconfined

USGS NAWQA study unit—Georgia-Florida Coastal Plain Drainages
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–3

in areas contributing recharge were tabulated into a relational 

database as described in Section 1 of this Professional Paper. 

This section provides the foundation for future ground-water 

susceptibility and vulnerability analyses of the study area and 

comparisons among regional aquifer systems.

Study Area Description

The Northern Tampa Bay regional study area was chosen 

because the Floridan aquifer system is used extensively for 

public water supply and is susceptible and vulnerable to 

contamination. The area also represents the range of hydrogeologic and land-use conditions throughout areas overlying 

the Floridan aquifer system (table 5.1). For example, variable hydrologic confining conditions and karst features are 

prevalent in both the Floridan aquifer system and the Northern 

Tampa Bay regional study area (Miller, 1986).

Topography and Climate

The Northern Tampa Bay regional study area is characterized by relatively flat, marshy lowlands along the coast 

(Coastal Swamps region), rolling hills of intermediate relief 

throughout parts of central Pasco County with elevations as 

high as 30 m above NAVD88 (Gulf Coastal Lowlands), and 

sand terraces to the northeast and southeast (Brooksville Ridge 

and Western Highlands, respectively) (White, 1970). The 

most prominent topographic feature in the study area is the 

Brooksville Ridge, located in central Hernando and eastern 

Pasco Counties. Land surface altitudes range from sea level 

to approximately 90 m above NAVD88 along the Brooksville 

Ridge (fig. 5.2).

The climate of the study area is subtropical with warm, 

wet summers and relatively dry, mild winters. Rainfall varies 

seasonally with more than one-half the total annual rainfall 

usually occurring between June and September, the result of 

convective storms. Average annual rainfall in the study area 

ranges from 125 to 140 cm per year (Metz and Sacks, 2002). 

Pan evaporation rates are high and average 125 to 150 cm per 

year (Farnsworth and others, 1982).

Surface-Water Hydrology

Karst features such as sinkholes and springs are prevalent 

throughout the study area (fig 5.2). Ancient, shallow, stable 

sinkhole depressions 5 to 8 m below land surface usually 

contain swamps and cypress domes, whereas deeper depressions infill with water and contain sinkhole lakes. At least 17 

major springs are located in the study area. Springs usually 

discharge to rivers or directly to the Gulf of Mexico. The two 

largest springs are the Weeki Wachee Springs complex in 

western Hernando County and Crystal Springs, located along 

the northern reaches of the Hillsborough River. Weeki Wachee 

and Crystal Springs provide base flow to the Weeki Wachee 

and Hillsborough Rivers, respectively (Yobbi, 2000).

Six major rivers and their tributaries are located in the 

study area (fig. 5.2). The two rivers with the largest discharge 

are the Hillsborough and Withlacoochee Rivers. Hundreds of 

lakes, swampy plains, and intermittent ponds ranging in size 

from 0.001 to 10 km2 also are dispersed throughout the study 

area.

Soils covering the Brooksville Ridge and the sand hills 

(the eastern edge of the study area) are very well drained and 

have relatively deep water tables, rapid percolation, internal drainage, and high recharge potential (HydroGeoLogic, 

Inc., 1997). Soils in the lower Gulf Coast Lowlands and 

Coastal Swamp regions (along river channels and the coast) 

are moderately to poorly drained with shallow water tables; 

numerous perched lakes, ephemeral ponds, and wetlands; and 

high organic contents (Soil Conservation Service, 1976, 1981, 

1989). Recharge is relatively low in these areas except in areas 

with sinkholes and other karst features (HydroGeoLogic, Inc., 

1997).

Land Use

Land use in the study area includes urban, residential, 

new-commercial, suburban, agriculture, wetland, and forests. 

Land-use change from agriculture and rural forests to residential and commercial is typical of areas overlying the Floridan 

aquifer system as a whole and the study area. The largest 

components of land use in the study area are agriculture (28 

percent), urban (22 percent), and wetlands (21 percent) (Hitt, 

2004). Within these categories, cropland (74 percent) and 

citrus groves (20 percent) dominate agricultural land uses, 

whereas residential (77 percent) and commercial (10 percent) 

land uses account for most of urban land uses. Wetlands are 

86 percent forested in the study area. Rangeland (7 percent), 

forests (10 percent), and waterways (6 percent) account for the 

remainder of land uses in the study area.

Water Use

Ground-water withdrawals from the entire Floridan aquifer system are 15.4 million cubic meters per day (Mm3

/d) and 

from the Floridan aquifer system within the study area they are 

1.8 Mm3/d (Marella and Berndt, 2005). The Tampa Metropolitan area relies heavily on the Floridan aquifer system as a 

drinking-water source. In 2000, Tampa Bay Water, the largest 

user of the Floridan aquifer system in the study area, withdrew 

about 0.7 Mm3/d from the Floridan aquifer system and served 

1.2 million people. In addition to public supply, the Floridan 

aquifer system is the primary source for domestic, irrigation, 

and industrial wells in the study area. Within the Northern 

Tampa Bay regional study area, public-supply wells are the 

basis of community water systems for the cities of Tampa, St. 

Petersburg, and Clearwater, Florida, and numerous smaller 

cities.
5–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 5.1. Summary of hydrogeologic and ground-water-quality characteristics for the Floridan aquifer system and the Northern 

Tampa Bay regional study area, Florida.

[m, meters; km, kilometers, cm/yr, centimeters per year; m3/d, cubic meters per day; m/d, meters per day; Kh, horizontal hydraulic conductivity; Kv, vertical 

hydraulic conductivity; Sy, specific yield; n, porosity; Mm3/d, million of cubic meters per day; mg/L, milligrams per liter; O2, dissolved oxygen; CH4 methane; 

Ca, calcium; Mg, magnesium; HCO3, bicarbonate; SO4, sulfate; Na, sodium; Cl, chloride]

Characteristic Floridan aquifer system Northern Tampa Bay regional study area

Geography

Topography Rolling hills below the Fall Line Hills of Central 

Georgia (fig. 1); elevations range from 100 to 

250 m; sandy terraces with elevations ranging 

from about 25 to 100 m; Coastal Plains and 

Wetlands from near sea level to about 25 m. Karst 

topography, in north through central Florida 

(Krause and Randolph, 1989).

Sandy hills in the Brooksville Ridge upland (fig. 2); 

relief generally less than 60 m; eolian deposits and 

sandy terraces less than 25 m; Coastal Plain and 

Swamps generally less than 3 m. Karst 

topography evident (Metz and Sacks, 2002; Ryder, 

1985; Yobbi, 2000).

Climate Temperate to subtropical; humid; precipitation 115

to165 cm/yr; evapotranspiration 115 to165 cm/yr 

(Bush and Johnston, 1988).

Subtropical; humid; precipitation 125 to150 cm/yr; 

evapotranspiration 125 to140 cm/yr (Metz and 

Sacks, 2002).

Land use Urban, suburban, water, wetland, rural residential/

commercial, woodlands, farmland (Hitt, 2004).

Urban, suburban, rural, water, wetland, residential/

commercial, woodlands, farmland (Hitt, 2004).

Geology

Surficial deposits Eolian sands and clays, gravel, and limestone; more 

fine-grained deposits further north, sand uplands 

(Miller, 1986).

Sand and clays; limited clay, mostly fine sand, 

unconsolidated limestone. Eolian sands 

discontinuous (Yobbi, 2000). 

Bedrock geologic units Thick carbonate sequence ranging from 30 to 

1,000 m in thickness from north to south 

Florida; fractured with many dissolution features 

especially in unconfined and semiconfined areas 

of south Georgia and Peninsular Florida.

Thick carbonate sequence from 200 to 400 m 

thick; fractured with many dissolution features 

especially in unconfined and semiconfined areas.

Ground-water hydrology

Aquifer conditions Unconfined; semiconfined; confined (Miller, 1986). Unconfined; semi-confined, confined (Miller, 1986; 

Yobbi, 2000).

Hydraulic properties Floridan: Kh=0.1 to 3,000 m/d; 

Kv=0.00006 m/d to 0.10 m/d; n=0.02 to 0.50 (Bush 

and Johnston, 1988; Knochenmus and Robinson, 

1996).

Surficial: Kh=0.3 to 5 m/d; n=0.25

Floridan: Kh=0.2 to 2,000 m/d; Kv=0.02 to 2 X 10–5

m/d; n=0.15 (Knochenmus and Robinson, 1996; 

SDI, Inc., 1997)

Ground-water budget Recharge from precipitation: 12.7 cm/yr or 12.1 

Mm3/d; evaporation: 92 to 102 cm/yr; discharge 

to springs: approximately 7.8 Mm3/d; river 

discharge, offshore springs, and diffuse leakage: 

0.73 Mm3/d; wells: 3.6 Mm3/d (Bush and 

Johnston, 1988; Ryder, 1985)

Recharge from precipitation: 23 cm/yr or 3.44 

Mm3/d; recharge from streams: 0.59 Mm3/d; 

discharge to springs and rivers: 2.04 Mm3/d; 

pumping: 1.8 Mm3/d. Loss to head-dependent 

boundaries: 0.30 Mm3/d (this study).

Lengths of ground-water travel 

paths

Generally thought short (less than 40 km) (Bush 

and Johnston, 1988; Knochenmus and Robinson, 

1996)

Generally less than 15 km; usually less than 7 km.
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–5

Characteristic Floridan aquifer system Northern Tampa Bay regional study area

Ground-water quality

Water chemistry (dissolved 

solids, pH, redox, major 

water types)

Dissolved solids less than 25 to greater than 1,000 

mg/L along the coast and in S. Florida; pH 6.0 

to 8.0; varies from O2 to CH4 reducing; Ca, and 

Ca,Mg-HCO3, Ca-SO4, and Na-Cl along the coast 

(Sprinkle,1989)

Dissolved solids less than 200 to greater than 1,000 

mg/L along the coast; pH 6.0 to 8.0; varies from 

O2 to Fe and SO4 reducing; Ca, and Ca,Mg-HCO3, 

Ca-SO4, and Na-Cl in Pinellas County (Ryder, 

1985). 

Contaminants Nutrients, uranium, radon, arsenic, halogenated 

volatile organic compounds, including some 

gasoline and drycleaner free product, triazine and 

bromated herbicides. Saline water in areas with 

large pumping wells near the coast (Sprinkle, 

1989).

Nutrients, uranium, radon, arsenic, halogenated 

volatile organic compounds including some 

gasoline and drycleaner free product, triazine and 

bromiated herbicides. Saline water in areas with 

large pumping wells near the coast (Ryder, 1985)

Table 5.1. Summary of hydrogeologic and ground-water-quality characteristics for the Floridan aquifer system and the Northern 

Tampa Bay regional study area, Florida.—Continued

[m, meters; km, kilometers, cm/yr, centimeters per year; m3/d, cubic meters per day; m/d, meters per day; Kh, horizontal hydraulic conductivity; Kv, vertical 

hydraulic conductivity; Sy, specific yield; n, porosity; Mm3/d, million of cubic meters per day; mg/L, milligrams per liter; O2, dissolved oxygen; CH4 methane; 

Ca, calcium; Mg, magnesium; HCO3, bicarbonate; SO4, sulfate; Na, sodium; Cl, chloride]
5–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.2. Topography, hydrologic features, and locations of public-supply wells, Northern Tampa Bay regional study area, 

Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION 3600

3200

2800

2400

2000

1600

1200

800

400

0

Land elevation, in meters above sea level

Extent of active model cells

Wetlands and lakes

Sinkholes

Springs

Public-supply well
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–7

Conceptual Understanding of the 

Ground-Water System

The study area is underlain by a sequence of Paleocene 

to Miocene carbonate rocks. Karst dissolution features control 

the ground-water flow, aquifer hydraulic properties, and to a 

lesser extent, ground-water chemistry (fig. 5.3). Ground-water 

recharge is greatest where karst sinkholes are present at the 

land surface. Ground-water discharge occurs to streams by 

way of karst springs. Aquifer hydraulic properties such as 

porosity and permeability are greatest where solution-enlarged 

fissures are present in the subsurface. Ground-water chemistry 

is controlled by ground-water flow paths and residence time in 

the carbonate rock aquifer, which are in turn controlled by the 

presence and location of karst features.

Geology

The ground-water flow system beneath the study area 

consists of a thick sequence of layered carbonate rocks 

overlain by surficial clastic deposits (table 5.2). The surficial 

deposits and carbonate rocks are subdivided into a hydrologeologic framework of two aquifers and one confining unit. 

The framework includes the unconfined surficial aquifer 

system, the intermediate confining unit that separates the 

surficial aquifer system from the Floridan aquifer system, 

and the Floridan aquifer system. The surficial aquifer system 

is composed of Pliocene to Holocene undifferentiated sands, 

clays, and marls. The intermediate confining unit is part of 

the late Miocene Hawthorn Group sediments and is composed 

of dense, plastic, green-grey clay, interbedded with varying 

amounts of chert, sand, clay, marl, shell, and phosphate. The 

intermediate confining unit is not present or is breached in 

parts of the study area where the Floridan aquifer system is 

semiconfined or unconfined (fig. 5.1). The Floridan aquifer 

system is composed of a thick sequence of limestone, dolomite, and evaporitic dolomite. The formational components of 

the Floridan aquifer system in the regional study area are as 

follows (in order of youngest to oldest): the Tampa Member of 

the Arcadia Formation and Hawthorn Group of early Miocene 

age, the Suwannee Limestone of Oligocene age, the Ocala 

Limestone of Oligocene to Eocene age, the Avon Park Formation of middle Eocene age, and the Oldsmar and Cedar Keys 

Formations of Eocene to Paleocene age (table 5.2) (Miller, 

1986; Southeastern Geological Society, 1986). A relatively 

impermeable layer composed of evaporitic limestone located 

at the base of the Avon Park Formation forms the middle 

confining unit at the base of the upper Floridan aquifer system 

and is considered the base of the freshwater flow system in the 

study area (Yobbi, 2000; Miller, 1986).

Ground-Water Occurrence and Flow

In general, unconfined ground-water conditions occur 

in the surficial aquifer system, and confined ground-water 

conditions occur in the Floridan aquifer system. Ground-water 

occurrence and flow for each of these aquifer systems are 

discussed in the following sections.

Surficial Aquifer System

The surficial aquifer system exists throughout most of 

the study area except where the Floridan aquifer system is 

exposed at land surface and unconfined (fig. 5.1) (Miller, 

1986; Berndt and Katz, 1992). The term surficial aquifer system refers to any permeable material exposed at land surface 

that contains ground water under water-table conditions and is 

Figure 5.3. Conceptual ground-water flow and geochemical conditions, Northern Tampa Bay regional study area, Florida.

Recharge

Southwest Northeast

Regional ground-water flow

Precipitation

High dissolved oxygen

Genreally oxygen

reducing

Generally iron reducing

High iron and sulfide

Generally sulfate reducing

High dissolved

oxygen

High

dissolved

oxygen

Spring, river, or

Gulf of Mexico

Not to scale

Residential land use

with septic tanks

Urban land use

Land surface

Sinkhole

Sinkholes

Recharge Recharge

EXPLANATION

Surface water—Spring, river, or Gulf of Mexico

Wetlands

Surficial aquifer

Intermediate confining unit

Upper Floridan aquifer

Karst dissolution features—Sinkholes, fissures, and conduits

Ground-water flow direction

Wells with typical screening locations
5–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 5.2. Geology, hydrogeology, and water-use characteristics of the Northern Tampa Bay regional study area, Florida [adapted from 

Ryder (1985) and Metz and Sacks (2002)].

[m, meters; SAS, surficial aquifer system; FAS, Floridan aquifer system; m3/d, cubic meters per day]

Age Stratigraphic unit Lithologic descriptions

Range in 

thickness

(m)

Hydrogeologic unit Aquifer characteristics

Holocene to Pliocene Undifferentiated 

surficial deposits, 

terrace sand, 

phosphorite

Predominantly fine 

sand; interbedded 

clay, marl, shell, 

limestone, sandy 

clay.

8 to 15 SAS Limited use; lawn 

irrigation; yields less 

than 27 m3/d; high 

iron content.

Miocene Undifferentiated 

deposits of the 

Hawthorn Group

Dense plastic greengrey clay, contains 

varying amounts 

of chert, sand; 

clay, marl, shell, 

phosphate.

0 to 6 Intermediate 

Confining bed if 

present

Semiconfining unit 

retards downward 

percolation from the 

SAS; breaches in clay 

unit preferentially 

transmit recharge to 

the Upper FAS.

Tampa Member of the 

Arcadia Formation 

of the Hawthorn 

Group

Weathered limestone 

surface, white to 

light tan, soft sandy, 

fossiliferous; clays 

in lower part in 

some areas.

6 to 75 FAS—Upper FAS Many domestic and 

public-supply wells 

tap this unit; poor 

to fair producer of 

water; yields from a 

few to 1,100 m3/d. 

Oligocene Suwannee Limestone Soft to hard limestone, 

vuggy, granular, 

fossiliferous 

limestone.

30 to 60 Domestic and large 

capacity publicsupply wells tap 

these units; yields 

from a 1,100 m3/d to 

11,000 m3 Oligocene to Eocene Ocala Limestone Limestone, chalky, /d.

foraminferal, 

dolomitic near 

bottom.

50 to 60

Eocene Avon Park Formation Hard brown dolomite 

and limestone, 

with intergranular 

evaporite in lower 

part.

120 to 200 Middle confining 

unit at the bottom 

of the Avon Park 

Formation

Eocene to Paleocene Oldsmar and Cedar 

Keys Formations

Dolomite and 

limestone with beds 

of anhydrite.

180 to 200 Lower FAS Not used for 

domestic or public 

supply—highly 

mineralized.
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–9

not part of the Floridan aquifer system. The surficial aquifer 

system may be in direct hydraulic contact with the Floridan 

aquifer system or be separated by confining beds. The base 

of the surficial aquifer system has been designated as “the 

top of the laterally extensive and vertically persistent beds of 

much lower permeability” (Southeastern Geological Society, 

1986)—the Hawthorn Group in the study area. The Floridan 

aquifer system underlies the surficial aquifer system directly 

where the intermediate confining unit is absent (Berndt and 

Katz, 1992).

The surficial aquifer system is recharged by rainfall, 

irrigation, and septic effluent (fig. 5.3). Rainfall easily infiltrates the surficial aquifer system and percolates downward 

to recharge the Floridan aquifer system by way of downward 

leakage through the intermediate confining unit. Ground water 

discharges from the surficial aquifer system through lakes, 

ditches, streams, evaporatranspiration, pumping, and downward leakage to the Floridan aquifer system (Tibbals and others, 1980). Water levels in the surficial aquifer system fluctuate widely and rapidly in response to rainfall and evaporation 

(Miller, 1986). The configuration of the top of the water table 

in the surficial aquifer system is a subdued reflection of the 

land surface and is generally within 0.1 to 3 m of the land-surface. The surficial aquifer system is not used for water supply 

(table 5.2) because of low yields (less than 27 m3/d), high iron 

content, and its vulnerability to contamination from overlying 

land use (Metz and Sacks, 2002).

Floridan Aquifer System

The Floridan aquifer system consists of a thick sequence 

of hydraulically connected carbonate rocks and covers a 

land area of more than 260,000 km2. The aquifer underlies 

coastal regions of southern Mississippi, Alabama, Georgia, 

and South Carolina and the entire Florida peninsula (fig. 5.1) 

(Miller, 1986). The Floridan aquifer system is composed of 

limestones and dolomites of late Paleocene to early Miocene 

age; however, neither the aquifer boundaries nor its high- and 

low-permeability zones necessarily conform to either formational boundaries or time-stratigraphic units. Solution-enlarged 

fissures (channel porosity) in combination with diffuse flow 

through more uniformly distributed interconnected pores (rock 

porosity) contribute to flow in the study area. The aquifer 

ranges in thickness from about 61 m in the north to over 1,000 

m in areas of central and south Florida (Miller, 1986). Units 

that compose the Floridan aquifer system outcrop in westcentral-southern Georgia and along the north- to south-central 

Gulf Coast of Florida (fig. 5.1). The Floridan aquifer system 

is considered unconfined or semiconfined where it outcrops 

and the intermediate confining unit is absent or less than 30 m 

thick and(or) breached. The Floridan aquifer system is considered confined where the intermediate confining unit is present 

and greater than 30 m thick (Miller, 1986).

Ground-water recharge to and discharge from the Floridan aquifer system are controlled by the prominent karst features and aquifer confinement. Precipitation recharge, which 

provides most of the recharge to the Floridan aquifer system in 

the study area, ranges from 25 to 55 cm/yr and occurs primarily in areas considered unconfined and semiconfined (fig. 5.1) 

(Aucott, 1988). Karst features such as springs, conduits, and 

sinkholes are common in the study area and elsewhere where 

the aquifer is unconfined or semiconfined and provide direct 

pathways for contaminants to travel from land surface to the 

aquifer (Miller, 1986). Ground-water discharge from the Floridan aquifer system occurs through springs, rivers, and coastal 

seeps and springs with approximately 75 percent of all Floridan aquifer system discharge flowing to springs (Bush and 

Johnston, 1988). The Floridan aquifer system in the study area 

supplies base flow to the Withlacoochee, Hillsborough, and 

other rivers, which are important water-supply and recreational 

resources (Bush and Johnston, 1988).

The Floridan aquifer system potentiometric surface is 

controlled by seasonally influenced recharge and local pumping. The regional ground-water flow direction is from east to 

west with a slightly southern component (fig. 5.4). Flow is 

convergent toward springs, rivers, and the Gulf of Mexico, and 

flow is transmitted vertically and laterally through karst conduits and enlarged fracture planes. The regional potentiometric 

surface exhibits highs and lows that generally correspond 

to topographic highs and lows. River and spring discharge 

features are topographic and potentiometric lows. In the study 

area, the potentiometric surface ranges from 0 to approximately 40 m in elevation (fig. 5.4).

Aquifer Hydraulic Properties

Hydraulic conductivity of the surficial aquifer system 

generally ranges from 0.1 to 5 m/d and averages 3 m/d in 

the modeled area (SDI Environmental Services Inc., 1997; 

Knochenmus and Robinson, 1996), although hydraulic 

conductivity may be as large as 30 m/d in some areas (Ryder, 

1985). The surficial aquifer system thickness ranges from 

approximately 0 in the northern part of the study area to 

more than 30 m in the southeastern part of the study area and 

averages between 8 and 25 m in the study area (Miller, 1986; 

Berndt and Katz, 1992). Effective porosity measurements for 

the surficial aquifer system vary, but an average value of 0.25 

based on geophysical measurements has been used in various 

models (SDI Environmental Services Inc., 1997; Knochenmus 

and Robinson, 1996).

Horizontal hydraulic conductivity of the Floridan aquifer 

system in the study area generally is reported to range from 

0.2 to 2000 m/d in the literature (Bush and Johnston, 1988; 

Knochenmus and Robinson, 1996), but it can vary by up to 

five orders of magnitude where karst features create secondary 

porosity in the aquifer (Langevin, 1998). Storage coefficients 

reported in the literature for the Floridan aquifer system range 

from 1 X 10–5 to 2 X 10–2 (Bush and Johnston, 1988). An 

average storage coefficient of 2.5 X 10–4 is reported for the 

study area (Tibbals and Grubb, 1982), and vertical hydraulic 

conductivity of the Floridan aquifer system ranges from 0.02 
5–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.4. Year-2000 potentiometric surface and thickness of the Floridan aquifer, Northern Tampa Bay regional study area, 

Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Anclote

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

36.6

33.5

30.5

27.4

24.4

21.3

18.3

15.2

12.2

9.1

3.1

6.1

3.1

6.1

9.1 12.2

15.2

18.3

0

3.1

6.1

9.1

12.2

15.2

18.3

21.3

24.4

27.4 30.5

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Thickness of the Floridan aquifer, in meters

 0.03 to 87.5

 87.5 to 180

 180 to 238

 238 to 287

 287 to 373

 373 to 500

 500 to 629

Equal potentiometric-surface elevation of the Floridan aquifer. 

 Contour interval, in meters, is variable. Datum is sea level.

Extent of active model cells

Extent of model grid

Springs 

30.5
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–11

to 2 X 10–5 m/d in the study area (Bush and Johnston, 1988; 

Knochenmus and Robinson, 1996).

Water Budget

Estimates of the water budget in the modeled area for the 

year 1987 (a representative year) are provided in Yobbi (2000) 

and are reported here. Recharge estimates for the modeled area 

vary greatly. A net recharge rate of 23.1 cm/yr from precipitation is considered reasonable, although site-specific values 

likely vary from 0 to more than 30 cm/yr because of the karst 

topography. An estimated net discharge rate of 1.05 Mm3/d 

was calculated from the total average annual ground-water 

discharge to 13 major springs in the modeled area. Total base 

flow to rivers from ground water, determined from hydrograph 

separation techniques for 21 sites in the modeled area, was 

1.37 Mm3/d. Discharge to wells estimated from year-2000 

pumping data is approximately 1.8 Mm3/d as discussed in the 

“Model Stresses” section.

Ground-Water Quality

Concentrations of major ions in any aquifer reflect the 

quality of recharge water, lithology and mineralogy of geologic deposits, residence time of water, and proximity to the 

coast and(or) other contaminant sources. The most commonly 

occurring water types in the surficial aquifer system in the 

study area are mixed and calcium-bicarbonate. Precipitation, 

which provides most of the recharge to the surficial aquifer 

system, is generally a sodium-chloride type water; however, 

water quality rapidly evolves to calcium-bicarbonate or mixed 

type water owing to water-rock interaction with the carbonate 

rocks (Berndt and Katz, 1992). Dissolved-solids concentrations are generally low (less than 100 mg/L) (Berndt and Katz, 

1992), pH is normally less than 5, and water entering the 

aquifer through recharge is normally oxic.

The intermediate confining unit overlying the Floridan 

aquifer system contains many minerals including magnesiumrich clay sediments, uranium, pyrite, and phosphatic minerals 

(Katz, 1992). Arsenic, uranium, radon, and radium are present 

as trace elements in the phosphatic and(or) pyrite minerals, 

and these constituents may leach into the Floridan aquifer system when conditions are favorable. The dominant water type 

for the intermediate confining unit is mixed, and the pH and 

dissolved-solids concentration in the intermediate confining 

unit are generally greater than those of water from the surficial 

aquifer system.

Ground water in the Floridan aquifer system has a 

predominantly calcium-bicarbonate to calcium-sulfate, or 

calcium-magnesium-bicarbonate-sulfate chemical signature 

(Katz, 1992), although water-chemistry conditions in the 

Floridan aquifer system can be highly variable because karst 

features can cause variable residence times. Ground-water pH 

of the Floridan aquifer system in the study area is generally 

between 6.0 and 8.0 pH units. Dissolved-solids concentrations 

range from 10 to 30,000 mg/L and average approximately 250 

mg/L depending on the degree of confinement, depth in the 

aquifer, and mixing with seawater. Calcium concentrations 

generally increase with depth in the Floridan aquifer system 

within the study area because aquifer residence times tend 

to increase with depth. The dissolution of gypsum may also 

contribute to high concentrations of calcium and sulfate. Pyrite 

dissolution from the Suwannee Limestone, and possibly the 

overlying Hawthorn Group, may contribute iron and arsenic 

to the Florida aquifer (Thomas Pichler, University of South 

Florida, Tampa, oral commun., 2002). Ground water in discharge areas is commonly mixed or of sodium-chloride type 

indicating mixing with or evolving to seawater (Katz, 1992).

Oxidation-reduction (redox) conditions in the Floridan 

aquifer system were difficult to generalize, but several observations came from analysis of retrospective data. Conditions 

consistent with oxygen reduction generally occurred in ground 

water from shallow sediments and in the Floridan aquifer 

system in areas where sinkhole density is highest and(or) the 

aquifer is unconfined or semiconfined (figs. 5.3, 5.5). Conditions consistent with oxygen reduction in deeper wells were 

observed almost exclusively in waters from large-capacity 

public-supply wells and may be the result of high pumping 

rates oxidizing ground water near the well. Reduced conditions, represented by iron-reducing waters, were more often 

present in proximity to wetlands, discharge areas, and at 

greater aquifer depths (fig. 5.3). Iron and sulfate concentrations are high in waters from shallower wells because of the 

iron- and magnesium-rich clay minerals, pyrite and dolomite 

dissolution from the Hawthorn Group intermediate confining 

unit, and gypsum dissolution in the deeper Floridan aquifer 

system.

Because of the complex karst ground-water flow system 

within the Floridan aquifer system and the various types of 

wells used to evaluate redox conditions (public-supply wells 

with large open intervals compared to monitoring wells with 

short open intervals), delineation of spatial or vertical redox 

zones is not possible with the available water-quality data. The 

ability to delineate redox zones in the Floridan aquifer system 

may be improved by defining a quantifiable link between the 

total area of wetlands and/or number of sinkholes (and other 

karst features) in the contributing areas of wells and the redox 

conditions of the aquifer.
5–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.5. Oxidation-reduction classification, Northern Tampa Bay regional study area, Florida.

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COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Floridan aquifer confinement class

 Confined

 Semiconfined

 Unconfined

Extent of active model cells

Oxidation-reduction classification

 Oxygen reduction

 Iron reduction

 Iron reduction with low sulfate

 Iron reduction with high sulfate

 Mixed
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–13

Ground-Water Flow Simulations

Ground-water flow of the Northern Tampa Bay regional 

study area was simulated by modifying an existing steadystate ground-water flow model, developed in MODFLOW88 

(McDonald and Harbaugh, 1988) of the Central-Northern 

Tampa Bay area (SDI Environmental Services, Inc., 1997). 

The Central-Northern Tampa Bay model was originally 

developed as a tool to evaluate the effects of ground-water 

withdrawal from specific well fields on aquifer and lake water 

levels. The Central-Northern Tampa Bay model was a transient, coupled surface-water/ground-water flow model with a 

simulation period of 1971 through 1993 (SDI Environmental 

Services, Inc., 1997). In the late 1990’s, the ground-water 

component of the Central-Northern Tampa Bay model was 

split from the coupled model, converted to a steady-state 

model, and the hydraulic parameters of the ground-water 

model were optimized by Yobbi (2000).

The optimized steady-state ground-water flow model of 

Yobbi (2000) was updated by this study to reflect withdrawal 

rates for year 2000, rediscretized, converted to MODFLOW2000 (Harbaugh and others, 2000), and recalibrated. The year 

2000 was selected for the steady-state simulations because 

estimated withdrawal rates for agricultural and industrial wells 

already existed (Nick Sepulveda, U.S. Geological Survey, 

Orlando, Florida, written commun., 2002), measured withdrawal rates for public-supply wells are available for year 

2000, and because year-2000 withdrawal rates are considered representative of withdrawal conditions for 1997–2001. 

The steady-state flow assumption is reasonable for the study 

area for 1997–2001 because the Floridan aquifer system has 

high transmissivity values, a large volume of water circulates 

through the system, and pumping rates were relatively stable 

during the time period of study. Other significant changes 

made to the Yobbi (2000) ground-water model for this study 

include:

•	 The surficial aquifer system and Floridan aquifer system were both modeled as convertible from confined to 

unconfined aquifers to prevent surficial aquifer system 

nodes from going dry during steady-state simulations. 

The model modification did not affect the resulting 

heads, recharge rates, or other parameters.

•	 The number of drain cells in layer 2 was reduced to 

represent only those cells with identified springs.

•	 All drain cells in layer 1 were removed because it was 

assumed that the springs emanate from the Floridan 

aquifer system (layer 2).

•	 The number of river cells was reduced to better represent model areas actually containing river channels.

•	 The potentiometric surface of the surficial aquifer system in the north-central portion of the model dropped 

below the bottom of layer 1. The dry cells in layer 

1 were therefore deactivated by this study (fig. 5.6) 

to correct the problem. Dry cells probably occurred 

because the surficial aquifer is very thin or not present 

in the area where the Floridan aquifer system outcrops 

(fig. 5.1).

Initial conditions for starting heads, hydraulic conductivity, base of the surficial aquifer system, transmissivity, leakance, hydraulic parameter zones, watershed boundaries, and 

boundary conditions were derived from the original CentralNorthern Tampa Bay model and Yobbi’s optimized hydraulic 

parameters (SDI Environmental Services, Inc., 1997; Yobbi, 

2000) with those exceptions previously mentioned. Land-surface elevation, thickness of the active freshwater flow system, 

base of the Floridan aquifer system, and recharge estimates 

were derived from Sepulveda (2002).

Modeled Area and Spatial Discretization

The Central-Northern Tampa Bay ground-water flow 

model covers 5,426 km2 in Hillsborough, Pasco, Hernando, 

Pinellas, and Polk Counties of Florida (fig. 5.2). The CentralNorthern Tampa Bay model had 121 columns, 131 rows, and 

2 layers, and cell sizes ranged from about 300 to 1,600 m on a 

side. The Central-Northern Tampa Bay model simulated flow 

in the surficial aquifer system as layer 1 and flow in the Floridan aquifer system as layer 2. The updated Northern Tampa 

Bay regional ground-water flow model has 227 columns, 

234 rows, and 4 model layers; cell sizes range from approximately 200 to 1,600 m on a side. Additional rows and columns 

were added in the middle of the modeled area to improve the 

simulation in areas where multiple large pumping wells or 

other stresses are in close proximity to one another (fig. 5.6). 

In addition, the Floridan aquifer system in the Northern Tampa 

Bay regional model was divided into three layers (layers 2, 3, 

and 4) to resolve weak-sink problems in the particle-tracking 

analysis (see discussion of weak-sink problems in Section 1 

of this Professional Paper). The layer spacing in the Floridan 

aquifer system was computed by dividing the total thickness 

of the active freshwater zone of the Floridan aquifer system 

into thirds.

Boundary Conditions

Model layer 1 lateral boundaries are represented by noflow cells except where the layer 1 boundary coincides with 

the coastline of the Gulf of Mexico and Tampa Bay, where the 

boundary is represented with constant heads (fig. 5.6). The 

surficial aquifer in the central northern portion of the modeled area is very thin if present and created problems with 

the steady-state potentiometric surface of layer 1 dropping 

below the bottom of layer 1, so the layer 1 cells in this area 

are inactive. In layers 2, 3, and 4, the southeastern and most 

of the northern boundary are no-flow boundaries representing 

ground-water flow lines in the Floridan aquifer system. The 
5–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.6. Ground-water flow model grid and boundary conditions, Northern Tampa Bay regional study area, Florida.

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Weeki

Wachee River

Rocky

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Brooker

Creek

Trout

River

River

Pithlachascootee

Anclote

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

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River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

General-head boundary

River cell in layer 2

River cell in layer 1

Drain (spring) in layer 2

Constant head in layer 2

Constant head in layer 1

Pumping in layer 2

Pumping in layer 3

Inactive cells in layer 1

Extent of active model cells

Model grid
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–15

extreme part of the northeastern boundary is represented by 

a general-head boundary in layer 2 (fig. 5.6). The southeastern edge of the study area is represented as a specified-head 

boundary in layers 2, 3, and 4. The coastline is represented as 

a no-flow boundary in layers 2, 3, and 4.

Model Stresses

Hydrologic stresses on the Northern Tampa Bay regional 

ground-water flow system include recharge from precipitation 

and surface water and discharge to wells, rivers, and springs.

Recharge

Recharge is defined as the amount of water that infiltrates and percolates through the unsaturated zone to reach the 

aquifer, in this case the surficial aquifer system (layer 1). In 

the Northern Tampa Bay regional model, the complexities of 

rainfall, runoff, infiltration, percolation, and evapotranspiration 

were highly simplified. The MODFLOW Recharge package 

was used to assign initial values of recharge to the modeled 

area using watershed by watershed recharge estimates from 

Aucott (1988). Final recharge values were derived from model 

calibration as discussed in the “Model Calibration” section.

Pumping

Total pumping withdrawal from the Floridan aquifer 

system in the modeled area for all public water supply, agricultural, and industrial wells was 1.8 Mm3

/d in 2000. Approximately 1.34 Mm3

/d were withdrawn for public-supply wells; 

the remaining 0.23 Mm3/d was the estimated withdrawal for 

agricultural and industrial purposes. Withdrawal rates for agricultural and industrial wells for 2000 were compiled and estimated by Nicasio Sepulveda of the U.S. Geological Survey in 

Orlando, Florida, from permit data from the Southwest Florida 

Water Management District—measured withdrawal rates 

were not available. Withdrawal rates for public-supply wells 

for 2000 were computed from average monthly withdrawal 

rates obtained from the Southwest Florida Water Management 

District. Domestic-well withdrawals of approximately 45,000 

m3/d are insignificant compared to public-supply withdrawals and were assumed offset by septic-tank-effluent recharge. 

Withdrawals are spaced throughout the modeled area based on 

actual well locations, and the largest public-supply withdrawals are concentrated in the southeastern part of the modeled 

area (fig. 5.6). The MODFLOW Well package was used to 

simulate ground-water pumping.

Rivers

The MODFLOW River package was used to simulate 

river/aquifer interaction in the modeled area. Major rivers 

included in the Northern Tampa Bay regional model were the 

Hillsborough, Withlacoochee, Anclote, and Pithlachascotee 

Rivers, and their tributaries. Other surface-water features simulated as rivers include Brooker, Rocky, Trout, and Cypress 

Creeks. River stage, conductance, bottom elevations, and layer 

of interaction were obtained from the optimized ground-water 

flow model (Yobbi, 2000). Most river cells were located in 

layer 1 (83 percent), but stretches of the Hillsborough and 

Withlacoochee Rivers and a few small rivers along the Gulf 

of Mexico (Weeki Wachee) were simulated in layer 2 (17 percent). Discharge to streams from the ground-water system was 

calculated for calibration purposes, but riverbed conductances 

were not altered for this study to improve model fit. Lakes 

and wetlands were assumed to be part of the surficial aquifer 

system and were not explicitly simulated.

Drains

Sixty-nine springs were simulated in layer 2 to represent discharge from the Floridan aquifer system using the 

MODFLOW Drain package. Spring stage, drain conductance, 

and bottom elevations were taken from the optimized model 

(Yobbi, 2000). Springs in the study emanate from the Floridan 

aquifer system (not the surficial aquifer system), so drains in 

the Northern Tampa Bay regional model were simulated only 

in layer 2. In the optimized model (Yobbi, 2000), drain cells in 

layer 1 were used to simulate wetlands. The layer 1 drains of 

Yobbi (2000) were eliminated from the current regional model 

because they were negatively affecting the models ability to 

determine flowpaths.

Aquifer Properties

Hydraulic conductivities (K) used for model layer 1 were 

defined using five different zones and values ranging from 0.3 

to 5 m/d (fig. 5.7) (Yobbi, 2000). A hydraulic conductivity of 

3.0 m/d or less was used in most of the upland areas of the 

model (3,500 km2). Hydraulic conductivity was greatest (4.5 

m/d) along the coast and river/wetland areas (1,600 km2).

Vertical leakance values used to simulate leakage 

between the surficial aquifer system and the Floridan aquifer 

system (through the intermediate confining unit) ranged from 

1 X 10–6 to 3.5 X 10–1 m/d/m (fig. 5.8) and were based on aquifer-test data reported in Knochenmus and Robinson (1996) 

and other references (SDI Environmental Services, Inc., 1997). 

Smaller values were assigned in areas where the intermediate 

confining unit is thick and(or) not breached and the Floridan 

aquifer system is confined. Vertical leakance values of 0.35 

m/d/m were assigned in areas where the Floridan aquifer system is considered unconfined. Using leakance values greater 

than 0.35 m/d/m resulted in equal model-computed head values for layers 1 and 2 in the optimized model (Yobbi, 2000).

Transmissivity of the Floridan aquifer system was defined 

by 23 zones with transmissivity values ranging from 60 to 

500,000 m2/d for each (fig. 5.9) (Yobbi, 2000). Transmissivity 

values for the Floridan aquifer system were derived from aqui-
5–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.7. Distribution of hydraulic conductivity for model layer 1, Northern Tampa Bay regional study area, Florida.

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SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

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X I C

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Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

0.0305

0.305

EXPLANATION

Hydraulic conductivity in layer 1, in meters per day

 0.0305

 0.305

 0.914

 1.37

 3.05

 4.57

Extent of active model cells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–17

Figure 5.8. Distribution of vertical leakance values assigned between model layers 1 and 2, Northern Tampa Bay regional 

study area, Florida.

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COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

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X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Vertical leakance values, in meters per day per meter

 Less than 0.0002

 >0.0002 to 0.0007

 >0.0007 to 0.0015

 >0.0015 to 0.004

 >0.004 to 0.006

 >0.006 to 0.01

 >0.01 to 0.35

Extent of active model cells
5–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.9. Distribution of transmissivity values assigned to the Floridan aquifer (model layers 2, 3, and 4), Northern Tampa 

Bay regional study area, Florida.

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COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Total transmissivity for layers 2, 3, and 4, in square meters per day

 61.3

 819

 1,225

 1,886

 2,295

 2,386

 2,945

 3,710

 5,440

 7,085

 8,451

 12,333

 19,735

 19,872

 25,205

 25,753

 31,726

 37,459

 41,054

 52,397

 56,532

 133,632

 494,709

Extent of active model cells

61.3

819

1,225

1,886

2,295

2,386

2,945

3,710

5,440

7,085

8,451 12,333

19,735

19,872

25,205

25,753

31,726

37,459

41,054

52,397

56,532

494,709 133,632
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–19

fer tests and published values (SDI Environmental Services, 

Inc., 1997), and the transmissivity distribution for the Northern 

Tampa Bay regional model (layers 2, 3, and 4) was the same 

as that based on parameter-estimation results of Yobbi (2000). 

Because the total thickness of the Floridan aquifer system was 

divided into equal thirds when layers 3 and 4 were added to 

the model, the total transmissivity shown in figure 5.9 was also 

divided into thirds and an identical transmissivity distribution 

was assigned to each of layers 2, 3, and 4. Transmissivity values were smallest in areas where the Floridan aquifer system 

is confined or semiconfined, and transmissivity values were 

largest in the northern sections of the modeled area, coastal 

areas, and in the Withlacoochee River Basin (Yobbi, 2000).

Model Calibration and Sensitivity

The Northern Tampa Bay regional model was recalibrated to year-2000 conditions using a trial-and-error approach 

by adjusting recharge and comparing model-computed (simulated) hydraulic head and ground-water discharge to measured 

hydraulic head and streamflow and spring-flow data. The 

optimized hydraulic conductivity, transmissivity, and vertical 

leakance distributions of Yobbi (2000) were not modified during model calibration.

Initial recharge values were adjusted during model 

calibration until the difference between model-computed and 

measured hydraulic heads and ground-water discharge were 

minimized. Calibrated recharge values in the modeled area 

ranged between 0 and 63.5 cm/yr (fig. 5.10), and the average 

recharge rate for the study area (23.1 cm/yr) was kept less than 

the Yobbi (2000) value of 33 cm/yr. Recharge is greatest in 

areas where the Floridan aquifer system is unconfined or semiconfined. Zero recharge was specified in discharge areas such 

as the Hillsborough River and the coastal areas (fig. 5.10).

Model-computed hydraulic head was compared to 

median head values for the year 2000 from 187 monitoring 

wells in the Floridan aquifer system and 210 wells in the surficial aquifer system. Model-computed discharge was compared 

to the increase in base flow to the Hillsborough River between 

gages on the Hillsbourough River near Zephyrhills, Florida, 

(station 02301990) and the Hillsborough River above Crystal 

Springs, near Zephyrhills, Florida, (station 02303000) (Coffin 

and Fletcher, 2001). The calibration goal was to reduce the 

difference between simulated and measured head (residual), 

especially in the Floridan aquifer system.

The overall goodness of fit of the model to the observation data was evaluated using summary measures and graphical analyses. The root-mean-squared error (RMSE), the range, 

the standard deviation, and the standard-mean error of the 

residuals (SME), were used to evaluate the model calibration. 

The RMSE is a measure of the variance of the residuals and 

was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of wells used in the computation. If the ratio of the RMSE 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).

The SME was calculated as:

where σ(hmeas – hsim) is the standard deviation of the residuals.

Model-Computed Hydraulic Heads

The spatial distribution of model-computed hydraulic 

heads for model layers 1 and 2 (figs. 5.11A and 5.11B) present 

a reasonable representation of potentiometric surfaces for the 

surficial and Floridan aquifer systems, respectively. Modelcomputed hydraulic head maps for both layers indicate highest 

heads in the northern and eastern parts of the modeled area 

and the lowest heads in the western and southwestern parts 

of the modeled area along the Gulf of Mexico. The maps of 

model-computed hydraulic head indicate ground-water flow is 

from the northern and eastern parts of the modeled area toward 

the coastal lowlands consistent with land-surface topography 

and previous maps of hydraulic head (Yobbi, 2000).

A simple method of assessing overall model fit is to 

plot the model-computed hydraulic head values against the 

measured observations. For a perfect fit, all points should 

fall on the 1:1 diagonal line, and a reasonable model fit is 

indicated in figures 5.12A and 5.12B. The spatial distribution 

of the head residuals is shown in figure 5.13 and can be used 

to understand the geographic distribution of head residuals. 

Head residual in the surficial aquifer system range from -8.9 

to 19.1 m with a mean of 0.6 m (median of 0.3 m) (figs. 5.13 

and 5.14A). Head residuals in the surficial aquifer system are 

greatest in the southern parts of the modeled area in locations 

where there are few water-level measurements and where head 

values are highest (figs. 5.11A and 5.13). Head residuals in the 

Floridan aquifer system range from –6.6 to 7.9 m and average 

0.2 m (median also of 0.2 m) (figs. 5.13 and 5.14B). Floridan 

aquifer system head residuals are smallest in the northern 

coastal lowlands and center of the model area and largest in 

northern Pinellas County and southeastern parts of the modeled area (fig. 5.13). The average residual for the entire model 

is 0.28 m. The RMSE for the entire model is 2.63 m, which is 
5–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.10. Ground-water flow model calibrated recharge rates, Northern Tampa Bay regional study area, Florida.

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COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Recharge rate, in centimeters per year

 0

 0.0 to 12.7

 12.7 to 25.4

 25.4 to 38.1

 38.1 to 63.5

Extent of active model cells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–21

Figure 5.11A. Distribution of model-computed hydraulic heads for the surficial aquifer system (model layer 1), Northern 

Tampa Bay regional study area, Florida.

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4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Model-computed head elevation, in meters above sea level

 –1.94 to 0

 0 to 5

 5 to 10

 10 to 15

 15 to 20

Surficial aquifer inactive

Extent of active model cells

Monitoring well

 20 to 25

 25 to 30

 30 to 85
5–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.11B. Distribution of model-computed hydraulic heads for the uppermost Floridan aquifer system (model layer 2), 

Northern Tampa Bay regional study area, Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Model-computed head elevation, in meters above sea level

 –4.45 to –1

 –1 to 0

 0 to 5

 5 to 10

 10 to 15

Extent of active model cells

 15 to 20 Monitoring well

 20 to 25

 25 to 30

 30 to 50
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–23

Figure 5.12A. Relation between model-computed and measured 

hydraulic head for model layer 1, Northern Tampa Bay regional 

study area, Florida.

Figure 5.12B. Relation between model-computed and measured 

hydraulic head for model layer 2, Northern Tampa Bay Regional 

study area, Florida.

1:1 line

–5

0

5

10

15

20

25

30

35

Model-computed head elevation, in meters

Measured head elevation, in meters

–5 0 5 10 15 20 25 30 35

1:1 line

–10

0

10

20

30

40

Model-computed head elevation, in meters

Measured head elevation, in meters

–10 0 10 20 30 40 50

approximately 6 percent of the range of head observations for 

the model (41.3 m) and also indicates a reasonable model fit. 

The standard deviation of the residuals is 2.62 m, and the SME 

is 0.13 m. Ultimately, more water-level measurements and 

more accurate recharge estimates could improve the model fit 

for the surficial aquifer system. Of all residuals in both the surficial and Floridan aquifer systems, ninety percent are between 

–1.6 and 1.6 m (figs. 5.14A and 5.14B).

Model-Computed Discharge and Recharge

Model-computed base-flow and spring discharge were 

compared to measured discharge as another model-calibration 

criterion. The segment of the Hillsborough River used to calibrate the model is located between gaging stations 02301990 

and 02303000. This segment was chosen because there are 

no major flow-altering structures between the two gages. The 

estimated base-flow increase (based on measured values) in 

the reach is 121,000 m3/d; the model-computed discharge to 

the river in the reach was 112,000 m3/d. The difference of 

9,000 m3/d is considered a good match between simulated and 

measured discharge along this stream segment. The difference between simulated discharge and measured discharge to 

springs was calculated for several important springs including the Weeki Wachee Spring as a further check on model 

calibration. For Weeki Wachee Spring, the measured average 

discharge is approximately 450,000 m3/d (Coffin and Fletcher, 

2001); however, the model-computed steady-state discharge is 

122,000 m3/d. Model-computed discharge from the aquifer to 

this and other springs is lower than measured values indicating 

the model does a poor job of simulating discharge to springs. 

This regional-scale simulation likely does not include sufficient localized karst features to adequately simulate local 

springs.

Recharge is the most sensitive parameter in this model 

according to Yobbi (2000). Simulated hydraulic heads in the 

surficial aquifer system and Floridan aquifer system can be 

readily manipulated by adding or subtracting recharge from an 

area. A complete description of hydraulic-parameter sensitivities is provided by Yobbi (2000).

Model-Computed Water Budget

The Northern Tampa Bay regional model simulated water 

budget for the year 2000 is shown in table 5.3. Recharge from 

precipitation composed most of the inflow of water to the 

modeled area at 3.44 Mm3/d (55.4 percent of model inflow). 

Inflow to the modeled area through constant head cells along 

the southeastern border composed the second highest amount 

of inflow to the modeled area (2.17 Mm3/d or 35.0 percent 

of model inflow). River inflow to the aquifer was somewhat 

balanced by river outflow (0.59 Mm3/d inflow compared to 

0.83 Mm3/d outflow, respectively) (table 5.3; fig. 5.15). Inflow 

to the aquifer from the rivers occurred mainly in the upper 

reaches of the Hillsborough and Withlacoochee Rivers and 

their tributaries and along lower sections of the Hillsborough 

River. Outflow from the aquifer to rivers was simulated in 

smaller rivers near the Gulf of Mexico and the mid section 

of the Hillsborough River among others. Other simulated 

discharge included outflow at constant-head boundaries 

along the Gulf of Mexico and Tampa Bay and at the northern general-head boundary to the Withlacoochee River (2.36 

Mm3/d or 38.0 percent of model outflow), wells (1.81 Mm3/d 

or 29.1 percent of model outflow—84 percent of which was to 

public-supply wells), and springs (0.90 Mm3/d or 14.6 percent 

of model outflow). There was zero percent error between 

model-calculated inflows and outflows for this steady-state 

simulation.
5–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.13. Distribution of head residuals for model layers 1 and 2, Northern Tampa Bay regional study area, Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Head residuals in layer 1

 –8.9 to –2.00

 –2.00 to 0.00

 0.00 to 2.00

 2.00 to 10.00

 10.00 to 19.1

Head residuals in layer 2

 –6.6 to –2.00

 –2.00 to 0.00

 0.00 to 2.00

 2.00 to 5.00

 5.00 to 7.9

Extent of active model cells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–25

Figure 5.14A. Probability distribution of head residuals for model 

layer 1, Northern Tampa Bay regional study area, Florida.

Figure 5.14B. Probability distribution of head residuals for model 

layer 2, Northern Tampa Bay regional study area, Florida.

0

10

20

30

40

50

60

70

80

90

100

Percent of residual values

Residual values, in meters

–20 –15 –10 –5 0 5 10 15 20

0

10

20

30

40

50

60

70

80

90

100

Percent of residual values

Residual values, in meters

–8 –6 –4 –2 0 2 4 6 8

Table 5.3. Model-computed water budget for year 2000, 

Northern Tampa Bay regional study area, Florida.

[m3/d, cubic meters per day]

Water-budget component Flow

(m3/d)

Percentage of 

inflow or outflow*

Model inflow

Precipitation recharge 3,440,000 55.4

Lateral ground-water inflow 

from constant-head wells

2,173,000 35.0

Rivers 591,000 9.5

TOTAL INFLOW 6,207,000 100

Model outflow

To the Gulf of Mexico, 

Tampa Bay and the 

central-northern portion of 

modeled area

2,360,000 38.0

Wells 1,810,000 29.1

Rivers 830,000 13.4

Springs 904,000 14.6

TOTAL OUTFLOW 6,207,000 100

*

Total may not equal 100 percent because of rounding.
5–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.15. Model-computed ground-water inflows and outflows, Northern Tampa Bay regional study area, Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Pumping in layers 2, 3, and/or 4

Constant head, layer 2

 Outflow

 Inflow

Constant head, layer 1

 Outflow

 Inflow

Drains, layer 2

River, layer 1

 Outflow

 Inflow

River, layer 2

 Outflow

 Inflow

General-head boundary

Extent of active model cells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–27

Simulation of Areas Contributing Recharge to 

Wells

The calibrated steady-state ground-water flow model was 

used to estimate areas contributing recharge and zones of contribution for approximately 104 public-supply wells from the 

four quartiles of pumping rates using the MODPATH (Pollock, 

1994) particle-tracking post processor and methods outlined 

in Section 1 of this Professional Paper. The model-computed 

areas contributing recharge represent advective ground-water 

flow and do not account for mechanical dispersion. Advection-dispersion transport simulations would likely yield larger 

areas contributing recharge than advective particle-tracking 

simulations because the effects of dispersion caused by aquifer 

heterogeneity would be included.

Along with output from the ground-water flow model, 

the MODPATH simulation requires effective porosity values 

to calculate ground-water flow velocities. For the Northern 

Tampa Bay regional model, porosity values were assumed 

uniform within each layer based on typical regional values. 

A porosity of 0.25 was used for the surficial aquifer system (model layer 1), and a porosity of 0.15 was used for the 

Floridan aquifer system (model layers 2, 3, and 4). Because 

of the karst nature of ground-water flow in the study area, the 

porosity values used for this regional simulation would not be 

applicable to local karst conditions.

Results of the MODPATH simulations used to delineate 

areas contributing recharge for selected wells are shown on 

figure 5.16. In general, areas contributing recharge extend 

upgradient (fig. 5.4) toward the northeast boundary of the 

modeled area. Summary statistics were computed for the 

particle-tracking results for wells from all quartiles of pumping rates. Areas contributing recharge ranged from near 0 

to 1.25 km2, and the average area contributing recharge was 

approximately 0.26 km2. Minimum computed traveltimes for 

all wells ranged from 0.7 to 233 years and averaged 19 years. 

Maximum computed traveltimes ranged from 32 to 1,875 

years and averaged 600 years. On the basis of average traveltimes of particles reaching the wells, about 3 percent of the 

flow to a public-supply well was less than 10 years old, about 

36 percent of the flow to a public-supply well was less than 50 

years old, and about 80 percent of the flow to a public-supply 

well was less than 200 years old. Simulated traveltimes are 

probably much longer than actual traveltimes in the aquifer 

because the regional ground-water flow model does not accurately represent flow through local karst dissolution features.

Limitations and Appropriate Use of the Model

The ground-water flow model for the Northern Tampa 

Bay regional study area was designed to delineate areas 

contributing recharge to public-supply wells, to help guide 

data collection, and to support future local modeling efforts. 

Sources of error in the model may include the steady-state 

flow assumption and errors in the conceptual model of the 

system, hydraulic properties, and boundary conditions.

The steady-state flow assumption is reasonable for the 

study area for 1997–2001 because the Floridan aquifer system 

has high transmissivity values, a large volume of water circulate through the system, and pumping rates were relatively 

stable during the time period of study. However, errors related 

to the steady-state assumption can be substantial, and further 

calibration for transient conditions may be needed to accurately represent temporal changes in the system.

For karst terrains, where a substantial percentage of flow 

occurs through a series of discrete openings, conduits, and 

fractures, a porous-media approach at a regional scale cannot 

accurately predict zones of contribution, areas contributing 

recharge, and traveltimes to public-supply wells. Secondary 

porosity created by karst dissolution features contributes to 

uncertainty in values of hydraulic conductivity, which can 

vary by up to five orders of magnitude (Langevin, 2003; 

Bush and Johnston, 1988), and porosity, which also can vary 

substantially. Knochenmus and Robinson (1996) used very 

low effective porosities in order to achieve realistic traveltimes 

in the Floridan aquifer system and Kuniansky and others 

(2001) found that an effective porosity of 1 to 3 percent was 

needed for the karst Edwards aquifer system in Texas to match 

estimated traveltimes derived from geochemical mixing models. Changes to input porosity values will change computed 

traveltimes from recharge to discharge areas in direct proportion to changes of effective porosity because there is an inverse 

linear relation between ground-water flow velocity and effective porosity and a direct linear relation between traveltime 

and effective porosity. For example, a one-percent decrease in 

porosity will result in a one-percent increase in velocity and a 

one-percent decrease in particle traveltime. A detailed sensitivity analysis of porosity distributions was beyond the scope of 

this regional study.

The ground-water flow model for the Northern Tampa 

Bay regional study area represents a first approximation of 

ground-water conditions and the areas contributing recharge 

to public-supply wells in the modeled area. The model is suitable for evaluating regional water budgets and ground-water 

flow paths in the study area for the time period of interest but 

may not be suitable for long-term predictive simulations. To 

improve contributing area delineation, the model could incorporate karst features, possibly using a probabilistic (Monte 

Carlo) simulation approach over a much smaller area. Additional hydraulic head observations in the surficial aquifer system in the southern part of the modeled area would improve 

the calibration of the existing model as would additional 

measurements of recharge and discharge if possible. This 

regional model does provide a useful tool to evaluate aquifer 

vulnerability at a regional scale, to facilitate comparisons of 

ground-water traveltime between regional aquifer systems, and 

to guide future detailed investigations in the study area.
5–28 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 5.16. Model-computed areas contributing recharge for selected public-supply wells, Northern Tampa Bay regional 

study area, Florida.

275

75

41

699

75

4

98

301

50

60

589

301 98

92

HERNANDO COUNTY

PASCO COUNTY

SUMPTER COUNTY

SUMPTER COUNTY

LAKE COUNTY

LAKE COUNTY

POLK COUNTY

POLK COUNTY

HILLSBOROUGH COUNTY

HILLSBOROUGH COUNTY

PASCO COUNTY

HILLSBOROUGH COUNTY

PINELLAS COUNTY

B R O O K S V I L L E

R I D G E

W E S T E R N

H I G H L A N D S

COASTAL

SWAMPS

Weeki

Wachee River

Rocky

Creek

Brooker

Creek

Trout

River

River

Pithlachascootee

Creek

Withlacoochee

River

Cypress

River

Hillsborough

G

U

L

F

O

F

M

E

X I C

O

T A M P A B A Y

Anclote River

Weeki

Wachee

Springs

Zyphyrhills

Crystal

Springs

Brooksville

Clearwater TAMPA

SAINT

PETERSBURG

20° 00'

28° 15'

28° 30'

82° 45' 82° 30' 82° 15' 82° 00'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' and 45° 30', central meridian 83°, North

American Datum of 1983

0 10 20 30 40 KILOMETERS

0 10 20 MILES

EXPLANATION

Urban

Areas contributing recharge for seleted wells

Pathlines outlining zones of contribution to public-supply wells

Extent of active model cells

Sampled public-supply wells

Other public-supply wells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Northern Tampa Bay Regional Study Area, Florida 5–29

References Cited

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Aucott, W.R., 1988, Areal variation in recharge to and discharge from the Floridan Aquifer System in Florida: U.S. 

Geological Survey Water-Resources Investigations Report 

88–4057, 1 sheet.

Berndt, M.P., and Katz, B.G., 1992, Hydrochemistry of the 

surficial and intermediate aquifer systems in Florida: U.S. 

Geological Survey Water-Resources Investigations Report 

91–4186, 24 p.

Bush, P.W., and Johnston, R.H., 1988, Ground-water hydraulics, regional flow, and ground-water development of the 

Floridan Aquifer System in Florida and in parts of Georgia, 

South Carolina, and Alabama: U.S. Geological Survey Professional Paper 1403–C, 80 p.

Coffin, J.E. and Fletcher, W.L, 2001, Water Resources Data 

Florida Water Year 2000, Vol. 3A. Southwest Florida 

Surface Water: U.S. Geological Survey Water-Data Report 

FL–00–3A, 359 p.

Farnsworth, R.K., Thompson, E.S., and Peck, E.L., 1982, 

Evaporation atlas for the contiguous 48 United States: Asheville, N.C., National Oceanic and Atmospheric Administration Technical Report NWS 33, 26 p., 4 sheets.

Harbaugh, A.W., Banta, E.R., Hill, M.C., McDonald, M.G., 

2000, MODFLOW-2000, The U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. Geological Survey Open-File Report 00–92, 121 p., accessed 

Feb. 6, 2007, at http://water.usgs.gov/nrp/gwsoftware/

modflow2000/modflow2000.html

Hitt, K.J., 2004, Refining 1970’s land-use data with 1990 

population data to indicate new residential development: 

U.S. Geological Survey Water-Resources Investigations 

Report 94–4250, 21 p.

HydroGeoLogic, Inc., 1997, Development of a computer 

model of the regional groundwater flow system in Hernando County Water Resources Assessment Project, Phase 

I—Data compilation and analysis: Brooksville, report on 

file at the Southwest Florida Water Management District, 

variously paged.

Katz, B.G., 1992, Hydrochemistry of the upper Floridan 

Aquifer System, Florida: U.S. Geological Survey WaterResources Investigations Report 91–4196, 37 p., 10 pls.

Knochenmus, L.A., and Robinson, J.L., 1996, Descriptions 

of anisotropy and heterogeneity and their effect on groundwater flow and areas of contribution to public-supply wells 

in a karst carbonate aquifer system: U.S. Geological Survey 

Water-Supply Paper 2475, 43 p.

Krause, R.E., and Randolph, R.B., 1989, Hydrology of the 

Floridan Aquifer System in southeast Georgia and adjacent 

parts of Florida and South Carolina: U.S. Geological Survey 

Professional Paper 1403–D, 65 p.

Kuniansky, E.L., Fahlquist, Lynne, and Ardis, A.F., 2001, 

Travel times along selected flow paths of the Edwards 

Aquifer, Central Texas in Kuniansky, E.L. ed., 2001, U.S. 

Geological Survey Karst Interest Group Proceedings, St. 

Petersburg, Florida, February 13–16, 2001: U.S. Geological 

Survey Water Resources Investigations Report 01–4011, 

p. 69–77, accessed Feb. 6, 2007, at http://water.usgs.gov/

ogw/karst/kigconference/proceedings.htm.

Langevin, C.D., 1998, Stochastic methods for evaluating the 

potential for wetland rehydration in covered-karst terrains: 

Tampa University of South Florida dissertation, 133 p.

Langevin, C.D., 2003, Stochastic ground water flow simulation with a fracture zone continuum model: Ground Water, 

v. 41, no. 5, p. 587–601.

Marella, R.L., and Berndt, M.P., 2005, Water withdrawals and 

trends from the Floridan aquifer system in the Southeastern 

United States, 1950–2000: U.S. Geological Survey Circular 

1278, 20 p.

McDonald, M.G., and Harbaugh, A. W., 1988, A modular 

three-dimensional finite-difference ground-water flow 

model: Techniques of Water-Resources Investigations of 

the U.S. Geological Survey, book 6, chap. A1, [variously 

paginated].

Metz, P.A., and Sacks, L.A., 2002, Comparison of the hydrogeology and water quality of a ground-water augmented 

lake with two nonaugmented lakes in northwest Hillsborough County, Florida: U.S. Geological Survey Water-Resources Investigations Report 02–4032, 74 p.

Miller, J.A., 1986, Hydrogeologic framework of the Floridan 

Aquifer System in Florida and parts of Georgia, South 

Carolina, and Alabama: U.S. Geological Survey Professional Paper 1403–B, 91 p.
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Pollock, D.W., 1994, User’s guide for MODPATH/MODPATH-PLOT, Version 3—A particle tracking post-processing package for MODFLOW, the U.S. Geological Survey 

finite-difference ground-water flow model: U.S. Geological 

Survey Open-File Report 94–464, accessed Feb. 6, 2007 

at http://water.usgs.gov/nrp/gwsoftware/modpath41/modpath41.html

Ryder, P.D., 1985, Hydrology of the Floridan Aquifer System 

in West Central Florida: U.S. Geological Survey Professional Paper 1403–F, 63 p.

SDI Environmental Services, Inc., 1997, Water resources 

evaluation and integrated hydrologic model of the northern 

Tampa Bay region: Consultant’s report on file at Tampa Bay 

Water, Clearwater, Florida., 146 p.

Sepulveda, Nicasio, 2002, Simulation of ground-water flow in 

the intermediate and Florida aquifer systemss in Peninsular 

Florida: U.S. Geological Survey Water-Resources Investigations Report 02–4009, 130 p., accessed Feb. 6, 2007, at 

http://pubs.er.usgs.gov/usgspubs/wri/wri024009

Soil Conservation Service, 1976, General soil map, Hernando 

County, Florida: Soil Conservation Service, 1 sheet.

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County, Florida: Soil Conservation Service, 1 sheet.

Soil Conservation Service, 1989, General soil map, Hillsborough County, Florida: Soil Conservation Service, 1 sheet.

Southeastern Geological Society, 1986, Hydrogeological units 

of Florida: Tallahassee, Florida Bureau of Geology Special 

Publication 28, 9 p.

Sprinkle, C.L., 1989, Geochemistry of the Floridan Aquifer 

System in Florida and in parts of Georgia, South Carolina, 

and Alabama: U.S. Geological Survey Professional Paper 

1403–I, 105 p.

Tibbals, C.H., Anderson, W., and Laughlin, C.P., 1980, 

Ground-water hydrology of the Dade City area, Pasco 

County, Florida, with emphasis on the hydrologic effects 

of pumping from the FAS: U.S. Geological Survey WaterResources Investigations 80–33, 64 p.

Tibbals, C.H., and Grubb, H.F., 1982, Aquifer test results, 

Green Swamp area, Florida: U.S. Geological Survey WaterResources Investigations Report 82–35, 29 p.

White, W.A., 1970, The geomorphology of the Florida Peninsula: Tallahassee, Florida Bureau of Geology Bulletin 51, 

164 p.

Yobbi, D.K., 2000, Application of nonlinear least-squares 

regression to ground-water flow modeling, west-central 

Florida: U.S. Geological Survey Water-Resources Investigations 00–4094, 58 p., accessed Feb. 6, 2007, at http://pubs.

er.usgs.gov/usgspubs/wri/wri004094.
Hydrogeologic Setting and Ground-Water 

Flow Simulations of the Pomperaug River 

Basin Regional Study Area, Connecticut

By Forest P. Lyford, Carl S. Carlson, Craig J. Brown, and J. Jeffrey Starn

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 6 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
Suggested citation:

Lyford, F.P., Carlson, C.S., Brown, C.J., and Starn, J.J., 2007, Hydrogeologic setting and ground-water flow simulation 

of the Pomperaug River Basin Regional Study Area, Connecticut, section 6 of Paschke, S.S., ed., Hydrogeologic settings and ground-water flow simulations for regional studies of the transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 2001: Reston, Va., U.S. Geological Survey Professional Paper 1737–A, 

pp. 6–1 – 6–26.

U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

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reproduce any copyrighted materials contained within this report.
iii

Contents

Abstract...................................................................................................................................................... 6–1

Introduction................................................................................................................................................ 6–1

Purpose and Scope ......................................................................................................................... 6–1

Study Area Description................................................................................................................... 6–1

Topography and Hydrography .............................................................................................. 6–3

Land Use................................................................................................................................... 6–3

Water Use ................................................................................................................................ 6–3

Conceptual Understanding of the Ground-Water System................................................................. 6–8

Geologic Units and Hydraulic Properties .................................................................................... 6–8

Bedrock .................................................................................................................................... 6–8

Surficial Materials .................................................................................................................. 6–9

Ground-Water Occurrence and Flow......................................................................................... 6–11

Water Budget ................................................................................................................................. 6–11

Ground-Water Quality ................................................................................................................... 6–13

Ground-Water Flow Simulations .......................................................................................................... 6–14

Modeled Area and Spatial Discretization.................................................................................. 6–14

Boundary Conditions and Model Stresses................................................................................ 6–14

Aquifer Hydraulic Properties ....................................................................................................... 6–18

Model Calibration........................................................................................................................... 6–18

Model-Computed Hydraulic Heads ................................................................................... 6–20

Model-Computed Water Budget........................................................................................ 6–20

Simulation of Areas Contributing Recharge to Public-Supply Wells .................................... 6–22

Model Limitations and Uncertainties ......................................................................................... 6–22

References Cited..................................................................................................................................... 6–24

Figures

Maps showing:

6.1. Location of the Pomperaug River Basin regional study area within 

the glacial aquifer system.......................................................................................6–2

6.2. Topography, hydrologic features, and locations of public-supply wells, 

Pomperaug River Basin regional study area, Connecticut. .............................6–7

6.3. Generalized hydrogeologic section showing conceptual ground-water flow 

patterns, representative hydraulic properties, and recharge rates, 

Pomperaug River Basin regional study area, Connecticut.......................................... 6–8

Maps showing:

6.4. Bedrock and surficial geologic units, Pomperaug River Basin 

regional study area, Connecticut ........................................................................6–10

6.5. Wells sampled, oxidation-reduction classification zones, and 

directions of ground-water flow, Pomperaug River Basin 

regional study area, Connecticut........................................................................6–12
iv

6.6. Ground-water flow model grid and simulated streams and wells, 

Pomperaug River Basin regional study area, Connecticut. ...........................6–16

6.7. Ground-water recharge zones, Pomperaug River Basin 

regional study area, Connecticut........................................................................6–17

6.8. Hydraulic-conductivity and porosity zones for model layer 1, 

Pomperaug River Basin regional study area, Connecticut. ...........................6–19

6.9. Graph showing relation between model-computed and measured 

hydraulic head, Pomperaug River Basin regional study area, Connecticut........... 6–20

Maps showing:

6.10. Observation points and head residuals, Pomperaug River Basin 

regional study area, Connecticut. .......................................................................6–21

6.11. Model-computed flow paths, areas contributing recharge to 

public-supply wells, and gaining and losing stream reaches, 

Pomperaug River Basin regional study area, Connecticut.............................6–23

Tables

6.1. Summary of hydrogeologic and ground-water quality characteristics 

for the glacial aquifer system and the Pomperaug River Basin 

regional study area, Connecticut..................................................................................... 6–4

6.2. Public-supply wells and pumping rates, Pomperaug River Basin 

regional study area, Connecticut..................................................................................... 6–6

6.3. Summary of aquifer-system and model characteristics, 

Pomperaug River Basin regional study area, Connecticut........................................ 6–15

6.4. Model-computed water budget for 1997–2001 average conditions, 

Pomperaug River Basin regional study area, Connecticut........................................ 6–20
Hydrogeologic Setting and Ground-Water Flow 

Simulations of the Pomperaug River Basin Regional

Study Area, Connecticut

By Forest P. Lyford, Carl S. Carlson, Craig J. Brown, and J. Jeffrey Starn

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated for the glacially derived 

valley-fill aquifer in the Pomperaug River Basin, Connecticut, 

as part of the U.S. Geological Survey National Water-Quality 

Assessment Program. The glacial valley-fill aquifer in the 

Pomperaug River Basin regional study area is representative 

of the glacial aquifer system in the Northeastern United States, 

is used extensively for public water supply, and is susceptible 

and vulnerable to contamination. A two-layer, steady-state 

ground-water flow model of the study area was developed and 

calibrated to average conditions for the period from 1997 to 

2001. The calibrated model and advective particle-tracking 

simulations were used to compute areas contributing recharge 

and traveltimes from recharge areas for selected public-supply 

wells. Model results indicate areal recharge provides approximately 87 percent of the ground-water inflow and streams 

provide approximately 13 percent of ground-water inflow. 

Ground-water discharge from the model area is to streams (96 

percent) and wells (4 percent). Particle-tracking results indicate traveltimes from recharge areas to wells range from less 

than 1 year to more than 275 years, the median traveltime to 

wells range from 0.2 to 25 years. Approximately 73 percent of 

the traveltimes are less than 10 years indicating water quality 

in the glacial valley-fill aquifer is susceptible to the effects of 

overlying land use.

Introduction

The Pomperaug River Basin regional study area for the 

transport of anthropogenic and natural contaminants to publicsupply wells (TANC) study is located in the northeast glacial 

aquifer system (Warner and Arnold, 2005) within the Connecticut, Housatonic, and Thames River Basins study unit of the 

U.S. Geological Survey National Water-Quality Assessment 

(NAWQA) program (fig. 6.1).

Purpose and Scope

The purpose of this Professional Paper section is to present the hydrogeologic setting of the Pomperaug River Basin 

regional study area. The section also documents the setup and 

calibration of a steady-state regional ground-water flow model 

for the study area. Ground-water flow characteristics, pumping-well information, and water-quality data were compiled 

from existing data to develop a conceptual understanding 

of ground-water conditions in the study area. A two-layer 

steady-state ground-water flow model of the glacial aquifer 

of the Pomperaug River Basin was developed and calibrated 

to average conditions for the period from 1997 to 2001. The 

5-year period 1997–2001 was selected for data compilation 

and modeling exercises for all TANC regional study areas 

to facilitate future comparisons between study areas. The 

ground-water flow model and associated particle tracking 

were used to simulate advective ground-water flow paths and 

to delineate areas contributing recharge to selected public-supply wells. Ground-water traveltimes from recharge to publicsupply wells, oxidation-reduction (redox) conditions along 

flow paths, and presence of potential contaminant sources in 

areas contributing recharge were tabulated into a relational 

database as described in Section 1 of this Professional Paper. 

This section provides the foundation for future ground-water 

susceptibility and vulnerability analyses of the study area and 

comparisons among regional aquifer systems.

Study Area Description

The Pomperaug River Basin regional study area encompasses the glacially derived, valley-fill aquifer of the Pomperaug River Basin. The study area was chosen because the 

aquifer is used extensively for public water supply, is susceptible and vulnerable to contamination, and is representative of 

the glacial aquifer system in the Northeastern United States. 

Characteristics of the Pomperaug River Basin aquifer system 

are similar to many valley-fill aquifer system in the Eastern 
6–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 6.1. Location of the Pomperaug River Basin regional study area within the glacial aquifer system.

A T L A N T I C

O C E A N

Long Island Sound

Chesapeake

Delaware

Bay

Lake Ontario

Cape Cod

Bay

Massachusetts

Bay

MASSACHUSETTS

CONNECTICUT

RHODE

ISLAND

VERMONT

NEW

HAMPSHIRE

M A I N E

N E W Y O R K

P E N N S Y L V A N I A

NEW

JERSEY

DELAWARE

MARYLAND

C A N A D A

Long Island

Cape

Cod

Nantucket Martha's

Vinyard

Nantucket

Sound Rhode Island Sound

Sandy

Hook

Cape

May

Bay

Boston

Providence

Hartford

New York

Philadelphia

Baltimore

77° 76° 75° 74° 73° 72° 71° 70° 

45° 

44° 

43° 

42° 

41° 

40° 

39° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 25 50 75 100 kilometers

0 25 50 miles

EXPLANATION

Pomeraug River Basin regional study area

Glacial deposits aquifer—Darker areas represent sand, gravel, and valley-fill aquifers locally

USGS NAWQA study unit—Connecticut, Housatonic, and Thames River Basins

Southern limit of Pleistocene continental glaciation
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–3

Hills and Valley Fills hydrophysiographic region of Randall 

(2001), which encompasses much of the most populated parts 

of New England, northern New Jersey, and eastern New York 

within the glacial aquifer system (table 6.1).

Topography and Hydrography

The Pomperaug River Basin regional study area covers 

about 128 km2 of the Pomperaug River Basin in west-central 

Connecticut and includes parts of the towns of Southbury, 

Woodbury, Roxbury, Watertown, Bethlehem, and Middlebury 

(fig. 6.2). The upper part of the basin is drained by the Nonnewaug and Weekeepeemee Rivers, which join in Woodbury 

to form the Pomperaug River. Most of the study area is in 

the Nonnewaug River and Pomperaug River drainage areas. 

Subbasins of the Pomperaug River Basin that are not in the 

study area are Transylvania Brook, East Spring Brook, and 

most of the Weekeepeemee River (fig. 6.2). The major valleys 

trend north to south and are bounded on the east and west by 

till-covered bedrock uplands drained by numerous perennial 

streams. Streams in upland areas are oriented mostly from 

east to west on the east side and northwest to southeast on the 

north and west sides. Hesseky Brook flows northward through 

an area underlain by sand and gravel and joins the Pomperaug 

River near its origin at the confluence of the Nonnewaug and 

Weekeepeemee Rivers. Manmade ponds are present on several 

tributary streams. Altitudes range from about 30 m near the 

confluence of the Pomperaug River with the Housatonic River 

to about 300 m at places on the basin divide.

Precipitation in the Pomperaug Basin averages about 117 

cm/yr (Randall, 1996). Basin runoff measured in the Pomperaug River at Southbury, Connecticut, averaged 61 cm/yr 

during 1933–2001 (Morrison and others, 2002; table 1). The 

balance of about 56 cm/yr is lost mainly to evapotranspiration 

(Randall, 1996).

Land Use

Land use in the Pomperaug River watershed has changed 

over the past 50 years from primarily undeveloped or agricultural lands to expanded residential, commercial, and light 

industrial areas. Most residential areas are served by individual 

septic disposal systems (ISDS) and are characterized by lowdensity housing. Agricultural lands are located mostly within 

flood plains and produce silage corn, hay, and berries. Industrial uses are limited and include small, modern, high-tech 

industries. Upland areas are largely forested with scattered 

residences on 0.16-km2 (40-acre) or larger lots.

Water Use

Most water for public supply is obtained from wells 

completed in valley fill. Mazzaferro (1986a) estimated that 

as much as 33,300 m3/d could be withdrawn from valley-fill 

materials. Public-supply systems distribute water from wells 

completed in valley-fill deposits at six locations (fig. 6.2; 

table 6.2). Three of the locations (WF, WT, and HV) include 

several closely spaced wells, and two locations (UW1 and 

UW2) each include a single well. One condominium complex 

(WP) obtains water from a single well completed in valley 

fill, and four additional condominium complexes obtain water 

from wells completed in bedrock (fig. 6.2). Pumping rates at 

WF, UW1, UW2, HV, and WT wells (table 6.2) are based on 

several months to 5 years of measurements. Pumping rates 

for other wells are based on the population served, assuming 

a per-capita consumption of 0.38 m3/d. This rate is reasonable 

for household use (John Mullaney, U.S. Geological Survey, 

written commun., 2003) but may be somewhat higher than 

rates for condominium residents where grounds are not irrigated as heavily and for the NHS (Nonnewaug High School) 

and for the RM (Romatic Manufacturing Company) wells. 

Numerous residents in the valley and uplands obtain water 

from private wells for domestic uses, including lawn irrigation.

All of the water pumped from the WF wells and approximately 30 percent of the water pumped from the HV wells is 

transported out of the basin. Water pumped from other supply 

wells is used within the basin. Wastewater at the HV facility 

is treated in a wastewater-treatment plant south of the supply 

wells and then discharged to the Pomperaug River. Elsewhere, 

wastewater is disposed to ground water through private septic 

systems and local treatment facilities.
6–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 6.1. Summary of hydrogeologic and ground-water-quality characteristics for the glacial aquifer system and the Pomperaug River 

Basin regional study area, Connecticut.

[m, meters; cm/yr, centimeters per year; m3/s, cubic meters per second; m3/d, cubic meters per day; km, kilometers; Kh, horizontal hydraulic conductivity; Kz, 

vertical hydraulic conductivity; Sy, specific yield; n, porosity; mg/L, milligrams per liter]

Characteristic Glacial aquifer system Pomperaug River Basin regional study area

Geography

Topography Relief generally less than 300 m (Randall, 2001). Relief approximately 300 m.

Climate Precipitation 91 to 127 cm/yr; evapotranspiration 46

to 58 cm/yr (Randall, 1996).

Precipitation 117 cm/yr; evapotranspiration 53 to 56 

cm/yr (Randall, 1996).

Surface-water hydrology Runoff 41 to 76 cm/yr (Randall, 1996); streamflow 

varies widely with the size of drainage basin. 

Water-supply reservoirs and former mill ponds are 

common in upland and valley settings.

Runoff 61 cm/yr; flow in Pomperaug River at 

Southbury averages 71 m3/s (Morrison and others, 

2002). Ponds and former water-supply reservoirs 

are present in uplands. A mill pond, largely silted, 

forms behind a dam on the Pomperaug River at 

Pomperaug.

Land use Urban, suburban, rural residential, woodlands, 

farmland.

Suburban, rural residential, woodlands, farmland.

Water use Potential aquifer yields generally less than 60,500 

m3/d (Kontis and others, 2004).

Pumpage for public supply about 7,570 m3/d (this 

study). Potential aquifer yield of 33,300 m3/d 

(Mazzaferro, 1986a).

Geology

Surficial geology Glacially-derived sand and gravel in valleys that 

slope away from retreating ice sheets; limited 

fine-grained deposits; till prevalent in uplands but 

discontinuous under valley fill (Randall and others, 

1988; Randall, 2001).

Mainly sand and gravel in a southward sloping 

valley (Stone and others, 1998); till covers 

uplands and underlies valley fill (Mazzaferro, 

1986a).

Bedrock geology Crystalline granitic and metamorphic rocks and 

sedimentary rocks; limited carbonate rocks 

(Randall, 2001; Randall and others, 1988).

Metamorphic crystalline rocks, granite, sedimentary 

rocks, and volcanics, mainly basalts.

Ground-water hydrology

Aquifer conditions Valley-fill aquifers that are generally less than 2.5 km 

wide and are unconfined; valley fill generally less 

than 67 m thick; depth to water generally less than 

15 m. Streams that cross valley fill from upland 

areas are commonly sources of recharge; pumping 

near surface water commonly induces infiltration 

(Kontis and others, 2004).

A valley-fill aquifer that is generally less than 1.6 

km wide and unconfined; valley fill generally less 

than 67 m thick; depth to water generally less 

than 15 m (Mazzaferro, 1986a; 1986b). Several 

tributary streams are likely sources of recharge. 

Pumping induces infiltration from streams in at 

least two areas.

Hydraulic properties Valley fill: Kh= 1.5 to150 m/d; Kh/Kz = 10:1 

(commonly); n = 0.3 to 0.4; Sy = 0.2 to 0.3

Till: Kh = 0.003 to 3 m/d; Kh/Kz = 1; n = 0.1to 0.3; 

Sy = 0.04 to 0.28

Bedrock: Kh = 0.003–0.3 m/d; Kh/Kz (limited 

information); n = 0.005–0.02; Sy = 0.0001–0.005 

(Randall and others, 1988; Bradbury and others, 

1991; Melvin and others, 1992; Gburek and others, 

1999).

Valley fill: Kh = 1.5 to 76 m/d; n = 0.3 to 0.45.

Till: Kh = 0.003to 3 m/d; n = 0.2 to 0.3

Bedrock: K = 0.003 to1.5 m/d; n = 0.005 to 0.02.

Sy values not used for current study; Kh/Kz 

estimated at 1:1. (Mazzaferro, 1986a; Grady and 

Weaver, 1988; Starn and others, 2000).
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–5

Characteristic Glacial aquifer system Pomperaug River Basin regional study area

Ground-water hydrology—Continued

Ground-water budget Recharge to valley fill from infiltration of 

precipitation, 36 to 76 cm/yr. Recharge to valley 

fill from upland runoff often exceeds recharge from 

precipitation (Kontis and others, 2004; Morrissey 

and others, 1988). Pumpage generally less than 

15 percent of water budget; most discharge is 

to streams (Morrissey, 1983; Tepper and others, 

1990; Dickerman and others, 1990; Dickerman 

and others, 1997; Mullaney and Grady, 1997; Starn 

and others, 2000; Barlow and Dickerman, 2001; 

DeSimone and others, 2002.)

Recharge to valley fill from infiltration of 

precipitation, 48 to 61 cm/yr. Recharge to valley 

fill from upland runoff at least 50 percent of total 

recharge. Pumpage for public supply less than 

5 percent of water budget; most ground water 

discharges to streams (Mazzaferro, 1986a; this 

study)

Ground-water quality

Dissolved solids less than 150 mg/L in crystallinerock terrains and greater than 150 mg/L in 

sedimentary-rock terrains; pH, 6–8; oxic. Calcium 

and bicarbonate are the principal ions (Rogers, 

1989). Redox conditions not defined regionally.

Dissolved solids generally less than 200 mg/L. 

Calcium and bicarbonate are the principal 

dissolved ions. Redox conditions are typically 

oxic in valley fill and suboxic to anoxic in 

bedrock (Grady and Weaver, 1988; this study).

Table 6.1. Summary of hydrogeologic and ground-water-quality characteristics for the glacial aquifer system and the Pomperaug River 

Basin regional study area, Connecticut.—Continued

[m, meters; cm/yr, centimeters per year; m3/s, cubic meters per second; m3/d, cubic meters per day; km, kilometers; Kh, horizontal hydraulic conductivity; Kz, 

vertical hydraulic conductivity; Sy, specific yield; n, porosity; mg/L, milligrams per liter]
6–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 6.2. Public-supply wells and pumping rates, Pomperaug River Basin regional study area, Connecticut. 

[m, meters; m3/d, cubic meters per day]

Map 

name

(fig. 2)

Well name Number of 

wells

Depth or 

depth range (m)

Geologic unit 

(model layer in parenthesis)

Combined 

pumping rate 

(m3/d)

Basis for pumping rate

HV Heritage Village 5 17–21 Sand and gravel (1) 3,544 1997 – 2001; well owner’s records1

WF Watertown Fire 

District

10 9–12 Sand and gravel (1) 2,450 1997 – 2001; well owner’s records2

UW1 United Water

Company

1 38 

(screened 35–38)

Sand and gravel (1) 334 June – December 2001; well owner’s 

records3

UW2 United Water 

Company

1 19

 (screened 12–16)

Sand and gravel (1) 392 June – December 2001; well owner’s 

records3

WT Woodlake Tax District3 9–12 Sand and gravel (1) 264 October 2001 – September 2002; 

well owner’s records4

WP Woodbury Place 

Condominiums

1 12 Sand and gravel (1) 27 Population served: 72

WK Woodbury Knolls 

Condominiums

1 38 

(screened 9–38)

Crystalline bedrock 

(1)

98 Population served: 258

TC Town in Country 

Condominiums

2 43 

(screened 9–33) 

and 85

Crystalline bedrock 

(1 and 2)

91 Population served: 240

HH Heritage Hill 

Condominiums

1 84 Crystalline bedrock 

(2)

45 Population served: 120

QH Quassuk Heights 

Condominiums

3 61–107 Crystalline bedrock 

(2)

41 Population served: 108

RM Romatic

Manufacturing 

Co.

1 Unknown Crystalline bedrock 

(2)

45 Population served: 120

NHS Nonnewaug

High School

1 Unknown Crystalline bedrock 

(2)

322 Population served: 850

1

 Roy Adamitis, Heritage Village, written commun., 2003

2

 Ernie Coppock, Watertown Fire District, written commun., 2003

3

 Kevin Moran, United Water, written commun., 2003

4

 Woodlake Tax District, written commun., 2003
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–7

Figure 6.2. Topography, hydrologic features, and locations of public-supply wells, Pomperaug River Basin regional study area, 

Connecticut.

84

6

84

6 WF

UW1

WT UW2

WP

HV

RM

WK HH

TC

NHS

QH

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Land elevation, in meters above sea level

Extent of model grid

Extent of active model cells

Public-supply well with identifier 

 (table 2)

 Completed in bedrock

 Completed in valley fill

Gaging station—Pomperaug River at 

 Southbury, Connecticut; Station 01204000

3600

3200

2800

2400

2000

1600

1200

800

400

0

WP

QH
6–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Conceptual Understanding of the 

Ground-Water System

Ground water beneath the Pomperaug River Basin 

regional study area occurs in the glacial valley-fill deposits 

of the Pomperaug River valley and the underlying Mesozoic 

and Paleozoic bedrock (fig. 6.3). Recharge to the valley-fill 

aquifer is from infiltration of precipitation, surface-water flow 

from upland areas, and ground-water inflow from underlying 

bedrock. Ground water discharges to wells and surface-water 

features.

Geologic Units and Hydraulic Properties

Geologic units in the Pomperaug River valley consist of 

Mesozoic sedimentary and volcanic bedrock within a structural basin in the central and western parts of the study area, 

surrounded by Paleozoic crystalline bedrock in upland areas; 

these consolidated units are overlain by Pleistocene-age glacial 

till and valley-fill surficial deposits. The geologic setting and 

hydraulic properties of the bedrock and surficial deposits are 

presented in the following sections.

Bedrock

The Pomperaug River valley in Woodbury and Southbury 

lies partly within a partial graben (Gates, 1954, 1959; Scott, 

1974; Stanley and Caldwell, 1976) composed of Mesozoic-age 

sedimentary and volcanic rocks. The Pomperaug fault extends 

north to south through the study area (fig. 6.4) and marks the 

eastern limit of Mesozoic-age rocks. East Hill, Bear Hill, and 

the Orenaug Hills (fig. 6.2) are topographically high areas in 

the Pomperaug River valley underlain by erosion-resistant 

basalts. Highlands east and west of the valley and structural 

basin are underlain by crystalline bedrock (Rodgers, 1985).

The Mesozoic-age sequence consists of three basalt layers interbedded with shale, arkosic sandstone, and conglomerate, which dip eastward at various angles but average about 

40 ̊ (Scott, 1974). The Mesozoic bedrock in the structural

Figure 6.3. Conceptual ground-water flow patterns, representative hydraulic properties, and recharge rates, Pomperaug River 

Basin regional study area, Connecticut.

A B

C

K = 3 to 5.2

n = 0.35

GLACIAL

AQUIFER

K = 0.03 to 1.5 n = 0.005 to 0.02

MESOZOIC BEDROCK

K = 0.003 to 0.3

n = 0.005 to 0.02

PALEOZOIC

CRYSTALLINE BEDROCK

K = 0.003 to 8 to 5.2

n = 0.25 to 0.30

PLEISTOCENE

TILL

Pomperaug River

Basalt

Shale

Basalt

Arkose

Granofels

Fault

Fault

Basalt

Till

Till 0 100 200 300 400 500 meters

0 500 1000 1500 feet

Vertical exaggeration X 4

Datum is sea level

A A'

0

25

50

75

100

125

150

175

200

225

METERS

700

600

500

400

300

200

100

0

FEET

EXPLANATION

Recharge source and identifier

Recharge sources

 Infiltration of precipitation equals 56 to 76 centimeters per year in glacial aquifer

 Upland surface shallow subsurface runoff equals 20 to 30 percent of ground-water budget for glacial aquifer

 Ground-water flow from bedrock equals 10 to 15 percent of ground-water budget for glacial aquifer

Ground-water flow path direction

Water table

Supply well and screen

Hydraulic conductivity, in meters per day

Porosity

A

B

C

K

n
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–9

basin was fully penetrated at a depth of 376 m in an oil test 

well drilled in the late 1800s near Southbury (fig. 6.2) (Hovey, 

1890). Thicknesses elsewhere are unknown. Faults, which are 

too numerous to show at the scale on figure 6.4, cause offsets 

of beds. Mapped faults are oriented approximately northeast 

to southwest in the southern part of the study area and north to 

south in the northern part of the study area (Scott, 1974; Rodgers, 1985).

Paleozoic-age crystalline rocks underlying the western 

part of the study area include granite, quartzite, schist, and 

gneiss (Scott, 1974; Gates, 1954). Numerous folds have been 

mapped in the crystalline rocks. Foliation planes typically dip 

steeply at angles exceeding 45 ̊. Foliation strike varies widely,

but a north-northwest to south-southeast trend appears to 

dominate in much of the study area (Scott, 1974; Gates, 1954).

Wells completed in bedrock obtain most of their water 

from fractures. Aquifer-test data are not available for bedrock wells in the study area, but driller-reported yields and 

water levels during pumping are indicators of transmissive 

properties. Average yields from numerous wells completed in 

Paleozoic-age crystalline rocks and Mesozoic-age rocks are 

similar, but wells completed in Paleozoic crystalline rocks are 

typically deeper than those completed in Mesozoic rocks. A 

sample of driller’s reports for 60 domestic wells was summarized for this study. Yields reported for 14 wells completed 

in Mesozoic rocks average about 37m3/d and depths average 

83 m. Yields for 46 wells completed in Paleozoic crystalline 

rocks average about 49 m3/d and depths average 99 m. Starn 

and others (2000) report an average hydraulic conductivity of 

0.18 m/d for Paleozoic rocks and 1.43 m/d for Mesozoic rocks 

in the Transylvania Brook Basin, a tributary to the Pomperaug 

River west of the study area (fig. 6.2). Lower values of 0.006 

to 0.03 m/d for crystalline rocks in northern New Hampshire 

were determined by model calibration (Tiedeman and others, 

1997). Lyford and others (2003) report hydraulic conductivity values that range from 0.006 to 4.3 m/d near public-supply 

wells completed in metamorphic rocks in eastern Massachusetts.

Bedrock transmissivities estimated by applying the 

Cooper-Jacob formula (Cooper and Jacob, 1946; Fetter, 1994) 

for driller-reported yields, drawdowns, and pumping times 

average about 1.9 m2/d for Mesozoic rocks and about 1.0 m2/d 

for Paleozoic rocks. For the average thicknesses of rocks penetrated by wells, hydraulic conductivity values average about 

0.03 m/d for Mesozoic rocks and 0.01 m/d for Paleozoic rocks. 

Because of uncertainties associated with the data, method 

of analysis, and small data set, these estimates are presented 

as “order-of-magnitude” values and support the concept that 

Mesozoic rocks are more transmissive than Paleozoic rocks.

Water-bearing fractures commonly are found along 

foliation planes in metamorphic rocks and bedding planes in 

Mesozoic rocks (Janet Stone, U.S. Geological Survey, oral 

commun., 2002; Walsh, 2001a, 2001b, 2002). A dominant 

high-angle foliation in metamorphic rocks and numerous highangle fractures in Mesozoic rocks (Gates, 1954; Scott, 1974) 

indicate the rocks are well connected vertically, but values of 

vertical hydraulic conductivity are not available. Lyford and 

others (2003) report vertical conductance (vertical hydraulic 

conductivity divided by thickness) values of 0.0015 to 0.04 

1/d for two areas where high-angle fractures are present and 

metamorphic rocks are well connected vertically to surficial 

materials. Porosity values reported for crystalline bedrock 

range from 0.005 to 0.02 (Ellis, 1909; Heath, 1989; Barton 

and others, 1999).

Surficial Materials

Surficial materials are largely glacially derived and 

include till deposited on bedrock and glacial sand and gravel 

outwash deposited in valleys (fig. 6.4). Also present but not 

shown separately on figure 6.4 are Holocene alluvial materials, typically less than 3 m thick, which were deposited by 

streams after glaciers receded. The alluvial materials commonly include organic matter (Pessl, 1970).

Till includes a surface till unit (also called thin till) 

deposited by the last glacial ice sheet and a thick till unit (also 

called drumlin till) deposited during an earlier glacial epoch 

and compacted by the last ice sheet (Melvin and others, 1992). 

The surface till unit is fairly continuous and typically less than 

5 m thick. The thick till unit typically is found in stream-lined 

hills, exceeds a thickness of 15 m in places, and is covered by 

surface till. The depth to bedrock reported by drillers for 60 

wells completed in bedrock, mostly in upland areas, ranges 

from 0.9 to 46 m and averages 12 m. The surface till averages 75 percent sand or coarser and 25 percent silt and clay 

and typically is not oxidized except in places along sand and 

gravel lenses. The thick till typically is finer grained, averaging 60 percent sand or coarser and 40 percent silt and clay and 

is oxidized throughout (Pessl, 1970).

The hydraulic properties of till described by Melvin and 

others (1992) for Connecticut are reasonable for the study 

area. They report an average hydraulic conductivity of 0.8 m/d 

for loose surface till and 0.02 m/d for compact drumlin till 

derived from crystalline rocks. Horizontal hydraulic- conductivity values for surface and drumlin tills range from 0.0009 to 

20 m/d, and vertical hydraulic-conductivity values range from 

0.004 to 29 m/d. Porosity ranges from 0.2 for compact drumlin 

till to 0.35 for surface till (Melvin and others, 1992).

Stratified, glacially derived sediments underlie about 

33 km2 of the valley, or about 26 percent of the study area. 

The valley-fill deposits include sand and gravel deposited by 

glacial streams, usually in contact with stagnant ice masses, 

and silt, sand, and gravel deposited in glacial Lake Pomperaug. The distribution of valley-fill sediments is consistent with 

the morphosequence depositional model for glacial sediments 

(Stone and others, 1998; Randall, 2001). A morphosequence 

is defined as “a body of stratified drift that was laid down 

by meltwater when deposition was controlled by a specific 

base level such as a proglacial lake or spillway; the deposits 

become generally finer distally and their upper surface (where 

not collapsed) slopes smoothly in the same distal direction” 

(Randall, 2001, p. 178). Several glacial-lake stages are appar-
6–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 6.4. Bedrock and surficial geologic units, Pomperaug River Basin regional study area, Connecticut.

84

6

84

6

Pomperaug

Fault

A A'

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Surficial deposits—Where hachured, underlain by Mesozoic-

 age rocks (arkose, basalt, and shale); where not hacured,

 underlain by Paleozoic-age crystalline rocks (schist, gneiss, 

 and granite)

 Valley fill—Mostly sand and gravel, includes layers of silt

 and fine sand in some areas

 Surface till—Overlies bedrock or thick till; thickness 

 generally less than 4.6 meters; also called thin till

 Thick till—Denser and generally thicker than surface till;

 generally covered by surface till to a depth of 4 meters

 or less

Line of generalized hydrogeologic section (figure 3)

Fault

Extent of active model cells

A A'
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–11

ent in relative altitudes of deposits. The last stage of the lake 

drained when a dam consisting of sand and gravel at Pomperaug (fig. 6.2) was breached (Pessl, 1970). Coarse-grained 

materials predominate at the land surface, but as much as 47 

m of fine-grained sand, silt, and clay has been identified in the 

subsurface in some parts of the Pomperaug Valley (Mazzaferro, 1986a).

The hydraulic conductivity of outwash deposits, which 

was determined on the basis of aquifer tests and specificcapacity tests, ranges from 1.5 m/d for fine materials to 76 

m/d or more for gravel (Mazzaferro, 1986a; Starn and others, 

2000). The greatest hydraulic conductivity areas are mapped 

near the towns of Woodbury, Pomperaug, and Southbury 

(Grady and Weaver, 1988). The vertical hydraulic conductivity 

for sand and gravel has not been determined, but a ratio of 10 

for horizontal to vertical commonly is assumed (Kontis and 

others, 2004). The porosity of sand and gravel typically ranges 

from 0.3 to 0.45 (Morris and Johnson, 1967; Masterson and 

others, 1997; Mullaney and Grady, 1997).

Ground-Water Occurrence and Flow

Ground water generally is unconfined and within 15 m 

of the land surface throughout much of the Pomperaug River 

Basin regional study area. Depths to water exceed 15 m for 

some areas of sand and gravel near valley walls and in an area 

of deltaic sediments near Woodbury (Mazzaferro, 1986b). 

The valley-fill saturated thickness ranges from zero near the 

contact with upland till to 37 m near Woodbury (Grady and 

Weaver, 1988).

Ground-water flow in upland areas includes shallow 

subsurface flow through surface till and soil to nearby wetlands and stream channels and deep flow through thick till and 

fractured bedrock to more distant discharge points, including tributaries to the Pomperaug River and valley fill. During 

periods of high recharge, when the water table is near the land 

surface, the shallow flow and short flow paths predominate. 

However, water levels are lower during extended dry periods, 

and deep flow along longer flow paths predominates. Meinzer 

and Stearns (1929) report numerous dug wells and groundwater depths generally less than 9 m in upland areas of the 

Pomperaug River Basin. Driller-reported water levels that 

average 7.3 m in depth for wells completed in Paleozoic rocks 

also support the concept of a water table generally less than 

9 m deep.

Ground-water flow directions shown in figure 6.5 are 

based on a water-table map for the valley fill presented by 

Mazzaferro (1986a) and basin-wide flow paths simulated 

as part of this study. In general, ground-water flow is from 

upland recharge areas toward discharge areas along the Pomperaug River and its tributaries. Pumping from public-supply 

wells may affect ground-water flow locally, but depressions 

in the water table caused by pumping are not apparent at the 

3-m contour interval used to map the water table in valley fill 

(Mazzaferro, 1986a). Conceptually, pumping has a minimal 

effect on area-wide flow patterns.

Water Budget

Recharge in upland areas is largely by infiltration of precipitation. Other minor sources include wastewater return from 

septic systems and leakage from ponds and streams. Recharge 

rates in upland areas are not well understood in New England, 

but controlling factors appear to include the distribution of 

surface till and topography. Areas of shallow ground water can 

be extensive during wet periods, particularly during the spring. 

In these areas, a major control on recharge rates is the depth to 

the water table and the rate at which ground water at the water 

table drains vertically or laterally. The vertical and lateral flow 

of ground water varies widely in upland areas and relates to 

the transmissivity of till and bedrock, topographic relief, and 

hydraulic gradient at the water table. Annual recharge rates, 

therefore, can vary widely from near zero in wetland discharge 

areas where the water table is perennially at or near the land 

surface to rates that approach annual runoff rates.

Numerous streamflow records in Connecticut have been 

analyzed for the ground-water runoff component, which is an 

approximation of ground-water recharge. For basins underlain 

principally by till, data presented by Mazzaferro and others (1979) indicate ground-water runoff is approximately 33 

percent of total runoff. Ground-water runoff from uplands in 

the Pomperaug River Basin would average about 20 cm/yr 

on the basis of the statewide analysis. Mazzaferro (1986a) 

estimated long-term effective recharge rates (ground-water 

recharge minus ground-water evapotranspiration) of about 18 

cm/yr. Analysis of streamflow data in similar upland settings 

using the programs of Rutledge (1993, 1997, 1998) typically yield higher recharge rates of 38 cm/yr or more (Bent, 

1995, 1999; Robert Flynn and Gary Tasker, U.S. Geological 

Survey, written commun., 2003). Starn and others (2000) 

determined area-averaged recharge rates of 56 cm/yr for areas 

underlain by Mesozoic rocks and 20 cm/yr for areas underlain 

by crystalline rocks on the basis of the statewide analysis of 

ground-water runoff and numerical modeling of ground-water 

flow near Transylvania Brook. A water-budget study of the 

Pomperaug River Basin by Meinzer and Stearns (1929) for 

1913–1916 indicated basin-wide ground-water recharge averaged 39.5 cm/yr and precipitation averaged 113 cm/yr. They 

stated that nearly one-half of the ground-water recharge was 

lost to evapotranspiration.

Major recharge sources in areas underlain by valley fill 

include direct infiltration of precipitation, ground-water inflow 

from bedrock, runoff from bordering hillslopes, and infiltration from tributary streams (Lyford and Cohen, 1988; Randall 

and others, 1988). Other sources include induced infiltration 

from streams near wells and disposal of wastewater from 

septic systems. Direct infiltration of precipitation to valley 

fill probably approaches annual runoff rates (precipitation 
6–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 6.5. Wells sampled, oxidation-reduction classification zones, and directions of ground-water flow, Pomperaug River Basin 

regional study area, Connecticut.

84

6

84

6

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

A A'

55

75

35 53

78

58

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Estimated low dissolved-oxygen—

 Less than 0.5 milligrams per liter

Generalized ground-water flow direction

Line of generalized hydrogeologic section (figure 3)

Valley fill boundary

Extent of active model cells

Oxidation-reduction classification—Bedrock 

 wells are shown with depth in meters

 Oxygen or nitrate reduction

 Manganese or iron reduction

 Mixed

 Indeterminant

58

75

A A'
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–13

minus evapotranspiration) or about 61 cm/yr (Randall, 1996; 

Morrison and others, 2002). Mazzaferro (1986a) estimated 

long-term effective recharge rates of 48 to 51 cm/yr for areas 

underlain by sand and gravel. Starn and others (2000) simulated rates of 56 cm/yr for sand and gravel in the Transylvania 

Brook area. Inflow rates from crystalline rocks typically are 

small relative to other sources, but inflow rates from Mesozoic 

rocks, which potentially receive more recharge from precipitation and are more transmissive than crystalline rocks, may be a 

major source of recharge to valley fill in some areas. Recharge 

rates from upland hillslopes that border valley-fill materials 

vary with the size of the hillslope contributing area and can 

account for 50 percent or more of the total recharge to valleyfill materials (Williams and Morrissey, 1996; Morrissey and 

others, 1988). Water-budget summaries, which were compiled 

from ground-water flow models in New England, indicated 

that from 30 to 60 percent of the inflow to valley fill is from 

upland sources. Natural infiltration from streams that cross 

valley fill from upland areas also can be a major component of 

recharge to valley-fill aquifers in some settings (Williams and 

Morrissey, 1996). An analysis of streamflow data for the Pomperaug River at Southbury, using the programs of Rutledge 

(1993, 1997, 1998), indicated that for 1995–96, a period when 

total runoff was about 5 cm above long-term average runoff, 

basin-wide recharge was 70 to 80 percent of total runoff, or 46 

to 53 cm/yr (J.J. Starn, U.S. Geological Survey, written commun., 2002).

Ground-Water Quality

Ground-water quality data for wells completed in the 

valley-fill aquifer of the study area indicate dissolved-solids 

concentrations are generally less than 200 mg/L (Mazzaferro 

and others, 1979; Mazzaferro, 1986a; Grady and Weaver, 

1988). Ground water generally is of the calcium-sodiummagnesium-bicarbonate-chloride type, and the pH typically 

ranges from 6.0 to 7.5 (Mazzaferro and others, 1979; Mazzaferro, 1986a; Grady and Weaver, 1988). Some water samples 

in the study area indicate contamination from anthropogenic 

sources, including road salt, agricultural chemicals, petroleum 

hydrocarbons, chlorinated compounds, and septic systems. A 

study by Grady and Weaver (1988) of the effects of land use 

on ground-water quality in shallow monitoring wells found 

several contaminants associated with human activities in 

residential, commercial, light industrial, and agricultural landuse settings. Concentrations of natural contaminants, including radionuclides (Thomas and McHone, 1997) and arsenic 

(Brown and Chute, 2002), can be high in fractured bedrock 

aquifers in parts of Connecticut and potentially migrate to 

community water supplies in adjacent stratified-drift aquifers. High concentrations of radon have been associated with 

crystalline rocks (the Nonnewaug Granite and the Collinsville 

and Taine Mountain Formations) (Thomas and others, 1988; 

Thomas and McHone, 1997).

Ground water in most of the stratified glacial aquifer is 

oxygen and nitrate reducing, but in some areas near the central 

part of the valley, manganese- and iron-reducing conditions 

are present where water along longer flow paths discharge 

to surface-water bodies (fig. 6.5). In these waters, concentrations of dissolved oxygen typically are low, dissolved iron 

and manganese concentrations are high, and nitrate concentrations generally are low or below detection. Organic-rich 

sediments beneath surface-water bodies and in wetlands also 

can consume dissolved oxygen and create manganese- and 

iron-reducing shallow ground water, as observed in a flowpath study by Mullaney and Grady (1997) in a glacial aquifer 

in north-central Connecticut. Ground water in the fractured 

bedrock generally is older than water from the glacial aquifer, 

and tends to be manganese and iron reducing. Ground water 

that has flowed through rocks of Mesozoic or Paleozoic age 

before passing into the glacial aquifer could reflect chemical 

characteristics of the bedrock.
6–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Ground-Water Flow Simulations

A steady-state model of ground-water flow in the study 

area was developed using MODFLOW-2000 (Harbaugh and 

others, 2000) to estimate aquifer-system properties, delineate 

areas contributing recharge to public-supply wells, and support 

future local modeling efforts. The model represents average 

ground-water flow conditions from 1997 to 2001. Model input 

includes boundary conditions, model stresses, and hydraulic 

properties. The preprocessor Argus ONE (Argus Interware, 

1997) with the graphical interface for MODFLOW (Winston, 

2000), using MODFLOW-2000 (Harbaugh and others, 2000), 

provided flexibility for setting up model grids, layer thicknesses, and stream characteristics. Aquifer-system and model 

characteristics are summarized in table 6.3.

Modeled Area and Spatial Discretization

The Pomperaug River Basin regional ground-water flow 

model encompasses an area of 128 km2 (fig. 6.6). A no-flow 

(zero-flux) boundary surrounds the modeled area, which 

assumes that ground-water divides are coincident with topographic divides, that inflow to the modeled area as underflow 

from three tributary basins is negligible, and that underflow at 

the mouth of the Pomperaug River is negligible.

Experiments with uniform model grid sizes consisting of 

30.5-m- and 152.4-m-square cells indicated simulated water 

budgets, flow paths, and contributing recharge areas were 

nearly identical for the two cell sizes. The calibrated model 

discussed here is for the 152.4-m cell size because the larger 

spacing was more numerically stable, computer simulation 

times were shorter, and output data were easier to manage 

than those for the 30.5-m cell size. The 30.5-m cell size was 

later used for particle-tracking simulations to delineate areas 

contributing recharge to public-supply wells. Two layers 

that parallel the land surface were selected to represent the 

vertical dimension. Layer 1 is 46 m thick and represents till 

and shallow bedrock in upland areas and stratified, glacially 

derived sediments and shallow bedrock in the valleys. Layer 

2 represents a 107-m- thick section of bedrock. It is assumed 

that most ground water flows through a total thickness of 

about 152 m. Early attempts to use a uniform 15-m thickness 

for layer 1 and four layers resulted in numerical instabilities 

that could not be resolved. The two-layer model was generally 

stable for a layer 1 thickness of 46 m. Layer 1 was specified as 

convertible to unconfined where heads were below the top of 

the layer, and layer 2 was specified as confined.

Boundary Conditions and Model Stresses

Model stresses include streams, recharge, and extraction 

wells. Perennial streams were simulated using the MODFLOW stream package (Prudic, 1989). The stream package 

accounts for gains and losses in the simulated streams and 

routes flow from upstream reaches to downstream reaches. 

The ends of stream segments were placed at mapped stream 

origins in headwater areas, at stream intersections, and at 

major changes in stream-channel slope. The stream altitudes 

were interpolated linearly within a segment. This approach 

closely matched actual stream altitudes at stream reaches 

for low-gradient, uniformly sloped main stems but was less 

accurate for tributary streams with high-gradient, nonuniform 

slopes. The top of the streambed was placed 0.9 m below the 

stream stage, and the bottom of the streambed was placed 

1.2 m below the stream stage. The Nonnewaug, Weekeepeemee, and Pomperaug Rivers were assumed 15 m wide except 

near the Watertown Fire District Wells (WF) where a 30-m 

width was assigned to account for diversions from the Nonnewaug River through recharge ponds. All other streams were 

assumed to be 3 m wide. A streambed hydraulic conductivity 

of 0.3 m/d was assumed for all streams on the basis of literature-reported values (Kontis and others, 2004).

Recharge was applied in five zones defined by geology 

(fig. 6.7), and recharge rates were assigned so basin runoff 

approximated 70 to 80 percent of long-term average runoff 

measured for the Pomperaug River at Southbury. Evapotranspiration of ground water was accounted for in the recharge 

estimates but was not modeled explicitly. A recharge rate of 

56 cm/yr was used for the valley fill by Starn and others 

(2000) for the Transylvania Brook area and was also applied 

to areas underlain by valley fill in this study. Surface runoff 

is limited in areas underlain by valley-fill materials, thus the 

recharge rate should approximate runoff rates (Lyford and 

Cohen, 1988). A rate less than the basin runoff rate of about 

61 cm/yr accounts for some storm runoff from impermeable 

surfaces. A recharge rate of 61 cm/yr was applied on hillslopes 

that adjoin the valley fill to account for water that runs off of 

these areas and recharges the valley fill near the valley edges. 

Most areas underlain by Mesozoic rocks form hillslopes 

adjacent to valley fill, so a recharge rate of 61 cm/yr also was 

applied in this zone. This rate is similar to a rate of 56 cm/yr 

used be Starn and others (2000) in the Transylvania Brook 

area. A rate of 38.1 cm/yr was applied in thick till and thin till 

areas underlain by crystalline rocks.

Discharge wells were placed at locations of public-supply wells completed in sand and gravel and bedrock. Wells 

completed in valley fill were placed in layer 1. Wells in upland 

areas that service condominium units and the Romatic Manufacturing Company (RM) are completed in bedrock. All but 

two of the bedrock wells were placed in layer 2. A well 43 m 

deep at the Town in Country Condominiums (TC) and a well 

38 m deep at the Woodbury Knolls Condominiums (WK) were 

placed in layer 1 because of depths less than the thickness of 

layer 1. A well completed to an unknown depth in bedrock at 

Nonnewaug High School (NHS) is in a valley setting but also 

was placed in layer 2. Extraction rates were set to measured or 

estimated average rates (combined pumping rate; table 6.2).

Screened intervals for wells in sand and gravel and producing intervals for wells in bedrock were available for only 

United Water Company Wells #1 and #2 (UW1 and UW2), 
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–15

Table 6.3. Summary of aquifer-system and model characteristics, Pomperaug River Basin regional 

study area, Connecticut 

[m, meters; m/d, meters per day; cm/yr, centimeters per year]

Characteristic Measured or

estimated range Simulated value

Thickness

Valley fill 0 to 61 m Total thickness of layer 1 is 46 m, 

which may include any of the 

following: valley fill, till, and 

bedrock

Thick till 5 to 46 m

Surface till 0 to 5 m

Bedrock Less than 152 m 107 m

Hydraulic conductivity

Valley fill 1.5 to 76 m/d Less than 3 m thick: 0.12 m/d

3 to 15 m: 6.28 m/d

Greater than 15 m thick: 5.7 m/d

Gravel over fines: 2.8 m/d

Thick till 0.003 to 0.3 m/d 0.12 m/d

Surface till 0.003 to 3 m/d 0.09 m/d

Crystalline bedrock 0.003 to 0.3 m/d 0.03 m/d

Mesozoic bedrock 0.03 to 1.5 m/d 0.09 m/d

Ratio of horizontal to vertical 

hydraulic conductivity

1.0 to 10 1

Porosity

Valley fill 0.3 to 0.45 Less than 3 m thick: 0.01

3 to 15 m: 0.07

Greater than 15 m thick: 0.23

Gravel over fines: 0.23

Thick till 0.25 0.08

Surface till 0.2 to 0.35 0.035

Crystalline bedrock 0.005 to 0.02 0.02

Mesozoic bedrock 0.005 to 0.02 0.02

Stream characteristics

Width 3 to 30 m Near Watertown Fire District 

wells: 30 m;

Main stems: 15 m; tributaries: 

3 m

Hydraulic conductivity of 

streambed

0.1 to 3 m/d 0.3 m/d

Thickness of streambed 0.3 to 1.5 m 0.3 m

Recharge rates

Hillslope 38 to 66 cm/yr 61 cm/yr 

Valley fill 48 to 61 cm/yr 56 cm/yr 

Mesozoic rocks 38 to 66 cm/yr 61 cm/yr 

Surface till 20 to 6 cm/yr 38 cm/yr 

Thick till 20 to 56 cm/yr 38 cm/yr 
6–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 6.6. Ground-water flow model grid and simulated streams and wells, Pomperaug River Basin regional study area, 

Connecticut.

84

6

84

6 WF

UW1

WT UW2

WP

HV

RM

WK HH

TC

NHS

QH

WF

UW1

WT UW2

WP

HV

RM

WK HH

TC

NHS

QH

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Stream—Stream simulated with stream package

Model grid—Consists of square blocks 152 meters 

 on a side

Extent of model grid

No-flow boundary and extent of active model cells

Extraction well with identifier (table 2)

 Completed in bedrock

 Completed in valley fill

RM

HV
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–17

Figure 6.7. Ground-water recharge zones, Pomperaug River Basin regional study area, Connecticut.

84

6

84

6

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Hillslope adjacent to Mesozoic rocks and valley fill

Valley fill

Mesozoic rocks

Surface till over crystalline rocks

Thick till

Extent of active model cells
6–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Woodbury Knoll Condominium (WK), and Town in Country Condominium (TC) (table 6.2). For purposes of tracking 

particles, a screen length of 6.1 m at the bottom of the well 

was assumed for wells completed in valley fill, and a producing interval from the top of layer 2 to the bottom of the well 

was assumed for bedrock wells. For Romatic Manufacturing 

Company (RM) and Nonnewaug High School (NHS), where 

well depths are unknown, the producing interval was assumed 

to be the thickness of layer 2.

Aquifer Hydraulic Properties

Hydraulic-conductivity zones for each layer were defined 

on the basis of the mapped distribution of geologic units and 

saturated thicknesses presented by Grady and Weaver (1988). 

Layer-1 zones included surface till and thick till zones in 

uplands and four zones in valley fill (fig. 6.8). The zones for 

valley-fill materials are defined largely on the basis of saturated thickness of sand and gravel and are best visualized as 

transmissivity zones rather than hydraulic-conductivity zones 

because layer-1 thickness generally is greater than actual 

geologic-unit thickness. These zones include (1) areas along 

the valley wall where the saturated thickness is less than 3 m, 

(2) areas where the saturated thickness is 3 to 15 m, (3) areas 

where the saturated thickness is greater than 15 m, and (4) a 

fairly extensive area near North Woodbury where coarse materials overlie fine materials. The hydraulic-conductivity values 

summarized in table 6.3 for valley-fill zones were refined 

somewhat from initial estimates by the parameter-estimation 

option in MODFLOW-2000. The hydraulic-conductivity zones 

for layer 2 include one for Paleozoic crystalline rocks and a 

second for the more transmissive Mesozoic rocks (fig. 6.4).

Porosity values for layer 1 were adjusted for thickness 

to simulate approximate cross-sectional pore areas in surficial materials and, thereby, more accurately simulate lateral 

traveltimes through surficial materials. Model porosities were 

calculated by multiplying estimated actual porosities by the 

ratio of saturated thickness to the thickness of layer 1 (46 m). 

For example, a saturated thickness of 4.6 m for thin till divided 

by a layer 1 thickness of 46 m and multiplied by an estimated 

porosity of 0.35 yields a model porosity of 0.035. Estimated 

and simulated porosity values for layer 1 zones are summarized in table 6.3. A uniform porosity of 0.02 was used for 

layer 2 to represent fracture porosity in bedrock.

Model Calibration

The Pomperaug River Basin regional ground-water flow 

model was calibrated by manually adjusting model-input 

parameters for hydraulic conductivity and comparing modelcomputed to measured hydraulic heads. Data used for model 

calibration include average water levels reported by Mazzaferro (1986a) for January 1979 to February 1980 and for one 

USGS observation well (SB-39) for 1991 to 2002. Water-level 

data from driller’s logs for upland areas indicated a shallow 

water table but were not used explicitly for model calibration. 

The calibration goal was to approximately simulate observed 

heads in valley fill with a uniform distribution of residuals 

(measured minus model-computed heads) and a shallow water 

table that approximated the land-surface configuration in 

upland areas. Streamflow data were not available for model 

calibration.

The overall goodness of fit of the model to the observation data was evaluated using summary measures and graphical analyses. The root-mean-squared error (RMSE), the range, 

the standard deviation, and the standard-mean error of the 

residuals (SME), were used to evaluate the model calibration. 

The RMSE is a measure of the variance of the residuals and 

was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of wells used in the computation. If the ratio of the RMSE 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).

The SME was calculated as:

where σ(hmeas – hsim) is the standard deviation of the residuals.
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–19

Figure 6.8. Hydraulic-conductivity and porosity zones for model layer 1, Pomperaug River Basin regional study area, Connecticut.

84

6

84

6

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Thick till

Surface till

Sand and gravel

 Less than 3 meters thick

 3 to 15 meters thick

 Greater than 15 meters thick

 Over fines consisting of fine sand and silt

Extent of active model cells

(Values shown in table 3)
6–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Model-Computed Hydraulic Heads

A simple method of assessing model fit is to plot the 

model-computed hydraulic head values against the measured 

observations. For a perfect fit, all points should fall on the 1:1 

diagonal line. Figure 6.9 presents a plot of the model-computed compared to the measured hydraulic heads for the study 

area and indicates a reasonable model fit. The average residual 

for the entire model is 0.43 m, and residuals range from 

-10.1 m to 8.2 m (range of 18.1 m). The RMSE for the entire 

model is 4.43 m, which is 11 percent of the range of head 

observations in the model (40.8 m). The standard deviation 

of the residuals is 4.50 m, and the SME is 0.88 m. The spatial 

distribution of model-computed hydraulic heads in layer 1 

approximately parallels the land surface in upland areas, with 

the largest differences between model-computed and measured 

heads occurring near the contact between valley-fill sediments 

and bedrock (fig. 6.10). Factors that may cause differences 

between model-computed and measured heads include imprecise measuring-point elevations determined from topographic 

maps, spatial variation in saturated thicknesses and hydraulic 

conductivity not accounted for in the model, and imprecise 

recharge rates near the edge of the valley.

The simulated potentiometric surface for valley fill and 

analysis of basin-wide flow patterns indicate most ground 

water flows from upland areas toward the Pomperaug River at 

approximately right angles to the Pomperaug River consistent 

with the potentiometric surface for valley fill presented by 

Mazzaferro (1986a). For Bullet Hill Brook and its tributaries, 

potentiometric-surface data and model results indicate that 

ground-water flow approximately parallels the stream channels.

Model-Computed Water Budget

The modeled-area water budget (table 6.4) indicates 

that areal recharge provides approximately 87 percent of the 

ground-water inflow, and about 13 percent of the groundwater inflow is from streams. Stream recharge is mostly from 

tributary streams where they cross valley-fill sediments (fig. 

6.11). Stream losses also are apparent near the HV and WF 

wells. About 96 percent of ground-water discharge is to rivers, 

and about 4 percent of ground-water discharge is to wells. 

Recharge of wastewater discharged to ground water from septic tanks was not simulated but could account for an additional 

1 percent of the inflow. Simulated streamflow at the outflow 

point for the basin is 161,000 m3/d, which is 46.2 cm/yr for the 

modeled area, or about 77 percent of average basin runoff of 

59.9 cm/yr, as measured in the Pomperaug River at Southbury, 

Connecticut (Morrison and others, 2002).

A water budget for layer 1 in the area underlain by valley fill was determined using the program ZONEBUDGET 

(Harbaugh, 1990). This analysis indicated that more than onehalf of the inflow to the valley-fill aquifer can be attributed 

Figure 6.9. Relation between model-computed and measured 

hydraulic head, Pomperaug River Basin regional study area, 

Connecticut.

Table 6.4. Model-computed water budget for 1997–2001 

average conditions, Pomperaug River Basin regional study area, 

Connecticut.

[m3/d, cubic meters per day]

Water-budget component Flow rate

(m3/d)

Percentage of 

inflow or outflow

Modeled-area inflow

Recharge 169,000 87.2

Rivers 24,800 12.8

TOTAL 193,800 100

Modeled-area outflow

Wells 7,650 3.9

Rivers 187,000 96.1

TOTAL 194,650 100

Valley-fill aquifer inflow

Precipitation 45,500 34.2

Rivers 20,200 15.2

Lateral flow from layer 1 36,400 27.4

Vertical flow from layer 2 30,800 23.2

TOTAL 132,900 100

Valley-fill aquifer outflow

Wells 7,100 5.3

Rivers 117,800 88.7

Lateral flow to layer 1 4,800 3.6

Vertical flow to layer 2 3,200 2.4

TOTAL 132,900 100

1:1 line

45

50

55

60

65

70

75

80

85

90

95

100

105

Model-computed head elevation, in meters

Measured head elevation, in meters

45 50 55 60 65 70 75 80 85 90 95 100 105
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–21

Figure 6.10. Observation points and head residuals, Pomperaug River Basin regional study area, Connecticut.

84

6

84

6

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Extent of valley fill

Extent of active model cells

Observation well and residual head (measured

 minus modeled) range, in meters

 –9.3 to –3.1

 –3.0 to 3.0

 3.1 to 9.9
6–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

to upland runoff, which includes river leakage from tributary 

streams, lateral flow from layer 1 upland areas, and vertical 

leakage from layer 2 (table 6.4). The net contribution from 

uplands to valley fill is about 60 percent of the inflow, after 

adjusting for lateral and vertical outflows to layers 1 and 2 that 

eventually reenter the valley-fill aquifer. Discharge to wells is 

about 5 percent of the outflow for the valley-fill aquifer (table 

6.4).

Simulation of Areas Contributing Recharge to 

Public-Supply Wells

Areas contributing recharge to eight public-supply wells 

or well fields and traveltimes from recharge to discharge 

areas were simulated by particle-tracking using MODPATH 

(Pollock, 1994) and methods as described in Section 1 of 

this Professional Paper (fig. 6.11). A grid spacing of 30.5 

m was used for the analysis of contributing areas to better 

identify flow paths for individual wells. Properties from the 

calibrated model were used for the finer grid. Porosity values 

were assigned as discussed in the section “Aquifer Hydraulic 

Properties.” The model-computed areas contributing recharge 

represent advective ground-water flow and do not account for 

mechanical dispersion. Advection-dispersion transport simulations would likely yield larger areas contributing recharge than 

advective particle-tracking simulations because the effects of 

dispersion caused by aquifer heterogeneity would be included.

Several features of areas contributing recharge and zones 

of contribution that appear in figure 6.11 are considered noteworthy:

•	 For all wells completed in valley fill, the areas contributing recharge and zones of contribution extend 

upgradient into upland areas.

•	 Areas contributing recharge extend perpendicularly 

away from the Pomperaug River and its major tributaries reflecting that ground-water flow direction is 

perpendicular from upland areas toward the rivers.

•	 Areas contributing recharge can extend large distances 

from some wells. For example, the contributing area 

for WP extends approximately 3 km to the eastern 

model boundary and topographic divide.

•	 The contributing areas for WF and HV are larger than 

for other well sites because of larger pumping rates, as 

expected.

•	 Simulated losing reaches of streams occur within 

several of the contributing areas (fig. 6.11) indicating 

streams contribute recharge to public-supply wells.

An area-wide analysis indicated that traveltimes from 

recharge areas to wells ranged from less than 1 year to more 

than 275 years. The median traveltime to wells ranged from 

0.2 to 25 years indicating the valley-fill aquifer is susceptible 

and vulnerable to contamination from overlying land uses. 

Approximately 73 percent of the traveltimes were less than 10 

years, 92 percent of the traveltimes were less than 25 years, 98 

percent of the traveltimes were less than 45 years, and about 1 

percent of the traveltimes were greater than 60 years.

Model Limitations and Uncertainties

The ground-water flow model for the Pomperaug River 

Basin regional study area was designed to delineate areas contributing recharge to public-supply wells, to help guide data 

collection, and to support future local modeling efforts. The 

model represents the general ground-water flow characteristics 

of the study area with some limitations including representation of steady-state conditions and the spatial distribution of 

aquifer parameters.

Water-level hydrographs and computed water budgets 

indicate the Pomperaug River valley-fill aquifer was generally 

in steady-state equilibrium for 1997–2001, although the data 

are not conclusive. Other uses of the model, such as assessing 

water-management alternatives or transient simulation of flow 

paths and water budgets, may not be appropriate without further calibration for transient conditions. Also, the model may 

not be appropriate for local-scale delineation of flow paths and 

rates, such as near local areas of ground-water contamination.

Particle-tracking simulations were done routinely during 

model calibration and indicated the contributing areas to wells 

did not change appreciably for the ranges of adjusted properties. Also, reduction of the grid size had a limited effect on 

contributing areas to wells except for the UW1 well, which 

received some water from the southeast for the finer grid (fig. 

6.10) but not for the coarser grid. The observation that contributing areas did not change appreciably with variations in 

model characteristics adds support to the areas shown in figure 

6.10. A formal uncertainty analysis, such as one described by 

Starn and others (2000), however, would be appropriate for 

delineation of wellhead-protection zones. The contributing 

areas to bedrock wells could change appreciably with refinements in bedrock properties and, particularly, recharge rates to 

till (Lyford and others, 2003).

Uncertainty is associated with simulated traveltimes 

because of uncertain porosity values and hydraulic conductivities of individual geologic units and the geometry of highly 

conductive zones, which were generalized in the model. 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 will change computed traveltimes 

from recharge to discharge areas in direct proportion to 

changes of effective porosity because there is an inverse linear 

relation between ground-water flow velocity and effective 

porosity and a direct linear relation between traveltime and 

effective porosity. For example, a one-percent decrease in 

porosity will result in a one-percent increase in velocity and a 

one-percent decrease in particle traveltime. A detailed sensitivity analysis of porosity distributions was beyond the scope 

of this study, although future work could compare simulated 
Hydrogeologic Setting and Ground-Water Flow Simulations, Pomperaug River Basin Regional Study Area, Connecticut 6–23

Figure 6.11. Model-computed flow paths, areas contributing recharge to public-supply wells, and gaining and losing stream 

reaches, Pomperaug River Basin regional study area, Connecticut.

84

6

84

6

Bear Hill

Orenaug

Hills

East Hill

Pomperaug

River

Transylvania

Brook

Hesseky

Brook

Nonnewaug

River

East

Spring

Brook

Weekeepeemee

River

Bullet Hill Brook

South Brook

RIVER

HOUSATONIC

Woodbury

Pomperaug

R O X B U R Y

B R I D G E W A T E R

N E W 

M I L F O R D

W A S H I N G T O N

B E T H L E H E M W A T E R T O W N

W O O D B U R Y

M I D D L E B U R Y

O X F O R D

S O U T H B U R Y

N E W T O W N

B R O O K F I E L D

LITCHFIELD COUNTY

NEW HAVEN COUNTY

LITCHFIELD COUNTY

FAIRFIELD COUNTY

NEW HAVEN COUNTY

FAIRFIELD COUNTY

WF

UW1

UW2 W1

WP

HV

RM

HH WK

TC

NHS

QH

41° 30'

41° 35'

73° 20' 73° 15' 73° 10'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

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

73° 30' West, North American Datum of 1983

0 1 2 3 4 5 6 KILOMETERS

0 1 2 3 MILES

EXPLANATION

Area contributing recharge to well or well field

Extent of valley fill

Simulated reach of stream

 Gaining

 Losing

Urban

Pathlines outlining zones of contribution

 to public-supply wells

Extent of active model cells

QH Discharging well and identifier
6–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

ground-water traveltimes to ground-water ages to more thoroughly evaluate effective porosity values.

The Pomperaug River Basin regional ground-water flow 

model uses justifiable aquifer properties and boundary conditions and provides a reasonable representation of ground-water 

flow conditions in the study area for 1997–2001. The model 

has been helpful for refining concepts about area-wide groundwater flow patterns and water budgets in the study area for the 

time period of interest but may not be suitable for long-term 

predictive simulations. This regional model provides a useful 

tool to evaluate aquifer vulnerability at a regional scale, to 

facilitate comparisons of ground-water traveltime between 

regional aquifer systems, and to guide future detailed investigations in the study area.

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6–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

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00–315, 27 p. 
Hydrogeologic Setting and Ground-Water 

Flow Simulations of the Great Miami River 

Basin Regional Study Area, Ohio

By Rodney A. Sheets

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 7 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
Suggested citation:

Sheets, R.A., 2007, Hydrogeologic setting and ground-water flow simulations of the Great Miami Basin Regional 

Study Area, Ohio, section 7 of Paschke, S.S., ed., THydrogeologic settings and ground-water flow simulations for 

regional studies of the transport of anthropogenic and natural contaminants to public-supply wells—studies begun in 

2001: Reston, Va., U.S. Geological Survey Professional Paper 1737–A, pp. 7–1 – 7–24.

U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

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U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.
iii

Contents

Abstract...................................................................................................................................................... 7–1

Introduction................................................................................................................................................ 7–1

Purpose and Scope ......................................................................................................................... 7–1

Study Area Description................................................................................................................... 7–3

Conceptual Understanding of the Ground-Water System................................................................. 7–3

Geology.............................................................................................................................................. 7–3

Ground-Water Occurrence and Aquifer Properties .................................................................. 7–5

Recharge and Discharge................................................................................................................ 7–5

Ground-Water Flow Directions, Depth to Water, and Hydraulic Gradients........................... 7–5

Ground-Water Quality ..................................................................................................................... 7–9

Ground-Water Flow Simulations ............................................................................................................ 7–9

Modeled Area and Spatial Discretization.................................................................................. 7–11

Boundary Conditions and Model Stresses................................................................................ 7–11

Aquifer Hydraulic Properties ....................................................................................................... 7–12

Model Calibration........................................................................................................................... 7–12

Comparison of Models......................................................................................................... 7–12

Model Zonation, Sensitivity Analysis, and Parameter Estimation................................ 7–13

Model-Computed Water Budget........................................................................................ 7–18

Simulation of Areas Contributing Recharge to Public-Supply Wells .................................... 7–19

Model Limitations and Uncertainties ......................................................................................... 7–19

References Cited..................................................................................................................................... 7–21

Figures

Maps showing:

7.1. Location of the Great Miami River Basin regional study area 

within the glacial aquifer system. .........................................................................7–2

7.2. Topograpy, hydrologic features, and locations of public-supply wells, 

Great Miami River Basin regional study area, Ohio...........................................7–4

7.3. Generalized geologic and hydrogeologic sections showing (A) geology, 

(B) ground-water flow directions, and (C) geochemical conditions 

within the buried valleys around Dayton, Ohio.............................................................. 7–8

7.4. Map showing location of ground-water flow model grid and parameterestimation zones, Great Miami River Basin regional study area, Ohio. .................. 7–10

Graphs showing:

7.5. Composite scaled sensitivity of ground-water flow model 

parameters, Great Miami River Basin regional study area, Ohio. ................ 7–15

7.6. Relation between model-computed and measured hydraulic heads, 

Great Miami River Basin regional study area, Ohio......................................... 7–16

7.7. Weighted residuals plotted against weighted simulated equivalents, 

Great Miami River Basin regional study area, Ohio......................................... 7–17

7.8. Map showing model-computed areas contributing recharge for 60 

public-supply wells, Great Miami River Basin regional study area, Ohio............... 7–20
iv

Tables

7.1. Summary of hydrogeologic and ground-water quality 

characteristics for the glacial aquifer system and the 

Great Miami River Basin regional study area, Ohio...................................................... 7–6

7.2. Comparison of root-mean-squared error and mean-absolute difference 

of model-computed and measured hydraulic heads between the original 

ground-water flow model and the revised parameter-estimation model, 

Great Miami River Basin regional study area, Ohio.................................................... 7–13

7.3. Comparison of model-computed and measured streamflow gains 

or losses between the original ground-water flow model and 

the revised parameter-estimation model, Great Miami River Basin 

regional study area, Ohio. ............................................................................................... 7–14

7.4. Parameters used in construction of the revised parameterestimation ground-water flow model, Great Miami River Basin 

regional study area, Ohio. ............................................................................................... 7–14

7.5. Root-mean-squared error and mean-absolute difference between 

model-computed and measured hydraulic heads in the revised 

parameter-estimation ground-water flow model, Great Miami River Basin 

regional study area, Ohio. ............................................................................................... 7–17

7.6. Comparison of model-computed and measured streamflow gains 

or losses between the original ground-water flow model and the 

revised parameter-estimation model, Great Miami River Basin 

regional study area, Ohio. ............................................................................................... 7–18

7.7. Water budget computed by the revised parameter-estimation model 

for 1997–2001 average conditions, Great Miami River Basin 

regional study area, Ohio. ............................................................................................... 7–18
Hydrogeologic Setting and Ground-Water Flow 

Simulations of the Great Miami River Basin Regional 

Study Area, Ohio

By Rodney A. Sheets

Abstract

The transport of anthropogenic and natural contaminants 

to public-supply wells was evaluated for the glacially derived 

valley-fill aquifer underlying the Great Miami River and its 

tributaries near Dayton, Ohio, as part of the U.S. Geological 

Survey National Water-Quality Assessment Program. The 

glacial valley-fill aquifer in the Great Miami River regional 

study area is representative of the glacial aquifer system in the 

North-Central United States. Water needs in the study area for 

industry, agriculture, and public water supply are met almost 

entirely by pumping from the glacial aquifer, and the aquifer 

is susceptible and vulnerable to contamination. An existing 

three-layer, steady-state ground-water flow model of the study 

area was modified to include some bedrock islands within 

the glacial valleys and recalibrated with parameter estimation to represent average ground-water flow conditions for the 

period from 1997 to 2001. The calibrated model and advective particle-tracking simulations were used to compute areas 

contributing recharge and traveltimes from recharge areas to 

60 public-supply wells. Model results indicate streamflow loss 

from streams (39 percent of inflow) and precipitation (39 percent of inflow) provide most of the ground-water inflow, while 

the majority of ground-water discharge is to pumping wells 

(53 percent of outflow) and gaining stream reaches (40 percent 

of outflow). Median simulated traveltimes from recharge areas 

to wells ranged from 21 days to 184 years. Approximately 

73 percent of the traveltimes were less than 25 years indicating water quality in the aquifer is susceptible to the affects of 

overlying land use.

Introduction

The Great Miami River Basin regional study area for the 

transport of anthropogenic and natural contaminants to public-supply wells (TANC) study is located in the east-central 

portion of the White River-Great and Little Miami River Basin 

National Water-Quality Assessment (NAWQA) study unit 

(fig. 7.1). Nationwide, the glacial aquifer system is the largest 

in areal extent of any principal aquifer and is an important 

source of water for public water supply providing public and 

domestic water for approximately 41 million people in 2000 

(Warner and Arnold, 2005).

Purpose and Scope

The purpose of this Professional Paper section is to present the hydrogeologic setting of the Great Miami River Basin 

regional study area. The section also documents the setup and 

calibration of a steady-state regional ground-water flow model 

for the study area. Ground-water flow characteristics, pumping-well information, and water-quality data were compiled 

from existing data to develop a conceptual understanding of 

ground-water conditions in the study area. An existing groundwater flow model was modified to include some bedrock 

islands within the glacial valleys and was recalibrated with 

parameter estimation to represent average conditions for the 

period from 1997 to 2001. The 5-year period 1997–2001 was 

selected for data compilation and modeling exercises for all 

TANC regional study areas to facilitate future comparisons 

between study areas. The recalibrated ground-water flow 

model and associated particle tracking were used to simulate 

advective ground-water flow paths and to delineate areas 

contributing recharge to selected public-supply wells. Groundwater traveltimes from recharge to public-supply wells, 

oxidation-reduction (redox) conditions along flow paths, and 

the presence of potential contaminant sources in areas contributing recharge were tabulated into a relational database as 

described in Section 1 of this Professional Paper. This section 

provides the foundation for future ground-water susceptibility 

and vulnerability analyses of the study area and comparisons 

among regional aquifer systems.
7–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 7.1. Location of the Great Miami River Basin regional study area within the glacial aquifer system.

O H I O I N D I A N A

M I C H I G A N

K E N T U C K Y

W E S T

V I R G I N I A

V I R G I N I A

ILLINOIS

Lake

Michigan

Lake Erie

C A N A D A

Dayton

Cincinnati

Columbus

Cleveland

Detroit

Lexington

Charleston

Indianapolis

Chicago

88° 87° 86° 85° 84° 83° 82° 81° 

42°

41°

40°

39°

38°

37°

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 25 50 75 100 kilometers

0 25 50 miles

EXPLANATION

Great Miami River Basin regional study area

Glacial deposits aquifer—Darker areas represent sand, gravel, and valley-fill aquifers locally

USGS NAWQA study unit—White River-Great and Little Miami River Basins

Southern limit of Pleistocene continental glaciation
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–3

Study Area Description

The study area is centered on the city of Dayton, Ohio 

(fig. 7.2), and examines the effects of pumping unconfined 

ground water from the unconsolidated, glacially derived valley-fill aquifer underlying the Great Miami River and its tributaries. The Great Miami River Basin regional study area represents the glacial aquifer system (Warner and Arnold, 2005) in 

the North-Central United States (table 7.1) with ground water 

occurring in the valley-fill glacial aquifer underlying the Great 

Miami River and its tributaries. The study area includes the 

confluence of the Great Miami River and Mad River at Dayton 

(1,700 km2) and several tributaries to the Great Miami River, 

including the Stillwater River (1,750 km2). The study area also 

includes the parts of the upper Little Miami River drainage 

basin. In the Great Miami River Basin regional study area, 

water needs for industry, agriculture, and public water supply 

are met almost entirely by pumping from the glacial aquifer.

The primary aquifer within the study area consists of 

Quaternary glacial deposits overlying Ordovician and Silurian bedrock (Dumouchelle, 1998). The glacial deposits are 

primarily a result of glacial meltwater or outwash deposits 

left by retreating continental glaciers. The most productive 

aquifers in the White-Miami study unit are those that were 

deposited in buried-valley settings underlying the Great Miami 

River (fig. 7.2). The buried-valley aquifer in the study area is 

heavily used by industry and municipalities with well yields 

commonly greater than 5,300 m3/d (Dumouchelle, 1998). 

These high pumping rates often induce infiltration from 

nearby rivers or artificial recharge lagoons. The buried-valley aquifer has been designated a Sole-Source Aquifer by the 

U.S. Environmental Protection Agency (Debrewer and others, 

2000). Low permeability Ordovician shale with well yields 

less than approximately 6 m3/d underlies the buried-valley 

aquifer beneath most of the study area; Silurian limestone 

and dolomite form a thin carbonate aquifer that underlies the 

buried-valley aquifer in the higher elevations of the study area 

(Dumouchelle, 1998).

The study area is in the Till Plains section of the Central 

Lowland Physiographic Province. The topography of the till 

plains was formed by several continental glaciations resulting in a flat to gently rolling land surface (Fenneman, 1938). 

Bedrock features formed by pre- and periglacial drainage 

systems were buried under the glacial deposits (Dumouchelle, 

1998). In areas where modern rivers dissect the land surface, 

topographic relief is low to moderate, with steep-walled valleys formed by the river drainages. Surface drainage through 

the study area is from north to south, toward the Ohio River. 

Average annual precipitation is 96.5 cm (Harstine, 1991).

Even though Dayton lies near the center of the study 

area (fig. 7.2), approximately 44 percent of the land use in 

the study area (2001) is agricultural (row crops, pasture, and 

so forth); about 41 percent of the land use in the study area 

is developed. Primarily, the upper reaches of the subbasins 

are agricultural, and the areas along the main drainages are 

suburban to urban. The remaining land uses are forested or 

grasslands (13 percent) and wetlands, quarries, or open water 

(2 percent) (Homer and others, 2004).

Water use in the study area consists almost entirely of 

ground-water supplies for domestic, agricultural, industrial 

and public-supply users. In 1993, Dayton supplied approximately 285,000 m3

/d of water to the areas in and around the 

city with two well fields (Dumouchelle, 1998). The Dayton 

Rohrers’ Island well field lies along the Mad River, just south 

of Wright Patterson Air Force Base, and supplied approximately 190,000 m3

/d. The Miami River well field, the second 

Dayton well field, is located along the Great Miami River and 

consists of about 50 wells that pumped ground water at the 

rate of approximately 95,000 m3/d in 1993. The remaining 

water use in the study area, approximately 245,000 m3/d, is 

provided by other public ground-water supplies (for example, 

Wright Patterson Air Force Base, smaller cities, and hospitals), 

industrial ground-water supplies, and agricultural groundwater supplies (Dumouchelle, 1998).

Conceptual Understanding of the 

Ground-Water System

Ground-water flow is controlled by the geology and the 

hydraulic properties of the geologic materials. Areal recharge 

and discharge to streams in this system are the primary inputs 

and outputs to this system; the ground-water chemistry seems 

to be controlled by the residence time (from recharge to 

discharge) and geology. The generalized geologic section in 

figure 7.3 illustrates features of the conceptual model for the 

Dayton study area.

Geology

Surficial geology of the study area is dominated by Wisconsinan glacial deposits. Glacial till (ground moraine) covers 

most of the bedrock in upland areas. The clay-rich tills are 

unstratified and poorly sorted; grain size ranges from clay size 

to boulders. Some thin gravel deposits can be found interspersed within the till cover.

Glacial deposits cover the bedrock in the buried river 

valleys. Illinoian glacial deposits may underlie the Wisconsinan deposits in the deepest areas of the buried valleys (Dumouchelle, 1998). The glacial deposits range from 

fine-grained sand to gravel with some glacial till interspersed 

within as sheets that sometimes extend across the buried valleys (Dumouchelle, 1998).

The buried-valley floor and walls consist of Late Ordovician interbedded shale and limestone and form the base of 

the buried-valley aquifer. The limestone beds typically are 

thin—from less than a centimeter to several centimeters thick, 

and typically account for about 25 percent of the Ordovician 

rocks (Eberts and George, 2000). In upland areas, the Brassfield Formation (Early Silurian) overlies the Ordovician rocks 
7–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 7.2. Topography, hydrologic features, and locations of public-supply wells, Great Miami River Basin regional 

study area, Ohio.

70

40

127

49

48

75

675

70

71

40

68

42

68

4

35

35

Miami

Well

Field

Rohrers

Island

Well Field

Rohrers

Island

Wolf

Creek

Stillwater

River

Great

Miami

River

Great

Miami

River

Little

Miami

River

Mad

River

D A Y T O N X E N I A

S P R I N G F I E L D

M I D D L E T O W N

Wright Patterson

Air Force Base

DARKE COUNTY

PREBLE COUNTY MONTGOMERY COUNTY

MIAMI COUNTY

MONTGOMERY COUNTY

BUTLER COUNTY

PREBLE COUNTY

PREBLE COUNTY

MONTGOMERY COUNTY

GREENE COUNTY

CLARKE COUNTY

MIAMI COUNTY CLARKE COUNTY

CLARKE COUNTY

CHAMPAIGN COUNTY

WARREN COUNTY

GREENE COUNTY

CLINTON COUNTY

39° 45'

39° 30'

40° 00'

84° 30' 84° 15' 84° 00' 83° 45'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

37° 50' North and 41° 10' North, central meridian 84° West,

North American Datum of 1983

0 5 10 15 20 25 30 KILOMETERS

0 5 10 15 MILES

EXPLANATION

Land elevation, in meters above sea level

Extent of model grid

Extent of active model cells

Buried glacial valley

Public-supply well or pumping center

3600

3200

2800

2400

2000

1600

1200

800

400

0
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–5

(Dumouchelle, 1998). The Brassfield Formation consists of 

fossiliferous, fine-grained limestone beds that range from massive to irregularly bedded (Sheets and Yost, 1994). Overlying 

the Brassfield Formation in the study area are thinly bedded 

Silurian shale and limestone formations.

The study area lies over the axis of the Cincinnati arch, 

a bedrock high formed between the Appalachian and Illinois 

Basins (Casey, 1994, 1997). The bedrock at the axis of the 

arch essentially has zero dip.

Ground-Water Occurrence and Aquifer 

Properties

The clay-rich tills that cover the upland areas in the study 

area are generally thin (less than 9 m) and poorly permeable–

wells completed in these units yield from 11 to 65 m3/d 

(Norris and others, 1948, 1950; Schmidt, 1986, 1991). Vertical 

hydraulic conductivity of the till ranges from approximately 4 

X10-3 to 43 m/d (Dumouchelle, 1998). Typically, wells in the 

upland unconsolidated deposits are completed in sand “stringers.” Ground-water flow in the upland unconsolidated deposits 

is toward small streams or local pumping centers.

The coarse sand and gravels in the glacial deposits are 

as much as 90 m thick in the center of the valleys and yield 

as much as 11,500 m3/d of water to wells (Norris and others, 

1950). Hydraulic conductivities range from 860 to 1.1X106

m/d (Dumouchelle, 1998, table 2) based on more than 30 multiple-well aquifer tests. Transmissivities have been reported as 

much as 65,000 m2/d but generally range from 280 to 6,500 

m2/d (Dumouchelle, 1998). Where laterally continuous tills 

are present within the glacial deposits, the outwash deposits 

are separated into two or more aquifers, and the lower aquifers 

may be confined or semiconfined by the till layers (Norris 

and Spieker, 1966). Porosity in the glacial deposits has been 

estimated from 0.15 to 0.25 (Cunningham and others, 1994; 

Sheets and others, 1998). In the absence of pumping, groundwater flow in the glacial deposits is lateral and upward toward 

the major streams in the valleys. Ground-water flow can be 

reversed and streams can lose water to the aquifer near areas 

such as Dayton where pumping rates are large.

Generally, the Ordovician bedrock is not considered an 

aquifer—most wells drilled into these rocks yield less than 6 

m3/day and drawdown is generally very large (Dumouchelle, 

1998). Only near the subcrop of the Ordovician units, where 

weathering has created some secondary permeability in fractures and bedding planes, is the permeability high enough to 

support localized domestic water supplies (hydraulic conductivity of approximately 430 m/d; Dumouchelle and others, 

1993). Sheets and others (1998) showed that excess radiogenic 

helium found in 3Hydrogen-3Helium samples might indicate 

some ground-water flow from the Ordovician bedrock through 

the valley walls and into the glacial deposits (fig. 7.3). Wells 

in the Brassfield Formation and overlying formations ordinarily yield about 30 to 90 m3

/d, which is generally adequate 

for domestic water supplies in the uplands (Sheets and Yost, 

1994). Springs occur at the base of the Brassfield Formation 

and at the top of the shale units above the Brassfield (Sheets 

and Yost, 1994).

Recharge and Discharge

Recharge to the Great Miami River Basin regional study 

area is primarily through direct precipitation and infiltration, 

but recharge also occurs from surface-water infiltration and 

inflow from bedrock (Dumouchelle, 1998). Recharge estimates for the glacial deposits are from water-budget analyses 

(31.5 cm/yr; Walton and Scudder, 1960), recession-curve 

analyses (31.5 to 40.0 cm/yr; Dumouchelle and others, 1993) 

and ground-water flow modeling (8 to 31 cm/yr; Dumouchelle 

and others, 1993; Dumouchelle, 1998). Recharge estimates 

for the upland areas (2.5 to 15 cm/yr) are lower than estimates 

for the glacial deposits because of lower permeability soils 

and till (Sheets, 1994). Particle-tracking analyses show the 

majority of recharge to the ground-water system is from direct 

precipitation and infiltration to the glacial deposits and from 

the upland areas (Cunningham and others, 1994). Additional 

sources of recharge are induced infiltration from streams 

near pumping wells and, to a much lesser extent, inflow from 

the Ordovician bedrock. Some recharge to the ground-water 

flow systems occurs at the boundary between the valleys and 

the bedrock hills, where surface-water runoff flows from the 

low-permeability tills to much higher permeability glacial 

deposits (Sheets, 1994; Dumouchelle, 1998). Recharge to the 

glacial deposits from bedrock is generally considered negligible, relative to the amount of recharge from other sources 

(Dumouchelle, 1998).

Under natural flow conditions, the major streams and 

rivers within the glacial deposits are the primary discharge 

areas for the regional ground-water flow system (Yost, 1995; 

Dumouchelle, 1998; Sheets, 1994). However, ground water 

in the study area is heavily pumped for water supply, and this 

pumping locally alters natural ground-water flow conditions in 

the glacial deposits. Because most of the large pumping centers are near the major cities and rivers (for example, Dayton), 

induced infiltration from streams lessens the effect of pumping 

on regional ground-water flow.

Ground-Water Flow Directions, Depth to Water, 

and Hydraulic Gradients

Dumouchelle (1998) compiled water-level data from 

678 wells to assess ground-water levels and flow directions 

in the buried-valley aquifer for September 1993. Wells were 

completed at varying depths within the glacial deposits. 

Ground-water flow directions in the buried-valley aquifer are 

generally toward the major rivers and downvalley toward the 

south/southwest. Horizontal hydraulic-head gradients in the 

center part of the buried valley and away from the discharge 

areas (rivers, pumping centers) are approximately 0.0006 m/m; 

in pumping areas (Miami Well Field, for example) horizon-
7–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 7.1. Summary of hydrogeologic and ground-water-quality characteristics for the glacial aquifer system and the Great Miami 

River Basin regional study area, Ohio.

[m, meters; cm/yr, centimeters per year; m3/s, cubic meters per second; m3/d, cubic meters per day; km, kilometers; Kh, horizontal hydraulic conductivity; 

Kz, vertical hydraulic conductivity; Sy, specific yield; n, porosity; mg/L, milligrams per liter]

Characteristic Glacial aquifer system Great Miami River Basin regional study area

Geography

Topography Relief generally less than 300 m. (Randall, 2001). Relief approximately 200 m.

Climate Precipitation 91 to 127 cm/yr; evapotranspiration 46 

to 58 cm/yr (Randall, 1996).

Precipitation 100 cm/yr; evapotranspiration up to 

67 cm/yr (Harstine, 1991; Debrewer and others, 

2000).

Surface-water hydrology Runoff 41 to 76 cm/yr (Randall, 1996); streamflow 

varies widely with the size of drainage basin. 

Water-supply reservoirs and former mill ponds are 

common in upland and valley settings.

Runoff 31 cm/yr (Debrewer and others, 2000); 

average flow in Great Miami River at Dayton is 

96 m3/s (Shindel, and others, 2002). Some watersupply reservoirs are present in upper reaches. 

Land use Urban, suburban, rural residential, woodlands, 

farmland.

Urban, suburban, rural residential, woodlands, 

farmland.

Water use Potential aquifer yields generally less than 60,500 

m3/d (Kontis and others, 2004).

Pumpage for public supply about 510,000 m3/d. 

Aquifer yields range from 300 to as much as 

11,000 m3/d (Dumouchelle, 1998).

Geology

Surficial geology Glacially-derived sand and gravel in valleys that 

slope away from retreating ice sheets; limited 

fine-grained deposits; till prevalent in uplands but 

discontinuous under valley fill (Randall and others, 

1988; Randall, 2001).

Mainly glacial alluvial sand and gravel in buried 

bedrock valleys; till covers uplands and is 

interspersed in valley fill (Dumouchelle, 1998).

Bedrock geology Crystalline granitic and metamorphic rocks and 

sedimentary rocks; limited carbonate rocks 

(Randall, 2001; Randall and others, 1988).

Uplands underlain by limestone/dolomite; buried 

valleys underlain by shales and limestones 

(Dumouchelle, 1998).

Ground-water hydrology

Aquifer conditions Valley-fill aquifers that are generally less than 2.5 km 

wide and are unconfined; valley fill generally less 

than 67 m thick; depth to water generally less than 

15 m. Streams that cross valley fill from upland 

areas are commonly sources of recharge; pumping 

near surface water commonly induces infiltration 

(Kontis and others, 2004).

A valley-fill aquifer that is generally less than 3 km 

wide and unconfined; valley fill generally less 

than 100 m thick; depth to water generally less 

than 15 m. Areal recharge dominates with some 

leakage in from bedrock. Induced infiltration 

from streams where pumping is nearby. 
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–7

Characteristic Glacial aquifer system Great Miami River Basin regional study area

Hydraulic properties Valley fill: Kh = 6 to 150 m/d; Kh/Kz = 10:1 

(commonly); n = 0.3 to 0.4; Sy = 0.2 to 0.3

Till: Kh = 0.003 to 3 m/d; Kh/Kz = 1; n = 0.1 to 0.3; 

Sy = 0.04 to 0.28

Bedrock: Kh = 0.003 to 0.3 m/d; Kh/Kz (limited 

information); n = 0.005 to 0.02; Sy = 0.0001 

to 0.005

(Randall and others, 1988; Bradbury and others, 

1991; Melvin and others, 1992; Gburek and others, 

1999).

Valley fill: Kh = 0.1 to 150 m/d; n = 0.15 to 0.25; Kh/

Kz estimated at10:1. 

Till: Kh = 0.02 to 3 m/d; n = 0.15 to 0.25

Bedrock: K = 0.001 – 1.5 m/d.

(Dumouchelle, 1998; Sheets and others, 1998). 

Ground-water hydrology—Continued

Ground-water budget Recharge to valley fill from infiltration of 

precipitation, 36 to 76 cm/yr. Recharge to valley 

fill from upland runoff often exceeds recharge 

from precipitation. (Kontis and others, 2004; 

Morrissey and others, 1988). Pumpage generally 

less than 15 percent of water budget; most 

discharge is to streams (Morrissey, 1983; Tepper 

and others, 1990; Dickerman and others, 1990; 

Dickerman and others, 1997; Mullaney and 

Grady, 1997; Starn and others, 2000; Barlow and 

Dickerman, 2001; DeSimone and others, 2002.)

Recharge to valley fill from infiltration of 

precipitation, 8 to 40 cm/yr. Recharge increases 

along valley walls from upland runoff. Pumpage 

for public supply greater than 25 percent of 

water budget; where induced infiltration doesn’t 

occur, most ground water discharges to streams. 

(Dumouchelle, 1998). 

Ground-water quality

Dissolved solids less than 150 mg/L in crystallinerock terrains and greater than 150 mg/L in 

sedimentary-rock terrains; pH, 6 – 8; oxic. Calcium 

and bicarbonate are the principal ions (Rogers, 

1989). Redox conditions not defined regionally.

Calcium and bicarbonate are the principal dissolved 

ions. Redox conditions are typically oxic in 

shallow valley fill, suboxic to anoxic in deep 

valley fill and in bedrock (Rowe and others, 1999; 

this study).

Table 7.1. Summary of hydrogeologic and ground-water-quality characteristics for the glacial aquifer system and the Great Miami 

River Basin regional study area, Ohio.—Continued

[m, meters; cm/yr, centimeters per year; m3/s, cubic meters per second; m3/d, cubic meters per day; km, kilometers; Kh, horizontal hydraulic conductivity; 

Kz, vertical hydraulic conductivity; Sy, specific yield; n, porosity; mg/L, milligrams per liter]
7–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 7.3. (A) geology, (B) ground-water flow directions, and (C) geochemical conditions within the buried valleys around 

Dayton, Ohio.

Vertical scale greatly exaggerated

Datum is sea level

Southwest Northeast

100

125

150

175

200

225

250

275

300

325

METERS

800

100

200

300

400

500

600

700

FEET

0 1,000 2,000 3,000 4,000 meters

0 4,000 8,000 12,000 feet

Vertical scale greatly exaggerated

Datum is sea level

Southwest Northeast

100

125

150

175

200

225

250

275

300

325

METERS

800

100

200

300

400

500

600

700

FEET

0 1,000 2,000 3,000 4,000 meters

0 4,000 8,000 12,000 feet

Vertical scale greatly exaggerated

Datum is sea level

Southwest Northeast

100

125

150

175

200

225

250

275

300

325

METERS

800

100

200

300

400

500

600

700

FEET

0 1,000 2,000 3,000 4,000 meters

0 4,000 8,000 12,000 feet

Wetland

Domestic

well

Great Miami River Tributary

Public-supply well

Public-supply well

Industrial

waste

Septic

systems

A. Generalized geologic section

B. Generalized flow patterns

C. Generalized oxidation-reduction conditions

EXPLANATION

GEOLOGY

Glacial deposits

 Clay and till

 Sand and gravel

Bedrock

 Silurian carbonates

 Ordovician shale with 

 limestone

OXIDATION-REDUCTION

 CONDITIONS

 Oxygen and/or nitrate 

 reduction (iron less 

 than 100 micrograms 

 per liter)

Manganese and/or iron

 reduction 

Iron reduction with low 

 sulfate (iron greater 

 than 100 micrograms 

 per liter)

GROUND-WATER FLOW

 Ground-water flow 

 direction
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–9

tal hydraulic-head gradients are about 0.001 m/m. Near the 

edge of the buried valley, adjacent to the uplands, horizontal 

hydraulic-head gradients commonly are greater than 0.0003 

m/m.

Water levels for the uplands were not measured by 

Dumouchelle (1998), but previous work at Wright Patterson 

Air Force Base indicates the ground-water potentiometrichead surface mimics land-surface topography in the uplands 

(Schalk, 1992). Ground water flows roughly radial off of 

upland highs and toward the center of the major river valleys 

(Dumouchelle, 1998).

Because the ground-water and surface-water systems are 

generally connected in the study area, depth to ground water 

often is directly related to land-surface topography. Near the 

rivers and streams, depth to ground water commonly is just a 

few feet. Away from the rivers, as elevation increases, depth 

to ground water generally increases; maximum depth to water 

away from the river is approximately 15 m, under natural 

conditions. In areas of heavy pumping, depth to water can be 

greater than 30 m. The saturated thickness of the buried-valley 

aquifer also varies in relation to proximity to the axis of the 

buried valley and in relation to pumping centers. Near the axis 

of the valley, the maximum depth to bedrock is approximately 

90 m; therefore, the maximum buried-valley aquifer saturated 

thickness is about 80 m. Depth to water in the upland bedrock aquifer is generally between 6 and 9 m (Schalk, 1992). 

Saturated thickness of the upland bedrock aquifer also varies 

in relation to topography but generally is about 15 m.

Ground-Water Quality

Ground-water quality in the study area has been divided 

into two compositional groups—calcium-magnesium-bicarbonate (Ca-Mg-HCO3

) and sodium-chloride (NaCl) type 

waters (Lloyd and Lyke, 1995; Dumouchelle and others, 1993; 

Debrewer and others, 2000). Water from the unconsolidated 

deposits is predominantly Ca-Mg-HCO3, and water from the 

bedrock ranges from NaCl to Ca-Mg-HCO3 type water.

Within the unconsolidated deposits, only subtle variations in major cation concentrations were observed between 

shallow, intermediate, and deep wells (Dumouchelle and others, 1993). Shallow ground water (less than 18 m below land 

surface) had higher mean temperatures, specific conductances, 

and dissolved-solids concentrations than ground water from 

deep (20 to 70 m below land surface) wells. Median groundwater pH from the unconsolidated deposits was 7.3.

Ground water from the bedrock deposits in the study area 

varies greatly in its composition. Ordovician shale produces 

exclusively NaCl-type water with highly variable calcium, 

magnesium, and bicarbonate concentrations. Median pH of 

bedrock ground water from Ordovician shale was 7.4. Groundwater quality in the Brassfield limestone, however, is similar 

to ground-water quality in the glacial deposits consisting of 

Ca-Mg-HCO3 type water with a similar pH range of 7.1 to 7.6 

(Dumouchelle and others, 1993).

Dissolved oxygen is typically present only in ground 

water from the shallow glacial deposits (Dumouchelle and 

others, 1993). Bedrock wells rarely yield water with any 

measurable dissolved oxygen (greater than 0.1 mg/L). The 

dissolved oxygen in the shallow aquifers tends to react quickly 

with organic material in glacial sediments and causes reducing conditions that promote dissolution of iron and manganese 

oxyhydroxide minerals. Under these low-oxygen and circumneutral pH conditions that are typical of the buried-valley 

sediments, iron or manganese concentrations can increase in 

excess of several milligrams per liter (Debrewer and others, 

2000). Ground-water concentrations of nitrate greater than 

a few milligrams per liter are present in shallow, oxygenated parts of the buried-valley aquifers (Debrewer and others, 

2000; fig. 7.3), which also are characterized by relatively short 

ground-water residence times (less than 5 to 10 years) (Rowe 

and others, 1999). Nitrate in the shallow parts of aquifers in 

the study area can be reduced to nitrogen gas by denitrification 

processes as ground-water flows from the oxygenated recharge 

areas to iron-reducing parts of the buried-valley aquifer (Rowe 

and others, 1999; fig. 7.3).

Ground-Water Flow Simulations

A numerical ground-water flow model was developed for 

the glacial deposits in the Great Miami River Basin regional 

study area by Dumouchelle (1998) (fig. 7.4). Revisions to the 

steady-state model were made during this study. The following is a brief description of the previously developed model 

including the original modeled area, boundary conditions, 

aquifer properties, model stresses, modifications to the original model, and rationale for the changes.

The original model was developed using MODFLOW88 

(McDonald and Harbaugh, 1988), MODFLOWARC (Orzol 

and McGrath, 1992), and ARC/INFO (Environmental Systems Research Institute, 1987). For this study, the model input 

parameters were translated into files compatible with MODFLOW-2000 (Harbaugh and others, 2000; Hill and others, 

2000) using MODFLOW-GUI (Shapiro and others, 1997; 

Winston, 2000), a graphical user interface for MODFLOW2000 (Argus Interware, 1997).

The original conceptual model was largely based on previous hydrogeologic investigations and analysis of modeling 

performed at Wright Patterson Air Force Base (Dumouchelle, 

1998). The original model simulated ground-water flow only 

in the buried-valley aquifer because the underlying Ordovician 

bedrock and bedrock uplands were not considered significant 

sources of water to the buried-valley aquifer. The buried-valley aquifer was simulated using three model layers of varying 

thickness, and the till layers within the aquifer were represented implicitly by reducing horizontal and vertical hydraulic 

conductivity in locations where tills are present (Dumouchelle, 

1998).
7–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 7.4. Location of ground-water flow model grid and parameter-estimation zones, Great Miami River Basin 

regional study area, Ohio.

70

40

127

49

48

75

675

70

71

40

68

42

68

4

35

35

Rohrers

Island

Wolf

Creek

Stillwater

River

Great

Miami

River

Great

Miami

River

Little

Miami

River

Mad

River

D A Y T O N

X E N I A

S P R I N G F I E L D

M I D D L E T O W N

Wright Patterson

Air Force Base

DARKE COUNTY

PREBLE COUNTY MONTGOMERY COUNTY

MIAMI COUNTY

MONTGOMERY COUNTY

BUTLER COUNTY

PREBLE COUNTY

PREBLE COUNTY

MONTGOMERY COUNTY

GREENE COUNTY

CLARKE COUNTY

MIAMI COUNTY CLARKE COUNTY

CLARKE COUNTY

CHAMPAIGN COUNTY

WARREN COUNTY

GREENE COUNTY

CLINTON COUNTY

39° 45'

39° 30'

40° 00'

84° 30' 84° 15' 84° 00' 83° 45'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

37° 50' North and 41° 10' North, central meridian 84° West,

North American Datum of 1983

0 5 10 15 20 25 30 KILOMETERS

0 5 10 15 MILES

EXPLANATION

Parameter-estimation zones

 Edge (EDGE)

 Buried valley (BV)

 Uplands (UP)

 Oakwood (OAK)

Urban

Extent of model grid

Extent of active model cells

Buried valley—Darker green underlies urban area
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–11

The original model extended laterally to the 800-ft 

topographic contour around the valley because this contour 

roughly approximates the knick point between the land surface 

of the river valleys and the uplands. In some areas, the model 

was extended into the uplands to account for substantial 

(greater than 15 m) thickness of sand and gravel deposits 

(Dumouchelle, 1998). Bedrock islands within the active area 

of the model (see “Uplands” parameter-estimation zones, 

fig. 7.4) were not represented in the original model.

The original model simulates steady-state conditions, as 

observed from water-level and streamflow gain/loss data for 

late 1993. The revised TANC model simulates these same conditions, as well as those from 1997 through 2001, using waterlevel data taken from various sources for 1997–2001. The 

revised model includes two steady-state stress periods with the 

same model stresses (recharge, river stage and conductance, 

and so forth) as the original model, except that pumping rates 

were updated for 1997–2001.

Modeled Area and Spatial Discretization

The original active modeled area covers approximately 

620 km2 and is shown in figure 7.4. The original finite-difference model grid was spatially discretized into 230 rows and 

370 columns, corresponding to cells 152.4 m on each side. 

The model grid was oriented 25 degrees north of east. The 

original model grid spacing and orientation were not changed 

by this study.

The ground-water flow system was simulated using three 

model layers. Layer 1 is simulated as unconfined, with the 

top representing the ground-water surface and bottom set to 

the altitude of the uppermost clay layer, an equivalent altitude to the clay layer, or the bedrock surface. Layers 2 and 3 

were simulated as confined. The bottom of layer 2 was set to 

approximately 46 m below the estimated water level or the 

bedrock altitude. The bedrock valley floor defined the bottom of layer 3 (Dumouchelle, 1998). The vertical connection 

between model layers was simulated by a vertical leakance 

parameter.

Boundary Conditions and Model Stresses

No-flow boundaries were used to simulate the Ordovician bedrock-valley walls and floor (Dumouchelle, 1998). The 

steepness of the valley walls created some numerical instabilities in the original (and revised) model, as narrow or very thin 

model layers were created during the automatic population of 

the model grid using MODFLOWARC. Numerical instabilities 

occurred at the junction between the buried-valley aquifer and 

uplands or near the four upland “islands” within the modeled 

area (see “Uplands” parameter estimation zones in fig. 7.4). 

Similar problems occurred after transferring the model to 

Argus (Argus Interware, 1997). To decrease numerical instability, the four bedrock islands were simulated using hydraulic 

conductivities and recharge rates comparable to those given 

by Sheets and others (1998), who demonstrated that changing 

the conceptualization of bedrock hills in the Dayton area can 

improve calibration of numerical ground-water flow models.

Numerical instability in the original model also occurred 

in the vicinity of the city of Oakwood (fig. 7.4). The Oakwood 

wells are located in a “hanging valley”—a glacially formed 

valley that is higher in altitude than the primary buried valley. This area was originally simulated as two layers, with 

pumping primarily in the second (lower) layer. In the revised 

model, the Oakwood area was modified to include only one 

active model layer, and hydraulic conductivity of the layer was 

assigned as a composite of the original two layers.

At several locations along the edge of the active model 

layers, specified-head boundaries were used to represent 

downvalley flow into or out of the modeled area. Specified-head boundaries were typically located in narrow sections of bedrock valleys and far away from the pumping 

areas, to minimize the effect of boundaries on the simulations (Dumouchelle, 1998). The specified-head boundaries 

remained unchanged in the revised model.

Stresses on the aquifer system consisted of recharge, 

rivers, drains, and pumping/recharging wells. The original and 

revised models are nearly identical in terms of how recharge 

(except for the bedrock islands), rivers, and drains are simulated. After calibration, recharge in the original model ranged 

from 15 to 31.0 cm/yr. During the transfer from ARC/INFO to 

Argus in the revised model, recharge was increased by a small 

percentage (less than 10 percent) in some model cells near the 

valley walls to increase numerical stability.

Rivers and larger streams were simulated with the 

MODFLOW River package (McDonald and Harbaugh, 1988). 

River stage and river-bottom altitude were obtained by surveying, supplied survey data, U.S. Geological Survey (USGS) 

topographic maps, or estimates from Geographic Information 

Systems (GIS) (Dumouchelle, 1998) and were unchanged in 

the revised model. Values of riverbed hydraulic conductivity 

for the rivers and streams in the model ranged from 0.09 to 

4.3 m/d (Dumouchelle, 1998, p. 20). Drains were used to 

simulate many streams in the study area, specifically those 

marked as intermittent on USGS topographic maps. Drains 

can only remove water from the system, using a drain conductance value (McDonald and Harbaugh, 1988). Drain conductance was not altered from the original model and ranged from 

0.0007 to 21.5 m2/d (most values were 0.003 m2/d).

In 1993, pumping data were collected for 281 nonresidential pumping wells and 3 recharge wells. As a result of 

adjustments for model grid size, area, and layering, 187 pumping wells were simulated in the original model at 138 modelcell locations. The total pumping for the original model was 

approximately 500,000 m3/d.

Ground-water pumping data for wells in the study area 

were collected for 1997–2001 from State of Ohio files. Most 

of these wells were the same as wells simulated in the original 

model, and well locations, screen lengths, and model grid cells 

in the revised model were the same as in the original model. 

Some of the wells in the 1997–2001 data set were previously 
7–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

unused wells, and the locations and screen lengths were taken 

from either USGS water-use files (on file at USGS Ohio Water 

Science Center, Columbus) or Ohio Department of Natural 

Resource-Division of Water well-log files. In a few cases 

where inadequate information was obtained from the wateruse files, location and screen-length information was obtained 

from the well owner or a State or local agency. Ground-water 

pumping data for well fields (for example, Rohrer’s Island 

Well Field) was reported as a single value; the pumping rate 

for an individual well in the well field was apportioned pumping on a weighted basis of flow, relative to the specific capacity reported. To obtain the pumping rate for a particular well, 

the total volume reported for the well field was multiplied by 

the specific capacity of the well divided by the sum of specific 

capacity for all wells in the well field.

Pumping-rate data for all the wells for 1997–2001 were 

averaged to obtain average pumping rates representative of the 

time period. In the revised model, 309 pumping centers were 

simulated (fig. 7.2); the number of pumping nodes simulated 

in model layers 1, 2, and 3 were 131, 153, and 25, respectively. 

The total pumping for the second steady-state stress period 

of the revised model was approximately 500,000 m3/d, which 

is the same as the pumping rate used for the first steady-state 

stress period, although the spatial distribution of pumping was 

slightly different for the two different stress periods.

Aquifer Hydraulic Properties

Layer 1 in the original model was simulated as an unconfined layer, and horizontal hydraulic-conductivity values in 

the original calibrated model ranged from 1.6X10-3 to 140 m/d 

(Dumouchelle, 1998). The lowest values were near the edge 

of the buried valley near the bedrock subcrop, and the highest 

values were concentrated in the main valleys (Dumouchelle, 

1998). The original model uses the Block-Centered Flow 

(BCF) package in MODFLOW-96 (Harbaugh and McDonald, 1996). The revised model uses the Layer Property Flow 

(LPF) in MODFLOW-2000 (Harbaugh and others, 2000). The 

LPF package requires that an unconfined layer be simulated 

as convertible between unconfined and confined flow conditions. This does not make an effectual change in the internal 

solutions to the ground-water flow equation, as the top of 

layer 1 in the revised model was assigned to the land-surface 

elevation, and water levels in layer 1 did not rise above land 

surface.

In the original model, layers 2 and 3 were simulated as 

confined layers using the BCF package. Assigned transmissivities ranged from 0.09 m2

/d to approximately 3,900 m2/d 

in layer 2 and from 0.09 m2/d to 2,800 m2/d in layer 3. These 

transmissivity values represent hydraulic-conductivity values 

ranging from approximately 1.2 X 10–3 to 1.6 X 10–2 m/d 

(Dumouchelle, 1998). In the revised model, the LPF package 

requires that hydraulic conductivity and thickness, not transmissivity, are assigned to grid cells. The original GIS layers 

of hydraulic conductivity and thickness (tops and bottoms 

of model layers) were available and were used to assign the 

appropriate values in the revised model.

A vertical conductance value was used to simulate 

hydraulic connection between model layers in the original 

model; the discontinuity of the clay layers did not allow for 

direct simulation of confining units. In areas where clay layers were present, vertical hydraulic conductivity was set to 

3.5 X 10–5 m/d (Dumouchelle, 1998). In areas where no clay 

layer was present, vertical conductance was calculated using 

one-tenth of the horizontal hydraulic conductivity, weighted 

for the thickness of grid cells above and below. In the revised 

model, the LPF package allowed use of a vertical hydraulicconductivity value, and vertical hydraulic conductivity was set 

to one-tenth of the horizontal hydraulic conductivity.

Model Calibration

Calibration of the revised model consisted of several 

steps including evaluation and reevaluation of input values of 

hydraulic parameters (as previously discussed), comparisons 

of original model to revised model output heads and flows, 

sensitivity analysis, and parameter estimation. With each step 

of the calibration process, hypotheses about the hydrologic 

system were tested. Some of these hypotheses tested were 

local scale (well field) and some were regional scale (buried 

valley), with the goal of calibrating the model to represent 

average conditions for 1997–2001.

Comparison of Models

Upon reconstruction of the original model, including 

modifying the isolated bedrock hills and changing the flow 

package to accommodate MODFLOW-2000, the model was 

recalibrated to 1993 conditions. The model calibration to 

1993 conditions was evaluated by comparing model-computed 

and measured hydraulic heads for each layer and comparing 

model-computed ground-water discharge to gain-loss data 

collected from selected river reaches. The root-mean-squared 

error (RMSE) and the mean-absolute difference (MAD), 

which are statistical measures of the variance and bias, respectively, were used to evaluate the model calibration. The RMSE 

was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of wells used in the computation.
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–13

The MAD was calculated using:

where abs indicates the absolute value of the expression. The 

heads calculated by the ground-water flow model were interpolated to their relative position within the grid cell.

Table 7.2 shows the total number of measured hydraulichead values changed in all three layers during reconstruction 

of the original model. In an attempt to isolate the numerical 

instability in the original model, slight changes were made 

to the bottom of layer 1, especially in the uplands, which 

changed the layer in which some head observations and pumping wells were located. In a few locations, observations and 

wells originally in layer 2 were reassigned to layer 1. In one 

case, a layer 3 well was reassigned to layer 2. Four pumping 

wells in the city of Oakwood were changed from layer 2 to 

layer 1.

The RMSE and MAD values for the revised model are 

higher for layer 1, nearly the same for layer 2, and somewhat 

lower for layer 3 than for the original model, and the overall 

(average) RMSE and MAD are slightly higher for the revised 

model than for the original model. Differences between 

model-computed and measured hydraulic heads in the vicinity of the Oakwood pumping wells affected the MAD and 

RMSE for layer 1 and the entire model. In the original model, 

the Oakwood measured hydraulic heads were in layer 2, but 

the measured hydraulic heads were in layer 1 of the revised 

model; inclusion of these points in layer 1 of the revised model 

produces a higher RMSE and MAD than the original model. 

There also was a large difference between model-computed 

and measured hydraulic heads for the Oakwood well field in 

the original model, which Dumouchelle (1998) attributed to 

(1) error in spatial distribution of pumping, (2) large grid size 

(measured hydraulic heads and pumping well within same 

cell), (3) measured hydraulic-head location near the pumping wells, or (4) a combination of these and other factors. The 

same factors likely affected model-computed hydraulic heads 

in the revised model.

Table 7.3 presents a comparison of model-computed and 

measured streamflows for the two versions of the model for 

the first steady-state period. The revised parameter-estimation 

model-computed streamflow gains and losses were roughly 

equivalent to those computed by the original model, although 

the model-computed flow from the original model more 

closely matched the measured streamflow than the revised 

model for the Great Miami River from Needmore Road to 

Railroad and for Little Beaver Creek.

Model Zonation, Sensitivity Analysis, and 

Parameter Estimation

Because the revised model was constructed with MODFLOW-2000, parameter estimation (Hill and others, 2000) was 

used to assess and improve performance of the revised model. 

An additional 34 measured hydraulic-head values were available for 1997–2001, so a second steady-state stress period was 

added to the model for that period. Some water-level measurements were averaged over the period and some were single 

measurements. All water-level measurements from both stress 

periods were weighted according to the range and accuracy of 

water levels and confidence in measuring average conditions. 

Some wells were within the immediate influence of drawdown 

from pumping wells, and water levels from these wells were 

weighted lower than wells distal from pumping because the 

distal wells were more representative of regional conditions. 

Streamflow measurements from 1993 were weighted with a 

coefficient of variation according to the error in consecutive 

downstream measurements (based on subjective estimates 

by the measurement taker; for example, Excellent, 2 percent; 

Table 7.2. Comparison of root-mean-squared error and mean-absolute difference of model-computed 

and measured hydraulic heads between the original ground-water flow model (Dumouchelle, 1998) and 

the revised parameter-estimation model, Great Miami River basin regional study area, Ohio. 

[N, number of observations; RMSE, root-mean-squared error in meters; MAD, mean absolute difference in meters; 

—, not applicable]

Layer N

(original)

N

(modified)

RMSE

(original)

RMSE

(revised)

MAD

(original)

MAD

(revised)

1 303 311 2.23 4.88 1.37 2.07

2 259 252 3.08 3.01 1.98 2.10

3 17 16 2.69 2.03 2.07 1.46

Total1 579 579 — — — —

Weighted* 

averages

— — 2.62 3.99 1.66 2.07

*

Total RMSE and MAD values are weighted averages. 
7–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Good, 5 percent; Fair, 8 percent; Poor, more than 8 percent 

[Rantz and others (1982)].

The modeled area was divided into four zones representing different hydrologic conditions to evaluate each area’s sensitivity to model input parameters. The four parameter-estimation zones in the revised model are (1) the main buried valley 

(BV); (2) the edge of the main buried valley, next to the upland 

areas (EDGE); (3) the newly modified upland areas (UP); 

and (4) the Oakwood area (OAK) (fig. 7.4). Model sensitivity 

to the input parameters of horizontal hydraulic conductivity, 

recharge, river conductance, and vertical hydraulic conductivity are compared among the four parameter-estimation zones.

After reconstructing the original model in MODFLOW2000 as described in the “Initial Calibration” section, the 

model input parameters of horizontal and vertical hydraulic conductivity, recharge, and riverbed conductance were 

parameterized within the MODFLOW-2000 framework. 

MODFLOW-2000 multiplier arrays were created for each 

parameter in each layer for each of the two stress periods. 

The original model output was recreated by using a multiplier 

value of 1.0 for horizontal hydraulic conductivity in layers 1, 

2, and 3 and for recharge in all parameter-estimation zones. A 

multiplier value of 0.1 was used for vertical hydraulic conductivity to represent vertical hydraulic conductivity as one-tenth 

of horizontal hydraulic conductivity. The riverbed hydraulic 

conductivity was also parameterized using the same conductance values as in the original model. A list of parameters used 

for each parameter-estimation zone is in table 7.4.

Table 7.3. Comparison of model-computed and measured streamflow gains or losses between the 

original ground-water flow model (Dumouchelle, 1998) and the revised parameter-estimation model, 

Great Miami River Basin regional study area, Ohio.

[units in m3/d, cubic meters per day; WPAFB, Wright Patterson Air Force Base]

Streamflow gain or loss (1993)

Stream reach Measured Model computed 

(original)

Model computed 

(revised)

Great Miami River, Taylorsville Dam to 

Needmore Road

+0.481 –0.139 –0.033

Great Miami River, Needmore Road to 

Railroad

–0.983 –0.949 +0.0006

Mad River, Huffman Dam to Harshman Road –2.24 –1.55 –1.45

Little Miami River from Dayton-Xenia Road 

to Narrows Park

+0.439 +0.425 –0.405

Hebble Creek, WPAFB to Mad River –0.008 –0.006 –0.006

Little Beaver Creek, Research Road to 

Factory Road

–0.062 +0.042 +0.031

Table 7.4. Parameters used in construction of the revised parameter-estimation ground-water flow 

model, Great Miami River Basin regional study area, Ohio.

Parameter Layer Main buried 

valley

Edge of main 

buried valley Uplands Oakwood

Horizontal hydraulic 

conductivity

1 HK1_BV HK1_EDGE HK1_UP HK1_OAK

2 HK2 HK2 HK2 HK2

3 HK3 HK3 HK3 HK3

Vertical hydraulic 

conductivity

1 VK1 VK1 VK1 VK1

2 VK2 VK2 VK2 VK2

3 VK3 VK3 VK3 VK3

Recharge* RCH_BV RCH_EDGE RCH_UP RCH_OAK

River conductance RIV_BV RIV_UP

*

Recharge also was parametized separately for stress period 2 (1997–2001); parameters have a suffix of 2 (for 

example, RCH_UP2).
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–15

The revised model was run in sensitivity mode to 

determine the relative effect a parameter might have on the 

weighted residuals (difference between model-computed and 

measured heads and flows). Figure 7.5 shows the composite 

scaled sensitivities of all parameters for the two steady-state 

stress periods. Composite scaled sensitivities are used to 

evaluate whether the available observations provide enough 

information for parameter estimation (Hill and others, 2000). 

The most sensitive parameters in the modified model are 

shown in red on figure 7.5 and include the horizontal hydraulic 

conductivity in layer 1 of the main part of the buried valley 

(HK1_BV), recharge to the buried valley (RCH_BV) and 

the edges of the buried valley (RCH_EDGE), and the river 

conductance of that part of the river which overlies the buried 

valley (RIV_BV). The range of composite scaled sensitivities 

indicates that parameter estimation should be able to estimate 

all of the parameters. If the composite scaled sensitivities 

ranged over an order of magnitude or more, the optimization 

procedure may have difficulty estimating values for the least 

sensitive parameters.

All parameters were input to the parameter-estimation 

mode of MODFLOW-2000 to determine which parameters of 

the nonlinear regression are highly correlated. Highly correlated parameter pairs are problematic in parameter estimation because of the difficulty in determining unique values for 

these parameters (Hill and others, 2000). Preliminary results of 

the nonlinear regression indicate that a few of the values chosen for regression are highly correlated to each other (r2

>0.85). 

The highly correlated pairs are as follows: HK1_EDGE and 

RCH_EDGE, and RCH_OAK and HK1_OAK. HK1_EDGE 

was fixed using an interim value obtained during preliminary model runs; this value was used in the final parameter 

estimation and was not allowed to vary with the parameter 

estimation, whereas RCH_EDGE was estimated because 

it had a somewhat higher composite scaled sensitivity than 

HK1_EDGE. RCH_OAK and HK1_OAK had relatively low 

composite scaled sensitivities (fig. 7.5) and were fixed using 

values obtained during preliminary model runs.

Based on relative sensitivity and correlation of parameters, six parameters (HK1_BV, HK2, RCH_BV, RCH_UP, 

RCH_EDGE, and RIV_BV) were chosen for final parameter estimation, where the least-squares objective function 

(derived from the sum of squared, weighted residuals between 

model-computed and measured values) is minimized using 

Figure 7.5. Composite scaled sensitivity of ground-water flow model parameters, Great Miami River Basin regional study 

area, Ohio.

0

2

4

6

8

10

12

Composite scaled sensitivity

Parameter name (see table 4)

HK1_OAK

HK1_BVHK1_UP

HK1_EDGE

HK2HK3

RCH_OAK

RCH_BVRCH_UP

RCH_EDGE

RIV_BVRIV_UP

VK1VK2

RCH_OAK2

RCH_BV2RCH_UP2

VK3

RCH_EDGE2

EXPLANATION

Most sensitive model parameters

Less sensitive model parameters
7–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

the modified Gauss-Newton method (Hill, 1998). During each 

parameter-estimation model simulation, each parameter value 

is modified by MODFLOW-2000 by using their sensitivities, 

and new parameter values are input to the model to calculate a 

new objective function. No prior information was used in the 

nonlinear regression. Parameter estimation was run with a low 

primary convergence criterion (0.01) and a low convergence 

criterion (0.001).

Figure 7.6 shows graphs comparing model-computed and 

measured hydraulic heads for both stress periods, by layer, 

for the results of the parameter-estimation simulations. The 

1:1 line shows where the results would plot if the model-computed heads exactly matched the measured heads for the stress 

periods. The correlation coefficient between model-computed 

and measured hydraulic heads is 0.865, which indicates a reasonable model fit. Figure 7.7 presents the weighted residuals 

compared to the weighted simulated equivalents for both head 

and streamflow observations and shows that the two variables 

are independent and that the weighted residuals are scattered 

evenly about 0.0 (Hill, 1998).

The calculated error variance and standard error for the 

final calibrated model are 152.6 and 12.4, respectively. A 

standard deviation of 0.22 m (variance = 0.15 m) was used 

to calculate weights for the majority of head observations, so 

the fitted standard error is 2.7 m and represents the overall fit 

achieved for these hydraulic heads. A calculation of the RMSE 

and MAD for each layer for stress period 1 (1993) and stress 

period 2 (1997–2001) is shown in table 7.5. When the results 

of stress period 1 are compared to the original and revised 

model (from table 7.2), a slight decrease in the overall MAD 

and RMSE can be seen, indicating the parameter-estimation 

resulted in a slightly improved model with respect to hydraulic 

heads. A coefficient of variation of 0.10 (10 percent) was used 

to calculate the weights associated with streamflow measurements (1993), so the fitted coefficient of variation of 1.24 (124 

percent) represents the overall fit with streamflow measurements. Table 7.6 shows the model-computed and measured 

streamflow from the calibrated parameter-estimation model. 

The coefficient of variation and direct comparisons with measurements indicate streamflow is not well represented by this 

model, and the representation of streamflow is not as good as 

in the original Dayton-area model (Dumouchelle, 1998). Low 

weights were applied to streamflow data in the parameterestimation simulations, which indicates confidence in these 

measurements is low, and likely resulted in the poorer representation of streamflow in the revised model.

Figure 7.6. Relation between model-computed and measured 

hydraulic heads, Great Miami River Basin regional study area, 

Ohio.

1:1 line

1:1 line

200

220

240

260

280

300

Model-computed head elevation, in meters

Measured head elevation, in meters

200 220 240 260 280 300

STRESS PERIOD 2—1997–2001

200

220

240

260

280

300

Model-computed head elevation, in meters

Measured head elevation, in meters

200 220 240 260 280 300

200

220

240

260

280

300

Model-computed head elevation, in meters

Measured head elevation, in meters

200 220 240 260 280 300

STRESS PERIOD 1—1993

EXPLANATION

Layer 1 Layer 2 Layer 3
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–17

Figure 7.7. Weighted residuals plotted against weighted simulated equivalents, Great Miami River Basin 

regional study area, Ohio.

Table 7.5. Root-mean-squared error and mean-absolute difference between model-computed and 

measured hydraulic heads in the revised parameter-estimation ground-water flow model, 

Great Miami River Basin regional study area, Ohio.

[N, number of observations; RMSE, root-mean-squared error in meters; MAD, mean absolute difference in meters; 

SP1—Stress period 1 (1993 measurements); SP2—Stress period 2 (1997–2001 measurements); —, not applicable]

Layer N

(SP1)

N

(SP2)

RMSE

(SP1)

RMSE

(SP2)

MAD

(SP1)

MAD

SP2)

1 311 22 3.04 3.90 1.63 2.96

2 252 12 2.58 4.18 1.73 2.62

3 16 — 1.67 — 1.14 —

Total 579 34 — — — —

Weighted* 

averages

— — 2.80 4.00 1.66 2.84

*

Total RMSE and MAD values are weighted averages.

–75

–50

–25

0

25

50

75

100

Weighted residual

Weighted simulated equivalents

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400

EXPLANATION

Streamflow measurements

Head measurements

 Stress period 1 (1993)

 Stress period 2 (1997–2001)
7–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

The modified Beale measure is used to test linearity of a 

model, especially if the model’s linear confidence and prediction intervals are to be used. The modified Beale’s measure of 

this model (using the F-statistic of 2.1689) is 0.146, indicating 

the model is somewhat nonlinear with respect to the parameters. If Beale’s measure is greater than 0.46, the model is 

nonlinear; if Beale’s is less than 0.041, the model is effectively 

linear. These results are particularly applicable if this model 

will be used in predictive simulations where linear confidence 

intervals on predictions are to be used.

Model-Computed Water Budget

The water budget simulated by the calibrated parameterestimation model (table 7.7) indicates less than one percent 

error in the steady-state-model water balance. Recharge to the 

modeled area is from losing stream reaches (38.9 percent of 

inflow), precipitation (38.8 percent of inflow), and downvalley 

ground-water underflow (22.3 percent of inflow). Discharge 

from the modeled area is to pumping wells (53.5 percent of 

outflow), gaining stream reaches (40.1 percent of outflow), 

and downvalley ground-water underflow (6.4 percent of 

outflow). The model-computed water balance is a reasonable 

approximation of the conceptual-model water balance.

Table 7.6. Comparison of model-computed and measured streamflow gains or losses between the original 

ground-water flow model (Dumouchelle, 1998) and the revised parameter-estimation model, Great Miami River 

Basin regional study area, Ohio.

[units in m3/d, cubic meters per day]

Streamflow gain or loss (1993)

Stream reach Measured Simulated 

(original)

Simulated

(parameter estimation)

Great Miami River, Taylorsville Dam to 

Needmore Road

+0.481 –0.139 –0.191

Great Miami River, Needmore Road to 

Railroad

–0.983 –0.949 –0.752

Mad River, Huffman Dam to Harshman Road –2.24 –1.55 –1.31

Little Miami River from Dayton-Xenia Road 

to Narrows Park

+0.439 +0.425 –0.489

Hebble Creek to Mad River –0.008 –0.006 –0.011

Little Beaver Creek, Research Road to 

Factory Road

–0.062 +0.042 +0.040

Table 7.7. Water budget computed by the revised parameter 

estimation model for 1997–2001 average conditions, Great Miami 

River Basin regional study area, Ohio.

[m3/d, cubic meters per day]

Water-budget component Flow

(m3/d)

Percentage of 

inflow or outflow

Model inflow

Downvalley flow into the 

modeled area

224,000 22.3

Rivers 391,000 38.9

Precipitation 390,000 38.8

TOTAL 1,005,000 100

Model outflow

Downvalley flow out of the 

modeled area

64,100 6.4

Wells 538,000 53.5

Rivers 403,000 40.1

TOTAL 1,005,100 100
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–19

Simulation of Areas Contributing Recharge to 

Public-Supply Wells

The calibrated revised ground-water flow model was used 

to simulate areas contributing recharge for 60 public-supply 

wells and traveltimes from recharge areas to wells. The particle-tracking software MODPATH (Pollock, 1994) was used in 

conjunction with flux output from the revised flow model and 

a constant assumed effective porosity value of 0.2 to calculate 

flow paths and traveltimes. An effective porosity value of 0.2 

is reasonable for the study area on the basis of previous work 

(Cunningham and others, 1994). A nested rediscretization 

method for particle tracking near wells (Spitz, 2001) was used 

for the analysis of contributing areas to identify flow paths for 

individual wells. A grid spacing of approximately 50 m was 

used for the rediscretization. Properties from the calibrated 

model were used for the finer grid. The model-computed 

areas contributing recharge represent advective ground-water 

flow and do not account for mechanical dispersion. Advection-dispersion transport simulations would likely yield larger 

areas contributing recharge than advective particle-tracking 

simulations because the effects of dispersion caused by aquifer 

heterogeneity would be included.

The areas contributing recharge are presented in figure 

7.8, and several features of contributing areas are noteworthy.

•	 Areas contributing recharge can extend great distances 

from some wells.

•	 The areas contributing recharge and zone of contribution for wells with higher pumping rates are generally 

larger than those with lower pumping rates.

•	 Losing stream reaches coincide with several of the 

areas contributing recharge and likely affect the sizes 

of contributing areas.

•	 Zones of contribution often are similar to the areas contributing recharge, indicating that the primary source 

of water to those wells is water recharged at the water 

table.

Median simulated traveltimes from recharge areas to 

wells ranged from 21 days to 184 years; approximately 73.2 

percent of the traveltimes were less than 25 years. Generally, 

traveltimes are shorter for shallow well screens and longer 

for wells screened in the lower part of the aquifer. For deeper 

wells, pathlines are longer and zones of contribution and areas 

contributing recharge are more distal from the well than those 

for shallower wells. Zones of contribution and areas contributing recharge mostly originate upgradient and upvalley from 

the wellhead. In some areas around Dayton, where multiple 

wells are completed in close proximity to each other, nearly all 

the water recharged to the valley is withdrawn by production 

wells.

Model Limitations and Uncertainties

The purpose of the original ground-water flow model 

for the Great Miami River Basin regional study area was to 

provide a better understanding of the flow system in the valley-fill deposits. The purpose of the revised model was to aid 

in determining contributing areas to public-supply wells and 

ground-water traveltimes. Both models simulate steady-state 

conditions. Water-level data and computed water budgets 

indicate the Great Miami River valley-fill aquifer in the study 

area was generally in steady-state equilibrium for 1997–2001. 

However, further calibration for transient conditions may be 

needed to accurately represent temporal changes in the system. 

Also, there may be areas where much more detailed geologic 

information may be necessary to define local flow paths and 

traveltimes. Because of the regional nature of the modeling 

effort, some generalizations, including how surface-water bodies (streams) were treated in the model, may adversely affect 

traveltimes, especially from wells near streams.

Computed areas contributing recharge and traveltimes 

through zones of contribution are based on the calibrated 

revised model and a constant assumed effective porosity value 

of 0.2 for all three model layers. 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 will change computed traveltimes from recharge to 

discharge areas in direct proportion to changes of effective 

porosity because there is an inverse linear relation between 

ground-water flow velocity and effective porosity and a direct 

linear relation between the traveltime and effective porosity. For example, a one-percent decrease in porosity will 

result in a one-percent increase in velocity and a one-percent 

decrease in particle traveltime. A detailed sensitivity analysis 

of porosity distributions was beyond the scope of this study, 

although future work could compare simulated ground-water 

traveltimes to ground-water ages to more thoroughly evaluate 

effective porosity values.

The Great Miami River Basin regional ground-water 

flow model uses justifiable aquifer properties and boundary 

conditions and provides a reasonable representation of groundwater flow conditions in the study area for 1997–2001 average 

conditions. The model is suitable for evaluating regional water 

budgets and ground-water flow paths in the study area for the 

time period of interest but may not be suitable for long-term 

predictive simulations. This regional model provides a useful 

tool to evaluate aquifer vulnerability at a regional scale, to 

facilitate comparisons of ground-water traveltime between 

regional aquifer systems, and to guide future detailed investigations in the study area.
7–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 7.8. Model-computed areas contributing recharge for 60 public-supply wells, Great Miami River Basin regional 

study area, Ohio.

70

40

127

49

48

75

675

70

71

40

68

42

68

4

35

35

Rohrers

Island

Wolf

Creek

Stillwater

River

Great

Miami

River

Great

Miami

River

Little

Miami

River

Mad

River

D A Y T O N

X E N I A

S P R I N G F I E L D

M I D D L E T O W N

Wright Patterson

Air Force Base

DARKE COUNTY

PREBLE COUNTY MONTGOMERY COUNTY

MIAMI COUNTY

MONTGOMERY COUNTY

BUTLER COUNTY

PREBLE COUNTY

PREBLE COUNTY

MONTGOMERY COUNTY

GREENE COUNTY

CLARKE COUNTY

MIAMI COUNTY CLARKE COUNTY

CLARKE COUNTY

CHAMPAIGN COUNTY

WARREN COUNTY

GREENE COUNTY

CLINTON COUNTY

39° 45'

39° 30'

40° 00'

84° 30' 84° 15' 84° 00' 83° 45'

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

37° 50' North and 41° 10' North, central meridian 84° West,

North American Datum of 1983

0 5 10 15 20 25 30 KILOMETERS

0 5 10 15 MILES

EXPLANATION

Areas contributing recharge

 First to 25th percentile (highest quartile of pumping rates)

 26th to 50th percentile (second quartile of pumping rates)

 51st to 75th percentile (thrid quartile of pumping rates)

 76th to 100th percentile (lowest quartile of pumping rates)

Urban area

Pathlines outlining zones of contribution to public-supply wells

Extent of active model cells

Buried valley—Darker green underlies built-up urban area

Well location (percentile of pumping)

 First to 25th percentile

 26th to 50th percentile

 51st to 75th percentile

 76th to 100th percentile

Multiple well location

Other pumping wells
Hydrogeologic Setting and Ground-Water Flow Simulations of the Great Miami River Basin Regional Study Area, Ohio 7–21

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Randall, A.D., 2001, Hydrogeologic framework of stratifieddrift aquifers in the glaciated Northeastern United States: 

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water-quality trends in a buried-valley aquifer, Dayton 

area, southwestern Ohio: U.S. Geological Survey WaterResources Investigations Report 99–4113, 81 p.

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Geological Survey Open-File Report 95–357, 57 p.

Hydrogeologic Setting and Ground-Water 

Flow Simulations of the Eastern High Plains 

Regional Study Area, Nebraska

By Matthew K. Landon and Michael J. Turco

Professional Paper 1737–A

U.S. Department of the Interior

U.S. Geological Survey

Section 8 of

Hydrogeologic Settings and Ground-Water Flow Simulations for 

Regional Studies of the Transport of Anthropogenic and Natural 

Contaminants to Public-Supply Wells—Studies Begun in 2001

Edited by Suzanne S. Paschke
Suggested citation:

Landon, Matthew K., and Turco, Michael J., 2007, Hydrogeologic setting and ground-water flow simulation of the 

Eastern High Plains Regional Study Area, Nebraska, section 8 of Paschke, S.S., ed., Hydrogeologic settings and 

ground-water flow simulations for regional studies of the transport of anthropogenic and natural contaminants to 

public-supply wells—studies begun in 2001: Reston, Va., U.S. Geological Survey Professional Paper 1737–A, pp. 8–1 

– 8–28.

U.S. Department of the Interior

DIRK KEMPTHORNE, SECRETARY

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.
iii

Contents

Abstract...................................................................................................................................................... 8–1

Introduction................................................................................................................................................ 8–1

Purpose and Scope ......................................................................................................................... 8–1

Study Area Description................................................................................................................... 8–1

Topography and Climate ........................................................................................................ 8–4

Surface-Water Hydrology ..................................................................................................... 8–4

Land Use................................................................................................................................... 8–4

Water Use ................................................................................................................................ 8–4

Conceptual Understanding of the Ground-Water System................................................................. 8–5

Geology.............................................................................................................................................. 8–5

Ground-Water Occurrence and Flow........................................................................................... 8–8

Aquifer Hydraulic Properties ......................................................................................................... 8–9

Water Budget ................................................................................................................................... 8–9

Ground-Water Quality ................................................................................................................... 8–10

Ground-Water Flow Simulations .......................................................................................................... 8–11

Modeled Area and Spatial Discretization.................................................................................. 8–11

Boundary Conditions and Model Stresses................................................................................ 8–13

Aquifer Hydraulic Properties ....................................................................................................... 8–18

Model Calibration and Sensitivity ............................................................................................... 8–18

Model-Computed Hydraulic Heads ................................................................................... 8–20

Model-Computed Water Budget........................................................................................ 8–24

Simulation of Areas Contributing Recharge to Public-Supply Wells .................................... 8–24

Limitations and Appropriate Use of the Model......................................................................... 8–24

References Cited..................................................................................................................................... 8–26

Figures

Maps showing:

8.1. Location of the Eastern High Plains regional study area within 

the High Plains aquifer. ............................................................................................8–2

8.2. Topography, hydrologic features, and location of public-supply wells, 

Eastern High Plains regional study area, Nebraska..........................................8–3

8.3. Generalized hydrogeologic section showing ground-water flow and 

geochemical conditions, Eastern High Plains regional study area, Nebraska ........ 8–8

8.4. Map showing oxidation-reduction conditions in wells screened in 

the confined part of the High Plains aquifer, Eastern High Plains

regional study area, Nebraska ....................................................................................... 8–12
iv

8.5. Graph showing changes in concentration of oxidation-reduction 

sensitive species in three York public-supply wells from 1996, prior to 

withdrawals for public water supply, and for 1997–2002, when municipal 

withdrawals occurred...................................................................................................... 8–13

8.6. Map showing ground-water flow model grid boundary and selected 

boundary conditions in different model layers, Eastern High Plains 

regional study area, Nebraska. ...................................................................................... 8–14

8.7A. Hydrogeologic section showing hydraulic-conductivity zones and fluxboundary values for layers of calibrated ground-water flow model. ...................... 8–15

8.7B. Map showing hydraulic-conductivity and active-cell zones in layer 1 of 

calibrated ground-water flow model, Eastern High Plains regional study 

area, Nebraska.................................................................................................................. 8–16

8.8. Map showing distribution of recharge estimates used as ground-water 

flow model input, Eastern High Plains regional study area, Nebraska. .................. 8–19

8.9. Graph showing relation between model-computed and measured 

hydraulic head, Eastern High Plains regional study area, Nebraska ...................... 8–20

8.10. Map showing model-computed potentiometric surface in layer 4 and 

observation points and residuals in all layers, Eastern High Plains 

regional study area, Nebraska ....................................................................................... 8–21

8.11. Graph showing relation between head residuals and measured 

hydraulic head, Eastern High Plains regional study area, Nebraska ...................... 8–22

8.12. Hydrogeologic section showing model-computed hydraulic heads through 

row 100 of calibrated ground-water flow model, Eastern High Plains 

regional study area, Nebraska. ...................................................................................... 8–22

8.13. Map showing model-computed areas contributing recharge and 

zones of contribution for 12 public-supply wells, Eastern High Plains 

regional study area, Nebraska. ...................................................................................... 8–25

Tables

8.1. Summary of hydrogeologic and ground-water quality characteristics for the 

High Plains aquifer and the Eastern High Plains regional study area, Nebraska.... 8–6

8.2. Average ground-water pumping rates for public-supply wells, 1997–2001, 

Eastern High Plains regional study area, Nebraska. .................................................. 8–17

8.3. Model-computed water budget for 1997–2001 average conditions, 

Eastern High Plains regional study area, Nebraska. .................................................. 8–23
Hydrogeologic Setting and Ground-Water Flow Simulations 

of the Eastern High Plains Regional Study Area, Nebraska

By Matthew K. Landon and Michael J. Turco

Abstract

The transport of anthropogenic and natural contaminants to public-supply wells was evaluated in a part of the 

High Plains aquifer near York, Nebraska, as part of the U.S. 

Geological Survey National Water-Quality Assessment Program. The aquifer in the Eastern High Plains regional study 

area is composed of Quaternary alluvial deposits typical of 

the High Plains aquifer in eastern Nebraska and Kansas, is an 

important water source for agricultural irrigation and public 

water supply, and is susceptible and vulnerable to contamination. A six-layer, steady-state ground-water flow model of the 

High Plains aquifer near York, Nebraska, was constructed and 

calibrated to average conditions for the time period from 1997 

to 2001. The calibrated model and advective particle-tracking 

simulations were used to compute areas contributing recharge 

and traveltimes from recharge areas to selected public-supply 

wells. Model results indicate recharge from agricultural 

irrigation return flow and precipitation (about 89 percent of 

inflow) provides most of the ground-water inflow, whereas the 

majority of ground-water discharge is to pumping wells (about 

78 percent of outflow). Particle-tracking results indicate areas 

contributing recharge to public-supply wells extend northwest 

because of the natural ground-water gradient from the northwest to the southeast across the study area. Particle-tracking 

simulations indicate most ground-water traveltimes from areas 

contributing recharge range from 20 to more than 100 years 

but that some ground water, especially that in the lower confined unit, originates at the upgradient model boundary instead 

of at the water table in the study area and has traveltimes of 

thousands of years.

Introduction

The Eastern High Plains regional study area for the 

transport of anthropogenic and natural contaminants to public-supply wells (TANC) is within the High Plains Regional 

Ground Water study unit of the U.S. Geological Survey 

National Water-Quality Assessment (NAWQA) program near 

York, Nebraska (fig. 8.1). The study area is in the High Plains 

aquifer, which is an important water source for agricultural 

irrigation and drinking-water supply throughout the region and 

for York, Nebraska.

Purpose and Scope

The purpose of this Professional Paper Chapter is to 

present the hydrogeologic setting of the Eastern High Plains 

regional study area. The chapter also documents the setup and 

calibration of a steady-state regional ground-water flow model 

for the study area. Ground-water flow characteristics, pumping-well information, and water-quality data were compiled 

from existing data to develop a conceptual understanding of 

ground-water conditions in the study area. A six-layer steadystate ground-water flow model of the High Plains aquifer near 

York, Nebraska, was developed and calibrated for this study to 

represent average conditions for the period from 1997 to 2001. 

The 5-year period 1997–2001 was selected for data compilation and modeling exercises for all TANC regional study areas 

to facilitate future comparisons between study areas. The 

calibrated ground-water flow model and associated particle 

tracking were used to simulate advective ground-water flow 

paths and to delineate areas contributing recharge to selected 

public-supply wells. Ground-water traveltimes from recharge 

to public-supply wells, oxidation-reduction (redox) conditions along flow paths, and presence of potential contaminant 

sources in areas contributing recharge were tabulated into a 

relational database as described in Section 1 of this Professional Paper. This section provides the foundation for future 

ground-water susceptibility and vulnerability analyses of the 

study area and comparisons among regional aquifer systems.

Study Area Description

The Eastern High Plains regional study area encompasses 

388.5 km2 and is located in east-central Nebraska around 

the city of York (fig. 8.2). Ground water in the study area is 

contained within Quaternary alluvial deposits that compose 

the High Plains aquifer in eastern Nebraska and Kansas. The 

study area was chosen because the aquifer is used extensively for public water supply, is susceptible and vulnerable 
8–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 8.1. Location of the Eastern High Plains regional study area within the High Plains aquifer. 

M E X I C O

N E W

M E X I C O

T E X A S

O K L A H O M A

K A N S A S

C O L O R A D O

W Y O M I N G

N E B R A S K A

S O U T H D A K O T A

I O W A

M I N N E S O T A

M I S

S

O

U

R I

A

R

K

A

N

S

A

S

Sioux

Falls

Sioux

City

Omaha

Lincoln

Kansas

City

Topeka

Wichita

Tulsa

Oklahoma

City

Dallas Fort

Worth

Lubbock

Albuquerque Amarillo

Colorado

Springs

Denver

Cheyenne

109° 108° 107° 106° 105° 104° 103° 102° 101° 100° 99° 98° 97° 96° 95° 94° 93° 

41° 

40° 

42° 

43° 

39° 

38° 

37° 

36° 

35° 

34° 

33° 

32° 

Base from U.S. Geological Survey digital data,

1:2,000,000, 1972, Albers equal-area projection

0 50 100 150 200 kilometers

0 50 100 miles

EXPLANATION

Eastern High Plains regional study area

High Plains aquifer

 Quaternary units, undivided

 Tertiary units

 Ogallala Formation

 Arikaree Group

 Brule Formation

USGS NAWQA study unit—High Plains Regional Ground Water Study
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–3

Figure 8.2. Topography, hydrologic features, and location of public-supply wells, Eastern High Plains regional study 

area, Nebraska.

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Land elevation, in meters above sea level

Extent of active model cells

Beaver Creek perennial reach

York city limit

Public-supply well

3600

3200

2800

2400

2000

1600

1200

800

400

0
8–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

to contamination, and is representative of the High Plains 

aquifer (table 8.1). The rectangular study area was selected to 

facilitate ground-water flow modeling of the region upgradient from and around York and coincides with the area between 

two ground-water flow lines from a regional ground-water 

flow-model (COHYST, 2001).

Topography and Climate

The Eastern High Plains regional study area is located 

within a mostly flat lying region of windblown silt (loess) with 

relatively little dissection by streams (fig. 8.2, table 8.1). The 

study area includes portions of the upper Lincoln and Beaver 

Creek Basins, tributaries to the Big Blue River. The topography is typical of the extensive upland areas of the High Plains 

with low relief.

Mean annual precipitation at York for 1950–2001 is 71.1 

cm/yr (High Plains Regional Climate Center, 2003) with most 

of the precipitation falling during thunderstorms in the spring 

and fall (Verstraeten and others, 1998) (table 8.1). The High 

Plains generally has a middle-latitude dry continental climate 

with abundant sunshine, moderate precipitation, frequent 

winds, low humidity, and a relatively high rate of evaporation (Gutentag and others, 1984). Because evaporation rates 

usually exceed precipitation (table 8.1), there is little water 

available to recharge the aquifer (Luckey and Becker, 1999). 

Estimates of recharge rates from precipitation range from 

0.1 cm/yr in parts of Texas to 15.2 cm/yr in areas of dune sand 

in Kansas and Nebraska (Gutentag and others, 1984); average 

rates are about 1.5 cm/yr based upon regional water budgets 

(Luckey and others, 1986; Dennehy and others, 2002). The 

High Plains in eastern Nebraska and central Kansas have a 

humid continental climate that has slightly greater precipitation and humidity than the dry continental climate of the 

remainder of the High Plains and is therefore likely to have 

greater recharge from precipitation (table 8.1) (Dugan and 

Zelt, 2000).

Surface-Water Hydrology

The High Plains aquifer is in hydraulic connection with 

the major river systems crossing the aquifer from west to east 

(Weeks and others, 1988). During low-flow periods, water 

in the rivers is almost entirely derived from ground-water 

discharge. However, the major rivers derive most of their flow 

from the Rocky Mountains to the west (Dennehy and others, 

2002). Because evaporation rates exceed precipitation rates 

and topographic slopes are relatively flat, little water is available to produce surface-water runoff (Gutentag and others, 

1984; Litke, 2001).

There are no naturally perennial streams in the Eastern 

High Plains regional study area other than the lower reaches 

of Beaver Creek near the southeastern edge of the study area. 

Flows in Beaver Creek east of York (fig. 8.2) are maintained 

by discharges from the York wastewater plant (6,500 m3/d, 

1997–2001 average) and York Cold Storage (2,700 m3/d, 

1997–2001 average), which pumps ground water for cooling 

in western York and discharges the water to Beaver Creek. 

Low-flow streamflow measurements on Beaver Creek near 

the southeastern edge of the study area reported by Fallon and 

McChesney (1993) average about 5,600 m3/d. Subtracting the 

downstream measurement of 5,600 m3/d from the sum of the 

upstream inflow (9,200m3/d), implies a loss of about 3,600 

m3/d from Beaver Creek to the aquifer in the measured stream 

reach. Seasonally, flow in Beaver Creek may be greatest during the June through August irrigation season owing to irrigation return flows.

Land Use

Irrigated agriculture is the primary land use in the study 

area (85 percent of total land in the study area). Predominant 

crops in the study area, with their percentage of total land 

area in parentheses, are irrigated corn (50.0 percent); dryland 

corn (12.8 percent); irrigated soybeans (9.7 percent); dryland 

soybeans (5.6 percent); irrigated sorghum, alfalfa, and small 

grains (1.3 percent); and dryland sorghum, alfalfa, and small 

grains (3.9 percent) (Center for Advanced Land Management 

Information Technologies, 2000). The study area is within one 

of the most heavily irrigated parts of the High Plains aquifer 

(Thelin and Heimes, 1987; Qi and others, 2002). Irrigation 

well density in the study area is 2.0 wells/km2 compared to an 

average of about 0.4 well/km2 in the High Plains. Urban land 

uses, including commercial/industrial/transportation and low 

intensity, residential areas account for about 2.6 percent of the 

study area (U.S. Geological Survey, 1999–2000).

The population of the study area is approximately 9,400 

(U.S. Census Bureau, 2003) with an average population 

density of about 24.2 people/km2. The population of York is 

approximately 8,100 (U.S. Census Bureau, 2003), 86 percent 

of the total population in the study area. The only other community in the study area is Bradshaw (about 16 km west of 

York), with a population of approximately 330. Rural households account for about 10 percent of the population.

Water Use

Ground-water withdrawals for irrigation are the largest outflow from the ground-water system in both the High 

Plains aquifer and the Eastern High Plains regional study 

area (table 8.1). Irrigation withdrawals from the High Plains 

aquifer were about 72 million m3/d in 1995 and accounted 

for 96 percent of withdrawals from the High Plains aquifer 

(Dennehy and others, 2002). The average withdrawal rate over 

the entire irrigated area of the High Plains aquifer (approximately 55,000 km2

) was about 39 cm/yr in 1995. In the study 

area, withdrawal rates for irrigation were estimated at 25.4 

cm/yr for 1998 through 2002 on the basis of metered pumping reported to the Upper Big Blue Natural Resources District 

(NRD) in 50 to 150 wells per year (Rod DeBuhr, Upper Big 
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–5

Blue Natural Resources District, written commun., April 15, 

2003). Withdrawal rates for irrigation have changed through 

time with gradual decreases in withdrawal rates since the early 

1980s because of increased irrigation efficiency, conversion 

of gravity irrigation systems to center pivot irrigation systems, 

and wetter climatic conditions than in the 1970s and early 

1980s (Orville Davidson, Public Utilities Director, City of 

York, Nebraska, written comm., February 15, 2002).

Ground-water withdrawals for public-supply and industrial purposes account for less than 6 percent of withdrawals 

in both the Eastern High Plains regional study area and the 

High Plains aquifer (table 8.1). Ground water withdrawn from 

the High Plains aquifer is the source of drinking water for 100 

percent of the population in the study area and 82 percent of 

the people in the area underlain by the High Plains aquifer 

(Dennehy and others, 2002). Public-supply withdrawals in 

the study area increased by about 4 percent per year during 1997–2001, and average public-supply withdrawals for 

1997–2001 were about 15 percent greater than withdrawals 

for 1981–1996. Public-supply withdrawals fluctuate seasonally because of outdoor water use during the summer months. 

Average monthly withdrawals for May through September are 

about 65 percent greater than those for October through April 

for 1997–2001.

Withdrawals for commercial/industrial purposes slightly 

exceed those for public supply. Withdrawals for self-supplied 

domestic or livestock purposes were not quantified because 

they are considered negligible compared to other withdrawals 

(Upper Big Blue Natural Resources District, 1999).

Conceptual Understanding of the 

Ground-Water System

The conceptual model of ground-water flow for the 

Eastern High Plains regional study area was developed on the 

basis of data and interpretations of previous investigations 

including test-hole logs and hydrogeologic studies, water-level 

data, potentiometric maps, hydraulic-property measurements, 

measurements or estimates of pumping rates and irrigated 

areas, climatic data, and ground-water quality data. Average 

ground-water fluxes were estimated for 1997–2001.

Geology

The Quaternary-age sediments that compose the High 

Plains aquifer in the study area consist of heterogeneous, 

mostly fluvial deposits of sand, gravel, silt, and clay that 

form a layered sequence of unconfined and confined units 

with intervening confining units. About 70 geologic logs in 

the study area were assembled from test holes drilled by the 

Nebraska Conservation and Survey Division and the U.S. 

Geological Survey (Smith, 2000), wells drilled by the City 

of York (Orville Davidson, Public Utilities Manager, City of 

York, Nebraska, written commun., February 15, 2002), and 

registered wells (Nebraska Department of Natural Resources, 

2002) that fully penetrated the High Plains aquifer. Inspection 

of the logs led to the conceptualization of a 6-layer system 

(fig. 8.3).

Layer 1 is mostly unsaturated loess (Keech and others, 

1967; Swinehart and others, 1994) consisting of silty clay or 

clayey silt and ranging from 5 to 27 m thick with an average 

thickness of 16 m. The loess is thinnest in the valleys along 

Beaver and Lincoln Creeks, where a thin veneer of loess and 

soil overlies sand and gravel.

Layer 2 is sand and gravel with some discontinuous silt 

and clay. This layer is 6 to 43 m thick with an average thickness of 21 m and contains the coarsest gravels of all layers in 

the study area. Ground water in layer 2 is mostly unconfined, 

and the water table is at or just below the top of this unit. 

Depth to water ranges from 15 to 30 m below land surface. 

The sand and gravel deposits are sometimes fining downwards 

and contain abundant interbedded clays and silts, especially 

near the bottom of the unit. Layer 2 is continuous across the 

study area.

Layer 3 is predominantly clayey glacial till but includes 

silt layers where they directly underlie or overlie the clayey 

till. Cross sections by Keech and others (1967) indicate that 

thin silt layers adjacent to the glacial till are common. The 

glacial till has been interpreted as deposited by continental 

glaciers that advanced southward into eastern Nebraska; the 

western extent of these deposits is slightly to the west and 

south of the study area (Swinehart and others, 1994). Layer 

3 is mostly continuous across the study area but is absent in 

a few locations in the southeastern portion. The thickness 

ranges from 0 to 35 m with an average thickness of 16 m, and 

the layer serves as a confining unit for the underlying sand of 

layer 4.

Layer 4 was assigned as the uppermost sand layer 

underlying the clayey till/silt. This fine to medium sand 

contains minor amounts of gravel and is considerably more 

homogeneous than layer 2. This upper confined sand thins in 

the northwestern one-half of the study area and is absent in 

some areas. Nearly all public-supply wells and many irrigation 

wells are fully screened across the layer 4 sand. The thickness 

ranges from 0 to 25 m with an average thickness of 11 m.

Layer 5 consists of clay and silt deposits underlying layer 

4 but includes minor amounts of interbedded sand. Five public-supply wells are partially screened across layer 5. Layer 5 

thins both at the southeast edge and in the northwestern half 

of the study area, where a bedrock high limits layer thickness. 

Layer 5 is heterogeneous, and the individual thin lithologic 

layers within it are probably not continuous over great distances. The thickness ranges from 0 to 32 m with an average 

thickness of 12 m.

Layer 6 consists of thinly interbedded fine to medium 

sand and silty clay. Most public-supply wells and some irrigation wells have screens that partially penetrate sand deposits in 

layer 6. Layer 6 has a spatial distribution of thickness similar 
8–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Table 8.1. Summary of hydrogeologic and ground-water-quality characteristics for the High Plains aquifer and the Eastern High Plains 

regional study area, Nebraska.

[m, meters; cm/yr, centimeters per year; %, percent; m3/s, cubic meters per second, km2, square kilometers; m/d, meters per day; mg/L, milligrams per liter; Kh, 

horizontal hydraulic conductivity; Kz, vertical hydraulic conductivity; NRD, Natural Resources District]

Characteristic High Plains aquifer Eastern High Plains regional study area

Geography

Topography Flat to gently rolling with local relief of less than 

90 m (Gutentag and others, 1984).

Mostly flat to gently rolling upland with shallow 

depressions; some stream valleys are incised into 

the uplands with local relief of less than 20 m.

Climate Semiarid: mean annual precipitation 40 to 72 cm/

yr from west to east; pan evaporation 150 to 270 

cm/yr from north to south (Gutentag and others, 

1984).

Subhumid; mean annual precipitation 68 cm/yr 

(High Plains Regional Climate Center, 2003); 

potential evapotranspiration 165 cm/yr (Gutentag 

and others, 1984).

Surface-water hydrology Relatively low precipitation and slopes produce low 

runoff (0.1 to 6.1 cm/yr) (Hedman and Engel, 

1989; Litke, 2001).

Ephemeral streams with relatively low runoff 

(3.3–4.5 cm/yr) (Hedman and Engel, 1989; 

Ma and Spalding, 1997); Beaver Creek is only 

perennial stream; flows maintained by municipal 

and commercial discharges.

Land use Rangeland, 56%; agriculture, 41%; wetlands, forest, 

urban, water, and barren, 3% (U.S. Geological 

Survey, 1999–2000); irrigated lands, 12% (Qi and 

others, 2002).

Agriculture, 85%; rangeland, 8%, wetlands, forest, 

urban, water, and barren, 7% (U.S. Geological 

Survey, 1999–2000); irrigated lands, 61% (Center 

for Advanced Land Management Information 

Technologies, 2000).

Water use Irrigation: 833 m3/s, 39 cm/yr average application on 

12% of area, 94% of total; 

Municipal: 18.5 m3/s, 3% of total;

Livestock: 9.7 m3/s, 1% of total; 

Mining: 9.3 m3/s, 1% of total; 

Industrial: 6.8 m3/s, 1% of total (values calculated 

from Dennehy and others, 2002).

Irrigation: about 25 cm/yr withdrawal over 61% of 

study area, 1.89 m3/s, 94% of total;

Industrial: 0.08 m3/s, 4% of total;

Municipal: 0.05 m3/s, 2% of total.

Geology

Surficial geology Eolian loess overlying Quaternary alluvial and 

valley-fill deposits of the High Plains aquifer 

(Gutentag and others, 1984).

Heterogeneous, layered Quaternary deposits; loess 

overlying sand and gravel overlying clayey glacial 

till overlying fine sand overlying layered silt, clay, 

and sand.

Bedrock geology Semiconsolidated Ogallala Formation (principal 

unit of High Plains aquifer) with heterogeneous 

sequences of sand, gravel, clay, and silt; 

Underlain by consolidated Tertiary, Cretaceous, 

Jurassic, Triassic, and Permian units (Gutentag and 

others, 1984).

Consolidated Cretaceous Carlile Shale and 

Niobrara Formation (Chalky Shale) underlie 

unconsolidated High Plains aquifer (Keech and 

others, 1967).

to layer 5. The thickness ranges from 0 to 48 m with an average thickness of 16 m.

The six model layers are underlain by the Carlile Shale 

of Late Cretaceous age in the southeastern two-thirds of the 

study area and the Cretaceous Niobrara Formation, consisting 

of chalky shale and chalk, in the northwestern one-third of the 

study area (Keech and others, 1967). The Cretaceous rocks 

are much less permeable than the sands and gravels of the 

High Plains aquifer and are considered the base of the High 

Plains aquifer (Gutentag and others, 1984). A bedrock high in 

the northwestern one-half of the study area results in thinning 

of the overlying Quaternary deposits to about one-half their 

thickness compared to similar deposits beneath York.
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–7

Characteristic High Plains aquifer Eastern High Plains regional study area

Ground-water hydrology

Aquifer conditions Extent: 450,660 km2, primarily bounded by erosional 

contacts; regionally unconfined, locally confined; 

saturated thickness: average 61 m, ranges 0 to 

366 m; in hydraulic connection with major river 

systems crossing aquifer (Gutentag and others, 

1984; Weeks and others, 1988; Dennehy and 

others, 2002).

Extent: 388.5 km2, bounded laterally by approximate 

regional ground-water flow lines; unconfined 

and confined layers in aquifer (Keech and others, 

1967); 

Saturated thickness: average 64 m, range 15 to 106 

m; only perennial stream is artificially maintained 

by municipal and commercial discharges, 

primarily loses water to aquifer.

Hydraulic properties Kh: average 18.3 m/d, range 0 to 91.4 m/d 

(Gutentag and others, 1984); 

Specific yield: average 15.1%, range 5 to 30% 

(Gutentag and others, 1984).

Kh unconfined: 41.5 m/d;

Kh upper confined: 19.8 m/d;

Kh lower confined: 4.8 to 6.9 m/d;

Storage: Specific yield for unconfined, 0.01–0.3; 

storage coefficient for confined, 6 X 10–6 – 2 X 

10–3 (Argonne National Laboratory, 1995; Upper 

Big Blue NRD, 1999).

Ground-water budget Precipitation recharge: 0.1 to 15.2 cm/yr, average 1.5 

cm/yr, 1 to 25% of precipitation (Gutentag and 

others, 1984; Luckey and others, 1986; Dugan and 

Zelt, 2000; Dennehy and others, 2002);

Irrigation recharge: as much as 30 to 40% of applied 

(Luckey and others, 1986);

Other inflow: canal and reservoir seepage (Luckey 

and others, 1986);

Irrigation pumpage: average 39 cm/yr (Dennehy and 

others, 2002), consumptive irrigation demand, 20 

to 53 cm/yr (Dugan and Zelt, 2000); 

Other outflow: discharge to streams (Luckey and 

others, 1986) 

Precipitation recharge: 14.2 cm/yr, 20% of 

precipitation;

Irrigation recharge: 6.4 cm/yr, 25% of irrigation 

pumpage;

Stream seepage: 0.04 m3/s;

Irrigation pumpage: 25.4 cm/yr, 1.89 m3/s;

Industrial pumpage: 0.08 m3/s;

Municipal pumpage: 0.05 m3/s.

Ground-water quality

Water chemistry In areas unaffected by natural or anthropogenic 

contamination, primarily calcium bicarbonate 

waters with dissolved solids less than 517 mg/L, 

pH ranging from 7 to 8, median concentrations of 

dissolved oxygen greater than 5.4 mg/L; generally 

oxidizing conditions but some more reducing 

conditions occur locally (Dennehy and others, 

2002).

Calcium bicarbonate waters with dissolved solids 

of 280 to 474 mg/L; 

pH ranges from 6.2 to 8.0;

Oxygen reducing in unconfined to iron-reducing 

in lower confined; nitrate-to-iron reducing 

conditions in confined can locally become more 

oxidizing as a result of pumping.

Contaminants Natural: salinity, iron, manganese, fluoride, radon, 

uranium, arsenic;

Anthropogenic: nitrate, pesticides, salinity, carbon 

tetrachloride.

Natural: arsenic and uranium;

Anthropogenic: nitrate, chlorinated solvents, 

carbon tetrachloride, pesticides.

Table 8.1. Summary of hydrogeologic and ground-water-quality characteristics for the High Plains aquifer and the Eastern High Plains 

regional study area, Nebraska.—Continued

[m, meters; cm/yr, centimeters per year; %, percent; m3/s, cubic meters per second, km2, square kilometers; m/d, meters per day; mg/L, milligrams per liter; Kh, 

horizontal hydraulic conductivity; Kz, vertical hydraulic conductivity; NRD, Natural Resources District]
8–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Ground-Water Occurrence and Flow

Unconfined and confined ground-water conditions occur 

in the Quaternary sediment layers as defined in the “Geology” 

section. Ground-water flow in the Eastern High Plains regional 

study area is predominantly from the northwest to the southeast with an average gradient of about 0.001326 (Johnson and 

Keech, 1959; Keech and others, 1967; Conservation and Survey Division, 1980; Verstraeten and others, 1998; Dreeszen, 

2000). Quaternary sediment thickness, and therefore, aquifer 

saturated thickness increases near the center of the study area 

(fig. 8.3). Saturated thickness ranges from a minimum of 15 

m in the northwestern part of the study area to a maximum of 

106 m in the region near York, with an average of about 64 m. 

Ground water passing under the study area that is not withdrawn by pumping farther downgradient probably discharges 

into the West Fork of the Big Blue River about 24 to 32 km 

to the southeast. Exchanges of water between the High Plains 

aquifer and underlying Cretaceous units are considered negligible in comparison to other fluxes (Luckey and others, 1986).

Historical water-level data indicate the ground-water system was in a quasi-steady-state condition from 1997 through 

Figure 8.3. Ground-water flow and geochemical conditions, Eastern High Plains regional study area, Nebraska.

2001. Winter water levels in observation wells generally fluctuated by less than 1.2 m from 1997 through 2001 and were 

similar to winter water levels prior to 1960, before substantial 

effects from ground-water withdrawals for irrigation occurred. 

During summer months, hydraulic heads in the confined 

aquifer decrease by as much as 15 m in response to irrigation 

withdrawals. After irrigation ceases in August or September, 

hydraulic heads in the confined aquifer increase sharply and 

then gradually recover until reaching stable maximum values 

during the following winter or spring. Thereafter, this annual 

cycle is repeated when irrigation withdrawals begin again in 

June. Over periods greater than 1 year, the effect of a single 

season cycle diminishes, and hydraulic heads in the late winter-early spring reflect climatic and water-use conditions over 

several preceding years.

Long-term ground-water hydrographs (U.S. Geological 

Survey Ground Water Site Inventory Data Base; Rod DeBuhr, 

Upper Big Blue Natural Resources District, written commun., 

April 15, 2003) indicate winter hydraulic heads around York 

decreased about 4.6 m from 1957 to 1982, increased about 4.6 

to 5.2 m from 1983 to 1995, and were relatively stable from 

1995 to 2001. The water-level history probably reflects the 

A

B

C

D

E

F

G H

Land surface

Mostly unsaturated loess

Unconfined sand and gravel

Upper confining clay till/silt

Upper confined sand

Lower confining

clay/silt

Lower confined sand and clay/silt

LAYER 1

LAYER 2

LAYER 3

LAYER 4

LAYER 5

LAYER 6

Not to scale

Northwest Southeast

EXPLANATION

Oxidation-reduction conditions

 Oxygen reduction

 Nitrate reduction

 Manganese reduction

 Iron reduction

Generalized ground-water flow direction

Water table

Withdrawal well with typical screen placement

Inflow source and identifier

Outflow sink and identifier

A

B

C

D

E

F

G

H

Recharge from precipitation—20 percent of annual precipitation (71.1 cm/yr) equals 14.2 cm/yr,

 about 151,000 m3/d across study area, 67 percent of inflows

Withdrawals for irrigation—25.4 cm/yr application over about 61 percent of study area, about 

 163,300 m3/d across study area, 73 percent of outflows

Ground-water outflow to downgradient boundary—Estimated as 43,900 m3/d, 22 percent of outflows

Withdrawals for industrial supply—Estimated as 6,910 m3/d, 3 percent of outflows

Withdrawals for municipal supply—Estimated as 4,320 m3/d, 2 percent of outflows

Recharge from irrigation—25 percent of irrigation return flow from 25.4 cm/yr application equals 6.4 cm/yr

 over about 61 percent of study area, about 44,900 m3/d across study area, 20 percent of inflows

Regional ground-water inflow from upgradient boundary—Estimated as 24,200 m3/d, 11 percent of inflows

Seepage from streams—Estimated as 3,460 m3/d, 2 percent of inflows
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–9

the upper confined layer was 19.8 m/d, and horizontal hydraulic-conductivity values for the lower confined layer were 4.8 

and 6.9 m/d. Thickness-weighted horizontal hydraulic conductivity for the entire thickness of the High Plains aquifer in the 

study area used in previous regional ground-water flow models 

was about 15 m/d (Luckey and others, 1986; COHYST, 2001). 

Horizontal hydraulic- conductivity values from the aquifer 

tests were used as initial estimates in the Eastern High Plains 

regional ground-water flow model.

Storage properties of the unconfined and confined layers 

were determined from aquifer tests in and around York and 

generally span a considerable range and have high uncertainties (table 8.1). Thickness-weighted average values of specific yield determined from interpretations of lithologic-log 

analysis reported by Gutentag and others (1984) indicate that 

specific yield in most of the study area is in the range of 10 to 

20 percent.

Systematic estimates of vertical hydraulic conductivity, ratios of horizontal to vertical hydraulic conductivity, and 

porosity have not been made across the High Plains aquifer 

or in the study area. Chen and Yin (1999) summarize results 

from several aquifer tests in Quaternary or younger alluvial 

deposits along the Platte and Republican Rivers in Nebraska 

(north and south, respectively, of the study area), as having 

ratios of horizontal to vertical hydraulic conductivity ranging 

between 15 and 70. Values in this range were used as initial 

estimates for the Eastern High Plains regional ground-water 

flow model. Estimates of porosity for the various lithologic 

materials ranged from 0.2 to 0.4 based on specific-yield values 

presented by Gutentag and others (1984) and typical values 

reported by Zheng and Bennett (2002).

Water Budget

A conceptual water budget for the study area was developed and provided initial estimates of boundary fluxes for 

the ground-water flow model (fig. 8.3, table 8.1). Estimates 

of ground-water withdrawals and seepage from streams were 

reasonably well constrained. Withdrawals for irrigation per 

unit area are estimated as 25.4 cm/yr (see “Water Use”) over 

the irrigated part of the study area (61 percent) resulting in an 

estimated volumetric flux of 163,300 m3/d. Withdrawals for 

industrial and public-supply purposes were known or estimated from historical records and were 6,910 m3

/d and 4,320 

m3/d, respectively. Seepage from streams to ground water (see 

“Surface-Water Hydrology”) was estimated as 3,460 m3/d by 

subtracting measured low-flow stream discharge in Beaver 

Creek near the southeast end of the study area from commercial and wastewater discharges to Beaver Creek in York.

Ground-water inflows through the northeastern model 

boundary and outflows through the southwestern model 

boundary were estimated from Darcy’s equation (Freeze 

and Cherry, 1979). The Darcy’s equation calculation used 

a horizontal hydraulic-conductivity value of 61 m/d for the 

unconfined sand and gravel and 23 m/d for the confined sand, 

effect of agricultural irrigation in the area. Pumping apparently exceeded recharge prior to 1982, but the conversion from 

gravity to sprinkler irrigation, improved irrigation efficiency, 

and slightly wetter climatic conditions during the 1980s and 

early 1990s resulted in smaller irrigation withdrawals, greater 

recharge, and rising water levels. Winter hydraulic heads in 

2002 and 2003 decreased by more than 2 m in response to 

persistent drought conditions beginning in 2001.

Ground-water withdrawals from the confined sand layers 

induce large downward vertical gradients and flow (fig. 8.3). 

Comparison of hydraulic head in well clusters with wells 

screened in the unconfined and upper confined layers from 

1957 to 1970 and from 1990 to 1994 shows heads in the confined layer are a maximum of 12.2 m lower than in the unconfined layer during the summer irrigation season. Heads in the 

confined layer are 0.3 to 2.7 m lower than in the unconfined 

layer during the fall, winter, and spring when irrigation withdrawals are absent. Seasonal water-level declines in response 

to irrigation withdrawals are larger in the confined layers than 

in the unconfined layer because storage coefficients are much 

smaller in the confined than in the unconfined layer. Hydrographs from a well cluster in north York showed that heads 

in the lower confined layer were 0.6 to 2.4 m lower than in 

the upper confined layer during 1983–2002 (U.S. Geological 

Survey Ground Water Site Inventory Data Base; Rod DeBuhr, 

Upper Big Blue Natural Resources District, written commun., 

April 15, 2003).

Many irrigation and some older public-supply wells are 

screened across both the unconfined and upper and lower 

confined layers of the aquifer. Those wells with multiple 

screened intervals and boreholes penetrating confining layers 

may provide pathways for water and contaminants to move to 

deeper parts of the aquifer. Active York public-supply wells 

are screened only in the confined part of the aquifer. Several 

wells with screens that partially penetrate the unconfined parts 

of the system were decommissioned in the last decade because 

of contamination with nitrate or trichloroethylene (Orville 

Davidson, Public Utilities Director, City of York, Nebraska, 

written comm., February 15, 2002).

Aquifer Hydraulic Properties

Horizontal hydraulic conductivity of the unconfined layer 

ranges from 41 to 122 m/d (Argonne National Laboratory, 

1995). Results of a 5-day aquifer test just west of York indicate a horizontal hydraulic conductivity value of 41.5 m/d for 

the unconfined layer (Ma, 1996). Results of a 63-hour aquifer 

test in northern York indicate a range of horizontal hydraulicconductivity values between 41 and 122 m/d for the unconfined layer (Argonne National Laboratory, 1995). Horizontal 

hydraulic-conductivity values for the confined layers were 

determined from one 24-hour aquifer test in the upper confined layer and two 24-hour aquifer tests in the lower confined 

layer (Layne Geosciences, Valley, Nebraska,, written commun., 1997). The horizontal hydraulic-conductivity value of 
8–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

an average regional hydraulic gradient of 0.001326 (Keech 

and others, 1967), and saturated-thickness values representative of the boundary. Hydraulic-conductivity values in the 

upper range of possible values were selected so the calculated 

boundary fluxes would be near the upper limits of any boundary-flux estimates. On the basis of data from nearby test holes, 

a saturated thickness of 19 m was assigned for the unconfined 

sand and gravel on the upgradient boundary, and saturated 

thicknesses of 33 m and 13 m were assigned for the unconfined sand and gravel and confined sand, respectively, on the 

downgradient boundary. The resulting calculated inflow on 

the upgradient boundary was 24,200 m3/d, and the calculated 

outflow on the downgradient boundary was 49,300 m3/d.

Areal recharge is the primary source of inflow to the 

ground-water system and typically has greater uncertainty 

associated with its estimation than other budget terms. 

Recharge estimates were constrained by the need to balance 

the inflow and outflows of the water budget. The assumption 

of a balanced water budget is justified by the quasi-steadystate condition of winter water levels during 1995–2001 and 

the similarity of these water levels to those prior to the late 

1950s. Total recharge across the study area is about 196,000 

m3/d, assuming a balanced water budget. Recharge from irrigation return flows was assumed as 25 percent of withdrawals 

(25.4 cm/yr) or 6.4 cm/yr over the irrigated area for a volumetric flux of about 44,900 m3

/d. The assumed proportion of 

irrigation return flow is less than some historical estimates in 

the High Plains of 30 to 40 percent (Luckey and others, 1986) 

but reflect that irrigation efficiency has improved in the last 

2 decades and that there has been considerable conversion of 

gravity irrigation to more efficient center-pivot irrigation in the 

study area. To balance the water budget, recharge from precipitation was assumed as 20 percent of annual precipitation 

or 14.2 cm/yr. Applied over the entire study area, this assumed 

recharge rate results in a flux of 151,000 m3/d. The assumption 

of precipitation recharge as 20 percent of annual average precipitation is slightly higher than a previous recharge estimate 

of 15 percent of precipitation for the study area, based upon 

soil-water balance simulations (Dugan and Zelt, 2000), but is 

similar to values used in a previous local ground-water modeling study (Upper Big Blue Natural Resources District, 1999).

In the conceptual water budget (fig. 8.3), recharge 

accounts for about 87 percent of inflows, and withdrawals 

account for about 78 percent of outflows. Boundary inflows 

(11 percent of total) and outflows (22 percent of total) are 

lesser but important terms in the water budget. Conceptually, the dominance of recharge and withdrawals in the water 

balance indicates there should be considerable vertical and 

horizontal flow in the system between recharge areas and 

withdrawal wells, considering the relatively small size of the 

study area.

Ground-Water Quality

Sources of ground-water quality information in the 

study area include (1) samples collected as part of compliance monitoring of public-supply wells from the Nebraska 

Department of Health and Human Services (Ann Pamperl, 

Nebraska Department of Health and Human Services, Lincoln, 

Nebraska, written comm., January 15, 2002); (2) data from 

test wells drilled by the City of York (Orville Davidson, Public 

Utilities Director, City of York, Nebraska, written comm., February 15, 2002); (3) ground-water contamination investigations 

(Argonne National Laboratory, 1995); (4) regional groundwater quality investigations (Verstraeten and others, 1998); 

(5) data bases with compilations of historical data collected 

in the area (U.S. Geological Survey National Water Information System; University of Nebraska–Lincoln, 2000); and (6) 

samples collected from eight York public-supply wells for the 

NAWQA Source Water Quality Assessment (SWQA) program 

in October through December 2002. Of these sources, there 

are relatively few analyses with complete data with which to 

classify the oxidation-reduction (redox) state of the water. 

Moreover, many samples have been collected from wells with 

long screened intervals and large withdrawal rates such as 

irrigation or public-supply wells that may cause mixing of 

waters with different redox characteristics or have incomplete 

well-construction information so that the screened interval is 

not known. These factors limit the number of analyses useful 

for characterization of redox conditions.

The major-ion chemical data from City of York test wells, 

Argonne National Laboratory (1995), Verstraeten and others 

(1998), and SWQA data indicate ground water in the study 

area is of calcium-bicarbonate type water with dissolved-solids 

concentrations ranging from 280 to 474 mg/L with an average of about 364 mg/L (35 analyses). Values of pH are neutral 

ranging from 6.2 to 8.0 with an average of about 7.1 (151 

analyses). Consistent spatial patterns of pH are not apparent 

from the available data.

Of the 124 sample results with sufficient data for redox 

classification, 98 of the samples were collected from the 

unconfined sand and gravel. Only one of the 98 samples had 

a dissolved-oxygen analysis (7.4 mg/L). All 98 samples had 

concentrations of nitrate-nitrogen greater than 0.5 mg/L, indicating the waters are likely in the range of oxygen- to nitratereducing waters.

Twenty-six samples with sufficient data for redox classification were collected from wells screened in the confined parts 

of the aquifer. Of these, 23 samples were collected from wells 

with unique locations: 10 were from public-supply wells, 12 

were from test wells temporarily installed during exploratory 

drilling for public-supply wells by the City of York, and one 

was from a monitoring well. The spatial distribution of these 
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–11

samples is limited to areas in or near York (fig. 8.4). The four 

oxygen-reducing samples were all collected from public-supply wells. Most of the samples from test or monitoring wells 

(7 of 12) were consistent with manganese- or iron-reducing 

conditions. At four of the locations with redox data in the 

confined aquifer, data were available from different depths. At 

all four locations, the water generally became more reduced 

with depth, becoming either iron or manganese reduced in 

the lowermost sample. Generally, the redox data indicate the 

unconfined parts of the aquifer are oxidized and the confined 

parts of the aquifer are reduced with some mixtures and 

oxidized waters. The occurrence of more mixed and oxidized 

waters from public-supply wells than in test or monitoring 

wells is consistent with the redox chemistry being affected by 

withdrawals from the wells.

Direct evidence of changes in redox status as a result of 

pumping is demonstrated by water-chemistry data from York 

public-supply well 97-1A, screened in the upper confined 

layer, and wells 97-1 and 97-2, screened in the lower confined 

layer (fig. 8.5). Samples collected in 1996 (prior to public-supply well operation) from nearby test wells with screen lengths 

similar to those of the public-supply wells indicated ground 

water in 97-1A was manganese reducing and water in the 

lower confined sand was iron reducing at 97-1 and manganese 

reducing at 97-2. No nitrate-nitrogen was detected in any of 

the three samples. After withdrawals from the three publicsupply wells began in 1997, nitrate-nitrogen was detected in 

all three wells, and concentrations of iron, manganese, and 

arsenic decreased in wells 97-1 and 97-2. Sampling results in 

2001-2002 indicate oxygen-reducing conditions at well 97-1A, 

manganese-reducing conditions at well 97-1, and oxygen- or 

nitrate-reducing conditions at well 97-2.

The changes in the public-supply wells to more oxidized 

conditions has two implications: (1) the redox data in largecapacity wells can be affected by the withdrawals and may not 

be representative of ambient chemistry in most of the confined 

aquifer, and (2) the reducing conditions in the confined aquifer 

are weakly poised and subject to change to more oxidized 

conditions in places in the aquifer. The persistence of ironreducing conditions in two public-supply wells and manganese-reducing conditions in three public-supply wells indicates that redox conditions are not as changeable in response 

to withdrawals in all locations as in 97-1, 97-1A, and 97-2. 

The variability of redox conditions in public-supply wells may 

indicate spatial variations in the mineralogy, hydrogeology, 

and distribution of redox-sensitive dissolved constituents that 

influence the redox condition.

The time-series chemistry data from wells 97-1, 97-1A, 

and 97-2 indicate ambient redox conditions in the confined 

layers are primarily manganese or iron reducing, conditions 

become more reducing with depth, and redox conditions can 

change in response to withdrawals. The time-series data and 

the preponderance of evidence from other sites in the confined 

layers (fig. 8.4) indicate ground water in the confined layers 

is predominantly manganese or iron reduced and leads to the 

conceptual model shown in fig. 8.3.

Ground-Water Flow Simulations

A MODFLOW-2000 (Harbaugh and others, 2000) model 

was constructed to simulate ground-water flow in a 388.5-

km2 area of the High Plains aquifer near York, Nebraska. The 

model created for this study is discretized into rows, columns, 

and layers to represent the various hydrogeologic materials in 

the area, to simulate ground-water flow, and to delineate the 

areas contributing recharge to York public-supply wells. The 

flow model assumes steady-state conditions and represents 

average conditions for 1997–2001. Historical water-level data 

indicate the ground-water system was in a quasi-steady-state 

condition during 1997–2001 (see “Ground-Water Occurrence 

and Flow”). Most of the hydraulic-head data used to calibrate 

the model were collected in April 2001, and the values reflect 

average winter conditions for 1997–2001.

Modeled Area and Spatial Discretization

A previous regional ground-water flow model (COHYST, 

2001) of a 26,936-km2 area was used to select the model 

boundaries for this study. The Eastern High Plains regional 

ground-water flow model was aligned northwest to southeast 

at an azimuth of 117 degrees (fig. 8.6), which approximately 

corresponds to the regional flow direction on potentiometric 

maps from before 1953 (Johnson and Keech, 1959), 1964 

(Keech and others, 1967), 1979 (Conservation and Survey 

Division, 1980), 1995 (Dreeszen, 2000), and 1996 (Verstraeten 

and others, 1998). The southeast model boundary is located 

closer to York than the northwest model boundary because 

ground-water flow is from the northwest, and areas contributing recharge to wells will likely extend toward the northwest. 

The northeastern and southwestern boundaries, approximately 

corresponding to lateral no-flow boundaries of two groundwater flow lines in the regional flow model, were selected far 

enough from York so as not to affect simulated flow paths to 

York public-supply wells.

Horizontal and vertical discretization was specified to 

yield representative simulation of ground-water flow and areas 

contributing recharge to public-supply wells while maintaining simplicity in model geometry. The flow model consists of 

200 rows and 300 columns of square cells with dimensions of 

82.57 m on each side. There are six model layers corresponding to the loess-unconfined, unconfined, upper confining, 

upper confined, lower confining, and lower confined units, as 

shown in the conceptual model (fig. 8.3).

Layer thicknesses are not uniform except for layer 1, 

which has a uniform thickness of 4.57 m. Layer 1 was specified with a relatively thin uniform thickness to better represent 

the interaction between Beaver Creek, which is simulated 

exclusively in layer 1, and the unconfined aquifer. The loess 

areas in layer 1 outside of the Beaver Creek alluvial valley go 

dry during the simulation. The remaining model layer thicknesses were interpolated from 71 driller’s logs in the study 

area, after assigning lithologies in the logs to the layers of 
8–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 8.4. Oxidation-reduction conditions in wells screened in the confined part of the High Plains aquifer, Eastern 

High Plains regional study area, Nebraska.

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Extent of active model cells

York city limit

Beaver Creek perennial reach

Oxidation-reduction condition—Triangles represent test or monitoring wells, 

 circles represent public-supply wells

 Oxygen reduction

 Manganese reduction

 Mixture of manganese reduction to oxygen reduction

 Iron reduction

 Mixture of iron or manganese reduction to nitrate reduction
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–13

Figure 8.5. Changes in concentration of oxidation-reduction 

sensitive species in three York public-supply wells from 1996, prior 

to withdrawals for public water supply, and for 1997–2002, when 

municipal withdrawals occurred.

the conceptual model. Interpolations between geologic logs 

to develop hydrogeologic sections and three-dimensional 

stratigraphic models were done using the Department of 

Defense Groundwater Modeling System (GMS), version 4.0, 

developed by the Engineering Computer Graphics Laboratory 

at Brigham Young University. A minimum thickness of 0.3 m 

was assigned to model layers where layers were absent, which 

was primarily an issue for layers 4, 5, and 6. In general, the 

overall model thickness is smaller in the northwestern one-half 

of the modeled area than in the southeastern one-half to reflect 

changes in the bedrock topography (fig. 8.3).

Boundary Conditions and Model Stresses

The northeastern and southwestern model boundaries 

were specified as no-flow boundaries because they correspond 

to ground-water flow lines from the regional ground-water 

flow model. The northwestern (upgradient) and southeastern (downgradient) boundaries were initially specified-head 

boundaries by using heads telescoped to the model from the 

regional model and following the methods of Leake and Claar 

(1999). Following initial model simulations, the upgradient 

and downgradient model boundaries were changed from specified-head to specified-flux boundaries to more realistically 

represent ground-water underflow in the aquifer. Specifying 

flux rather than head along the boundaries allows head along 

the boundary to change with varying stress, which eliminates 

the artificial constraint of specified head.

Flux boundaries were specified for each of the primary 

water-bearing units on the upgradient and downgradient 

boundaries of the flow model. Flux boundaries were simulated 

using wells in each cell on the boundary for the unconfined, 

upper confined, and lower confined units, corresponding to 

layers 2, 4, and 6 (fig. 8.7). It is assumed that lateral inflow 

or outflow in the two confining layers is negligible. The flux 

boundaries are uniform along the boundary and unique for 

each water-bearing unit at the upgradient and downgradient 

boundaries. Initial boundary-flux estimates were based on 

conceptual-model estimates.

Anthropogenic stresses on the ground-water system 

include withdrawal for agricultural, industrial, and municipal 

needs. The MODFLOW Well package was used to simulate 

withdrawals from the aquifer. The locations of registered irrigation and industrial wells and data on potential irrigated area 

per well were available from a State of Nebraska data base 

(Nebraska Department of Natural Resources, 2002). The locations of public-supply wells were determined with a Global 

Positioning System and verified on street and topographic 

maps. Available well-screen elevations were used to assign 

withdrawal values to corresponding model layers. Withdrawal 

from wells without well-screen information was assigned to 

model layers considering nearby well-screen elevations and 

water use. For wells screened in multiple layers, the proportion 

of the total withdrawal assigned to each layer was determined 

from the ratio of an individual layer’s transmissivity to the 

0

2

4

6

8

10

12

14

16

18

Concentration of arsenic, in

micrograms per liter, or nitratenitrogen, in milligrams per liter

Iron, managanese concentration,

in micrograms per liter

Jan

1996

Jan

1997

Jan

1998

Jan

1999

Jan

2000

Jan

2001

Jan

2002

Jan

2003

A. Well 97-1A: Upper confined layer

0

40

80

120

160

200

240

280

320

360

0

2

4

6

8

10

12

14

16

18

Concentration of arsenic, in

micrograms per liter, or nitratenitrogen, in milligrams per liter

Iron, managanese concentration,

in micrograms per liter

Jan

1996

Jan

1997

Jan

1998

Jan

1999

Jan

2000

Jan

2001

Jan

2002

Jan

2003

C. Well 97-2: Lower confined layer

0

40

80

120

160

200

240

280

320

360

0

2

4

6

8

10

12

14

16

18

Concentration of arsenic, in

micrograms per liter, or nitratenitrogen, in milligrams per liter

Iron, managanese concentration,

in micrograms per liter

Jan

1996

Jan

1997

Jan

1998

Jan

1999

Jan

2000

Jan

2001

Jan

2002

Jan

2003

B. Well 97-1: Upper confined layer

0

40

80

120

160

200

240

280

320

360

EXPLANATION

Arsenic

Nitrate-nitrogen

Iron

Manganese
8–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 8.6. Ground-water flow model grid boundary and selected boundary conditions in different model layers, 

Eastern High Plains regional study area, Nebraska.

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Specified-flux boundaries in layers 2, 3, and 4

River boundary condition in layer 1

Drain boundary condition in layer 1

No-flow boundary

York city limit

York public-supply well

Well
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–15

Figure 8.7A. Hydrogeologic section showing hydraulic-conductivity zones and flux-boundary values for layers of calibrated 

ground-water flow model.

86.35

7.18

2.83

127.41

96.26

11.33

Land surface

LAYER 6

LAYER 5

LAYER 4

LAYER 3

LAYER 2

LAYER 1

Kh / Kv Kh = 49 = 5 n = 0.25

Kh / Kv Kh = 0.03 = 20 n = 0.35

Kh / Kv Kh = 6 = 5 n = 0.20

Kh / Kv Kh = 0.03 = 20 n = 0.40

Kh / Kv Kh = 55 = 5 n = 0.35

(Values shown in figure 7B)

0 1 2 3 4 5 kilometers

0 1 2 3 miles

Vertical scale greatly exaggerated

Northwest Southeast

63 meters

54 meters

EXPLANATION

Horizontal hydraulic conductivity, in meters per day

 Less than 1.0

 1.01 to 10.0

 10.01 to 50.0

 Greater than 50.0

Specified volumetric flux per model-boundary node in

 indicated layer—Flux on northwest boundary is into

 model; flux on southeast boundary is out of model.

 Values in cubic meters per day

Horizontal hydraulic conductivity, in meters per day

Ratio of horizontal to vertical hydraulic conductivity

Porosity

Kh / Kv

Kh

n

7.18

overall transmissivity. For example, the proportion of flow 

from layer 1 would be calculated as:

Where K1 is the hydraulic conductivity of layer 1, b1 is 

the saturated thickness of layer 1, Ki is the hydraulic conductivity of individual layer i, bi

 is the saturated thickness of that 

layer, and n is the total number of layers.

A constant withdrawal rate of 25.4 cm/yr (see “Water 

Use”) was multiplied by the estimated irrigated area to 

calculate the 1997–2001 average volumetric withdrawal rate 

for each irrigation well. For the 794 registered irrigation 

wells in the study area, the sum of the irrigated areas associated with each well record was considerably larger than the 

irrigated area in the study area indicated by a map of 1997 

land use (Center for Advanced Land Management Information 

Technologies, 2000), a year with relatively normal climatic 

conditions. The irrigated areas listed in the well registration 

overestimate actual irrigated area because not all farmers 

irrigate all of the irrigable land each year. Consequently, the 

actual irrigated area per well was estimated by multiplying the 

potential irrigated area for each well by the ratio of the 1997 

irrigated area from the 1997 land-use map to the sum of the 

irrigated areas from the well registration for the study area.

There were 14 public-supply wells active in York for 

all or most of 1997–2001 (table 8.2). Several public-supply 

wells have multiple screens that typically fully penetrate the 

upper confined sand (layer 4) and fully or partially penetrate 

the lower confined sand (layer 6). Six wells have screens in 

sand lenses that partially penetrate layer 5, the lower confining 

clay/silt. Three wells have screens that partially penetrate the 

unconfined sand and gravel, layer 2; two of these wells were 

shut down due to nitrate-nitrogen concentrations in excess 

of the EPA MCL of 10 mg/L during 2000–2001. Average 

1997–2001 withdrawal rates were assigned for the steady-state 

simulations.
8–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 8.7B. Hydraulic-conductivity and active-cell zones in layer 1 of calibrated ground-water flow model, Eastern 

High Plains regional study area, Nebraska

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Horizontal hydraulic conductivity, in meters per day

 Less than 1.00—Kh = 0.03; Kh/Kv = 20; n = 0.40

 Greater than 50.01—Kh = 55; Kh/Kv = 5; n = 0.35

Extent of active model cells

York city limit

Beaver Creek perennial reach

York public-supply well

[Kh, horizontal hydraulic conductivity, in meters per day; Kh/Kv, ratio of horizontal to vertical conductivity; n, porosity]
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–17

There were 10 commercial/industrial wells active in the 

study area, and most of the withdrawals were from 4 of the 10 

wells. Withdrawal rates for commercial wells were estimated 

using values from the Upper Big Blue NRD (1999), or from 

the City of York, or by contacting commercial water users. 

The commercial/industrial wells were screened in layers 2, 4, 

and(or) 6.

Beaver Creek is the only continuously flowing stream in 

the modeled area (see “Surface Water Hydrology”), and flow 

in the creek results from municipal wastewater and commercial discharges in York. Downstream (southeast) from York, 

surface water in Beaver Creek seeps into the ground-water 

system, contributing about 3,630 m3/d. Beaver Creek is simulated as a MODFLOW drain upstream from the York Cold 

Storage facility discharge (fig. 8.6). This part of the creek is 

dry except after rainstorms. Outflow to the drain is assumed 

to be zero during the steady-state simulation. The streambedconductance factor is the product of the streambed hydraulic 

conductivity and the streambed width divided by the thickness 

of the streambed material. A 0.3048-m streambed thickness, 

a 3.048-m-wide stream channel, and a streambed hydraulic 

conductivity of 0.1 m/d were assumed, yielding a streambedconductance factor of 1.0 m2

/d. The conductance factor was 

multiplied by the length of the stream reach in each drain 

cell to calculate the conductance (in m3/d). Drain elevation 

was set as the estimated elevation of land surface. Four flow 

observations of zero were intermittently specified along the 

drain reach. The drain was included in the model as an aid in 

calibration rather than for its role in the water budget.

MODFLOW river cells represent Beaver Creek downstream from the York Cold Storage discharge to the southeastern model boundary to represent ground-water/surfaceTable 8.2. Average ground-water pumping rates for public-supply wells, 1997–2001, Eastern High Plains regional study area, Nebraska 

(Orville Davidson, Public Utilities Director, City of York, Nebraska, written commun., Feb. 15, 2002).

[m, meters; m3/d, cubic meters per day]

Well name

Elevation of 

land surface 

(m)

Year of

construction

Average 

withdrawal 

1997–2001 

(m3/d)

Total length of 

well screens

(m)

Well status Actual screen placmement

48–1 501.40 1948 0.43 10.67 Shut down 2000* 2 screens partially penetrate layer 2

62–1 485.24 1962 9.53 35.66 Active 2 screens partially penetrate layer 2 and 

fully penetrate layer 4

68–1 499.87 1968 1,315.62 57.61 Active 2 screens fully penetrate layers 4 and 6

73–1 503.53 1973 535.68 71.63 Active 7 screens fully penetrate layer 4, partially 

layers 5 and 6

76–1 485.55 1976 123.98 21.34 Active 1 screen in layer 4

77–1 502.31 1977 239.84 60.96 Active 3 screens fully penetrate layer 4, 

partially layers 5 and 6

77–3 492.25 1977 276.63 43.28 Active 2 screens fully penetrate layers 4 and 6

77–4 489.20 1977 350.38 34.14 Active 2 screens fully penetrate layer 4 and 

partially penetrate 5 or 6

82–1 502.62 1982 465.93 59.44 Active 2 screens fully penetrate layer 4 and 

partially penetrate 5 and 6

82–2 502.92 1982 381.65 51.82 Active 3 screens fully penetrate layer 4 and 

partially penetrate 5 or 6

88–1 501.70 1988 1,646.23 44.20 Shut down 2001* 3 screen partially penetrate layers 2 and 5, 

fully penetrate 4

97–1 503.22 1997 278.25 25.73 Active 1 screen partially penetrates layer 6

97–1A 502.62 1997 230.55 20.12 Active 1 screen fully penetrates layer 4

97–2 502.92 1997 340.38 32.89 Active 2 screens partially penetrate layer 6

* Wells shut down because of nitrate contamination. 
8–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

water interaction (figs. 8.6 and 8.7). The MODFLOW River 

package allows surface water to flow into the ground-water 

system where river leakage occurs and allows ground water to 

discharge to surface water near the southeastern edge of the 

study area where the stream becomes perennial. River conductance was calculated similar to drain conductance. A 0.3048-m 

streambed thickness, a 3.048-m-wide stream channel, and a 

streambed hydraulic conductivity of 0.8 m/d were assumed, 

yielding a streambed-conductance factor of 8.0 m2/d. Stage 

was specified as 0.3048 m above the land surface. About onehalf of the Beaver Creek leakage to the ground-water system 

is assumed to occur along the river reach within York where 

downward head gradients between the river and the aquifer are 

relatively large.

The upper model boundary consists of a water-table surface allowing inflow from recharge throughout the uppermost 

active model layer. A specified-flux boundary was used to 

simulate recharge to the ground-water flow system. Recharge 

was specified for the entire modeled area and was categorized 

as predominantly nonirrigated, gravity-irrigated, or sprinklerirrigated agricultural land, urban land, or surface water. A 

recharge rate was specified for each of the following recharge 

zones, with percentage of total land area in parentheses: 

nonirrigated land 17.1 cm/yr (33 percent), gravity-irrigated 

agricultural land 22.8 cm/yr (33 percent), and sprinkler-irrigated agricultural land 20.6 cm/yr (28 percent), urban land 1.5 

cm/yr (4 percent), and surface water 0 cm/yr (1 percent) (fig. 

8.8). Initial estimates were values described in the conceptual 

model (see “Water Budget”). Urban recharge was assumed 

principally derived from leakage from the water-distribution 

system, and urban recharge from precipitation was considered negligible because of the large proportion of impervious 

area. For 1997–2001, the unaccounted water, the difference 

between water pumped and the water delivered, was 27,600 

m3/d (Orville Davidson, Public Utilities Director, City of York, 

Nebraska, written commun., June 6, 2003) or 12 percent of the 

annual pumping. Areal recharge in urban areas was therefore 

assumed equal to 27,600 m3/d uniformly distributed across 

the urban area. Infiltration of surface water, with the exception of Beaver Creek, was considered insignificant; therefore, 

cells designated as “surface water” were given a value of zero 

recharge. The surface of the Carlile Shale and Niobrara Formation, underlying the High Plains aquifer in the study area, is 

represented as a no-flow boundary beneath the model.

Aquifer Hydraulic Properties

Aquifer hydraulic properties were assigned to model layers on the basis of lithology of the six layers of the conceptual 

model (figs. 8.3 and 8.7, table 8.1). Horizontal hydraulic- conductivity and vertical-anisotropy parameter values were incorporated into the model by using the Layer Property Flow Package (Harbaugh and others, 2000). Layer 1 of the flow model 

contains parameter zones representing the unconfined sand 

and gravel in the Beaver and Lincoln Creeks alluvial valleys 

and the more widespread silt and clay of the loess elsewhere 

(fig. 8.7B). Layers 2 through 6 were each assigned homogeneous values for hydraulic conductivity, vertical anisotropy, 

and porosity consistent with the predominant lithology based 

on the conceptual model. Final hydraulic-conductivity values 

were determined from model calibration.

Model Calibration and Sensitivity

Model calibration is the process by which model parameter values are adjusted within reasonable limits to minimize 

the difference between model-computed and measured heads 

and fluxes. Ground-water levels in 31 wells, mostly measured 

during the spring of 2001, and estimated fluxes from Beaver 

Creek into the aquifer were used as the basis of calibration. 

Every parameter used in the simulation was adjusted within 

reasonable limits until the differences between the model-computed and measured hydraulic heads were reduced to about 

5.0 percent of the total head change across the study area. The 

final model was compared to measured hydraulic heads and 

estimated discharges in Beaver Creek to evaluate the calibration process.

The overall goodness of fit of the model to the observation data was evaluated using summary measures and graphical analyses. The root-mean-squared error (RMSE), the range 

of head and residuals, the mean residual, the standard deviation, and the standard-mean error of the residuals (SME), 

were used to evaluate the model calibration. The RMSE is a 

measure of the variance of the residuals and was calculated as:

where hmeas is the measured hydraulic head, hsim is the modelcomputed (simulated) hydraulic head, (hmeas – hsim) is the head 

residual, and N is the number of wells used in the computation. If the ratio of the RMSE 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).

The mean residual (Rmean) is computed as:

R N mean 

and its positive or negative sign indicates whether model-computed hydraulic heads were higher or lower than measured 

hydraulic heads, respectively.

The SME was calculated as:
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–19

Figure 8.8. Distribution of recharge estimates used as ground-water flow model input, Eastern High Plains regional 

study area, Nebraska.

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Recharge zonation, in centimeters per year

 22.8 Irrigated by gravity method

 20.6 Irrigated by sprinkler methods

 17.1 Non-irrigated

 1.5 Urban

 0 Surface water

Extent of active model cells

York city limit

Beaver Creek perennial reach

York public-supply well
8–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

where σ(hmeas – hsim) is the standard deviation of the residuals.

Model calibration continued until the mean residual and 

RMSE of the residuals for all model layers were minimized. 

The flow model was considered calibrated when the following 

criteria were satisfied:

1. Incremental changes in model parameters did not 

substantially reduce the RMSE (Hill and others, 

2000) or other calibration statistics.

2. The RMSE of the entire model was less than 

approximately 5 percent of the total head change in 

the study area.

3. The simulated vertical gradients in two sets of nested 

wells were similar to the measured vertical gradients.

4. Simulated seepage to the High Plains aquifer from 

Beaver Creek was within one order of magnitude of 

the conceptual discharge of about 3,630 m3/d.

The calibrated model is a simplified representation of 

a complex hydrogeologic system and inherently sensitive to 

some model parameters. The model is influenced by the uncertainty in the value of these parameters and in the dynamics of 

the boundary conditions. A sensitivity analysis characterizes 

the effect of model-parameter change on the model results. 

The model is considered sensitive to a model parameter when 

changes in the model parameter produce substantial changes in 

the model results. This type of analysis can be used to identify 

areas where additional hydrogeologic information is needed.

Sensitivity analysis was performed using MODFLOW2000 and the sensitivity process (Hill and others, 2000). 

The calibrated steady-state model is nearly four orders of 

magnitude more sensitive to recharge than to any other type 

of parameter. The model also is sensitive to the hydraulic conductivity of layers 2 and 4 and the specified-flux boundaries. 

The model is relatively insensitive to the vertical anisotropy 

and the conductance factor of Beaver Creek.

Parameter values were changed within acceptable limits 

from initial estimated values to the final values during the 

calibration process. Most of the parameter changes before the 

change from specified-head to specified-flux boundaries were 

limited to the hydraulic conductivity of layers 2, 4, and 6; values in layer 2 yielding the best model fit at one point reached 

a value of about 150 m/d, about 3 times greater than values 

estimated from pumping tests. After the switch to the specified-flux boundary, hydraulic-conductivity values in all layers 

were changed to previously estimated values (see “Aquifer 

Hydraulic Properties”) resulting in a lower sum of square 

residuals and better vertical head distribution. Recharge values 

in the five zones were specified such that the total amount of 

recharge applied to the study area agreed with the conceptual 

model. Adjustments to the recharge distribution among the 

five recharge zones assumed gravity irrigation provided more 

recharge than sprinkler irrigation (Mustick and Stewart, 1992), 

irrigated land provided more recharge than nonirrigated land, 

urban land provided less recharge than agricultural lands, and 

surface-water areas provided no recharge (fig. 8.8). Although 

individual initial recharge parameters may have changed during the calibration process, the total recharge applied to the 

model remained essentially the same. After about 200 model 

runs, adjustments were made only to the most sensitive model 

parameters with most of the final adjustments occurring at the 

specified-flux boundaries.

Model-Computed Hydraulic Heads

The model-computed hydraulic heads in all model layers 

were in good agreement with ground-water flow directions 

and gradients indicated by previous regional investigations. A simple method of assessing model fit is to plot the 

model-computed hydraulic head values against the measured 

observations. For a perfect fit, all points should fall on the 

1:1 diagonal line. Figure 8.9 presents a graph of the modelcomputed hydraulic heads plotted against measured hydraulic 

heads for the Eastern High Plains regional study area and 

indicates reasonable model fit. The mean residual for the 

entire model is -0.7 m, and residuals range from -3.6 m to 

3.5 m (range of 7.1 m). The RMSE for the entire model is 

1.66 m, which is about 5.4 percent of the 31-m range of head 

observations in the model, and the head residuals appear to 

be randomly distributed across the study area (fig. 8.10) at all 

values of measured head (fig. 8.11). The standard deviation 

of the residuals is 1.53 m, and the SME is 0.28 m. Individual 

layer calibration statistics vary, which is likely because most 

of the water-level measurements are located in layers 2 and 

4, with only two water-level measurements in layer 6. Mean 

error and RMSE for layers 2, 4, and 6 are 0.53 m and 1.56 m, 

0.15 m and 0.94 m, and 1.87 and 2.69, respectively. The sum 

Figure 8.9. Relation between model-computed and measured 

hydraulic head, Eastern High Plains regional study area, 

Nebraska.

1:1 line

475

480

485

490

495

500

505

510

Model-computed head elevation, in meters

Measured head elevation, in meters

475 480 485 490 495 500 505 510
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–21

Figure 8.10. Model-computed potentiometric surface in layer 4 and observation points and residuals in all layers, Eastern 

High Plains regional study area, Nebraska.

80

81

80

81

34

34

–1.9

–2.1

–2.6

–2.0

–2.3

0.3

–3.6

–2.5

–0.5

–1.5

–1.3 3.5 0.2 1.0

–0.4

–1.0 –1.5

0.9

–0.3

1.8

0.2

0.3 –0.9 0.3 0.1

0.1

–3.3

–0.9

–0.9

–0.4

–2.0

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

506

504

502

500

498

496

494

492

490

488

486

484

482

480

478

476

474

472

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Elevation contour of model-computed potentiometric surface in model layer 4, in meters above sea level. Contour interal 2 meters

Observation well and residual head values (measured minus modeled), values in meters

 Greater than 2

 2 to –2

 Less than –2

York public-supply well

Extent of active model cells

York city limit

Beaver Creek perennial reach

490

3.5

–0.3

–3.3
8–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Figure 8.11. Relation between head residuals and measured 

hydraulic head, Eastern High Plains regional study area, 

Nebraska.

Figure 8.12. Hydrogeologic section showing model-computed hydraulic heads through row 100 of calibrated ground-water 

flow model, Eastern High Plains regional study area, Nebraska.

of squared-weighted residuals for all heads in the model is 

74.17 m, whereas the sum of squared-weighted residuals for 

all observations, including estimated Beaver Creek discharge, 

is 97.61 m. The reported correlation between the weighted 

residuals and normal order statistics is 0.950 (which is greater 

than the 5-percent significance level of 0.946), indicating the 

hypothesis that the weighted residuals are independent and 

normally distributed at the 5-percent significance level is valid 

(Hill, 1998).

The calibrated steady-state ground-water flow model 

calculates water levels and internal fluxes for each model cell. 

The simulated potentiometric surface in the upper confined 

unit (layer 4) and the simulated vertical distribution of head 

along row 100 in the model are shown in figs. 8.10 and 8.12, 

respectively. Simulation results indicate the direction of flow 

is predominantly from the northwest to the southeast, as 

expected from the conceptual model. The potentiometric surface of layer 2 in the area near Beaver Creek, indicates leakage 

from the reach of the creek downstream from York.

The magnitude and horizontal extent of vertical groundwater flow between model layers is greatest between the 

unconfined and upper confined layers (layers 2 and 4) (fig. 

8.12, table 8.3). Although there are localized areas of vertical 

downward gradients between the upper confined and lower 

confined aquifers (layers 4 and 6) comparable to the gradients 

between layers 2 and 4, the typical head difference is about 

1 m. The largest area of vertical downward movement is 

in and around the city of York between layers 2 and 4. The 

magnitude of the largest difference in simulated head between 

layers 2 and 4 is about 5 m.

–5

–4

–3

–2

–1

0

1

2

3

4

5

Head residual, in meters

Measured head elevation, in meters

470 475 480 485 490 495 500 505 510

506

504

502

500

498

496

494

492

490

488

486

484

482

480

478

476

474

Land surface

LAYER 6

LAYER 5

LAYER 4

LAYER 3

LAYER 2

LAYER 1

0 1 2 3 4 5 kilometers

0 1 2 3 miles

Vertical scale greatly exaggerated

Northwest Southeast 63 meters 54 meters

EXPLANATION

Elevation contour of model-computed head, in meters above sea level

Water table

490
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–23

Table 8.3. Model-computed water budget for 1997–2001 average conditions, Eastern High Plains regional study area, Nebraska.

[m3/d, cubic meters per day; %, percent; <, less than; —-, not computed]

Water-budget component

Layer

Total

Percentage 

of inflow 

1 2 3 4 5 6 or outflow

Model inflow (m3/d)

Upgradient constant-flux boundary — 13,875 — 1,416 — 566 15,857 6.9

Recharge 14,431 189,932 — — — — 204,363 89.3

Beaver Creek—downstream from York 8,780 — — — — — 8,780 3.8

Beaver Creek—upstream from York — — — — — — — — 

Wells — — — — — — — — 

Downgradient constant-flux boundary — — — — — — — — 

SUBTOTAL (boundary fluxes) 23,211 203,807 — 1,416 — 566 229,000 100

INTERNAL FLUXES From: — — — — — — — — 

Layer 1 — 25,436 — — — — 25,436 9.4

Layer 2 2,206 103,509 — — — 105,715 39.1

Layer 3 — 287 — 95,385 — — 95,672 35.3

Layer 4 — — 4,350 — 19,428 — 23,778 8.8

Layer 5 — — — 995 — 16,255 17,250 6.4

Layer 6 — — — — 2,667 — 2,667 1.0 

SUBTOTAL (internal fluxes) 2,206 25,723 107,859 96,380 22,095 16,255 270,518 100

TOTAL (boundary + internal fluxes): 25,417 229,530 107,859 97,796 22,095 16,821 499,518

Model outflow (m3/d)

Upgradient constant flux boundary — — — — — — — — 

Recharge — — — — — — — — 

Beaver Creek—downstream from York 27.2 — — — — — 27.2 0.01 

Beaver Creek—upstream from York 5.7 — — — — — 5.7 0.0 

Wells — 95,838 12,186 54,617 4,844 11,828 179,313 78.3

Downgradient constant-flux boundary — 27,895 — 19,402 — 2,326 49,623 21.7 

SUBTOTAL (boundary fluxes): 32.9 123,733 12,186 74,019 4,844 14,154 228,969 100 

INTERNAL FLUXES To: — — — — — — — 

Layer 1 — 2,206 — — — — 2,206 0.8

Layer 2 25,436 — 287 — — — 25,723 9.5 

Layer 3 — 103,509 — 4,350 — — 107,859 39.9 

Layer 4 — — 95,385 — 995 — 96,380 35.6 

Layer 5 — — — 19,428 — 2,667 22,095 8.2 

Layer 6 — — — — 16,255 — 16,255 6.0 

SUBTOTAL (internal fluxes): 25,436 105,715 95,672 23,778 17,250 2,667 270,518 100 

TOTAL (boundary + internal fluxes): 25,469 229,448 107,858 97,797 22,094 16,821 499,487

INFLOW-OUTFLOW -52 82 1.0 <-1.0 <1.0 0.0 31

Percent discrepancy -0.2% 0.04% 0.00% 0.00% 0.00% 0.00% 0.01% 
8–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Model-Computed Water Budget

The calibrated model produces a detailed distribution 

of ground-water fluxes across cell faces and boundary conditions. The model-computed water budget indicates areal 

recharge from irrigation return flow and precipitation provides 

about 89 percent (14,431 m3/d) of the total water flow into the 

modeled area (table 8.3). Inflow from the upgradient specified-flux boundary and ground-water seepage from Beaver 

Creek accounts for about 6.9 and 3.8 percent of model inflow, 

respectively. Simulated inflow from Beaver Creek in and 

below the city of York is 8,780 m3/d. The model-computed 

water budget indicates that about 78 percent (179,314 m3/d) of 

the model outflow is to wells, with the downgradient specified-flux boundary accounting for about 22 percent of the total 

outflow (49,623 m3/d). A small outflow (0.01 percent) occurs 

along Beaver Creek near the southeastern boundary and at a 

topographic low near the middle of the simulated reach.

The simulated internal flux distribution indicates most of 

the water flows downward from the overlying layers to layer 

4 with decreasing downward flow from layer 4 to layer 5 and 

from layer 5 to layer 6. Based on model results, a downward 

flux is persistent throughout the area. Overall, the difference 

between inflows and outflows throughout the entire modeled 

area was about 0.01 percent.

Simulation of Areas Contributing Recharge to 

Public-Supply Wells

The calibrated steady-state model was used to estimate 

the areas contributing recharge to selected public-supply wells 

in the city of York by using the MODPATH (Pollock, 1994) 

particle-tracking post processor. Output from the steady-state 

model is used in the MODPATH simulation to calculate the 

path of imaginary particles moving through the simulated 

ground-water system (Pollock, 1994). As MODPATH tracks 

the path of each particle, it also tracks the time required for 

the particle to travel along the path, yielding results both in 

direction and time, which is useful information when delineating areas contributing recharge to wells (Pollock, 1994). The 

model-computed areas contributing recharge represent advective ground-water flow and do not account for mechanical 

dispersion. Advection-dispersion transport simulations would 

likely yield larger areas contributing recharge than advective 

particle-tracking simulations because the effects of dispersion 

caused by aquifer heterogeneity would be included.

Along with output from the calibrated steady-state MODFLOW model, the MODPATH simulation requires specified 

porosity values to calculate ground-water flow velocities. 

Porosity values were assumed uniform within each layer (fig. 

8.7) based on layer lithology, specific-yield values presented 

by Gutentag and others (1984), and typical porosity values 

listed in Zheng and Bennett (2002).

Results from the MODPATH simulations were used to 

delineate areas contributing recharge and zones of contribution to York public-supply wells (fig. 8.13). Because of the 

natural horizontal gradient from the northwest to the southeast 

across the study area, the areas contributing recharge extend 

northwest from the public-supply wells of York. Additional 

pumping upgradient from the public-supply wells affects the 

locations and orientations of the areas contributing recharge, 

as indicated by their occasionally irregular shapes. Traveltimes 

from the areas contributing recharge to wells range from 20 to 

more than 100 years. Based on particle-tracking results, some 

particles, especially those reaching screens in the lower confined unit, do not originate at the water table in the study area 

but track to the northwestern specified-flux boundary. These 

particles have estimated traveltimes of thousands of years. 

The zones of contribution to public-supply wells typically 

broaden until the area contributing recharge at the water table 

is reached then narrow as only a few deeper pathlines delineating the zones of contribution continue upgradient.

Limitations and Appropriate Use of the Model

The ground-water flow model for the Eastern High Plains 

regional study area was designed to delineate contributing 

areas to public-supply wells, to help guide data collection, and 

to support future local modeling efforts. Limitations of the 

ground-water flow model, assumptions made during model 

development, and results of model calibration and sensitivity 

analysis all are factors that constrain the appropriate use of the 

model and highlight potential future improvements.

The Eastern High Plains regional ground-water flow 

model simulates flow in the High Plains aquifer, assuming 

steady-state conditions. Although hydrologic conditions for 

the nonirrigation season from 1997 to 2001 appeared in a 

quasi-steady-state condition, hydrologic conditions during 

the late 1950s through the mid-1990s were not steady state. 

The effects of these deviations from steady-state conditions 

compared to the simulated ground-water fluxes and areas contributing recharge are difficult to predict without developing a 

transient model of the last several decades, which was beyond 

the scope of this study. Results of this steady-state model may 

not be representative of instances when hydrologic conditions 

are dissimilar to the assumed steady-state conditions. Seasonally transient stresses and vertical gradients of large magnitude 

that occur in the ground-water system during the irrigation 

season are not represented in the steady-state model. Publicsupply withdrawals for 1997–2001 were greater than during 

earlier times, so the simulated areas contributing recharge and 

zones of contribution to public-supply wells using 1997–2001 

average pumping in a steady-state model are likely larger than 

those that would be calculated for previous time frames. The 

1997–2001 average areas contributing recharge and zones of 

contribution are therefore considered conservative (maximum) 

estimates of potential source areas for water reaching publicsupply wells.

Recharge was estimated and its areal distribution was 

assigned on the basis of 1997 land use (U.S. Geological Sur-
Hydrogeologic Setting and Ground-Water Flow Simulation of the Eastern High Plains Regional Study Area, Nebraska 8–25

Figure 8.13. Model-computed areas contributing recharge and zones of contribution for 12 public-supply wells, Eastern High 

Plains regional study area, Nebraska.

80

81

80

81

34

34

Big Blue River

Lincoln

Creek

Beaver

Creek

Y O R K

HAMILTON COUNTY

YORK COUNTY

Base from U.S. Geological Survey digital data,

Albers equal-area projection, standard parallels

29° 30' North and 45° 30' North, central meridian 97° 30' West, 

North American Datum of 1983

41° 00'

40° 55'

40° 50'

98° 00' 97° 45' 97° 40' 97° 35' 97° 30'

0 2 4 6 8 10 KILOMETERS

0 2 4 MILES

EXPLANATION

Land use

 Agriculture

 Urban

 Open water, wetlands, and woodlands

Area contributing recharge for public-supply wells

Extent of active model cells

Beaver Creek perennial reach

Pathlines outlining zones of contibution to public-supply wells

 Well 62–1

 Well 68–1

 Well 73–1

 Well 76–1

 Well 77–1

 Well 77–3

Wells selected for contributing-area analysis

 Well 77–4

 Well 82–1

 Well 82–2

 Well 97–1

 Well 97–1A

 Well 97–2
8–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

vey, 1999–2000). Considering the significant sensitivity of the 

model to recharge values, the recharge distribution could be a 

significant, but presently unknown, source of error.

The ground-water flow model does not account for the 

heterogeneous nature of the High Plains aquifer but rather 

approximates all lithologies as being uniform throughout each 

layer. Heterogeneous aquifer complexity is beyond the scope 

of this study, but detailed mapping of aquifer lithology and 

layering would be appropriate for more site-specific modeling 

studies.

Computed areas contributing recharge and traveltimes 

through zones of contribution are based on a calibrated 

model and estimated effective porosity values. In a steadystate model, changes to input porosity values do not change 

the area contributing recharge to a given well. Changes to 

input porosity values will change computed traveltimes from 

recharge to discharge areas in direct proportion to changes of 

effective porosity because there is an inverse linear relation 

between ground-water flow velocity and effective porosity 

and a direct linear relation between traveltime and effective 

porosity. For example, a one-percent decrease in porosity will 

result in a one-percent increase in velocity and a one-percent 

decrease in particle traveltime. A detailed sensitivity analysis 

of porosity distributions was beyond the scope of this study, 

although future work could compare simulated ground-water 

traveltimes to ground-water ages to more thoroughly evaluate 

effective porosity values.

The Eastern High Plains regional ground-water flow 

model uses justifiable aquifer properties and boundary conditions and provides a reasonable representation of ground-water 

flow conditions in the study area for 1997–2001. The model 

can be used to better understand regional water budgets and 

ground-water flow paths in the study area for the time period 

of interest but may not be suitable for long-term predictive 

simulations. The model also proved helpful for understanding the vertical movement of water between various layers of 

the High Plains aquifer. This model provides a useful tool to 

evaluate aquifer vulnerability at a regional scale, to facilitate 

comparisons of ground-water traveltime between regional 

aquifer systems, and to guide future detailed investigations in 

the study area.

References Cited

Anderson, M.P., and Woessner, W.W., 1992, Applied groundwater modeling: Academic Press, Inc., New York, 381 p.

Argonne National Laboratory, 1995, Final phase II report—

Expedited site characterization, York, Nebraska: Prepared 

for Community Credit Corporation, United States Department of Agriculture, April 1995.

Center for Advanced Land Management Information Technologies, 2000, Delineation of 1997 land use patterns for 

the Cooperative Hydrology Study in the Central Platte 

River Basin: University of Nebraska, Lincoln, Center for 

Advanced Land Management Information Technoligies.

Chen, X., and Yin, Y., 1999, Evaluation of streamflow depletion for vertical anisotropic aquifers: Journal of Environmental Systems, v. 27, no. 1, p. 55–70.

COHYST, 2001, Pre-groundwater development 1-mile 

groundwater flow model for the Eastern Model Unit: 

COoperative HYdrology STudy Technical Committee, May 

2, 2001, 46 p., accessed June 26, 2006, at http://cohyst.dnr.

ne.gov/

Conservation and Survey Division, 1980, Configuration of 

the water table 1979, 1:250,000 Lincoln and Nebraska City 

quadrangle, Nebraska: Conservation and Survey Division, 

Lincoln University of Nebraska, accessed June 26, 2006, at 

http://csd.unl.edu/general/gis-datasets.asp

Dennehy, K.F., Litke, D.W., and McMahon, P.B., 2002, The 

High Plains aquifer, USA—Groundwater development and 

sustainability, in Hiscock, K.M., Rivett, M.O., and Davison, 

R.M., eds., Sustainable groundwater development: Geological Society, London, Special Publication, 193, p. 99–119.

Dreezen, V. H., 2000, Configuration of the water table 

1995, 1:250,000 Lincoln and Nebraska City quadrangle, 

Nebraska: Conservation and Survey Division, Lincoln University of Nebraska, accessed June 26, 2006, at http://csd.

unl.edu/general/gis-datasets.asp
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Dugan, J.T., and Zelt, R.B., 2000, Simulation and analysis of 

soil-water conditions in the Great Plains and adjacent areas, 

Central United States, 1951–80: U.S. Geological Survey 

Water-Supply Paper 2427, 81 p.

Fallon, J.D., and McChesney, J.A., 1993, Surface-water-quality assessment of the lower Kansas River Basin, Kansas 

and Nebraska—project data, November 1986 through April 

1990: U.S. Geological Survey Open-File Report 93–51, 

593 p.

Freeze, R.A., and Cherry, J.A., 1979, Groundwater: Englewood Cliffs, N.J., Prentice-Hall Inc., 604 p.

Gutentag, E.D., Heimes, F.J., Krothe, N.C., Luckey, R.R., and 

Weeks, J.B., 1984, Geohydrology of the High Plains aquifer 

in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological 

Survey Professional Paper 1400–B, 63 p.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, The U.S. Geological 

Survey modular ground-water flow model—User guide to 

modularization concepts and the ground-water flow process: 

U.S. Geological Survey Open-File Report 00-92, 121 p.

Hedman, E.R., and Engel, G.B., 1989, Flow characteristics for 

selected streams in the Great Plains subregion of the Central 

Midwest Regional Aquifer System and selected adjacent 

areas—Kansas and Nebraska, and parts of Colorado, Iowa, 

Missouri, New Mexico, Oklahoma, South Dakota, Texas, 

and Wyoming: U.S. Geological Survey Hydrologic Investigations Atlas HA–708, 3 sheets.

High Plains Regional Climate Center, 2003, National Weather 

Service surface observations and automated weather data 

network: accessed March 11, 2003 at http://www.hprcc.unl.

edu/data.htm

Hill, M.C., Banta, E.R., Harbaugh, A.W., and Anderman, 

E.R., 2000, MODFLOW-2000, The U.S. Geological Survey 

modular ground-water flow model—User guide to the 

observation, sensitivity, and parameter-estimation processes 

and three post-processing programs: U.S. Geological Survey Open-File Report 00–184, 209 p.

Hill, M.C., 1998, Methods and guidelines for effective model 

calibration: U.S. Geological Survey Water-Resources Investigations Report 98–4005, 90 p.

Johnson, C.R., and Keech, C.F., 1959, Geology and groundwater resources of the Big Blue River Basin above Crete, 

Nebraska, with a section on chemical quality of water, by 

Robert Brennan: U.S. Geological Survey Water-Supply 

Paper 1474, 94 p.

Keech, C.F., Dreeszen, V.H., and Emery, P.A., 1967, Availability of ground water in York County, Nebraska: U.S. 

Geological Survey Water-Supply Paper 1839–F, 17 p.

Leake, S.A., and Claar, D.V., 1999, Procedures and computer 

programs for telescopic mesh refinement using MODFLOW: U.S. Geological Survey Open-File Report 99–238, 

53 p.

Litke, D.W., 2001, Historical water-quality data for the High 

Plains Regional Ground-Water study area in Colorado, 

Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, 

Texas, and Wyoming, 1930-98: U.S. Geological Survey 

Water-ResourcesInvestigations Report 00–4254, 65 p.

Luckey, R.R., Gutentag, E.D., Heimes, F.J., and Weeks, J.B., 

1986, Digital simulation of ground-water flow in the High 

Plains aquifer in parts of Colorado, Kansas, Nebraska, New 

Mexico, Oklahoma, South Dakota, Texas, and Wyoming: 

U.S. Geological Survey Professional Paper 1400–D, 63 p.

Luckey, R.R., and Becker, M.F., 1999, Hydrogeology, water 

use, and simulation of flow in the High Plains aquifer in 

northwestern Oklahoma, southeastern Colorado, southwestern Kansas, northeastern New Mexico, and northwestern 

Texas: U.S. Geological Survey Water-Resources Investigations Report 99–4104, 35 p.

Ma, Li, 1996, Impact of artificial groundwater recharge at two 

Nebraska sites: Lincoln University of Nebraska, Ph.D. dissertation, 209 p.

Ma, Li, and Spalding, R.F., 1997, Herbicide persistence and 

mobility in a recharge lake watershed in York, Nebraska: 

Journal of Environmental Quality, v. 26, no. 1, p. 115–125.

Mustik, J.T., and Stewart, B.A., 1992, Irrigation technologies, in Kromm, D.E., and White, S.E., eds., Groundwater 

exploitation in the High Plains: Lawrence, University Press 

of Kansas, p. 110–144.

Nebraska Department of Natural Resources, 2002, Registered 

groundwater wells data base: accessed January–July 2002, 

at http://nrcnt3.dnr.state.ne.us/wellssql/wellsindex.asp

Pollock, D.W., 1994, User’s guide for MODPATH/MODPATH-PLOT, Version 3—A particle tracking post-processing package for MODFLOW, the U.S. Geological Survey 

finite-difference ground-water flow model: U.S. Geological Survey Open-File Report 94–464, accessed Feb. 6, 

2007, at http://water.usgs.gov/nrp/gwsoftware/modpath41/

modpath41.html

Qi, S.L., Konduris, Alexandria, Litke, D.W., and Dupree, Jean, 

2002, Classification of irrigated land using satellite imagery, 

the High Plains aquifer, nominal date 1992: U.S. Geological 

Survey Water-Resources Investigations Report, 02–4236, 

35 p.

Smith, F.A., 2000, York County test-hole logs: Nebraska 

Water Survey Test-Hole Report No. 93, Conservation 

and Survey Division, Institute of Agriculture and Natural 

Resources, 60 p.
8–28 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

Swinehart, J.B., Dreeszen, V.H., Richmond, G.M., Tipton, 

M.J., Bretz, R., Steece, F.V., Hallberg, G.R., and Goebel, 

J.E., 1994, Quaternary geologic map of the Platte River 4° 

X 6° quadrangle, United States: U.S. Geological Survey 

Miscellaneous Investigations Series Map I–1420 (NK-14), 

1 plate.

Thelin, G.P., and Heimes, F.J., 1987, Mapping irrigated 

cropland from Landsat data for determination of water use 

from the High Plains aquifer in parts of Colorado, Kansas, 

Nebraska, New Mexico, Oklahoma, South Dakota, Texas, 

and Wyoming: U.S. Geological Survey Professional Paper 

1400–C, 38 p., 1 plate.

University of Nebraska–Lincoln, 2000, Quality-assessed 

agrichemical contaminant database for Nebraska ground 

water: A cooperative project of the Nebraska Departments of Agriculture, Environmental Quality, and Natural Resources and the University of Nebraska – Lincoln: 

accessed May 15, 2002 at http://nrcnt3.dnr.state.ne.us/

clearinghouse/index.asp

Upper Big Blue Natural Resources District, 1999, A study 

of ground-water pumping for existing uses and proposed 

industrial development of the Heartland Fibers Processing 

Plant, York County, Nebraska: York, Nebraska, Upper Big 

Blue Natural Resources District, August 3, 1999, 32 p.

U.S. Census Bureau, 2003, 2000 Census of population and 

housing—population and housing unit counts: Washington, 

D.C., PHC–3–29, Nebraska,

U.S. Geological Survey, 1999-2000, National land cover data 

base: accessed June 26, 2006, at http://edcwww.cr.usgs.gov/

products/landcover.html

Verstraeten, I.M., McGuire, V.L., and Heckman, K.L., 1998, 

Hydrogeology and subsurface nitrate in the Upper Big Blue 

Natural Resources District, Central Nebraska, July 1995 

through September 1997: U.S. Geological Survey WaterResources Investigations Report 98–4207, 81 p.

Weeks, J.B., Gutentag, E.D., Heimes, F.J., and Luckey, R.R., 

1988, Summary of the High Plains Regional Aquifer-System Analysis in parts of Colorado, Kansas, Nebraska, New 

Mexico, Oklahoma, South Dakota, Texas, and Wyoming: 

U.S. Geological Survey Professional Paper 1400–A, 30 p.

Zheng, Chunmiao, and Bennett, G.D., 2002, Applied contaminant transport modeling (2nd ed.): New York, Wiley and 

Sons, 621 p.
Appendix 1. Database Dictionary for the Study 

of Anthropogenic and Natural Contaminants

TANC Database—TANC_STUDIES Table Data Dictionary ................................................................A–2

TANC Database—SITES Table Data Dictionary ..................................................................................A–4

TANC Database—WELL_INFO Table Data Dictionary .......................................................................A–6

TANC Database—RESULTS_RGNL Table Data Dictionary................................................................A–8

TANC Database—PARAMETERS Table Data Dictionary .................................................................A–10

TANC Database—PUMPING_RGNL Table Data Dictionary............................................................A–11

TANC Database—ANCILLARY Table Data Dictionary......................................................................A–13

TANC Database—CAREASUM_RGNL Table Data Dictionary.........................................................A–15

TANC Database—CAREARDXPH_RGNL Table Data Dictionary.....................................................A–22

TANC Database—CAREASRCE_RGNL Table Data Dictionary........................................................A–25
A–2 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—TANC_STUDIES Table Data Dictionary

[The TANC_Studies table stores descriptions of the TANC study areas]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

TANC_STUDY (TANC Study Identifier) Character; Width 12; MANDATORY

Each site for a study unit is given a code to identify the study unit,TANC, and the year the study unit was incorporated into the 

overall TANC study. The field is 12 characters wide so that an a, b, or c can be appended for study units with more than one 

TANC study area (nvbrtanc01a, nvbrtanc01b, sanjtanc01, hpgwtanc01)

SU_START_DATE (Study Unit Starting Date) Integer; Width 4

The year the study unit was started, or restarted in USGS NAWQA Cycle II

REGIONAL (Regional-Scale Investigation Flag) Boolean; Width 1; Yes (-1), No (0)

Indicates that the study unit conducted a TANC regional-scale investigation

LOCAL (Local-Scale Investigation Flag) Boolean; Width1; Yes (-1), No (0)

Indicates that the study unit conducted a TANC local-scale investigation

GENERAL_LOCATION (General Geographic Location) Character; Width 50

General geographic location of the TANC regional-scale investigation

SPECIFIC_LOCATION (Specific Geographic Location) Character; Width 50

Additional information on the specific geographic location of the TANC regional-scale investigation, if needed

AREA (Area of Regional-Scale Investigation) Real; Width 10; Decimal 2

Area of the regional-scale investigation, in square miles. This is the area of the regional ground-water flow model

AREA_SQUARE_KILOMETERS (Area of Regional–Scale Investigation, in Square Kilometers) Real; Width 10; Decimal 2

This is a calculated field (AREA multiplied by 2.59)

AQUIFER_LITH (Aquifer Lithology); Character; Width 4

Lithology(ies) of the aquifer simulated. For example, sand and gravel or limestone. Use USGS National Water Information 

System, Ground Water Site Inventory System (NWIS GWSI) C096 definitions (National Water Information System, Ground Water 

Site Inventory System http://pubs.usgs.gov/of/2005/1251/pdf/gwcoding_Sect2-1.pdf accessed May 15, 2007)

AQUIFER_TYPE (Aquifer Type Code); Character; Width 1

Aquifer type code for the aquifer simulated. Use NWIS GWSI [C713] definitions

PRINCIPAL_AQUIFER (USGS NAWQA Principal Aquifer); Character; Width 50

USGS NAWQA principal aquifer in which the TANC regional-scale investigation is located

LOCAL_AQUIFER_NAME (Aquifer Name); Character; Width 50

Local or study-unit name for the aquifer that is simulated in the TANC regional-scale investigation. If no local name, enter NA

PRINCIPAL_CATEGORY; Character; Width 50

Principal category of the aquifer being studied. (Values from the Ground Water Atlas of the United States http://capp.water.

usgs.gov/aquiferBasics/index.html, accessed May 23, 2007)

HIERARCHICAL _CLASS_1; Character; Width 50

First level subdivision of the principal category of aquifer being studied. (Values are from the USGS Lexicon of Hydrogeologic 

Names in the United States, which were derived from the Ground Water Atlas of the United States http://capp.water.usgs.gov/

aquiferBasics/index.html, accessed May 23, 2007)
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–3

HIERARCHICAL_CLASS_2; Character; Width 50

Second level subdivision of the principal category of aquifer being studied. (Values are from the USGS Lexicon of Hydrogeologic 

Names in the United States, which were derived from the Ground Water Atlas of the United States http://capp.water.usgs.gov/

aquiferBasics/index.html, accessed May 23, 2007)

HIERARCHICAL_CLASS_3; Character; Width 50

Third level subdivision of the principal category of aquifer being studied. (Values are from the USGS Lexicon of Hydrogeologic 

Names in the United States, which were derived from the Ground Water Atlas of the United States http://capp.water.usgs.gov/

aquiferBasics/index.html, accessed May 23, 2007)

HIERARCHICAL_CLASS_4; Character; Width 50

Fourth level subdivision of the principal category of aquifer being studied. (Values are from the USGS Lexicon of Hydrogeologic 

Names in the United States, which were derived from the Ground Water Atlas of the United States http://capp.water.usgs.gov/

aquiferBasics/index.html, accessed May 23, 2007)
A–4 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—SITES Table Data Dictionary

[The Sites table, which is joined to tables in the greater USGS NAWQA Data Warehouse http://infotrek.er.usgs.gov/

traverse/f?p=NAWQA:HOME:822423385428597, accessed May 15, 2007, stores information on sites included in the 

TANC study]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

USGS NAWQA Program study unit code. Used in conjunction with SITE_ID to create multiple-field primary key

SITE_ID (Station ID) Character; Width 24; MANDATORY

USGS NWIS GWSI (National Water Information System, Ground Water Site Inventory System, http://pubs.usgs.gov/

of/2005/1251/, accessed May 15, 2007) Site ID [C1]. If a 15-digit Site ID is not available for a retrospective data site, SITE_ID 

can be the utility’s short ID or a shortened version of STATION_NM. Must be unique within a given study unit. SITE_IDs for 

retrospective data collected from different depths at a single location also must be unique, but may be similar except for an 

ending depth added to the end of the ID (for example, CPT1A_92.5; CPT1A_110). SITES_RMKS field can be used to identify such 

sites related by depth. Used with STUDY_UNIT to create multiple-field primary key 

STATION_NM (Local Number or Name) Character; Width 50

Name for sampling location, such as common name for a well or name of a well field if aggregate samples for a well field are 

stored. Commonly will match Station Name [C12] in GWSI database. May be the same as SITE_ID if no other local number or 

name is used

TANC_STUDY (Tanc Study Identifier) Character; Width 12; MANDATORY

Used to associate sites with year Study Unit was incorporated into TANC and separate sites from different study areas within a 

single Study Unit (sanjtanc01, nvbrtanc01a, nvbrtanc01b). TANC_STUDY codes are only served to the end user from the TANC_

Studies table

SUCODE (USGS NAWQA Study Unit Network Code) Character; Width 50

Four-digit study unit abbreviation concatenated to USGS NAWQA network code. Multiple codes are allowed and must be 

separated by commas

STATE (State) Character; Width 2

 Two-character State code. Not numeric State code

LAT (Latitude of Sampling Location) Real; Width 10; Decimal 2

Same as USGS NWIS GWSI field [C9]. Units of degrees, minutes, decimal seconds, no spaces. Horizontal datum must be 

NAD83. Latitude should be considered essential

LAT_DECIMAL (Latitude in Decimal Degrees) Real; Width 10; Decimal 6

LONG (Longitude of Sampling Location) Real; Width 10; Decimal 2

Same as USGS NWIS GWSI field [C10]. Units of degrees, minutes, decimal seconds, no spaces. Datum must be NAD83. 

Longitude should be considered essential 

LONG_DECIMAL (Longitude in Decimal Degrees) Real; Width 10; Decimal 6

Longitude should be negative

COOR_METH (Method Used to Determine Lat / Long) Character; Width 1

Same as USGS NWSI GWSI field Lat/Long Method code [C35]. Valid values include–but are not limited to–D, DGPS; G, GPS; M, 

map; S, survey; U, unknown

ALTITUDE (Altitude of Land Surface) Real; Width 10; Decimal, 2

Similar to USGS NWIS GWSI [C16]. Units in feet above NGVD 29. NULL value is –9999
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–5

ALTITUDE_METERS (Altitude of Land Surface, in Meters Above NGVD 29) Real; Width, 10; Decimal, 2

This is a calculated field (ALTITUDE multiplied by 0.3048) 

STA_TYPE (TANC Station Type Code) Character; Width 2

Valid values include USGS NWIS QWDATA (National Water Information System, Water Quality System, http://pubs.usgs.gov/

of/2006/1145/ accessed May 15, 2007) Table 11 Station Type codes (GW, well; used to identify sites that are composed of a 

single well. AG, aggregate ground water; used to identify sites where water from multiple wells has been blended by a water 

supplier. ME, meteorological). An additional code that is not a valid value for the NWIS database has been added to the TANC 

database. Specifically, BH, bore hole; used to identify sites where samples are collected but a well is not established (for 

example, hydropunch site or core hole not completed as a well). The BH code is equivalent to the combined C802 and C002 (X; 

test hole) fields in the NWIS GWSI database. (Note that the code CH is NOT used to identify core holes; rather, core samples 

are associated with a GW or BH STA_TYPE code and coded in the Results_Rgnl Table [Medium = ‘E’] independently of site 

information)

SITE_USE (Primary Use of Site Code) Character; Width 2

Valid values are the same as those for the USGS NWIS QWDATA Primary Use of Site

code Table 12 (C, standby; O, observation; R, recharge; T, test; U, unused; W, withdrawal of water; Z, destroyed)

WEB_FLAG (TANC Flag for Proprietary Data) Character; Width 1

P is stored if data from the site are proprietary and not available for release. All public-supply well sites (TANC database Well_

Info table WATER_USE codes CWS, NTNCWS, TNCWS, and WS) should have proprietary data flags to prevent the accidental 

disclosure of precise well location

SITES_RMKS (Relevant Information or Remarks) Character; Width 100
A–6 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—WELL_INFO Table Data Dictionary

[The Well_Info table, which is joined to tables in the greater USGS NAWQA Data Warehouse, stores information on wells included 

in the TANC study. Sites in this table have TANC database Sites table STA_TYPE codes of GW (finished wells), BH 

(considered to be unfinished wells), or AG (site represents combined wells). Null values are coded for BH and AG sites 

where Well_Info table fields are not applicable]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

PRIN_AQFR (USGS NAWQA Principal Aquifer) Character; Width 45

Valid values include the 19 USGS NAWQA principal aquifers. Blank if not a principal aquifer

AQFR_TYPE (Aquifer Type) Character; Width 1

Valid values are the same as the USGS NWIS GWSI (National Water Information System, Ground Water Site Inventory System, 

http://pubs.usgs.gov/of/2005/1251/, accessed May 15, 2007) Aquifer Type codes [C713]

CONS_DATE (Date of First Construction) Integer; Width 8

Dates should be entered as YYYYMMDD. NULL value is -9999

CSNG_MAT (Casing Material) Character; Width, 1

Valid values are the same as USGS NWIS GWSI Casing Material codes [C80].

CSNG_DIAM (Casing Diameter) Real; Width 8; Decimal 2

Diameter of well casing, in inches. If more than one casing diameter exists, the largest diameter is recorded. NULL value –9999 

is stored if the diameter is unknown

CSNG_DIAM_CENTIMETERS (Casing Diameter, in Cm) Real; Width 8; Decimal 2

This is a calculated field (CSNG_DIAM multiplied by 2.54) 

T_OPEN_BLS (Top of Uppermost Open Interval) Real; Width 8; Decimal 2

Depth to top of uppermost open section, in feet below land surface. NULL is –9999

T_OPEN_METERS_BLS (Top of Uppermost Open Interval, in Meters Below Land Surface) Real; Width 8; Decimal 2

This is a calculated field (T_OPEN_BLS multiplied by 0.3048) 

B_OPEN_BLS (Bottom of Lowermost Open Interval) Real; Width 8; Decimal 2

Depth to bottom of lowermost open section, in feet below land surface. NULL is –9999

B_OPEN_METERS_BLS (Bottom of Lowermost Open Interval, in Meters Below Land Surface) Real; Width 8; Dec. 2

This is a calculated field (B_OPEN_BLS multiplied by 0.3048) 

NUM_OPEN (Number of Open Intervals) Character; Width 3

TOT_LENGTH_OPEN (Total Length of All Open Intervals) Real; Width 8; Decimal 2

Combined length of all open intervals, in feet. NULL value is –9999

TOT_LENGTH_OPEN_METERS (Total Length of All Open Intervals, in Meters) Real; Width 8; Decimal 2

This is a calculated field (TOT_LENGTH_OPEN multiplied by 0.3048) 

GEN_LITH (Generalized Lithology) Character; Width 4

Single USGS GWSI code [C96] to generalize lithology of combined open/sample intervals
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–7

WELL_DPTH_BLS (Well Depth) Real; Width 10; Decimal 2

Units in feet below land surface. USGS NWIS GWSI field [C28]. NULL value is –9999

WELL_DPTH_METERS_BLS (Well Depth, in Meters Below Land Surface) Real; Width 10; Decimal 2

This is a calculated field (WELL_DPTH_BLS multiplied by 0.3048) 

CAPACITY (Rated Pump Capacity) Real; Width 8; Decimal 2

USGS NWIS GWSI Rated Pump Capacity, in gallons per minute [C268]. NULL is –9999

CAPACITY_LITERS_PER_MINUTE (Rated Pump Capacity, in Liters per Minute) Real; Width 8; Decimal 2

This is a calculated field (CAPACITY multiplied by 3.785) 

WATER_USE (TANC Water Use Code) Character; Width 6

Valid values include USGS GWSI National Water Use codes [C39] (DO, domestic; IN, industrial, IR, irrigation; LV, livestock) 

and one GWSI Primary Use of Water code (U, unused). A couple of codes that are not NWIS valid values have been added 

to accommodate TANC-specific project needs. CWS, community water system—public water system that provides water to 

the same population year round. Note that a public water system is one that provides piped water for human consumption to 

at least 15 service connections or serves an average of 25 people for at least 60 days each year as defined by the USEPA’s 

Public Drinking Water Systems Programs http://www.epa.gov/safewater/pws/pwss.html#pwsinfo, accessed August 20, 2005; 

NTNCWS, nontransient noncommunity water systems—public water systems that serve at least 25 of the same people at least 

6 months of the year and include schools, factories, and hospitals; and TNCWS, transient noncommunity water systems—

systems that cater to transitory customers in nonresidential areas (campgrounds, motels, and gas stations). NWIS code CO 

(commercial) is used if it is not known whether a noncommunity water system is an NTNCWS or a TNCWS. If no information 

can be found other than that the well is for water supply, WS is used

POP_SERVED (CWS, NTNCWS, & TNCWS Populations Served) Character; Width 2

Code used to further qualify Public Water Systems. Valid values include VS, very small <500 served; S, small 501–3,300; M, 

medium 3,301–10,000; L, large 10,001–100,000; VL, very large > 100,000

DRILLERS_LOG (Hyperlink to .pdf of Driller’s Log) Hyperlink

Intended for wells drilled specifically for the TANC study

WELL_INFO_RMKS (Relevant Information or Remarks) Character; Width 100

Good place for a study unit to code whether a CWS is screened across a confining unit
A–8 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—RESULTS_RGNL Table Data Dictionary

[The Results_Rgnl table stores information on concentrations or measurements associated with TANC regional-scale 

investigations. Entries are restricted to USGS NWIS QWDATA (National Water Information System, Water Quality 

System, http://pubs.usgs.gov/of/2006/1145/, accessed May 16, 2007) Sample Type codes 9, regular, and H, composite]

R_ID (Results ID) Integer; Width 10

Automatic sequence number used to serve as primary key for the Results_Rgnl table

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

DATE (Sample Date) Integer; Width 8; MANDATORY

Dates should be entered as YYYYMMDD

PCODE (Used to Uniquely Identify Parameter) Character; Width 7; MANDATORY

Code used to uniquely identify parameter, typically 5 digits. Additional information on parameters for which data exist in the 

TANC database can be found in the Parameters table. Null value –9999 will NOT be used 

PNAME (Short Name for Parameter) Character; Width 30; MANDATORY

Entry must be identical to PNAME in the Parameters table

RESULT (Concentration or Measurement Reported) Real; Width, autoformat

Only 1 RESULT per PCODE per DATE for a given STUDY_UNIT / SITE_ID / MEDIUM combination can be stored for a site

REMARK_CODE (Info about the Magnitude [or Absence] of a Value) Character; Width 1

Valid values are the same as those for the USGS NWIS QWDATA Remarks Code Table 10 (Result Level) field

UNITS (Units for RESULT) Character; Width 27

Required units for each PCODE are specified in the TANC Parameters table

AGENCY (Source of Data) Character; Width 50

Collecting agency from which RESULTs were procured (for example, Ohio EPA or Ohio Department of Health). Valid agency 

descriptions, not codes from the NWIS QWDATA Collecting Agency list, are used where applicable. Separate entries for PCODE 

00027 will not be coded

RETRO (Flag to Identify Result as TANC Retro Data) Character; Width 1

‘R’ is stored if the RESULT is part of the TANC retrospective data compilation. A blank is stored if the RESULT is not part of the 

retro compilation

MEDIUM (Code for Sample Medium) Character; Width 1; MANDATORY

6 (ground water), 7 (wet deposition), E (core material), F (interstitial water), $ (treated water supply). These are USGS NWIS 

QWDATA Medium codes

BEGIN_DPTH_BLS (Sample Beginning Depth) Real; Width 8; Decimal 2

Depth to top of sampled interval, in feet below land surface. Generally equal to top of screened interval for ground-water 

samples from wells. NULL is –9999

BEGIN_DPTH_METERS_BLS (Sample Beginning Depth, in Meters Below Land Surface) Real; Width 8; Decimal 2

This is a calculated field (BEGIN_DPTH_BLS multiplied by 0.3048) 
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–9

END_DPTH_BLS (Sample Ending Depth) Real; Width 8; Decimal 2

Depth to bottom of sampled interval, in feet below land surface. Generally equal to bottom of screened interval for ground-water 

samples from wells. NULL is –9999

END_DPTH_METERS_BLS (Sample Ending Depth, in Meters Below Land Surface) Real; Width 8; Decimal 2

This is a calculated field (END_DPTH_BLS multiplied by 0.3048) 

FILTERED (Flag to Indicate if Sample was Filtered) Character; Width 1

Y, sample filtered; N, sample not filtered; blank if unknown or not applicable

ANAL_METH (Analytical Test Method Number) Character; Width 20

Valid values include USGS NWIS method codes, USEPA test method numbers http://www.epa.gov/epahome/index/, accessed 

May 15, 2007, Standard Methods for Examination of Water and Wastewater numbers (Cleseri and others, 1998), ASTM method 

numbers http://enterprise.astm.org/filtrexx40.cgi?index.frm, accessed May 15, 2007. Insert EPA or SM or ASTM in all caps 

followed by blank space before actual number

DET_LIMIT (Detection Limit) Real; Width, autoformat

The larger of the reported MDL—method detection limit—OR the MRL—minimum reporting limit—OR the LRL—laboratory 

reporting level—OR the PQL—practical quantitation limit. Units should match the required units for the PCODE in the TANC 

Parameters table

RESULTS_RMKS (Relevant Information or Remarks) Character; Width 100

Good place to note type of treatment for treated water-supply samples, if known. Additional laboratory data qualifiers also could 

be stored here

Reference Cited

Cleseri, L.S., Greenberg, A.E., and Eaton, A.D., eds., 1998, Standard methods for the examination of waste and wastewater 

(20th ed.): Washington, D.C., American Public Health Association, 1220 p.
A–10 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—PARAMETERS Table Data Dictionary

[The Parameters table includes information on parameters that are included in the TANC study]

PCODE (Parameter Code) Character; Width 7; MANDATORY

Code used to uniquely identify parameter, typically 5 digits. Generally follows usage of the USGS NWIS QWDATA (National 

Water Information System, Water Quality System, http://pubs.usgs.gov/of/2006/1145/, accessed May 15, 2007) database 

as of November, 2006. Several PCODEs from USEPA’s STORET database http://www.epa.gov/storpubl/legacy/ref_tables.

htm, accessed August 20, 2005, that are not valid values for NWIS are included in the TANC database to accommodate 

miscellaneous retrospective data obtained from outside sources. Valid values for parameters not in NWIS are coded in the 

TANC database as the STORET PCODE or the closest NWIS PCODE followed by a ‘.u’ for unofficial (for example, 81853.u, 

Trichloroethane, wu). Primary key for the Parameters table

PNAME (Short Name for Parameter) Character; Width 30; MANDATORY

Generally the ‘Short Name’ used in the USGS NWIS database as of November, 2006

R_UNITS (Required Units for Parameter) Character; Width 27

All results for a given PCODE must be converted to these required units before 

data are entered into the TANC database Results_Rgnl table

L_PNAME (Long Name for Parameter) Character; Width 175

‘Long Name’ in the November, 2006 parameters file for use in NWIS. More descriptive than the previous NWIS ‘Long Name’. 

Can be used to differentiate between similar parameters in NWIS

MCL (Maximum Contaminant Level) Real; Width, autoformat

The highest level of a contaminant that is allowed in drinking water http://www.epa.gov/safewater/mcl.html, accessed May 

15, 2007. MCLs are set as close to Maximum Contaminant Level Goals (MCLGs) as feasible using the best available treatment 

technology and taking cost into consideration. MCLs are enforceable standards. MCLs in the TANC database are stored in the 

same units as those specified for the parameter in the R_UNITS field

CAS_NUM (Unique Identifier for a Chemical Substance) Character; Width 12

Chemical Abstracts Service’s unique numeric identifier in the CAS Registry http://www.cas.org/EO/regsys.html, accessed 

May 15, 2007, for a chemical substance. Each CAS Registry Number designates only one substance and has no chemical 

significance. CAS numbers can be used to acquire information about chemical substances and will be useful for retrieving 

results for all PNAMEs associated with a particular substance regardless of PCODE. CAS numbers are not relevant for 

parameters unrelated to a chemical substance, such as Flow Rate

PARAMETERS_RMKS (Relevant Information or Remarks) Character; Width 100

Includes info on how PCODEs from outside sources are mapped to NWIS PCODEs, where relevant
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–11

TANC Database—PUMPING_RGNL Table Data Dictionary

[The Pumping_Rgnl table stores information about ALL pumping centers simulated in each of the TANC regional 

ground-water flow models, including pumping centers with no chemistry or contributing-area data stored in the 

database. This table enables the rest of the data in the database to be placed into a broader context with respect to 

pumping. It is a standalone table because, in many instances, different well identifiers were used in the models and in 

the Sites table]

TANC_STUDY (Tanc Study Identifier) Character; Width 12; MANDATORY

Used to associate sites with year Study Unit was incorporated into TANC and separate sites from different study areas within a 

single Study Unit (sanjtanc01, nvbrtanc01a, nvbrtanc01b).

WELL_ID (Well ID) Character; Width 24; MANDATORY

Unique well identifier used in the regional ground-water flow model

SITE_ID (Station ID) Character; Width 24

Site ID. Entry must be identical to the Sites table entry. Stored only for wells where the relationship between the WELL_ID and 

the SITE_ID in the Sites table is known. Some wells may exist within the Pumping_Rgnl table and the Sites table, but not contain 

a SITE_ID entry in the Pumping_Rgnl table because the relationship between the model WELL_ID and the SITE_ID cannot be 

readily determined

MFPUMP (Pumping Rate from Flow Model) Real; Width 8; Decimal 2

Representative pumping rate for the period of study (for example, 1997–2001 for most studies begun in 2001). Yield of well, in 

gallons per minute. Used to generate the contributing area data in the CAreaSum_Rgnl, CAreaRdxpH_Rgnl, and CAreaSrce_

Rgnl tables. Value will be identical to the value in the RATE field of the Ancillary table where the simulated pumping center 

represents an individual well, as opposed to multiple wells. Additional information on the pumping rate can be found in the 

MFPUMP_REMARK field

MFPUMP_LITERS_PER_MINUTE (Pumping Rate from Flow Model, in Liters per Minute) Real; Width 8; Decimal 2

This is a calculated field (MFPUMP multiplied by 3.785) 

MFPUMP_REMARK (Information Related to Pumping Rate from Flow Model) Char; Width 100

Additional information on the representative pumping rate in MFPUMP field. Must identify the period represented by the 

pumping rate. Should also record whether the MFPUMP entry represents the most recent pumping value for the stated period 

(if pumping was fairly constant) or some other representative value, such as the median

SOURCE (Source of Pumping Data) Character; Width 100

Source of the pumping data incorporated in the regional ground-water flow model

CWS (Flag to Indicate if a Well IS a Community Water Supply Well) Integer; Width 1

‘1’ is stored for wells that are community water-supply wells; ‘0’ is stored for other types of supply wells, such industrial wells or 

irrigation wells

T_OPEN_BLS (Top of Uppermost Open Interval) Real; Width 8; Decimal 2

Depth to top of uppermost open section/top of screened interval, in feet below land surface. NULL is –9999

T_OPEN_METERS_BLS (Top of Uppermost Open Interval, in Meters Below Land Surface) Real; Width 8; Decimal 2

This is a calculated field (T_OPEN_BLS multiplied by 0.3048) 

B_OPEN_BLS (Bottom of Lowermost Open Interval) Real; Width 8; Decimal 2

Depth to bottom of lowermost open section/screened interval, in feet below land surface. NULL is -9999

B_OPEN_METERS_BLS (Bottom of Lowermost Open Interval, in Meters Below Land Surface) Real; Width 8; Decimal 2

This is a calculated field (B_OPEN_BLS multiplied by 0.3048) 
A–12 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

SIMULATED_T_OPEN_BLS (Top of Uppermost Simulated Open Interval) Real; Width 8; Decimal 2

Depth to top of uppermost simulated open section/top of screened interval, in feet below land surface. NULL is –9999

SIMULATED_T_OPEN_METERS_BLS (Top of Uppermost Simulated Open Interval, in Meters Below Land Surface) Real; 

Width 8; Decimal 2

This is a calculated field (SIMULATED_T_OPEN_BLS multiplied by 0.3048) 

SIMULATED_B_OPEN_BLS (Bottom of Lowermost Simulated Open Interval) Real; Width 8; Decimal 2

Depth to bottom of lowermost simulated open section/screened interval, in feet below land surface. NULL is –9999

SIMULATED_B_OPEN_METERS_BLS (Bottom of Lowermost Simulated Open Interval, in Meters Below Land Surface) Real; 

Width 8; Decimal 2

This is a calculated field (SIMULATED_B_OPEN_BLS multiplied by 0.3048) 

MF_COL (Column in Modflow Model) Integer; Width 5

MF_ROW (Row in Modflow Model) Integer; Width 5

MF_TOP_LAYER (Model Layer that Corresponds to the Top of the Screened Interval) Integer; Width 2

MF_BOT_LAYER (Model Layer that Corresponds to the Bottom of the Screened Interval) Integer; Width 2

RANK_ALL (Percentile Rank of All Wells) Real; Width, Autoformat

Percentile rank of pumping within a given study unit based on ALL simulated pumping centers in the regional ground-water flow 

model

RANK_CWS (Percentile Rank of All Wells) Real; Width, Autoformat

Percentile rank of pumping within a given study unit based on simulated community water-supply wells in the regional groundwater flow model

PUMPNG_RGNL_RMKS (Relevant Information or Remarks) Character; Width 100
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–13

TANC Database—ANCILLARY Table Data Dictionary

[The Ancillary table, which is joined back to tables in the greater USGS NAWQA Data Warehouse, stores ancillary data used 

to assist the TANC study team]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

SWQA (Flag to Indicate Selected Use of Site) Integer; Width 1

‘1’ is stored for sites sampled as part of the NAWQA Source Water-Quality Assessment (SWQA) study. ‘2’ is stored for sites 

where samples similar to SWQA study samples (‘SWQA-like’ samples) were specifically collected for the TANC study. ’0’ is 

stored for sites where neither SWQA nor SWQA-like samples were collected for use by the TANC study team 

RDX_SWQA (Code to Indicate Redox Signature) Character; Width 6

Code to describe SWQA sample in terms of redox indicators. ‘O2’ is stored when sample has a signature consistent with 

oxygen reducing; ‘NO3’, consistent with denitrifying; ‘MN’, consistent with manganese reducing; ‘FEHSO4’, consistent with iron 

reducing high sulfate; ‘FELSO4’, consistent with iron reducing low sulfate. ‘X’ (miXed) is stored when sample contains evidence 

of two or more redox states; ‘R#’ (Range) is stored when redox indicators are missing from sample and redox signature can’t 

be narrowed beyond a given range; # holds the number of redox indicator species used to describe redox (for example, R3; 

Nitrate, ferrous iron, and sulfate data are available). ‘I’ (Indeterminate) is stored where appropriate data are available but are 

not consistent with any of the above categories. Blank is stored if data are insufficient to describe redox. The TANC redoxclassification system is the foundation for assigning redox codes

RDX_SWQAQ (X and R Redox Signature Qualifier) Character; Width 30

Code to further qualify samples for which an X or R# code is stored in the RDX_SWQA field. Valid values include any 

combination of the following redox codes: O2, NO3, MN, FEHSO4, FELSO4 separated by ‘/’. A ‘?’ will identify redox states that 

can’t be ruled out due to lack of data (for example, O2?/NO3?/; O2 data are missing and NO3 is present above the significance 

level)

BAL_RETRO (Charge Balance Flag for Retro Data Sample) Integer; Width 1

‘2’ is stored for sites where the representative retro data sample balances electrochemically within 10 percent; ‘1’ is stored if 

the sample is not balanced; and ‘0’ is stored if a charge balance was not or could not be calculated

RDX_RETRO (Code to Indicate Redox Signature) Character; Width 6

Code to describe representative retro data sample for the site in terms of redox indicators. ‘O2’ is stored when sample has a 

signature consistent with oxygen reducing; ‘NO3’, consistent with denitrifying; ‘MN’, consistent with manganese reducing; 

‘FEHSO4’, consistent with iron reducing high sulfate; ‘FELSO4’, consistent with iron reducing low sulfate. ‘X’ (miXed) is stored 

when sample contains evidence of two or more redox states; ‘R#’ (Range) is stored when redox indicators are missing from 

sample and redox signature can’t be narrowed beyond a given range; # holds the number of redox indicator species used 

to describe redox (for example, R3; Nitrate, ferrous iron, and sulfate data are available). ‘I’ (Indeterminate) is stored where 

appropriate data are available but are not consistent with any of the above categories. Blank is stored if data are insufficient to 

describe redox. The TANC redox-classification system is the foundation for assigning redox codes

RDX_RETROQ (X and R Redox Signature Qualifier) Character; Width 30

Code to further qualify samples for which an X or R# code is stored in the RDX_RETRO field. Valid values include any 

combination of the following redox codes: O2, NO3, MN, FEHSO4, FELSO4 separated by ‘/’. A ‘?’ will identify redox states that 

can’t be ruled out due to lack of data (for example, O2?/NO3?/; O2 data are missing and NO3 is present above the significance 

level)

QW (Flag to Indicate if Site HAS Water Quality Data) Integer; Width 1

‘1’ is stored for sites with water-quality data in the database 
A–14 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

SOLIDS (Flag to Indicate if Site HAS Solid Phase Data) Integer; Width 1

‘1’ is stored for sites with solid phase data

C_AREA (Flag to Indicate if Site HAS Simulated Contributing Area) Integer; Width 1

Flag to indicate if site has contributing area data in the TANC database modeling tables (CAreaSum_Rgnl, CAreaRdxpH_Rgnl, 

and CAreaSrce_Rgnl). ‘1’ is stored where data in the modeling tables represent the individual site; ‘2’ is stored where data in 

the modeling tables represent multiple sites, including the individual site, and occurs when contributing areas were computed 

using combined pumping from more than one well in the same model grid block due to a lack of well-by-well location 

information

INSIDE_MODEL (Flag to Indicate if Site is IN Modeled Area) Integer; Width 1

‘1’ is stored for sites WITHIN the boundary of the regional ground-water flow modeled area. ‘0’ is stored if the site is NOT within 

the regional ground-water flow modeled area

RATE (Representative Pumping Rate) Real; Width 8; Decimal 2

Representative pumping rate for the selected period of study (for example, 1997–2001 for most studies begun in 2001). Yield 

of well, in gallons per minute. May be based on the most recent value for the period, if pumping was fairly constant, or can 

be a median. The key here is to store what is most representative for the well/study area and to note what was done in the 

RATE_REMARK field. Generally consistent with pumping rates simulated in the regional ground-water flow model. Value will be 

less than the rate simulated in the corresponding model when the simulated pumping rate represents combined pumping from 

multiple sites (i.e., C_AREA flag of ‘2’) 

RATE_LITERS_PER_MINUTE (Representative Pumping Rate) Real; Width 8; Decimal 2

This is a calculated field (RATE multiplied by 3.785) 

RATE_REMARK (Information Related to Representative Pumping Rate) Char; Width 100

Additional information on the representative pumping rate stored in the RATE field. Must include the period of time represented 

by the pumping rate

LOCAL_NETWORK (Flag to Indicate if Site IS Part of a TANC Local-Scale Sampling Network) Integer; Width 1

‘1’ is stored for sites that are part of a TANC local-scale sampling network

TANC_ANCILLARY_RMKS (Relevant Information or Remarks) Char; Width 100

Good place to store info related to the retro redox determination

Reference Cited

Chapelle, F.H., 2001, Ground-water microbiology and geochemistry (2nd ed.): New York, John Wiley and Sons, Inc., p. 291.
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–15

TANC Database—CAREASUM_RGNL Table Data Dictionary

[The CAreaSum_Rgnl table stores information on supply-well contributing areas from TANC regional-scale 

investigations. All fields summarize steady-state contributing areas for discharging supply wells that were computed 

by use of regional ground-water flow models and pumping data stored in the Pumping_Rgnl table]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

AREA_CONTRIBUTING_RECHARGE (Area Contributing Recharge, In Square Feet) Real; Width; autoformat

Steady state ‘area contributing recharge’ to the simulated discharging supply well, in square feet, computed using pumping 

data stored in the Pumping_Rgnl table. Follows usage of the USGS Office of Ground Water (OGW Technical Memorandum 

No. 2003.02 http://water.usgs.gov/admin/memo/GW/auto.html, accessed May 15, 2007) and is the surface area on the threedimensional boundary of the ground-water system that delineates the location of the water entering the ground-water system 

that eventually flows to the well and discharges

AREA_CONTRIBUTING_RECHARGE_SQUARE_METERS (Area Contributing Recharge, In Square Meters) Real; Width; 

autoformat

This is a calculated field (AREA_CONTRIBUTING_RECHARGE multiplied by 0.0929) 

ZOC_AREA (Area of Zone of Contribution, In Square Feet) Real; Width, autoformat

Steady state ‘areal extent of the zone of contribution’ to the simulated discharging supply well, in square feet, computed using 

pumping data stored in the Pumping_Rgnl table. Follows usage of the USGS Office of Ground Water and is the projection of 

the three-dimensional volume of water flowing to the discharging well to a two-dimensional map [see AREA_CONTRIBUTING_

RECHARGE for reference]

ZOC_AREA_SQUARE_METERS (Area of Zone of Contribution, In Square Meters) Real; Width, autoformat

This is a calculated field (ZOC_AREA multiplied by 0.0929)

ZOC_VOLUME (Volume of Zone of Contribution) Real; Width, autoformat

Steady state ‘zone of contribution’ to the simulated discharging supply well, in cubic feet. Follows usage of the USGS Office of 

Ground Water and is the three-dimensional volumetric part of the aquifer through which ground water flows to the discharging 

well from the area contributing recharge [see AREA_CONTRIBUTING_RECHARGE for reference]

ZOC_VOLUME_CUBIC_METERS (Volume of Zone of Contribution, In Cubic Meters) Real; Width, autoformat

This is a calculated field (ZOC_VOLUME multiplied by 0.02832)

TOTINFLOW (Simulated Inflow to Supply Well, In Cubic Feet Per Second) Real; Width, autoformat

Flow to supply well computed from forward tracked particles, in cubic feet per second

TOTINFLOW_CUBIC_METERS_PER_SECOND (Simulated Inflow to Supply Well, In Cubic Meters Per Second) Real; 

Width, autoformat

This is a calculated field (TOTINFLOW multiplied by 0.02832) 

TTMIN (Minimum Traveltime) Real; Width, autoformat

Minimum traveltime along simulated particle pathlines that define the zone of contribution to the supply well, in years

TTMAX (Maximum Traveltime) Real; Width, autoformat

Maximum traveltime along simulated particle pathlines that define the zone of contribution to the supply well, in years

TT_LT10YR_PCT (Percent of Well Inflow <10 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 10 years
A–16 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TT_LT20YR_PCT (Percent of Well Inflow <20 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 20 years 

TT_LT30YR_PCT (Percent of Well Inflow <30 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 30 years 

TT_LT40YR_PCT (Percent of Well Inflow <40 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 40 years 

TT_LT50YR_PCT (Percent of Well Inflow <50 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 50 years 

TT_LT60YR_PCT (Percent of Well Inflow <60 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 60 years 

TT_LT100YR_PCT (Percent of Well Inflow <100 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 100 years 

TT_LT200YR_PCT (Percent of Well Inflow <200 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime less than 200 years 

TT_GTE200YR_PCT (Percent of Well Inflow >= 200 Years) Real; Width, autoformat

Percentage of inflow to the supply well that has a simulated traveltime equal to or greater than 200 years 

TIME_10TH (10th Percentile Traveltime, In Years) Real; Width, autoformat

10th percentile of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the 

supply well, in years

TIME_25TH (25th Percentile Traveltime, In Years) Real; Width, autoformat

25th percentile of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the 

supply well, in years

TIME_50TH (Median Traveltime, In Years) Real; Width, autoformat

Median of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the supply 

well, in years

TIME_75TH (75th Percentile Traveltime, In Years) Real; Width, autoformat

75th percentile of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the 

supply well, in years

TIME_90TH (90th Percentile Traveltime, In Years) Real; Width, autoformat

90th percentile of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the 

supply well, in years

TIME_MEAN (Mean Traveltime, In Years) Real; Width, autoformat

Mean of the traveltimes associated with the simulated particle pathlines that define the zone of contribution to the supply well, 

in years

DISTANCE_10TH (10th Percentile Distance Traveled) Real; Width, autoformat

10th percentile of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles

DISTANCE_10TH_KM (10th Percentile Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_10TH multiplied by 1.6093)

DISTANCE_25TH (25th Percentile Distance Traveled) Real; Width, autoformat

25th percentile of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–17

DISTANCE_25TH_KM (25th Percentile Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_25TH multiplied by 1.6093) 

DISTANCE_50TH (Median Distance Traveled) Real; Width, autoformat

Median of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles

DISTANCE_50TH_KM (Median Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_50TH multiplied by 1.6093) 

DISTANCE_75TH (75th Percentile Distance Traveled) Real; Width, autoformat

75th percentile of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles

DISTANCE_75TH_KM (75th Percentile Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_10TH multiplied by 1.6093) 

DISTANCE_90TH (90th Percentile Distance Traveled) Real; Width, autoformat

90th percentile of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles

DISTANCE_90TH_KM (90th Percentile Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_90TH multiplied by 1.6093)

DISTANCE_MEAN (Mean Distance Traveled) Real; Width, autoformat

Mean of the length of the simulated particle pathlines that define the zone of contribution to the supply well, in miles

DISTANCE_MEAN_KM (Mean Distance Traveled, In Kilometers) Real; Width, autoformat

This is a calculated field (DISTANCE_MEAN multiplied by 1.6093) 

VELOCITY_10TH (10th Percentile Velocity) Real; Width, autoformat

10th percentile of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in 

miles per year

VELOCITY_10TH_ KILOMETERS_PER_YEAR (10th Percentile Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_10TH multiplied by 1.6093) 

VELOCITY_25TH (25th Percentile Velocity) Real; Width, autoformat

25th percentile of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in 

miles per year

VELOCITY_25TH_ KILOMETERS_PER_YEAR (25th Percentile Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_25TH multiplied by 1.6093) 

VELOCITY_50TH (Median Velocity) Real; Width, autoformat

Median of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in miles per 

year

VELOCITY_50TH_ KILOMETERS_PER_YEAR (Median Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_50TH multiplied by 1.6093) 

VELOCITY_75TH (75th Percentile Velocity) Real; Width, autoformat

75th percentile of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in 

miles per year

VELOCITY_75TH_ KILOMETERS_PER_YEAR (75th Percentile Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_75TH multiplied by 1.6093) 
A–18 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

VELOCITY_90TH (90th Percentile Velocity) Real; Width, autoformat

90th percentile of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in 

miles per year

VELOCITY_90TH_ KILOMETERS_PER_YEAR (90th Percentile Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_90TH multiplied by 1.6093) 

VELOCITY_MEAN (Mean Velocity) Real; Width, autoformat

Mean of the velocities for the simulated particle pathlines that define the zone of contribution to the supply well, in miles per 

year

VELOCITY_MEAN_ KILOMETERS_PER_YEAR (Mean Velocity, In Kilometers per Year) Real; Width, autoformat

This is a calculated field (VELOCITY_MEAN multiplied by 1.6093)

PERM (Permeability, In Inches/Hour) Real; Width, autoformat

Flow-weighted average permeability of the soil in the area contributing recharge to the supply well, in inches/hour. Values from 

STATSGO Soil Characteristics for the Conterminous United States http://water.usgs.gov/lookup/getspatial?muid, accessed 

August 20, 2005

PERM_CM_PER_HOUR (Permeability, In Centimeters/Hour) Real; Width, autoformat

This is a calculated field (PERM multiplied by 2.54) 

AWC (Available Water Capacity) Real; Width, autoformat

Flow-weighted average available water capacity of the soil in the area contributing recharge to the supply well, in inches per 

inch [see PERM for data reference]

OM (Organic Material) Real; Width, autoformat

Flow-weighted average organic material in soil in the area contributing recharge to the supply well, in percent by weight [see 

PERM for data reference]

SAND (Percent Sand) Real; Width, autoformat

Flow-weighted average percent sand in soil in the area contributing recharge to the supply well [see PERM for data reference]

SILT (Percent Silt) Real; Width, autoformat

Flow-weighted average percent silt in soil in the area contributing recharge to the supply well [see PERM for data reference]

CLAY (Percent clay) Real; Width, autoformat

Flow-weighted average percent clay in soil in the area contributing recharge to the supply well [see PERM for data reference]

HDG_A (Percent Soil in Hydrologic Drainage Group A) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group A in area contributing recharge to the supply well [see PERM 

for data reference]

HDG_AC (Percent Soil in Hydrologic Drainage Group AC) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group AC in area contributing recharge to the supply well [see 

PERM for data reference]

HDG_AD (Percent Soil in Hydrologic Drainage Group AD) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group AD in area contributing recharge to the supply well [see 

PERM for data reference]

HDG_B (Percent Soil in Hydrologic Drainage Group B) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group B in area contributing recharge to the supply well [see PERM 

for data reference]
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–19

HDG_BC (Percent Soil in Hydrologic Drainage Group BC) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group BC in area contributing recharge to the supply well [see 

PERM for data reference]

HDG_BD (Percent Soil in Hydrologic Drainage Group BD) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group BD in area contributing recharge to the supply well [see 

PERM for data reference]

HDG_C (Percent Soil in Hydrologic Drainage Group C) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group C in area contributing recharge to the supply well [see PERM 

for data reference]

HDG_CD (Percent Soil in Hydrologic Drainage Group CD) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group CD in area contributing recharge to the supply well [see 

PERM for data reference]

HDG_D (Percent Soil in Hydrologic Drainage Group D) Real; Width, autoformat

Flow-weighted average percent soil in hydrologic drainage group D in area contributing recharge to the supply well [see PERM 

for data reference]

SAND_10TH (10th Percentile Traveltime Through Sand, In Years) Real; Width, autoformat

10th percentile of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers

SAND_25TH (25th Percentile Traveltime Through Sand, In Years) Real; Width, autoformat

25th percentile of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers

SAND_50TH (Median Traveltime Through Sand, In Years) Real; Width, autoformat

Median of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply well, in 

years. Based on discretized lithologies as defined by study unit modelers

SAND_75TH (75th Percentile Traveltime Through Sand, In Years) Real; Width, autoformat

75th percentile of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers

SAND_90TH (90th Percentile Traveltime Through Sand, In Years) Real; Width, autoformat

90th percentile of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers

SAND_MEAN (Mean Traveltime Through Sand, In Years) Real; Width, autoformat

Mean of traveltimes through sand along simulated particle pathlines that define the zone of contribution to the supply well, in 

years. Based on discretized lithologies as defined by study unit modelers

SLITCLAY_10TH (10th Percentile Traveltime Through Clay, Silt, or Till, In Years) Real; Width, autoformat

10th percentile of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SILTCLAY _25TH (25th Percentile Traveltime Through Clay, Silt or Till, In Years) Real; Width, autoformat

25th percentile of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SILTCLAY _50TH (Median Traveltime Through Clay, Silt, or Till, In Years) Real; Width, autoformat

Median of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers
A–20 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

SILTCLAY _75TH (75th Percentile Traveltime Through Clay, Silt, or Till, In Years) Real; Width, autoformat

75th percentile of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SILTCLAY _90TH (90th Percentile Traveltime Through Clay, Silt, or Till, In Years) Real; Width, autoformat

90th percentile of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SILTCLAY _MEAN (Mean Traveltime Through Clay, Silt, or Till, In Years) Real; Width, autoformat

Mean of traveltimes through clay, silt, or till along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers 

CARBONATE_10TH (10th Percentile Traveltime Through Carbonate, In Years) Real; Width, autoformat

10th percentile of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CARBONATE _25TH (25th Percentile Traveltime Through Carbonate, In Years) Real; Width, autoformat

25th percentile of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CARBONATE _50TH (Median Traveltime Through Carbonate, In Years) Real; Width, autoformat

Median of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers

CARBONATE _75TH (75th Percentile Traveltime Through Carbonate, In Years) Real; Width, autoformat

75th percentile of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CARBONATE _90TH (90th Percentile Traveltime Through Carbonate, In Years) Real; Width, autoformat

90th percentile of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CARBONATE _MEAN (Mean Traveltime Through Carbonate, In Years) Real; Width, autoformat

Mean of traveltimes through carbonate along simulated particle pathlines that define the zone of contribution to the supply well, 

in years. Based on discretized lithologies as defined by study unit modelers

SEDIMENTARY_10TH (10th Percentile Traveltime Through Sedimentary, In Years) Real; Width, autoformat

10th percentile of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SEDIMENTARY _25TH (25th Percentile Traveltime Through Sedimentary, In Years) Real; Width, autoformat

25th percentile of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SEDIMENTARY _50TH (Median Traveltime Through Sedimentary, In Years) Real; Width, autoformat

Median of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

SEDIMENTARY _75TH (75th Percentile Traveltime Through Sedimentary, In Years) Real; Width, autoformat

75th percentile of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

SEDIMENTARY _90TH (90th Percentile Traveltime Through Sedimentary, In Years) Real; Width, autoformat

90th percentile of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–21

SEDIMENTARY _MEAN (Mean Traveltime Through Sedimentary, In Years) Real; Width, autoformat

Mean of traveltimes through sedimentary rock along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE_10TH (10th Percentile Traveltime Through Crystalline, In Years) Real; Width, autoformat

10th percentile of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE _25TH (25th Percentile Traveltime Through Crystalline, In Years) Real; Width, autoformat

25th percentile of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE _50TH (Median Traveltime Through Crystalline, In Years) Real; Width, autoformat

Median of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to the 

supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE _75TH (75th Percentile Traveltime Through Crystalline, In Years) Real; Width, autoformat

75th percentile of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE _90TH (90th Percentile Traveltime Through Crystalline, In Years) Real; Width, autoformat

90th percentile of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to 

the supply well, in years. Based on discretized lithologies as defined by study unit modelers

CRYSTALLINE _MEAN (Mean Traveltime Through Crystalline, In Years) Real; Width, autoformat

Mean of traveltimes through crystalline rock along simulated particle pathlines that define the zone of contribution to the supply 

well, in years. Based on discretized lithologies as defined by study unit modelers
A–22 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

TANC Database—CAREARDXPH_RGNL Table Data Dictionary

[The CAreaRdxpH_Rgnl table stores information on redox and pH conditions within supply well contributing areas from 

TANC regional-scale investigations. All fields describe the steady state ‘zone of contribution’ for discharging supply 

wells that were computed by use of regional ground-water flow models and pumping data stored in the Pumping_Rgnl 

table]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

PCT_RDXUNK (Percentage of Water Entering Well from Unknown Redox Zone) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas defined by study unit modelers as having unknown redox 

conditions

PCT_O2NO3 (Percentage of Water Entering Well from O2NO3 Redox Zone) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas defined by study unit modelers as having O2- or NO3-reducing 

redox conditions

PCT_FESO4 (Percentage of Water Entering Well from FESO4 Redox Zone) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing 

redox conditions

MAX_O2NO3 (Maximum Traveltime for a Particle Through O2NO3 Redox Zone, In Years) Real; Width, autoformat

Maximum time that any particle travels through areas defined by study unit modelers as having O2- or NO3-reducing conditions, 

in years

MAX_FESO4 (Maximum Traveltime for a Particle Through FESO4 Redox Zone, In Years) Real; Width, autoformat

Maximum time that any particle travels through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing 

conditions, in years

FESO4_GT200_PCT (Percentage of Water That Spent Greater Than 200 Years in FESO4 Redox Zone) Real; Width, autoformat

Percentage of water that discharges to the supply well that is estimated to have spent greater than 200 years in areas defined 

by study unit modelers as having Mn-, Fe- or SO4-reducing conditions

ZOC_O2NO3_PCT (Percentage of Zone of Contribution That Is In O2NO3 Redox Zone) Real; Width, autoformat

Percentage of zone of contribution that is associated with areas defined by study unit modelers as having O2- or NO3-reducing 

redox conditions

ZOC_FESO4_PCT (Percentage of Zone of Contribution That Is In FESO4 Redox Zone) Real; Width, autoformat

Percentage of zone of contribution that is associated with areas defined by study unit modelers as having Mn-, Fe- or SO4-

reducing redox conditions

TT_RDXUNK_PCT (Percentage of Total Traveltime Spent in Unknown Redox Zone) Real; Width, autoformat

Percentage of total traveltime associated with unknown redox zones

TT_O2NO3_PCT (Percentage of Total Traveltime Spent in O2NO3 Redox Zone) Real; Width, autoformat

Percentage of total traveltime associated with O2- or NO3-reducing redox conditions. Computed as O2NO3_MEAN/TIME_

MEAN*100. O2NO3_MEAN is defined in this table (CAreaRdxpH_Rgnl); TIME_MEAN is defined in the TANC database 

CAreaSum_Rgnl table
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–23

TT_FESO4_PCT (Percentage of Total Traveltime Spent in FESO4 Redox Zone) Real; Width, autoformat

Percentage of total traveltime associated with Mn-, Fe- or SO4-reducing redox conditions. Computed as FESO4_MEAN/

TIME_MEAN*100. FESO4_MEAN is defined in this table (CAreaRdxpH_Rgnl); TIME_MEAN is defined in the TANC database 

CAreaSum_Rgnl table

O2NO3_10TH (10th Percentile Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

10th percentile of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

O2NO3_25TH (25th Percentile Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

25th percentile of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

O2NO3_50TH (Median Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

Median of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

O2NO3_75TH (75th Percentile Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

75th percentile of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

O2NO3_90TH (90th Percentile Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

90th percentile of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

O2NO3_MEAN (Mean Traveltime Through O2NO3 Zone, In Years) Real; Width, autoformat

Mean of the traveltimes through areas defined by study unit modelers as having O2- or NO3-reducing conditions along simulated 

particle pathlines that define the zone of contribution to the supply well, in years

FESO4_10TH (10th Percentile Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

10th percentile of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions 

along simulated particle pathlines that define the zone of contribution to the supply well, in years

FESO4_25TH (25th Percentile Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

25th percentile of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions 

along simulated particle pathlines that define the zone of contribution to the supply well, in years

FESO4_50TH (Median Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

Median of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

FESO4_75TH (75th Percentile Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

75th percentile of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions 

along simulated particle pathlines that define the zone of contribution to the supply well, in years

FESO4_90TH (90th Percentile Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

90th percentile of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions 

along simulated particle pathlines that define the zone of contribution to the supply well, in years

FESO4_MEAN (Mean Traveltime Through FESO4 Zone, In Years) Real; Width, autoformat

Mean of the traveltimes through areas defined by study unit modelers as having Mn-, Fe- or SO4-reducing conditions along 

simulated particle pathlines that define the zone of contribution to the supply well, in years

PH_GT8_10TH (10th Percentile Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

10th percentile of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated 

particle pathlines that define the zone of contribution to the supply well, in years
A–24 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

PH_GT8_25TH (25th Percentile Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

25th percentile of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated 

particle pathlines that define the zone of contribution to the supply well, in years

PH_GT8_50TH (Median Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

Median of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated particle 

pathlines that define the zone of contribution to the supply well, in years

PH_GT8_75TH (75th Percentile Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

75th percentile of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated 

particle pathlines that define the zone of contribution to the supply well, in years

PH_GT8_90TH (90th Percentile Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

90th percentile of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated 

particle pathlines that define the zone of contribution to the supply well, in years

PH_GT8_MEAN (Mean Traveltime Through pH>8 Zone, In Years) Real; Width, autoformat

Mean of the traveltimes through areas defined by study unit modelers as having pH greater than 8 along simulated particle 

pathlines that define the zone of contribution to the supply well, in years
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–25

TANC Database—CAREASRCE_RGNL Table Data Dictionary

[The CAreaSrce_Rgnl table stores information on potential contaminant sources within supply-well contributing 

areas from TANC regional-scale investigations. All fields describe the steady state ‘area contributing recharge’ for 

discharging supply wells that were computed by use of regional ground-water flow models and pumping data stored in 

the Pumping_Rgnl table]

STUDY_UNIT (USGS NAWQA Study Unit Code) Character; Width 4; MANDATORY

STUDY_UNIT is only served to the end user from the TANC Sites table

SITE_ID (Station ID) Character; Width 24; MANDATORY

Site ID. Entry must be identical to the Sites table entry. SITE_ID is only served to the end user from the TANC Sites table

AREAL_RECHARGE (Percentage of Well Inflow from Areal Recharge) Real; Width, autoformat

Percentage of simulated inflow to the supply well from simulated areal recharge 

SW_LEAKAGE (Percentage of Well Inflow from Surface Water Leakage) Real; Width, autoformat

Percentage of simulated inflow to the supply well from simulated surface-water features 

MF_RECHARGE (Percentage of Well Inflow from Mountain Front Recharge) Real; Width, autoformat

Percentage of simulated inflow to the supply well from simulated mountain-front recharge 

REG_INFLOW (Percentage of Well Inflow from Regional Inflow) Real; Width, autoformat

Percentage of simulated inflow to the supply well from lateral boundaries of the simulated aquifer 

URBAN (Percentage of Well Inflow from Urban Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from urban areas based on the enhanced National Land Cover Data (NLCDE), 

which is the National Land Cover Data (NLCD) for the period 1990-1995 enhanced with historical land use and land cover 

(GIRAS) data for the period 1970-1985 where problems with attribute miscoding and data coverage at quadrangle boundaries 

existed in the original NLCD http://pubs.usgs.gov/ds/2006/240/#proc, accessed August 20, 2005

AGRICULTURE (Percentage of Well Inflow from Agricultural Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were agricultural in the early 1990’s based on the enhanced 

National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]

FOREST (Percentage of Well Inflow from Forested Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were forested in the early 1990’s based on the enhanced 

National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]

RANGELAND (Percentage of Well Inflow from Rangeland/Shrubland Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were rangeland/shrubland in the early 1990’s based on the 

enhanced National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]

BARREN (Percentage of Well Inflow from Barren Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were barren in the early 1990’s based on the enhanced 

National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]

WETLAND (Percentage of Well Inflow from Wetland Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were wetlands in the early 1990’s based on the enhanced 

National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]

WATER (Percentage of Well Inflow from Water Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were water in the early 1990’s based on the enhanced 

National Land Cover Data (NLCDE) [see URBAN for a more complete data reference]
A–26 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

URB_RES (Percentage of Well Inflow from Urban Residential Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were urban residential in the early 1990’s based on the 

enhanced National Land Cover Data (NLCDE). This is a subdivision of the URBAN field [see URBAN for a more complete data 

reference]

URB_COMIND (Percentage of Well Inflow from Urban Commercial/Industrial Areas) Real; Width, autoformat

Percentage of simulated inflow to the supply well from areas that were urban commercial/industrial in the early 1990’s based 

on the enhanced National Land Cover Data (NLCDE). This is a subdivision of the URBAN field [see URBAN for a more complete 

data reference]

PERSONS2000 (People in Contributing Area from 2000 Census) Real; Width, autoformat

Estimated number of people in the contributing area from the 2000 census data based on the percentage of the census block 

within the simulated area contributing recharge. Census data obtained by the USGS NAWQA Program from http://www.esri.

com/data/download/census2000_tigerline/index.html, accessed August 20, 2005

A_PERSONS2000 (People in Contributing Area from 2000 Census Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of people in the contributing area from the 2000 census data based on the percentage of urban area within 

the census block in the simulated area contributing recharge. Census data obtained by the USGS NAWQA Program from http://

www.esri.com/data/download/census2000_tigerline/index.html, accessed August 20, 2005; urban land use data from the NLCDE 

http://landcover.usgs.gov/ , accessed August 20, 2005

HOUSES2000 (Houses in Contributing Area from 2000 Census) Real; Width, autoformat

Estimated number of houses in the contributing area from the 2000 census data based on the percentage of the census block 

within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_HOUSES2000 (Houses in Contributing Area from 2000 Census Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses in the contributing area from the 2000 census data based on the percentage of urban area within 

the census block in the simulated area contributing recharge [see A_PERSONS2000 for data reference]

PERSONS1990 (People in Contributing Area from 1990 Census) Real; Width, autoformat

Estimated number of people in the contributing area from the 1990 census data based on the percentage of the census block 

within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_PERSONS1990 (People in Contributing Area from 1990 Census Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of people in the contributing area from the 1990 census data based on the percentage of urban area within 

the census block in the simulated area contributing recharge [see A_PERSONS2000 for data reference]

HOUSES1990 (Houses in Contributing Area from 1990 Census) Real; Width, autoformat

Estimated number of houses in the contributing area from the 1990 census data based on the percentage of the census block 

within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_HOUSES1990 (Houses in Contributing Area from 1990 Census Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses in the contributing area from the 1990 census data based on the percentage of urban area within 

the census block in the simulated area contributing recharge [see A_PERSONS2000 for data reference]

PRVWAT1990 (Houses Served By Private Well in Contributing Area from 1990 Census) Real; Width, autoformat

Estimated number of houses served by a private well in the contributing area from the 1990 census data based on the 

percentage of the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_PRVWAT1990 (Houses Served By Private Well in Contributing Area from 1990 Census Adjusted by Urban Area) Real; Width, 

autoformat

Estimated number of houses served by a private well in the contributing area from the 1990 census data based on the 

percentage of urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data 

reference]
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–27

PRVSEW1990 (Houses Served By Private Sewer in Contributing Area from 1990 Census) Real; Width, autoformat

Estimated number of houses served by a private sewer in the contributing area from the 1990 census data based on the 

percentage of the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_PRVSEW1990 (Houses Served By Private Sewer in Contributing Area from 1990 Census Adjusted by Urban Area) Real; 

Width, autoformat

Estimated number of houses served by a private sewer in the contributing area from the 1990 census data based on the 

percentage of urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data 

reference]

BLT_B70 (Houses Built Before 1970) Real; Width, autoformat

Estimated number of houses built before 1970 in the contributing area from the 1990 census data based on the percentage of 

the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_ BLT_B70 (Houses Built Before 1970 Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses built before 1970 in the contributing area from the 1990 census data based on the percentage of 

urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data reference]

BLT_7079 (Houses Built Between 1970 and 1979) Real; Width, autoformat

Estimated number of houses built between 1970 and 1979 in the contributing area from the 1990 census data based on the 

percentage of the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_ BLT_7079 (Houses Built Between 1970 and 1979 Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses built between 1970 and 1979 in the contributing area from the 1990 census data based on the 

percentage of urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data 

reference]

BLT_8084 (Houses Built Between 1980 and 1984) Real; Width, autoformat

Estimated number of houses built between 1980 and 1984 in the contributing area from the 1990 census data based on the 

percentage of the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_ BLT_8084 (Houses Built Between 1980 and 1984 Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses built between 1980 and 1984 in the contributing area from the 1990 census data based on the 

percentage of urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data 

reference]

BLT_8589 (Houses Built Between 1985 and 1989) Real; Width, autoformat

Estimated number of houses built between 1985 and 1989 in the contributing area from the 1990 census data based on the 

percentage of the census block within the simulated area contributing recharge [see PERSONS2000 for data reference]

A_BLT_8589 (Houses Built Between 1985 and 1989 Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses built between 1985 and 1989 in the contributing area from the 1990 census data based on the 

percentage of urban area within the census block in the simulated area contributing recharge [see A_PERSONS2000 for data 

reference]

BLT_9099 (Houses Built Between 1990 and 1999) Real; Width, autoformat

Estimated number of houses built between 1990 and 1999 in the contributing area based on the percentage of the census block 

within the simulated area contributing recharge; difference between the 2000 and 1990 censuses [see PERSONS2000 for data 

reference]. Changes in census block boundaries between 1990 and 2000 may affect results [for example, negative values could 

result from changes in census block boundaries, or they could indicate that houses were vacated or destroyed]
A–28 Hydrogeologic Settings and Ground-Water Flow Simulations for Regional TANC Studies Begun in 2001

A_BLT_9099 (Houses Built Between 1990 and 1999 Adjusted by Urban Areas) Real; Width, autoformat

Estimated number of houses built between 1990 and 1999 in the contributing area based on the percentage of urban area 

within the census block in the simulated area contributing recharge; difference between the 2000 and 1990 censuses [see A_

PERSONS2000 for data reference]. Changes in census block boundaries between 1990 and 2000 may affect results [for example, 

negative values could result from changes in census block boundaries, or they could indicate that houses were vacated or 

destroyed]

ROADLENGTH (Length of Roads) Real; Width, autoformat

Total length of roads in the area contributing recharge, in feet. Data obtained by the USGS NAWQA Program from http://www.

esri.com/data/download/census2000_tigerline/index.html, accessed August 20, 2005

ROADLENGTH_METERS (Length of Roads, In Meters) Real; Width, autoformat

This is a calculated field (ROADLENGTH multiplied by 0.3048)

TANKS_ALL (Underground Storage Tanks) Real; Width, autoformat

Number of underground storage tanks (gas stations, dry cleaners, unknown; leaking and not known to be leaking) in the area 

contributing recharge. Underground storage tank data are from Vista Information Solutions, Inc., San Diego, CA, and were 

retrieved by the USGS NAWQA Program by using the proprietary Starview 2.5.1 software and the June 1998 database. For 

tanks that did not have good location data, a probability that the tank would be in the contributing area was computed and then 

added to the number of tanks in the contributing area with more certain locations. Probabilities were computed by buffering 

the tank location in question with the radius of uncertainty provided in the dataset, overlaying the buffer on the simulated area 

contributing recharge, and dividing the area represented by the overlap of the buffer and contributing area by the total area of 

the buffer

TANKS_LEAKING_GAS (Leaking Underground Storage Tanks at Gas Stations) Real; Width, autoformat

Number of leaking underground storage tanks at gas stations in the area contributing recharge. Underground storage tank data 

are from Vista Information Solutions, Inc. For tanks that did not have good location data, a probability that the tank would be in 

the contributing area was computed and then added to the number of tanks in the contributing area with more certain locations 

[see TANKS_ALL for a more complete description and data reference]

TANKS_LEAKING_DRYCLEANER (Leaking Underground Storage Tanks at Dry Cleaners) Real; Width, autoformat

Number of leaking underground storage tanks at dry cleaners in the area contributing recharge. Underground storage tank data 

are from Vista Information Solutions, Inc. For tanks that did not have good location data, a probability that the tank would be in 

the contributing area was computed and then added to the number of tanks in the contributing area with more certain locations 

[see TANKS_ALL for a more complete description and data reference]

TANKS_LEAKING_UNKNOWN (Leaking Underground Storage Tanks at Unknown Facilities) Real; Width, autoformat

Number of leaking underground storage tanks in the area contributing recharge at facilities that are not known to be gas 

stations or dry cleaners. Underground storage tank data are from Vista Information Solutions, Inc. For tanks that did not have 

good location data, a probability that the tank would be in the contributing area was computed and then added to the number of 

tanks in the contributing area with more certain locations [see TANKS_ALL for a more complete description and data reference]

TANKS_UNDERGROUND_GAS (Underground Storage Tanks at Gas Stations not Known to be Leaking) Real; Width, autoformat

Number of underground storage tanks at gas stations in the area contributing recharge that are not known to be leaking. 

Underground storage tank data are from Vista Information Solutions, Inc. For tanks that did not have good location data, 

a probability that the tank would be in the contributing area was computed and then added to the number of tanks in the 

contributing area with more certain locations [see TANKS_ALL for a more complete description and data reference]

TANKS_UNDERGROUND_DRYCLEANER (Underground Storage Tanks at Dry Cleaners not Known to be Leaking) Real; 

Width, autoformat

Number of underground storage tanks at dry cleaners in the area contributing recharge that are not known to be leaking. 

Underground storage tank data are from Vista Information Solutions, Inc. For tanks that did not have good location data, 

a probability that the tank would be in the contributing area was computed and then added to the number of tanks in the 

contributing area with more certain locations [see TANKS_ALL for a more complete description and data reference]
Appendix 1. Database Dictionary for the Study of the Transport of Anthropogenic and Natural Contaminants A–29

TANKS_UNDERGROUND_UNKNOWN (Underground Storage Tanks at Unknown Facilities not Known to be Leaking) Real; 

Width, autoformat

Number of underground storage tanks in the area contributing recharge that are not known to be leaking at facilities that are 

not known to be gas stations or dry cleaners. Underground storage tank data are from Vista Information Solutions, Inc. For 

tanks that did not have good location data, a probability that the tank would be in the contributing area was computed and 

then added to the number of tanks in the contributing area with more certain locations [see TANKS_ALL for a more complete 

description and data reference]

FERTILIZER (Nitrogen in Fertilizer Applied) Real; Width, autoformat

Estimated amount of nitrogen in fertilizer applied to the area contributing recharge, in kilograms. Average based on 1990 

through 1998 annual State- and county-level information on the tonnage of fertilizer product sales obtained by the USGS 

NAWQA Program from the Association of American Plant Food Control Officials (AAPFCO), University of Kentucky

MANURE (Nitrogen in Manure Applied) Real; Width, autoformat

Estimated amount of nitrogen in manure applied to the area contributing recharge, in kilograms. Average based on 1992 and 

1997 animal populations http://water.usgs.gov/lookup/getspatial?manure, accessed May 15, 2007


Paschke, Suzzane S., ed.—Hydrogeologic Settings and Ground-Water Flow Simulations for Regional Studies of the Transport of Anthropogenic

 and Natural Contaminants to Public-Supply Wells—Studies Begun in 2001—Professional Paper 1737–A