U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2013–5069

Prepared in cooperation with the Rosebud Sioux Tribe

Conceptual and Numerical Models of Groundwater 

Flow in the Ogallala Aquifer in Gregory and Tripp 

Counties, South Dakota, Water Years 1985–2009
Cover. Left photograph: Sand Creek near Olsonville, South Dakota (streamgage 06464120). Sand 

Creek is a tributary to the Keya Paha River and is fed by seeps or springs that originate from the 

Ogallala aquifer. Photograph taken on October 12, 2005, by Brad Kniss, U.S. Geological Survey.

Right photograph: Keya Paha River at Wewela, South Dakota (streamgage 06464500). Groundwater 

discharge from the Ogallala aquifer provides base flow to the Keya Paha River. Photograph taken on 

July 17, 2006, by Brad Kniss, U.S. Geological Survey.
Conceptual and Numerical Models of 

Groundwater Flow in the Ogallala Aquifer 

in Gregory and Tripp Counties, South 

Dakota, Water Years 1985–2009

By Kyle W. Davis and Larry D. Putnam

Prepared in cooperation with the Rosebud Sioux Tribe

Scientific Investigations Report 2013–5069

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation:

Davis, K.W., and Putnam, L.D., 2013, Conceptual and numerical models of groundwater flow in the Ogallala aquifer in 

Gregory and Tripp Counties, South Dakota, water years 1985–2009: U.S. Geological Survey Scientific Investigations 

Report 2013–5069, 82 p., http://pubs.usgs.gov/sir/2013/5069/.
iii

Acknowledgments

The authors would like to recognize important contributions made by the Rosebud Sioux Tribe to 

the development of the groundwater-flow model described in this report. Development of a calibrated numerical model resulted from the tribe’s long-term commitment to obtaining hydrologic 

information. The tribe was actively involved in the design of the study, the conceptualization of 

the groundwater-flow system, the technical evaluation of model performance, and the review 

of this report. The South Dakota Department of Environment and Natural Resources Geological 

Survey lithologic database was the primary source of data for interpretation of the hydrogeologic framework. The Water Rights Program of the South Dakota Department of Environment 

and Natural Resources provided permitting and water-use data and long-term water-level data 

for their groundwater monitoring network in the study area.
iv

Contents

Acknowledgments........................................................................................................................................iii

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

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

Purpose and Scope ..............................................................................................................................2

Previous Investigations........................................................................................................................2

Description of Study Area ............................................................................................................................5

Physiography, Land Use, and Climate ...............................................................................................5

Drainage Features and Streamflow...................................................................................................5

Geology...................................................................................................................................................5

Hydrogeology.........................................................................................................................................7

Conceptual Model........................................................................................................................................10

Hydrogeologic Framework................................................................................................................10

Groundwater Flow ..............................................................................................................................10

Hydraulic Properties...........................................................................................................................14

Water Budget Components...............................................................................................................16

Recharge.....................................................................................................................................18

Discharge....................................................................................................................................21

Evapotranspiration ...........................................................................................................21

Discharge to Streams ......................................................................................................25

Well Withdrawals .............................................................................................................27

Numerical Model .........................................................................................................................................29

Simulation Methods............................................................................................................................29

Definitions ............................................................................................................................................30

Assumptions ........................................................................................................................................30

Model Design.......................................................................................................................................32

Grid and Boundary Conditions.................................................................................................32

Hydrogeologic Representation................................................................................................33

Representation of Hydraulic Properties .......................................................................33

Recharge............................................................................................................................33

Discharge...........................................................................................................................33

Model Calibration................................................................................................................................35

Calibration Targets.....................................................................................................................37

Calibrated Parameter Values...................................................................................................38

Sensitivity Analysis....................................................................................................................39

Simulation of Groundwater Flow.............................................................................................41

Initialization Period...........................................................................................................41

Transient Simulation.........................................................................................................41

Simulation of Future Scenarios ........................................................................................................44

Comparison of Simulated Groundwater Budgets.................................................................48

Model Limitations................................................................................................................................55

Summary........................................................................................................................................................60

References Cited..........................................................................................................................................62
v

Figures

1. Map showing study area, extent of the northern High Plains aquifer, and location of

main physiographic divisions .....................................................................................................3

2. Map showing location and altitude of the study area............................................................4

3. Map showing drainage basins and generalized land cover in the study area ..................6

4. Map showing generalized surface geology in the study area..............................................8

5. Map showing estimated mean saturated thickness of the Ogallala aquifer in the

study area ....................................................................................................................................11

6. Map showing the location of South Dakota Department of Environment and Natural

Resources observation wells, test holes, and individual wells used to estimate the

mean potentiometric surface of the Ogallala aquifer in the study area............................12

7. Map showing estimated mean potentiometric surface of the Ogallala aquifer in the

study area, water years 1985–2009..........................................................................................13

8. Graph showing generalized relationship between hydraulic head, hydrogeologic

units, and topographic features for cross-section A–A’......................................................16

9. Map showing the altitude of the base of the Ogallala aquifer in the study area.............17

10. Map showing calculated specific capacity of selected wells completed in the

Ogallala aquifer and estimated hydraulic conductivity of the aquifer in the study 

area ...............................................................................................................................................19

11. Map showing the locations of climate stations and streamgages in and around the

study area ....................................................................................................................................20

12. Map showing the spatial distribution of mean annual recharge to the Ogallala

aquifer in the study area for water years 1985–2009 estimated with the

soil-water-balance method.......................................................................................................22

13. Map showing production wells completed in the Ogallala aquifer in the study 

area ...............................................................................................................................................28

14. Map showing the numerical model grid design for the study area and boundary

conditions used to simulate groundwater flow in the Ogallala aquifer.............................31

15. Map showing pilot-point zones and locations used for representing horizontal

hydraulic conductivity in the Ogallala aquifer in the study area........................................34

16. Map showing model representation of discharge including river cells and drain

cells for the Ogallala aquifer in the study area......................................................................36

17. Map showing calibrated horizontal hydraulic conductivity of the Ogallala aquifer 

in the study area .........................................................................................................................40

18. Bar graph showing relative composite parameter sensitivities, as defined by 

Doherty (2010), for the numerical model.................................................................................41

19. Map showing simulated long-term mean potentiometric surface in the Ogallala 

aquifer in the study area............................................................................................................42

20. Map showing difference between the observed and simulated potentiometric

surfaces in the study area.........................................................................................................43

Supplemental Information..........................................................................................................................67

Supplement 1. Data Used to Estimate Mean Potentiometric Surface................................................68

Supplement 2. Estimates of Transmissivity and Hydraulic Conductivity from Specific 

Capacity Data..................................................................................................................................76

Supplement 3. Analysis of Recharge and Evapotranspiration With a Soil-Water-Balance

Method.............................................................................................................................................79
vi

21. Map showing the mean residuals between observed and simulated hydraulic

heads for State observation wells completed in the Ogallala aquifer in the study

area, water years 1985–2009 ....................................................................................................47

22. Histogram of residuals of observed and simulated hydraulic head in State

observation wells for the Ogallala aquifer in the study area, water years 

1985–2009 .....................................................................................................................................48

23. Hydrographs showing observed and simulated hydraulic heads for State

observation wells completed in the Ogallala aquifer in the study area............................49

24. Graph showing linear regression of observed and simulated hydraulic heads for

State observation wells in the Ogallala aquifer in the study area......................................54

25. Graph showing estimated and simulated base flow from groundwater discharge

from the Ogallala aquifer in the study area for the Keya Paha River.................................54

26. Hydrographs showing the difference in hydraulic heads between the results of 

the calibrated model (non-drought simulation) and the assumed potential drought

scenario for the 25-year simulation period for selected State observation wells

completed in the Ogallala aquifer in the study area.............................................................56

27. Map showing the simulated difference in hydraulic head between the calibrated

model (non-drought simulation) and the simulation representing a potential 

drought scenario for the Ogallala aquifer in the study area ...............................................57

28. Map showing the simulated difference in hydraulic head between the calibrated

model and the simulation representing a potential increased pumping scenario for

the Ogallala aquifer in the study area .....................................................................................58

S3–1. Map of soil type as defined for recharge calculations in soil-water-balance method

in the study area .........................................................................................................................81
vii

Tables

1. Generalized stratigraphic column showing geologic units west of the Missouri

River in study area........................................................................................................................9

2. Selected data for long-term State observation wells completed in the Ogallala

aquifer in Gregory and Tripp Counties ....................................................................................15

3. Previously published hydraulic properties within or near the study area........................18

4. Recharge to the Ogallala aquifer in the study area estimated by using the

soil-water-balance method, water years 1985–2009............................................................23

5. Measured pan evaporation at Pickstown, South Dakota, and maximum potential

evapotranspiration estimated by using the soil-water-balance method, water years

1985–2009 .....................................................................................................................................24

6. Discharge to the Keya Paha River as base flow estimated using hydrograph

separation, water years 1985–2009 .........................................................................................26

7. Estimated withdrawals from the Ogallala aquifer for irrigation use in the study 

area, water years 1985–2009 ....................................................................................................29

8. Estimated per capita use and withdrawals from the Ogallala aquifer for public

supply in the study area.............................................................................................................30

9. Estimated discharge components from the Ogallala aquifer as base flow to the

Keya Paha River between streamgages at Keyapaha and Wewela, South Dakota,

for the for the initialization stress period................................................................................38

10. Calibrated horizontal hydraulic conductivity for pilot points used in numerical model .38

11. Calibrated parameters for the numerical model ...................................................................39

12. Water budget for the numerical model simulating long-term mean conditions

compared with flow estimates from the conceptual model................................................44

13. Comparison of observed and simulated hydraulic heads for State observation wells

for the transient simulation .......................................................................................................45

14. Comparison of estimated to simulated base flow for the Keya Paha River for the

transient simulation....................................................................................................................55

15. Simulated groundwater budget for the initialization period, water years 1985–2009,

potential drought scenario, and potential increased pumping scenario for the

Ogallala aquifer in the study area............................................................................................59

S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala

aquifer for water years 1985–2009...........................................................................................68

S2–1. Specific capacity data, transmissivity, and hydraulic conductivity for selected 

wells completed in the Ogallala aquifer in the study area ..................................................76

S3–1. Infiltration rates assigned by soil type....................................................................................82

S3–2. Interception storage values and depth of root zone assigned by land-cover 

category .......................................................................................................................................82
viii

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

square mile (mi2) 259 hectare (ha)

square mile (mi2) 2.59 square kilometer (km2) 

square feet (ft2) 0.0929 square meter (m2)

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3) 

acre-foot (acre-ft) 1,233 cubic meter (m3)

Flow rate

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

gallon per minute (gal/min) 0.06309 liter per second (L/s)

million gallons per day (Mgal/d) 0.04381 cubic meter per second (m3/s)

inch per year (in/yr) 25.4 millimeter per year (mm/yr)

Specific capacity

gallon per minute per foot [(gal/

min)/ft]

0.207 liter per second per meter 

[L/s/m]

Hydraulic conductivity

foot per day (ft/d) 0.3048 meter per day (m/d)

Transmissivity*

foot squared per day (ft2/d) 0.0929 meter squared per day (m2/d) 

Conductance

feet squared per day (ft2/d) 0.0929 meter squared per day (m2/d)

Gradient

foot per mile (ft/mi) 0.1894 meters per kilometer (m/km)

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

°C=(°F–32)/1.8

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 

(NGVD 29).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

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

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

foot of aquifer thickness [(ft3/d)/ft2] ft. In this report, the mathematically reduced form, foot 

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

A water year (WY) is the 12-month period from October 1 through September 30 and is 

designated by the calendar year in which it ends.

Abbreviations

± plus or minus

DEM digital elevation model

GIS geographic information system

NED National Elevation Dataset (U.S. Geological Survey)

NOAA National Oceanic and Atmospheric Administration

PEST Parameter Estimation

RASA Regional Aquifer-System Analysis (U.S. Geological Survey)

SDDENR South Dakota Department of Environment and Natural Resources

SWB Soil-Water Balance (software program) or soil-water balance 

SWUDS Site-specific Water-Use Data System (U.S. Geological Survey)

UPW Upstream Weighting (MODFLOW–NWT solver package)

USGS U.S. Geological Survey

WY water year

Conceptual and Numerical Models of Groundwater Flow 

in the Ogallala Aquifer in Gregory and Tripp Counties, 

South Dakota, Water Years 1985–2009

By Kyle W. Davis and Larry D. Putnam

Abstract

The Ogallala aquifer is an important water resource for 

the Rosebud Sioux Tribe in Gregory and Tripp Counties in 

south-central South Dakota and is used for irrigation, public 

supply, domestic, and stock water supplies. To better understand groundwater flow in the Ogallala aquifer, conceptual and 

numerical models of groundwater flow were developed for the 

aquifer. A conceptual model of the Ogallala aquifer was used 

to analyze groundwater flow and develop a numerical model 

to simulate groundwater flow in the aquifer. The MODFLOW–

NWT model was used to simulate transient groundwater conditions for water years 1985–2009. The model was calibrated 

using statistical parameter estimation techniques. Potential 

future scenarios were simulated using the input parameters 

from the calibrated model for simulations of potential future 

drought and future increased pumping.

Transient simulations were completed with the numerical 

model. A 200-year transient initialization period was used to 

establish starting conditions for the subsequent 25-year simulation of water years 1985–2009. The 25-year simulation was 

discretized into three seasonal stress periods per year and used 

to simulate transient conditions.

A single-layer model was used to simulate flow and mass 

balance in the Ogallala aquifer with a grid of 133 rows and 

282 columns and a uniform spacing of 500 meters (1,640 feet). 

Regional inflow and outflow were simulated along the western 

and southern boundaries using specified-head cells. All other 

boundaries were simulated using no-flow cells. Recharge to 

the aquifer occurs through precipitation on the outcrop area.

Model calibration was accomplished using the Parameter 

Estimation (PEST) program that adjusted individual model 

input parameters and assessed the difference between estimated and model-simulated values of hydraulic head and base 

flow. This program was designed to estimate parameter values 

that are statistically the most likely set of values to result 

in the smallest differences between simulated and observed 

values, within a given set of constraints. The potentiometric 

surface of the aquifer calculated during the 200-year initialization period established initial conditions for the transient 

simulation. Water levels for 38 observation wells were used 

to calibrate the 25-year simulation. Simulated hydraulic heads 

for the transient simulation were within plus or minus 20 feet 

of observed values for 95 percent of observation wells, and the 

mean absolute difference was 5.1 feet. Calibrated hydraulic 

conductivity ranged from 0.9 to 227 feet per day.

The annual recharge rates for the transient simulation 

(water years 1985–2009) ranged from 0.60 to 6.96 inches, 

with a mean of 3.68 inches for the Ogallala aquifer. This 

represents a mean recharge rate of 280.5 ft3

/s for the model 

area. Discharge from the aquifer occurs through evapotranspiration, discharge to streams through river leakage and 

flow from springs and seeps, and well withdrawals. Water is 

withdrawn from wells for irrigation, public supply, domestic, 

and stock uses. Simulated mean discharge rates for water 

years 1985–2009 were about 185 cubic feet per second (ft3

/s) 

for evapotranspiration, 66.7 ft3

/s for discharge to streams, and 

5.48 ft3/s for well withdrawals. Simulated annual evapotranspiration rates ranged from about 128 to 254 ft3

/s, and outflow 

to streams ranged from 52.2 to 79.9 ft3

/s.

A sensitivity analysis was used to examine the response 

of the calibrated model to changes in model parameters for 

horizontal hydraulic conductivity, recharge, evapotranspiration, and spring and riverbed conductance. The model was 

most sensitive to recharge and maximum potential evapotranspiration and least sensitive to riverbed and spring 

conductances.

Two potential future scenarios were simulated: a potential drought scenario and a potential increased pumping 

scenario. To simulate a potential drought scenario, a synthetic 

drought record was created, the mean of which was equal to 

60 percent of the mean estimated recharge rate for the 25-year 

simulation period. Compared with the results of the calibrated 

model (non-drought simulation), the simulation representing 

a potential drought scenario resulted in water-level decreases 

of as much as 30 feet for the Ogallala aquifer. To simulate the 

effects of potential future increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 25-year simulation period. Compared with the 

results of the calibrated model, the simulation representing an 
2 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

increased pumping scenario resulted in water-level decreases 

of as much as 26 feet for the Ogallala aquifer.

Groundwater budgets for the potential future scenario 

simulations were compared with the transient simulation representing water years 1985–2009. The simulation representing 

a potential drought scenario resulted in lower aquifer recharge 

from precipitation and decreased discharge from streams, 

springs, seeps, and evapotranspiration. The simulation representing a potential increased pumping scenario was similar to 

results from the transient simulation, with a slight increase in 

well withdrawals and a slight decrease in discharge from river 

leakage and evapotranspiration.

This numerical model is suitable as a tool that could 

be used to better understand the flow system of the Ogallala 

aquifer, to approximate hydraulic heads in the aquifer, and to 

estimate discharge to rivers, springs, and seeps in the study 

area. The model also is useful to help assess the response of 

the aquifer to additional stresses, including potential drought 

conditions and increased well withdrawals.

Introduction

The High Plains aquifer, which includes the Ogallala 

and Arikaree aquifers, underlies almost 112 million acres 

in the central United States (Stanton and others, 2011). The 

High Plains aquifer underlies parts of eight States and extends 

from southern South Dakota to Texas (fig. 1). The aquifer has 

been used extensively for irrigation, public supply, domestic, 

and stock water use and is an important water supply for the 

United States. About 2 million people rely on the High Plains 

aquifer for drinking water with total public supply withdrawals 

of 418 million gallons per day (Mgal/d; Dennehy, 2000). The 

High Plains region supplies approximately one-fourth of the 

Nation’s agricultural production (McMahon and others, 2007).

The High Plains aquifer underlies about 4,750 square 

miles (mi2) in south-central South Dakota (Gutentag and 

others, 1984), including parts of Gregory and Tripp Counties 

(fig. 2). The Ogallala aquifer overlies the Arikaree aquifer 

throughout much of this area and is used extensively for 

irrigation, public supply, domestic, and stock water supplies. 

Although the Arikaree aquifer is considered part of the High 

Plains aquifer, it is used much less extensively than the Ogallala aquifer within Gregory and Tripp Counties.

The High Plains aquifer generally is less developed 

in South Dakota compared with other parts of the Nation 

underlain by this aquifer, and thus, water levels in the aquifer 

in South Dakota generally changed less than 5 feet (ft) from 

1980 to 1999 (McGuire, 2001). Despite minimal water-level 

changes in the High Plains aquifer in South Dakota, extensive 

withdrawals of groundwater for irrigation have caused waterlevel decreases in many parts of the aquifer and increased concerns about the long-term sustainability of the aquifer (Stanton 

and others, 2011). Since the 1950s, water-level decreases of as 

much as 100 ft have been measured in parts of Kansas, New 

Mexico, Oklahoma, and Texas (Dennehy, 2000). Discharge 

from the aquifer through springs and seeps provides base flow 

for several important streams in the area (Carter, 1998; Filipovic, 2004). Therefore, continued or increased withdrawals 

from the aquifer or prolonged drought may have the potential to affect water levels within the aquifer and discharge to 

important streams in the area.

The Rosebud Sioux Tribe has identified a need for waterresource tools to analyze the effects of potential increased 

groundwater demand or prolonged drought and to evaluate 

potential future management issues associated with the Ogallala aquifer, such as planning for source-water protection, 

describing potential effects of contamination, and estimating 

sustainable aquifer withdrawals. A primary tool conceived 

by the tribe was a numerical groundwater-flow model for the 

Ogallala aquifer in Gregory and Tripp Counties. Therefore, the 

U.S. Geological Survey (USGS) has worked in cooperation 

with the tribe to develop the conceptual and numerical models 

described in the report.

The numerical model is a water-resource tool used to 

analyze the groundwater system and can be used to assess 

water-management issues associated with the Ogallala aquifer 

in Gregory and Tripp Counties. The model could be used by 

water managers to evaluate the effects of various hydrologic 

scenarios, including increased well withdrawals or prolonged 

drought within the study area.

Purpose and Scope

This report describes and documents conceptual and 

numerical models of groundwater flow in the Ogallala aquifer, 

developed in cooperation with the Rosebud Sioux Tribe. The 

conceptual and numerical models were developed to describe 

and simulate groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties in south-central South Dakota. The 

conceptual model describes the geology, hydrogeology, and 

groundwater flow for water years (WYs) 1985–2009 (October 

1, 1984, through September 30, 2009). A transient numerical 

model was executed for a 25-year period of measured data 

consisting of WYs 1985–2009. This report also documents 

numerical simulations of two potential future scenarios. The 

first scenario represented a potential 25-year drought, and the 

second scenario represented a potential increase in groundwater withdrawals from existing production wells.

Previous Investigations

Newport (1959) described the groundwater resources for 

the lower Niobrara River and Ponca Creek drainage basins, 

which includes parts of the Ogallala aquifer in Gregory and 

Tripp Counties, S. Dak. Rahn and Paul (1975) conducted an 

aquifer test in southeastern Todd County, S. Dak., to determine 

hydraulic properties of the Ogallala aquifer. Kolm and Case 

(1983) developed a two-dimensional numerical groundwater 

model for the High Plains aquifer, which includes the Ogallala 
Introduction 3

Missouri River

Loup

River

Lodgepole Creek

Big Blue River

South Platte River

Republican River

Arikaree River

South Loup River

Solomon River

Kansas River

Little Blue River

Elk Horn River

Niobrara River

Middle Loup River

Keya Paha River

White River

Cedar River

Sappa Creek

Smoky Hill River

Platte River

North Fork Solomon River

Frenchman Creek

South Fork Solomon River

Beaver Creek

Ponca Creek

Study area

IOWA MINNESOTA

SOUTH 

DAKOTA

WYOMING

NEBRASKA

COLORADO

KANSAS

Cheyenne

Fort Collins

Scottsbluff

Denver

Colorado

Springs

North

Platte Grand

Island

Hays

Rapid City

Sioux Falls

Sioux City

CENTRAL

LOWLAND

GREAT

PLAINS

SOUTHERN

ROCKY

MOUNTAINS

WYOMING

BASIN

106° 104° 102° 100° 98°

44°

42°

40°

North PlatteRiver

North Loup River

0 30 60 90 120 MILES

0 30 60 90 120 KILOMETERS

EXPLANATION

Northern High Plains aquifer boundary

Physiographic division (modified from Fenneman, 1946)

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985

Universal Transverse Mercator projection, zone 14

Aquifer extent modified from Qi, 2010

Location map

High Plains aquifer

Area

shown

Central High Plains

Southern High Plains

Figure 1. Study area, extent of the northern High Plains aquifer, and location of main physiographic divisions.
4 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota FORT RANDALL DAM

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou

Hills LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

YTNUOC DDOT

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

EXPLANATION

Land-surface altitude, in feet above 

National Geodetic Vertical Datumof 1929

High : 3,505Low : 1,212

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

SOUTH DAKOTA

NEBRASKA

R. 25 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

Missouri

River

SO

UTH

D

A

K

OTA

NEBRASKA

Study area 

boundary

Location map

ETTELLE M

YTNUOC

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28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 2. Location and altitude of the study area.
Description of Study Area 5

and Arikaree aquifers, in southern South Dakota and northern 

Nebraska. Kremin-Smith (1984) analyzed aquifer test data 

for the Ogallala aquifer in south-central Todd County. Carter 

(1998) described the water resources for Mellette and Todd 

Counties (located to the west of Tripp County; fig. 2), where 

the High Plains aquifer is used extensively for irrigation, 

public supply, domestic, and stock water supplies. Long and 

others (2003) and Long and Putnam (2010) performed threedimensional groundwater-flow modeling for the Ogallala and 

Arikaree aquifers in Mellette and Todd Counties. The model 

developed by Long and Putnam (2010) was an extension of 

the model developed by Long and others (2003) to address the 

effects of potential increased pumping and extended drought. 

Filipovic (2004) published a generalized water table and 

saturated thickness map and developed cross-sections for the 

Ogallala aquifer in Gregory and Tripp Counties based on lithologic, water-level, and geochemical data collected during 2003 

and 2004. LaBelle (2011) estimated recharge to the Ogallala 

and Arikaree aquifers in Bennett, Jackson, and Shannon Counties in southwest-central South Dakota.

In 1978, the USGS initiated a study called the High 

Plains Regional Aquifer-System Analysis to evaluate the 

effects of groundwater development on the High Plains aquifer. The High Plains Regional Aquifer-System Analysis was 

completed as a part of the Regional Aquifer-System Analysis 

(RASA) Program, which was a response to a congressional 

mandate to quantitatively appraise the major groundwater systems of the United States (Weeks and others, 1988). Gutentag 

and others (1984) presented the geohydrology of the High 

Plains aquifer, including its depositional history in relation to 

bedrock, the quantity and quality of groundwater, and the history of groundwater development. Luckey and others (1986) 

described digital models used to simulate groundwater flow 

in the High Plains aquifer in the United States and subdivided 

the aquifer into the northern, central, and southern High Plains 

(fig. 1). Thelin and Heimes (1987) used satellite imagery to 

map irrigated land and estimated groundwater use on the basis 

of irrigated acreage. Luckey and others (1988) projected the 

effects of groundwater withdrawals on the High Plains aquifer 

for three potential scenarios. Weeks and others (1988) summarized the findings of the High Plains RASA study in detail.

Description of Study Area

The study area includes parts of Gregory and Tripp Counties and small parts of Mellette and Todd Counties in South 

Dakota as well as small parts of Boyd and Keya Paha Counties 

in Nebraska where the Ogallala aquifer is present. The study 

area is located within the Great Plains physiographic division 

(Fenneman, 1946) in the northern High Plains aquifer region 

(fig. 1; Luckey and others, 1988).

Physiography, Land Use, and Climate

Much of the study area has rolling topography and 

numerous deep valleys that drain to the southeast toward the 

Missouri River (figs. 2 and 3). The altitude of the study area 

ranges from more than 3,500 ft above the National Geodetic 

Vertical Datum of 1929 (NGVD 29) near the western edge of 

the study area to slightly less than 1,200 ft above NGVD 29 in 

the southeastern part of the study area.

Agriculture is the primary land use within the study area. 

Approximately 55 percent of the land within the study area 

is used for cultivated crops, which include corn, alfalfa, grain 

sorghum, oats, and wheat (Springer, 1979; Wiesner, 1984). 

Approximately 42 percent of the land is range land used for 

grazing where native hay also is harvested. Land cover within 

Gregory and Tripp Counties includes herbaceous grassland, 

cultivated crops, hay and pasture, wetlands, forest, and lowdensity urban development (fig. 3; Multi-Resolution Land 

Characteristics Consortium, 2009). Most of land cover in the 

study area is herbaceous grassland.

The climate is continental, characterized by wide daily 

and annual ranges in temperature (Filipovic, 2004). The spring 

weather usually is rainy, cool, and windy; summer usually has 

moderate precipitation, hot days, and cool nights; the autumn 

months generally are mild; and the winter is characterized 

by low temperatures accompanied by wind and snow (Newport, 1959). The mean annual precipitation (1961–1990) is 

about 24 inches (in.) in Winner, S. Dak. (National Oceanic 

and Atmospheric Administration station 399367; High Plains 

Regional Climate Center, 2011).

Drainage Features and Streamflow

The major rivers that drain the study area are the Keya 

Paha River, the White River, the Ponca Creek, and the Missouri River (fig. 3). Smaller streams include several tributaries to the White and Missouri Rivers. Groundwater discharge 

from the Ogallala aquifer provides base flow to the Keya Paha 

River, which generally receives more than one-half of its flow 

from groundwater discharge, especially during the winter 

months (Carter, 1998). Direct runoff is the largest component 

of streamflow for streams that do not receive discharge from 

the Ogallala aquifer (Long and Putnam, 2010). The Missouri 

River flows through the eastern part of the study area and 

is impounded by the Fort Randall Dam, which forms Lake 

Francis Case within the Fort Randall Reservoir drainage basin 

(fig. 3).

Geology

Buried rocks in the study area include those of Precambrian age, the Ordovician-age Red River and Winnipeg 

Formations, and Cretaceous-age Dakota Sandstone. The 

exposed geologic formations within the study area consist 

of Cretaceous-, Tertiary-, and Quaternary-age rocks and 
6 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W. T. 101 N. T. 100 N. T. 99 N. T. 98 N. T. 97 N. T. 96 N. T. 95 N. T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W. FORT RANDALL DAM

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EXPLANATION

Generalized land cover, from National Land Cover Database 2001

(Multi-Resolution Land Characteristics Consortium, 2009)

Herbaceuous grasslandCultivated cropsHay/pasture

WetlandsForestDeveloped, low intensityOpen water

Drainage basin boundary with basin name

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

SOUTH DAKOTA

NEBRASKA

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MISSOURI RIVER

LAKE FRANCIS 

CASE

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North Fork Whetstone Creek

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Ponca Creek

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Dog Ear Creek

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Figure 3. Drainage basins and generalized land cover in the study area.
Description of Study Area 7

sediments (fig. 4; table 1). These exposed geologic formations are divided into the Cretaceous-age Niobrara Formation (small outcrop area in the southeastern corner of study 

area) and Pierre Shale; the Tertiary-age White River Group, 

Arikaree Formation, and Ogallala Formation; and Quaternaryage unconsolidated deposits. Unconsolidated deposits include 

glacial sediments east of the Missouri River and windblown, 

terrace, and alluvial sediments to the west of the Missouri 

River (fig. 4). Unconsolidated glacial sediments do not directly 

overlie the Ogallala Formation in the study area and therefore, 

glacial sediments are not included in table 1.

The Cretaceous-age Pierre Shale is a marine shale that is 

predominantly dark-gray and is present throughout the study 

area (Filipovic, 2004). The Oligocene-age White River Group 

is present to the west of the Missouri River near the western 

boundary of the study area (fig. 4) and was deposited unconformably on top of the Pierre Shale. The White River Group 

sometimes is divided into two units where distinguishable—

the Chadron and Brule Formations (Filipovic, 2004). The 

Chadron Formation is the lower unit and is mainly composed 

of varicolored quartz sand and conglomerate interbedded with 

clay and silt deposited in channels. The overlying Brule Formation is a massive white, pink, light-green, and light-brown, 

bentonitic claystone and siltstone (Filipovic, 2004).

The Arikaree Formation is a moderately indurated, pinkcolored shale and siltstone. In the study area, the Arikaree Formation may be present only in the southwestern part (fig. 4), 

but the exact extent is not known because few wells penetrate 

this formation. The thickness of the Arikaree Formation varies 

with the undulating unconformity between it and the overlying 

Ogallala Formation (Rahn and Paul, 1975). The lower 50 to 

150 ft is characterized by silty and sandy beds that commonly 

are separated from the upper clayey part by 5 to 10 ft of thinbedded limestone (Long and Putnam, 2010).

The extent of the Ogallala Formation in the study area 

is indicated by the extent of the northern High Plains aquifer 

in figure 1; thus, it is not present to the east of the Missouri 

River. The Ogallala Formation directly overlies parts of the 

Arikaree Formation, the White River Group, and the Pierre 

Shale within the study area. Early South Dakota Geological 

Survey quadrangle maps (Stevenson and Buckmeier, 1958; 

Sevon and Petsch, 1960) divided the Ogallala Formation 

into two units—the underlying Valentine Formation and the 

overlying Ash Hollow Formation. More recently, Ellis and 

others (1971) and Harksen and McDonald (1969) have called 

the Ogallala Formation one unit because of the indistinct field 

identification of the two units (Rahn and Paul, 1975). The 

Ogallala Formation consists of an olive-colored, mediumgrained pure quartz sandstone that is poorly indurated (Rahn 

and Paul, 1975). The formation consists of interbedded layers 

of sandy gravel, sand, silt, and clay. Some lenses of volcanic 

ash also are present (Newport, 1959).

The Ogallala Formation was deposited unconformably 

on the uneven surface of the Pierre Shale, White River Group, 

or Arikaree Formation where present in the study area. The 

Ogallala Formation was deeply eroded by streams in the 

Quaternary period; therefore, it differs considerably in thickness from place to place (Newport, 1959). The thickness of the 

Ogallala Formation ranges from 0 to 200 ft in the study area 

and is controlled primarily by the morphology of the eroded 

pre-Ogallala surface (Filipovic, 2004). The altitude of the 

base of the Ogallala Formation in Gregory and Tripp Counties 

was estimated from lithologic logs and ranged from 1,621 to 

2,445 ft above NGVD 29. The basal dip of the Ogallala aquifer is about 10 feet per mile (ft/mi) to the southeast.

Sediments of Quaternary age consist of glacial, terrace, 

windblown, and alluvial deposits. The windblown deposits 

consist of sand that is sometimes calcareous and is derived 

from the Ogallala Formation. In some places, the contact 

between the windblown deposits and the Ogallala Formation is 

not easily identified. Alluvium is present in fluvial floodplains 

and terrace sediments along active streams and rivers (Filipovic, 2004). Glacial sediments were deposited to the east of the 

Missouri River.

Hydrogeology

The Dakota Sandstone, the Ogallala Formation, and 

deposits of sandy gravel of Quaternary age are the principal 

water-bearing rocks in the study area (Newport, 1959). The 

shallow aquifers in the study area are the alluvial, Ogallala, 

Arikaree, and White River aquifers. These shallow aquifers 

consist primarily of unconsolidated sand and gravel or poorly 

consolidated sandstones and siltstones (Long and Putnam, 

2010). Well logs indicate that the deep bedrock aquifers are 

the Pierre and Dakota aquifers (South Dakota Department of 

Environment and Natural Resources, 2011).

The Ogallala aquifer is composed of the saturated sandstones, gravel, sand, and silt of the Ogallala Formation. The 

upper unit of the Ogallala Formation has relatively low permeability, but small seeps occur near its base (Ellis and others, 

1971). The lower unit of the Ogallala Formation generally is 

water bearing; however, the permeability of that unit varies 

with lithology. Where the Ogallala Formation caps narrow 

ridges or is near deeply entrenched streams, discharge generally is greater than recharge, and the Ogallala aquifer will not 

yield large amounts of water to wells (Newport, 1959). Where 

the Ogallala Formation is thick and at least a few miles distant 

from deeply entrenched streams, it contains a large quantity 

of water (Newport, 1959). The base of the Ogallala aquifer is 

coincident with the base of the Ogallala Formation. Unconsolidated Quaternary-age windblown, terrace, and alluvial 

deposits overlying the Ogallala Formation to the west of the 

Missouri River are considered part of the Ogallala aquifer 

because these deposits are assumed to be in hydraulic connection with the Ogallala aquifer (Weeks and Gutentag, 1981).

The Ogallala aquifer is considered unconfined within the 

study area even though it is overlain by younger deposits in 

some areas. In the study area, the depth to water ranges from 

about 5 to 132 ft below the land surface, and the saturated 

thickness ranges from about 0 to 190 ft (Filipovic, 2004). The 
8 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota FORT RANDALL DAM 98°30' 99°00' 99°30' 100°00' 43°30' 43°20' 43°10' 43°00' EXPLANATION Quaternary-age unconsolidated deposits Alluvium Qa Qwd Windblown deposits Qt Terrace deposits Qg Glacial deposits Tertiary-age sedimentary deposits To Ogallala Formation Ta Arikaree Formation Tw White River Group Cretaceous-age sedimentary deposits

Kp Pierre ShaleKn Niobrara Formation

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14Geology modified from Martin and others, 2004; University of Nebraska-Lincoln, 2010

Bonesteel

Burke

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ETTELLE M

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0 5 10 15 20 MILES

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SOUTH DAKOTA

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R. 25 W. R. 24 W. R. 20 W. R. 22 W. R. 19 W. R. 21 W. R. 23 W. R. 18 W. R. 11 W. R. 13 W. R. 12 W. R. 16 W. R. 17 W. R. 15 W. R. 14 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

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MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

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naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

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Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 4. Generalized surface geology in the study area.
Description of Study Area 9

Table 1. Generalized stratigraphic column showing geologic units west of the Missouri River in study area.

[Modified from Carter (1998), Diffendal and Voorhies (1994), and Newport (1959). --, not applicable]

Era System Series Mapped unit Subdivisions Thickness 

(feet) Description and origin

Cenozoic

Quaternary

Holocene Alluvium -- 0–30

Light brown to gray, unconsolidated, clay, silt, and 

fine sand; discontinuous sandy and clayey gravel 

beds in lower part. Fluvial.

Holocene and 

Pleistocene

Windblown sand 

deposits -- 0–50

Brown, unconsolidated, very fine to medium 

grained, uniform, quartz sand; characterized by 

dune topography and blowouts. Eolian.

Pleistocene Terrace deposits -- 0–80

Brown, silty clay, sand, and gravel. Commonly, the 

silty and sandy layers are partly cemented, and the 

gravel and sand beds are commonly interbedded 

with laminated silty clay. Fluvial.

Mesozoic

Tertiary

Pliocene Ogallala Formation

Ash Hollow 

Formation

0–200

Gray, fine- to medium-grained calcareous, interbedded sandstone, sand and volcanic ash. Fluvial.

Valentine 

Formation

Tan to pale olive, fine- to medium-grained sand, 

sandstone, and gravel with some silty clay. 

Fluvial.

Miocene Arikaree Formation

Turtle Butte 

Formation

0–235

White to light gray, reddish brown, tuffaceous and 

calcareous clay, sand, sandstone, and silt. Fluvial.

Rosebud 

Formation

Light-tan to brown, interbedded calcareous sand, 

silt, and clay; contains gray to pinkish-gray 

tabular concretions and small light-brown and 

greenish clay beds. Fluvial.

Oligocene White River Group, 

undifferentiated -- 0–350

Yellow to brown, poorly consolidated siltstone and 

claystone with some beds of fine-grained sand. 

Units of the White River Group sometimes are 

differentiated into the Brule and Chadron Formations. Fluvial.

Cretaceous

Upper 

Cretaceous

Pierre Shale -- 0–1,000 Dark-gray marine shale and mudstone with some 

layers of bentonite. Marine.

Niobrara Formation -- 200–275 Tan to gray, highly calcareous shale, commonly 

described by drillers as “chalk.” Marine.

Carlile Shale -- 130–400 Light grayish blue to black, non-calcareous shale. 

Marine.

Greenhorn Formation -- 25–30 Tan, bluish, white, or gray limestone interbedded 

with shale. Marine.

Graneros Shale -- 65–200 Dark-gray noncalcareous shale containing thin beds 

of limestone and of sandy shale. Marine.

Lower 

Cretaceous

Dakota Formation 

(Dakota Sandstone) -- 350–700

Interbedded tan to white sandstone and dark-colored 

shale. Sandstone is composed of loose to wellcemented, very fine to coarse quartz sand; cement 

most commonly is calcium carbonate. Marine.

Paleozoic

Ordovician

Red River and Winnipeg Formations 

(undifferentiated)

-- 0–170

The Red River Formation mostly consists of dolomite, and the Winnipeg Formation mostly consists 

of sandstones. Marine.

Precambrian -- -- -- Granite and quartzite1.

1

From McCormick (2010).
10 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Ogallala aquifer is present throughout most of the southern part of the study area where it underlies approximately 

1,050 mi2 in Gregory and Tripp Counties and is absent in the 

northern part of the study area where older formations are 

exposed at land surface and to the east of the Missouri River 

(fig. 4).

Drainages of the large streams in the study area have cut 

down through the base of the aquifer and have exposed the 

underlying rock units. Within the study area, both the Keya 

Paha River and Ponca Creek are eroded through the base of 

the aquifer. The alluvial sediments surrounding the Keya Paha 

River are in contact with the Ogallala aquifer and thus are considered hydraulically connected to the aquifer (fig. 4). Alluvial 

sediments surrounding Ponca Creek are separated from the 

Ogallala aquifer by the low permeability Pierre Shale, and 

therefore are not hydraulically connected to the Ogallala aquifer. In the study area, the Ogallala aquifer is generally thickest 

in the central part of Tripp County (Filipovic, 2004).

The Arikaree aquifer generally comprises the saturated 

sandstones and siltstones of the Arikaree Formation and generally is confined where overlain by low permeability materials 

at the base of the Ogallala Formation (Long and others, 2003). 

Although the Arikaree aquifer contains saturated material, 

it will not readily yield water for withdrawal, unless highly 

fractured or fissured, because of its low permeability (Rahn 

and Paul, 1975). For this study, the Arikaree Formation, where 

present, is considered to represent the impermeable lower 

boundary of the overlying Ogallala aquifer because of its low 

permeability. Additionally, few wells within the study area 

penetrate the Arikaree aquifer. The Arikaree aquifer is present in the southwestern part of the study area where it underlies the Ogallala aquifer. The Ogallala and Arikaree aquifers 

collectively compose the High Plains aquifer system, which 

extends southward for hundreds of miles.

Where directly underlying the Ogallala Formation, the 

Brule Formation of the White River Group serves as the 

lower impermeable boundary for the Ogallala aquifer. The 

White River Group exists in the western part of the study area. 

Where the White River Group and Arikaree Formation are 

not present, the Pierre Shale serves as the impermeable lower 

boundary for the Ogallala aquifer (Newport, 1959).

Conceptual Model

A conceptual model of the Ogallala aquifer was used to 

analyze groundwater flow in the study area and to develop 

input datasets for a numerical model to simulate groundwater 

flow in the aquifer. The conceptual model describes the hydrogeologic framework, groundwater flow, hydraulic properties, 

and water budget components of the Ogallala aquifer for WYs 

1985–2009.

Hydrogeologic Framework

The unconsolidated Quaternary-age windblown, terrace, 

and alluvial deposits overlying the Ogallala aquifer within the 

study area have similar hydrogeologic properties and are in 

direct hydraulic connection with the Ogallala aquifer (Weeks 

and Gutentag, 1981); therefore, these units are considered 

together with the Ogallala aquifer as a single, water-bearing 

unit for the purposes of this study. The Pierre Shale, White 

River Group, and Arikaree Formation are considered the 

underlying confining units for the Ogallala aquifer where they 

directly underlie the Ogallala Formation because of their low 

permeability.

Recharge to the Ogallala aquifer occurs from precipitation on the outcrop of the Ogallala Formation. Groundwater 

originating from precipitation moves from areas of high altitude toward streams that gain flow from the Ogallala aquifer. 

Discharge by evapotranspiration from the aquifer occurs in 

areas where the water table is at or near the land surface. Additionally, discharge from the Ogallala aquifer occurs through 

withdrawals for irrigation, production, domestic, and stock 

wells (Filipovic, 2004).

The saturated thickness of the aquifer was determined by 

examining well completion reports (South Dakota Department 

of Environment and Natural Resources, 2011) and saturated 

thickness contours published by Filipovic (2004). The saturated thickness at individual well locations and saturated thickness contours were used to interpolate the saturated thickness 

of the Ogallala aquifer in the study area. A geographic information system (GIS) layer of the distribution of the saturated 

thickness in the study area was developed using the kriging 

interpolation from the Geostatistical Analyst tool in ArcGIS 

(Esri, 2011a,b). The mean saturated thickness for the Ogallala 

aquifer ranged from 10 to 166 ft (fig. 5).

Groundwater Flow

A mean potentiometric surface was estimated for the 

analysis period (WYs 1985–2009) for the Ogallala aquifer. 

The extents of the Ogallala aquifer were modified from Martin 

and others (2004) and Filipovic (2004) to represent areas 

with sufficient saturation for inclusion in the numerical model 

(figs. 6 and 7). The mean potentiometric surface was constructed from water-level data and associated land-surface altitudes from 261 wells between October 1, 1984, and September 

30, 2009 (WYs 1985–2009).

Water levels during 2002 and 2003 were documented by 

Filipovic (2004) for selected wells completed in the Ogallala 

aquifer. Filipovic (2004) drilled 126 test holes, 21 of which 

were completed as observation wells in the Ogallala aquifer 

(fig. 6). Filipovic (2004) concluded that water-level altitudes in wells completed in the Ogallala aquifer ranged from 

1,898 to 2,476 ft above NGVD 29. From 1978 through 2003, 

selected wells showed water-level fluctuations of less than 

10 ft (Filipovic, 2004). Estimated water levels from test holes 
Conceptual Model 11

R. 25 W. R. 24 W. R. 20 W. R. 22 W. R. 19 W. R. 21 W. R. 23 W. R. 18 W. R. 11 W. R. 13 W. R. 12 W. R. 16 W. R. 17 W. R. 15 W. R. 14 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

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Colome

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LYMAN COUNTY AURORA COUNTY

BRULE COUNTY

TRIPP COUNTY

GREGORY COUNTY

CHARLES MIX COUNTY

DOUGLAS COUNTY

KEYA PAHA COUNTY BOYD COUNTY

YTNUOCDDOT

FORT RANDALL 

DAM

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLEM

YTNUOC

EXPLANATION Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985 Universal Transverse Mercator projection, zone 14

Saturated thickness, in feet

Greater than 0 to 25Greater than 25 to 50Greater than 50 to 75Greater than 75 to 100Greater than 100 to 125Greater than 125 to 150Greater than 150 to 175

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SOUTH DAKOTA

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wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

Figure 5. Estimated mean saturated thickness of the Ogallala aquifer in the study area.
12 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

1£¤8 28£¤1

18£¤3

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Mud Creek

Willow Creek

48 36

29

51 43

35 22

13

18

68 100

83 74

97 87 71

209

181 188

132

126

157

167

249 235 239 237 236 238

243

244

159 242 241 240

233 234

11 10 9 55

7 8

56

4 5 6 37 3 1

59 58

57

53

52

54 46

42 41

47 45

44 34

33

21 23

26 24

25

50 40

49

39 32

27 20

19 16

14

17

115 111

38 102 31 101 103

30 90 91

28

85 86 79

78 76 66 65

77 69

64

67

15 12

117

118

113

114

109 108

110 107 99

89

82

84 73 75 61 62 63

116 112 105 215 217 106

104 94

98

95 96 92 93

154

88

155 153

152 147

81 80

72

121

122

138

40

60

231

214

206

205

207

216

213 212

208

18

1

6

87

211 210

194

192

193 191

182

185 190

189

151 146 144 145 143

127 125 12

1

4

23

135

136

128

120

134

133

131

130

137

129 22

2

9

23 222

230 228

225

226

220

219

221

227

224 218

199

201

196

195

203 204 200 161 168165

149

166

150 148 141

142

140

139

119

256

258

259

257

261

260 251 253

248

247 254

252

250

160

245

156

158 246 232

255

2

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

M

A

N

CO

U

NTY

A

U

R

O

R

A

CO

U

NTY

BR

ULE

CO

U

NTY

TRIPP

CO

U

NTY

G

REG

O

RY

CO

U

NTY

CH

A

RLES

MIX CO

U

NTY

D

O

U

GLAS

CO

U

NTY

KEYA PA

H

A CO

U

NTY

FORT RANDALL 

DAM

169

184

180 179 183

202

198

197

176

163

177

173

170 174

162

164

172

175

178

182

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

31

22

21

ETTELLE M

YTNUOC

EXPLANATION

State observation wellTest hole, domestic, or stock water wellObservation well completed by Filipovic (2004)

Extent of the Ogallala aquifer

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

Wells—Number is index number from table 2; supplement 1 (table S1–1)

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Figure 6. Location of South Dakota Department of Environment and Natural Resources observation wells, test holes, and individual wells used to estimate the mean potentiometric surface of the Ogallala aquifer in the study area.
Conceptual Model 13

R. 25 W. R. 24 W. R. 20 W. R. 22 W. R. 19 W. R. 21 W. R. 23 W. R. 18 W. R. 11 W. R. 13 W. R. 12 W. R. 16 W. R. 17 W. R. 15 W. R. 14 W. R. 10 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

2 3, 00

2 3, 00

2 2, 00

2,200

2,050

2,050

2 0, 50

2,250

, 2

01 0

2,10

2

0

,100

058

, 1

2,250

2 1, 50

2,050

2,150

2 2, 50

2,150 008, 1

, 2

03 0

2,000

2,300

000

, 2

001, 2

2,400

2,100

2,350

2 2, 50

2 2, 00

2,350

2,150

2,300

2 1, 50

2,350

2 3, 50

2,150

2,350

2,250

2,100

, 1

59 0

050

, 2

1 9, 50

2 2, 00 2,100 2,200

000, 2

2 0, 00

2,150

2 5, 00

2,150

9

, 1

00

2,400

1 9, 00

2,300

2,300

2 2, 00

2,300

2 1, 50

2,200

2 4, 50

2 4, 00

2 1, 50

2 4, 50

2 3, 50

2,250

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

EXPLANATION

Potentiometric contour—Shows mean altitude at which water level

would have stood in tightly cased wells, water years 1985–2009, in feetabove National Geodetic Vertical Datum of 1929. Dashed whereapproximately located. Contour interval 50 feet

General direction of groundwater flow—Dashed where approximate

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Extent of the Ogallala aquiferLine of geologic section (fig. 8)

A' A

FORT RANDALL 

DAM

A A'

2,250

LYMAN COUNTY AURORA COUNTY

BRULE COUNTY

TRIPP COUNTY

GREGORY COUNTY

CHARLES MIX COUNTY

DOUGLAS COUNTY

KEYA PAHA COUNTY BOYD COUNTY

YTNUOCDDOT

ETTELLEM

YTNUOC

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

Figure 7. Estimated mean potentiometric surface of the Ogallala aquifer in the study area, water years 1985–2009 (modified from Filipovic, 2004).
14 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

and measured water levels in observation wells completed 

by Filipovic (2004) were used to estimate the mean potentiometric surface for the study area for WYs 1985–2009 (table 

S1–1).

Long-term records were available for 38 State observation wells completed in the Ogallala aquifer in the study area 

that are maintained by the South Dakota Department of Environment and Natural Resources (SDDENR; fig. 6; table 2; Ken 

Buhler, South Dakota Environment and Natural Resources, 

written commun., 2009). During the 25-year analysis period, 

some water levels increased, some decreased, and some 

changed very little.

Additional water-level data were obtained from the 

USGS National Water Information System database (U.S. 

Geological Survey, 2011), well completion reports (Ken 

Buhler, South Dakota Environment and Natural Resources, 

written commun., 2009), and lithologic logs (South Dakota 

Department of Environment and Natural Resources, 2010) 

for 223 well and test hole locations (fig. 6; table S1–1). These 

additional data represent SDDENR test holes and domestic 

and stock wells located within the study area. Data used for 

the construction of the mean potentiometric surface included 

well locations, land-surface altitude, and depth to water. In 

many cases, the land-surface altitude of a well location was 

not provided. Any well that did not have land-surface altitude 

information was plotted at its legal location using the GIS 

software ArcMap (Esri, 2011c), and the National Elevation 

Dataset (NED; U.S. Geological Survey, 2006) for the study 

area was used to determine the land-surface altitude at each 

well.

Using the land-surface altitude for each well and the 

depth to water, the mean water-level altitude (hydraulic head) 

for each well was determined (table S1–1). Wells with a single 

water-level measurement were used without adjustment. All 

water-level measurements for individual State observation 

wells were averaged for the 25-year analysis period. In locations where few water-level data were available, the potentiometric surface published by Filipovic (2004) was used as control. The kriging interpolation from the Geostatistical Analyst 

tool was used to interpolate the mean potentiometric surface in 

the study area. Kriging assumes that the distance or direction 

between sample points (hydraulic-head measurements) reflects 

a spatial correlation that can be used to explain the variation 

in a surface (potentiometric surface). The kriging interpolation 

from the Geostatistical Analyst tool fit a mathematical function 

to a specified number of points or all points within a specified 

radius of measurement locations to determine the output value 

for each location. Kriging weights surrounding measured 

values were used to derive a prediction for an unmeasured 

location (Esri, 2011b). The Geostatistical Analyst tool and the 

kriging algorithm are described in the help documentation for 

ArcGIS (Esri, 2011a,b).

In some low-lying parts of the study area, the interpolated 

potentiometric surface was above the land surface. Where 

above the land surface, the interpolated hydraulic head was set 

equal to the land-surface altitude. The resulting potentiometric 

surface map represents mean conditions for the 25-year 

analysis period. Water-level data for the Ogallala aquifer were 

not available southeast of Fairfax, S. Dak., in the study area 

(fig. 7). Therefore, the potentiometric surface was extrapolated 

southeast of Fairfax to include all parts of the Ogallala aquifer 

within the study area.

The mean potentiometric surface for WYs 1985–2009 

(fig. 7) indicates that the hydraulic head of the Ogallala aquifer 

ranged from less than 1,800 to greater than 2,500 ft, and the 

hydraulic gradient was about 6 ft/mi toward the southeast. 

Locally, groundwater flow is topographically controlled and 

is toward perennial streams and rivers (figs. 7 and 8). On the 

basis of the orientation of the potentiometric surface, regional 

inflow occurs along the western and southwestern boundaries of the study area, and regional outflow occurs along the 

southeastern boundary of the study area. Because of the low 

permeability units at the base of the Ogallala aquifer, upward 

and downward seepage of groundwater were assumed to be 

negligible. Thus, groundwater flow in the Ogallala aquifer is 

assumed to be predominantly horizontal.

ArcGIS layers for the mean saturated thickness (fig. 5) 

and the mean potentiometric surface (fig. 7) were used to 

determine the base of the Ogallala aquifer in the study area. 

The mean saturated thickness was subtracted from the mean 

potentiometric surface to calculate the aquifer base (fig. 9). 

The altitude of the base of the aquifer ranged from 1,621 ft 

above NGVD 29 in the southeast part of the study area to 

2,445 ft above NGVD 29 in the western part of the study area.

Hydraulic Properties

Hydraulic properties (transmissivity, hydraulic conductivity, storage coefficient, and specific yield) for the Ogallala 

aquifer in and near the study area have been estimated by previous investigators (table 3). Rahn and Paul (1975) estimated 

hydraulic properties for the Ogallala aquifer by conducting 

an aquifer test in southwestern Todd County and analyzing 

time- and distance-drawdown data for water levels measured 

in 11 observation wells. The mean hydraulic conductivity 

determined from the aquifer test, assuming a mean saturated 

thickness of 84 ft, was 58.7 feet per day (ft/d). The hydraulic 

conductivity ranged from 28.8 to 189.4 ft/d. This represents 

a mean transmissivity of 4,930 square feet per day (ft2/d). 

Specific yields ranged from 0.00921 to 0.23 (Rahn and Paul, 

1975). Kolm and Case (1983) estimated hydraulic conductivity for the High Plains aquifer in South Dakota by analyzing 

grain-size descriptions from 205 wells logs. The estimated 

hydraulic conductivity ranged from 3.6 to 160 ft/d (Kolm and 

Case, 1983). Kremin-Smith (1984) analyzed data from three 

aquifer tests. The hydraulic conductivity ranged from 7.9 to 

21.6 ft/d, and transmissivity ranged from 1,644 to 3,088 ft2/d 

for the three aquifer tests.

Long and others (2003) and Long and Putnam (2010) 

simulated groundwater flow in the Ogallala and Arikaree 

aquifers in Mellette and Todd Counties in south-central South 
Conceptual Model 15

Table 2. Selected data for long-term State observation wells completed in the Ogallala aquifer in Gregory and Tripp Counties.

[Hydraulic heads are estimated means for water years 1985–2009. NGVD 29, National Geodetic Vertical Datum of 1929; --, no data]

Index number 

(fig. 6) Well name Site identification number Legal location Land-surface altitude (feet above NGVD 29) Well depth

Mean measured 

hydraulic head 

(feet above NGVD 29)

74 GY–57A 430743099115001 96N71W13CCBB 2,163 39 2,138.5

68 GY–57B 430542099055901 96N70W34AAAD 2,085 16 2,080.0

126 GY–77A 431153099212201 97N72W21DDDD 2,150 53 2,145.2

132 GY–77B 431101099211901 97N72W27DDDD 2,163 56 2,152.9

71 GY–78A 431006099163801 96N71W 6AAAA 2,165 123 2,112.9

22 GY–78B 430129099201201 95N72W22DDDD 2,217 104 2,182.7

13 GY–78C 430405098563401 95N69W 1DDDD 1,930 64 1,897.7

18 GY–78D 430310098574401 95N69W14AAAA 1,943 83 1,909.7

29 TR–57C 425946099382001 95N74W31DDCC 1 1,990 30 1,963.1

48 TR–59B 430010099580601 95N77W32CAAD 2,380 76 2,342.3

233 TR–72A 431711099510601 98N76W20DDDD 2,231 70 2,169.7

234 TR–72B 431703099502901 98N76W28BAAA 2,198 84 2,171.8

235 TR–72C 431714099510501 98N76W29DDAA 2,231 57 2,216.4

243 TR–72D 431604099510401 98N76W32AADD 2,241 63 2,221.8

159 TR–72E 431519099520301 97N76W 5BBBA 2,264 42 2,257.3

237 TR–72F 431553099525701 98N76W31BDCA 2,282 118 2,238.3

238 TR–72G 431553099524602 98N76W31BDDB 2 2,265 -- 2,231.2

239 TR–72H 431553099525503 98N76W31BDDB 3 2,265 -- 2,225.3

236 TR–74A 431550099524501 98N76W31ACCC 2,260 28 2,248.8

242 TR–74D 431527099523001 98N76W31DCDD 2,279 34 2,258.2

241 TR–74E 431527099524501 98N76W31DCCC 2,275 39 2,253.4

240 TR–74F 431528099522801 98N76W31DCBB 2,263 29 2,257.1

244 TR–75B 431605099504001 98N76W33BACC 2,230 65 2,223.3

169 TR–78A 431334099520701 97N76W17BBBB 1 2,398 165 2,323.1

181 TR–78B 431156099521701 97N76W19DDDD 2 2,390 168 2,342.8

209 TR–78C 431243099553601 97N77W23BBBB 2,340 105 2,335.7

249 TR–78D 431608100051101 98N78W33BBBB 2,430 78 2,416.7

51 TR–78E 430133100061501 95N78W20CCCC 2,430 105 2,388.3

35 TR–78F 430128099520001 95N76W29BBBB 2,253 77 2,222.4

157 TR–78G 431434099462401 97N76W 1DDDD 2,341 45 2,323.3

167 TR–78H 431330099484501 97N76W15AABA 2,332 85 2,327.4

188 TR–78I 431156099472601 97N76W23DDDD 2,362 65 2,355.8

97 TR–78J 430919099521501 96N76W 6DDDD 2,309 25 2,305.5

87 TR–78K 430923099461001 96N75W 6CCCC 2,301 30 2,290.3

100 TR–78L 430638099520801 96N76W29BBBB 2,246 46 2,235.7

43 TR–78M 430037099535601 95N77W25DCCC 2,288 185 2,244.9

36 TR–78N 425956099520501 95N76W32CCCC 2,348 66 2,337.8

83 TR–79A 430732099353201 96N74W16DDDD 2,342 35 2,334.8
16 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Dakota. Long and others (2003) estimated that hydraulic 

conductivity ranged from 0.2 to 120 ft/d based on previously 

published values and the spatial distribution of specific capacities of wells. Long and Putnam (2010) published an extension 

of the model by Long and others (2003) and used inverse 

modeling techniques to estimate the hydraulic conductivity for 

the Ogallala aquifer. Estimated hydraulic conductivity ranged 

from 0.2 to 84.4 ft/d (Long and Putnam, 2010).

Hammond and others (1996) conducted an aquifer test in 

the southeastern part of the study area near Bonesteel, S. Dak. 

Analysis of aquifer test data indicated an estimated hydraulic 

conductivity of 86.7 ft/d and a storage coefficient of 0.00045. 

Hammond and others (1996) concluded that the aquifer was 

under semiconfined conditions and suggested that the silt and 

clay layers in the aquifer act as confining or semiconfining 

layers in the aquifer near Bonesteel.

Specific capacity was calculated using data for 88 wells 

completed in the Ogallala aquifer in the study area (fig. 10; 

table S2–1). Specific capacity of the 88 wells ranged from 0.03 

to 24 gallons per minute per foot [(gal/min)/ft] of drawdown, 

with a mean of 2.54 (gal/min)/ft. Transmissivity for the same 

wells was calculated with methods documented by Mace 

(2001). Based on the well discharge rate, measured drawdown, pumping time, well radius, and storage coefficient, the 

calculated transmissivity at these 88 wells ranged from 2.59 to 

about 4,950 ft2/d (table S2–1). 

The calculated transmissivity data were compiled 

in a GIS layer. Using the kriging interpolation from the 

Geostatistical Analyst tool, the transmissivity for the study 

area was plotted in a GIS layer representing the spatial distribution of transmissivity. The spatial distribution of hydraulic conductivity (fig. 10) for the study area was calculated 

by dividing the GIS layer for the estimated transmissivity 

distribution by the GIS layer for the estimated mean saturated 

thickness distribution (fig. 5) in ArcMap.

Water Budget Components

Water budget components of recharge and discharge are 

described in this section. Recharge occurs by infiltration of 

precipitation. Discharge occurs through evapotranspiration, 

discharge to streams, and well withdrawals.

In order to more clearly describe water budget components, each water year during the 25-year analysis period 

(WYs 1985–2009) was subdivided into three discrete time 

intervals called stress periods. For each year of the analysis, 

stress periods represent (1) fall/winter (October through February), (2) spring (March through May), and (3) summer (June 

through September). Three stress periods per year were determined to adequately represent seasonal changes in hydrologic 

data. Stress periods were numbered from 1 through 75, with 

stress period 1 representing October 1984 through February 

1985, and stress period 75 representing June 2009 through 

September 2009.

Willow Creek

Ponca Creek

Tripp County

Gregory County

1,950

2,050

2,150

2,250

2,350

2,450

2,550

0 5 10 15 20 25 30 35 40 45 50 55

Altitude, in feet above

National Geodetic Vertical Datum of 1929

Land surface Hydraulic head Aquifer base

Distance along section, in miles

EXPLANATION

WEST

A

EAST

A'

Ogallala Formation and 

overlying Quaternary-age 

deposits

Undifferentiated

underlying units

VERTICAL SCALE GREATLY EXAGGERATED

General direction of groundwater flow

Figure 8. Generalized relationship between hydraulic head, hydrogeologic units, and topographic features for 

cross-section A–A’. Location of section shown in figure 7.
Conceptual Model 17

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

YTNUOCDDOT

LYMAN

COUNTY COUNTY

AURORA BRULE

COUNTY

TRIPP

COUNTY

GREGORY

COUNTY

CHARLES

MIX COUNTY

DOUGLAS

COUNTY

KEYA PAHA COUNTY

FORT RANDALL 

DAM

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLEM

YTNUOC

EXPLANATION

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Altitude of the base of the Ogallala aquifer, in feet 

above National Geodetic Vertical Datum of 1929

High : 2,445Low : 1,621

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

Figure 9. Altitude of the base of the Ogallala aquifer in the study area.
18 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 3. Previously published hydraulic properties within or near the study area.

[ft2/d, feet squared per day; ft/d, feet per day; --, no data]

Method

In 

study 

area

Transmissivity 

(ft2

/d)

Hydraulic 

conductivity 

(ft/d)

Storage 

coefficient 

(dimensionless)

Specific yield 

(dimensionless)Location Source

Ogallala aquifer

Time drawdown 

aquifer test

Yes 5,027 86.7a 0.00045 -- 95N69W12 (near Bonesteel, 

S. Dak.)

Hammond and 

others, 1996

Time drawdown 

and distance 

drawdown 

aquifer tests

No 4,930 28.8–189.4; 

mean 58.7b

0.0026–

0.055

0.00921–0.23; 

mean 0.057

Todd County 36N32W22 Rahn and Paul, 

1975

Aquifer test No 2,995 21.6 -- 0.02 Todd County 37N29W31CCA Kremlin-Smith, 

1984

Aquifer test No 1,644 7.9 -- 0.03 Todd County 36N29W14CAC Kremlin-Smith, 

1984

Aquifer test No 3,088 17.5 -- 0.02 Todd County 37N29W 8ABB Kremlin-Smith, 

1984

Specific capacity No 180–3,476 1.2–25.2 -- -- Todd County Kremlin-Smith, 

1984

Specific capacity No 2–2, 400; 

mean 600

-- -- -- Todd County Carter, 1998

Specific capacity 

and other data

No -- 0.2–120 -- -- Todd and Mellette Counties Long and others, 

2003

Inverse modeling 

techniques

No -- 0.2–84.4 -- -- Todd and Mellette Counties Long and others, 

2010

Unknown Yes 800–9,200; 

mean 2,800

-- -- -- 16 wells to the south and southwest of Tripp County within 

100 miles of Tripp County

Newport, 1959

High Plains aquiferc

Grain size 

descriptions

Yes -- 3.6–160; 

mean 30

-- 0–0.25 Tripp County Kolm and Case, 

1983

a

Calculated from a transmissivity based on saturated thickness of 58 feet.

b

Range calculated from transmissivity based on saturated thickness of 84 feet.

c

Includes Ogallala aquifer and Arikaree aquifer.

Recharge

Recharge to the Ogallala aquifer occurs from infiltration of precipitation on the outcrop of the Ogallala Formation 

and the overlying Quaternary-age deposits in the study area 

(Long and Putnam, 2010). Data were available for 13 National 

Oceanic and Atmospheric Administration (NOAA) climate 

stations in and surrounding the study area, 8 of which are 

within the study area (fig. 11; National Oceanic and Atmospheric Administration, 2010). The mean annual precipitation 

for WYs 1985–2009 for these stations was 22.9 in.

Recharge to the Ogallala aquifer for WYs 1985–2009 was 

estimated using the Soil-Water-Balance (SWB) software program of Westenbroek and others (2010) to calculate recharge 

based on a modified Thornthwaite-Mather SWB approach 

(Thornthwaite, 1948; Thornthwaite and Mather, 1957). The 

SWB program uses climate data, land-use characteristics, 

hydrologic soil properties, surface-water flow direction, and 

available soil-water capacity to calculate recharge for individual model cells. The SWB program calculates recharge as 

the difference between the sources and sinks of water and the 

change in soil moisture. A full description of the SWB method 

used to determine recharge to the Ogallala aquifer is available 

in supplement 3.

Two separate recharge simulations were completed using 

different climate inputs for the SWB program. Recharge calculated by the SWB program was based on climate data from 

stations located in the towns of Winner (station 399367) and 

Gregory (station 393452), S. Dak. (fig. 11; National Oceanic 

and Atmospheric Administration, 2010). The SWB program 

calculated recharge based on daily climate data from each 

station. The results of each simulation were averaged on a 
Conceptual Model 19

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

YTNUOCDDOT

LYMAN

COUNTY

AURORA

COUNTY

BRULE

COUNTY

TRIPP

COUNTY

GREGORY

COUNTY

CHARLES

MIX COUNTY

DOUGLAS

COUNTY

KEYA PAHA COUNTY

2 1 6 3

10

4

11 7 8 5 9

12

13 14

17

16

18 21

19

20

15

22 23

24

28 29 27 26 30

25

36 31

50

32

35 43 51 34 39 42 46 47 48 49 40 4 41 4 45 33 37 38 56

65

54

75

76

66

57

59

60 61 64

72

73 74

52 5

6

8

2

67

70

77

53

63

71 68

69

55

80 81 82 8

8

3

4 85

86 87

78

79

88

FORT RANDALL 

DAM

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

14

20

25

ETTELLEM

YTNUOC

EXPLANATION

Hydraulic conductivity, in feet per day

0.26 to 5.0Greater than 5.0 to 10.0Greater than 10.0 to 20.0Greater than 20.0 to 50.0Greater than 50.0 to 100Greater than 100 to 200Greater than 200

Specific capacity, in gallons per 

minute per foot of drawdown—Number is index number from table S2−1.

0.03 to 4Greater than 4 to 12Greater than 12 to 24

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14 0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8 28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

Figure 10. Calculated specific capacity of selected wells completed in the Ogallala aquifer and estimated hydraulic conductivity of the aquifer in the study area.
20 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

392822

390778

396574

393452

399367

396669

390043

394195

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

06464500 06453400

06464100

LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

YTNUOC DDOT FORT RANDALL DAM

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

EXPLANATION

Climate station—Number is National Oceanic and

Atmospheric Administration cooperative stationidentification number (National Climatic Data Center, 2010)

# Streamgage—Number is U.S. Geological Survey site identification number

(U.S. Geological Survey, 2011)

Extent of the Ogallala aquifer X

X

X X X X

X

Missouri River

SO

UTH

D

A

K

OTA

NEBRASKA

Study area

2

Location map

51365

394516

255040

395620

258040

258090

399442

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

ETTELLE M

YTNUOC

Figure 11. Locations of climate stations and streamgages in and around the study area.
Conceptual Model 21

cell-by-cell basis and aggregated by stress period. Recharge 

calculated using the SWB method varies spatially within the 

study area; therefore, the results of the SWB method in this 

report represent spatially averaged rates for the part of the 

study area underlain by the Ogallala aquifer.

Estimated annual recharge for the Ogallala aquifer in the 

study area generally ranged from 0.51 to 5.94 in., with a mean 

of 3.14 in. (table 4). For the study area, this represents a mean 

total recharge rate of 239 ft3/s. Seasonally, mean recharge 

for the study area varied from as low as zero in the summer 

months (stress periods 15, 48, 54, and 57) to as high as 5.43 in. 

in the spring months (stress period 32; table 4). Annually, 

recharge generally was highest during the spring stress periods 

(March through May) and lowest during the summer stress 

periods (June through September). On average, calculated 

recharge was 12.1 percent of precipitation for the study area. 

The spatial distribution of mean annual recharge for SWB 

model cells for WYs 1985–2009 ranged from 0.1 to 15.4 in. 

across the study area (fig. 12).

The recharge rates estimated using the SWB method 

were compared with previous estimates of recharge for the 

Ogallala aquifer. The 25-year mean recharge of 3.14 inches 

per year (in/yr) (12.1 percent of precipitation) estimated by 

the SWB method for the Ogallala aquifer in Gregory and 

Tripp Counties generally was similar to previously published 

estimates of recharge for the aquifer. Previous estimates of 

recharge include 15 percent of precipitation or 3.4 in/yr for the 

study area (Langbein, 1949). Kolm and Case (1983) estimated recharge to the Ogallala aquifer in the study area to be 

8 percent of annual precipitation or 1.8 in/yr. Newport (1959) 

estimated 1–2 in/yr of recharge to the aquifer for the lower 

Niobrara River (fig. 1), which includes the Keya Paha River 

and Ponca Creek drainage basins (fig. 3). LaBelle (2011) estimated recharge to the Ogallala and Arikaree aquifers in Bennett, Jackson, and Shannon Counties in South Dakota, which 

are located immediately west of Mellette and Todd Counties, 

using the SWB program; the mean recharge to the Ogallala 

aquifer between 1970 and 2009 was estimated to be 3.28 in/yr.

Previously published estimates of recharge for the Ogallala aquifer provide a reasonable representation of recharge 

to the aquifer, but these estimates generally are only defined 

as a constant percentage of precipitation. The SWB program 

calculates spatially and temporarily variable recharge based on 

multiple input data. For these reasons, the results of the SWB 

program are considered an improvement compared with previous estimates of recharge for the Ogallala aquifer.

Discharge

Discharge from the Ogallala aquifer occurs through 

evapotranspiration, discharge to streams, and well withdrawals. Discharge by evapotranspiration generally occurs in topographically low areas or where the water table is near the land 

surface. Discharge to streams occurs as flow from springs and 

seeps and as base flow where the aquifer is hydraulically connected to the streams (river leakage). For the purpose of this 

analysis, all discharge from springs and seeps was assumed to 

reach a stream and contribute to base flow. Well withdrawals 

are from irrigation, public supply, domestic, and stock wells.

Evapotranspiration

Evapotranspiration represents the amount of water 

removed from the saturated groundwater regime by plant 

transpiration and direct evaporation from groundwater in the 

saturated and unsaturated zone (Wilson and Moore, 1998). 

Evapotranspiration from groundwater occurs when the water 

table is at or near the land surface; therefore, evapotranspiration generally occurs in topographically low areas, such as 

river valley bottoms (Long and Putnam, 2010). When the 

water table is at the land surface, evapotranspiration is greater 

than when the water table is below the land surface. Potential evapotranspiration represents the maximum amount of 

groundwater that could be evapotranspired if the system is 

not water-limited. Evapotranspiration is assumed equal to the 

maximum potential evapotranspiration rate when the water 

table is at the land surface, and it decreases linearly to zero 

when the water table is beneath the root zone. For the study 

area, the rate of evapotranspiration is a product of the surface 

vegetation, depth of the root zone, and depth to water, where 

applicable.

The SWB method was used to calculate estimates for 

maximum potential evapotranspiration for the study area, in 

addition to recharge, as described in supplement 3. The SWB 

method can be used to calculate potential evapotranspiration 

based on five commonly used evapotranspiration methods 

(Westenbroek and others, 2010). Calculations of evapotranspiration for the study area using the SWB program were based 

on methods developed by Hargreaves and Samani (1985), 

which incorporate the latitudinal location of the study area and 

maximum and minimum daily temperatures. The other four 

evapotranspiration methods available to the SWB program 

were not used because they required humidity and wind speed, 

which were not available.

The maximum potential evapotranspiration estimated 

with the SWB method for the 25 summer stress periods (third 

stress period for each water year) ranged from 19.1 to 22.0 in. 

(table 5), with a mean of 20.6 in.. Estimated mean maximum 

potential evapotranspiration for the fall/winter and spring 

stress periods (first and second stress periods for each water 

year, respectively) was 0.7 and 4.1 in., respectively. Estimates 

from the SWB method indicate an annual mean maximum 

potential evapotranspiration of 25.4 in/yr for the study area 

(table 5). This does not represent the actual amount of water 

removed from the saturated groundwater regime; rather, it represents the maximum amount of water that could be removed 

if there was never a deficiency of water in the soil for use by 

vegetation (Wilson and Moore, 1998).

The evapotranspiration rates estimated using the SWB 

method for this study were compared with previous estimates 

of evapotranspiration of the Ogallala aquifer to examine plausible ranges for the estimates. Farnsworth and others (1982) 
22 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W. T. 101 N. T. 100 N. T. 99 N. T. 98 N. T. 97 N. T. 96 N. T. 95 N. 98°30' 99°00' 99°30' 100°00' 43°30' T. 40 N. T. 39 N. 43°20' T. 38 N. T. 37 N. 43°10' T. 36 N. T. 35 N. 43°00' R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

YTNUOC DDOT FORT RANDALL DAM

ETTELLE M

YTNUOC

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Average recharge, in inches

Greater than 0 to 1.5Greater than 1.5 to 3.0Greater than 3.0 to 6.0Greater than 6.0 to 10.0Greater than 10.0 to 15.4

EXPLANATION

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 12. Spatial distribution of mean annual recharge to the Ogallala aquifer in the study area for water years 1985–2009 estimated with the soil-water-balance method.
Conceptual Model 23

Table 4. Recharge to the Ogallala aquifer in the study area estimated by using the soil-water-balance method, water years 1985–2009.

[--, not applicable]

Water 

year

Stress 

period Months

Precipitation 

(inches)

Recharge 

(inches)

Recharge as 

a percentage of precipitation

1985 1 Oct.–Feb. 2.87 0.10 3.37

1985 2 Mar.–May 4.72 0.62 13.10

1985 3 June–Sept. 14.74 0.34 2.32

1986 4 Oct.–Feb. 5.36 2.18 40.64

1986 5 Mar.–May 10.67 2.50 23.45

1986 6 June–Sept. 18.27 1.17 6.41

1987 7 Oct.–Feb. 5.14 1.34 26.02

1987 8 Mar.–May 10.70 3.46 32.29

1987 9 June–Sept. 12.37 0.21 1.70

1988 10 Oct.–Feb. 6.02 1.81 30.15

1988 11 Mar.–May 11.13 2.73 24.56

1988 12 June–Sept. 11.32 0.22 1.95

1989 13 Oct.–Feb. 1.99 0.47 23.64

1989 14 Mar.–May 3.33 0.57 17.14

1989 15 June–Sept. 8.91 0.00 0.04

1990 16 Oct.–Feb. 2.96 0.12 4.06

1990 17 Mar.–May 10.87 2.47 22.73

1990 18 June–Sept. 11.66 0.26 2.20

1991 19 Oct.–Feb. 3.73 0.09 2.45

1991 20 Mar.–May 12.27 2.39 19.49

1991 21 June–Sept. 6.66 0.29 4.34

1992 22 Oct.–Feb. 5.69 0.67 11.84

1992 23 Mar.–May 4.41 1.34 30.32

1992 24 June–Sept. 15.63 0.04 0.27

1993 25 Oct.–Feb. 4.18 0.25 5.94

1993 26 Mar.–May 7.58 2.91 38.42

1993 27 June–Sept. 13.20 0.01 0.07

1994 28 Oct.–Feb. 4.05 0.48 11.92

1994 29 Mar.–May 4.13 0.94 22.79

1994 30 June–Sept. 14.26 0.01 0.07

1995 31 Oct.–Feb. 4.34 0.50 11.45

1995 32 Mar.–May 16.27 5.43 33.39

1995 33 June–Sept. 8.96 0.01 0.11

1996 34 Oct.–Feb. 7.16 1.56 21.81

1996 35 Mar.–May 8.84 2.40 27.11

1996 36 June–Sept. 13.06 0.63 4.80

1997 37 Oct.–Feb. 5.16 2.13 41.38

1997 38 Mar.–May 5.48 1.73 31.55

1997 39 June–Sept. 11.67 0.17 1.43

Water 

year

Stress 

period Months

Precipitation 

(inches)

Recharge 

(inches)

Recharge as 

a percentage of precipitation

1998 40 Oct.–Feb. 6.11 0.98 16.08

1998 41 Mar.–May 9.61 2.97 30.94

1998 42 June–Sept. 14.63 0.67 4.56

1999 43 Oct.–Feb. 4.50 0.84 18.71

1999 44 Mar.–May 10.25 2.53 24.65

1999 45 June–Sept. 13.64 0.32 2.35

2000 46 Oct.–Feb. 1.64 0.08 4.94

2000 47 Mar.–May 6.21 0.43 6.98

2000 48 June–Sept. 4.60 0.00 0.00

2001 49 Oct.–Feb. 6.92 0.27 3.92

2001 50 Mar.–May 11.69 3.44 29.47

2001 51 June–Sept. 11.10 0.01 0.13

2002 52 Oct.–Feb. 2.94 0.44 15.01

2002 53 Mar.–May 5.22 1.13 21.76

2002 54 June–Sept. 6.63 0.00 0.04

2003 55 Oct.–Feb. 2.87 0.05 1.75

2003 56 Mar.–May 7.12 1.16 16.25

2003 57 June–Sept. 8.36 0.00 0.01

2004 58 Oct.–Feb. 3.21 0.04 1.22

2004 59 Mar.–May 7.91 0.94 11.84

2004 60 June–Sept. 11.82 0.48 4.09

2005 61 Oct.–Feb. 3.41 0.92 26.94

2005 62 Mar.–May 9.09 1.54 16.95

2005 63 June–Sept. 12.73 1.05 8.29

2006 64 Oct.–Feb. 2.63 0.06 2.13

2006 65 Mar.–May 4.08 0.67 16.50

2006 66 June–Sept. 10.90 0.01 0.14

2007 67 Oct.–Feb. 5.17 1.32 25.58

2007 68 Mar.–May 12.02 2.72 22.64

2007 69 June–Sept. 11.86 0.42 3.58

2008 70 Oct.–Feb. 6.05 2.05 33.95

2008 71 Mar.–May 7.32 2.32 31.76

2008 72 June–Sept. 11.94 0.41 3.45

2009 73 Oct.–Feb. 6.76 1.58 23.44

2009 74 Mar.–May 5.28 2.11 39.91

2009 75 June–Sept. 14.35 0.04 0.30

Annual 

mean

-- -- 24.4 3.14 12.1
24 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 5. Measured pan evaporation at Pickstown, South Dakota, and maximum potential evapotranspiration estimated by using the 

soil-water-balance method, water years 1985–2009.

[--, not applicable]

Water 

year

Stress 

period

Measured 

pan evaporation 

(inches)

Maximum potential evapotranspiration 

(inches)

Evapotranspiration as a 

percentage of 

evaporation

1985 1 -- 0.6 --

1985 2 -- 6.7 --

1985 3 24.00 22.0 91.7

1986 4 -- 0.6 --

1986 5 -- 4.6 --

1986 6 28.17 20.6 73.1

1987 7 -- 0.8 --

1987 8 -- 6.3 --

1987 9 29.46 19.3 65.5

1988 10 -- 0.8 --

1988 11 -- 5.2 --

1988 12 32.10 19.5 60.7

1989 13 -- 0.8 --

1989 14 -- 4.9 --

1989 15 30.55 20.4 66.8

1990 16 -- 0.8 --

1990 17 -- 3.9 --

1990 18 30.78 21.1 68.6

1991 19 -- 0.8 --

1991 20 -- 4.7 --

1991 21 36.04 20.0 55.5

1992 22 -- 0.8 --

1992 23 -- 5.6 --

1992 24 25.28 21.6 85.4

1993 25 -- 0.6 --

1993 26 -- 3.2 --

1993 27 24.05 21.4 89.0

1994 28 -- 0.7 --

1994 29 -- 5.2 --

1994 30 26.03 20.4 78.4

1995 31 -- 0.7 --

1995 32 -- 2.6 --

1995 33 31.39 20.8 66.3

1996 34 -- 0.5 --

1996 35 -- 2.1 --

1996 36 28.18 21.5 76.3

1997 37 -- 0.7 --

1997 38 -- 2.7 --

1997 39 27.03 20.8 77.0

Water 

year

Stress 

period

Measured 

pan evaporation 

(inches)

Maximum potential evapotranspiration 

(inches)

Evapotranspiration as a 

percentage of 

evaporation

1998 40 -- 0.6 --

1998 41 -- 3.7 --

1998 42 27.87 19.9 71.4

1999 43 -- 0.8 --

1999 44 -- 3.6 --

1999 45 25.81 20.5 79.4

2000 46 -- 0.9 --

2000 47 -- 5.0 --

2000 48 30.61 20.9 68.3

2001 49 -- 0.5 --

2001 50 -- 3.1 --

2001 51 27.62 19.6 71.0

2002 52 -- 0.9 --

2002 53 -- 3.2 --

2002 54 34.45 20.2 58.6

2003 55 -- 0.5 --

2003 56 -- 4.0 --

2003 57 30.09 20.9 69.5

2004 58 -- 0.7 --

2004 59 -- 5.0 --

2004 60 28.05 21.5 76.6

2005 61 -- 0.7 --

2005 62 -- 3.9 --

2005 63 31.97 20.1 62.9

2006 64 -- 0.9 --

2006 65 -- 3.9 --

2006 66 29.94 20.8 69.5

2007 67 -- 0.6 --

2007 68 -- 4.1 --

2007 69 28.69 19.1 66.6

2008 70 -- 0.7 --

2008 71 -- 2.6 --

2008 72 27.33 20.8 76.1

2009 73 -- 0.6 --

2009 74 -- 2.9 --

2009 75 23.99 21.6 90.0

Annual 

mean

-- 28.78 25.4 --
Conceptual Model 25

estimated maximum evapotranspiration for the Ogallala 

aquifer to be 70 percent of pan evaporation. Pan evaporation 

rates for the study area were assumed to be similar to those 

measured at the NOAA climate station at Pickstown, S. Dak. 

(station 396574; fig. 11; National Oceanic and Atmospheric 

Administration, 2010). Pan evaporation records were available for June through September for the 25 water years of 

the analysis period (table 5). Multiplying the pan evaporation 

records by the 70 percent estimate of Farnsworth and others 

(1982) yielded estimated maximum evapotranspiration for the 

summer months ranging from 16.8 to 26.2 in., with a mean of 

20.4 in. These estimates are similar to those estimated using 

the SWB method for the summer stress periods. Sparse pan 

evaporation data were available for the fall, winter, and spring 

months. Long and Putnam (2010) estimated evapotranspiration rates of 2.1 and 6.3 in., respectively, for the fall/winter 

and spring stress periods, based on pan evaporation rates 

recorded at the NOAA climatological data station at Cottonwood, S. Dak., which is approximately 90 miles (mi) westnorthwest of the study area in Jackson County.

The maximum potential evapotranspiration for the 

summer stress periods estimated using the SWB method was 

compared with the measured pan evaporation at Pickstown 

(table 5). Calculations of maximum potential evapotranspiration generally averaged about 73 percent of total pan evaporation during the summer stress periods. Pan evaporation 

measurements for the fall/winter and spring stress periods 

were sparse; therefore, the maximum potential evapotranspiration estimated by the SWB method for the fall/winter and 

spring stress periods was not compared with measured pan 

evaporation data. The evapotranspiration rates estimated using 

the SWB method for the study area were similar to previously 

estimated evaporation rates for the Ogallala aquifer and thus 

deemed to be reasonable estimates. On the basis of relative 

accuracy of the evapotranspiration rates estimated using the 

SWB method for the summer stress periods, the SWB estimates of evapotranspiration for the fall/winter and spring 

stress periods were assumed to be reasonable, even though pan 

evaporation records for those months were not available for 

comparison.

Discharge to Streams

Springs and seeps discharge groundwater to streams in 

the study area. The Keya Paha River, Ponca Creek, and the 

North Fork and South Fork Whetstone Creek are the major 

streams in the study area that likely receive discharge from 

the Ogallala aquifer based on groundwater-flow directions 

(fig. 7). Base flow is the part of stream discharge that is not 

attributable to direct runoff from precipitation or melting snow 

(Wilson and Moore, 1998), and base flow is considered to 

occur as discharge through springs, seeps, and the hydraulic 

connection between the aquifer and streams flowing over it 

(river leakage).

Base flow in the Keya Paha River in the study area 

was estimated for WYs 1985–2009 using the hydrograph 

separation (partitioning) program PART (Rutledge, 1998). 

The PART program uses hydrograph separation methods on 

continuous streamflow data to estimate a daily record of base 

flow. The discharge from the Ogallala aquifer to the Keya 

Paha River in the study area was estimated to be the difference between the base flow estimated for the farthest upstream 

streamgage and the base flow estimated for the farthest 

downstream streamgage. Long-term streamflow records from 

upstream streamgage 06464100 (Keya Paha River near Keyapaha, S. Dak.) and downstream streamgage 06464500 (Keya 

Paha River at Wewela, S. Dak.) were used to estimate mean 

monthly discharge from the Ogallala aquifer to the Keya Paha 

River in the study area as base flow (fig. 11; U.S. Geological 

Survey, 2011). Streamflow measurements are given a rating 

such as excellent if the measurement is within 2 percent of the 

actual flow, good if within 5 percent, fair if within 8 percent, 

and poor if greater than 8 percent (Rantz and others, 1982). 

For the time period used to calculate base flow, 58 percent of 

measurements were rated good, 29 percent were rated fair, 

and 13 percent were rated poor (U.S. Geological Survey, 

2011). The estimated annual mean base flow of the Keya Paha 

River between Keyapaha and Wewela was 35.8 ft3/s for WYs 

1985–2009 (table 6).

Base flow estimated using the PART program (table 6) 

generally increased dramatically from the fall/winter stress 

period (October through February) to the spring period (March 

through May). Actual base flow probably does not fluctuate to 

this magnitude, and the large increases in estimated base flow 

during the spring months probably include a component of 

shallow interflow that occurs after periods of high precipitation and possibly some direct runoff (Long and others, 2003). 

The fall/winter stress periods alone probably provide a better 

estimate of base flow, because these periods generally are not 

affected by recent precipitation. Springtime base flow was 

assumed to increase somewhat compared with the fall/winter 

stress period, but the magnitude of base flow estimated using 

the PART program likely was an overestimation of actual base 

flow during the spring months.

To account for the overestimation, base flow for the 

spring stress period was calculated as the fall/winter base flow 

plus 25 percent of the increase between the fall/winter stress 

period and the spring stress period. The base flow for the summer stress period was then estimated as the mean base flow 

of the two previous periods. The adjustment between the fall/

winter stress period and the spring stress period, as described 

in Long and others (2003), was used by Long and Putnam 

(2010) for the Keya Paha River upstream from Tripp County 

and was considered to be applicable for the Kaya Paha River 

in the study area. The base-flow estimates were then increased 

by 4 percent to account for a possible underestimation of 

annual base flow in the study area (table 6).

A large component of the base flow for the Keya Paha 

River is likely to be discharge from springs and seeps that 

originate in the Ogallala aquifer. Additionally, Sand, Shadley, 

Willow, Lost, Cottonwood, and Timber Creeks drain into the 

Keya Paha River between the streamgages (06464100 and 
26 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 6. Discharge to the Keya Paha River as base flow estimated using hydrograph separation, water years 1985–2009.

[--, not applicable]

Water 

year

Stress 

period

Base flow calculated by 

PART (Rutledge, 1998), 

in cubic feet per second

Adjusted estimated 

base flow, 

in cubic feet per 

second

1985 1 15.9 16.5

1985 2 33.5 21.0

1985 3 28.4 18.7

1986 4 19.7 20.4

1986 5 71.7 33.8

1986 6 19.1 27.1

1987 7 37.5 38.8

1987 8 77.6 49.2

1987 9 28.8 44.0

1988 10 22.7 23.5

1988 11 121.4 49.1

1988 12 27.0 36.3

1989 13 15.7 16.2

1989 14 31.2 20.2

1989 15 25.8 18.2

1990 16 20.7 21.4

1990 17 31.1 24.1

1990 18 10.6 22.8

1991 19 8.70 9.01

1991 20 41.4 17.5

1991 21 23.3 13.3

1992 22 24.9 25.8

1992 23 24.4 25.7

1992 24 20.1 25.7

1993 25 15.8 16.4

1993 26 60.5 27.9

1993 27 24.9 22.1

1994 28 43.3 44.8

1994 29 66.8 50.9

1994 30 28.3 47.9

1995 31 18.2 18.8

1995 32 142.3 51.0

1995 33 19.7 34.9

1996 34 88.3 91.4

1996 35 84.5 90.4

1996 36 70.2 90.9

1997 37 71.2 73.7

1997 38 131.5 89.4

1997 39 42.0 81.6

Water 

year

Stress 

period

Base flow calculated by 

PART (Rutledge, 1998), 

in cubic feet per second

Adjusted estimated 

base flow, 

in cubic feet per 

second

1998 40 40.3 41.7

1998 41 58.9 46.6

1998 42 45.9 44.1

1999 43 77.2 79.9

1999 44 113.4 89.3

1999 45 72.1 84.6

2000 46 28.6 29.6

2000 47 54.2 36.3

2000 48 41.7 33.0

2001 49 11.7 12.2

2001 50 110.3 37.7

2001 51 17.3 24.9

2002 52 35.7 36.9

2002 53 45.8 39.6

2002 54 42.7 38.3

2003 55 24.1 24.9

2003 56 38.0 28.6

2003 57 10.6 26.7

2004 58 12.8 13.3

2004 59 32.9 18.5

2004 60 10.7 15.9

2005 61 19.2 19.9

2005 62 48.0 27.4

2005 63 15.8 23.7

2006 64 16.1 16.6

2006 65 41.9 23.3

2006 66 30.0 20.0

2007 67 28.9 29.9

2007 68 135.3 57.5

2007 69 13.0 43.7

2008 70 19.0 19.7

2008 71 60.0 30.3

2008 72 27.2 25.0

2009 73 25.5 26.4

2009 74 63.2 36.1

2009 75 44.0 31.3

Annual 

mean

-- 43.7 35.8
Conceptual Model 27

06464500) that were used to estimate base flow (fig. 11). 

Other smaller tributaries also drain into the Keya Paha River 

between these two streamgages. These small streams are likely 

to be fed by seeps or springs that originate from the Ogallala 

aquifer. The total base-flow gain between the two streamgages, 

as estimated using the PART program (table 6), was assumed 

to be the sum of the discharge from springs adjacent to the 

Keya Paha River; seeps along the Keya Paha River and Sand, 

Shadley, Willow, Lost, Cottonwood, and Timber Creeks; and 

the hydraulic connection between the aquifer and streams 

through riverbed material.

Ponca Creek, in the eastern part of the study area (figs. 3 

and 11), likely obtains its base flow from small springs and 

seeps that originate in the Ogallala aquifer at the contact 

between the Ogallala Formation and the underlying Pierre 

Shale. Intermittent streamflow data were available for Ponca 

Creek from 1960 through 1974 at streamgage 06453400 

(Ponca Creek near Naper, Nebr.; U.S. Geological Survey, 

2011). Streamflow measurements from October through 

December of each year were assumed to have little effect from 

precipitation and runoff. The mean streamflow during those 

months from 1960 through 1974 was assumed to represent the 

mean discharge as flow from springs and seepage from the 

Ogallala aquifer for the Ponca Creek drainage basin, which 

was 3.85 ft3/s.

Streamflow data were not available for the North Fork 

and South Fork Whetstone Creek and smaller streams in the 

study area (fig. 11); therefore, discharge from the Ogallala 

aquifer into these streams was not estimated for the conceptual 

model. Smaller streams are mainly intermittent, runoff-fed 

streams during periods of high precipitation (Newport, 1959).

Well Withdrawals

Well withdrawals in the study area are primarily for irrigation and public supplies but also for domestic and stock use. 

Irrigation withdrawals are variable because they are affected 

by numerous factors, such as climatic conditions, commodity prices, and energy costs. The locations of irrigation wells 

(fig. 13) in Gregory and Tripp Counties were interpreted 

from driller’s logs (Ken Buhler, South Dakota Department of 

Environment and Natural Resources, written commun., 2009) 

and SDDENR water-use permits (South Dakota Department of 

Environment and Natural Resources, 2011).

Water-use data for irrigation are compiled every 5 years 

as part of the USGS National Water-Use Information Program 

in cooperation with Federal, State, and local agencies. The 

information is aggregated by counties for each State (U.S. 

Geological Survey, 2009). Data on irrigation withdrawals 

for the Ogallala aquifer in Gregory and Tripp Counties were 

obtained from the USGS Site-Specific Water-Use Data System 

(SWUDS) for the period of available record. The SWUDS 

database includes water use reported by operators under 

specific water-use permits. Data for 19 irrigation wells existed 

for the available period of record (WYs 1985–2005). On the 

basis of completion information in driller’s logs and water-use 

permits, it was assumed that the 19 irrigation wells were 

completed in the Ogallala aquifer. The data available for the 

19 wells indicated that some wells were pumped annually for 

the period of record, others were pumped intermittently, and 

others reported no pumping. Reported annual records were 

used to determine irrigation withdrawals for WYs 1985–2005 

(table 7). Withdrawals for WYs 2006–2009 were assumed 

to be equal to the 2005 reported values. The mean irrigation 

withdrawal rate for WYs 1985–2009 was 4.5 ft3/s for the 

4-month irrigation season (June through September), which 

equates to an annual irrigation withdrawal rate of 1.1 ft3/s.

Public supply use accounts for most of the groundwater 

withdrawal from the Ogallala aquifer in Gregory and Tripp 

Counties. The locations of production wells (fig. 13) were 

approximated from specific water-use permits and licenses 

(South Dakota Department of Environment and Natural 

Resources, 2011). Estimates of public supply withdrawals 

were based on the mean reported per capita use for Winner, Gregory, Colome, the Tripp County Water User District, 

and the East Gregory County Rural Water System (table 8). 

Withdrawals for Winner were estimated using mean withdrawals for 2012 (City of Winner, 2012). Withdrawals for Gregory 

were based on withdrawals for 2008 (South Dakota Department of Environment and Natural Resources, 2011). Rates for 

per capita use for Bonesteel, Burke, and Herrick were assumed 

to be equal to the per capita use for Colome and were based on 

withdrawal rates for 1965–1968 (South Dakota Department of 

Environment and Natural Resources, 2011). The per capita use 

for the Tripp County Water User District was estimated based 

on present (2012) withdrawals and the number of connections served by the district (Tripp County Water User District, 

2012), with the assumption that each connection served a 

mean of three persons. Withdrawals for the East Gregory 

County Rural Water System were estimated based on an average water-use scenario for 1977 (South Dakota Department of 

Environment and Natural Resources, 2011). It was assumed 

that the per capita use did not change substantially between 

1965 and 2012, and the reported per capita use was used without adjustment for WYs 1985–2009.

The maximum per capita use for public supply was 

assumed to occur and be at that constant rate during summer 

(June to September). The minimum per capita use for public 

supply was assumed for the remaining months (table 8). Estimated withdrawals from the Ogallala aquifer for public supply 

were calculated using per capita use and the population served. 

The population served was assumed to be equal to the town’s 

population in 2000 (table 8; U.S. Census Bureau, 2002). 

The per capita use was multiplied by the estimated population served to calculate minimum and maximum withdrawal 

rates for the analysis period. The aggregate minimum and 

maximum water use for each water year represents the mean 

estimated annual withdrawal. Annual public supply use was 

estimated to be 4.38 ft3/s. Estimated water use was assumed to 

not fluctuate during the analysis period; therefore, withdrawals 

for public supply were assumed to be a constant annual rate 

for the analysis period.
28 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

YTNUOC DDOT FORT RANDALL DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.

T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLE M

YTNUOC

EXPLANATION

Production well

Irrigation wellOther production well

Extent of the Ogallala aquifer

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 13. Production wells completed in the Ogallala aquifer in the study area.
Numerical Model 29

Table 7. Estimated withdrawals from the Ogallala aquifer for 

irrigation use in the study area, water years 1985–2009.

Water year Irrigation withdrawals

Acre-feet Cubic feet per seconda

1985 629 2.6

1986 774 3.2

1987 895 3.7

1988 968 4.0

1989 2,250 9.3

1990 1,476 6.1

1991 1,113 4.6

1992 605 2.5

1993 508 2.1

1994 944 3.9

1995 774 3.2

1996 920 3.8

1997 895 3.7

1998 847 3.5

1999 823 3.4

2000 1,089 4.5

2001 1,041 4.3

2002 1,863 7.7

2003 1,234 5.1

2004 1,355 5.6

2005 1,283 5.3

2006 1,283 5.3

2007 1,283 5.3

2008 1,283 5.3

2009 1,283 5.3

Mean 1,097 4.5

a

Withdrawal rate based on a 4-month irrigation season (June–September).

Private domestic and stock wells that exist within the 

study area were not included in the analysis because the total 

withdrawals from domestic and stock wells are assumed to 

account for a small fraction of the total water budget for the 

study area. The estimated combined mean annual withdrawal 

from production wells (irrigation and public supply) was 

5.48 ft3/s.

Numerical Model

The numerical groundwater-flow model of the Ogallala 

aquifer described in this report represents WYs 1985–2009 

and was developed from the data included in the conceptual 

model. The numerical model was used for transient simulations of historical conditions and potential future scenarios. 

The model was temporally discretized into one transient 

200-year initialization stress period followed by 75 seasonal 

stress periods for simulating transient conditions for WYs 

1985–2009. The 200-year initialization period was simulated 

in order to define the starting conditions for the transient 

simulation.

Simulation Methods

This section describes the methods used to simulate 

groundwater flow in the Ogallala aquifer. The numerical 

model was developed to simulate groundwater flow, groundwater withdrawals, groundwater levels, and the interactions 

between streams and the Ogallala aquifer in Gregory and Tripp 

Counties. The simulation was completed using MODFLOW–

NWT (Niswonger and others, 2011), a newtonian formulation 

of MODFLOW–2005 (Harbaugh, 2005). MODFLOW–2005 

can be used to simulate two- and three-dimensional groundwater flow through an aquifer by means of a finite difference 

solution technique.

The study area is subdivided into a grid of discrete 

cells, and flow into and out of each model cell is calculated 

by MODFLOW–2005. The actual hydrogeologic system is 

continuous rather than discrete; therefore, groundwater-flow 

simulations are always an approximation of the actual system. 

The study area was simulated using a single-layer, uniformly 

spaced grid of 133 rows oriented east-west and 282 columns 

oriented north-south. All grid cells were 500 meters (m; 

1,640 ft) on each side (fig. 14).

A 200-year stress period was used as an initialization 

part of the simulation where the mean of aquifer stresses 

for the period were applied, and it provided the starting 

conditions for the subsequent 75 transient seasonal stress 

periods. The 200-year initialization stress period used mean 

rates of recharge, evapotranspiration, base flow, discharge 

from springs, and well withdrawals for WYs 1985–2009. 

The 200-year stress period was simulated in transient mode 

because the simulation was more stable and converged more 

quickly than one steady-state stress period. It was determined 

that 200 years was a sufficient amount of time to reproduce 

equilibrium conditions because simulated change in groundwater storage was close to zero. Time-varying values were 

used for the 75 transient seasonal stress periods and for numerical model calibration. The 200-year initialization stress period 

was calibrated to steady-state conditions, and the 75 seasonal 

stress periods were calibrated to transient conditions for each 

period. Calibration objectives for the simulation included 

(1) simulating the long-term mean potentiometric surface and 

hydraulic gradients to those of the mapped potentiometric 

surface, (2) balancing inflows and outflows for the steady-state 

part of the simulation, (3) matching trends in hydrographs and 

hydraulic heads for the 38 State observation wells at 95 percent of wells to within plus or minus (±) 25 ft of observed 

hydraulic heads, and (4) matching the trends in the base-flow 

hydrograph for the Keya Paha River.
30 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 8. Estimated per capita use and withdrawals from the Ogallala aquifer for public supply in the study area.

[TCWUD, Tripp County Water User District; EGCRWS, East Gregory County Rural Water System; --, not applicable]

City or water use district

Estimated daily per capita use 

(gallons) Estimated population served 

(U.S. Census Bureau, 2002)

Withdrawal rate,

in cubic feet per second

Minimum Maximum Minimum Maximum

Winnera 200 250 3,137 0.97 1.21

TCWUDb 205 249 -- 2.17 2.63

Gregoryc 154 174 1,342 0.32 0.36

Colomed 100 200 340 0.05 0.11

Burkee 100 200 676 0.10 0.21

Herricke 100 200 105 0.02 0.03

Bonesteele 100 200 297 0.05 0.09

EGCRWSf 275 300 -- 0.37 0.40

a

Based on present mean withdrawals (City of Winner, 2012).

b

Based on present mean withdrawals assuming three people per connection (Tripp County Water Users District, 2012).

c

Based on 2008 withdrawals (South Dakota Department of Environment and Natural Resources, 2011).

d

Based on withdrawal rates for 1965–1968 (South Dakota Department of Environment and Natural Resources, 2011).

e

Estimated based on per capita use for Colome, South Dakota.

f

Based on an average water use scenario for 1977 (South Dakota Department of Environment and Natural Resources, 2011).

Simulations were calibrated by adjusting selected parameters within user-defined constraints until simulated groundwater levels and base flow reproduced measured values. The 

calibration process was accomplished using the Parameter 

Estimation (PEST) software program (Doherty, 2010), which 

is an open source, public domain software suite that systematically adjusts model input parameters in an attempt to match 

simulated and measured values. The software is accompanied 

by supplementary open source and public domain software 

applications for calibration of groundwater models (Doherty, 

2008). In this report, parameter estimation is used to specifically describe the automated process of adjusting parameter 

values, using PEST, to match simulated and measured values 

for hydraulic head and base flow in the study area.

Definitions

This section describes terms specific to groundwater 

modeling that are used in the remainder of this report. Model 

malperformance as a result of dry cells often occurs when 

modeling unconfined aquifers (Niswonger and others, 2011). 

A dry cell is a grid cell that becomes dewatered during any 

part of the simulation (Niswonger and others, 2011). MODFLOW–2005 calculates flow between model cells on the basis 

of a conductance term. Conductance is defined as the product 

of the hydraulic conductivity and cross-sectional area of flow 

divided by the distance between cell centers (Harbaugh, 2005). 

For parts of the simulation, certain cells are designated as 

either constant specified head or time-variant specified head. 

Constant specified-head cells are cells that have a user-defined 

hydraulic head that remains constant during a stress period. 

Time-variant specified-head cells are cells that have userdefined hydraulic head that changes from the start to the end 

of a stress period.

During model calibration, hydraulic conductivity 

parameters are estimated with the use of pilot points (Doherty, 

2010). Pilot points are discrete locations distributed throughout the model domain (Doherty and Hunt, 2010) and represent 

surrogate parameters from which hydraulic property values 

are interpolated to the model grid (Doherty and others, 2010). 

Pilot points were subdivided further into multiple zones. 

Model zones are used to prevent parameters from being interpolated across zone boundaries and to represent the location 

of discrete changes in hydrogeologic properties in a model 

domain (Doherty, 2010).

Assumptions

Using MODFLOW–NWT to simulate groundwater-flow 

systems through finite-difference solution techniques implies 

many assumptions (Harbaugh, 2005). The primary assumptions that were made follow.

• Flow in the Ogallala aquifer in the study area is predominantly horizontal, and the aquifer is unconfined 

within the study area. The aquifer is therefore represented appropriately with a single model layer.

• The spatial variability in aquifer properties is adequately represented with uniform grid cells that are 

1,640 by 1,640 ft in size, and aquifer properties are 

uniform within the area of each cell. The sediments 

of the Ogallala aquifer are fluvial in origin and have a 
Numerical Model 31

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

LYMAN COUNTY AURORA COUNTY

BRULE COUNTY

TRIPP COUNTY

GREGORY COUNTY

CHARLES MIX COUNTY

DOUGLAS COUNTY

KEYA PAHA COUNTY BOYD COUNTY

YTNUOCDDOT

FORT RANDALL 

DAM

ETTELLEM

YTNUOC

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

0 50 100 150 200 250 282

0

50

100133

50

EXPLANATION

Model grid

Inactive cellActive cellSpecified-head cell

Boundary condition

No-flow boundary

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Drain cellRiver cell

Finite-difference grid with uniform cell size of 500 meters. Number is row or column number

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

Figure 14. Numerical model grid design for the study area and boundary conditions used to simulate groundwater flow in the Ogallala aquifer.
32 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

greater degree of vertical and horizontal heterogeneity 

than is represented by the current scale of the model. 

It is recognized that actual hydraulic properties at individual sites could vary widely from those represented 

in the model. A 1,640-ft grid spacing was assumed 

to be an appropriate discretization of the model to 

represent the heterogeneity of the Ogallala aquifer for 

the scale of the groundwater-flow model. Additionally, 

a 1,640-ft spacing was similar to that used by Long 

and Putnam (2010) to simulate groundwater flow in 

the High Plains aquifer in Mellette and Todd Counties 

directly to the west of the study area.

• Sources and sinks of water that have an important effect on the groundwater-flow system, such 

as streams, well withdrawals, and recharge, can be 

adequately simulated using a grid spacing of 1,640 by 

1,640 ft. Streams in the study area actually are much 

less than 1,640 ft wide, but as with assumption 2, the 

1,640-ft spacing is sufficient discretization for the scale 

of the groundwater-flow model.

• Starting conditions for the 25-year transient simulation 

can be appropriately estimated with a 200-year transient initialization stress period. The 200-year initialization stress period does not represent a steady-state 

condition. The initialization stress period represents a 

quasi-steady-state condition, and it provides adequate 

initial conditions for the transient 25-year simulation. 

The mean of aquifer stresses was applied during the 

200-year initialization stress period, and the simulated 

change in aquifer storage was close to zero. Therefore, 

this assumption seems appropriate.

• Sources and sinks of water that have an important 

effect on the groundwater-flow system were appropriately represented by three stress periods per water year. 

The stress periods represented fall/winter (October 

through February), spring (March through May), and 

summer (June through September). It is recognized 

that aquifer stresses exist at a higher degree of variability that is not represented by three stress periods 

per water year. Temporally varying stresses, such as 

well withdrawals, are smoothed and averaged compared with what may exist in reality. Although, as with 

assumptions 2 and 3, the degree of discretization used 

is appropriate for the scale of groundwater-flow model.

Model Design

MODFLOW–NWT (Niswonger and others, 2011) was 

used to simulate groundwater flow for the Ogallala aquifer in the study area. MODFLOW–NWT is a numerical, 

three-dimensional, finite-difference groundwater modeling program that uses many of the packages distributed 

with MODFLOW–2005. Additional packages used by 

MODFLOW–NWT are either modified MODFLOW–2005 

packages or new packages. The MODFLOW–NWT and 

MODFLOW–2005 packages that were incorporated into the 

model were documented in Niswonger and others (2011) and 

Harbaugh (2005), and included the Well, Drain, Evapotranspiration, River, Recharge, and Upstream Weighting (UPW) 

packages.

MODFLOW–2005 solver packages can encounter convergence problems if parts of the model domain become dewatered during a simulation. The UPW package is a new solver 

used by MODFLOW–NWT that provides a robust representation of dry cells in the model. The UPW package is useful for 

simulating flow in unconfined aquifer systems because it does 

not deactivate and subsequently reactivate dry cells during a 

simulation like MODFLOW–2005 solver packages would. 

Instead, the UPW package reduces the conductance between a 

dry cell and an adjoining cell to zero. This method keeps a dry 

cell active while not allowing water to flow out of a dry cell 

(Niswonger and others, 2011). The Well package is the only 

MODFLOW–2005 package that was modified for MODFLOW–NWT. The new Well package has the ability to reduce 

the pumping rate of a well located in a cell that is dewatered 

during a simulation. This method prevents water from being 

removed from a dewatered cell.

Grid and Boundary Conditions

The model grid consisted of one layer made up of 133 

rows oriented east-west and 282 columns oriented north-south 

(fig. 14). The western part of the model grid overlaps the 

eastern part of the model of the Ogallala and Arikaree aquifers 

in Mellette and Todd County developed by Long and Putnam 

(2010) and has similar grid spacing. The height of each cell 

was equal to the mean estimated formation thickness. The 

model includes the parts of the aquifer that have a saturated 

thickness of 10 ft or greater. The calculation of the formation 

thickness is described with more detail in the “Hydrogeologic 

Representation” section of this report.

Although the aquifer is considered unconfined in the 

study area, a requirement for MODFLOW–NWT simulations 

is that all cells are convertible between confined and unconfined conditions. Cells on the western and southern edges of 

the model domain were designated as specified-head cells (fig. 

14), which were constant specified-head cells for the 200-year 

initialization stress period and time-variant specified-head 

cells for the transient part of the simulation. Most cells that 

represent the aquifer edges were simulated as no-flow boundaries. Rivers and streams were placed in locations where the 

mean potentiometric surface intersected the land surface in 

topographically low areas of river drainages that coincided 

with perennial stream reaches (fig. 14) and were simulated 

using the River package. Locations of springs and seeps were 

assumed to be along the edge of the aquifer (fig. 14) and were 

simulated using the Drain package. Ephemeral stream drainages at the edge of the Ogallala aquifer also were simulated 

as drains. Simulation of these cells as drains allowed water 
Numerical Model 33

to flow out of the aquifer at the edge of the model where the 

groundwater flow was not approximately perpendicular to the 

aquifer edge.

Hydrogeologic Representation

The aquifer base was assumed to be the contact between 

the Ogallala aquifer and the low permeability units at the base 

of the aquifer. In the study area, these formations included the 

Pierre Shale, the White River Group, and the Arikaree Formation. The potentiometric surface and saturated thickness of the 

Ogallala aquifer were used to calculate the altitude of the base 

of the aquifer as described in the “Groundwater Flow” section 

of this report. Using the potentiometric surface (fig. 7), the 

saturated thickness of the aquifer (fig. 5) was subtracted from 

the water-table altitude (hydraulic head) to determine the base 

of the aquifer for each model cell. The formation thickness 

was then calculated by subtracting the base of the aquifer from 

the land-surface altitude within each cell.

Representation of Hydraulic Properties

Previously published values (table 3) and interpreted 

specific capacity and transmissivity data were used as general 

indicators for hydraulic conductivity; parameter estimation of 

hydraulic conductivity using PEST was used to interpret the 

final values and distributions. Values for horizontal hydraulic 

conductivity were estimated using pilot-point parameterization, described further in the “Model Calibration” section of 

this report. In contrast to subdividing the model into a subset 

of zones representing uniform hydraulic conductivity, pilotpoint parameterization allowed a smooth variation of hydraulic conductivity over the model domain.

Two separate pilot-point zones (HK1 and HK2) were 

used to simulate hydraulic conductivity in the Ogallala aquifer 

(fig. 15). Zone HK1 represented sediments west of Ponca 

Creek, and zone HK2 represented sediments east of Ponca 

Creek. Zone delineation was determined by considering 

potential structural features. Ponca Creek was assumed to be 

the approximate location of a zone boundary because of the 

potential structural effect of the location of Ponca Creek.

The Ogallala aquifer was represented with uniform storage coefficient and specific yield in the model. MODFLOW–

NWT requires specific storage for input and does not actually 

read storage coefficient. Therefore, a multiplier was assigned 

to each model cell to represent the inverse of the maximum 

saturated thickness of the cell. This value for each cell was 

multiplied by the uniform storage coefficient value to calculate 

specific storage for the model domain.

Calculated specific capacity (table S2–1) and the orientation of the potentiometric surface (fig. 7) indicated a high 

degree of heterogeneity within the aquifer. The heterogeneity 

was simulated by assuming horizontally and vertically anisotropic conditions within the aquifer. The anisotropy of the 

Ogallala aquifer was represented by directing PEST on how to 

interpolate hydraulic conductivity to the model domain based 

on the estimated values at pilot-point locations. The hydraulic 

conductivity interpolated to an individual model cell was more 

dependent on the estimated values from pilot points oriented 

in the major direction of anisotropy and less dependent on 

the values from pilot points oriented in the minor direction of 

anisotropy. The major direction and magnitude of anisotropy 

is assignable in PEST. The minor direction of anisotropy is 

oriented perpendicular to the major direction of anisotropy.

The direction and magnitude of anisotropy was determined by trial and error to improve model performance and 

is described further in the “Model Calibration” section of this 

report. Anisotropy was assumed to be different in each of the 

hydraulic conductivity zones (HK1 and HK2; fig. 15).The vertical hydraulic conductivity was assumed to be a uniform ratio 

of 10 percent of the horizontal hydraulic conductivity.

Recharge

The Recharge package (Harbaugh, 2005) was used to represent recharge to the Ogallala aquifer in the numerical model. 

Recharge to the model was estimated using the SWB method 

described in the “Water Budget Components” section of this 

report and supplement 3. One parameter (RCH1_TS) was used 

as a multiplier to optimize the SWB recharge estimates during 

the calibration process, as described in the “Model Calibration” section of this report. The mean annual recharge rate 

estimated for WYs 1985–2009 using the SWB method was 

used as the constant recharge rate for the 200-year transient 

initialization stress period. Monthly recharge rates estimated 

using the SWB method were aggregated for the 75 seasonal 

stress periods.

Discharge

Various MODFLOW–2005 packages were used to 

simulate the discharge components of evapotranspiration, 

discharge to streams, and well withdrawals. The Evapotranspiration package (Harbaugh, 2005) was designed to simulate 

evapotranspiration from the uppermost aquifer in any given 

cell where the water table is within a specified depth below the 

land surface, referred to as the extinction depth. The extinction depth was set to 10 ft in areas of woody vegetation and 

7 ft elsewhere (fig. 3; Multi-Resolution Land Characteristics 

Consortium, 2009). The evapotranspiration rate is zero at the 

extinction depth and increases linearly to a maximum rate 

when the water level is at or above the land surface. The land 

surface of each model cell was calculated as the mean landsurface altitude for the area covered by the cell, based on a 

30-m (98-ft) digital elevation model (DEM) of the study area 

(U.S. Geological Survey, 2006).

Land cover in the study area was generalized, and the 

rooting depths represent average ranges. The maximum depth 

of the root zone was based on previously published values and 

assumed to be approximately 7 to 10 ft in the study area, with 

root penetration of 10 ft attributed with trees (Canadell and 

others, 1996). Land cover for the study area was determined 

from land-use information obtained from the Multi-Resolution 
34 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

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D

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KEYA PA

H

A CO

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NTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLE M

YTNUOC

EXPLANATION

Pilot-point location

—Used for representing horizontal 

Hydraulic conductivity zones hydraulic conductivity

HK1HK2

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14 0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

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naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 15. Pilot-point zones and locations used for representing horizontal hydraulic conductivity in the Ogallala aquifer in the study area.
Numerical Model 35

Land Characteristics Consortium (2009) to differentiate 

forested areas from grassland and agricultural areas. Forested 

areas generally occurred in the eastern part of Gregory County, 

west of the Missouri River (fig. 3). For forested areas, the 

extinction depth of evapotranspiration was set to 10 ft below 

the land surface (Multi-Resolution Land Characteristics Consortium, 2009). All other regions of the model were assigned 

an extinction depth of 7 ft (fig. 3). 

The SWB program calculated the maximum potential 

evapotranspiration for each model cell, and these values were 

used in the Evapotranspiration package in which the parameter 

EVT1_TS was used as a multiplier to adjust for SWB error. 

The EVT1_TS parameter was optimized during the calibration process described in the “Model Calibration” section. The 

mean of the annual maximum potential evapotranspiration 

rates for each model cell, estimated for WYs 1985–2009 using 

the SWB method, were used as the initial MODFLOW input 

for the 200-year transient stress period simulating long-term 

mean conditions. Monthly maximum potential evapotranspiration rates estimated using the SWB method were used as 

initial values for the 75 seasonal stress periods.

The SWB program subtracts evapotranspiration from 

precipitation as a means of calculating recharge, and in 

MODLFOW-NWT, evapotranspiration is accounted for as 

a part of the water budget in the Evapotranspiration package. Evapotranspiration estimated using the SWB method is 

assumed to originate from plant roots above the water table 

in the study area, whereas evapotranspiration estimated using 

MODFLOW–NWT is evapotranspiration from plant roots that 

extend beneath the water table. Therefore, in areas where the 

water table is near the land surface, a portion of evapotranspiration may be accounted for twice. To minimize the effect of a 

double accounting of evapotranspiration, plant rooting depths 

in the SWB program were assumed to be approximately onehalf the published rooting depths.

Discharge to streams, including river leakage and flow 

from springs and seeps, was represented with two packages. 

The River package (Harbaugh, 2005) was used to simulate the 

hydraulic connection between groundwater and surface water 

by allowing streams to gain or lose water through streambed 

material based on the difference between the surrounding 

hydraulic head and stream stage. The hydraulic conductance 

of the riverbed material (riverbed conductance) controls the 

rate at which water can flow from the aquifer to the surface 

or from the surface into the aquifer. The riverbed conductance was defined by McDonald and Harbaugh (1988) as 

the hydraulic conductivity multiplied by the cross-sectional 

area of the stream reach, divided by the streambed thickness. 

Riverbed conductances were represented as parameters that 

were adjusted during model calibration (fig. 16). Model cells 

were represented by the River package for major streams and 

tributaries in six groups—(1) the Keya Paha River and minor 

tributaries (KP_RIV), (2) Cottonwood Creek (CTNWD_CR), 

(3) Buffalo Creek (BUFF_CR), (4) Lost Creek (LOST_CR), 

(5) Sand Creek (SAND_CR), and (6) Timber Creek (TIMB_

CR) (fig. 16).

The Drain package (Harbaugh, 2005) was used to 

simulate springs discharging from the Ogallala aquifer along 

the banks of Keya Paha River, Ponca Creek, and North Fork 

and South Fork Whetstone Creek, and at the northern edge 

of the aquifer. The Drain package also was used to simulate 

leakage from ephemeral stream drainages, including Shadley 

and Willow Creeks. The Drain package is similar to the River 

package because drain cells can remove water from the aquifer 

when the surrounding hydraulic head is above the altitude of 

the drain within a cell, except that water does not move from 

the drain cell to the aquifer when the surrounding hydraulic 

head is lower than the altitude of the drain cell (McDonald and 

Harbaugh, 1988). Drain conductance is defined the same as 

riverbed conductance and was determined by model calibration. Drain cells were divided into five spring groups (fig. 16) 

that include springs and seeps that discharge into (1) the Keya 

Paha River and tributaries (KEYA_SP), (2) Ponca Creek and 

tributaries (PONCA_SP), (3) Shadley Creek (SHADLEY_

CR), (4) Willow Creek (WILLOW_CR), and (5) streams at 

the northern edge of the Ogallala aquifer including North Fork 

and South Fork Whetstone Creek (DRAIN_1).

Irrigation and public supply withdrawals were simulated with the Well package (Niswonger and others, 2011) to 

withdraw water from each production well at a specified rate. 

Some cells represented withdrawal from multiple production 

wells. The total withdrawal from each production well was 

aggregated for cells with multiple production wells. Irrigation 

withdrawals are listed in table 7. Per capita use and maximum 

and minimum withdrawal rates for public supply are listed in 

table 8. All production well locations are shown in figure 13.

Model Calibration

Model calibration was completed by linking parameter 

estimation software PEST (Doherty, 2010) with MODFLOW–

NWT (Niswonger and others, 2011). PEST uses statistical 

parameter estimation techniques to estimate model parameters, such as aquifer storage properties, spring and river 

conductance, and hydraulic conductivity. PEST is a modelindependent calibration tool that applies nonlinear estimation techniques and systematically adjusts model parameters 

and compares model simulated values to observed values of 

hydraulic head and base flow. PEST attempts to minimize the 

sum of square weighted differences (residuals) between model 

simulated and observed values (Doherty, 2010); this sum is 

referred to as the objective function. Parameter sensitivities 

and confidence intervals are determined by calculating the 

derivatives of all observations with respect to all parameters. 

User-defined ranges for each adjustable parameter can be used 

to prevent PEST from estimating unrealistic parameter values 

during the calibration process.

PEST uses regularized inversion (Doherty, 2003, 2010) 

and can use pilot points for estimation of spatial hydraulic 

properties. This approach allowed a relatively large number of 

parameters to be estimated. Classical methods for estimating 
36 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

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TRIPP CO

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FORT RANDALL 

DAM

ETTELLE M

YTNUOC

1£¤8

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18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

EXPLANATION

Active cells in the Ogallala aquiferDrain cell simulating spring discharge

Spring group showing parameter name

DRAIN_1KEYA_SPPONCA_SPSHADLEY_CRWILLOW_CR

River cell simulating river leakage

River group showing parameter name

BUFF_CRCTNWD_CRKP_RIVLOST_CRSAND_CRTIMB_CR

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14 0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

Figure 16.

Model representation of discharge including river cells and drain cells for the Ogallala aquifer in the study area.
Numerical Model 37

hydraulic conductivity values and distributions within a model 

include subdividing a model area into zones of piecewise consistency where the hydraulic properties are assumed constant. 

However, recent studies have shown that interpolating values 

for a model area on the basis of a set of estimable points (pilot 

points) distributed throughout the model area can produce a 

more robust set of input parameter values and output observations (Doherty, 2003).

Pilot points were used as the method of spatial parameterization for the model inputs of hydraulic conductivity, 

representing the heterogeneity of the aquifer at a scale that 

was manageable for calibration. Hydraulic conductivity was 

optimized using PEST and assigned to pilot points distributed 

throughout the model domain rather than directly to the grid 

elements of the model (Doherty, 2003; 2010). This method 

allowed a smooth variation of hydraulic conductivity over the 

model domain. The values of hydraulic conductivity were estimated for 196 pilot-point locations distributed throughout the 

model area (fig. 15). Pilot points were spaced closest together 

in an area south of Winner that coincided with the greatest 

densities of monitoring wells and production wells. Kriging 

was used to interpolate hydraulic conductivity for each model 

cell based on the estimated hydraulic conductivity of the 

nearest pilot points. Kriging assumes the parameters vary in a 

continuous manner from one pilot-point location to the next. 

Thus, points that are near each other have a certain degree of 

spatial correlation as would be expected given the proximity, 

but values kriged at points that are widely separated are more 

independent. PEST uses semivariograms to create relations 

between neighboring pilot points. A semivariogram was 

defined by Dunlap and Spinazola (1984) as a “graph of the 

variability of the difference of the regionalization data versus 

the distance between points.” In other words, a semivariogram 

is a graph of the amount by which two points differ, plotted 

against the distance between those points. The kriging factors 

used in the parameter estimation were created based on usersupplied variograms generated with the PEST groundwater 

utility programs PPK2FAC and FAC2REAL that are explained 

in the PEST documentation (Doherty, 2008).

Model cells were separated into two distinct zones, HK1 

and HK2 (fig. 15). Zone HK1 contained 169 pilot points, and 

zone HK2 contained 27 pilot points. The defined hydraulic 

conductivity range for pilot points was between 1.0 and 180 

ft/d. The anisotropy of the Ogallala aquifer was adjusted by 

trial and error to produce the best model to measurement fit for 

measured water levels in observation wells and estimated base 

flow.

Other parameters optimized during the calibration 

process included recharge and evapotranspiration multipliers 

(RCH1_TS and EVT1_TS) and drain and riverbed conductance parameters (DRAIN_1, KEYA_SP, PONCA_SP, SHADLEY_CR, WILLOW_CR, BUFF_CR, CTNWD_CR, KP_RIV, 

LOST_CR, SAND_CR, and TIMB_CR).

Calibration Targets

The 200-year initialization stress period and 75 seasonal 

stress periods were combined and calibrated as one continuous simulation. The 200-year initialization period was visually 

calibrated to the estimated mean potentiometric surface for the 

Ogallala aquifer. Long-term water-level measurements for the 

38 State observation wells (fig. 6) that were used to estimate 

the mean potentiometric surface of the Ogallala aquifer (fig. 7) 

were considered for calibration of the transient model. Most 

of the State observation wells (tables 2 and S1–1) are south 

of Winner in the central part of Tripp County (fig. 6) where 

multiple production wells exist (fig. 13). The legal locations of 

State observation wells are listed in tables 2 and S1–1.

Estimated discharge to streams from the Ogallala aquifer, as base flow from springs, seeps, and through riverbed 

material along the Keya Paha River, also was used during 

the calibration process. The total groundwater discharge to 

the Keya Paha River between streamgages at Keyapaha and 

Wewela was determined using the PART program to estimate 

base flow as described in the “Discharge to Streams” section 

of this report. Actual calibration targets for individual spring 

and river seepage segments were unknown, although the total 

contribution of all groundwater discharge between the two 

streamgages was estimated for each stress period. Therefore, 

trial and error was used to determine the most likely calibration targets for discharge to individual streams from springs, 

seeps, and hydraulic connection. The total of the calibration 

targets for each stress period was equal to the estimated base 

flow for the Keya Paha River for that stress period. Table 9 

shows the contribution of individual streams and springs 

between streamgages at Keyapaha and Wewela for the initialization part of the simulation and the associated river or 

drain parameter. The total discharge for the Keya Paha River 

fluctuated seasonally, but it was assumed that the contribution of individual stream and spring components remained 

constant. Therefore, the contribution of individual stream and 

spring components fluctuated as a fixed percentage of the total 

discharge between the two streamgages.

Fewer estimates of base flow were used during the calibration process compared with hydraulic-head measurements. 

For this reason, simulated discharge to streams through river 

leakage and from individual springs and seeps was given more 

weight during the calibration process. Additionally, the relative area of a streambed is greater than the point location of a 

well within the model. However, the total contribution to the 

objective function from all simulated discharge was equal to 

the total contribution to the objective function from simulated 

hydraulic-head values. Discharge from springs represented 

by DRAIN_1 and PONCA_SP was not used for calibration 

because sufficient information was not available; however, the 

parameters DRAIN_1 and PONCA_SP were optimized for 

purposes of balancing the simulated water budget.
38 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 9. Estimated discharge components from the Ogallala aquifer as base flow to the Keya Paha River between streamgages at 

Keyapaha and Wewela, South Dakota, for the for the initialization stress period.

[DRN, parameter used in Drain package of numerical model; RIV, parameter used in River package of numerical model]

Component Parameter name Parameter type Discharge rate 

(cubic feet per second)

Percentage of total river 

and spring discharge

Springs

Multiple springs adjacent to the 

Keya Paha River KEYA_SP DRN 1.9 5.3

Seeps and hydraulic connection

Keya Paha River KP_RIV RIV 3.9 10.8

Willow Creek WILLOW_CR DRN 4.3 11.9

Sand Creek SAND_CR RIV 2.8 7.9

Shadley Creek SHADLEY_CR DRN 2.8 7.9

Lost Creek LOST_CR RIV 11.3 31.7

Cottonwood Creek CTNWD_CR RIV 4.9 13.8

Timber Creek TIMB_CR RIV 3.8 10.6

Total 35.7a 99.9b

a

Does not add to the annual mean discharge of 35.8 cubic feet per second due to rounding.

b

Does not add to 100 due to rounding.

Table 10. Calibrated horizontal hydraulic conductivity for pilot points used in numerical model.

[Hydraulic conductivity values are in feet per day. The locations of the pilot points and hydraulic conductivity zones are shown in figure 15]

Parameter 

group name

Number of 

pilot points Mean sensitivity Minimum parameter value

Mean 

parameter value

Maximum 

parameter value

HK1 169 0.0534 1.0 71.2 180

HK2 27 0.0512 6.4 26.1 111

Calibrated Parameter Values

Calibrated values were determined for hydraulic conductivity, riverbed and drain conductance, and recharge and 

maximum potential evapotranspiration rates based on the 

recharge and evapotranspiration multipliers (tables 10 and 11). 

Calibrated hydraulic conductivity ranged from 1.0 to 180 ft/d, 

with a mean of 71.2 ft/d for pilot points in hydraulic conductivity group HK1 and from 6.4 to 111 ft/d, with a mean 

of 26.1 ft/d for pilot points in hydraulic conductivity group 

HK2 (table 10). Hydraulic conductivity interpolated to model 

cells from pilot-point values ranged from 0.9 to 227 ft/d 

(fig. 17). Actual values interpolated to each cell were higher 

and lower than the predefined parameter limits for pilot points 

and were a result of the method used to interpolate values to 

each model cell. Riverbed and drain conductance ranged from 

2.9 × 102 to 1.3 × 104 ft2/d (table 11). High drain conductance 

was associated with drain parameter DRAIN_1, and high 

riverbed conductance was associated with river parameter 

CTNWD_CR. The calibrated recharge multiplier was 1.2, and 

the calibrated maximum potential evapotranspiration multiplier was 1.2. Fixed values for storage coefficient and specific 

yield were used. Storage coefficient was 0.004, and specific 

yield was 0.13.

For zone HK1, a horizontal anisotropy magnitude of 2 

was applied in a direction south 65 degrees east. For zone 

HK2, a horizontal anisotropy magnitude of 2 was applied in a 

direction south 60 degrees east. This anisotropy produced the 

most reasonable hydraulic conductivity distribution throughout the model domain, based on the spatial interpolation of 

pilot-point values to model cells (fig. 17). The orientation 

of the anisotropy was determined to be consistent with the 

general orientation of major streams within the study area; 

thus, it is possible that the anisotropy orientation is a result of 

structural control within the aquifer. Additionally, the general 

direction of groundwater flow in the study area likely supports 

this anisotropy orientation.

PEST calculated the 95-percent confidence intervals 

on parameters, which indicates 95-percent confidence that a 

parameter value within the confidence interval results in the 

best fit between model simulated and observed values (table 

11). Confidence intervals are an indicator of parameter uncertainty, and they rely on a linearity assumption. For parameters 

with large confidence intervals, the linearity assumption may 
Numerical Model 39

Table 11. Calibrated parameters for the numerical model.

[ft2/d, square feet per day; --, not applicable]

Parameter name Estimated parameter value 95-percent confidence intervals

Lower limit Upper limit

Vertical hydraulic conductivity (fraction of horizontal hydraulic conductivity)

VKA1_1 0.1 -- --

Specific yield (dimensionless)

SY1_1 0.13 -- --

Storage coefficient (dimensionless)

SC1_1 0.004 -- --

Vertical conductance of sediments separating ephemeral streams and springs and the Ogallala aquifer 

(ft2

/d; see figure 16 for location of stream reach)

DRAIN_1 1.30 × 104 2.59 × 103 6.50 × 104

KEYA_SP 9.69 × 102 4.48 × 102 2.09 × 103

PONCA_SP 1.16 × 104 4.61 × 10-6 2.92 × 1013

SHADLEY_CR 6.90 × 102 3.55 × 102 1.34 × 103

WILLOW_CR 3.64 × 103 2.30 × 103 5.75 × 103

Vertical conductance of sediments separating perennial streams and the Ogallala aquifer 

(ft2

/d; see figure 16 for location of stream reach)

KP_RIV 2.90 × 102 1.64 × 102 5.15 × 102

BUFF_CR 6.93 × 103 4.37 × 10-7 1.10 × 1014

CTNWD_CR 1.07 × 104 3.04 × 103 3.77 × 104

LOST_CR 1.04 × 104 4.65 × 103 2.31 × 104

SAND_CR 6.44 × 102 1.70 × 102 2.44 × 103

TIMB_CR 5.28 × 103 1.05 × 102 2.66 × 105

Recharge multiplier

RCH1_TS 1.2 1.07 1.33

Evapotranspiration multiplier

EVT1_TS 1.2 0.96 1.44

not be valid. The largest confidence intervals are associated 

with parameters BUFF_CR, PONCA_SP, CTNWD_CR, 

and TIMB_CR. Other parameters, for example RCH1_TS 

and EVT1_TS, had small confidence intervals, indicating 

a high degree of confidence in these estimates relative to 

other parameters. Parameters RCH1_TS and EVT1_TS were 

optimized to their predefined upper limit, which likely had 

an effect on the small confidence limits associated with those 

parameters.

Sensitivity Analysis

The model’s ability to estimate a parameter value during calibration is related to the sensitivity of the changes in 

the model output relative to changes in the parameter value. 

The relative composite sensitivity of a model parameter is 

a measure of the composite changes in model outputs that 

are incurred by a small change in the value of the parameter 

(Doherty, 2010). The model is most sensitive to parameters 

associated with a high relative composite sensitivity and least 

sensitive to parameters associated with a low relative composite sensitivity. PEST calculated the relative composite sensitivity for each adjustable model parameter (fig. 18). Relative 

composite sensitivities for hydraulic conductivity groups HK1 

and HK2 represent the mean relative composite sensitivity of 

all pilot points within their associated group. Model outputs 

were most sensitive to changes in the multiplier parameter 

RCH1_TS, which is associated with recharge to the model. 

Model outputs also were highly sensitive to changes in the 

evapotranspiration multiplier EVT1_TS and drain conductance parameter DRAIN_1. The model was least sensitive to 

drain and riverbed conductance parameters PONCA_SP and 

BUFF_CR.
40 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLE M

YTNUOC

EXPLANATION

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Horizontal hydraulic conductivity, in feet per day

0.9 to 20Greater than 20 to 40Greater than 40 to 60Greater than 60 to 80Greater than 80 to 100Greater than 100 to 120

Greater than 120 to 140Greater than 140 to 160Greater than 160 to 180Greater than 180 to 200Greater than 200 to 220Greater than 220 to 227

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 17. Calibrated horizontal hydraulic conductivity of the Ogallala aquifer in the study area.
Numerical Model 41

Parameter

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

DRAIN_1

KEYA_SP

PONCA_SP

SHADLEY_CR

WILLOW_CR

BUFF_CR

CTNWD_CR

KP_RIV

EVT1_TS

LOST_CR

SAND_CR

TIMB_CR

HK1HK2

RCH1_TS

Relative composite sensitivity

Figure 18. Relative composite parameter sensitivities, as defined by Doherty (2010), for the numerical model.

Simulation of Groundwater Flow

The numerical model was used to simulate transient 

conditions for the 25-year period (WYs 1985–2009) previously described. The calibration objective for the 200-year 

initialization period was to simulate the observed potentiometric surface and balance inflows and outflows for the aquifer. 

The calibration objective for the 25-year transient part of the 

simulation was to reproduce long-term water-level measurements for 38 State observation wells and estimated base flow 

for the Keya Paha River.

Initialization Period

The primary objective of model calibration was to minimize the objective function. A secondary objective of model 

calibration was that the simulated potentiometric surface and 

hydraulic gradients for the initialization period generally 

match those of the observed mean potentiometric surface. The 

simulated potentiometric surface from the 200-year initialization period (fig. 19) generally was similar to the observed 

potentiometric surface (fig. 7) based on hydraulic heads and 

gradients, indicating a satisfaction of this objective. For all 

active model cells, the simulated potentiometric surface was 

within ±35 ft of the observed potentiometric surface for 96 

percent of all active model cells (fig. 20). The difference 

between the observed and simulated potentiometric surfaces 

ranged from +85 to -72 ft. Generally, the maximum differences between the observed and simulated potentiometric surfaces were associated with areas near the edge of the model. 

The simulated potentiometric surface generally had lower 

hydraulic heads than did the observed potentiometric surface, 

which is indicated by the mean difference of +3.3 ft (observed 

minus simulated hydraulic heads) for all model cells. The 

standard deviation of differences between the observed and 

simulated potentiometric surfaces for all cells was 15.3 ft, and 

the variance was 236 square feet (ft2

). The standard deviation 

and variance (Helsel and Hirsch, 1992) are used as general 

indicators of the accuracy of the model to measurement fit.

The numerical solution for the water budget for the initialization part of the simulation was balanced (inflows minus 

outflows) with a percentage discrepancy of 0.00 (table 12). 

Simulated recharge was 18 percent greater than the recharge 

estimated using the SWB method for the initialization period. 

This represents a total simulated recharge rate of 281.2 ft3/s 

for the initialization period. Model-calculated maximum 

potential evapotranspiration was 20 percent greater than the 

SWB-estimated maximum potential evapotranspiration for this 

period. As a result of the maximum potential evapotranspiration multiplier, the total evapotranspiration rate was 225.6 ft3

/s 

for the initialization period. The simulated river leakage from 

the aquifer to the Keya Paha River of 30.5 ft3/s calculated by 

the numerical model for the initialization period was within 

6.0 ft3/s of estimated base flow for the conceptual model.

Transient Simulation

The primary calibration objective was to minimize the 

objective function. The first objective as a part of the calibration process was to minimize the difference between simulated 

transient water-level altitudes (hydraulic heads) and observed 

hydraulic heads for the 38 State observation wells for WYs 

1985–2009. The model was calibrated to 6,191 water-level 

measurements for the 38 State observation wells so that 
42 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota EXPLANATION Simulated potentiometric contour—Shows mean altitude at which water level would have stood in tightly cased wells, water years 1985–2009, in feet above National Geodetic Vertical Datum of 1929. Contour interval 50 feet Active model cells for the Ogallala aquifer Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985 Universal Transverse Mercator projection, zone 14

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

6, 1 05

050, 2

0, 2 00

2,000

1 8, 00

2 2, 00

2 2, 50

1,850

1,850

2,150

, 1 57 0

1,950

2 1, 00

09, 1 0

2,000

2,350

7, 1 00

2 1, 50

1,950

2,100

2 1, 00

009, 1

2,150

2 1, 50

003, 2

2 0, 50

057, 1

2 0, 50

2 2, 50

2 2, 50

2,250

2 2, 50

2,300

2 0, 00

1,750

2,350

050, 2

2,050

2,100

2 1, 50

2,250

2,200

2 1, 50

2 1, 50

2 3, 50

052, 2

2,050

059, 1

002, 2

2 0, 00

2,250

2,300

, 2 51 0

2 3, 50

2,150

052

0, 2 ,150

2 0, 00

2,400

008, 1

2 5, 00 2,150

2,200

2,250

2 3, 50

2,300

2 2, 00

2 3, 50

2,300

2200

2,300

2,100

2 0, 50

2,100

054, 2

2 1, 00

2,350

2,150

2400

2,200

2 4, 50

2,250

2,400

2,150

2 3, 00

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

2,000

ETTELLE M

YTNUOC

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 19. Simulated long-term mean potentiometric surface in the Ogallala aquifer in the study area.
Numerical Model 43

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Cottonwood Creek

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

YTNUOCDDOT

LYMAN COUNTY

AURORA COUNTY

BRULE COUNTY

TRIPP COUNTY

GREGORY COUNTY

CHARLES MIX COUNTY

DOUGLAS COUNTY

KEYA PAHA COUNTY BOYD COUNTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLEM

YTNUOC

EXPLANATION

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Difference in the observed and simulated

potentiometric surface, in feet

-72 to -60Greater than -60 to -45Greater than -45 to -30Greater than -30 to -15Greater than -15 to 0

Greater than 0 to 15Greater than 15 to 30Greater than 30 to 45Greater than 45 to 60Greater than 60 to 75Greater than 75 to 85

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Dog Ear Creek

Figure 20. Difference between the observed and simulated potentiometric surfaces in the study area.
44 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 12. Water budget for the numerical model simulating 

long-term mean conditions compared with flow estimates from 

the conceptual model.

[ft3/s, cubic feet per second; --, not estimated or not applicable]

Flow component

Flow rate

(ft3

/s)

Numerical 

model

Conceptual 

model

Inflows

Storage 0.0016 --

Constant-head boundaries 18.6 --

River leakage 0.7 --

Recharge 281.2 239

Total inflows 300.5 --

Outflows

Storage 0.0016 --

Constant-head boundaries 7.0 --

Well withdrawals 5.5 5.48

Springs along Ponca Creek 8.3 3.85

Other springs and seeps 19.5 --

Keya Paha Rivera 30.5 35.8

Other river leakage 4.1 --

Evapotranspiration 225.6 --

Total outflows 300.5 --

Inflows minus outflows 0.00 --

Percent discrepancy 0.00 --

a

Discharge between streamgages 06464100 (Keya Paha River near 

Keyapaha) and 06464500 (Keya Paha River at Wewela). Includes springflow along river banks.

mean simulated hydraulic heads for 95 percent of wells were 

within ±20 ft of the observed hydraulic heads. This calibration criterion was met by calibrating the model using PEST as 

described in the “Model Calibration” section of this report.

Basic statistics were calculated for comparison of 

observed and simulated hydraulic heads for State observation 

wells (table 13). Comparisons of the mean, standard deviation, 

and variance for observed and simulated hydraulic heads were 

used as general indicators of the accuracy of model to measurement fit. Mean simulated water levels matched observed 

values within ±20 ft for 95 percent and to within ±10 ft for 

84 percent of State observation wells, with a mean difference 

of -1.6 ft (observed minus simulated) and a mean absolute 

difference of 5.1 ft. For the State observation wells, mean 

differences between observed and simulated hydraulic heads 

were within 22 ft. Large discrepancies between observed and 

simulated hydraulic heads generally were associated with 

observation wells near specified-head boundaries or where 

observation wells were near production wells that were closely 

spaced (fig. 21). The model overestimated mean hydraulic 

heads for 21 of the State observation wells and underestimated 

mean hydraulic heads for 15 of the State observation wells. 

The mean of the difference between observed and simulated 

means was -1.6 ft (table 13).

A histogram shows the distribution of the difference 

between the observed and simulated hydraulic heads (residuals) for all 6,191 measurements from the State observation 

wells (fig. 22). Simulated hydraulic heads ranged from +41.6 

to -50.0 ft of observed hydraulic heads. Hydrographs for State 

observation wells for the 25-year transient part of the simulation are shown in figure 23, which shows that the general 

trends in simulated and observed hydraulic heads matched 

reasonably well. Analysis of the data indicates a model bias of 

overestimating hydraulic heads. For all water-level measurements for State observation wells, the model overestimated 

56.5 percent of hydraulic heads and underestimated 43.5 percent of hydraulic heads. A linear regression analysis between 

simulated and observed hydraulic heads for State observation 

wells yielded an R2

 value (coefficient of determination; fraction of the variance explained by regression) of 1.00 (fig. 24).

The second objective as a part of the calibration process 

was to minimize the difference between model-simulated base 

flow and PART-estimated base flow. Base flow is sensitive to 

many model components besides riverbed conductance. The 

simulated base flow from groundwater discharge had less 

seasonal variability between stress periods than the base flow 

(fig. 25) estimated using PART as described in the “Discharge 

to Streams” section of this report. In general, base flow was 

overestimated by the model and within 42 percent of the mean 

estimated values for the Keya Paha River (fig. 25; table 14). 

This discrepancy could represent limitations in estimates of 

base flow, the ability of the model to simulate base flow, or 

both. Simulated base flow for the Keya Paha River ranged 

from 25.5 to 39.0 ft3

/s.

Simulated rates of recharge for the transient stress 

periods, applying the calibrated recharge multiplier, ranged 

from 0.60 to 6.96 in/yr, with a mean of 3.68 in/yr for the 

Ogallala aquifer. This represents a mean total recharge rate 

of 280.5 ft3/s for the numerical model. Transient simulated 

annual evapotranspiration rates, applying the calibrated 

evapotranspiration multiplier, ranged from 128.1 to 253.6 ft3

/s, 

with a mean annual evapotranspiration rate of about 185 ft3

/s. 

Simulated net discharge rate to streams through river leakage 

and flow from springs and seeps ranged from 52.2 to 79.9 ft3

/s, 

with a mean annual rate of 66.7 ft3

/s. Reported irrigation well 

withdrawals (table 7) and estimated public supply withdrawals 

(table 8) were used in the numerical model and had a combined annual rate of 5.48 ft3

/s. 

Simulation of Future Scenarios

Using the input parameters determined during model calibration, simulations were conducted to estimate groundwater 

responses to hypothetical potential future scenarios of drought 

and increases in well withdrawals. A synthetic drought record 

was created that used the spatial and temporal variations in 
Numerical Model 45

Table 13. Comparison of observed and simulated hydraulic heads for State observation wells for the transient simulation.

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not applicable]

State observation well 

(index number 

on figure 21)

Data type

Mean 

hydraulic 

head 

(feet above 

NGVD 29)

Standard 

deviation 

(feet)

Variance 

(feet 

squared)

Range 

(feet)

Minimum 

hydraulic 

head 

(feet above 

NGVD 29)

Maximum 

hydraulic 

head 

(feet above 

NGVD 29)

Difference between observed 

and simulated 

means 

(feet)

Mean of 

absolute 

values of 

residuals 

(feet)

GY–57A (74) Observed 2,138.5 3.38 11.40 16.8 2,127.2 2,144.0

Simulated 2,137.2 1.14 1.30 4.8 2,134.7 2,139.5 1.3 2.6

GY–57B (68) Observed 2,080.0 1.54 2.38 6.3 2,077.6 2,083.9

Simulated 2,081.1 1.05 1.10 4.3 2,078.9 2,083.2 -1.2 1.4

GY–77A (126) Observed 2,145.2 1.01 1.03 4.8 2,142.8 2,147.6

Simulated 2,140.8 0.72 0.52 3.3 2,139.2 2,142.5 4.5 4.5

GY–77B (132) Observed 2,152.9 1.69 2.84 7.8 2,150.0 2,157.8

Simulated 2,151.4 1.30 1.69 5.2 2,148.8 2,154.0 1.5 1.7

GY–78A (71) Observed 2,112.9 1.70 2.88 7.4 2,108.3 2,115.7

Simulated 2,113.1 1.19 1.43 4.9 2,110.7 2,115.6 -0.1 1.0

GY–78B (22) Observed 2,182.7 2.56 6.58 8.7 2,178.5 2,187.2

Simulated 2,182.8 1.73 3.00 7.4 2,178.8 2,186.3 0.0 1.7

GY–78C (13) Observed 1,897.7 3.52 12.42 12.5 1,892.8 1,905.3

Simulated 1,899.8 1.02 1.05 4.1 1,897.7 1,901.8 -2.1 3.1

GY–78D (18) Observed 1,909.7 2.24 5.00 8.2 1,906.6 1,914.8

Simulated 1,910.6 0.98 0.96 4.0 1,908.6 1,912.6 -0.9 1.6

TR–57C (29) Observed 1,963.1 0.75 0.56 3.4 1,961.8 1,965.2

Simulated 1,985.4 1.58 2.48 6.6 1,982.9 1,989.5 -22.3 22.3

TR–59B (48) Observed 2,342.3 1.57 2.46 6.6 2,339.9 2,346.5

Simulated 2,346.5 1.57 2.47 6.6 2,343.7 2,350.2 -4.3 4.3

TR–72A (233) Observed 2,169.7 4.59 21.11 18.4 2,163.6 2,182.0

Simulated 2,186.6 0.94 0.88 4.7 2,183.5 2,188.2 -17.0 17.0

TR–72B (234) Observed 2,171.8 0.94 0.88 3.7 2,170.4 2,174.1

Simulated 2,181.6 0.51 0.26 2.2 2,180.4 2,182.7 -9.8 9.8

TR–72C (235) Observed 2,216.4 2.32 5.39 11.5 2,211.9 2,223.4

Simulated 2,212.6 2.13 4.55 8.8 2,208.1 2,216.8 3.8 4.0

TR–72D (243) Observed 2,221.8 2.40 5.78 11.5 2,215.4 2,226.9

Simulated 2,224.7 2.01 4.02 8.3 2,220.7 2,229.0 -3.0 3.1

TR–72E (159) Observed 2,257.3 1.91 3.64 9.8 2,252.7 2,262.5

Simulated 2,260.3 1.61 2.58 6.9 2,257.0 2,263.9 -3.0 3.0

TR–72F (237) Observed 2,238.3 6.20 38.43 22.3 2,227.7 2,250.0

Simulated 2,242.2 1.65 2.71 7.1 2,239.0 2,246.1 -3.8 4.9

TR–72G (238) Observed 2,231.2 17.86 318.85 50.7 2,201.6 2,252.3

Simulated 2,236.0 2.53 6.41 10.6 2,231.0 2,241.6 -4.8 13.9

TR–72H (239) Observed 2,225.3 10.03 100.63 35.9 2,202.6 2,238.5

Simulated 2,242.7 1.46 2.13 6.3 2,239.8 2,246.2 -17.3 17.3

TR–74A (236) Observed 2,248.8 2.72 7.41 12.5 2,242.3 2,254.8

Simulated 2,242.7 2.42 5.87 10.1 2,237.8 2,247.9 6.1 6.1

TR–74D (242) Observed 2,258.2 1.80 3.22 9.4 2,253.4 2,262.8

Simulated 2,255.2 1.66 2.76 7.2 2,251.6 2,258.8 3.0 3.0
46 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table 13. Comparison of observed and simulated hydraulic heads for State observation wells for the transient simulation.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not applicable]

State observation well 

(index number 

on figure 21)

Data type

Mean 

hydraulic 

head 

(feet above 

NGVD 29)

Standard 

deviation 

(feet)

Variance 

(feet 

squared)

Range 

(feet)

Minimum 

hydraulic 

head 

(feet above 

NGVD 29)

Maximum 

hydraulic 

head 

(feet above 

NGVD 29)

Difference between observed 

and simulated 

means 

(feet)

Mean of 

absolute 

values of 

residuals 

(feet)

TR–74E (241) Observed 2,253.4 1.75 3.06 7.9 2,250.0 2,257.9

Simulated 2,254.0 1.73 3.00 7.4 2,250.4 2,257.8 -0.5 1.0

TR–74F (240) Observed 2,257.1 1.82 3.31 8.4 2,253.7 2,262.1

Simulated 2,251.5 1.95 3.80 8.1 2,247.7 2,255.8 5.6 5.6

TR–75B (244) Observed 2,223.3 2.06 4.25 8.6 2,218.8 2,227.4

Simulated 2,219.0 1.72 2.95 7.8 2,215.5 2,223.3 4.3 4.3

TR–78A (169) Observed 2,323.1 2.18 4.73 6.7 2,320.4 2,327.1

Simulated 2,324.6 2.47 6.10 9.8 2,319.5 2,329.4 -1.6 2.7

TR–78B (181) Observed 2,342.8 2.00 4.01 7.6 2,338.8 2,346.4

Simulated 2,341.4 1.76 3.08 6.9 2,337.9 2,344.8 1.3 2.1

TR–78C (209) Observed 2,335.7 1.59 2.53 6.2 2,333.0 2,339.2

Simulated 2,336.1 2.01 4.05 9.3 2,332.2 2,341.5 -0.4 1.2

TR–78D (249) Observed 2,416.7 1.63 2.66 6.5 2,414.0 2,420.5

Simulated 2,416.7 1.59 2.52 6.4 2,413.5 2,419.9 0.0 1.6

TR–78E (51) Observed 2,388.3 1.82 3.33 8.0 2,384.2 2,392.2

Simulated 2,392.3 2.54 6.43 10.6 2,387.1 2,397.7 -4.0 4.0

TR–78F (35) Observed 2,222.4 1.47 2.16 5.5 2,219.6 2,225.1

Simulated 2,222.2 1.45 2.09 6.1 2,219.1 2,225.2 0.3 0.8

TR–78G (157) Observed 2,323.3 2.16 4.65 9.1 2,319.0 2,328.1

Simulated 2,323.0 2.07 4.28 8.2 2,319.3 2,327.4 0.3 1.1

TR–78H (167) Observed 2,327.4 1.52 2.30 6.5 2,324.4 2,330.9

Simulated 2,329.2 1.72 2.94 8.2 2,325.8 2,334.0 -1.8 1.9

TR–78I (188) Observed 2,355.8 2.33 5.44 9.5 2,351.8 2,361.3

Simulated 2,354.6 1.42 2.02 6.7 2,351.3 2,358.1 1.1 1.3

TR–78J (97) Observed 2,305.5 1.42 2.02 6.9 2,302.6 2,309.5

Simulated 2,304.7 1.61 2.59 7.4 2,301.9 2,309.3 0.8 1.2

TR–78K (87) Observed 2,290.3 2.93 8.60 12.3 2,285.5 2,297.8

Simulated 2,294.2 0.79 0.62 3.4 2,292.6 2,295.9 -3.9 4.0

TR–78L (100) Observed 2,235.7 3.39 11.49 13.3 2,229.3 2,242.6

Simulated 2,237.0 1.28 1.64 5.6 2,234.7 2,240.3 -1.4 2.5

TR–78M (43) Observed 2,244.9 5.65 31.97 35.5 2,215.1 2,250.6

Simulated 2,256.1 1.69 2.85 6.9 2,252.7 2,259.6 -11.2 11.2

TR–78N (36) Observed 2,337.8 2.15 4.60 9.9 2,332.4 2,342.3

Simulated 2,319.9 17.18 295.11 55.9 2,284.6 2,340.5 17.9 18.7

TR–79A (83) Observed 2,334.8 2.98 8.90 11.8 2,330.0 2,341.8

Simulated 2,334.3 1.49 2.22 6.5 2,331.4 2,337.8 0.5 1.5

Mean -- -- -- -- -- -- -- -1.6 5.1
Numerical Model 47

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

48

36

29

51 43

35 22

13

18

68

100

83 74

97 87 71

209

181 188 132

126

169

157

167

249 235 239

237

236

238

243

244

15

2

9

42

241 240

233

234

YTNUOCDDOT

LYMAN

COUNTY

AURORA

COUNTY

BRULE

COUNTY

TRIPP

COUNTY

GREGORY

COUNTY

CHARLES

MIX COUNTY

DOUGLAS

COUNTY

KEYA PAHA COUNTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.

T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

68

74

4329

236

36

ETTELLEM

YTNUOC

EXPLANATION

Mean residual between observed and simulated

hydraulic heads for State observation wells, in feet(table 13)—Number is index number from table 2

-22.3 to -15.0Greater than -15.0 to -5.0Greater than -5.0 to 0

Greater than 0 to 5.0Greater than 5.0 to 15.0Greater than 15.0 to 18.0

Active cells in the Ogallala aquifer

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood Creek

Dog Ear Creek

Figure 21. Mean residuals between observed and simulated hydraulic heads for State observation wells completed in the Ogallala aquifer in the study area, water years 1985–2009.
48 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

0

5

10

15

20

25

30

35

40

45

50

55

60

-45-5 -39 -33 -27 -21 -15 -9 -3 3 9 15 21 27 33 39 45

Frequency, in percent

Residual, in feet

Figure 22. Histogram of residuals of observed and simulated hydraulic head in State observation wells for the Ogallala aquifer in the 

study area, water years 1985–2009.

recharge calculated using the SWB method (table 4), except 

that the synthetic record represented the 30th-percentile 

recharge rates for each model season of the original record. 

This resulted in a mean recharge for the drought simulation 

of 1.89 in/yr, or 60 percent of the original estimated mean 

recharge rate of 3.14 in/yr. The simulation was executed with 

a 200-year initialization period using the same recharge rates 

as the calibration simulation, followed by 75 seasonal stress 

periods representing 25 years of potential drought conditions. 

Hydrographs of the hydraulic heads simulated by the calibrated model (non-drought simulation) plotted in relation to 

hydraulic heads simulated using the drought scenario show the 

effects of this drought scenario for selected State observation 

wells (fig. 26). The simulated maximum decrease in water levels of the 38 State observations wells as a result of the drought 

simulation ranged from 2.28 to 26.2 ft, and about 50 percent 

of the wells had decreases of less than 10.6 ft.

The differences in hydraulic head for the study area for 

the drought scenario compared with the non-drought simulation ranged from 0 to 30 ft, with a mean of 6.05 ft for the 

Ogallala aquifer (fig. 27). Generally, the largest differences 

were in the central and southern parts of Tripp County where 

groundwater withdrawals from wells are greatest.

To assess the effects of potential increases in pumping, 

well withdrawal rates for production wells were increased by 

50 percent from those that were used during the calibrated 

simulation (tables 7 and 8). The potential effects of pumping 

were simulated using the same 200-year initialization period 

followed by 75 seasonal stress periods representing 25 years 

of increased pumping. The simulated maximum decrease in 

water levels for the 38 State observation wells ranged from 

0.02 to 25.0 ft, and about 50 percent of observation wells had 

a maximum difference of 0.6 ft. The decreases in hydraulic 

heads in the study area between the results of the calibrated 

model and the scenario of increased pumping at the end of the 

25-year simulation ranged from 0 to 26 ft, with a mean difference of 0.14 ft for the Ogallala aquifer (fig. 28). Generally, the 

greatest differences in simulated hydraulic heads between the 

calibrated model and the increased pumping scenario were in 

the central and southern parts of Tripp County and southeast 

of the town of Gregory where the current (2009) groundwater 

withdrawals from wells are greatest.

Comparison of Simulated Groundwater Budgets

For the long-term initialization period, the aquifer 

received about 92 percent of its simulated inflow as recharge 

from precipitation, less than 1 percent from river leakage, and 

about 8 percent as lateral flow through specified-head cells 

on the western and southern model boundaries (table 15). 

For the initialization period, about 75 percent of simulated 

outflow was from evapotranspiration, 12 percent was discharged through springs and seeps, 9 percent was discharged 

to streams through riverbed material, 2 percent was removed 

through well withdrawals, and 2 percent of water exited the 

model through specified-head boundaries. The simulated 

change in storage for the initialization period was zero.

The transient distribution of evapotranspiration and 

recharge from precipitation for WYs 1985–2009 altered 

the water budget components from the initialization period. 

Simulated recharge from precipitation accounted for about 

94 percent of inflows for the aquifer, lateral flow through 

specified-head boundaries accounted for 6 percent of inflows, 

and recharge from river leakage accounted for less than 

1 percent. Simulated outflow from the aquifer was through 

evapotranspiration (70 percent), river leakage (11 percent), 

spring and seepage discharge (15 percent), well withdrawals 

(2 percent), and lateral outflow through specified-head boundaries (3 percent).

As expected, the simulation representing a potential 

drought scenario showed much less water entering the aquifer 

as recharge from precipitation (84 percent). Simulated river 

leakage accounted for 1 percent of inflow to the aquifer, and 

lateral inflow through specified-head boundaries accounted for 

15 percent of inflows. The potential drought scenario simulation had much less water leaving the aquifer though evapotranspiration (65 percent), river leakage (12 percent), and 
Numerical Model 49

Observed Simulated

2,125

2,130

2,135

2,140

2,145

2,150 GY–57A (74) 

2,136

2,138

2,140

2,142

2,144

2,146

2,148

2,150 GY–77A (126)

2,146

2,148

2,150

2,152

2,154

2,156

2,158

2,160 GY–77B (132) 

2,106

2,108

2,110

2,112

2,114

2,116

2,118 GY–78A (71) 

1,892

1,894

1,896

1,898

1,900

1,902

1,904

1,906

1984 1992 2000 2008

GY–78C (13)

2,076

2,078

2,080

2,082

2,084

2,086 GY–57B (68) 

2,176

2,178

2,180

2,182

2,184

2,186

2,188 GY–78B (22)

1,904

1,906

1,908

1,910

1,912

1,914

1,916

1984 1992 2000 2008

Calendar year 

GY–78D (18)

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

Figure 23. Observed and simulated hydraulic heads for State observation wells completed in the 

Ogallala aquifer in the study area. The numbers in parentheses are the index number for the well as 

shown on figure 21. The State observation wells are listed in table 2.
50 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Observed Simulated

1984 1992 2000 2008

Calendar year 

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

2,220

2,225

2,230

2,235

2,240

2,245

2,250

2,255

2,260

1984 1992 2000 2008

TR-72F (237)

2,338

2,340

2,342

2,344

2,346

2,348

2,350

2,352 TR–59B (48)

2,160

2,165

2,170

2,175

2,180

2,185

2,190

2,195 TR–72A (233)

2,165

2,170

2,175

2,180

2,185 TR–72B (234) 

2,200

2,205

2,210

2,215

2,220

2,225 TR–72C (235) 

2,210

2,215

2,220

2,225

2,230

2,235 TR–72D (243) 

2,252

2,254

2,256

2,258

2,260

2,262

2,264

2,266 TR–72E (159)

1,960

1,965

1,970

1,975

1,980

1,985

1,990 TR– 57C (29)

Figure 23. Observed and simulated hydraulic heads for State observation wells completed in the 

Ogallala aquifer in the study area. The numbers in parentheses are the index number for the well as 

shown on figure 21. The State observation wells are listed in table 2.—Continued
Numerical Model 51

Observed Simulated

1984 1992 2000 2008 1984 1992 2000 2008

Calendar year 

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

2,235

2,240

2,245

2,250

2,255

2,260 TR–74A (236)

2,245

2,250

2,255

2,260

2,265 TR–74D (242)

2,240

2,245

2,250

2,255

2,260

2,265 TR–74F (240)

2,210

2,215

2,220

2,225

2,230 TR–75B (244) 

2,315

2,320

2,325

2,330

2,335 TR–78A (169)

2,190

2,200

2,210

2,220

2,230

2,240

2,250

2,260 TR–72G (238)

2,246

2,248

2,250

2,252

2,254

2,256

2,258

2,260

2,262 TR–74E (241)

2,200

2,210

2,220

2,230

2,240

2,250

2,260 TR–72H (239)

Figure 23. Observed and simulated hydraulic heads for State observation wells completed in the 

Ogallala aquifer in the study area. The numbers in parentheses are the index number for the well as 

shown on figure 21. The State observation wells are listed in table 2.—Continued
52 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Observed Simulated

1984 1992 2000 2008 1984 1992 2000 2008

Calendar year 

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

2,325

2,330

2,335

2,340

2,345

2,350 TR–78B (181)

2,330

2,332

2,334

2,336

2,338

2,340

2,342

2,344 TR–78C (209)

2,405

2,410

2,415

2,420

2,425 TR–78D (249)

2,384

2,386

2,388

2,390

2,392

2,394

2,396

2,398

2,400 TR–78E (51) 

2,216

2,218

2,220

2,222

2,224

2,226 TR–78F (35)

2,314

2,316

2,318

2,320

2,322

2,324

2,326

2,328

2,330 TR–78G (157)

2,322

2,324

2,326

2,328

2,330

2,332

2,334

2,336 TR–78H (167)

2,350

2,352

2,354

2,356

2,358

2,360

2,362

2,364 TR–78I (188)

Figure 23. Observed and simulated hydraulic heads for State observation wells completed in the 

Ogallala aquifer in the study area. The numbers in parentheses are the index number for the well as 

shown on figure 21. The State observation wells are listed in table 2.—Continued
Numerical Model 53

Observed Simulated

1984 1992 2000 2008 1984 1992 2000 2008

Calendar year 

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

2,300

2,302

2,304

2,306

2,308

2,310

2,312 TR–78J (97) 

2,284

2,286

2,288

2,290

2,292

2,294

2,296

2,298

2,300 TR–78K (87) 

2,225

2,230

2,235

2,240

2,245

2,250

2,255 TR–78L (100)

2,210

2,220

2,230

2,240

2,250

2,260

2,270 TR–78M (43) 

2,280

2,290

2,300

2,310

2,320

2,330

2,340

2,350 TR–78N (36) 

2,324

2,328

2,332

2,336

2,340

2,344 TR–79A (83) 

Figure 23. Observed and simulated hydraulic heads for State observation wells completed in the 

Ogallala aquifer in the study area. The numbers in parentheses are the index number for the well as 

shown on figure 21. The State observation wells are listed in table 2.—Continued
54 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Coefficient of determination (R2) = 1.00

1,800

1,900

2,000

2,100

2,200

2,300

2,400

2,500

1,800 1,900 2,000 2,100 2,200 2,300 2,400 2,500

Simulated hydraulic head, in feet above

National Geodetic Vertical Datum of 1929

Observed hydraulic head, in feet above National Geodetic Vertical Datum of 1929

Figure 24. Linear regression of observed and simulated hydraulic heads for State observation wells in the Ogallala 

aquifer in the study area.

0

10

20

30

40

50

60

70

80

90

100

1984 1988 1992 1996 2000 2004 2008

Calendar year 

Simulated

Estimated using PART

 program (Rutledge, 1998)

EXPLANATION

River gain, in cubic feet per second 

Figure 25. Estimated and simulated base flow from groundwater discharge from the Ogallala aquifer in the study area 

for the Keya Paha River.
Numerical Model 55

Table 14. Comparison of estimated to simulated base flow for 

the Keya Paha River for the transient simulation.

[ft3/s, cubic feet per second]

Water year

Base flowa

(ft3

/s)

Estimatedb Simulated

1985 18.7 28.2

1986 27.1 36.2

1987 44.0 37.1

1988 36.3 39.0

1989 18.2 31.6

1990 22.8 30.5

1991 13.3 30.8

1992 25.7 30.2

1993 22.1 30.3

1994 47.9 27.3

1995 34.9 35.5

1996 90.9 36.6

1997 81.6 37.9

1998 44.1 37.8

1999 84.6 37.1

2000 33.0 29.4

2001 24.9 33.0

2002 38.3 30.6

2003 26.7 27.5

2004 15.9 25.5

2005 23.7 28.8

2006 20.0 25.5

2007 43.7 30.8

2008 25.0 34.9

2009 31.3 34.8

Mean 35.8 32.3

a

Discharge between streamgages 06464100 (Keya Paha River near 

Keyapaha) and 06464500 (Keya Paha River at Wewela). Includes springflow and seeps along river banks.

b

Base flow estimated by using the PART program (Rutledge, 1998) for 

the conceptual model.

discharge through springs and seeps (16 percent). Simulated 

discharge from the Ogallala aquifer through river leakage, 

springs, and seeps for the drought scenario accounted for a 

larger portion of the water budget when compared with the 

simulation representing WYs 1985–2009, although the amount 

of water being discharged was less in comparison (table 15). 

The decrease in discharge from river leakage, springs, and 

seeps as well as the decrease in simulated evapotranspiration 

for the drought scenario likely is due to substantial decreases 

in the potentiometric surface (fig. 27) for the simulation 

period. Well withdrawals accounted for 3 percent of simulated 

outflow, and leakage through specified-head boundaries 

accounted for 3 percent of simulated outflow.

The simulated groundwater budget representing a 

potential increased pumping scenario was similar to the 

groundwater budget for WYs 1985–2009, although well withdrawals accounted for a slightly larger portion of simulated 

outflow (3 percent), and river leakage and evapotranspiration 

accounted for a slightly smaller portion of simulated outflow 

(10 and 69 percent, respectively) for the increased pumping scenario. Simulated discharge from springs and seeps 

decreased slightly from 39.0 to 38.7 ft3

/s but still accounted 

for 15 percent of total simulated outflow. Simulated inflow 

for the potential increased pumping scenario was the same 

as WYs 1985–2009. Simulated outflow from river leakage, 

spring and seepage discharge, and lateral flow through specified-head boundaries was the same for both budget periods. 

The decrease in evapotranspiration for the potential increased 

pumping scenario is likely due the water-level decreases near 

pumping wells. The amount of simulated discharge from river 

leakage did not decrease as a result of a 50-percent increase in 

withdrawals from existing production wells.

Model Limitations

The numerical model adequately simulated flow in the 

Ogallala aquifer in the study area for transient and potential future conditions. However, as with any conceptual or 

numerical model, certain limitations should be considered. 

These include uncertainties in many of the numerical model 

input parameters, most importantly recharge, evapotranspiration, and horizontal hydraulic conductivity. These parameters 

greatly affected model results, and extensive parameter data 

were not available. Therefore, these parameters were estimated 

or calculated with the data that were available. Recharge was 

calculated by subtracting evapotranspiration from precipitation using the SWB method, which included assumptions and 

limitations inherent to the SWB method.

Driller’s completion reports and lithologic logs were used 

to determine hydrogeologic properties such as the base of the 

aquifer. In many parts of the study area, data were sparse, and 

driller’s completion reports were the only available source of 

hydrogeologic information. The reliability of information from 

driller’s completion reports was largely unknown. As a result, 

completion reports and lithologic logs with descriptive well 

locations and hydrogeologic information were given priority. 

In some cases, hydrogeologic properties were interpolated 

over large distances. The conceptualization of the hydrogeologic properties of the Ogallala aquifer was dependent on 

the spatial availability of hydrogeologic information and the 

interpolation methods used. 

Groundwater discharge locations, primarily seeps, 

springs, and wells, were assumed based on available information. Ephemeral stream drainages were used to approximately 

locate springs and seeps along the contact between the Ogallala Formation and underlying geologic units. Well locations 
56 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

1984 1992 2000 2008 1984 1992 2000 2008

Calendar Year 

EXPLANATION 

Hydraulic head, in feet above National Geodetic Vertical Datum of 1929 

2,134

2,136

2,138

2,140

2,142

2,144 GY–78A (71) 

1,980

1,982

1,984

1,986

1,988

1,990 TR–57C (29)

2,335

2,340

2,345

2,350

2,355 TR–59B (48) 

2,280

2,290

2,300

2,310

2,320

2,330

2,340

2,350 TR–78N (36) 

2,298

2,300

2,302

2,304

2,306

2,308

2,310 TR–78J (97) 

2,240

2,245

2,250

2,255

2,260 TR–74F (240)

2,140

2,142

2,144

2,146

2,148

2,150

2,152

2,154

2,156 GY–77B (132) 

Calibrated Pumping scenario

2,340

2,345

2,350

2,355

2,360 TR–78I (188)

Figure 26. The difference in hydraulic heads between the results of the calibrated model (non-drought 

simulation) and the assumed potential drought scenario for the 25-year simulation period for selected 

State observation wells completed in the Ogallala aquifer in the study area. The numbers in parentheses 

are the index number for the well as shown on figure 21. The State observation wells are listed in table 2.
Numerical Model 57

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Cottonwood Creek

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake

Andes

Pickstown

Platte

Colome

New

Witten

Winner

St.

Charles

Bijou

Hills

YTNUOCDDOT

LYMAN COUNTY AURORA COUNTY

BRULE COUNTY

TRIPP COUNTY

GREGORY COUNTY

CHARLES MIX COUNTY

DOUGLAS COUNTY

KEYA PAHA COUNTY BOYD COUNTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.

T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLEM

YTNUOC

EXPLANATION

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Simulated change in hydraulic head, in feet

0 to 5Greater than 5 to 10Greater than 10 to 15Greater than 15 to 20Greater than 20 to 25Greater than 25 to 30

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T

rebeer C k

naS dCreek

soL

Ct er ek

oC

no Creek

Mud Creek

t

Burn

k Roc

Creek Lute

Cre

ek

East

Co

tto

n

wood Creek

hS

da el

C

y

er ek

Murphy Creek

Willow Creek

Co

ttonwood Creek

tse W

oC

ott

wn

oo d C er ek

ar B

t

se W

cn

Bh

l u

Cl er ek P al t et Creek

North Fork Whetstone Creek

Thunder

Creek

South ForkWhetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Dog Ear Creek

Figure 27. The simulated difference in hydraulic head between the calibrated model (non-drought simulation) and the simulation representing a potential drought scenario for the Ogallala aquifer in the study area.
58 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota T. 40 N. T. 39 N. T. 38 N. T. 37 N. T. 36 N. T. 35 N. R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.

T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLE M

YTNUOC

EXPLANATION

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14

Simulated change in hydraulic head, in feet

0 to 1Greater than 1 to 2Greater than 2 to 4Greater than 4 to 6Greater than 6 to 12Greater than 12 to 26

0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure 28. The simulated difference in hydraulic head between the calibrated model and the simulation representing a potential increased pumping scenario for the Ogallala aquifer in the study area.
Numerical Model 59

Table 15. Simulated groundwater budget for the initialization period, water years 1985–2009, potential drought scenario, and potential 

increased pumping scenario for the Ogallala aquifer in the study area.

[<, less than; --, not estimated or not applicable]

Budget component

Inflows Outflows

Cubic feet 

per second

Percentage of 

budget inflows

Cubic feet 

per second

Percentage of 

budget outflows

Initialization stress period budget (calibration simulation)

Specified-head boundaries 18.6 8 7.0 2

River leakage 0.7 <1 26.1 9

Recharge from precipitation 281.2 92 -- --

Spring and seepage discharge -- -- 36.3 12

Well withdrawals -- -- 5.5 2

Evapotranspiration -- -- 225.6 75

Total 300.5 100 300.5 100

Change in storage (inflows minus outflows) 0.0 -- -- --

Average annual budget for water years 1985–2009 (transient simulation)

Specified-head boundaries 18.3 6 7.3 3

River leakage 0.7 <1 27.7 11

Recharge from precipitation 280.5 94 -- --

Spring and seepage discharge -- -- 39.0 15

Well withdrawals -- -- 5.5 2

Evapotranspiration -- -- 184.6 70

Total 299.6 100 264.1 101a

Change in storage (inflows minus outflows) -35.7 -- -- --

Average annual budget for the potential drought scenario

Specified-head boundaries 21.5 15 4.8 3

River leakage 1.0 1 19.1 12

Recharge from precipitation 120.3 84 -- --

Spring and seepage discharge -- -- 25.4 16

Well withdrawals -- -- 5.4 3

Evapotranspiration -- -- 102.3 65

Total 142.8 100 157.0 99a

Change in storage (inflows minus outflows) 14.1 -- -- --

Average annual budget for the potential increased pumping scenario

Specified-head boundaries 18.3 6 7.3 3

River leakage 0.8 <1 27.7 10

Recharge from precipitation 280.5 94 -- --

Spring and seepage discharge -- -- 38.7 15

Well withdrawals -- -- 8.0 3

Evapotranspiration -- -- 183.7 69

Total 299.6 100 265.4 100

Change in storage (inflows minus outflows) -35.0 -- -- --

a

Does not add to 100 percent due to rounding.
60 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

were determined from driller’s completion logs, previous 

investigations, and water-use permits. In many cases, the 

actual well location was unknown, and therefore, the location was assumed based on the legal location provided in the 

source document. Assumed discharge locations affected local 

and regional groundwater-flow directions and the subsequently 

simulated hydraulic heads and discharges in the study area. 

Better quantification of discharge locations would improve the 

model’s ability to accurately simulate groundwater-flow directions, hydraulic heads, and discharge volumes in the study 

area.

Groundwater flow between the Ogallala aquifer and 

underlying hydrogeologic units was assumed to be negligible. 

In other parts of South Dakota, the Ogallala aquifer is hydraulically connected to underlying hydrogeologic units such as 

the Arikaree aquifer (Long and Putnam, 2010). Little information was available that indicated the Arikaree aquifer was a 

substantial source of groundwater in the study area; therefore, 

the assumption that the Arikaree aquifer serves as the lower 

impermeable boundary of the Ogallala aquifer within the study 

area seems appropriate.

Ranges of hydraulic conductivity used in the numerical 

model were based on general ranges of previously published 

values, but final values were determined through model 

calibration. The model’s accuracy is dependent, in part, on the 

accuracy of the estimates of model parameters. Calibration of 

the model yielded a hydraulic conductivity distribution that 

was acceptable, given the data available, but it is reasonable to 

assume that similar hydraulic conductivity distributions could 

exist that also would yield satisfactory model results. Given 

the depositional origin of the Ogallala Formation, horizontal 

hydraulic conductivity anisotropy was assumed to exist in the 

Ogallala aquifer. Multiple anisotropy magnitudes and directions were tested to achieve the best fit between observed and 

simulated hydraulic head in the aquifer. The final anisotropy 

direction was coincident with the general flow direction of 

major streams within the study area. It is likely that the final 

horizontal hydraulic conductivity distribution was dependent 

on the accuracy of the horizontal anisotropy. Without more 

field data, a different hydraulic conductivity distribution and 

horizontal anisotropy cannot be verified. 

Parameter values representing recharge and evapotranspiration were optimized to their upper limits during the calibration process and likely were the result of sparse flow data for 

the aquifer; therefore, the results of the calibration process are 

non-unique. The two primary calibration objectives for the 

model were to simulate transient hydraulic heads and discharge as base flow in the Keya Paha River. Because sparse 

discharge information was available in some parts of the study 

area, hydraulic-head measurements were the only means of 

calibration in those areas. An increase in simulated recharge 

was offset by an increase in evapotranspiration, and the 

parameters increased to their plausible limits. Even though the 

solution is non-unique, the remaining parameter estimates are 

a result of the plausible limits assigned to those parameters.

The calibration targets all contain error, which contributed to uncertainty in parameter estimation. It is difficult to 

quantify the error and uncertainty of individual targets. The 

two calibration targets, transient hydraulic-head measurements 

and discharge to the Keya Paha River, were used to the extent 

of available information. The number of calibration targets for 

individual hydraulic-head measurements at State observation 

wells was much greater compared to the number of calibration 

targets for base-flow estimates. To account for variability in 

the frequency of measurements associated with calibration targets, individual targets for base flow were given more weight 

in the calibration process, and individual hydraulic-head targets were given less weight. This weighting scheme was used 

to prevent the model calibration process from becoming biased 

to one calibration target type compared to the other.

Simulated hydraulic heads at State observation wells and 

simulated base flow generally had less seasonal variability 

when compared with observed or estimated values (figs. 23 

and 25). A single-layer model grid with 1,640-ft spacing was 

determined to be sufficient spatial discretization, and three 

stress periods per year were determined to be sufficient temporal discretization for the scale of the model. The discretization 

of spatially varied aquifer parameters and temporally varied 

aquifer stresses likely smooth simulated changes in hydraulic 

head and base flow for the study area.

Summary

The Ogallala aquifer is an important water resource for 

the Rosebud Sioux Tribe in Gregory and Tripp Counties in 

South Dakota. The Ogallala aquifer is used extensively for irrigation and for public supply, domestic, and stock water supplies. Continued or increased withdrawals from the Ogallala 

aquifer in Gregory and Tripp Counties have the potential to 

affect water levels within the aquifer and base flow discharge 

to streams in the area. A water resource tool was needed to 

better understand management and environmental issues 

associated with the Ogallala aquifer, such as estimating the 

effects of various hydrologic stresses. These stresses include 

prolonged drought and increased groundwater withdrawal. To 

address this need, a conceptual model and a numerical model 

to simulate groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties were developed by the U.S. Geological 

Survey in cooperation with the Rosebud Sioux Tribe. This 

report describes a conceptual model of groundwater flow in 

the aquifer and documents the development and calibration of 

the numerical model to simulate groundwater flow. Data for a 

25-year period (water years 1985–2009) were analyzed for the 

conceptual model, and transient simulations were performed 

for the same 25-year period.

Regional flow in the Ogallala aquifer enters the study 

area from the west and southwest and exits the study area 

to the southeast. Recharge to the Ogallala aquifer occurs 

from precipitation on the outcrop areas. Groundwater from 
Summary 61

precipitation recharge moves from areas of high altitude 

toward streams that gain flow from the Ogallala aquifer. 

Discharge from the Ogallala aquifer occurs through evapotranspiration, discharge to streams, and well withdrawals. 

Evapotranspiration generally occurs in topographically low 

areas along streams, and maximum evapotranspiration occurs 

when the water level is at the land surface. Base flow was 

estimated for two streamgages on the Keya Paha River using 

a hydrograph separation method. The 25-year estimated mean 

base flow was 35.8 cubic feet per second (ft3/s) for the Keya 

Paha River.

Well withdrawals in the study area are from irrigation, 

public supply, domestic, and stock wells. Mean annual withdrawals for irrigation were 1.1 ft3

/s, and mean annual public 

supply use was estimated to be 4.38 ft3/s. Withdrawals for 

individual domestic and stock wells were not accounted for 

individually because the total withdrawals from domestic and 

stock wells were assumed to account for a small fraction of the 

total water budget for the study area.

The conceptual model of groundwater flow was simulated as a single-layer numerical model using MODFLOW–

NWT. The single layer model represented the Ogallala aquifer. 

The study was divided into grid blocks 500 meters [1,640 feet 

(ft)] on each side, with 282 rows and 133 columns. Cell 

heights were equal to the mean formation thickness in each 

cell. Combinations of constant-head and no-flow boundaries 

were used to best represent boundary conditions.

Hydraulic conductivity for the numerical model was 

represented using pilot points. Actual values were interpolated 

to the model domain and assigned to individual model cells. 

The vertical hydraulic conductivity used for the numerical 

model was assumed to be a uniform ratio of 10 percent of the 

horizontal hydraulic conductivity. Uniform storage coefficient 

and specific yield values were used for the numerical model.

Model calibration was accomplished using a parameter 

estimation program that adjusted individual model input 

parameters and assessed the difference between estimated and 

model simulated values of hydraulic head and base flow. A 

simulation that included an initialization period calibrated to 

steady-state conditions and transient stress periods calibrated 

to transient conditions was analyzed to optimize model parameters. The potentiometric surface calculated from the initialization part of the simulation was used to establish the initial 

conditions for the transient part of the simulation. Water-level 

measurements were available for 38 observation wells and 223 

test holes and private wells. A sensitivity analysis was used 

to examine the response of the calibrated model to changes 

in model parameter values. The model was most sensitive to 

recharge and maximum potential evapotranspiration and least 

sensitive to riverbed and spring conductances.

Calibrated hydraulic conductivity for the numerical 

model ranged from 0.9 to 227 feet per day in the Ogallala 

aquifer. The annual recharge rates for the numerical model for 

the transient simulation (water years 1985–2009) ranged from 

0.60 to 6.96 inches, with a mean of 3.68 inches for the Ogallala aquifer. This represents a mean recharge rate of 280.5 ft3

/s 

for the model area. Simulated annual evapotranspiration 

rates ranged from about 128 to 254 ft3/s, and net discharge 

to streams through river leakage and flow from springs and 

seeps ranged from 52.2 to 79.9 ft3/s. Mean annual discharge 

rates were about 185 ft3/s for evapotranspiration, 66.7 ft3/s for 

discharge to streams, and 5.48 ft3/s for well withdrawals.

Constant values for storage coefficient and specific yield 

were used for the numerical model. The storage coefficient 

was 0.004 and specific yield was 0.13.

Calibration objectives for the simulation included (1) 

simulating the long-term mean potentiometric surface and 

hydraulic gradients to those of the mapped potentiometric 

surface, (2) balancing inflows and outflows for the steady-state 

part of the simulation, (3) matching trends in hydrographs 

and hydraulic heads for the 38 State observation wells at 

95 percent of wells to within plus or minus 25 ft of observed 

hydraulic heads, and (4) matching the trends in the base flow 

hydrograph for the Keya Paha River.

Potential future scenarios were simulated using the input 

parameters from the calibrated simulation and included a 

potential drought and a potential increased pumping scenario. 

To simulate a potential drought scenario, a synthetic drought 

record was created, the mean of which was equal to 60 percent 

of the mean estimated recharge rate for the 25-year simulation 

period. The potential drought scenario resulted in water-level 

decreases as much as 30 ft when compared with the calibrated 

simulation. To simulate the effects of potential increases 

in future pumping, production well withdrawal rates were 

increased by 50 percent from those estimated for the 25-year 

simulation period. The simulation representing an increased 

pumping scenario resulted in water-level decreases of as much 

as 26 ft when compared with the calibrated simulation.

Groundwater budgets for the potential future scenario 

simulation were compared with the water budgets for the 

simulation for water years 1985–2009. Compared with the 

simulation for water years 1985–2009, the simulation that 

represented a potential drought scenario resulted in lower 

aquifer recharge from precipitation and decreased discharge 

from streams, springs, seeps, and evapotranspiration. The 

simulated groundwater budget that represented a potential 

increased pumping scenario was similar to the groundwater 

budget for water years 1985–2009, although well withdrawals 

accounted for a slightly larger portion of simulated outflow 

and river leakage, and evapotranspiration accounted for a 

slightly smaller portion of simulated outflow for the increased 

pumping scenario.

The numerical model is a tool that could be used to better 

understand the flow system of the Ogallala aquifer in Gregory 

and Tripp Counties. The long-term hydraulic-head measurements were simulated reasonably well using the numerical 

model. Discharge from the Ogallala aquifer to rivers, springs, 

and seeps was simulated using the model with reasonable 

accuracy where data were available.
62 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

References Cited

Canadell, J., Jackson, R.B., Ehleringer, J.R., Mooney, H.A., 

Sala, O.E., and Schulze, E.-D., 1996, Maximum rooting 

depth of vegetation types at the global scale: Oecologia, 

v. 108, p. 583–595, accessed January 20, 2011, at http://

biology.duke.edu/jackson/oecol96d.pdf.

Carter, J.M., 1998, Water resources of Mellette and Todd 

Counties, South Dakota: U.S. Geological Survey WaterResources Investigations Report 98–4146, 68 p. (Also available at http://pubs.usgs.gov/wri/wri984146/.)

City of Winner, South Dakota, 2012, Water: City of Winner, 

South Dakota, accessed January 27, 2012, at http://www.

winnersd.com/water.html.

Curve Number Work Group, 2004, Hydrologic soil-cover 

complexes, chap. 9 of National engineering handbook, Part 

630—Hydrology: U.S. Department of Agriculture, Natural 

Resources Conservation Service/Agricultural Research Service 210–VI–NEH, 20 p., accessed June 28, 2010, at ftp://

ftp.wcc.nrcs.usda.gov/wntsc/H&H/NEHhydrology/ch9.pdf.

Dennehy, K.F., 2000, High Plains regional ground-water 

study: U.S. Geological Survey Fact Sheet 2000–091, 2 p. 

(Also available at http://pubs.usgs.gov/fs/2000/0091/report.

pdf.)

Diffendal, R.F., and Voorhies, M.R., 1994, Geologic framework of the Niobrara River drainage basin and adjacent 

areas in South Dakota generally east of the 100th meridian 

west longitude and west of the Missouri River: Nebraska 

Geological Survey Report of Investigations No. 9, 13 

p. (Also available at http://digitalcommons.unl.edu/cgi/

viewcontent.cgi?article=1093&context=geosciencefacpub.)

Doherty, John, 2003, Ground water model calibration using 

pilot points and regularization: Ground Water, v. 41, no. 2, 

p. 170–177. (Also available at http://info.ngwa.org/gwol/

pdf/031075995.pdf.)

Doherty, J.E., 2008, Manual for the groundwater data utilities—PEST: accessed November 20, 2012, at http://www.

pesthomepage.org/Downloads.php.

Doherty, J.E., 2010, PEST—Model-independent parameter 

estimation—User manual (5th ed.): Brisbane, Australia, 

Watermark Numerical Computing, accessed June 28, 2010, 

at http://www.pesthomepage.org/files/pestman.pdf.

Doherty, J.E., and Hunt, R.J., 2010, Approaches to highly 

parameterized inversion—A guide to using PEST for 

groundwater-model calibration: U.S. Geological Survey 

Scientific Investigations Report 2010–5169, 59 p., accessed 

June 28, 2010, at http://pubs.usgs.gov/sir/2010/5169/.

Doherty, J.E., Fienen, M.N., and Hunt, R.J., 2010, Approaches 

to highly parameterized inversion—Pilot-point theory, 

guidelines, and research directions: U.S. Geological Survey 

Scientific Investigations Report 2010–5168, 36 p., accessed 

June 28, 2010, at http://pubs.usgs.gov/sir/2010/5168/.

Dunlap, L.E., and Spinazola, J.M., 1984, Interpolating 

water-table altitudes in west-central Kansas using kriging 

techniques: U.S. Geological Survey Water-Supply Paper 

2238, 19 p., accessed July 8, 2010, at http://pubs.usgs.gov/

wsp/2238/report.pdf.

Ellis, M.J., Ficken, J.H., and Adolphson, D.G., 1971, Hydrology of the Rosebud Indian Reservation, South Dakota: 

U.S. Geological Survey Hydrologic Investigations Atlas 

HA–335, 2 sheets, scale 1:100,000.

Esri, 2011a, An overview of the Geostatistical Analyst toolbar and toolbox: Redlands, Calif., Esri ArcGIS 10.0 help, accessed May 15, 2011, at http://

help.arcgis.com/en/arcgisdesktop/10.0/help/index.

html#//003000000002000000.htm.

Esri, 2011b, How kriging works: Redlands, Calif., Esri 

ArcGIS 10.0 help, accessed May 15, 2011, at http://

help.arcgis.com/en/arcgisdesktop/10.0/help/index.

html#//009z00000076000000.htm.

Esri, 2011c, Mapping and visualization in ArcGIS Desktop: 

Redlands, Calif., Esri ArcGIS 10.0 help, accessed July 11, 

2010, at http://help.arcgis.com/en/arcgisdesktop/10.0/help/

index.html#//00660000042t000000.

Farnsworth, R.K., Thompson, E.S., and Peck, E.L., 1982, 

Evaporation atlas for the contiguous 48 United States: 

National Oceanic and Atmospheric Administration Technical Report NWS 33, 26 p. (Also available at http://www.

nws.noaa.gov/oh/hdsc/PMP_related_studies/TR33.pdf.)

Fenneman, N.M., 1946, Physical divisions of the United 

States: U.S. Geological Survey, scale 1:7,000,000 (reprinted 

1964).

Filipovic, Dragan, 2004, Hydrogeologic assessment of the 

High Plains aquifer in Gregory and Tripp Counties, South 

Dakota: South Dakota Geological Survey Open File Report 

90–UR, 1 sheet, scale 1:100,000. (Also available at http://

www.sdgs.usd.edu/pubs/pdf/UR-90_20040630.pdf.)

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. (Also available at 

http://pubs.usgs.gov/pp/1400b/report.pdf.)
References Cited 63

Hammond, P.D., 1996, Hydrogeologic investigation of the 

Herrick Formation near the city of Herrick, South Dakota: 

South Dakota Geological Survey Open-File Report 75–UR, 

31 p. (Also available at http://www.sdgs.usd.edu/pubs/pdf/

UR-75.pdf.)

Harbaugh, A.W., 2005, MODFLOW–2005, the U.S. Geological Survey modular ground-water model—The groundwater flow process: U.S. Geological Survey Techniques 

and Methods, book 6, chap. A16, variously paged, accessed 

June 28, 2010, at http://pubs.usgs.gov/tm/2005/tm6A16/.

Hargreaves, G.H., and Samani, Z.A., 1985, Reference crop 

evapotranspiration from temperature: Applied Engineering 

in Agriculture, v. 1, no. 2, p. 96–99.

Harksen, J.C., and McDonald, J.R., 1969, Guidebook to the 

major Cenozoic deposits of southwestern South Dakota: 

South Dakota Geological Survey Guidebook, v. 2, 103 p.

Helsel, D.R. and R. M. Hirsch, 2002, Statistical Methods in 

Water Resources, U.S. Geological Survey Techniques of 

Water Resources Investigations, Book 4, chapter A3, 522 p. 

(Also available at http://pubs.usgs.gov/twri/twri4a3/pdf/

twri4a3-new.pdf.)

High Plains Regional Climate Center, 2011, Historical 

climate data summaries: Lincoln, Nebraska, University of 

Nebraska, accessed September 30, 2011, at http://www.

hprcc.unl.edu/data/historical/.

Kolm, K.E., and Case, H.L., III, 1983, A two-dimensional, 

finite-difference model of the High Plains aquifer in southern South Dakota: U.S. Geological Survey Water-Resources 

Investigations Report 83–4175, 34 p. (Also available at 

http://pubs.usgs.gov/wri/1983/4175/report.pdf.)

Kremin-Smith, D.J., 1984, Hydrogeology of a portion of the 

Ogallala aquifer, south-central Todd County, South Dakota: 

Rapid City, South Dakota School of Mines and Technology 

M.S. thesis, 76 p.

LaBelle, Anneka, 2011, Using Thornthwaite-Mather soil-water 

balance method to estimate current and future recharge 

trends near Pine Ridge Reservation, South Dakota: Rapid 

City, South Dakota School of Mines and Technology M.S. 

thesis, 79 p.

Langbein, W.B. and others, 1949, Annual runoff in the United 

States: U.S. Geological Survey Circular 52, 14 p., 1 pl., 

scale 1:8,740,000. (Also available at http://pubs.usgs.gov/

circ/1949/0052/report.pdf.)

Long, A.J., and Putnam, L.D., 2010, Simulated groundwater 

flow in the Ogallala and Arikaree aquifers, Rosebud Indian 

Reservation area, South Dakota—Revisions with data 

through water year 2008 and simulations of potential future 

scenarios: U.S. Geological Survey Scientific Investigations 

Report 2010–5105, 64 p., accessed September 30, 2011, at 

http://pubs.usgs.gov/sir/2010/5105/.

Long, A.J., Putnam, L.D., and Carter, J.M., 2003, Simulated 

ground-water flow in the Ogallala and Arikaree aquifers, 

Rosebud Indian Reservation area, South Dakota: U.S. 

Geological Survey Water-Resources Investigations Report 

03–4043, 69 p. (Also available at http://pubs.usgs.gov/wri/

wri034043/wri034043.html.)

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, 57 p. 

(Also available at http://pubs.usgs.gov/pp/1400d/report.

pdf.)

Luckey, R.R., Gutentag, E.D., Heimes, F.J., and Weeks, J.B., 

1988, Effects of future ground-water pumpage on 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–E, 44 p. 

(Also available at http://pubs.usgs.gov/pp/1400e/report.pdf.)

Mace, R.E., 2001, Estimating transmissivity using specificcapacity data: Austin, Texas, University of Texas at Austin, 

Bureau of Economic Geology Geological Circular 01–2, 

44 p.

Martin, J.E., Sawyer, J.F., Fahrenbach, M.D., Tomhave, D.W., 

and Schulz, L.D., 2004, Geologic map of South Dakota: 

South Dakota Geological Survey General Map G–10, 1 

sheet, scale 1:500,000, 20 p. reference pamphlet. (Also 

available at http://www.sdgs.usd.edu/publications/general.

html.)

McCormick, K.A., 2010, Elevation contour map of the Precambrian surface of South Dakota: South Dakota Geological Survey General Map G–11, scale 1:500,000. (Also available at http://www.sdgs.usd.edu/pubs/pdf/G-11%20-%20

statewide%20map.pdf.)

McDonald, M.G., and Harbaugh, A.W., 1988, A modular 

three-dimensional finite-difference ground-water flow 

model: U.S. Geological Survey Techniques of WaterResources Investigations, book 6, chap. A1, variously 

paged. (Also available at http://pubs.usgs.gov/twri/

twri6a1/.)

McGuire, V.L., 2001, Water-level changes in the High Plains 

aquifer, 1980 to 1999: U.S. Geological Survey Fact Sheet 

2001–029, 2 p. (Also available at http://pubs.usgs.gov/

fs/2001/fs-029-01/.)

McMahon, P.B., Dennehy, K.F., Bruce, B.W., Gurdak, J.J., and 

Qi, S.L., 2007, Water-quality assessment of the High Plains 

aquifer, 1999–2004: U.S. Geological Survey Professional 

Paper 1749, 136 p. (Also available at http://pubs.usgs.gov/

pp/1749/.)
64 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Multi-Resolution Land Characteristics Consortium, 2009, 

National land cover database 2001: U.S. Geological Survey, 

accessed October 26, 2010, at http://www.mrlc.gov/nlcd.

php.

National Oceanic and Atmospheric Administration, 2010, 

NOAA satellite and information service: National Oceanic 

and Atmospheric Administration, accessed August 8, 2010, 

at http://www.ncdc.noaa.gov/oa/climate/stationlocator.html.

Natural Resources Conservation Service, 2009a, Physical soil 

properties—Tripp County, South Dakota, tabular data version 13: U.S. Department of Agriculture, Natural Resources 

Conservation Service, 25 p., accessed January 12, 2011, at 

http://soildatamart.nrcs.usda.gov/State.aspx?State=SD.

Natural Resources Conservation Service, 2009b, Water features—Tripp County, South Dakota, tabular data version 13: 

U.S. Department of Agriculture, Natural Resources Conservation Service, 19 p., accessed January 12, 2011, at http://

soildatamart.nrcs.usda.gov/State.aspx?State=SD.

Newport, T.G., 1959, Ground-water resources of the lower 

Niobrara River and Ponca Creek Basins, Nebraska and 

South Dakota, with a section on Chemical quality of the 

water, by R.A. Krieger: U.S. Geological Survey WaterSupply Paper 1460–G, p. 272–323. (Also available at http://

pubs.usgs.gov/wsp/1460g/report.pdf.)

Niswonger, R.G., Panday, Sorab, and Ibaraki, Motomu, 2011, 

MODFLOW–NWT, a Newton formulation for MODFLOW–2005: U.S. Geological Survey Techniques and 

Methods 6–A37, 44 p., accessed May 17, 2011, at http://

pubs.usgs.gov/tm/tm6a37/.

Qi, S.L., 2010, Digital map of the aquifer boundary of the 

High Plains aquifer in parts of Colorado, Kansas, Nebraska, 

New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological Survey Data Series 543, accessed 

May 15, 2011, at http://pubs.usgs.gov/ds/543/. 

Rahn, P.H., and Paul, H.A., 1975, Hydrogeology of a portion 

of the Sand Hills and Ogallala aquifer, South Dakota and 

Nebraska: Ground Water, v. 13, no. 5, p. 428–437.

Rutledge, A.T., 1998, Computer programs for describing the 

recession of ground-water discharge and for estimating 

mean ground-water recharge and discharge from streamflow 

records—Update: U.S. Geological Survey Water-Resources 

Investigations Report 98–4148, 43 p., accessed December 

29, 2011, at http://pubs.usgs.gov/wri/wri984148/.

Sevon, W.D., and Petsch, B.C., 1960, Geology of the Spring 

Creek quadrangle, South Dakota: South Dakota Geological 

Survey Geologic Quadrangle GQ62K–092, scale 1:62,500, 

2 sheets. (Also available at http://www.sdgs.usd.edu/pubs/

pdf/GQ62K-092.pdf.)

South Dakota Department of Environment and Natural 

Resources, 2010, Lithologic logs database: South Dakota 

Geological Survey, accessed July 15, 2010, at http://sddenr.

net/lithdb/.

South Dakota Department of Environment and Natural 

Resources, 2011, South Dakota water rights database: South 

Dakota Department of Environment and Natural Resources, 

accessed November 30, 2011, at http://denr.sd.gov/des/wr/

dbwrsearch.aspx.

South Dakota State University, 2011, Frost dates for coop stations: South Dakota State University, accessed January 20, 

2010, at http://climate.sdstate.edu/w_info/frost/frost.shtm.

Springer, R.F., 1979, Soil survey of Tripp County, South 

Dakota: U.S. Department of Agriculture Soil Conservation 

Service and Bureau of Indian Affairs, 197 p. plus guide 

to mapping units. (Also available at http://soils.usda.gov/

survey/online_surveys/south_dakota/SD123/tripp.pdf.)

Stanton, J.S., Qi, S.L., Ryter, D.W., Falk, S.E., Houston, N.A., 

Peterson, S.M., Westenbroek, S.M., and Christenson, S.C., 

2011, Selected approaches to estimate water-budget components of the High Plains, 1940 through 1949 and 2000 

through 2009: U.S. Geological Survey Scientific Investigations Report 2011–5183, 79 p., accessed July 12, 2012, at 

http://pubs.usgs.gov/sir/2011/5183/.

Stevenson, R.E., and Buckmeier, F.J., 1958, Geology of the 

Gregory quadrangle, South Dakota: South Dakota Geological Survey Geologic Quadrangle GQ62K–066, scale 

1:62,500, 2 sheets. (Also available at http://www.sdgs.usd.

edu/pubs/pdf/GQ62K-066.pdf.)

Theis, C.V., Brown, R.H., and Meyer, R.R., 1963, Estimating 

the transmissibility of aquifers from the specific capacity 

of wells, in Bentall, Ray, comp., Methods of determining 

permeability, transmissivity, and drawdown: U.S. Geological Survey Water-Supply Paper 1536–I, p. 331–340. (Also 

available at http://pubs.er.usgs.gov/publication/wsp1536I.)

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. (Also available at http://pubs.usgs.

gov/pp/1400c/.)

Thornthwaite, C.W., 1948, An approach toward a rational 

classification of climate: Geographical Review, v. 38, 

no. 1, p. 55–94. (Also available at http://www.jstor.org/

sici?sici=0016-7428%28194801%2938%3A1%3C55%3AA

ATARC%3E2.0.CO%3B2-O.)
 65

Thornthwaite, C.W., and Mather, J.R., 1957, Instructions and 

tables for computing potential evapotranspiration and the 

water balance: Centerton, N.J., Drexel Institute of Technology, Laboratory of Climatology Publications in Climatology, v. 10, no. 3, p. 183–311.

Tripp County Water User District, 2012, History: Tripp 

County Water User District, accessed January 27, 2012, at 

http://trippcountywater.com/?page_id=179.

U.S. Census Bureau, 2002, South Dakota—2000—Summary 

population and housing characteristics: U.S. Census Bureau 

2000 Census of Population and Housing PHC–1–43, 

November, 351 p., accessed December 10, 2011, at http://

www.census.gov/prod/cen2000/phc-1-43.pdf.

U.S. Geological Survey, 2006, National elevation dataset: U.S. 

Geological Survey, accessed May 12, 2010, at http://ned.

usgs.gov/.

U.S. Geological Survey, 2009, Water use in the United States: 

U.S. Geological Survey database, accessed March 17, 2011, 

at http://water.usgs.gov/watuse/.

U.S. Geological Survey, 2011, USGS water data for South 

Dakota: U.S. Geological Survey National Water Information System, accessed June 28, 2011, at http://waterdata.

usgs.gov/sd/nwis/.

University of Nebraska-Lincoln, 2010, Bedrock geology of 

Nebraska: Lincoln, University of Nebraska-Lincoln GIS 

geology database, accessed July 12, 2012, at http://snr.unl.

edu/data/geographygis/NebrGISgeology.asp#bedrock.

Weeks, J.B., and Gutentag, E.D., 1981, Bedrock geology, 

altitude of base, and 1980 saturated thickness of the High 

Plains aquifer in parts of Colorado, Kansas, Nebraska, New 

Mexico, Oklahoma, South Dakota, Texas, and Wyoming: 

U.S. Geological Survey Hydrologic Investigations Atlas 

HA–648, 2 plates.

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. 

(Also available at http://pubs.usgs.gov/pp/1400a/.)

Westenbroek, S.M., Kelson, V.A., Dripps, W.R., Hunt, R.J., 

and Bradbury, K.R., 2010, SWB—A modified Thornthwaite-Mather soil-water-balance code for estimating 

groundwater recharge: U.S. Geological Survey Techniques 

and Methods, book 6, chap. A31, 60 p., accessed June 28, 

2011, at http://pubs.usgs.gov/tm/tm6-a31/.

Wiesner, C.H., 1984, Soil survey of Gregory County, South 

Dakota: U.S. Department of Agriculture, 175 p.

Wilson, W.E., and Moore, J.E., eds., 1998, Glossary of hydrology: Alexandria, Virginia, American Geological Institute, 

248 p.

Supplemental Information
68 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Supplement 1. Data Used to Estimate Mean Potentiometric Surface

Data for all wells used to estimate the mean potentiometric surface of the Ogallala aquifer for water years 1985 through 

2009 are presented in table S1–1.

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

1 425923099134101 35N16W20DC 2,153 136 5/30/2009 1 2,119 --

2 425902099085501 35N16W25AB 2,111 134 10/12/2006 1 2,066 --

3 425913099330401 35N19W28AA 1,983 15 10/27/2000 1 1,974 --

4 425944099521201 35N22W23AA 2,360 90 6/14/2007 1 2,349 --

5 425939099513501 35N22W24BA 2,370 60 9/14/2001 1 2,347 --

6 425856099530201 35N22W26BB 2,424 140 7/16/1996 1 2,339 --

7 425932099580401 35N23W24AD 2,474 105 7/5/1999 1 2,426 --

8 425924099583801 35N23W24CA 2,471 118 4/18/2000 1 2,399 --

9 425937100095901 35N24W20AC 2,549 120 9/3/1994 1 2,499 --

10 425919100092901 35N24W21DA 2,561 146 9/3/1994 1 2,508 --

11 425846100113601 35N24W30BC 2,515 80 8/9/2002 1 2,503 --

12 430422098565001 95N69W 1BB 1 1,955 66 4/22/1998 1 1,945 --

13 430405098563401 95N69W 1DDDD 1,930 64 11/13/1984–9/30/2009 174 1,897.7 GY–78C

14 430416098580901 95N69W 2DC 1,970 70 12/30/1992 1 1,947 --

15 430435099004001 95N69W 4 2,025 50 6/14/1985 1 1,998 --

16 430403098580901 95N69W11AB 1,961 60 7/16/1996 1 1,947 --

17 430344098570701 95N69W12CA 1,921 74 12/28/1984 1 1,909 --

18 430310098574401 95N69W14AAAA 1,943 83 11/13/1984–9/30/2009 173 1,909.7 GY–78D

19 430350099054901 95N70W11BC 2,069 37 12/16/2004 1 2,049 --

20 430403099201001 95N72W10AAAA 2,161 -- 6/11/2003 1 2,153 R2–2003–28

21 430128099234101 95N72W20CCCC 2,285 133 7/22/2003 1 2,188 R2–2003–27a

22 430129099201201 95N72W22DDDD 2,217 104 11/13/1984–9/30/2009 174 2,182.7 GY–78B

23 430203099193401 95N72W23CD 2,193 94 2/25/1986 1 2,163 --

24 430118099201901 95N72W27AD 2,233 144 8/28/1993 1 2,178 --

25 430144099194302 95N72W32CD 3 2,223 -- 7/8/1993 1 2,193 --

26 430028099181401 95N72W36AC 2,225 60 5/11/1995 1 2,205 --

27 430404099282801 95N73W 4DDDD 2,305 -- 6/10/2003 1 2,258 R2–2000–25

28 430441099365401 95N74W 5BD 2,309 60 5/25/2004 1 2,297 --

29 425946099382001 95N74W31DDCC 1 1,990 30 11/14/1984–9/30/2009 119 1,963.1 TR–57C

30 430454099482801 95N76W 2BB 2,304 62 6/17/1992 1 2,290 --
Supplement 1. Data Used to Estimate Mean Potentiometric Surface 69

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

31 430454099495701 95N76W 4AA 2,297 38 5/1/2001 1 2,277 --

32 430215099522801 95N76W19A 2,203 90 4/17/1993 1 2,173 --

33 430035099465201 95N76W25CDDD 2,138 -- 5/18/1999 1 2,100 R2–99–02

34 430053099505001 95N76W28CC 2,318 55 7/13/2000 1 2,290 --

35 430128099520001 95N76W29BBBB 2,253 77 11/14/1984–9/30/2009 172 2,222.4 TR–78F

36 425956099520501 95N76W32CCCC 2,348 66 11/14/1984–9/30/2009 173 2,337.8 TR–78N

37 430002099501501 95N76W33DC 2,262 45 12/5/1996 1 2,250 --

38 430429099575701 95N77W 4CB 2,204 55 9/5/1991 1 2,163 --

39 430312099554501 95N77W14BBBB 2,214 50 3/11/2002–8/7/2003 4 2,175 R2–2001–60a

40 430235099592601 95N77W18DD 2,311 80 4/1/1998 1 2,297 --

41 430144099592601 95N77W19DD 1 2,326 60 10/2/2000 1 2,318 --

42 430144099592602 95N77W19DD 2 2,326 -- 5/14/2001 1 2,318 --

43 430037099535601 95N77W25DCCC 2,288 185 11/14/1984–9/30/2009 165 2,244.9 TR–78M

44 430053099551601 95N77W26CD 2,289 98 3/8/1994 1 2,278 --

45 430106099562801 95N77W27CA 2,353 130 8/15/2006 1 2,334 --

46 430043099584601 95N77W29CD 2,289 60 8/16/2006 1 2,277 --

47 430100100001001 95N77W30C 2,340 58 2/25/1991 1 2,329 --

48 430010099580601 95N77W32CAAD 2,380 76 11/14/1984–9/30/2009 170 2,342.3 TR–59B

49 430332100012201 95N78W12C 2,332 130 9/15/1994 1 2,292 --

50 430248100014801 95N78W14DB 2,342 120 9/14/1994 1 2,312 --

51 430133100061501 95N78W20CCCC 2,430 105 11/14/1984–9/30/2009 174 2,388.3 TR–78E

52 430131100063401 95N78W30AA 2,432 -- 7/19/1991 1 2,378 --

53 430015100061601 95N78W32DC 2,421 100 9/23/1988 1 2,405 --

54 430035100040401 95N78W33AAAA 2,426 -- 6/8/1999 1 2,400 R20–99–16a

55 430003100022401 95N78W35CD 2,451 90 8/14/1986 1 2,391 --

56 430003100014801 95N78W35DD 2,402 60 12/7/2000 1 2,382 --

57 430131100091401 95N79W26AB 2,480 100 9/19/2001 1 2,423 --

58 430053100121201 95N79W28CC 2,431 90 7/30/1993 1 2,427 --

59 430035100111001 95N79W33AAAA 2,500 -- 7/20/1999 1 2,414 R20–99–40

60 430856099014201 96N69W 8AC 2,041 80 11/10/1990 1 2,013 --

61 430804099042101 96N70W13BD 2,104 70 8/25/1994 1 2,079 --

62 430738099053101 96N70W14CD 1 2,122 74 9/16/1989 1 2,072 --

63 430758099074401 96N70W16BD 2,140 50 8/11/1997 1 2,131 --

64 430621099060701 96N70W27AD 2,103 60 3/23/1994 1 2,081 --

65 430635099085501 96N70W29BB 1 2,140 45 12/20/1984 1 2,112 --
70 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

66 430537099104001 96N70W31BBCC 1 2,155 74 6/27/1990 1 2,107 R20–90–26

67 430543099071801 96N70W33AA 2,147 80 3/1/1999 1 2,091 --

68 430542099055901 96N70W34AAAD 2,085 16 11/13/1984–9/30/2009 175 2,080.0 GY–57B

69 430457099060001 96N70W34DDDD 2,077 -- 6/17/2003 1 2,064 R2–2003–36

70 430947099140501 96N71W 3BC 2,140 60 9/22/2001 1 2,092 --

71 431006099163801 96N71W 6AAAA 2,165 123 11/13/1984–9/30/2009 173 2,112.9 GY–78A

72 430923099174601 96N71W 6CCCB 2,092 -- 7/19/1994 1 2,084 R20–94–42

73 430830099164501 96N71W 7DD 2,159 70 9/16/1991 1 2,152 --

74 430743099115001 96N71W13CCBB 2,163 39 11/13/1984–9/30/2009 174 2,138.5 GY–57A

75 430758099122701 96N71W14AC 2 2,172 73 11/18/1984 1 2,134 --

76 430621099125401 96N71W26BC 2,173 70 9/18/1991 1 2,166 --

77 430530099105001 96N71W36AD 2,120 48 9/18/2000 1 2,100 --

78 430556099305901 96N73W30DD 2,284 60 5/15/1990 1 2,279 --

79 430505099304901 96N73W32CCBB 2,310 -- 6/6/2000 1 2,280 R2–2000–08

80 430921099332101 96N74W 2DD 2,291 70 3/31/1991 1 2,281 --

81 431008099375501 96N74W 5BBBB 2,275 -- 6/25/2001 1 2,245 R20–2001–18

82 430823099353501 96N74W16AAAA 2,325 -- 10/2/2001 1 2,300 R2–2001–59

83 430732099353201 96N74W16DDDD 2,342 35 11/13/1984–9/30/2009 169 2,334.8 TR–79A

84 430725099341401 96N74W23BB 2,290 48 11/17/1984 1 2,278 --

85 430555099330301 96N74W25CC 2,331 50 9/26/1990 1 2,318 --

86 430608099345001 96N74W27DB 1 2,325 36 9/29/1999 1 2,317 --

87 430923099461001 96N75W 6CCCC 2,301 30 11/13/1984–9/30/2009 175 2,290.3 TR–78K

88 430902099411201 96N75W11DA 2,311 40 4/29/1998 1 2,302 --

89 430647099410301 96N75W32CD 2,340 46 5/5/1993 1 2,325 --

90 430545099424001 96N75W34BBBB 2,275 -- 6/20/2001 1 2,261 R20–2001–15

91 430546099401701 96N75W36BBBB 2,360 -- 5/19/1999 1 2,307 R20–99–04

92 430947099473501 96N76W 2AD 2,349 54 7/11/2002 1 2,342 --

93 430921099482801 96N76W 2CC 2,308 70 9/20/1989 1 2,296 --

94 431000099503301 96N76W 4BA 2,310 52 11/18/2000 1 2,285 --

95 431000099510801 96N76W 5AA 2,310 60 11/4/1988 1 2,304 --

96 431008099521001 96N76W 5BBBB 2,306 -- 6/13/2001 1 2,267 R20–2001–13

97 430919099521501 96N76W 6DDDD 2,309 25 11/13/1984–9/30/2009 175 2,305.5 TR–78J

98 430855099510801 96N76W 8AD 2,291 60 11/8/1988 1 2,283 --

99 430823099483601 96N76W14BBBB 2,282 -- 10/2/2001 1 2,260 R2–2001–58

100 430638099520801 96N76W29BBBB 2,246 46 11/14/1984–9/30/2009 175 2,235.7 TR–78L
Supplement 1. Data Used to Estimate Mean Potentiometric Surface 71

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

101 430530099525501 96N76W31BD 2,198 40 11/8/2000 1 2,186 --

102 430504099520101 96N76W32CC 2,168 51 10/22/2003 1 2,150 --

103 430543099484601 96N76W34AA 2,290 50 7/7/1992 1 2,278 --

104 431008099543301 96N77W 1BBBB 2,317 -- 6/13/2001 1 2,291 R20–2001–10

105 431008099580401 96N77W 4BBBB 2,375 207 6/9/1999 1 2,303 R20–99–18

106 430856099570401 96N77W 9DC 2,354 32 8/24/1989 1 2,340 --

107 430811099563701 96N77W15B 2,307 47 8/27/2000 1 2,299 --

108 430824099565501 96N77W15BBBB 2,309 -- 10/31/2000 1 2,294 R2–2000–83

109 430811100001001 96N77W18B 2,290 66 4/1/1996 1 2,255 --

110 430726099542401 96N77W24BB 2,301 24 10/10/2003 1 2,291 --

111 430609099590801 96N77W29CB 2,227 70 9/16/1992 1 2,204 --

112 430923100035301 96N78W 3CC 2,314 55 6/7/1990 1 2,306 --

113 430825100025101 96N78W10DDDD 2,288 -- 10/1/2001 1 2,278 R2–2001–55

114 430648100022401 96N78W23CD 2,244 42 11/10/2000 1 2,230 --

115 430512100071701 96N78W31C 2,401 200 9/16/1988 1 2,286 --

116 430920100100001 96N79W 3DDDD 2,300 -- 7/27/1999 1 2,285 R20–99–42

117 430816100095701 96N79W14BBCC 2,240 -- 5/20/1997 1 2,238 R2–97–01

118 430812100095901 96N79W14BBCC 2 2,240 30 8/6/1997 1 2,237 R20–97–38

119 431304099140601 97N71W15CB 2,022 60 9/2/2004 1 2,014 --

120 431113099173801 97N71W30CCBA 2,180 148 8/24/1988 1 2,134 R20–88–39

121 431034099174501 97N71W31CBBB 2,147 97 8/30/1988 1 2,144 R20–88–44

122 431034099171101 97N71W31DBBB 2,200 152 8/30/1988 1 2,124 R20–88–43

123 431238099224101 97N72W20AA 1 2,169 72 12/2/1987 1 2,148 --

124 431238099224102 97N72W20AA 2 2,169 40 5/3/1988 1 2,146 --

125 431159099213001 97N72W21DD 2,169 83 2/16/1996 1 2,139 --

126 431153099212201 97N72W21DDDD 2,150 53 11/13/1984–9/30/2009 175 2,145.2 GY–77A

127 431159099205501 97N72W22CD 2,148 70 10/15/1991 1 2,126 --

128 431102099182501 97N72W25CDDD 2,223 172 8/24/1988 1 2,175 R20–88–40

129 431146099185001 97N72W25DC 2,228 148 8/30/1989 1 2,143 --

130 431146099200101 97N72W26BB 2,143 55 6/20/1989 1 2,134 --

131 431107099200101 97N72W26CC 2,161 70 7/1/1992 1 2,146 --

132 431101099211901 97N72W27DDDD 2,163 56 11/13/1984–9/30/2009 175 2,152.9 GY–77B

133 431047099195301 97N72W35BB 1 2,194 70 5/17/1990 1 2,159 --

134 431047099195302 97N72W35BB 2 2,194 70 5/17/1990 1 2,159 --

135 431052099174801 97N72W36AADA 2,195 147 8/31/1988 1 2,172 R20–88–45
72 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

136 431055099181101 97N72W36ABAC 2,222 164 8/24/1988 1 2,176 R20–88–41

137 431054099183201 97N72W36BA 2,235 150 8/15/1989 1 2,157 --

138 431021099180601 97N72W36DD 2,215 55 9/30/1999 1 2,180 --

139 431435099250401 97N73W 1DD 2,167 50 6/30/1989 1 2,157 --

140 431409099261501 97N73W11AD 2,162 40 4/14/1989 1 2,155 --

141 431422099255701 97N73W12BB 2,178 63 10/20/2005 1 2,169 --

142 431412099254501 97N73W12BD 2,178 61 10/22/2005 1 2,166 --

143 431047099314401 97N73W31BC 1 2,277 80 8/21/1989 1 2,271 --

144 431116099331301 97N74W26DADA 2,282 -- 6/26/2001 1 2,272 R20–2001–19

145 431110099353401 97N74W27CCBB 2,285 35 3/11/2002–8/7/2003 4 2,262 R20–99–35a

146 431146099354401 97N74W28AA 2,277 30 5/20/1991 1 2,271 --

147 431028099374801 97N74W32CB 2,290 22 3/25/1989 1 2,282 --

148 431435099460601 97N75W 6CC 2,328 41 7/21/2001 2 2,313 --

149 431435099460602 97N75W 6CC 2 2,328 41 7/21/2001 2 2,313 --

150 431343099454801 97N75W 7CD 2,305 23 4/20/1990 1 2,282 --

151 431107099421501 97N75W27CD 2,249 60 10/30/1991 1 2,228 --

152 431009099450001 97N75W32CCCC 2,300 55 3/11/2002–8/7/2003 4 2,276 R2–2000–06a

153 431009099424001 97N75W34CCCC 2,292 -- 6/20/2001 1 2,280 R20–2001–14

154 431014099421501 97N75W34CD 2,295 70 5/14/1991 1 2,280 --

155 431009099413001 97N75W35CCCC 1 2,298 -- 6/18/2001 1 2,295 R20–2001–12

156 431502099462401 97N76W 1AD 2,317 36 12/5/2000 1 2,313 --

157 431434099462401 97N76W 1DDDD 2,341 45 11/13/1984–9/30/2009 173 2,323.3 TR–78G

158 431515099484601 97N76W 3AA 2,256 46 5/7/1992 1 2,248 --

159 431519099520301 97N76W 5BBBA 2,264 42 11/13/1984–9/30/2009 172 2,257.3 TR–72E

160 431502099523701 97N76W 6AC 1 2,272 60 3/1/2000 1 2,262 --

161 431449099521901 97N76W 6CC 2,284 45 5/22/1990 1 2,269 --

163 431403099521301 97N76W 7DAAA 2,370 -- 5/20/2003 1 2,305 R2–2003–11

162 431404099521701 97N76W 7DAAA 1 2,370 142 7/22/2003 1 2,307 R2–2003–12a

164 431403099524801 97N76W 7DBBB 2,337 98 7/22/2003 1 2,307 R2–2003–07a

165 431410099490401 97N76W10AC 2,392 130 7/10/2003 1 2,316 --

166 431252099465901 97N76W13CD 2,373 46 7/15/1989 1 2,348 --

167 431330099484501 97N76W15AABA 2,332 85 11/13/1984–9/30/2009 175 2,327.4 TR–78H

168 431336099510001 97N76W16BBBB 2,420 163 3/11/2002–8/7/2003 4 2,329 R20–2001–08a

169 431334099520701 97N76W17BBBB 1 2,398 165 11/13/1984–9/30/2009 174 2,323.1 TR–78A

170 431312099524801 97N76W18ACCC 1 2,433 -- 5/7/2003 1 2,324 R2–2003–04
Supplement 1. Data Used to Estimate Mean Potentiometric Surface 73

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

171 431313099524802 97N76W18ACCC 2 2,433 172 7/22/2003 1 2,324 R2–2003–05a

173 431338099525001 97N76W18BAAA 2,409 -- 5/6/2003 1 2,319 R2–2003–02

172 431338099525101 97N76W18BAAA 1 2,409 162 7/22/2003 1 2,319 R2–2003–03a

174 431318099531301 97N76W18BC 2,432 254 10/6/2004 1 2,344 --

175 431248099532301 97N76W18CCCC 2,454 300 7/22/2003 1 2,332 R2–2003–16a

176 431246099524701 97N76W18CDDD 2,461 -- 5/28/2003 1 2,314 R2–2003–17

177 431310099521301 97N76W18DAAA 2,408 -- 5/13/2003 1 2,337 R2–2003–08

178 431311099521401 97N76W18DAAA 2 2,408 182 7/22/2003 1 2,337 R2–2003–10a

179 431239099531301 97N76W19BB 2,447 195 11/17/1986 1 2,327 --

180 431226099531302 97N76W19BC 2,405 126 7/11/1990 1 2,338 --

181 431156099521701 97N76W19DDDD 2 2,390 168 11/13/1984–9/30/2009 174 2,342.8 TR–78B

182 431245099513701 97N76W20BAAA 2,419 142 7/22/2003 1 2,342 R2–2003–22a

183 431239099520101 97N76W20BB 2,448 180 8/24/1998 1 2,343 --

184 431244099521001 97N76W20BBBB 2,446 -- 6/4/2003 1 2,337 R2–2003–23

185 431220099521101 97N76W20BCCC 2,463 182 7/22/2003 1 2,342 R2–2000–19a

186 431220099513601 97N76W20BDDD 2,455 -- 6/3/2003 1 2,344 R2–2003–20

187 431239099501501 97N76W21AB 2,418 100 8/29/2002 1 2,377 --

188 431156099472601 97N76W23DDDD 2,362 65 11/13/1984–9/30/2009 176 2,355.8 TR–78I

189 431239099465901 97N76W24AB 2,383 60 10/25/1996 1 2,367 --

190 431107099482801 97N76W26C 2,352 58 10/4/1991 1 2,338 --

191 431102099505801 97N76W28CCCC 2,348 125 3/11/2002–8/7/2003 4 2,340 R20–99–37a

192 431146099512601 97N76W29AB 2,404 58 8/2/1990 1 2,391 --

193 431146099520101 97N76W29BB 2,402 110 8/6/1992 1 2,360 --

194 431041099510801 97N76W32AD 2,331 66 11/1/1988 1 2,322 --

195 431436099534801 97N77W 1DC 2,294 80 10/4/2000 1 2,289 --

196 431436099544101 97N77W 2DD 2,342 92 8/17/2001 1 2,289 --

197 431344099534801 97N77W12DC 1 2,339 200 8/8/1994 1 2,322 --

198 431339099534101 97N77W12DCDD 2,340 -- 7/27/1992 1 2,298 R20–92–24

199 431338099543201 97N77W13BBBB 1 2,362 141 7/22/2003 1 2,327 R2–2003–14a

200 431338099543301 97N77W13BBBB 2,362 -- 5/21/2003 1 2,327 R2–2003–13

201 431436099545901 97N77W13BD 2,383 286 10/7/2004 1 2,281 --

202 431315099540001 97N77W13BDDA 2,410 -- 5/21/2003 1 2,325 R2–2003–15

203 431312099550801 97N77W14DD 2,381 160 7/10/1997 1 2,296 --

204 431337099555301 97N77W15AAAB 2,393 -- 6/12/2001 1 2,316 R20–2001–09

205 431239099575701 97N77W21BB 1 2,350 60 10/22/1991 1 2,340 --
74 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

206 431239099575702 97N77W21BB 2 2,350 27 10/25/1991 1 2,345 --

207 431154099574501 97N77W21CDCC 2,371 -- 10/31/2000 1 2,355 R2–2000–84

208 431200099564601 97N77W22DD 2,331 31 7/24/1986 1 2,325 --

209 431243099553601 97N77W23BBBB 2,340 105 11/13/1984–9/30/2009 174 2,335.7 TR–78C

210 431213099533001 97N77W24DA 2,389 120 9/12/1991 1 2,329 --

211 431134099533001 97N77W25A 2,379 54 8/3/1989 1 2,367 --

212 431108099545901 97N77W26DC 2,325 85 6/14/1993 1 2,315 --

213 431055099570401 97N77W33AB 2,331 42 10/26/1993 1 2,317 --

214 431042099575701 97N77W33BA 2,336 50 10/26/1993 1 2,316 --

215 431026099573101 97N77W33CD 2,340 113 10/20/2004 1 2,317 --

216 431042099555301 97N77W34AD 2,346 70 5/10/2001 1 2,336 --

217 431016099564601 97N77W34CC 2,394 77 10/4/2000 1 2,330 --

218 431417100041901 97N78W 9AB 2,367 34 10/27/1989 1 2,361 --

219 431253100072601 97N78W18CC 2,409 62 11/4/1997 1 2,379 --

220 431437100080201 97N79W 1DC 1 2,441 60 5/28/1986 1 2,433 --

221 431437100080202 97N79W 1DC 2 2,441 52 1/7/1998 1 2,439 --

222 431345100122801 97N79W 8DD 2,562 144 12/7/1987 1 2,482 --

223 431412100111601 97N79W 9AD 2,507 60 8/16/2006 1 2,495 --

224 431358100100601 97N79W10DA 1 2,468 175 4/28/2003 1 2,439 --

225 431351100073501 97N79W12DDAA 2,420 -- 6/21/2000 1 2,381 R2–2000–21

226 431332100094801 97N79W14BB 2,480 58 11/20/1987 1 2,452 --

227 431337100095701 97N79W14BBBB 2,462 77 3/11/2002–8/7/2003 4 2,455 R2–2000–18a

228 431327100111001 97N79W16AADD 2,606 -- 6/13/2000 1 2,476 R2–2000–14

229 431327100111002 97N79W16AADD 2 2,606 173 3/11/2002–8/7/2003 4 2,476 R2–2000–15a

230 431306100122801 97N79W17DA 2,539 90 6/6/1994 1 2,474 --

231 431102100111001 97N79W33AAAA 2,440 -- 6/19/2000 1 2,399 R2–2000–16

232 431528099445501 98N75W32CC 2,274 60 7/16/2004 1 2,267 --

233 431711099510601 98N76W20DDDD 2,231 70 11/13/1984–9/30/2009 146 2,169.7 TR–72A

234 431703099502901 98N76W28BAAA 2,198 84 11/13/1984–9/30/2009 176 2,171.8 TR–72B

235 431714099510501 98N76W29DDAA 2,231 57 11/13/1984–9/30/2009 172 2,216.4 TR–72C

236 431550099524501 98N76W31ACCC 2,260 28 11/13/1984–9/30/2009 164 2,248.8 TR–74A

237 431553099525701 98N76W31BDCA 2,282 118 11/13/1984–9/30/2009 129 2,238.3 TR–72F

238 431553099524602 98N76W31BDDB 2 2,265 -- 11/13/1984–9/30/2009 130 2,231.2 TR–72G

239 431553099525503 98N76W31BDDB 3 2,265 -- 11/13/1984–9/30/2009 129 2,225.3 TR–72H

240 431528099522801 98N76W31DCBB 2,263 29 11/13/1984–3/18/2009 159 2,257.1 TR–74F
Supplement 1. Data Used to Estimate Mean Potentiometric Surface 75

Table S1–1. Selected data from wells used for mean potentiometric surface of the Ogallala aquifer for water years 1985–2009.—Continued

[NGVD 29, National Geodetic Vertical Datum of 1929; --, not available]

Index 

number

(fig. 6)

Site identification 

number Legal location

Land–

surface 

altitude 

(feet above 

NGVD 29)

Well 

depth

Hydraulic head 

measurement date or 

range of dates

Number 

of measurements

Mean 

measured 

hydraulic 

head 

(feet above 

NGVD 29)

Other

identifier

241 431527099524501 98N76W31DCCC 2,275 39 11/13/1984–9/30/2009 173 2,253.4 TR–74E

242 431527099523001 98N76W31DCDD 2,279 34 11/13/1984–9/30/2009 201 2,258.2 TR–74D

243 431604099510401 98N76W32AADD 2,241 63 11/14/1984–9/30/2009 172 2,221.8 TR–72D

244 431605099504001 98N76W33BACC 2,230 65 11/14/1984–2/19/2008 132 2,223.3 TR–75B

245 431528099473501 98N76W35DD 2,281 55 8/5/2004 1 2,275 --

246 431521099461501 98N76W36DDDD 2,320 -- 6/6/2001 1 2,302 R20–2001–06

247 431621100035201 98N78W27CC 2,452 75 12/13/2001 1 2,421 --

248 431621100042801 98N78W28DC 2,452 75 12/13/2001 1 2,429 --

249 431608100051101 98N78W33BBBB 2,430 78 11/14/1984–9/30/2009 177 2,416.7 TR–78D

250 431555100050301 98N78W33BC 2,439 82 12/18/1993 1 2,409 --

251 431533100051201 98N78W33CCBB 2,421 -- 10/25/2000 1 2,390 R2–2000–78

252 431542100025901 98N78W34DA 2,414 55 1/20/1992 1 2,389 --

253 431546100025101 98N78W34DAAA 2,420 -- 6/14/1999 1 2,380 R20–99–19

254 431608100020501 98N78W35AB 2,422 55 10/3/1990 1 2,398 --

255 431759100110801 98N79W15CCCC 2,406 -- 6/6/2000 1 2,382 R2–2000–10

256 431615100110801 98N79W34BBBB 2,522 -- 6/7/2000 1 2,469 R2–2000–11

257 431615100110802 98N79W34BBBB 2 2,522 95 3/11/2002–8/7/2003 4 2,469 R2–2000–12a

258 431529100104101 98N79W34CC 2,469 50 6/25/1990 1 2,459 --

259 431523100110801 98N79W34CCCC 2,493 75 3/11/2002–8/7/2003 4 2,456 R2–2000–04a

260 431523100095701 98N79W34DDDD 2,493 78 3/11/2002–8/7/2003 4 2,445 R2–2000–20a

261 431529100091201 98N79W35DC 2,493 100 5/29/1986 1 2,471 --
76 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Supplement 2. Estimates of Transmissivity and Hydraulic Conductivity from 

Specific Capacity Data

Data from five production wells (table 3) were analyzed to determine transmissivity values for the Ogallala aquifer. Specific 

capacity tests, where the well was pumped at a constant rate and the drawdown was measured after 1 to 39 hours, were conducted on 88 wells when they were completed (table S2–1). Well construction data included saturated thickness, well radius, 

pumping rate, drawdown, and pumping period. The specific yield, which is the storage term for unconfined aquifers, was 

assumed to be 0.036 because typical values range from 0.01 to 0.30 for unconfined aquifers (Freeze and Cherry, 1979).

Table S2–1. Specific capacity data, transmissivity, and hydraulic conductivity for selected wells completed in the Ogallala aquifer in 

the study area.

Index 

number

(fig. 10)

Discharge rate 

(gallons per 

minute)

Drawdown

(feet)

Pumping time 

(hours)

Well radius 

(inches)

Specific capacity

(gallons per minute 

per foot of drawdown)

Transmissivity 

(square feet 

per day)

Hydraulic 

conductivity

(feet per day)

1 20 13 12 2 1.54 300 9.1

2 15 18 2 2 0.83 129 6.1

3 2 4 2 2 0.50 73.0 1.7

4 30 16 1 2 1.88 294 11.3

5 3 22 2 2 0.14 16.8 0.3

6 15 74 1 2 0.20 24.0 0.5

7 20 49 1 2 0.41 53.3 0.9

8 20 71 1 2 0.28 34.9 0.7

9 25 30 2 2 0.83 129 1.8

10 10 3 1 2.5 3.33 529 18.9

11 10 12 1 2 0.83 119 2.5

12 10 21 1 2.5 0.48 59.7 1.6

13 12 60 12 2 0.20 32.2 0.4

14 125 18 39 3 7.07 1,600 26.7

15 20 3 1 2.5 6.67 1,140 19.9

16 7 10 2 2 0.70 106 2.3

17 2 65 1 2 0.03 2.59 0.3

18 10 2 1 12 5.00 558 37.2

19 32 5 2 2 6.40 1,210 43.2

20 30 2 3 2 15.00 3,150 286

21 7 12 2 2.5 0.58 82.2 1.6

22 5 10 24 2 0.50 93.9 4.3

23 15 14 1.5 2.5 1.09 159 8.9

24 9 32 2 2 0.28 38.3 2.1

25 6 10 1 12 0.60 43.5 1.6

26 15 21 2 2 0.71 109 5.7

27 31 40 3 2 0.78 124 3.1

28 34 10 1 2 3.40 567 8.5

29 5 6 1 2 0.83 119 2.2

30 10 5 3 2 2.00 352 5.4

31 15 12 1 2 1.25 187 4.0

32 33 10 2 2 3.30 587 15.0

33 62 38 12 6 1.63 260 2.5

34 20 24 2 2 0.83 129 1.3

35 15 6 1 2 2.50 404 8.6
Supplement 2. Estimates of Transmissivity and Hydraulic Conductivity from Specific Capacity Data 77

Table S2–1. Specific capacity data, transmissivity, and hydraulic conductivity for selected wells completed in the Ogallala aquifer in 

the study area.—Continued

Index 

number

(fig. 10)

Discharge rate 

(gallons per 

minute)

Drawdown

(feet)

Pumping time 

(hours)

Well radius 

(inches)

Specific capacity

(gallons per minute 

per foot of drawdown)

Transmissivity 

(square feet 

per day)

Hydraulic 

conductivity

(feet per day)

36 35 10 1 2 3.50 585 58.5

37 20 9 2 2.5 2.22 364 9.6

38 72 35 12 6 2.06 335 7.8

39 15 13 1 2 1.15 171 1.5

40 10 75 2 3 0.13 14.5 0.3

41 35 40 2 3 0.88 124 2.9

42 15 15 2 2 1.00 158 1.2

43 15 7 1 2 2.14 340 10.0

44 37 43 2 3 0.86 122 2.1

45 30 35 2 2 0.86 133 2.3

46 20 27 2 2 0.74 113 1.0

47 15 11 1 2 1.36 206 1.6

48 20 20 2 2 1.00 158 1.6

49 30 32 26 2 0.94 187 1.8

50 4 18 3 2 0.22 30.9 1.9

51 15 5 1 2 3.00 494 13.7

52 15 16 2 2 0.94 147 1.5

53 10 5 2 2 2.00 339 9.2

54 10 25 2 2 0.40 56.8 5.7

55 25 41 1 15 0.61 39.0 3.9

56 18 5 1 2 3.60 604 11.6

57 30 15 3 2 2.00 352 3.5

58 750 65 24 8 11.54 2,240 20.2

59 500 60 4 6 8.33 1,400 26.4

60 720 30 24 8 24.00 4,950 31.3

61 225 60 10 6 3.75 638 26.6

62 900 139 20 6 6.47 1,240 15.1

63 12 6 1.5 2 2.00 329 7.5

64 225 65 10 6 3.46 584 34.4

65 35 34 1 2 1.03 151 2.6

66 8 19 1 2 0.42 55.2 1.6

67 12 5 1.5 2 2.40 402 12.6

68 45 23 1 15 1.96 169 15.4

69 45 46 1 15 0.98 71.7 6.5

70 780 109 12 8 7.13 1,240 22.6

71 10 10 2 2 1.00 158 13.1

72 700 98 24 8 7.14 1,330 41.5

73 25 17 2 2 1.47 242 6.2

74 10 5 1 2 2.00 315 5.8

75 8.5 38 4 2 0.22 32.2 3.2

76 6 30 2 2 0.20 26.0 2.6
78 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table S2–1. Specific capacity data, transmissivity, and hydraulic conductivity for selected wells completed in the Ogallala aquifer in 

the study area.—Continued

Index 

number

(fig. 10)

Discharge rate 

(gallons per 

minute)

Drawdown

(feet)

Pumping time 

(hours)

Well radius 

(inches)

Specific capacity

(gallons per minute 

per foot of drawdown)

Transmissivity 

(square feet 

per day)

Hydraulic 

conductivity

(feet per day)

77 20 10 2 2 2.00 339 7.7

78 35 12 1 2 2.92 479 8.1

79 30 21 2 2 1.43 234 21.3

80 25 11 3 2 2.27 405 6.2

81 10 1 2 2 10.00 1,960 67.7

82 8 4 2 2 2.00 339 7.5

83 20 10 1 2 2.00 315 5.4

84 256 127 4 8 2.02 271 4.7

85 25 6 2 2 4.17 757 21.6

86 15 6 1 2 2.50 404 7.8

87 15 7 1 2 2.14 340 6.9

88 10 15 2 2 0.67 101 1.4

Transmissivity for the Ogallala aquifer was calculated using a form of the Theis and others (1963) nonequilibrium equation:

 

S T

Tt

r S

c

p

w

= 



 



 



 





4

2 25

2



ln . , (S2–1)

where

Sc is specific capacity, in gallons per day per foot of drawdown;

T is transmissivity, in gallons per day per foot;

t

p is pumping time, in days;

rw is the radius of the well, in feet; and

S is storativity (dimensionless).

The Theis and others (1963) method used in this analysis probably is the most common way to analytically estimate transmissivity from specific capacity (Mace, 2001).

The assumptions behind equation S2–1 are that the well is fully penetrating, the porous media is homogeneous and isotropic, the well loss is negligible, and the effective radius is equal to the radius of the production well (Mace, 2001). The equation 

was solved iteratively by rearranging equation S2–1 to solve for transmissivity (T) in the numerator (equation S2–2):

 

T S Tt

r S

c p

w

= 



 



 4

2 25

2 

ln . . (S2–2)

Values for specific capacity (Sc), pumping time (t

p

), and well radius (rw) were available from the well completion report, 

storage coefficient (S) was based on previously published values (table 3), and an initial estimate for the T in the numerator on 

the right side of equation S2–2 was used to calculate the T on the left side of equation S2–2. The calculated T was then substituted back into the numerator on the right side of equation S2–2, and this process was repeated using an iterative function until 

the T on the left side was within 0.01 gallons per day per foot of the T in the right side of equation S2–2.
Supplement 3. Analysis of Recharge and Evapotranspiration With a Soil-Water-Balance Method 79

Supplement 3. Analysis of Recharge and Evapotranspiration With a Soil-WaterBalance Method

This supplement describes the use of a soil-water-balance (SWB) method using the SWB software program developed by 

Westenbroek and others (2010) to determine the amount of recharge available to the Ogallala aquifer and the evapotranspiration 

from the aquifer. Two recharge simulations were completed using the SWB program, and the mean outputs were aggregated for 

use in the numerical model as described in the “Recharge” section of this report.

The SWB program uses daily precipitation and temperature data along with land cover, soil type, root depth, and runoff 

flow direction data to calculate runoff, evapotranspiration, and recharge. The SWB program can account for frozen ground, 

snowfall, snowmelt, and the dependency of recharge on the timing and spatial distribution of precipitation. A modified Thornthwaite-Mather soil-water accounting (Westenbroek and others, 2010) is used to calculate recharge as follows:

 recharge = (precipitation + snowmelt + inflow) – (interception + outflow + ET) – Δ(soil moisture), (S3–1)

where precipitation, snowmelt, and inflow are sources; interception, outflow, and evapotranspiration (ET) are sinks; and ∆soil 

moisture is the change in soil moisture as the amount of water added to or lost from the soil, with the maximum set by the holding capacity of the soil and the minimum set by the wilting point.

Runoff is calculated through the following equation (Westenbroek and others, 2010):

 

R

P I

P S I

a

max a

= ( ) −

( ) + − [ ]

2

, (S3–2)

where

R is runoff, in inches;

P is daily precipitation, in inches;

Ia is initial abstraction, the amount of precipitation that must fall before any runoff is generated, in inches; and

Smax is maximum soil-moisture holding capacity, in inches.

Daily precipitation (P) is greater than initial abstraction (Ia). The parameter Ia is related to maximum soil-moisture (Smax) 

through the following equation (Westenbroek and others, 2010):

 Ia = 0.2 Smax. (S3–3)

The maximum soil-moisture (Smax) is based on the Natural Resources Conservation Service curve number (CN; Curve 

Number Work Group, 2004) for a soil using the following equation (Westenbroek and others, 2010):

 

S

CN max = 



 



 − 1 000 10 , . (S3–4)

Two separate simulations were made using different climate inputs for the SWB program, one for each of two climate stations. Daily climatic data from two National Oceanic and Atmospheric Administration climate stations (Winner and Gregory, 

S. Dak., stations 399367 and 393452, respectively) were used as the climatic inputs for each of two simulations using the SWB 

program (fig. 11; National Oceanic and Atmospheric Administration, 2010). Daily climatic data for water years 1975–2009 

were used in the SWB model and included daily values for maximum and minimum temperature and total precipitation. Data 

for 1975–1984 were used as an initialization time period for the SWB program. Mean daily temperatures were calculated as the 

mean of the maximum and minimum daily values. For days of incomplete record, the mean precipitation for the month in which 

the missing record occurred and the mean daily precipitation during that month were used to create a synthetic precipitation 

record. One complete precipitation and temperature record for each station was used for two independent SWB model simulations, and outputs were averaged for input to MODFLOW_NWT. The precipitation data were in water-equivalent inches when 

the precipitation came in the form of snow (National Oceanic and Atmospheric Administration, 2010), and the SWB program 

used temperature data to determine when precipitation was snow (Westenbroek and others, 2010). The Hargreaves-Samani 

method of evapotranspiration calculation was chosen for use in the SWB program because only minimum, maximum, and mean 

temperature and precipitation data were required on a daily time step.
80 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

The flow direction grid was created from a resampled 30-meter [m; 98-foot (ft)] digital elevation model (DEM) of the study 

area (U.S. Geological Survey, 2006). The 30-m DEM was resampled to the 500-m (1,640-ft) grid that was used for the numerical groundwater-flow model (fig. 14). The SWB model only allows runoff to flow in one direction from a cell (Westenbroek 

and others, 2010), so cells that could have multiple runoff directions from the resampled DEM were examined and modified. If 

the runoff could flow in opposite directions, the cell was assigned an arbitrary number that was used for all depression cells. All 

depressions were allowed to infiltrate water from runoff the day the runoff was generated, but any ponding was removed at the 

start of the next day. The continuous frozen ground index (in degree Celsius-days) was used to increase the runoff resulting from 

precipitation or snowmelt that occurs while the ground is frozen. Antecedent moisture conditions are considered from the previous 5 days.

The hydrologic soil groups were assigned the designations A, B, C, D, C/D, and A/D based on soil survey data (fig. S3–1; 

Natural Resources Conservation Service, 2009a). The infiltration rate of each hydrologic soil groups A, B, C, and D was limited 

by the vertical hydraulic conductivity estimates of Long and Putnam (2010) for the Ogallala aquifer. Soil group A has the highest infiltration rate, and soil groups C and D has the lowest infiltration rate. The infiltration rate of combination soil groups was 

calculated from the mean of the two soil groups that were mixed (table S3–1).

Land-cover data for 2006 were obtained from Multi-Resolution Land Characteristics Consortium (2010) as 30-m (98-ft) 

raster data. The most prevalent land cover (fig. 3) was selected for each 500-m (1,640-ft) model cell (fig. 14). Each land cover 

was assigned values for interception storage in the growing seasons (table S3–2). For the dormant season, interception storage 

was assumed to be negligible. The growing season was set as the period from April 7 to October 26 and corresponds to the last 

and first frost occurrences each year for the climate station at Gregory, S. Dak. (station 393452; South Dakota State University, 

2011). Land cover and soil group were assigned to every cell in the model, and each combination of land cover and soil type was 

assigned a curve number and depth of root zone (table S3–2).

The curve number was identified for each soil type and land cover combination in the study area. Curve numbers were 

assigned based on classifications in the National Engineering Handbook (Curve Number Work Group, 2004). Land cover and 

soil group combinations were available for soil groups B, C, and D. Curve numbers for soil group A were determined by fitting a 

power trend function through the curve numbers plotted against soil groups B, C, and D. The curve number for combination soil 

groups was calculated from the mean of the two soil groups that were mixed.

The root zone depths were assigned as identical for every soil, but varied by land cover using data compiled by Canadell 

and others (1996) and Westenbroek and others (2010) because data were not sufficient to further constrain the inputs. The SWB 

model uses available water capacity for each root zone category to calculate the maximum amount of water that the soil can 

hold in storage (Westenbroek and others, 2010). The Natural Resources Conservation Service soil survey for Gregory and Tripp 

Counties contained available water capacity ranges for each horizon in every soil type (Natural Resources Conservation Service, 

2009b). The available water capacity ranges for each soil horizon were aggregated to determine a mean available water capacity for each individual soil type. The soil types were lumped according to hydrologic group, and the aggregate available water 

capacity data were averaged to generate one value per hydrologic group.
Supplement 3. Analysis of Recharge and Evapotranspiration With a Soil-Water-Balance Method 81

T. 40 N.T. 39 N.T. 38 N.T. 37 N.T. 36 N.T. 35 N.

R. 79 W. R. 78 W. R. 77 W. R. 76 W. R. 75 W. R. 74 W. R. 73 W. R. 72 W. R. 71 W. R. 70 W. R. 69 W. R. 68 W. R. 67 W. R. 66 W. R. 65 W.

Bonesteel

Burke

Dallas

Fairfax

Gregory

Herrick

Lake Andes

Pickstown

Platte

Colome

New

Witten

Winner

St. Charles

Bijou Hills

YTNUOC DDOT

LY

M

A

N CO

U

NTY

A

U

R

O

RA CO

U

NTY

BR

ULE CO

U

NTY

TRIPP CO

U

NTY

G

REG

O

RY CO

U

NTY

CH

A

RLES MIX CO

U

NTY

D

O

U

GLAS CO

U

NTY

KEYA PA

H

A CO

U

NTY BO

Y

D CO

U

NTY

FORT RANDALL 

DAM

R. 25 W. R. 24 W. R. 23 W. R. 22 W. R. 21 W. R. 20 W. R. 19 W. R. 18 W. R. 17 W. R. 16 W. R. 15 W. R. 14 W. R. 13 W. R. 12 W. R. 11 W. R. 10 W.

T. 101 N.T. 100 N.T. 99 N.T. 98 N.T. 97 N.T. 96 N.T. 95 N.

98°30' 99°00' 99°30' 100°00'

43°30'43°20'43°10'43°00'

ETTELLE M

YTNUOC

EXPLANATION

Hydrologic soil group (modified from Natural  Resources Conservation Service, 2009a)

AA/DBCC/DD

Base from U.S. Geological Survey digital data 1:100,000, 1980, 1982, 1983, 1985Universal Transverse Mercator projection, zone 14 0 5 10 15 20 MILES

0 5 10 15 20 KILOMETERS

SOUTH DAKOTA

NEBRASKA

1£¤8

28£¤1

18£¤3

18 ¤£

18£¤3

1£¤8

MISSOURI RIVER

LAKE FRANCIS 

CASE

mi T reb

eer C k

naS dCreek

soL Ct er ek

oC no Creek

Mud Creek

t Burn k

Roc

Creek

Lute Creek

East Cottonwood Creek

hS da el Cy er ek

Murphy Creek

Willow

Creek

Cottonwood Creek

tse W oC ott wn oo d C er ek

ar Btse W cn Bh l u Cl er ek

P al t et Creek

North Fork Whetstone Creek

Thunder Creek

South

Fork

Whetstone Creek

Bull Creek

Keya Paha River

Ponca Creek

Cottonwood

Creek

Dog Ear Creek

Figure S3–1. Map of soil type as defined for recharge calculations in soil-water-balance method in the study area.
82 Conceptual and Numerical Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota

Table S3–1. Infiltration rates assigned by soil type.

[Soil type designations are from Natural Resources Conservation Service 

(2009a)]

Infiltration rate for soil type

(inches per day)

A AD B C CD D

7.20 4.26 1.88 1.32 1.32 1.32

Table S3–2. Interception storage values and depth of root zone 

assigned by land-cover category.

[Land cover categories are from Multi-Resolution Land Characteristics 

Consortium (2010)]

Land-cover category

Interception 

storage, 

in inches

Depth of 

root zone, 

in feet

Open water 0.00 0.0

Developed, open space 0.06 2.0

Developed, low intensity 0.08 2.0

Developed, medium intensity 0.08 2.0

Developed, high intensity 0.08 2.0

Deciduous forest 0.09 4.5

Evergreen forest 0.11 5.5

Herbaceous grassland 0.09 4.0

Pasture/hay 0.09 4.0

Cultivated crops 0.09 3.5

Woody wetlands 0.05 4.5

Emergent herbaceous wetlands 0.00 2.0
Publishing support provided by: 

Pembroke and Rolla Publishing Service Centers 

For more information concerning this publication, contact:

Director, USGS South Dakota Water Science Center

1608 Mountain View Road

Rapid City, South Dakota 57702

(605) 394–3200

Or visit the South Dakota Water Science Center Web site at: 

http://sd.water.usgs.gov/
Davis and Putman—Models of Groundwater Flow in the Ogallala Aquifer in Gregory and Tripp Counties, South Dakota—SIR 2013–5069