U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2014–5241

Prepared in cooperation with the Oglala Sioux Tribe

Conceptual and Numerical Models of Groundwater Flow 

in the Ogallala and Arikaree Aquifers, Pine Ridge Indian 

Reservation Area, South Dakota, Water Years 1980–2009
Cover photograph. West branch of Cottonwood Creek about 4 miles east of Wanblee, South Dakota. Cottonwood Creek is a tributary to the 

White River and is fed by seeps or springs at originate from the Arikaree aquifer. Photograph taken on September 22, 2010, by Larry Putnam, 

U.S. Geological Survey.
Conceptual and Numerical Models of 

Groundwater Flow in the Ogallala and 

Arikaree Aquifers, Pine Ridge Indian 

Reservation Area, South Dakota, Water 

Years 1980–2009

By Kyle W. Davis, Larry D. Putnam, and Anneka R. LaBelle

Prepared in cooperation with the Oglala Sioux Tribe

Scientific Investigations Report 2014–5241

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: 2015

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Suggested citation:

Davis, K.W., Putnam, L.D., and LaBelle, A.R., 2015, Conceptual and numerical models of groundwater flow in the 

Ogallala and Arikaree aquifers, Pine Ridge Indian Reservation area, South Dakota, water years 1980–2009: U.S. Geological Survey Scientific Investigations Report 2014–5241, 68 p., http://dx.doi.org/10.3133/sir20145241.

ISSN 2328–0328 (online)
iii

Acknowledgments

The authors would like to recognize important contributions made by the Oglala 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 lithologic database of the South Dakota Department of Environment and 

Natural Resources Geological Survey and the Nebraska Statewide Test-hole Database from the 

University of Nebraska were 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.

v

Contents

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

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

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

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

Previous Investigations........................................................................................................................5

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

Physiography, Drainage Features, and Land Use ...........................................................................5

Climate....................................................................................................................................................6

Geologic Setting....................................................................................................................................6

Hydrogeologic Setting .........................................................................................................................8

Conceptual Model........................................................................................................................................11

Hydrogeologic Framework................................................................................................................12

Groundwater Flow .....................................................................................................................12

Ogallala Aquifer ................................................................................................................12

Arikaree Aquifer................................................................................................................18

Water Budget Components...............................................................................................................18

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

Discharge....................................................................................................................................22

Evapotranspiration ...........................................................................................................22

 Discharge to Streams .....................................................................................................24

Water Use ..........................................................................................................................24

Hydraulic Properties...........................................................................................................................28

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

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

Assumptions ........................................................................................................................................29

Model Design.......................................................................................................................................30

Finite-Difference Grid and Boundary Conditions .................................................................31

Hydrogeologic Representation................................................................................................31

Hydraulic Properties ........................................................................................................31

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

Discharge...........................................................................................................................34

Evapotranspiration ..................................................................................................34

Discharge to Streams .............................................................................................34

Water Use .................................................................................................................37

Model Calibration................................................................................................................................37

Calibration Targets.....................................................................................................................38

Calibrated Parameters..............................................................................................................40

Sensitivity Analysis....................................................................................................................40

Comparison of Simulated and Observed Values ..................................................................41

Simulated Water Budgets ........................................................................................................46

Hypothetical Simulations...................................................................................................................49

Model Limitations................................................................................................................................58
vi

Summary........................................................................................................................................................62

References Cited..........................................................................................................................................64

Appendix 1. Water-Level Data Used to Estimate Generalized Potentiometric Surface of 

Ogallala Aquifer..............................................................................................................................67

Figures

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

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

2. Map showing land-surface altitude, streamgages, and precipitation stations in the

study area ......................................................................................................................................4

3. Map showing generalized land use in the study area............................................................7

4. Map showing generalized surface geology in the study area..............................................9

5. Map showing location of aquifer extents and test holes and wells with lithologic

logs in the study area.................................................................................................................13

6. Map showing altitude of the bottom of the Ogallala aquifer in the study area................14

7. Map showing altitude of the bottom of the Arikaree aquifer in the study area...............15

8. Map showing generalized potentiometric surface of the Ogallala aquifer in the

study area ....................................................................................................................................16

9. Map showing generalized potentiometric surface of the Arikaree aquifer in the

study area ....................................................................................................................................17

10. Map showing saturated thickness of the Ogallala aquifer in the study area ..................19

11. Map showing saturated thickness of the Arikaree aquifer in the study area..................20

12. Map showing recharge zones and selected National Oceanic and Atmospheric

Administration precipitation stations in the study area.......................................................21

13. Map showing location of production wells completed in the Ogallala and Arikaree

aquifers in the study area..........................................................................................................27

14. Map showing boundary conditions for model layers 1 and 2 in the study area ..............32

15. Map showing location of pilot points used for interpolation of horizontal hydraulic

conductivity to the model domain in the study area.............................................................33

16. Map showing specific yield zones and associated model parameters for model

layer 2 representing the Arikaree aquifer in the study area ...............................................35

17. Map showing stream reaches represented with MODFLOW–2005 River and Drain

packages, streambed conductance parameters, selected contributing drainage

areas, and streamgages for modeled streams in the study area.......................................36

18. Map showing calibrated horizontal hydraulic conductivity for model layer 1

representing the Ogallala aquifer in the study area.............................................................42

19. Map showing calibrated horizontal hydraulic conductivity for model layer 2

representing the Arikaree aquifer in the study area ............................................................43

20. Graph showing relative composite parameter sensitivities, as defined by Doherty

 (2010), for the numerical model ...............................................................................................44

21. Map showing comparison of simulated potentiometric surface to the generalized

potentiometric surface for the Ogallala aquifer for the steady-state simulation in

the study area..............................................................................................................................45

22. Map showing mean difference between simulated and observed hydraulic heads 

for long-term observation wells completed in the Ogallala aquifer in the study area 

for the transient simulation, water years 1980–2009 ............................................................47
vii

23. Map showing difference between simulated and observed hydraulic heads for

wells completed in the Ogallala aquifer in the study area with a single

measurement for the transient simulation, water years 1980–2009...................................48

24. Graphs showing simulated and observed hydraulic heads for the transient

simulation for selected observation wells completed in the Ogallala aquifer in the

study area ....................................................................................................................................49

25. Map showing comparison of the simulated potentiometric surface to the

generalized potentiometric surface for the Arikaree aquifer for the steady-state

simulation in the study area......................................................................................................50

26. Map showing mean difference between simulated and observed hydraulic heads

for long-term observation wells completed in the Arikaree aquifer in the study area

for the transient simulation, water years 1980–2009 ............................................................52

27. Map showing difference between simulated and observed hydraulic head for wells

completed in the Arikaree aquifer in the study area with a single measurement for

the transient simulation, water years 1980–2009 ..................................................................53

28. Graphs showing simulated and observed hydraulic heads for the transient

simulation for selected observation wells completed in the Arikaree aquifer in the

study area ....................................................................................................................................54

29. Graphs showing simulated and estimated discharge for stream reaches with

gaged streamflow in the study area........................................................................................56

30. Map showing simulated difference in hydraulic head in the Arikaree aquifer in the

study area between the end of the calibrated simulation and the end of the 30-year

simulation with 50 hypothetical wells completed in the Arikaree aquifer

withdrawing 0.2 cubic foot per second...................................................................................59

31. Graph showing change in simulated water budget components in the study area

based on hypothetical additional withdrawals of 0.2 cubic foot per second at 50

hypothetical wells completed in the Arikaree aquifer compared to the calibrated

simulation.....................................................................................................................................60

32. Map showing difference in hydraulic head in the Arikaree aquifer in the study area

between the end of calibrated simulation and the end of the hypothetical 30-year 

drought simulation......................................................................................................................61

33. Graph showing change in simulated water budget components for the Arikaree

aquifer in the study area based on the hypothetical drought simulation when

compared to the calibrated simulation ...................................................................................62
viii

Tables

1. Precipitation for water years 1980–2009 for three precipitation stations in the study

area .................................................................................................................................................8

2. Mean monthly precipitation for water years 1980–2009 for National Oceanic and

Atmospheric Administration station 395281.............................................................................8

3. Generalized stratigraphic column with geologic map units and lithology in study

area ...............................................................................................................................................10

4. Estimated recharge to Ogallala and Arikaree aquifer in the study area for water

years 1980–2009 by recharge zone..........................................................................................22

5. Estimated maximum potential evapotranspiration rate in the study area, water

years 1980–2009 ..........................................................................................................................25

6. Streamgages in study area.......................................................................................................26

7. Estimated base-flow contribution to streamflow at streamgages in the study area......26

8. Estimated groundwater withdrawals for water years 1980–2009 in the study area .......28

9. Total population for Bennett, Jackson, and Shannon Counties and estimated

public-supply domestic water deliveries for South Dakota per capita per day, 1995,

2000, and 2005..............................................................................................................................29

10. Previously published horizontal hydraulic properties for the Ogallala and Arikaree

aquifers in or near the study area............................................................................................30

11. Stream reach identifier, conductance parameter, and observation weights for

modeled streams in the study area .........................................................................................37

12. Calibration targets for groundwater discharge for selected stream reaches.................39

13. Calibrated transient recharge rates by recharge zone........................................................41

14. Calibrated streambed conductance for stream reaches represented in model .............41

15. Difference between simulated and observed hydraulic heads for long-term

observation wells completed in the Ogallala aquifer for the transient simulation,

water years 1980–2009...............................................................................................................46

16. Difference between simulated and observed hydraulic heads for long-term

observation wells completed in the Arikaree aquifer in the study area for the

transient simulation, water years 1980–2009 .........................................................................51

17. Mean simulated groundwater discharge to stream reaches in the study area for

transient simulation, water years 1980–2009 .........................................................................55

18. Water budget for steady-state and transient simulations for selected water years......57

19. Water budget for transient simulation for dry and wet water years by model layer 

in the study area .........................................................................................................................58

1–1. Selected data from wells used for generalized potentiometric surface of Ogallala

aquifer in the study area............................................................................................................67
ix

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 0.4047 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 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)

Hydraulic conductivity

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

Transmissivity*

foot squared per day (ft2/d) 0.09290 meter squared per day (m2/d) 

Conductance

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

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

°C=(°F-32)/1.8

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

(NAVD 88).

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.

*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.

Water year (WY) is the 12-month period, October 1 through September 30, and is designated by 

the calendar year in which it ends.
x

Abbreviations

NAVD 88 North American Vertical Datum of 1988

NED National Elevation Dataset

NOAA National Oceanic and Atmospheric Administration

PEST Parameter ESTimation (computer code)

UPW Upstream Weighting (MODFLOW–NWT package)

USGS U.S. Geological Survey

WY water year
Conceptual and Numerical Models of Groundwater Flow 

in the Ogallala and Arikaree Aquifers, Pine Ridge Indian 

Reservation Area, South Dakota, Water Years 1980–2009

By Kyle W. Davis, Larry D. Putnam, and Anneka R. LaBelle

Abstract

The Ogallala and Arikaree aquifers are the largest sources 

of groundwater on the Pine Ridge Indian Reservation and are 

used extensively for irrigation and public and domestic water 

supplies. To assess the potential for decreased water levels and 

discharge to streams in the Pine Ridge Indian Reservation, conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers in southwestern South Dakota were 

developed by the U.S. Geological Survey in cooperation with 

the Oglala Sioux Tribe. The study area includes most of the Pine 

Ridge Reservation in Jackson and Shannon Counties and Indian 

trust lands in Bennett County in southwestern South Dakota.

The High Plains aquifer, which includes the Ogallala and 

Arikaree aquifers, generally is less developed in South Dakota 

compared with other areas underlain by this aquifer; therefore, water levels in the High Plains aquifer in South Dakota 

generally fluctuated by less than 5 feet (ft) from 1980 to 1999. 

Despite minimal water-level changes in the High Plains aquifer 

in South Dakota, extensive withdrawals of groundwater for 

irrigation have caused water-level declines in many areas and 

increased concerns about the long-term sustainability of the 

aquifer; 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 Ogallala and Arikaree aquifers generally consist of 

poorly consolidated claystones, siltstones, sandstones, and shale 

deposited in fluvial and lacustrine environments. Saturated 

thicknesses ranged from 10 to 314 ft for the Ogllala aquifer and 

from 10 to 862 ft for the Arikaree aquifer. Previous hydraulic 

conductivity estimates ranged from less than 1 to 180 feet per 

day (ft/d) for the Ogallala aquifer and from less than 1 to 13 ft/d 

for the Arikaree aquifer.

Recharge to the Ogallala and Arikaree aquifers is from 

precipitation on the outcrop areas, and discharge 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. 

The generalized groundwater-flow direction is to the 

northeast with local flow towards streams. Precipitation for 

water years 1980–2009 ranged from about 11 to 39 inches 

per year (in/yr) and averaged about 19 in/yr. Estimated mean 

recharge for water years 1980–2009 was about 17.3 percent 

of precipitation for the Ogallala aquifer and 7.9 percent of 

precipitation for the Arikaree aquifer. The estimated mean 

maximum evapotranspiration for water years 1980–2009 was 

about 35 in/yr. Estimated mean base flow for gaged streams 

was about 0.06 cubic foot per second (ft3/s) per square mile of 

drainage area. Estimated mean total water use for water years 

1980–2009 was 5.4 ft3/s from the Ogallala aquifer and 7.1 ft3/s 

from the Arikaree aquifer.

A two-layer numerical groundwater-flow model was 

constructed using MODFLOW–NWT with a uniformly 

spaced grid consisting of 166 rows and 288 columns with cells 

1,640 ft on a side. The numerical model of the Ogallala and 

Arikaree aquifers was used to simulate steady-state and transient conditions for water years 1980–2009. Model calibration 

was accomplished using the Parameter ESTimation (PEST) 

program that adjusted individual model input parameters 

and assessed the difference between estimated and modelsimulated values of hydraulic head and base flow. Aquifer 

boundaries were no-flow on the northern and western sides 

and constant-head on the southern and eastern sides. The mean 

arithmetic difference was 1.4 ft between the 731 simulated 

and observed hydraulic heads in the Ogallala aquifer and 9.8 ft 

between the 2,754 simulated and observed hydraulic heads 

in the Arikaree aquifer. Simulated mean discharge from the 

Ogallala and Arikaree aquifers to selected stream reaches was 

92.1 ft3/s compared to estimated discharge of 88.7 ft3/s.

Calibrated recharge for the transient simulation averaged 

3.3 in/yr for the Ogallala aquifer and 1.1 in/yr for the Arikaree aquifer. The mean maximum potential evapotranspiration 

rate was 35.4 in/yr. Streambed conductance for perennial 

stream reaches averaged 530 feet squared per day. Horizontal 

hydraulic conductivity averaged 27 ft/d for the Ogallala aquifer and 1.0 ft/d for the Arikaree aquifer. The vertical hydraulic 

conductivity averaged 1.4 ft/d for the Ogallala aquifer and 

0.004 ft/d for the Arikaree aquifer. Specific yield for the Ogallala aquifer was 0.15 (dimensionless) and averaged 0.02 for 
2 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

the Arikaree aquifer. Specific storage for the Arikaree aquifer 

was 1.7x10-6 per foot. Simulated steady-state model inflow 

and outflow was 459 ft3/s. The percentages of inflows were 

17 percent from constant-head boundaries, 9 percent from 

streams, and 74 percent from recharge. Percentages of outflow 

were 8 percent to constant-head boundaries, 1 percent to wells, 

31 percent to streams, and 59 percent to evapotranspiration. 

Simulated net inflow from the Ogallala aquifer to the Arikaree 

aquifer ranged from about 22 ft3/s in dry years to about 37 ft3/s 

in wet years.

Two hypothetical future stress scenarios were simulated 

using input from the 30-year calibrated simulation of water 

years 1980–2009. The first hypothetical scenario represented 

an increase in groundwater withdrawals from 50 hypothetical 

production wells completed in the Arikaree aquifer. At the end 

of the 30-year hypothetical increased pumping simulation, 

water levels declined as much as 66 ft in the Arikaree aquifer, 

decreased discharge to streams accounted for about 26 percent 

(2.6 ft3/s) of increased withdrawals, and decreased evapotranspiration accounted for about 53 (5.3 ft3

/s) percent of increased 

withdrawals.

The second hypothetical scenario represented a 30-year 

period of decreased recharge (drought) by decreasing recharge 

0.2 inch (24 ft3/s) for each water year. At the end of the 

hypothetical drought simulation, water levels declined as 

much as 10.9 ft in the Arikaree aquifer, decreased discharge to 

streams accounted for about 23 percent (5.5 ft3/s) of decreased 

recharge, and decreased evapotranspiration accounted for 

about 72 percent (17.3 ft3/s) of decreased recharge.

The numerical model is a tool that could be used to better understand the flow system of the Ogallala and Arikaree 

aquifers, to approximate hydraulic heads in the aquifer, and 

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

Ridge Reservation area in Bennett, Jackson, and Shannon 

Counties. The model also is useful to help assess the response 

of the aquifer to additional stress, including potential increased 

well withdrawals and potential drought conditions.

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 water supply, domestic 

water supply, and stock water use, and is an important water 

supply for the central United States. About 2 million people 

rely on the High Plains aquifer for drinking water with total 

withdrawals for domestic drinking water 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 in south-central South Dakota (fig. 1; Gutentag and 

others, 1984) including most of the Pine Ridge Indian Reservation area. The Pine Ridge Indian Reservation includes all 

of Shannon County and part of Jackson County south of the 

White River (fig.1; fig. 2). Extensive Indian trust lands are 

in Bennett County. The study area includes most of the Pine 

Ridge Indian Reservation in Jackson and Shannon Counties 

and trust lands in Bennett County. The study area is in the 

Great Plains physiographic division (Fenneman, 1946) in the 

northern High Plains aquifer region (fig. 1; Luckey and others, 

1988).

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 declines 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 declines 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; Carter 

and Heakin, 2007); 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 Ogallala and Arikaree aquifers are the largest sources 

of groundwater on the Pine Ridge Indian Reservation and are 

used extensively for irrigation and public and domestic water 

supplies. The Oglala Sioux Tribe has identified a need for 

scientific information and tools for use in the management, 

planning, and protection of these important water resources. 

The U.S. Geological Survey (USGS), in cooperation with 

the Oglala Sioux Tribe, developed conceptual and numerical 

models of the Ogallala and Arikaree aquifers to meet this need 

for scientific information. The numerical model is a waterresource tool used to analyze the groundwater system that can 

be used to assess water-management issues associated with the 

High Plains aquifer in the Pine Ridge Indian Reservation area. 

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

The purpose of this report is to describe conceptual and 

numerical models of groundwater flow in the Ogallala and Arikaree aquifers in the Pine Ridge Indian Reservation area. The 

conceptual model was developed based on hydrologic data 

for water years (WYs) 1980–2009 (October 1, 1979, through 

September 30, 2009). A WY is a 12-month period, October 1 
Introduction 3

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North Loup River

Loup River

Lodgepole Creek

Big Blue River

South Platte River

Republican River

Arikaree River

North Platte 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

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Ponca Creek

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Study area

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Little White River

PINE RIDGE

INDIAN

RESERVATION ROSEBUD

INDIAN

RESERVATION

106° 105° 104° 103° 102° 101° 100° 99° 98° 97°

44°

43°

42°

41°

40°

39°

0 30 60 90 120 MILES

0 30 60 90 120 KILOMETERS

EXPLANATION

Northern High Plains aquifer boundary

Physiographic division (modified from Fenneman, 1946)

Nebraska Sand Hills (Stanton and others, 2011)

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

Universal Transverse Mercator projection, Zone 14

Study

area

Central High Plains

Southern High Plains

High Plains aquifer

Aquifer extent modified from Qi, 2010

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 and Arikaree Aquifers

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EXPLANATION

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#06449000

! 395281

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Missouri River

NEBRASKA

SOUTH DAKOTA

! 391972

Study area

TODD COUNTY

MELLETTE COUNTY

Figure 2. Land-surface altitude, streamgages, and precipitation stations in the study area.
Description of Study Area 5

through September 30, and is designated by the calendar year 

in which it ends. Steady-state and transient numerical simulations for the 30-year period are described in this report. This 

report also documents numerical simulation of two potential 

future scenarios. The first scenario represented an increase in 

groundwater withdrawals from 50 hypothetical production 

wells, and the second scenario represented a potential 30-year 

period of decreased recharge (drought).

Previous Investigations

Kolm and Case (1983), Long and others (2003), Long 

and Putnam (2010), and Davis and Putnam (2013) previously 

developed groundwater models of the High Plains aquifer 

near the study area. Kolm and Case (1983) developed a twodimensional, finite-difference model of the High Plains aquifer 

within South Dakota. The model included parts of the Pine 

Ridge Indian Reservation and Bennett County in South Dakota 

and documented the generalized groundwater flow within the 

High Plains aquifer in South Dakota and northern Nebraska. 

Long and others (2003) developed a two-layer model of the 

Ogallala and Arikaree aquifers in Todd County and the southern part of Mellette County in the Rosebud Indian Reservation 

area, which is located directly east of the Pine Ridge Indian 

Reservation and in the central part of the High Plains aquifer 

in South Dakota (fig. 1). This model simulated groundwater flow of the Ogallala and Arikaree aquifers with a much 

smaller grid spacing compared to the model produced by 

Kolm and Case (1983). Long and Putnam (2010) updated the 

model developed by Long and others (2003) with additional 

data and simulations of hypothetical drought and increased 

groundwater withdrawal. Davis and Putnam (2013) developed 

conceptual and numerical models of groundwater flow for the 

Ogallala aquifer in Gregory and Tripp Counties, which are 

located east of Mellette and Todd Counties.

The hydrogeology of Pine Ridge Indian Reservation was 

described by Ellis and Adolphson (1971) and was further studied in 1987–89 with aquifer tests (Greene and others, 1991). 

Greene and others (1991) provided hydraulic characteristics 

of the Arikaree aquifer, including transmissivity, storage, and 

hydraulic conductivity. Carter and Heakin (2007) published a 

map of the generalized potentiometric surface of the Arikaree 

aquifer for the Pine Ridge Indian Reservation area and Bennett 

County. Filipovic (2011) conducted a hydrogeologic assessment of the High Plains aquifer in Bennett County, which 

included descriptions and interpretations of additional test 

hole data. LaBelle (2011) analyzed historical (1985–2009) and 

projected (2041–70) recharge trends near the Pine Ridge Reservation with a soil-water balance method. For the eastern part 

of the High Plains aquifer in South Dakota, Filipovic (2004) 

published a generalized water table and saturated thickness 

map and developed cross sections for the Ogallala aquifer in 

Gregory and Tripp Counties.

Description of Study Area

The study area includes most of the Pine Ridge Reservation in Shannon and Jackson Counties, Bennett County, small 

parts of Mellette and Todd Counties in South Dakota, and the 

northern edges of Cherry and Sheridan Counties in Nebraska 

where the Ogallala and Arikaree aquifers are present (fig. 2). 

The study area was extended southward into Nebraska and 

eastward into Mellette and Todd Counties in South Dakota to 

minimize effects of the southern and eastern boundaries in the 

numerical model.

Physiography, Drainage Features, and Land Use

The study area is located in the Great Plains physiographic division (Fenneman, 1946). The southern part of the 

study area is overlain by the Nebraska Sand Hills (Stanton and 

others, 2011; fig. 1). The Great Plains physiographic division 

is a vast eastward-tilted surface formed by the deposition of 

sediment from the uplift of the Rocky Mountains during the 

early Tertiary Period (University of Nebraska–Lincoln, 2011). 

The Nebraska Sand Hills is the largest field of grass-stabilized 

sand dunes in the Western Hemisphere (Koch, 1999). The 

Nebraska Sand Hills was developed on the northern Tertiaryage High Plains deposits and was undergoing dune formation 

and migration as recently as 700 years ago (Miao and others, 

2007).

The topography of the study area is diverse. Gently rolling plains are present throughout the study area. The Badlands, 

with sharply rising pinnacles, are located in the northwestern corner of the study area. The altitude of the land surface 

determined from the National Elevation Dataset (NED; U.S. 

Geological Survey, 2006) ranges from about 4,025 ft above 

the North American Vertical Datum of 1988 (NAVD 88) at 

the southern part of the study area to about 2,100 ft above 

NAVD 88 in the northeastern part of the study area (fig. 2). As 

intermittent and perennial streams drain north into the White 

River along the western and northern sides of the study area, 

the streams become more deeply incised into bedrock. Sand 

dunes are evident in the southern and southeastern parts of 

the study area where the Sand Hills are at an altitude of about 

3,700 ft above NAVD 88 on the western edge decreasing to 

about 3,400 ft above NAVD 88 on the eastern side of the study 

area.

The major streams that drain the study area are the White 

River and the Little White River. The White River, the Little 

White River, and their tributaries receive base flow from the 

Ogallala and Arikaree aquifers (Ellis and Adolphson, 1971; 

Kolm and Case, 1983). Perennial streamflow in major tributaries to the White River is sustained by a large component of 

base flow from the Arikaree aquifer (Carter and Heakin, 2007). 

The minimum monthly mean streamflow for 1960–2011 at 

USGS streamgage 06449100, which is located on the Little 

White River near the border of Bennett and Todd Counties 
6 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

(fig. 2), ranged from 12.5 to 33.5 cubic feet per second (ft3/s; 

U.S. Geological Survey, 2012).

The altitude of the Little White River ranges from about 

3,600 ft above NAVD 88 near its headwaters to about 2,800 ft 

above NAVD 88 near the eastern edge of the study area (fig. 2). 

The altitude of Wounded Knee Creek is about 3,800 ft above 

NAVD 88 at the southern edge of the study area and about 

2,700 ft above NAVD 88 near its confluence with the White 

River.

Agriculture is the primary land use in the study area, and 

the primary agricultural activities are cattle grazing and hay 

production (Tetra Tech, Inc., 2005). Cultivated crops are areas 

used for the production of annual crops, land that is actively 

tilled, and where crop vegetation accounts for greater than 

20 percent of total vegetation (Homer and others, 2004). Cultivated crops cover about 7 percent of the study area, primarily 

in west-central Bennett County (fig. 3). Pasture and hay cover 

about 1 percent of the study area. Herbaceous grasslands are 

any areas dominated by grammanoid or herbaceous vegetation, generally greater than 80 percent of total vegetation. 

These areas are not subject to intensive management such as 

tilling, but can be used for grazing (Homer and others, 2004). 

Herbaceous grasslands accounts for about 76 percent of the 

land use within the study area. Barren land covers about 7 percent of the study area and exists in and near Badlands National 

Park in the northwestern part of the study area. Deciduous, 

evergreen, or mixed forest and shrub or scrubs account for 

about 4 percent of the land use. The remaining 5 percent of 

land use is woody wetlands, emergent herbaceous wetlands, 

open water, or developed areas.

Climate

The climate is arid steppe, with hot summers and cold 

winters. The arid steppe cold climate is described as a climate 

with a mean annual temperature less than 64 degrees Fahrenheit (°F) that is too dry to support a forest, but not quite dry 

enough to be considered a desert, usually consisting of grassland plains (Peel and others, 2007).

Precipitation records were available for four National 

Oceanic and Atmospheric Administration (NOAA) precipitation stations in the study area (fig. 2): 395281 (Martin), 

395285 (Martin 5E), 394983 (Long Valley), and 396736 (Porcupine 11N) (National Climate Data Center, 2011). Precipitation data for NOAA station 395281 (Martin) were combined 

with NOAA station 395285 (Martin 5E) to create a complete 

record for WYs 1980–2009. Precipitation for WYs 1980–92 

and 1996–98 was from station 395285; precipitation for WYs 

1993–95 and 1999–2009 was from station 395281. The combined stations are referred to as station 395281 in this report. 

The other two stations (394983 and 396736) had records for 

WYs 1980–2009. Precipitation for WYs 1980–2009 for stations 395281, 394983, and 396736 in the study area ranged 

from about 11 to 39 inches per year (in/yr; table 1). The mean 

precipitation in the study area was about 19 in/yr with means 

for WYs 1980–2009 of 19.8, 19.6, and 17.9 in/yr at stations 

395281, 394983, and 396736, respectively. Extended periods 

of above average precipitation occurred during WYs 1995–99, 

and below average periods occurred during WYs 1987–90 and 

WYs 2002–04.

Precipitation generally increases in the spring and early 

summer, then decreases through the summer and fall with little 

precipitation in the winter months. Mean monthly precipitation for WYs 1980–2009 for station 395281 (Martin) indicates 

greater than 3 inches (in.) of precipitation in May and June 

with less than 2 in. per month in September through March 

(table 2).

Geologic Setting

The exposed geologic formations in the study area 

range from sedimentary rocks of Late Cretaceous age to 

unconsolidated deposits of Quaternary age (Martin and others, 2004; Stoeser and others, 2007; fig. 4). Cretaceous-age 

deposits are mostly shale, and the exposed units from oldest 

to youngest include the Carlile Shale, Niobrara Formation, 

and Pierre Shale (fig. 4). Tertiary-age rocks generally consist 

of poorly consolidated claystones, siltstones, sandstones, and 

shale deposited in fluvial and lacustrine environments. These 

include the Oligocene-age White River Group, the Mioceneage Arikaree Formation and Batesland Formation, and the 

Pliocene-age Ogallala Formation. Quaternary-age deposits 

include Holocene-age alluvial deposits and Holocene- and 

Pleistocene-age eolian deposits. The eolian (windblown) 

deposits include the Holocene- and Pleistocene-age Sand Hills 

Formation in the southern part of the study area. The lithology 

and thickness of mapped units and subdivisions are described 

in table 3.

The White River Group and older deposits generally are 

at the surface in the northern and western edges of the study 

area (fig. 4). The Arikaree Formation is present in most of the 

study area south and east of the White River. The maximum 

thickness of the Arikaree Formation ranges from about 800 ft 

in the southwestern part of the study area (Greene and others, 

1991) to about 500 ft in the southeastern part of the study area 

(Carter, 1998). The five subdivisions within the Arikaree Formation vary substantially in thickness (table 3) and, in many 

parts of the study area, are undifferentiated. Harksen (1965) 

described the thicknesses of the subdivisions present in the 

area near Porcupine and Wounded Knee Creeks as 350 ft for 

the Sharps Formation, 120 ft for the Monroe Creek Formation, 

160 ft for the Harrison Formation, and 235 ft for the Rosebud 

Formation. The Sharps and Monroe Formations outcrop in 

south-central Jackson County (Collins, 1960). The Rockyford 

Ash member of the Sharps Formation caps buttes and tables in 

the northwestern part of the study area and is widely but discontinuously exposed (Greene and others, 1991). The Arikaree 

Formation pinches out to the north and northwest where the 

White River Group is exposed (fig. 4).
Description of Study Area 7

W

HITE

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

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White

Little Whi et R vi er

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

eB ar- ni -the-Lodge Creek

Eagle Nest Creek

Spring Creek

Medicine Root Creek

River 18 £¤ 18 £¤

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Martin

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps Corner

Swett

Allen

Oglala

Tuthill

Wanblee

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

EXPLANATION

Generalized land use (modified from Homer and others, 2004)

Cultivated crops or pasture and hayHerbaceous grasslandDeciduous, evergreen, or mixed forest and shrub or scrubBarren landWoody wetlands, emergent herbaceous wetlands, or open waterDeveloped areas, various categories

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Figure 3. Generalized land use in the study area.
8 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 1. Precipitation for water years 1980–2009 for three 

precipitation stations in the study area.

[Precipitation data for National Oceanic and Atmospheric Administration 

(NOAA) stations from National Climate Data Center (2011). Shaded cells 

indicate an incomplete daily precipitation record for a given water year. 

Missing values were supplemented with daily precipitation from the nearest 

precipitation station]

Water year

Precipitation (inches per year)

395281a,b

(Martin)

394983c

(Long Valley)

396736c

(Porcupine 11N)

1980 11.9 10.6 10.7

1981 19.8 17.3 12.6

1982 24.1 24.5 20.4

1983 23.7 23.0 17.8

1984 17.1 15.8 15.6

1985 13.0 12.2 12.2

1986 27.1 26.8 21.2

1987 15.7 17.8 14.7

1988 15.4 19.7 15.2

1989 10.7 11.6 12.3

1990 19.2 18.9 14.8

1991 24.1 18.3 17.3

1992 17.4 17.0 20.3

1993 20.4 25.0 24.7

1994 18.9 15.2 16.9

1995 26.5 25.3 22.0

1996 22.2 25.5 20.8

1997 27.9 24.3 25.9

1998 24.4 22.2 15.9

1999 39.4 24.8 28.6

2000 16.7 16.8 17.7

2001 18.2 19.1 19.5

2002 11.9 13.0 15.0

2003 14.0 14.7 12.8

2004 18.2 15.7 15.1

2005 24.1 25.3 21.0

2006 14.5 16.6 18.8

2007 16.5 18.7 16.1

2008 18.8 24.0 20.5

2009 23.2 29.1 20.2

Mean 

annual 19.8 19.6 17.9

a

Precipitation for water years 1980–1992 and 1996–1998 was from NOAA 

station 395285.

b

Missing daily values were supplemented with daily values from NOAA 

station 394983.

c

Missing daily values were supplemented with daily values from NOAA 

station 396736.

Table 2. Mean monthly precipitation for water years 1980–

2009 for National Oceanic and Atmospheric Administration 

station 395281 (Martin).

[Precipitation data from National Climate Data Center (2011)]

Month

Mean monthly 

precipitation 

(inches)

January 0.3

February 0.6

March 1.3

April 2.0

May 3.2

June 3.3

July 2.5

August 2.0

September 1.5

October 1.6

November 1.1

December 0.4

Martin (fig. 4). The Batesland Formation is fill in paleo-valleys 

that are cut down into the Rosebud Formation. Most of the 

Batesland Formation has been removed by subsequent erosion 

(Harksen and Macdonald, 1967).

The Ogallala Formation includes two units: the upper, 

Ash Hollow Formation, and the lower, Valentine Formation 

(table 3; Carter and Heakin, 2007). The Ogallala Formation 

ranges in thickness from 0 to 200 ft in the study area. The 

Valentine Formation is poorly consolidated and slumps and 

washes easily. Most of the Valentine Formation is overlain 

by the eolian deposits with some exposed areas southeast of 

Martin (Collins, 1959). The Ash Hollow Formation is exposed 

in the area east of Pine Ridge and is more resistant to erosion 

than the underlying Rosebud Formation (Harksen, 1965). 

The Ogallala Formation crops out in the southern and eastern 

part of the study area, mostly south of the Little White River 

(fig. 4) where not overlain by the eolian deposits. The Sand 

Hills Formation (eolian deposits) consists mainly of fine sands 

derived from the Ogallala Formation and the Rosebud Formation (Harksen, 1965; Collins, 1959). Individual dunes may rise 

as much as 160 ft above their base and most are 80 to 120 ft in 

height (Collins, 1959).

Hydrogeologic Setting

The major shallow aquifers from top to bottom include 

the alluvial, Ogallala, and Arikaree aquifers. These aquifers 

consist of unconsolidated sand and gravels or poorly consolidated sandstones and siltstones. The White River Group 

The Batesland Formation is exposed in small areas west of 
Description of Study Area 9

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

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White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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agle Nest Creek

Spring Creek

Medicine Root Creek

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Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

EXPLANATION

Quaternary-age unconsolidated 

deposits

Alluvial deposits Qal

Terrace and landslide deposits Qt

Eolian deposits Qe

Tertiary-age sedimentary 

deposits

Gravel deposits TgOgallala Formation To

Batesland Formation Tb

Arikaree Formation Ta

White River Group Tw

Cretaceous-age sedimentary 

deposits

Pierre Shale KpNiobrara Formation KnCarlile Shale Kc

White Clay fault

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Geology modified from Martin and others, 2004;

University of Nebraska-Lincoln, 2010

Figure 4. Generalized surface geology in the study area.
10 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers Table 3. Generalized stratigraphic column with geologic map units and lithology in study area. [Modified from Ellis and Adolphson (1971), Heakin (2000), Carter and Heakin (2007), and Martin and others (2004). --, not applicable] System Series Mapped unit Subdivisions Thickness, in feet Lithology

Quaternary

Holocene Alluvial 

deposits

-- 0–60 Light brown to gray, unconsolidated, clay, silt, and fine sand; discontinuous sandy and clayey gravel beds 

in lower part. 

Holocene and 

Pleistocene

Landslide deposits -- 0–100 Landslide, slump, and collapsed material composed of chaotically mixed boulders and finer grained rock 

debris.

Eolian deposits -- 0–200 Brown, unconsolidated, very fine to medium grained, uniform, quartz sand; characterized by dune topography and blowouts. Includes the Sand Hills Formation.

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. 

Tertiary

Pliocene–

Oligocene

Gravel deposits -- 0–60 Clay- to boulder-sized clasts primarily from igneous and metamorphic rocks of the central Black Hills.

Pliocene Ogallala Formation -- 0–200 Tan to olive, fine- to medium-grained sandstone with some silty clay. Upper unit of the Ogallala Formation is also known as the Ash Hollow Formation and the lower unit as the Valentine Formation. Miocene Batesland Formation -- 30–50 Light gray to light greenish, fine- to coarse-grained, bedded and cross-bedded, fossiliferous sand with 

interbedded silts, clays, and marls.a

Arikaree 

Formation

Unit E 

(Rosebud Formation)b

0–235 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. 

Unit D 

(Harrison Formation)b

0–160 Gray, massive, poorly consolidated, fine to very fine sand; commonly contains layers of light-gray sandy 

marl, largely pipey concretions, and small spherical concretions. Formation becomes silty toward the east; concretions in the lower part present only in discontinuous zones. Unit is difficult to differentiate from underlying units. 

Unit C 

(Monroe Creek Formation)b

0–120 Buff siltstone and very fine-grained sandstone; sandier toward east. Unit is difficult to distinguish from 

overlying and underlying units. 

Unit B 

(unnamed member of Sharps Formation)b

0–375 Pinkish-tan, poorly consolidated silt and very fine-grained sand; gray, small (2–4 inches) calcareous 

concretions are common. Lenses of limestone and channel sand and gravel occur locally throughout the unit in central and western parts of the Pine Ridge Indian Reservation. 

Unit A 

(Rockyford Ash Member of the Sharps Formation)b

0–45 White, tan, buff, and reddish-brown silty volcanic ash; interbedded with thin layers of silt. 

Oligocene White River Group Brule Formation 0–450 Yellow to brown, poorly consolidated siltstone and claystone with some beds of fine-grained sand. 

Chadron Formation 0–110 Pale, gray-green bentonite clay alternating with layers of greenish-gray siltstone. 

Cretaceous

Upper 

Cretaceous

Pierre Shale -- 0–1,200 Dark-gray marine shale and mudstone with some layers of bentonite. Niobrara Formation -- 0–325 Tan to gray, highly calcareous shale. Commonly described by drillers as “chalk.” Carlile Shale -- 100–325 Dark-gray marine shale and mudstone. Middle part of the formation is sandy and contains thin limestone 

ledges locally. 

aFrom Harksen and Macdonald (1967). bCorresponding unit from Harksen and Macdonald (1969).
Conceptual Model 11

generally is too impermeable to serve as a source of groundwater; however, local fractured zones and channel sands may 

yield some water. The Upper Cretaceous units are not a source 

of groundwater (Carter and Heakin, 2007).

The Ogallala aquifer is composed of the saturated sandstone and siltstone of the Ogallala Formation. The overlying 

windblown deposits are composed of fine- to medium-grained 

sands and are similar in composition to the Ogallala Formation. For this reason, the Ogallala Formation and overlying 

windblown deposits are conceptualized together as a single 

water-bearing unit. The upper unit of the Ogallala Formation 

has a relatively low permeability, whereas the lower unit of 

the Ogallala Formation is water bearing (Ellis and Adolphson, 

1971). The water table in the Ogallala aquifer generally is at 

the base of the windblown sand deposits. Springs commonly 

exist at the margins of the sand dunes.

The Ogallala aquifer is present throughout about one-half 

of Bennett County and the southeastern corner of Shannon 

County, but is not present in the northern or the western part of 

the study area (fig. 5). The aquifer is thickest in southeastern 

Bennett County. Seeps and springs exist near the rivers and 

drainages throughout the study area most commonly at the 

contact between the Ogallala Formation and the Arikaree Formation. The Ogallala aquifer is considered to be unconfined 

throughout the study area; however, confined conditions may 

exist locally within the aquifer. Based on studies in Mellette 

and Todd Counties, the Ogallala aquifer has the highest yield 

potential of aquifers in the study area with yields ranging from 

1 to 1,250 gallons per minute (gal/min; Carter, 1998). Estimated hydraulic conductivity ranges from 0.2 to 120 feet per 

day (ft/d; Long and others, 2003). The generalized potentiometric surface of the High Plains aquifer in southern South 

Dakota, which grouped the Ogallala and Arikaree aquifers, 

indicates that groundwater flows from drainage divides to the 

east and toward the Little White River and major streams in 

Nebraska (Kolm and Case, 1983).

The Arikaree aquifer consists of the saturated siltstones 

and sandstones of the Arikaree Formation. The upper clayey 

part of the Arikaree Formation is composed of relativity lowpermeability beds, but generally yields water from fractures, 

joints, and thin silty lenses. The basal sandy and silty part of 

the formation is moderately permeable. Where not overlain by 

the Ogallala Formation or not exposed at the land surface, the 

Arikaree aquifer is overlain by younger unconsolidated deposits including alluvial and eolian deposits. The composition of 

the younger deposits generally is similar to the composition of 

the Arikaree aquifer and therefore these units are conceptualized together as a single water-bearing unit. Springs and seeps 

exist at the contact between the Arikaree Formation and the 

underlying White River Group and at contacts between impermeable and permeable layers within the Arikaree Formation 

(Ellis and Adolphson, 1971). The Arikaree aquifer is mostly 

unconfined but it can be confined where overlain by impermeable layers in the Ogallala Formation in the southern and 

southeastern parts of the study area (Carter and Heakin, 2007). 

Confined conditions also may exist locally where impermeable 

layers are present. Long and others (2003) estimated the 

horizontal hydraulic conductivity to be in the range of 0.1 to 

5.4 ft/d for the Arikaree aquifer in Mellette and Todd Counties.

The Arikaree Formation is present only south and east 

of the White River except for a small outcrop southwest of 

the town of Oglala, west of the White River (fig. 4); the small 

outcrop west of the White River is not included in the extent 

of the Arikaree aquifer shown in figure 5. Based on lithologic 

logs from wells that penetrated the White River Group (fig. 5), 

the Arikaree aquifer is thickest in the southern part of the 

study area. Water levels in the Arikaree aquifer range from 

0 to 200 ft below land surface (Carter and Heakin, 2007). Well 

yields from the Arikaree aquifer in the study area range from 

1 to 1,540 gal/min with the largest yields in Bennett County 

(Carter and Heakin, 2007) depending on the clay content in 

the aquifer, consolidation of the materials, and well construction; however, well yields from the Arikaree aquifer generally 

are less than those from the Ogallala aquifer.

Conceptual Model

The conceptual model describes a hydrogeologic 

framework, groundwater flow, recharge, evapotranspiration, 

discharge to streams, water use, and hydraulic properties of 

the Ogallala and Arikaree aquifers. The conceptual model of 

the Ogallala aquifer includes the overlying windblown and 

unconsolidated deposits, and the Arikaree aquifer includes 

isolated overlying unconsolidated deposits. The hydrogeologic 

framework describes the physical dimensions and location of 

the aquifer units. Water budget components were analyzed 

by WY for the period 1980–2009. Recharge to the Ogallala 

and Arikaree aquifers is from infiltration of precipitation on 

outcrop areas. Well withdrawals primarily are for irrigation 

and public and domestic water supplies. The Ogallala and 

Arikaree aquifers are assumed to have a hydraulic connection 

that is limited by the lower vertical hydraulic conductivity of 

the Arikaree aquifer.

The extents of the Ogallala and Arikaree aquifers were 

simplified from the extents of the Ogallala and Arikaree 

Formations (fig. 4) and were used to develop the conceptual 

model in this report (fig. 5). Thin and intermittently saturated 

parts near the outer extent of the Ogallala Formation were 

grouped with the Arikaree aquifer. Thin and intermittently 

saturated parts of the Arikaree Formation along the northern and western outcrop boundaries were removed. Isolated 

areas of eolian deposits and the Batesland Formation were 

grouped with the uppermost underlying Ogallala or Arikaree 

Formation. The Ogallala and Arikaree aquifers extend about 

130 miles (mi) beyond the eastern edge of the study area 

boundary and about 770 mi beyond the southern edge of the 

study area boundary. The conceptual model boundaries were 

extended 3 to 6 mi into Nebraska to the south and 1 to 2 mi 

into Mellette and Todd Counties to the east to minimize the 

effect of the boundary conditions in numerical modeling of 
12 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

the Pine Ridge Indian Reservation area. The conceptual model 

boundaries are coincident with the extent of the Ogallala and 

Arikaree aquifers shown in figure 5.

Hydrogeologic Framework

The tops and bottoms of the Ogallala and Arikaree Formations were identified from lithologic data (South Dakota 

Geological Survey, 2012; University of Nebraska-Lincoln, 

2012). The contacts between the Ogallala and Arikaree Formations and between the Arikaree and White River Formations 

were interpreted using descriptions of the geology (Ellis and 

Adolphson, 1971; Harksen and Macdonald, 1967; Greene and 

others, 1991; Martin and others, 2004). When a lithologic log 

included a geologic name with the units described, nearby 

lithologic logs without identification of geologic units were 

compared to improve the interpretations. The altitude of land 

surface near the perimeter where the Ogallala and Arikaree 

Formations pinched out also was used in the interpolation of 

the aquifer bottoms.

The top of the Ogallala Formation was coincident with 

land surface (fig. 2) within the simplified Ogallala aquifer 

extent (fig. 5). Quaternary-age deposits and Tertiary-age 

gravel deposits that directly overlie the Ogallala Formation 

were included with the Ogallala Formation in defining the 

hydrogeologic framework for the Ogallala aquifer because, 

in general, these deposits are hydraulically connected to the 

Ogallala aquifer (Weeks and Gutentag, 1981). The top of the 

Arikaree Formation within the simplified Arikaree aquifer 

extent and where the Ogallala aquifer does not exist (fig. 5) 

was coincident with land surface. Isolated Quaternary-age 

deposits, Tertiary-age gravel deposits, and thin isolated areas 

of the Ogallala and Batesland Formations that directly overly 

the Arikaree Formation were considered hydraulically connected to the underlying Arikaree aquifer.

The bottom of the Ogallala aquifer is coincident with 

the base of the Ogallala Formation and also is equivalent to 

the top of the Arikaree Formation. The bottom of the Ogallala 

aquifer was interpreted from wells and test holes (fig. 6). In 

addition to test holes or wells that fully penetrated the aquifer, 

the bottom of the Ogallala aquifer was interpreted from wells 

that partially penetrated the aquifer and test holes located 

along hydrologic cross sections of the High Plains aquifer in 

Bennett County (Filipovic, 2011). The interpolated altitude of 

the bottom of the Ogallala aquifer ranged from about 3,600 ft 

above NAVD 88 in the west to about 2,700 ft above NAVD 88 

in the east (fig. 6).

The bottom of the Arikaree aquifer is coincident with 

the bottom of the Arikaree Formation and is equivalent to the 

top of the White River Group. The bottom of the Arikaree 

aquifer (fig. 7) was interpreted from sparse lithologic logs that 

penetrated the White River Group (fig. 5). In addition to test 

holes or wells that fully penetrated the Arikaree aquifer, the 

altitude of the bottom of the Arikaree aquifer was interpreted 

from wells that partially penetrated the aquifer and test holes 

located along hydrologic cross sections of the High Plains 

aquifer in Bennett County (Filipovic, 2011). Wells from Carter 

and Heakin (2007) that partially penetrated the Arikaree 

aquifer were examined and several were selected to estimate 

the maximum possible altitude for the bottom of the Arikaree 

aquifer. Several wells were assumed to be close to fully penetrating the aquifer. The altitude of the bottom of the Arikaree 

aquifer ranged from about 3,200 ft above NAVD 88 in the 

southwestern part of the study area to about 2,200 ft above 

NAVD 88 in the eastern part of the study area (fig. 7).

Groundwater Flow

Generalized potentiometric surfaces of the Ogallala 

(fig. 8) and Arikaree (fig. 9) aquifers were estimated from 

water levels from wells screened in the aquifers. The potentiometric surfaces indicate a generalized northeasterly groundwater-flow direction following the topography. Groundwater 

generally flows from areas of recharge to streams or other 

topographically low areas where the aquifers discharge either 

through stream base flow, springs, or evapotranspiration. The 

general direction of groundwater flow in the Ogallala aquifer 

is west to east and towards the Little White River (fig. 8). The 

general direction of groundwater flow in the Arikaree aquifer 

is towards the north and east with local flow toward streams 

(fig. 9).

Ogallala Aquifer

The eolian deposits (windblown sand) that overlie the 

Ogallala aquifer have similar hydrogeologic properties and 

are in direct hydraulic connection with the Ogallala aquifer; 

therefore, the two units were conceptualized together as a 

single water-bearing unit (Weeks and Gutentag, 1981). The 

generalized potentiometric surface for the Ogallala aquifer was 

interpreted based on data from 12 long-term observation wells 

with multiple measurements and 60 wells with single waterlevel measurements (fig. 8 and table 1–1; U.S. Geological 

Survey, 2010). For the 12 long-term observation wells, a mean 

hydraulic head value for the period of record was calculated. 

The range in water-level fluctuations in the 12 wells with 

long-term data averaged 8.3 ft. Fluctuations in water levels 

for 10 of the 12 wells were less than 8 ft. The remaining two 

wells had water-level fluctuations of 17.8 and 32.1 ft and were 

close to irrigation wells; therefore, the use of wells with single 

water-level measurements was assumed to approximate the 

generalized potentiometric surface for the Ogallala aquifer. The 

general direction of groundwater flow in the Ogallala aquifer 

is west to east (fig. 8) and generally follows the topography 

(fig. 2). Near the South Dakota–Nebraska border, groundwater 

flow primarily was from west to the east. About 5 mi north 

of the South Dakota–Nebraska border, the groundwater-flow 

direction turns north towards the Little White River and Lake 

Creek. Water-level data were not available in the western part 

of the aquifer; however, groundwater flow was assumed to be 

north towards the tributaries flowing to the White River.
Conceptual Model 13

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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200

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

"""

##

Depth of test hole or well log, in feet

15 to 200Greater than 200 to 400Greater than 400 to 600Greater than 600 to 800Greater than 800 to 1,107

!648 Test hole or well that penetrated the 

White River Group—Number is depth to bottom of Arikaree aquifer, in feet

Ogallala aquiferArikaree aquifer—Extent includes 

area overlain by Ogallala aquifer

Simplified aquifer extent

Figure 5. Location of aquifer extents and test holes and wells with lithologic logs in the study area.
14 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

! !

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

"

")

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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2,920 2,870

2,810

2,875 2,856

2,868 2,870 2,717

2,871

2,777

2,805

2,705

2,809

2,815

3,208 3,228

3,195 3,200

3,100

2,991

2,807

2,940 2,820

2,853

2,750

3,295

3,582

3,475 2,990

3,180

2,990

2,840

2,940

2,930

3,180

3,000

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Altitude of the bottom of the Ogallala aquifer, in feet above NAVD 88

2,707 to less than 2,8002,800 to less than 2,9002,900 to less than 3,0003,000 to less than 3,100

3,100 to less than 3,2003,200 to less than 3,3003,300 to less than 3,4003,400 to less than 3,584

Well or test hole with partially penetrating lithologic log—Number 

is altitude of Ogallala aquifer bottom from hydrologic cross sections of the High Plains aquifer in Bennett County, in feet above NAVD 88 (Filipovic, 2011)

Well or test hole with lithologic log—Number is altitude of 

bottom of Ogallala aquifer, in feet above NAVD 88

Ogallala aquifer boundary

!3,582

(

2,990

Figure 6.

Altitude of the bottom of the Ogallala aquifer in the study area.
Conceptual Model 15

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

2,466

2,420

2,506 2,340

2,757

2,320

2,775 2,670

2,320

2,360

2,430

2,851

2,422

2,356

2,217

3,162

3,046

2,580

2,490

2,495

2,640

2,410

2,480

2,320

2,680

2,650 2,695

2,695

2,470

2,670

2,340

2,310

2,380

2,380

2,405

2,580

2,500

2,450

2,390

2,320

2,410 2,390

2,470

2,350

2,330 2,320

2,300 2,500

2,568

2,747

2,566

2,681

2,762

2,382

2,496

2,417 2,352

2,675

2,543

2,577

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Altitude of Arikaree aquifer bottom, in feet above NAVD 88

2,224 to less than 2,3002,300 to less than 2,4002,400 to less than 2,5002,500 to less than 2,6002,600 to less than 2,700

2,700 to less than 2,8002,800 to less than 2,9002,900 to less than 3,0003,000 to 3,176

Well or test hole with lithologic log—Number is altitude of bottom 

of Arikaree aquifer, in feet above NAVD 88

Well or test hole with partially penetrating lithologic log—Number is 

altitude of bottom of Arikaree aquifer from hydrologic cross sectionsof the High Plains aquifer in Bennett County, in feet above NAVD 88 (Filipovich, 2011)

Well selected from Carter and Heakin (2007) that was assumed to approach 

full penetration of the aquifer—Number is altitude of bottom of well, in feetabove NAVD 88

Arikaree aquifer boundary

!

2,757

(2,405

!2,356

Figure 7.

Altitude of the bottom of the Arikaree aquifer in the study area.
16 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

")

")

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")

")

")

")

")

")

"

")

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")

White River

SOUTH DAKOTA

NEBRASKA

BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

!

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1

2

5

7

4

3

8

6

9

10 11

12 72 70 69 68 67 66 65 64 62 60 59 56 54 53 52 51 50 49 48 47 46 45 44 42 41 40 39 37 36

34

32

31 30 29 28 27

24 23

22

21 20 19

16

15

14 13

71 63 61

58 57 55

43

38

35 33

26

25

18 17

3,000

3,300

3,200

3,400

2,900

3,000

3,000

3,000

3,300

3,200

3,400

2,900

3,000

3,000

3,500

3,600

3,100

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14Datum is North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Ogallala aquifer

Potentiometric contour—Shows the altitude at which water level would have stood in tightly cased wells. 

Dashed where approximately located. Contour interval 100 feet. Datum is NAVD 88

Well for which single water-level measurement is available—Number is site identifier in table 1−1Well for which long-term water-level data are available—Number is site identifier in table 1−1

Direction of groundwater flow

"

60

!12

Figure 8. Generalized potentiometric surface of the Ogallala aquifer in the study area.
Conceptual Model 17

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

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")

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")

")

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")

White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

3,000

3,100

3,200

2,900

2,800

2,700

3,300

3,400

2,600

3,500

2,500

2,800

2,500

2,800

2,600

3,100

2,800

2,800

3,000

3,000

3,000

2,700

2,700

3,300

3,400

2,900

3,500

2,900

3,300

3,400 2,900

2,600

3,000

3,100

3,200

2,900

2,800

2,700

3,300

3,400

2,600

3,500

2,500

2,800

2,500

2,800

2,600

3,100

2,800

2,800

3,000

3,000

3,000

2,700

2,700

3,300

3,400

2,900

3,500

2,900

3,300

3,400 2,900

2,600

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Arikaree aquifer

Potentiometric contour—Shows atlitude at which water 

level would have stood in tightly cased wells. Contour interval 100 feet. Datum is NAVD 88

Direction of groundwater flow

Figure 9. Generalized potentiometric surface of the Arikaree aquifer in the study area (modified from Carter and Heakin, 2007).
18 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Because the general direction of groundwater flow for 

the Ogallala aquifer at the southern boundary of the study area 

was mostly parallel to the boundary, inflow across the southern boundary was assumed to be small. The groundwater-flow 

direction at the eastern boundary of the study area primarily 

is towards the Little White River; thus, net flow across the 

eastern boundary also is assumed to be relatively small.

The generalized potentiometric surface of the Ogallala 

aquifer (fig. 8) and the bottom of the Ogallala aquifer (fig. 6) 

were used to calculate the saturated thickness of the aquifer. 

The saturated thickness of the Ogallala aquifer ranged from 

10 to 314 ft (fig. 10). The saturated thickness of the Ogallala 

aquifer on the northern and western sides and along the downstream part of the Little White River ranged from 10 to 100 ft. 

The saturated thickness in the south central part of the study 

area ranged from about 200 to 300 ft.

Arikaree Aquifer

Carter and Heakin (2007) created a generalized potentiometric surface for the Arikaree aquifer using water-level measurements between 1929 and 2006, but most measurements 

were made between 1980 and 2006. The Arikaree aquifer 

interpretation included all of subdivisions of the Arikaree Formation listed in table 3. Isolated water levels that are higher 

than surrounding hydraulic heads may represent groundwater 

perched on impermeable layers within the Arikaree Formation. 

Potentiometric contours of 100 ft (fig. 9) were used to interpret 

groundwater flow in the Arikaree aquifer (Carter and Heakin, 

2007).

The general direction of groundwater flow in the Arikaree 

aquifer is towards the north and east. Locally, groundwater 

flows downgradient from drainage divides towards major 

streams, tributaries, and wetlands (Carter and Heakin, 2007). 

The drainage divides and their relation to major streams and 

valleys are evident on the shaded relief map of the land surface (fig. 2). The hydraulic gradient generally increases as the 

Arikaree Formation pinches out towards the northern extent. 

In the south, the hydraulic gradient is affected by the overlying 

Ogallala aquifer.

The generalized potentiometric surface of the Arikaree 

aquifer (fig. 9) and the altitude of the bottom of the Arikaree 

aquifer (fig. 7) were used to calculate the saturated thickness 

of the aquifer. The saturated thickness of the Arikaree aquifer 

ranged from 10 to 862 ft (fig. 11). The saturated thickness of 

the Arikaree aquifer near the northern and western extents 

ranged from 10 to 100 ft. The saturated thickness in the southern and central part of the study area ranged from about 500 to 

800 ft.

Water Budget Components

Water budget components of recharge and discharge are 

described in this section. Recharge occurs by infiltration of 

precipitation in outcrop areas. Discharge occurs through evapotranspiration, discharge to streams, and well withdrawals.

Recharge

Recharge to the Ogallala aquifer occurs by infiltration of 

precipitation on the outcrop of the Ogallala Formation and the 

overlying windblown deposits in the southern part of the study 

area (fig. 4). Recharge to the Arikaree aquifer is from the infiltration of precipitation on the outcrop of the Arikaree Formation in the northern and western parts of the study area.

Previous reports characterizing the High Plains aquifer, 

which includes the Ogallala and Arikaree aquifers, provide 

estimates of recharge ranging from approximately 8 percent 

of annual precipitation or between 1.3 and 1.8 in/yr (Kolm 

and Case, 1983) to 15 percent of the annual precipitation or 

between 2.5 and 3 in/yr (Langbein, 1949). Recharge to the 

Sand Hills of Nebraska was estimated by Rahn and Paul 

(1975) as about 3 in/yr.

Recharge previously was estimated using a steady-state 

simulation of groundwater flow in the Ogallala and Arikaree 

aquifers in the Rosebud Indian Reservation area (Long and 

others, 2003), located directly east of this study area, and the 

Pine Ridge Reservation area, as 3.3 and 1.7 in/yr, respectively. 

Mean recharge rates of 2.91 in/yr for the Ogallala aquifer (or 

15 percent of mean precipitation) and 1.45 in/yr for the Arikaree aquifer (or 7 percent of mean precipitation) were estimated 

after recalibration of the steady-state simulation of the model 

by Long and others (2003) using additional hydrologic data 

and enhanced parameter estimation techniques (Long and 

Putnam, 2010).

Recharge to the Ogallala and Arikaree aquifers was estimated for three zones (fig. 12): (1) the Ogallala aquifer, (2) the 

eastern part of the Arikaree aquifer, and (3) the western part 

of the Arikaree aquifer. Recharge to the Ogallala aquifer was 

represented separate from the Arikaree aquifer because higher 

precipitation infiltration was expected to occur in the Ogallala aquifer due to the overlying sandy soils derived from the 

Sand Hills Formation. The lower permeability of the Arikaree 

aquifer and the greater presence of clay layers were assumed 

to limit precipitation infiltration in the Arikaree aquifer. The 

Arikaree aquifer was divided into eastern and western zones 

based on lower precipitation on the western side of the study 

area compared to the eastern side.

Mean annual recharge for the three recharge zones 

(fig. 12) was estimated as a percentage of measured precipitation. Precipitation data from station 395281 (Martin) were 

used for recharge zone 1 (Ogallala aquifer), station 394983 

(Long Valley) was used for recharge zone 2 (eastern part of 

the Arikaree aquifer), and station 396736 (Porcupine 11N) was 

used for recharge zone 3 (western part of the Arikaree aquifer; 

table 4). Mean recharge for WYs 1980–2009 for the Ogallala 

and Arikaree aquifers was estimated as 15 and 7.5 percent of 

mean annual precipitation, respectively, determined based on 

the calibrated recharge values, expressed as a percentage of 

precipitation, from the model of the adjacent Rosebud Indian 

Reservation area (Long and Putnam, 2010). 

Because of the sandy soil overlying the Ogallala aquifer, and to a lesser extent overlying the Arikaree aquifer, 
Conceptual Model 19

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

")

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")

")

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")

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

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Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Saturated thickness of the Ogallala aquifer, in feet

10 to less than 100100 to less than 200200 to less than 314

Ogallala aquifer boundary

Figure 10. Saturated thickness of the Ogallala aquifer in the study area.
20 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

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Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Saturated thickness of the Arikaree aquifer, in feet

10 to less than 100100 to less than 200200 to less than 300300 to less than 400

400 to less than 500500 to less than 600600 to less than 700700 to 862

Arikaree aquifer boundary

Figure 11. Saturated thickness of the Arikaree aquifer in the study area.
Conceptual Model 21

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

")

")

")

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")

")

")

")

")

")

")

")

")

")

")

")

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

¬« 407

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Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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396736

395281

394983

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Recharge zone

1 (Ogallala aquifer)2 (eastern part of Arikaree aquifer)3 (western part of Arikaree aquifer)

National Oceanic and Atmospheric Administration 

precipitation station with identification number

!

395281

Figure 12. Recharge zones and selected National Oceanic and Atmospheric Administration precipitation stations in the study area.
22 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

rainfall that exceeded evapotranspiration losses was assumed 

to infiltrate to the aquifers. When antecedent soil moisture 

conditions are dry and soil water is depleted, more of the soil 

moisture is removed from the soil profile as evapotranspiration. To account for the antecedent soil moisture condition in 

dry and wet years, recharge as a percentage of precipitation for 

the transient stress periods was estimated as a linear function 

of the ratio of the annual precipitation to the mean annual 

precipitation for WYs 1980–2009 (table 4). For example, the 

mean annual precipitation at station 395281 (Martin) for WYs 

1980–2009 was 19.8 in., and the annual precipitation in WY 

1980 was 11.9 in.; therefore, the recharge rate as percentage 

of precipitation was calculated as 11.9 divided by 19.8 times 

15 percent, which equals 9.0 percent of precipitation for WY 

1980. This calculation yields an estimated recharge of 1.1 in. 

(9.0 percent of 11.9 in.) for WY 1980 to the Ogallala aquifer 

(recharge zone 1). Transient recharge rates were estimated for 

each WY using this adjusted percentage of annual precipitation for each recharge zone (table 4). Mean annual recharge 

for WYs 1980–2009 was about 3.3 in/yr to the Ogallala 

aquifer and 1.5 in/yr to the Arikaree aquifer (mean of annual 

recharge for recharge zones 2 and 3), or 17.3 and 7.9 percent 

of the long-term (WYs 1980–2009) mean annual precipitation of 19.1 in/yr for the study area, respectively (mean of 

annual precipitation for stations 395281, 394983, and 396736; 

table 4).

Discharge

Discharge from the Ogallala and Arikaree aquifers 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 

land surface. Discharge to streams occurs as flow from springs 

and seeps and as base flow where the aquifers are 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 and public and domestic water supplies.

Evapotranspiration

Maximum potential evapotranspiration is herein defined 

as the maximum amount of water that could be evapotranspired from an aquifer when the water level is at land surface in 

an unconfined aquifer. Evapotranspiration decreases with the 

depth of the water level below land surface and is negligible 

when the depth to the water table is below the root zone (Long 

and Putnam, 2010). Generally, the depth of this root zone is 

assumed to be about 7 to 20 ft with the deeper root penetration 

(as much as 20 ft) associated with pine and deciduous forests. 

Most parts of the study area generally are grasslands or agricultural cropland (fig. 3) where the shallower root penetration (as 

little as 7 ft) is assumed. Evapotranspiration of infiltrating or 

suspended groundwater in the unsaturated zone was assumed 

to be accounted for in the estimates of aquifer recharge.Table 4. Estimated recharge to Ogallala and Arikaree aquifer in the study area for water years 1980–2009 by recharge zone.[Recharge zone 1 represents the Ogallala aquifer, recharge zone 2 represents the eastern part of the Arikaree aquifer, and recharge zone 3 represents the western part of the Ari-karee aquifer (fig. 12). Precipitation data for National Oceanic and Atmospheric Administration stations from National Climate Data Center (2011). Annual refers to the 12-month period designated by a water year. in/yr, inches per year]

Water 

year

Station 395281 Recharge zone 1 Station 394983 Recharge zone 2 Station 396736 Recharge zone 3

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

1980 11.9 0.60 9.0 1.1 10.6 0.54 4.1 0.4 10.7 0.60 4.5 0.5

1981 19.8 1.00 15.0 3.0 17.3 0.88 6.6 1.1 12.6 0.70 5.3 0.71982 24.1 1.22 18.3 4.4 24.5 1.25 9.4 2.3 20.4 1.14 8.6 1.81983 23.7 1.20 18.0 4.3 23.0 1.17 8.8 2.0 17.8 0.99 7.4 1.31984 17.1 0.86 12.9 2.2 15.8 0.81 6.1 1.0 15.6 0.87 6.5 1.01985 13.0 0.66 9.9 1.3 12.2 0.62 4.7 0.6 12.2 0.68 5.1 0.61986 27.1 1.37 20.6 5.6 26.8 1.37 10.3 2.8 21.2 1.18 8.9 1.9
Conceptual Model 23

Table 4. Estimated recharge to Ogallala and Arikaree aquifer in the study area for water years 1980–2009 by recharge zone.—Continued[Recharge zone 1 represents the Ogallala aquifer, recharge zone 2 represents the eastern part of the Arikaree aquifer, and recharge zone 3 represents the western part of the Ari-karee aquifer (fig. 12). Precipitation data for National Oceanic and Atmospheric Administration stations from National Climate Data Center (2011). Annual refers to the 12-month period designated by a water year. in/yr, inches per year]

Water 

year

Station 395281 Recharge zone 1 Station 394983 Recharge zone 2 Station 396736 Recharge zone 3

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

Precipitation 

(in/yr)

Ratio of 

annual 

precipitation 

to mean 

annual

Recharge as 

percentage of 

precipitation

Recharge 

rate 

(in/yr)

1987 15.7 0.79 11.9 1.9 17.8 0.91 6.8 1.2 14.7 0.82 6.2 0.9

1988 15.4 0.78 11.7 1.8 19.7 1.01 7.6 1.5 15.2 0.85 6.4 1.01989 10.7 0.54 8.1 0.9 11.6 0.59 4.4 0.5 12.3 0.69 5.2 0.61990 19.2 0.97 14.6 2.8 18.9 0.96 7.2 1.4 14.8 0.83 6.2 0.91991 24.1 1.22 18.3 4.4 18.3 0.93 7.0 1.3 17.3 0.97 7.3 1.31992 17.4 0.88 13.2 2.3 17.0 0.87 6.5 1.1 20.3 1.13 8.5 1.71993 20.4 1.03 15.5 3.2 25.0 1.28 9.6 2.4 24.7 1.38 10.4 2.61994 18.9 0.95 14.3 2.7 15.2 0.78 5.9 0.9 16.9 0.94 7.1 1.21995 26.5 1.34 20.1 5.3 25.3 1.29 9.7 2.5 22.0 1.23 9.2 2.01996 22.2 1.12 16.8 3.7 25.5 1.30 9.8 2.5 20.8 1.16 8.7 1.81997 27.9 1.41 21.2 5.9 24.3 1.24 9.3 2.3 25.9 1.45 10.9 2.81998 24.4 1.23 18.5 4.5 22.2 1.13 8.5 1.9 15.9 0.89 6.7 1.11999 39.4 1.99 29.9 11.8 24.8 1.27 9.5 2.4 28.6 1.60 12.0 3.42000 16.7 0.84 12.6 2.1 16.8 0.86 6.5 1.1 17.7 0.99 7.4 1.32001 18.2 0.92 13.8 2.5 19.1 0.97 7.3 1.4 19.5 1.09 8.2 1.62002 11.9 0.60 9.0 1.1 13.0 0.66 5.0 0.7 15.0 0.84 6.3 0.92003 14.0 0.71 10.7 1.5 14.7 0.75 5.6 0.8 12.8 0.72 5.4 0.72004 18.2 0.92 13.8 2.5 15.7 0.80 6.0 0.9 15.1 0.84 6.3 1.02005 24.1 1.22 18.3 4.4 25.3 1.29 9.7 2.5 21.0 1.17 8.8 1.82006 14.5 0.73 11.0 1.6 16.6 0.85 6.4 1.1 18.8 1.05 7.9 1.52007 16.5 0.83 12.5 2.1 18.7 0.95 7.1 1.3 16.1 0.90 6.8 1.12008 18.8 0.95 14.3 2.7 24.0 1.22 9.2 2.2 20.5 1.15 8.6 1.82009 23.2 1.17 17.6 4.1 29.1 1.48 11.1 3.2 20.2 1.13 8.5 1.7

Mean 

annual

19.8 1.00 16.4a 3.3 19.6 1.00 8.0a 1.6 17.9 1.00 7.9a 1.4

aDoes not equal the mean of annual values. Value calculated from mean annual precipitation and mean annual recharge.
24 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Maximum potential evapotranspiration during June–September periods was estimated as 70 percent of total annual pan 

evaporation based on the relation between pan evaporation and 

evapotranspiration data described by Farnsworth and others 

(1982). Pan evaporation rates were assumed to be similar to 

those at an NOAA climatological data station at Cottonwood 

(National Climatic Data Center, 2010; station 391972), which 

is located about 20 mi north of the study area (fig. 2). Pan 

evaporation records at station 391972 were available for the 

months of June through September for the 30 WYs included 

in the analysis. The estimated potential evapotranspiration for 

the 30 June–September periods (table 5) for WYs 1980–2009 

ranged from 20.4 to 30.7 in., with a mean of 26.0 in. Sparse 

pan evaporation data were available for October through May. 

The mean pan evaporation was estimated to be 4.25 in. for 

the October–February period and 8.5 in. for the March–May 

period, based on sparse available pan evaporation rates for the 

October–February and March–May periods. To estimate the 

maximum potential evapotranspiration rate for the October–

February and March–May periods for each WY, the mean 

annual maximum potential evapotranspiration rate of 35 in/yr 

was multiplied by the ratio of the monthly mean temperature 

for October–May in each WY divided by the mean monthly 

temperature for October–May in WYs 1980–2009 (National 

Climatic Data Center, 2010; station 391972). Based on these 

estimates and an assumption that maximum potential evapotranspiration was 70 percent of pan evaporation (Farnsworth 

and others, 1982), the mean maximum potential evapotranspiration was 3.0 in for the October–February period and 6.0 in 

for the March–May period. These estimates were then added 

to the values for the June–September period to estimate the 

maximum potential evapotranspiration rate for WYs 1980–

2009 (table 5). 

 Discharge to Streams

Groundwater discharges to streams where streams are 

incised to an altitude below the hydraulic head (altitude of the 

potentiometric surface) in the Ogallala and Arikaree aquifers. 

Long and Putnam (2010) calculated a steady-state discharge 

to streams from the Ogallala and Arikaree aquifers of about 

75 ft3/s in the adjacent Rosebud Indian Reservation area.

The daily base-flow contribution to streamflow at six 

streamgages (table 6; fig. 2) was estimated using HYSEP 

(Sloto and Crouse, 1996), a computer program that uses 

automatic hydrograph separation methods on daily mean 

streamflow data (U.S. Geological survey, 2012). The HYSEP 

program uses three methods for hydrograph separation: fixed 

interval, sliding interval, and local minimum. Descriptions of 

the three hydrograph separation methods are available in the 

HYSEP documentation (Sloto and Crouse, 1996). The local 

minimum method resulted in the smallest base-flow values 

and was assumed to minimize the effects of bank storage in 

the final estimates.

Mean base-flow rates for WYs 1980–2009 for the six 

streamgages ranged from 3.5 to 52.2 ft3

/s (table 7). The mean 

base flow for gaged streams was about 0.06 ft3

/s per square 

mile of drainage area. Base flow expressed in inches per year 

over the contributing drainage area for the Little White River 

upstream from streamgage 06449100 was 1.1 in/yr. The Little 

White River drainage basin includes most of the outcrop of the 

Ogallala Formation. Base flow for Bear-in-the-Lodge Creek 

for the contributing drainage area upstream from streamgage 

06446700 (fig. 2) was 0.4 in/yr. Most of the Bear-in-the-Lodge 

Creek drainage area includes the outcrop of the Arikaree 

Formation.

For streamgages with incomplete periods of record, base 

flow was estimated with equations developed by linear regression of the base flow for the existing period of record with the 

base flow calculated for streamgage 06447500 (Little White 

River near Martin, South Dakota [fig. 2]) for the same period 

for each streamgage. This procedure was completed using 

the method documented by Riggs (1972). The coefficient of 

determination for each of the linear regressions was 0.99. 

For streamgage 06446700 (Bear-in-Lodge Creek near Wanblee, S. Dak. [fig. 2]), base flow was 0.72 times base flow for 

streamgage 06447500; for streamgage 06446100 (Wounded 

Knee Creek at Wounded Knee, S. Dak. [fig. 2]), base flow 

was 0.21 times base flow for streamgage 06447500; and for 

streamgage 06445980 (White Clay Creek near Oglala, S. Dak. 

[fig. 2]), base flow was 0.50 times base flow for streamgage 

06447500.

Water Use

Water use from the Ogallala and Arikaree aquifers 

was primarily for irrigation and public supplies but also for 

domestic and stock use. Most production wells (fig. 13) that 

were used for irrigation were located in the southern part of 

the study area where the Ogallala aquifer is present (fig. 5) and 

the saturated thickness of the Arikaree aquifer is the greatest 

(fig. 11). Irrigators report their water use to the South Dakota 

Department of Environment and Natural Resources; these data 

were used to compile well withdrawals by aquifer for WYs 

1980–2009 (table 8). The mean irrigation water-use rates for 

WYs 1980–2009 were 5.4 ft3

/s for the Ogallala aquifer and 

5.2 ft3/s for the Arikaree aquifer.

The Arikaree aquifer is used extensively for public supplies. Water use for public supplies was compiled based on 

estimated community population and per capita water use. 

Public-supply wells were inventoried during a water-quality 

sampling program conducted by Heakin (2000) that identified 

27 communities including schools, housing authorities, and 

small towns. Population equivalents were estimated for these 

communities based on 2010 census data for census-designated 

places (U.S. Census Bureau, 2013). Per capita water use was 

assumed to average 93 gallons per population equivalent per 

day based on estimated public-supply domestic water deliveries for South Dakota (table 9; Amundson, 1998; Amundson, 

2002; Carter and Neitzert, 2008). Population was assumed to 

uniformly increase 0.4 percent per year based on population 

changes for Bennett, Jackson, and Shannon Counties (table 9). 
Conceptual Model 25

Table 5. Estimated maximum potential evapotranspiration rate in the study area, water years 1980–2009.

Water year

Estimated maximum potential 

evapotranspiration for 

June–Septembera

(inches)

Estimated maximum potential 

evapotranspiration for 

October–Mayb

(inches)

Maximum potential 

evapotranspiration rate 

(inches per water year)

1980 29.1 9.0 38.1

1981 24.4 9.9 34.3

1982 22.0 8.5 30.5

1983 28.3 9.1 37.4

1984 26.6 8.5 35.1

1985 27.8 8.8 36.6

1986 25.3 8.4 33.7

1987 27.7 9.4 37.1

1988 30.7 8.8 39.5

1989 29.5 8.7 38.2

1990 28.4 9.2 37.6

1991 26.5 9.0 35.5

1992 21.6 9.7 31.3

1993 20.4 8.1 28.5

1994 26.2 8.6 34.8

1995 25.3 9.0 34.3

1996 27.7 8.1 35.8

1997 22.5 7.9 30.4

1998 21.9 9.2 31.1

1999 22.4 9.6 32.0

2000 27.2 9.9 37.1

2001 24.8 8.4 33.2

2002 28.4 9.1 37.5

2003 28.4 9.1 37.5

2004 25.6 9.3 34.9

2005 27.2 9.8 37.0

2006 28.1 9.8 37.9

2007 28.4 9.4 37.8

2008 23.0 8.9 31.9

2009 25.6 8.9 34.5

Mean 26.0 9.0 35.0

a

Potential evapotranspiration during June–September periods was estimated as 70 percent of pan evaporation on the basis of the relation between pan evaporation and evapotranspiration described by Farnsworth and others (1982).

b

Potential evapotranspiration estimates for the October–May period were estimated on the basis of sparse pan evapotranspiration records.
26 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 6. Streamgages in study area.

[USGS, U.S. Geological Survey]

USGS 

streamgage Station name Drainage area (square miles)

Period of record available for 

water years 1980–2009

06445980 White Clay Creek near Oglala, S. Dak. 376 1988–1999

06446100 Wounded Knee Creek at Wounded Knee, S. Dak. 73.5 1993–1997

06446700 Bear-in-Lodge Creek near Wanblee, S. Dak. 423 1996–2009

06447500 Little White River near Martin, S. Dak. 313 1980–2009

06449000 Lake Creek below Refuge near Tuthill, S. Dak. 121 1980–2009

06449100 Little White River near Vetal, S. Dak. 619 1980–2009

Table 7. Estimated base-flow contribution to streamflow at streamgages in the study area.

Water year Base-flow rate for U.S. Geological Survey streamgages (cubic feet per second)

06445980 06446100 06446700 06447500 0644900 06449100

1980 5.0 2.1 7.2 10.0 13.7 40.5

1981 5.3 2.3 7.7 10.7 6.5 25.8

1982 7.4 3.2 10.7 14.9 17.3 46.7

1983 8.5 3.7 12.3 17.1 9.3 44.0

1984 7.9 3.4 11.5 16.0 16.9 52.0

1985 5.4 2.3 7.8 10.9 6.1 29.2

1986 7.6 3.3 11.1 15.4 18.6 47.1

1987 8.6 3.7 12.5 17.3 21.6 48.3

1988 7.5 3.3 10.9 15.2 19.6 48.0

1989 5.3 2.3 7.8 10.8 8.6 32.4

1990 6.1 2.6 8.9 12.3 11.4 41.3

1991 7.2 3.1 10.5 14.6 22.8 59.3

1992 5.9 2.6 8.6 12.0 13.8 44.5

1993 8.5 3.7 12.4 17.2 22.2 55.8

1994 10.6 4.6 15.3 21.3 30.2 66.9

1995 12.0 5.2 17.4 24.1 26.7 69.9

1996 9.9 4.3 14.4 20.0 30.5 70.3

1997 13.4 5.8 19.4 27.0 37.2 85.2

1998 11.0 4.7 15.9 22.1 31.7 82.6

1999 12.0 5.2 17.4 24.1 29.2 81.6

2000 10.9 4.7 15.9 22.1 16.2 56.4

2001 10.5 4.6 15.3 21.2 28.2 65.3

2002 6.9 3.0 10.0 13.9 21.6 47.7

2003 6.7 2.9 9.7 13.5 18.0 46.9

2004 5.4 2.3 7.8 10.8 14.8 39.9

2005 7.6 3.3 11.1 15.4 22.2 64.4

2006 6.9 3.0 10.1 14.0 10.7 37.4

2007 5.0 2.2 7.3 10.1 11.5 40.3

2008 6.5 2.8 9.5 13.2 21.6 48.3

2009 9.3 4.0 13.5 18.7 19.9 49.2

Mean 8.0 3.5 11.7 16.2 19.3 52.2

Mean per square mile of drainage area 0.02 0.05 0.03 0.05 0.16 0.08
Conceptual Model 27

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NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

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Spring Creek

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Potato Creek

Wounded Knee

Sharps 

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101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

! Ogallala aquifer production well! Arikaree aquifer production well

Extent of Ogallala aquiferExtent of Arikaree aquifer—Extent includes area overlain by Ogallala aquifer

Figure 13. Location of production wells completed in the Ogallala and Arikaree aquifers in the study area.
28 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 8. Estimated groundwater withdrawals for water years 1980–2009 in the study area.

Water 

year

Water-use rate (cubic feet per second)

Irrigation Public supplies Total water use

Ogallala aquifer Arikaree aquifer Arikaree aquifer Ogallala aquifer Arikaree aquifer

1980 1.2 4.6 1.7 1.2 6.3

1981 1.2 3.9 1.7 1.2 5.6

1982 1.6 2.4 1.7 1.6 4.1

1983 3.2 3.8 1.7 3.2 5.5

1984 3.2 4.1 1.8 3.2 5.9

1985 5.8 8.3 1.8 5.8 10.1

1986 2.8 3.8 1.8 2.8 5.6

1987 4.1 4.2 1.8 4.1 6.0

1988 5.4 4.9 1.8 5.4 6.7

1989 8.9 8.6 1.8 8.9 10.4

1990 5.7 5.3 1.8 5.7 7.1

1991 5.7 4.1 1.8 5.7 5.9

1992 5.8 2.8 1.8 5.8 4.6

1993 4.1 2.5 1.8 4.1 4.3

1994 6.8 3.3 1.8 6.8 5.1

1995 5.7 3.9 1.8 5.7 5.7

1996 5.6 6.5 1.8 5.6 8.3

1997 5.6 4.7 1.8 5.6 6.5

1998 5.7 3.7 1.9 5.7 5.6

1999 4.7 4.8 1.9 4.7 6.7

2000 7.0 5.0 1.9 7.0 6.9

2001 4.6 6.6 1.9 4.6 8.5

2002 6.3 7.7 1.9 6.3 9.6

2003 6.1 5.5 1.9 6.1 7.4

2004 7.5 6.8 1.9 7.5 8.7

2005 6.7 6.5 1.9 6.7 8.4

2006 8.7 8.0 1.9 8.7 9.9

2007 8.0 7.3 1.9 8.0 9.2

2008 7.3 6.8 1.9 7.3 8.7

2009 7.0 6.4 1.9 7.0 8.3

Mean 5.4 5.2 1.8 5.4 7.1

Consequently, estimated water use for public supplies from 

the Arikaree aquifer for WYs 1980–2009 averaged 1.8 ft3/s 

(table 8). 

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 were assumed to 

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

study area. Mean total water use for WYs 1980–2009 was 

5.4 ft3/s from the Ogallala aquifer and 7.1 ft3/s from the Arikaree aquifer (table 8).

Hydraulic Properties

Previously published hydraulic properties (table 10) 

determined based on aquifer tests, specific capacity tests, and 

numerical modeling near the study area indicate heterogeneity 

in aquifer properties. Transmissivity in the Ogallala aquifer 

ranged from 2 to about 7,000 feet squared per day (ft2

/d) 

and from 2 to 2,000 ft2/d for the Arikaree aquifer. Horizontal 

hydraulic conductivity ranged from less than 1 to 180 feet 

per day (ft/d) for the Ogallala aquifer and from less than 1 to 

13 ft/d for the Arikaree aquifer. Vertical hydraulic conductivity 

ranged from 4.18x10-4 to 18 ft/d for the Ogallala aquifer and 
Numerical Model 29

Table 9. Total population for Bennett, Jackson, and Shannon 

Counties and estimated public-supply domestic water deliveries 

for South Dakota per capita per day, 1995, 2000, and 2005.

Year

Total population by county Estimated 

public-supply domestic 

water deliveries for 

South Dakota per capita 

(gallons per day)

Bennett Jackson Shannon

1995a 3,310 2,870 11,680 89

2000b 3,570 2,930 12,470 90

2005c 3,590 2,860 13,660 99

a

Amundson (1998).

b

Amundson (2002).

c

Carter and Neitzert (2008).

from 8.77x10-5 to 3.66 ft/d for the Arikaree aquifer (Long and 

Putnam, 2010; Davis and Putnam, 2013). Specific yield ranged 

from 0.02 (dimensionless) to about 0.06 for the Ogallala 

aquifer and was 0.03 for the Arikaree aquifer. Gutentag and 

others (1984) estimated a specific yield of less than 0.1 for the 

High Plains aquifer based on lithologic descriptions from drillers logs. Storage coefficients for the Ogallala aquifer ranged 

from 0.003 to 0.06 and from 0.0003 to 0.007 for the Arikaree 

aquifer.

Numerical Model

The numerical model of the Ogallala and Arikaree aquifers described in this report includes analysis of WYs 1980–

2009 with 31 simulation stress periods, and was developed 

from the data included in the conceptual model. The numerical 

model was used to simulate steady-state and transient historical conditions and potential future scenarios. Stress period 1 

was a steady-state simulation with the mean of aquifer stresses 

applied for WYs 1980–2009. The hydraulic heads calculated from this simulation were used as starting heads in the 

transient simulation for stress periods 2–31, with each stress 

period representing a water year. The groundwater modeling 

program, MODFLOW–NWT (Niswonger and others, 2011) 

was used for the numerical simulation of groundwater flow. 

Zonebudget (Harbaugh, 1990), a program that calculates subregional water budgets from MODFLOW–NWT results, was 

used to compute selected water budgets for individual model 

layers.

Simulation Methods

MODFLOW–NWT is a Newton formulation variant of 

MODFLOW–2005 (Harbaugh, 2005), which is a numerical, 

three-dimensional, finite-difference groundwater modeling 

program. The Newton formulation described in this report 

extends the applicability of MODFLOW–2005, especially to 

those problems representing unconfined aquifers and surfacewater/groundwater interaction (Niswonger and others, 2011). 

The model includes two layers: the upper layer represented 

the Ogallala aquifer and the overlying unconsolidated deposits, and the lower layer represented the Arikaree aquifer and 

grouped sediments.

Assumptions

Using MODFLOW–NWT to simulate groundwater-flow 

systems through finite-difference solution techniques implies 

many assumptions (Harbaugh, 2005); the primary assumptions 

are listed:

1. Flow in the Ogallala and Arikaree aquifers in the study 

area is assumed to be predominantly horizontal where the 

aquifers are unconfined within the study area; therefore, 

each aquifer is represented appropriately with a single 

model layer.

2. The spatial variability in aquifer properties is adequately 

represented at the scale of a uniform grid with cells that 

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

uniform within the area of each cell. Sediments of the 

Ogallala and Arikaree aquifers are fluvial in origin and 

have a greater degree of vertical and horizontal heterogeneity than is represented by the scale of the model. It is 

recognized that actual hydraulic properties at individual 

sites could differ widely from those represented in the 

model. Nevertheless, a 1,640-ft grid spacing was assumed 

to be an appropriate discretization of the model to 

represent the heterogeneity of the Ogallala and Arikaree 

aquifer properties for the scale of the groundwater-flow 

model, given the intended purpose and study objectives. 

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 east of the study area.

3. 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 stated in assumption 2, the 1,640-ft spacing is sufficient 

discretization for the scale of the groundwater-flow model 

and the study objectives.

4. Starting conditions for the 30-year transient simulation 

can be appropriately estimated with a steady-state stress 

period, during which the mean of aquifer stresses for WYs 

1980–2009 was applied.

5. Sources and sinks of water that have an important effect 

on the groundwater-flow system were appropriately 

represented by stress periods of one WY in length. It is 

recognized that aquifer stresses exist at a higher degree of 
30 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 10. Previously published horizontal hydraulic properties for the Ogallala and Arikaree aquifers in or near the study area.

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

Method Transmissivity 

(ft2

/d)

Horizontal 

hydraulic 

conductivity 

(ft2

/d)

Storage 

coefficient 

(dimensionless)

Specific yield 

(dimensionless) Location Source

Ogallala aquifer

Time drawdown 

aquifer test

7,005 a

70 0.003 0.057 Todd County Rahn and Paul, 1975

Distance drawdown 

aquifer test

3,234 132 0.06 -- Todd County Rahn and Paul, 1975

Aquifer test 2,995 21.6 -- 0.02 Todd County Kremlin-Smith, 1984

Aquifer test 1,644 7.9 -- 0.03 Todd County Kremlin-Smith, 1984

Aquifer test 3,088 17.5 -- 0.02 Todd County Kremlin-Smith, 1984

Specific capacity 180–3,476 1.2–25.2 -- -- Todd County Kremlin-Smith, 1984

Specific capacity 2–2,400

average 600

-- -- -- Todd County Carter, 1998

Numerical model -- 0.2–120 -- -- Mellette and Todd 

Counties

Long and others, 2003

Numerical model -- 0.2–84 -- -- Mellette and Todd 

Counties

Long and Putnam, 2010

Numerical model -- 1.0–180 -- -- Gregory and Tripp 

Counties

Davis and Putnam, 2013

Arikaree aquifer

Specific capacity 2–2,000 

average 90

-- -- -- Todd County Carter, 1998

Aquifer test 1,250 13 0.007 0.03 Shannon County 

35N44W17

Greene and others, 1991

Aquifer test 300 1 0.0003 -- Shannon County 

35N44W17

Greene and others, 1991

Aquifer test 310 1.0 0.0004 -- Shannon County 

35N44W

Sipe, 1989

Time drawdown 

(single well)

298 1.0 0.0004 -- Shannon County 

35N44W

Sipe, 1989

Time recovery 

(single well)

326 1.0 -- -- Shannon County 

35N44W

Sipe, 1989

Numerical model -- 0.1–5.4 -- -- Mellette and Todd 

Counties

Long and others, 2003

Numerical model -- 0.1–4.3 -- -- Mellette and Todd 

Counties

Long and Putnam, 2010

variability than is represented by the temporal discretization of the model. Temporally varied stresses, such as well 

withdrawals, are smoothed and averaged compared with 

what may exist in reality. Nevertheless, as with assumptions 2 and 3, the degree of discretization used is appropriate for the scale of this groundwater-flow model and 

the study objectives.

a

Calculated from transmissivity based on saturated thickness of 100 feet.

Model Design

The MODFLOW–NWT (Niswonger and others, 2011) 

was used to simulate groundwater flow for the Ogallala and 

Arikaree aquifers 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 
Numerical Model 31

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.

The MODFLOW–2005 solver packages can have convergence problems if parts of the model domain become dewatered during a simulation. The UPW package is a new package that can be used in conjunction with the NWT solver in 

MODFLOW–NWT to provide 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 other MODFLOW–2005 solver packages would. Instead, 

the UPW package reduces the conductance between a dry cell 

and an adjoining wetted cell to zero. This reduction of conductance to zero 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 for this study. The 

modified Well package has the ability to reduce the pumping rate of a well located in a cell that is dewatered during a 

simulation. This prevents water from being removed from a 

dewatered cell.

Finite-Difference Grid and Boundary Conditions

The model grid consisted of two layers made up of 

166 rows oriented east to west and 288 columns oriented 

north to south. The boundaries of the model were represented 

by constant-head or no-flow cells (fig. 14). The southern and 

eastern boundaries of model layer 1, where the Ogallala aquifer existed beyond the study area boundary, were simulated 

by constant-head cells. The constant-head cells were used to 

represent groundwater flow into and out of the model domain. 

The hydraulic heads for the constant-head cells were assigned 

based on the generalized potentiometric surface of the Ogallala aquifer (fig. 8). For layer 1, the northern and western 

model boundaries were represented by no-flow cells where 

the Ogallala aquifer pinches out. The boundary was simplified to eliminate isolated and intermittently saturated areas of 

the aquifer. In general, areas with less than 10 ft of saturated 

thickness were removed from the model.

The southern and eastern boundaries of model layer 2, 

where the Arikaree aquifer existed beyond the study area 

boundary, were simulated by constant-head cells. The constant-head cells were used to represent groundwater flow into 

and out of the model domain. The hydraulic heads for the 

constant-head cells were assigned based on the generalized 

potentiometric surface of the Arikaree aquifer (fig. 9) and were 

used to represent groundwater flow into and out of the model 

domain. For model layer 2, the northern and western model 

boundaries were represented by no-flow cells where the Arikaree aquifer pinches out. The northern and western boundaries 

were simplified to eliminate thin or intermittently saturated 

areas of the aquifer. In general, areas with less than 10 ft of 

saturated thickness were removed from the model.

Hydrogeologic Representation

The thickness of model cells for layers 1 and 2 was 

determined based on the aquifer tops and bottoms described in 

the “Hydrogeologic Framework” section of this report. Cells 

representing the Ogallala and Arikaree aquifers were simulated as potentially being able to convert between confined 

and unconfined conditions. Although the Ogallala and Arikaree aquifers generally are unconfined within the study area, 

confined conditions exist within the Arikaree aquifer where 

overlain by the Ogallala aquifer in the southwestern part of the 

model area (fig. 14). 

Hydraulic Properties

Previously published values (table 10) were used as 

general indicators for hydraulic conductivity, but parameter 

estimation of hydraulic conductivity using the Parameter 

ESTimation (PEST) computer code (Doherty, 2010) was used 

to adjust the final values and distributions in the study area. 

Values for horizontal hydraulic conductivity were estimated 

using pilot-point parameterization, which is 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, pilot-point parameterization 

allowed a smooth variation of hydraulic conductivity over the 

model domain. 

Hydraulic conductivity for model layers 1 and 2 was 

simulated using pilot points (Doherty and others, 2010), which 

served as the “parameters” seen by the parameter estimation process. During each forward model run, the values of 

the pilot-point parameters are spatially interpolated to twodimensional arrays that are subsequently used by the model 

as inputs (Doherty, 2010; Doherty and others, 2010). Kriging 

is the method typically used to interpolate values of hydraulic 

conductivity estimated at the pilot points to the model grid 

cells. Kriging assumes that 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. Kriging requires specification of the correlation 

function, typically represented by a semivariogram, which 

defines the expected correlation between any two points, given 

the separation distance. For this study, an exponential variogram was defined for each model layer to facilitate interpolating pilot-point values to the model input arrays. 

Pilot points for model layer 1 were distributed diagonally 

at cell centers every 10 cells, except east of the town of Pine 

Ridge where an additional point was added. Pilot points for 

model layer 2 were evenly distributed at cell centers every 

20 cells throughout the model domain (fig. 15). Additional 

pilot points were added along the northern and eastern edges 
32 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

391

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Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Model layer 1 (Ogallala aquifer) 

boundary condition

No flowConstant head

Extent of Ogallala aquifer

Model layer 2 (Arikaree aquifer) 

boundary condition

No flowConstant head

Extent of Arikaree aquifer—Extent includes 

area overlain by Ogallala aquifer

Figure 14. Boundary conditions for model layers 1 and 2 in the study area.
Numerical Model 33

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

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44 ¬«

40 ¬« 73 ¬«

73 ¬«

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¬«

Kyle

Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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!

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Pilot point

! Model layer 1

A Model layer 2

!Ó Model layers 1 and 2

Extent of Ogallala aquifer (model layer 1)Extent of Arikaree aquifer (model layer 2)—Extent 

includes area overlain by Ogallala aquifer

Figure 15. Location of pilot points used for interpolation of horizontal hydraulic conductivity to the model domain in the study area.
34 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

of model layer 2. The additional pilot points were used to 

improve the model to measurement fit in those areas. Kriging 

factors used in parameter estimation were created based on 

user-supplied variograms generated with the PEST groundwater utility programs PPK2FAC and FAC2REAL (Doherty, 

2008). Each of the 40 pilot points in model layer 1 and the 

82 pilot points in model layer 2 were represented as a parameter in the parameter estimation process.

Vertical hydraulic conductivity for model layers 1 and 

2 was represented with parameters VKA1_1 and VKA2_1, 

respectively. Vertical hydraulic conductivity parameters 

represent the ratio of the vertical to horizontal hydraulic conductivity in each layer. Specific yield for the Ogallala aquifer 

was represented with parameter SY1_1. Specific yield for 

the Arikaree aquifer was represented by two zone parameters 

SY2_1 and SY2_2 (fig. 16). Parameter SY2_1 was used to 

represent the western and northern parts of the aquifer where 

the aquifer generally was unconfined. Parameter SY2_2 was 

used to represent the southeastern part of the Arikaree aquifer 

where withdrawals for irrigation were greatest. Specific storage for the Arikaree aquifer was represented with parameter 

SS2_2. Vertical hydraulic conductivity and storage parameters 

were optimized in model calibration.

Recharge

The MODFLOW Recharge package (Harbaugh, 2005) 

was used to simulate recharge to the Ogallala and Arikaree 

aquifers. Recharge rates, estimated based on the percentage of precipitation as described in the “Conceptual Model” 

section of this report, were represented in the model by three 

parameters that were optimized during model calibration. 

These parameters, RCH1_1 for recharge zone 1, RCH2_1 

for recharge zone 2, and RCH2_2 for zone 3 (fig. 12), were 

multipliers applied to the estimated recharge rates for each 

zone listed in table 4. MODFLOW–NWT applied recharge to 

the uppermost active model cell during the simulation process. 

Recharge was applied to the cell even if it went dry during the iterative numerical solution of the groundwater-flow 

equations. 

Discharge

 Evapotranspiration, well withdrawals, and discharge 

to streams were simulated using various MODFLOW–2005 

packages. Simulation of these discharge components are 

described in the following sections.

Evapotranspiration

The MODFLOW–2005 Evapotranspiration package 

(Harbaugh, 2005) was used to simulate evapotranspiration 

from the Ogallala aquifer and the unconfined part of the 

Arikaree aquifer. When the simulated water level was at land 

surface, the evapotranspiration rate was equal to the maximum 

potential evapotranspiration rate (table 5). An evapotranspiration multiplier parameter, EVT1_1, was adjusted during the 

model calibration process to refine application of the estimated 

maximum potential evapotranspiration rates in the model.

The evapotranspiration rate decreased linearly in relation to depth of the simulated hydraulic head below the mean 

land-surface altitude for the model cell to an extinction depth. 

The extinction depth was set to 10 to 20 ft in lowlying areas 

near streams and to 7 ft elsewhere. This extinction depth was 

assumed to be the mean depth of the root zone (Long and 

Putnam, 2010). The land-surface altitude was determined 

by taking the mean altitude from the NED (U.S. Geological 

Survey, 2006) within each model cell. For cells that included 

deeply incised stream channels, the mean altitude was 

compared to the minimum NED altitude within the cell, and 

the land-surface altitude was set as 2 ft above the minimum 

altitude. This adjustment was made to better approximate the 

evapotranspiration from riparian areas along deeply incised 

stream channels.

Discharge to Streams

Discharge to streams was simulated using the 

MODFLOW–2005 River and Drain packages (Harbaugh, 

2005). Perennial streams were represented with the River 

package, and intermittent streams were represented with the 

Drain package. The River package simulates the connection between surface water and groundwater. The hydraulic 

conductance between the streambed and aquifer (streambed 

conductance) is defined as hydraulic conductivity of the riverbed material times the cross-sectional area of the stream reach 

divided by the streambed thickness (McDonald and Harbaugh, 

1988). River cells can remove water from or add water to the 

aquifer depending on the direction of the gradient between 

river stage and aquifer hydraulic head. The Drain package is 

similar to the River package; however, only discharge from the 

aquifer to the drain is simulated. Drain cells can only remove 

water from the aquifer when water levels are at or above the 

elevation of the drain bottom.

Model cells that represented streams were grouped in 

17 reaches (fig. 17). Of the 17 stream reaches, 11 perennial 

streams were simulated using the River package and 6 ephemeral streams were simulated using the Drain package (fig. 17, 

table 11). Streambed conductance for the 11 perennial streams 

was represented as a parameter that was optimized during 

model calibration. Streambed conductance for the six ephemeral streams was determined by trial and error to produce 

the best initial model to measurement fit. Most groundwater discharge to the six ephemeral streams was taken up by 

evapotranspiration; unfortunately, no streamgaging records 

were available for comparison during the calibration period. 

A streambed conductance of 10 ft2

/s was used to simulate 

sporadic groundwater discharge to the six ephemeral streams 

represented by drain cells. The streambed conductance was 

set relatively low to produce a reasonable mean groundwater 

discharge by WY; however, the actual streambed conductance 

probably is greater than 10 ft2

/s. The stream reaches represented in the model as drains were identified based on the 
Numerical Model 35

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

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40 ¬« 73 ¬«

73 ¬«

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Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Specific yield zones and associated parameter 

names for Arikaree aquifer

SY2_1SY2_2

Figure 16. Specific yield zones and associated model parameters for model layer 2 representing the Arikaree aquifer in the study area.
36 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

MELLETTE COUNTY TODD COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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agle Nest Creek

Spring Creek

Medicine Root Creek

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Oglala

Tuthill

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Porcupine

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Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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BLC

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06445980

06446100

06446700

06447500

06449100

06449000

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Ogallala aquifer (model layer 1)Extent of Arikaree aquifer (model layer 2)—Extent 

includes area overlain by Ogallala aquifer

Drainage areas in model area contributing to 

selected stream reaches

U.S. Geological Survey streamgage with station 

identifier

Model cells representing stream reach with River package 

#LAKE_CR#LWR_MR#LWR_VBLW

#WCC_BL

#WKC_WK_BL

#BLC

#LWR_VET#MR_CR#POR_CR

#WCC_OGL#WKC_WK

Model cells representing stream reach 

with Drain package

E COT_CRE CRA_CRE EAG_N_CR

E GRA_CRE PASS_CRE POT_CR

# 06449000

Figure 17. Stream reaches represented with MODFLOW–2005 River and Drain packages, streambed conductance parameters, selected contributing drainage areas, and streamgages for modeled streams in the study area.
Numerical Model 37

Table 11. Stream reach identifier, conductance parameter, and observation weights for modeled streams in the study area.

[--, not applicable]

Stream reach identifier and 

conductance parameter 

(fig. 17)

Description of stream reach Observation weight for 

parameter estimation

Stream reach represented with MODFLOW–NWT River package

BLC Bear-in-the-Lodge Creek and Spring Creek tributary. Streamgage 06446700 is located at 

model boundary

10

LAKE_CR Lake Creek upstream from streamgage 06447500 10

LWR_MR Little White River upstream from streamgage 06447500 10

LWR_VBLW Little White River downstream from streamgage 06449100 to model boundary --

LWR_VET Little White River between streamgage 06447500 and streamgage 06449100, which includes the part of Lake Creek from streamgage 06449000 to mouth at Little White River10

MR_CR Medicine Root Creek 4

POR_CR Porcupine Creek 4

WCC_BL White Clay Creek downstream from streamgage 06445980 --

WCC_OGL White Clay Creek upstream from streamgage 06445980 10

WKC_WK Wounded Knee Creek upstream from streamgage 06446100 to model boundary 10

WKC_WK_BL Wounded Knee Creek downstream from streamgage 06446100 to model boundary 4

Stream reach represented with MODFLOW–NWT Drain package

COT_CR Cotton Creek --

CRA_CR Craven Creek --

EAG_N_CR Eagle Nest Creek --

GRA_CR Grass Creek --

PASS_CR Pass Creek --

POT_CR Potato Creek --

generalized potentiometric surface for the Arikaree aquifer 

(fig. 9), by selecting reaches where the groundwater gradient 

was towards the stream. 

Water Use

Well withdrawals were represented using the 

MODFLOW–NWT Well package (Niswonger and others, 

2011). Well withdrawals were assigned to the model cells at 

locations 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). The PEST software uses 

statistical parameter estimation techniques to optimize model 

parameters, such as aquifer storage properties, spring and river 

conductance, and hydraulic conductivity. The PEST software 

is a model-independent calibration tool that applies nonlinear 

parameter estimation techniques. The PEST software systematically adjusts model parameters based on comparisons 

between model simulated values and observed values of 

hydraulic head and base flow. The PEST software 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.

The PEST software uses regularized inversion (Doherty, 

2003, 2010) and can use pilot points for estimation of spatial 

hydraulic properties. This approach allowed for a relatively 

large number of parameters to be optimized and estimated 

simultaneously. Classical methods for estimating hydraulic 

conductivity values and distributions within a model include 

subdividing a model area into zones of piecewise consistency 

where the hydraulic properties are assumed to be spatially 

uniform. However, recent studies have shown that interpolating values for a model area based on a set of estimable 

points (pilot points) distributed throughout the model area 

can achieve a minimum error variance solution to the inverse 

problem and allow maximum extraction of information contained in the observation dataset (Doherty, 2003; Moore and 

Doherty, 2005).

Parameter estimation by use of PEST involves repeatedly comparing model-computed input variables to observed 

measurements, such as hydraulic head, until the best modeled 

fit to the observed data is mathematically determined. Guidelines by Doherty and Hunt (2010) for using PEST to calibrate 
38 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

groundwater models were used for the parameter estimation approach in this study. Hydraulic properties estimated 

by PEST included hydraulic conductivity, vertical hydraulic 

conductivity anisotropy, aquifer storage, and riverbed conductance. Groundwater recharge and evapotranspiration also were 

estimated by PEST.

During the calibration process, hydraulic conductivity 

was estimated at 122 pilot-point locations distributed throughout the model domain. Pilot points were used as the method 

of spatial parameterization for the model inputs of hydraulic 

conductivity and represent the heterogeneity of the aquifer at a 

scale that was manageable for calibration. Hydraulic conductivity was optimized using PEST and assigned to 122 pilot 

points (40 in model layer 1 and 82 in model layer 2) distributed throughout the model domain rather than directly to the 

grid elements of the model (Doherty, 2003, 2010). The result 

of this method is a smooth variation of calibrated hydraulic 

conductivity over the model domain. Other parameters optimized during the calibration process included vertical hydraulic conductivity anisotropy (VKA1_1 and VKA2_1), aquifer 

storage (SS2_2, SY1_1, SY2_1, and SY2_2), recharge and 

evapotranspiration multipliers (RCH1_1, RCH2_1, RCH2_2, 

and EVT1_1), and riverbed conductance (BLC, LAKE_CR, 

LWR_MR, LWR_VBLW, LWR_VET, MR_CR, POR_CR, 

WCC_BL, WCC_OGL, WKC_WK, and WKC_WK_BL). 

The location and distribution of model input parameters are 

described in the “Hydrogeologic Representation” section of 

this report.

Automated parameter estimation approaches, such as 

PEST, relate observed measurements, such as hydraulic head 

and stream base flow, to model input parameters that represent physical properties of the simulated groundwater system. 

The best modeled fit to the observed data is then iteratively 

evaluated by varying the input parameters and assessing the 

resulting model to measurement fit. Guidelines by Doherty 

and Hunt (2010) for using PEST for groundwater-model 

calibration were used for the parameter estimation approach in 

this study.

Calibration Targets

In this report, model calibration targets refer to observed 

or estimated values of hydraulic head and base flow that correspond to specific model output, which are used to assess 

the ability of the model to accurately simulate the groundwater system. A residual is the difference between the model 

simulated value and a calibration target (simulated minus 

observed). Calibration targets included 50 long-term observation wells that had time-series measurements of hydraulic 

head, 633 wells that had single hydraulic-head measurements (U.S. Geological Survey, 2010), and 9 stream reaches 

with estimated groundwater discharge (base flow) by water 

year. Relative weights were assigned to the observations to 

approximately equalize the contribution of different types of 

observations during the calibration process and to reflect the 

confidence in the observed values. Observations with a higher 

confidence were reflected in the calibration process with a 

higher weight.

Hydraulic heads for 12 long-term observation wells in the 

Ogallala aquifer were assigned a weight of 0.5 for 2 representative hydraulic heads per water year (60 total hydraulic head 

measurements per well); thus, the combined weight for each 

of these wells (number of measurements per well times the 

measurement weight for the 1980-2009 calibration period) 

would be about 30. Single hydraulic-head measurements for 

four wells completed in the Ogallala aquifer, which were site 

visited, were assigned a weight of 1.0. Single hydraulic-head 

measurements for 44 wells completed in the Ogallala aquifer, 

which were not site visited, were assigned a weight of 0.5.

Hydraulic heads for 38 long-term observation wells in the 

Arikaree aquifer with multiple measurements were assigned 

a weight of 0.5 for 2 representative hydraulic heads per water 

year. Single hydraulic-head measurements for 335 wells completed in the Arikaree aquifer, which were site visited, were 

assigned a weight of 1.0. Single hydraulic-head measurements 

for 248 wells completed in the Arikaree aquifer, which were 

not site visited, were assigned a weight of 0.5.

Groundwater discharge (base-flow) calibration targets 

(table 12) were estimated for nine of the stream reaches based 

on calculated base flow at gaged streams (table 7). A weight 

of 10 was assigned to discharge calibration targets that were 

determined directly from base-flow calculations, and a weight 

of 4 was assigned to calibration targets for the three stream 

reaches estimated from correlations with discharge determined 

for a nearby gaged stream (table 11), as described in the following paragraphs.

Bear-in-the-Lodge Creek and Spring Creek were represented with a single stream reach and riverbed conductance 

parameter (BLC; fig. 17, table 11). Streamgage 06446700 on 

Bear-in-the-Lodge Creek (fig. 17) is located at the northern 

edge of the model boundary for model layer 2, downstream 

from the confluence with Spring Creek, and has a contributing drainage area entirely within the study area; therefore, 

calibration targets for groundwater discharge by WY were the 

calculated base flow for streamgage 06446700 (table 7), with a 

mean discharge for WYs 1980–2009 of 11.7 ft3/s (table 12).

White Clay Creek was represented with stream reaches 

and riverbed conductance parameters WCC_OGL and 

WCC_BL (fig. 17, table 11). Parameter WCC_OGL represented the White Clay Creek stream reach in the model area 

upstream from streamgage 06445980 (fig. 17). The drainage 

area upstream from the streamgage was 146 mi2, or 39 percent 

of the total upstream contributing drainage area of 376 mi2 

(table 6). Calibration targets for this stream reach were 

assigned (table 12) as 39 percent of the base flow calculated for the streamgage (table 7) with a mean discharge for 

WYs 1980–2009 of 3.1 ft3/s (table 12). Parameter WCC_BL 

represented the small stream reach downstream from the 

streamgage. This stream reach was assumed to have the same 

streambed conductance as the upstream stream reach represented by parameter WCC_OGL. Parameter WCC_BL was 

tied to WCC_OGL in model calibration.
Numerical Model 39

Table 12. Calibration targets for groundwater discharge (base flow) for selected stream reaches.

Water year Stream reach identifier (table 11; fig. 17) and estimated discharge to stream reach (cubic feet per second) BLC WCC_OGLa WKC_WK WKC_WK_BL POR_CR MR_CR LWR_MR LAKE_CR LWR_VET

1980 7.2 2.0 2.1 4.2 2.7 4.2 10.0 13.7 16.81981 7.7 2.1 2.3 4.5 2.9 4.5 10.7 6.5 8.61982 10.7 2.9 3.2 6.2 4.1 6.3 14.9 17.3 14.51983 12.3 3.3 3.7 7.2 4.7 7.3 17.1 9.3 17.61984 11.5 3.1 3.4 6.7 4.4 6.8 16.0 16.9 19.11985 7.8 2.1 2.3 4.5 3.0 4.6 10.9 6.1 12.21986 11.1 3.0 3.3 6.4 4.2 6.5 15.4 18.6 13.11987 12.5 3.4 3.7 7.2 4.8 7.4 17.3 21.6 9.41988 10.9 2.9 3.3 6.3 4.1 6.4 15.2 19.6 13.21989 7.8 2.1 2.3 4.5 3.0 4.6 10.8 8.6 13.01990 8.9 2.4 2.6 5.2 3.4 5.3 12.3 11.4 17.61991 10.5 2.8 3.1 6.1 4.0 6.2 14.6 22.8 21.91992 8.6 2.3 2.6 5.0 3.3 5.1 12.0 13.8 18.71993 12.4 3.3 3.7 7.2 4.7 7.3 17.2 22.2 16.41994 15.3 4.1 4.6 8.9 5.8 9.0 21.3 30.2 15.41995 17.4 4.7 5.2 10.1 6.6 10.3 24.1 26.7 19.11996 14.4 3.9 4.3 8.4 5.5 8.5 20.0 30.5 19.81997 19.4 5.2 5.8 11.3 7.4 11.4 27.0 37.2 21.01998 15.9 4.3 4.7 9.2 6.0 9.4 22.1 31.7 28.81999 17.4 4.7 5.2 10.1 6.6 10.3 24.1 29.2 28.32000 15.9 4.3 4.7 9.2 6.0 9.4 22.1 16.2 18.12001 15.3 4.1 4.6 8.9 5.8 9.0 21.2 28.2 15.92002 10.0 2.7 3.0 5.8 3.8 5.9 13.9 21.6 12.22003 9.7 2.6 2.9 5.6 3.7 5.7 13.5 18.0 15.42004 7.8 2.1 2.3 4.5 3.0 4.6 10.8 14.8 14.32005 11.1 3.0 3.3 6.4 4.2 6.5 15.4 22.2 26.82006 10.1 2.7 3.0 5.8 3.8 6.0 14.0 10.7 12.72007 7.3 2.0 2.2 4.2 2.8 4.3 10.1 11.5 18.72008 9.5 2.5 2.8 5.5 3.6 5.6 13.2 21.6 13.52009 13.5 3.6 4.0 7.8 5.1 8.0 18.7 19.9 10.6

Mean 11.7 3.1 3.5 6.8 4.4 6.9 16.2 19.3 16.8

aValue calculated as 39 percent of base flow at streamgage on the basis of percentage of drainage area that was in study area.
40 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Wounded Knee Creek was represented with stream 

reaches and riverbed conductance parameters WKC_WK 

and WKC_WK_BL (fig. 17, table 11). Parameter WKC_WK 

represented the Wounded Knee Creek stream reach upstream 

from streamgage 06446100 (fig. 17). The drainage area 

upstream from the streamgage was about 72 mi2, and the 

total upstream contributing drainage area was 73.5 mi2

(table 6); therefore, the calibration targets (table 12) for this 

stream reach were assigned as the base flow calculated for 

the streamgage (table 7), with a mean discharge for WYs 

1980–2009 of 3.5 ft3/s (table 12). Parameter WKC_WK_BL 

represented the stream reach downstream from streamgage 

06446100. The calibration targets for this stream reach were 

assigned by correlation with stream reach BLC based on 

contributing drainage area. The contributing drainage area 

for stream reach WKC_WK_BL was 244 mi2 compared 

to 423 mi2 for stream reach BLC (table 6); therefore, the 

calibration targets for stream reach WKC_WK_BL were 

assigned as 58 percent of calibration target for stream reach 

BLC with a mean discharge for WYs 1980–2009 of 6.8 ft3/s 

(table 12).

Porcupine Creek was represented with stream reach 

identifier and riverbed conductance parameter POR_CR 

(fig. 17, table 11). The calibration targets for this stream 

reach were assigned by correlation with stream reach BLC 

based on contributing drainage area. The contributing drainage area for stream reach POR_CR was 159 mi2

 compared 

to 423 mi2 for stream reach BLC (table 6); therefore, the 

calibration targets for stream reach POR_CR were assigned 

as 38 percent of calibration target for stream reach BLC with 

a mean discharge for WYs 1980–2009 of 4.4 ft3/s (table 12).

Medicine Root Creek was represented with stream 

reach and riverbed conductance parameter MR_CR (fig. 17, 

table 11). The calibration targets for this stream reach were 

assigned by correlation with stream reach BLC based on 

contributing drainage area. The contributing drainage area 

for stream reach MR_CR was 250 mi2 compared to 423 mi2

for stream reach BLC (table 6); therefore, the calibration 

targets for stream reach MR_CR were assigned as 59 percent 

of calibration target for stream reach BLC with a mean discharge for WYs 1980–2009 of 6.9 ft3

/s (table 12).

Little White River and Lake Creek were represented 

with stream reaches and riverbed conductance parameters 

LWR_MR, LAKE_CR, LWR_VET, and LWR_VBLW 

(fig. 17, table 11). Calibration targets for stream reach 

LWR_MR (table 12) were assigned the calculated base 

flow for streamgage 06447500 (fig. 17; table 7) because 

the contributing drainage area is entirely within the study 

area. Mean discharge for stream reach LWR_MR for WYs 

1980–2009 was 16.2 ft3/s (table 12). Calibration targets for 

stream reach LAKE_CR (table 11) were assigned the calculated base flow for streamgage 06449000 (fig. 17; table 7) 

because the contributing drainage area is entirely within the 

study area. Mean discharge for stream reach LAKE_CR for 

WYs 1980–2009 was 19.3 ft3/s (table 12). Calibration targets 

for stream reach LWR_VET were assigned the calculated 

base flow for streamgage 06449100 (fig. 17; table 7) minus 

the calibration targets for stream reaches LWR_MR and 

LAKE_CR. Mean discharge for stream reach LWR_VET 

for WYs 1980–2009 was 16.8 ft3/s (table 12). Parameter 

LWR_VBLW was assumed to have the same conductance as 

parameter LWR_VET.

Calibrated Parameters

Parameter values were estimated for recharge multipliers, 

maximum potential evapotranspiration multiplier, streambed 

conductance, and horizontal and vertical hydraulic conductivity. Specific yield was estimated for model layers 1 and 2, and 

specific storage was determined for the part of model layer 2 

(the Arikaree aquifer) overlain by model layer 1 (the Ogallala 

aquifer).

The final calibrated recharge multipliers were 1.00 

for recharge zone 1, 0.74 for recharge zone 2, and 0.70 for 

recharge zone 3. The equivalent calibrated recharge rates for 

the transient simulation (table 13) for WYs 1980–2009 averaged 3.3 in/yr for the Ogallala aquifer (zone 1) and 1.1 in/yr 

for the Arikaree aquifer (zones 2 and 3). Recharge by WY 

ranged from 0.9 to 11.8 in/yr for the Ogallala aquifer and 

from 0.3 to 2.5 in/yr for the Arikaree aquifer. The calibrated 

mean maximum potential evapotranspiration multiplier was 

1.01. The equivalent maximum evapotranspiration rate averaged 35.4 in/yr for WYs 1980–2009 and ranged from 28.8 to 

39.9 in/yr by WY.

The final calibrated streambed conductance (table 14) for 

perennial stream reaches represented with the River package ranged from 101 to 1,360 ft2

/d and averaged 530 ft2/d. A 

uniform value of 10 ft2/d was specified for intermittent streams 

represented with the Drain package; these conductance values 

were not estimated during the calibration process.

The final calibrated horizontal hydraulic conductivity 

for the Ogallala aquifer ranged from 4 to 70 ft/d (fig. 18) and 

averaged 27 ft/d. The largest hydraulic conductivity values in 

model layer 1 (the Ogallala aquifer) were located in the southcentral part of the study area. The final calibrated horizontal 

hydraulic conductivity for model layer 2 (the Arikaree aquifer) 

ranged from 0.2 to 8 ft/d (fig. 19) and averaged 1.0 ft/d. The 

hydraulic conductivity for 98 percent of model layer 2 was 

less than 3 ft/d.

The vertical hydraulic conductivity for the Ogallala 

aquifer (parameter VKA1_1) averaged 1.4 ft/d (0.05 times 

the horizontal hydraulic conductivity). The vertical hydraulic 

conductivity for the Arikaree aquifer (parameter VKA2_1) 

averaged 0.004 ft/d (0.004 times the horizontal hydraulic 

conductivity).

Specific yield for the Ogallala aquifer was 0.15 (parameter SY1_1). Specific yield for the Arikaree aquifer was 0.027 

for zone 1 (parameter SY2_1) and 0.018 for zone 2 (parameter 

SY2_2; fig. 16) and averaged 0.02. Specific storage for the 

Arikaree aquifer (parameter SS2_2) was 1.7x10-6 per foot.
Numerical Model 41

Table 13. Calibrated transient recharge rates by recharge zone.

Water year

Calibrated recharge rate by zone (fig. 12) 

(inches per year)

Zone 1 Zone 2 Zone 3

1980 1.1 0.3 0.4

1981 3.0 0.8 0.5

1982 4.4 1.7 1.3

1983 4.3 1.5 1.0

1984 2.2 0.7 0.7

1985 1.3 0.4 0.4

1986 5.6 2.1 1.4

1987 1.9 0.9 0.7

1988 1.8 1.1 0.7

1989 0.9 0.4 0.4

1990 2.8 1.0 0.7

1991 4.4 1.0 1.0

1992 2.3 0.8 1.3

1993 3.2 1.8 1.9

1994 2.7 0.7 0.9

1995 5.3 1.9 1.5

1996 3.7 1.9 1.3

1997 5.9 1.7 2.1

1998 4.5 1.4 0.8

1999 11.8 1.8 2.5

2000 2.1 0.8 1.0

2001 2.5 1.0 1.2

2002 1.1 0.5 0.7

2003 1.5 0.6 0.5

2004 2.5 0.7 0.7

2005 4.4 1.9 1.3

2006 1.6 0.8 1.1

2007 2.1 1.0 0.8

2008 2.7 1.6 1.3

2009 4.1 2.4 1.3

Mean 3.3 1.2 1.0

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 

Table 14. Calibrated streambed conductance for stream reaches 

represented in model.

Stream reach identifier 

(table 11; fig. 17)

Streambed conductance 

(feet squared per second)

Stream reach represented with MODFLOW–NWT river package

BLC 1,360

LAKE_CR 337

LWR_MR 1,233

LWR_VET 209

LWR_VET 209

MR_CR 1,035

POR_CR 290

WCC_BL 426

WCC_OGL 426

WKC_WK 204

WKC_WK_BL 101

Stream reach represented with MODFLOW–NWT drain package

COT_CR 10

CRA_CR 10

EAG_N_CR 10

GRA_CR 10

PASS_CR 10

POT_CR 10

sensitive to parameters associated with a low relative composite sensitivity. PEST calculated the relative composite sensitivity for each adjustable model parameter (fig. 20). Parameter 

HK1 was used to represent the mean relative composite 

sensitivity for all pilot points associated with model layer 1, 

and parameter HK2 was used to represent the mean relative 

composite sensitivity for all pilot points associated with model 

layer 2. Model outputs were most sensitive to changes in the 

multiplier parameter EVT1_1, which was associated with the 

evapotranspiration applied to the model. Model outputs also 

were highly sensitive to changes in the multiplier parameter 

RCH1_1, which was associated with the recharge to the Ogallala aquifer in the model area. The model was least sensitive 

to the vertical hydraulic conductivity anisotropy parameters 

VKA1_1 and VKA2_1.

Comparison of Simulated and Observed Values

Comparison of the steady-state potentiometric surface 

simulated by the calibrated model to the generalized potentiometric surface for the Ogallala aquifer (fig. 21) indicates 

similar groundwater-flow directions and gradients. The largest 

differences between the potentiometric surfaces were in the 

south-central part of the model area where the simulated 

potentiometric surface was lower and smoother than the generalized potentiometric surface. The mean difference between 

simulated and observed hydraulic heads (residuals) for 
42 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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SOUTH DAKOTA

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CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

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Spring Creek

Medicine Root Creek

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Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Horizontal hydraulic conductivity, in feet per dayOgallala aqufier boundary (model layer 1)

4 to less than 2020 to less than 4040 to less than 6060 to 70

Figure 18. Calibrated horizontal hydraulic conductivity for model layer 1 representing the Ogallala aquifer in the study area.
Numerical Model 43

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SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

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Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

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White Clay Creek

Craven Creek

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Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Horizontal hydraulic conductivity, in feet per day

0.2 to less than 11 to less than 22 to less than 33 to less than 8

Arikaree aquifer boundary (model layer 2)

Figure 19. Calibrated horizontal hydraulic conductivity for model layer 2 representing the Arikaree aquifer in the study area.
44 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Relative composite sensitivity

Parameter

HK1

HK2

VKA1_1

VKA2_1

SS2_2

SY1_1

SY2_1

SY2_2

RCH1_1

RCH2_1

RCH2_2

EVT1_1

BLC

LAKE_CR

LWR_MR

LWR_VET

MR_CR

POR_CR

WCC_OGL

WKC_WK

WKC_WK_BL

Figure 20. Relative composite parameter sensitivities, as defined by Doherty (2010), for the numerical model.

long-term observation wells completed in the Ogallala aquifer 

for the transient simulation for WYs 1980–2009 ranged from 

-30.0 to 24.9 ft (table 15; fig. 22). The mean arithmetic difference for all measurements at observation wells completed 

in the Ogallala aquifer was 2.7 ft. Individual water-level 

measurements from 60 wells were used to create the generalized potentiometric surface, although measurements for 

only 48 wells occurred within the simulation period (WYs 

1980–2009); therefore, only these 48 water-level measurements made during WYs 1980–2009 were used during model 

calibration (table 1–1; fig. 23). The difference between simulated and observed hydraulic heads for wells with single measurements for WYs 1980–2009 ranged from -84.8 to 29.9 ft 

with the largest negative differences in the south-central and 

southeast parts of the study area (fig. 23). The mean arithmetic 

difference between the 731 simulated and observed hydraulic 

heads in the Ogallala aquifer (683 from observation wells and 

48 from single water-level measurements) was 1.4 ft, and the 

mean absolute difference was 12.6 ft.

Hydrographs for four representative wells labeled with 

letters A through D shown in figure 22 were selected for comparison between the simulated and observed hydraulic heads 

for the transient simulation (fig. 24A–D). The simulated and 

observed hydrographs for well A (fig. 24A) indicate similar 

hydraulic-head trends with some observed values that probably reflect intermittent pumping withdrawals. The hydrographs 

for well B (fig. 24B) indicate a downward trend in simulated 

hydraulic head at the beginning of the transient simulation that 

is not present in the observed values. The hydrographs for well 

C (fig. 24C) indicate similar trends with very small residuals 

between simulated and observed hydraulic heads. The hydrographs for well D (fig. 24D) indicate similar trends between 

simulated and observed hydraulic heads; however, the simulated values are about 15 ft lower than observed values.

Comparison of the simulated steady-state potentiometric 

surface for the Arikaree aquifer (fig. 25) to the generalized 

potentiometric surface indicates generally similar groundwater-flow directions; however, the simulated potentiometric surface indicates flatter hydraulic gradients in several areas where 

the generalized potentiometric surface indicates relatively 

steep hydraulic gradients. This difference in hydraulic gradients can generally be observed throughout Shannon County 

and in the western part of Jackson County (fig. 25). The mean 

difference between simulated and observed transient hydraulic 

heads (residuals) for individual long-term observation wells 

completed in the Arikaree aquifer for WYs 1980–2009 ranged 

from -29.6 to 70.4 ft (table 16; fig. 26). The mean arithmetic 

difference for the observation wells was 9.5 ft. The difference between simulated and observed hydraulic heads for 

wells with single measurements for the transient simulation 

for WYs 1980–2009 ranged from -164.9 to 155.4 (fig. 27). 

Eighty-two percent of the simulated single-measurement 

values were within plus or minus 50 ft of the observed values. 

The mean arithmetic difference between the 2,754 simulated 

and observed hydraulic heads in the Arikaree aquifer (2,171 

from observation wells and 583 from single water-level measurements) was 9.8 ft, and the mean absolute difference was 

17.2 ft.

Hydrographs for six representative wells labeled with 

letters E through J in figure 26 were selected for comparison of the simulated and observed trends in hydraulic heads 

(fig. 28A–F). The hydrographs for well E (fig. 28A) indicate 

a simulated flat hydraulic head with less fluctuation than the 

observed values. Well E is located close to a river cell, which 

limited the fluctuation in the simulated hydraulic heads. The 

hydrographs for well F (fig. 28B) indicate similar trends 

in hydraulic head with small residuals between simulated 

and observed values. The hydrographs for well G (fig. 28C) 

indicate similar upward trends but with more fluctuation in the 

simulated values than observed values. The hydrographs for 

well H (fig. 28D) indicate similar trends between simulated 

and observed hydraulic heads; however, the simulated values 
Numerical Model 45

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BADLANDS

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

Lake Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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Spring Creek

Medicine Root Creek

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Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

3600

3,400

3,100

3,300

3,400

3,000

3,200

3,000

2,900

3,400

3,100

3,300

3,400

3,000

3,200

3,000

2,900

3,400

3,400

3,600

3,500

3,400

3,200

3,300

3,000

2,900

3,100

3,400

3,400

3,600

3,500

3,400

3,200

3,300

3,000

2,900

3,100

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Ogallala aquifer (model layer 1)Simulated potentiometric contour—Shows the altitude at which water level would have stood in 

tightly cased wells. Contour interval 100 feet. Datum is NAVD 88

Generalized potentiometric contourSimulated direction of groundwater flow

—Shows the altitude at which water level would have stood in 

tightly cased wells. Dashed where approximately located. Contour interval 100 feet. Datum is NAVD 88 

Figure 21. Comparison of simulated potentiometric surface to the generalized potentiometric surface for the Ogallala aquifer for the steady-state simulation in the study area.
46 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 15. Difference between simulated and observed hydraulic heads for long-term observation wells completed in the Ogallala 

aquifer for the transient simulation, water years 1980–2009.

[USGS, U.S. Geological Survey; --, not applicable]

USGS station 

identifiction number Local number Number of observations

Arithmetic mean of differences 

between simiulated and 

observed values

Mean of absolute difference 

between simiulated and 

observed values

431531101282701 38N35W16CCCC 60 5.3 5.3

431255101212001 38N34W32DDDD 59 -3.1 5.2

431250101163701 37N34W 1AAAA2 48 24.9 24.9

431136101200901 37N34W 9AAAA 60 -4.2 6.9

431018101152001 37N33W17CCCC 60 21.5 21.5

430949101292701 37N35W20CBBA 60 1.8 1.8

430840101213602 37N34W28CCCC2 52 19.6 19.6

430825101151801 37N33W32BBBB2 57 8.6 8.6

430521101223401 36N34W18CCCC2 59 5.6 5.6

430256101160001 36N34W36DBCB 56 -1.7 1.8

430255101291801 36N35W31CDBD 53 -30.0 30.0

425956101424101 35N37W19AADD 59 -15.5 15.5

Mean -- -- 2.7 12.0

are about 30 ft higher than observed values. The hydrographs 

for well I (fig. 28E) also indicate simulated values about 30 ft 

higher than observed values. The hydrographs for well J 

(fig. 28F) indicate similar trends between the simulated and 

observed hydraulic heads; however, the simulated values are 

about 30 ft lower than the observed values.

Simulated mean groundwater discharge to streams in 

the transient simulation, which was represented by 17 stream 

reaches, was 107.8 ft3

/s (table 17). The difference between 

the mean simulated and observed discharges for the transient 

simulation ranged from -3.3 to 3.2 ft3

/s. For stream reaches 

with estimated (observed) groundwater base flow, the simulated total discharge was 92.1 ft3

/s compared to estimated 

(observed) total discharge of 88.7 ft3

/s.

Hydrographs comparing observed and simulated discharge for the six stream reaches with groundwater discharge 

estimated based on gaged streamflow (table 7) in general are 

similar (fig. 29). For stream reach WCC_OGL, simulated 

and observed discharge values were similar. For stream reach 

WKC_WK, simulated and observed values also were similar 

but the simulated values were higher than observed values 

at the end of the wet period in the late 1990s. For stream 

reach BLC, simulated and observed values were similar but 

there was less fluctuation in the simulated values. For stream 

reaches LWR_MR and LAKE_CR, simulated and observed 

discharge values were similar but the simulated values were 

lower than observed values during the wet period in the late 

1990s. For stream reach LWR_VET, trends in simulated and 

observed values were similar; however, the magnitude of 

change in the simulated values was greater in WY 1987 and 

less in WY 2006 compared to observed values.

Simulated Water Budgets

The simulated steady-state model water budget balanced; inflows and outflows averaged 459 ft/3

s (table 18). 

The percentages of inflows were 17 percent from constanthead boundaries, 9 percent from streams, and 74 percent 

from recharge. The percentages of outflows were 8 percent 

to constant-head boundaries, 1 percent to wells, 31 percent to 

streams, and 59 percent to evapotranspiration.

Simulated transient water budgets for selected years 

(table 18) indicate the difference in water budgets for a dry 

period (WYs 1987–1989) and a wet period (WYs 1997–1999). 

Precipitation (table 1) for WYs 1987–1989 averaged about 

4 in. less than the 30-year mean, and precipitation for WYs 

1987–1999 averaged about 7 in. greater than the 30-year 

mean. Compared to the steady-state budget, the recharge rate 

decreased 228 ft3

/s in WY 1989 and resulted in a decrease in 

water going into storage of 182 ft3

/s and a decrease in evapotranspiration of 27 ft3

/s. Compared to the steady-state budget, 

the recharge rate increased 699 ft3

/s in WY 1999 and resulted 

in an increase in water going into storage of 514 ft3

/s and an 

increase in evapotranspiration of 98 ft3

/s.

Water budgets for transient simulation by model layer 

(table 19) for dry WY 1989 and wet WY 1999 indicate that net 

flow from the Ogallala aquifer (model layer 1) to the Arikaree 

aquifer (model layer 2) ranged from about 22 ft3

/s in dry years 

(such as 1989) to about 36 ft3

/s in wet years (such as 1999). In 

WY 1989, 55 percent of the total recharge was applied to the 

Arikaree aquifer and 45 percent was applied to the Ogallala 

aquifer. In WY 1999, 33 percent of the total recharge was 

applied to the Arikaree aquifer and 67 percent was applied to 

the Ogallala aquifer.
Numerical Model 47

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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")

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")

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")

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")

White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

Lake Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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agle Nest Creek

Spring Creek

Medicine Root Creek

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Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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A

B

C

D

5.3

-3.1 24.9

-4.2

21.5

1.8

19.6

8.6

5.6

-1.7 -30

-15.5

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Extent of Ogallala aquifer (model layer 1)Observation well completed in Ogallala aquifer

—Number is mean 

difference between simulated and observed hydraulic head, in feet. Letter is well identifier for representative well hydrograph (fig. 24)

! -1.7

C

EXPLANATION

Figure 22.

Mean difference between simulated and observed hydraulic heads for long-term observation wells completed in the Ogallala aquifer in the 

study area for the transient simulation, water years 1980–2009.
48 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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")

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")

")

")

")

")

")

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")

White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

Lake Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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agle Nest Creek

Spring Creek

Medicine Root Creek

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Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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!

!

!(

!

!(

!

!

!(

!

!(

!

!(

!

!

!(

!(

!

!(

!

!(

!

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!(

!(

!(

!(

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Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Ogallala aquifer (model layer 1)Difference between simulated and observed hydraulic head, in feet

!( -84.8 to -50.0

!( Greater than -50.0 to -20.0

! Greater than -20.0 to 20.0

!( Greater than 20.0 to 29.9

Figure 23. Difference between simulated and observed hydraulic heads for wells completed in the Ogallala aquifer in the study area with a single 

measurement for the transient simulation, water years 1980–2009.
Numerical Model 49

Hydraulic head, in feet above North American Vertical Datum of 1988 

3,020

3,030

3,040

3,050

3,060

3,070

3,080

1979 1984 1989 1994 1999 2004 2009

Calendar year

3,260

3,270

3,280

3,290

3,300

3,310

3,320

1979 1984 1989 1994 1999 2004 2009

Calendar year

Simulated

Observed

C. Well C (station identification number 430256101160001) D. Well D (station identification number 425956101424101) 

EXPLANATION

Simulated

Observed

EXPLANATION

2,890

2,900

2,910

2,920

2,930

2,940

2,950

Simulated

Observed

A. Well A (station identification number 431531101282701) 

EXPLANATION

2,890

2,900

2,910

2,920

2,930

2,940

2,950

B. Well B (station identification number 430840101213602) 

Simulated

Observed

EXPLANATION

Ogallala aquifer in the study area. A, well A; B, well B; C, well C, and D, well D.

Figure 24. Simulated and observed hydraulic heads for the transient simulation for selected observation wells completed in the 

Hypothetical Simulations

Simulations of hypothetical increased well withdrawals 

and extended drought were completed using the calibrated 

model. The Arikaree aquifer is present in most of the Pine 

Ridge Indian Reservation area, and therefore the results of 

hypothetical increased withdrawal and extended drought simulations were compared to the results of the calibrated simulation for the Arikaree aquifer. The comparisons were made to 

provide a general characterization of the groundwater response 

to additional stresses.

A hypothetical increased well withdrawal scenario was 

simulated with additional withdrawals of 0.2 ft3

/s from 50 

hypothetical wells completed in the Arikaree aquifer (fig. 30). 

The simulation represents a total increase in well withdrawals 

of 10 ft3

/s from the Arikaree aquifer. The difference in hydraulic head between the end of the 30-year calibrated simulation 

and the end of the 30-year hypothetical increased pumping 

simulation ranged from 0 to 66 ft (fig. 30). A new equilibrium 

in hydraulic head was approached near the end of the 30-year 

simulation. As the effects of pumping on hydraulic head propogated outward, a larger fraction of pumping was offset by 

decreases in evapotranspiration and discharge to streams. The 

greatest drawdowns in hydraulic head were in upland areas 

and less in stream valleys where the hydraulic head was within 

7 ft of the evapotranspiration extinction depth. Where the Arikaree aquifer was confined, the decrease in hydraulic head was 

small compared to the unconfined part of the aquifer because 

of induced inflow to the Arikaree aquifer from the overlying 

Ogallala aquifer.

Simulation results for the hypothetical increased well 

withdrawals were compared to the calibrated 30-year simulation to describe how various water budget components 

for the Arikaree aquifer were affected over time (fig. 31). 

Increased well withdrawal resulted in an increase in inflow 

from the overlying Ogallala aquifer and decreases in aquifer storage, discharge to streams, and evapotranspiration. In 

the first year, decreased aquifer storage accounted for about 

69 percent (6.9 ft3/s) of the overall increased well withdrawal 

rate. Decreases in discharge to streams accounted for about 

6 percent (0.6 ft3

/s), decreased evapotranspiration accounted 

for about 7 percent (0.7 ft3

/s), and increased inflow from the 

Ogallala aquifer accounted for about 18 percent (1.8 ft3

/s) of 

increased well withdrawal. Increased inflow at constant-head 

boundaries as a result of increased pumping was less than 

1 percent. After 10 years of pumping, decreased discharge to 
50 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

")

White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

18 £¤

44 ¬«

40 ¬« 73 ¬«

73 ¬«

87 ¬« 61 ¬«

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Vetal

Swett

Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

2,800

3,100

2,700

3,600

2,600

2,700

2,900

2,900

2,600

2,700

2,900

2,700

2,500

2,800

2,800

2,900

2,900

2,600

3,100

3,000

2,900

3,500

6, 2 00

3,400

2,700

2,800

3,300

2,900

3,100

3,200

3,000

2,800

3,100

2,700

3,600

2,600

2,700

2,900

2,900

2,600

2,700

2,900

2,700

2,500

2,800

2,800

2,900

2,900

2,600

3,100

3,000

2,900

3,500

6, 2 00

3,400

2,700

2,800

3,300

2,900

3,100

3,200

3,000

3,000

3,100

3,200

2,900

2,800

2,700

3,300

3,400

2,600

3,500

2,500

2,800

2,500

2,600

3,100

2,800

3,000

3,000

3,000

2,700

3,300

3,400

2,900

3,500

2,900

3,300

3,400 2,900

2,600

3,000

3,100

3,200

2,900

2,800

2,700

3,300

3,400

2,600

3,500

2,500

2,800

2,500

2,600

3,100

2,800

3,000

3,000

3,000

2,700

2,700

3,300

3,400

2,900

3,500

2,900

3,300

3,400 2,900

2,600

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14North American Vertical Datum of 1988 (NAVD 88)

0 10 20 5 MILES

0 10 20 5 KILOMETERS EXPLANATION

Extent of Arikaree aquifer (model layer 2)Simulated potentiometric contourDirection of groundwater flow

—Shows the altitude at which water level would have stood in 

tightly cased wells. Contour interval 100 feet. Datum is NAVD 88

Generalized potentiometric contour—Shows the altitude at which water level would have stood in 

tightly cased wells. Dashed where approximately located. Contour interval 100 feet. Datum is NAVD 88

Figure 25. Comparison of the simulated potentiometric surface to the generalized potentiometric surface for the Arikaree aquifer for the steady-state simulation in the study area.
Numerical Model 51

Table 16. Difference between simulated and observed hydraulic heads for long-term observation wells completed in the Arikaree 

aquifer in the study area for the transient simulation, water years 1980–2009.

[USGS, U.S. Geological Survey; --, not applicable]

USGS station 

identifiction number Local number Number of observations

Arithmetic mean of differences 

between simiulated and 

observed values

Mean of absolute difference 

between simiulated and 

observed values

430027102311801 35N44W17DBCA 43 32.0 32.0

433100102002101 41N39W19ACAA 60 28.8 28.8

433020101394201 41N37W24DDDD 53 -3.9 3.9

432740101223501 40N34W 6DDDA 58 7.8 7.8

430055101440002 40N37W30DDDD2 58 36.5 36.5

432410101294002 40N35W31AAAA2 54 70.4 70.4

432120101120001 39N41W17CBBB 58 23.9 23.9

431958101582101 39N39W19DDBC (2) 56 -9.2 9.2

432038101223501 39N34W19AAAA (2) 56 29.2 29.2

431530101264101 38N35W23BABB 61 1.5 1.5

431458101483001 38N38W22CBDC 57 5.0 5.0

431022101570101 37N39W17DDDD 60 3.3 3.3

431022101555001 37N39W16DDDD 56 -7.7 7.7

431045101293701 37N35W18DABA 59 6.1 6.1

430928101532401 37N39W26AAAA 60 -0.8 0.8

431018101212001 37N34W17DDDD 59 -17.7 17.7

430923101484301 37N38W28AAAA 61 -1.1 1.1

430835101554601 37N39W34BBB 60 -2.4 2.4

430925101272001 37N35W28AAAA 60 9.4 9.4

430748102154801 36N42W 4ABA 58 4.7 4.7

430832101364701 37N36W31AAA 60 -0.1 0.1

430744101593201 36N40W 2ABA 60 5.6 5.6

430835101295001 37N35W31AAAA (2) 60 0.9 0.9

430840101213601 37N34W28CCCC 60 27.2 27.2

430715101444701 36N38W 1DCDD (2) 60 7.0 7.0

430706101391001 36N37W11BBBB 62 -4.1 4.1

430757101223801 36N35W 1AAAA 53 19.6 19.6

430642101455801 36N38W10ADDD 61 6.6 6.6

430757101264701 36N35W 9BAAA 53 -29.6 29.6

430653101383401 36N35W11BDAD 54 25.9 25.9

430620101234501 36N35W12CCCC 53 14.8 14.8

430524101481601 36N38W16CCCC 57 17.8 17.8

430520101260401 36N35W15CCCC 57 16.8 16.8

430429101320401 36N36W22DDDD (2) 60 5.1 5.1

430253101420701 36N37W32DBCB 52 -0.7 0.7

430200102130001 35N42W 1CDCB 57 -6.8 6.8

430027102311806 35N44W17DBCA6 45 32.1 32.1

432251103221001 39N43W 2BAAA 60 23.1 23.1

Mean -- -- 9.5 14.3
52 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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Spring Creek

Medicine Root Creek

18 £¤

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Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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28.8 -3.9

7.8

36.5 70.4

23.9

-9.2 29.2

1.5

5

3.3

-7.7 6.1

-0.8

-17.7

-1.1 -2.4

9.4 4.7

-0.1 5.6 0.9

27.2

7 -4.1

19.6 6.6

-29.6 25.9

14.8 17.8 16.8

5.1

-0.7

-6.8

32.1

23.1

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Observation well completed in Arikaree aquifer—Number is mean 

difference between simulated and observed hydraulic head, in feet. Letter is well identifier for representative well hydrograph (fig. 28)

!G 4.7

Extent of the Arikaree aquifer (model layer 2)

Figure 26.

Mean difference between simulated and observed hydraulic heads for long-term observation wells completed in the Arikaree aquifer in 

the study area for the transient simulation, water years 1980–2009.
Numerical Model 53

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

k

agle Nest Creek

Spring Creek

Medicine Root Creek

18 £¤

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44 ¬«

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Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

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Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Extent of Arikaree aquifer (model layer 2)Difference between simulated and observed hydraulic head, in feet

!( Greater than -164.9 to -100.0

!( Greater than -100.0 to -50.0

!( Greater than -50.0 to -20.0

! Greater than -20.0 to 20.0

!( Greater than 20.0 to 50.0

!( Greater than 50.0 to 100.0

!( Greater than 100.0 to 155.4

Figure 27. Difference between simulated and observed hydraulic head for wells completed in the Arikaree aquifer in the study area with a single measurement for the transient simulation, water years 1980–2009.
54 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

2,760

2,770

2,780

2,790

2,800

2,810

2,820

B. Well F (station identification number 433020101394201) 

2,860

2,870

2,880

2,890

2,900

2,910

2,920

Simulated

Observed

A. Well E (station identification number 432251103221001) 

EXPLANATION

Simulated

Observed

EXPLANATION

3,320

3,330

3,340

3,350

3,360

3,370

3,380

Simulated

Observed

C. Well G (station identification number 430748102154801) 

EXPLANATION

2,750

2,760

2,770

2,780

2,790

2,800

2,810

D. Well H (station identification number 432038101223501) 

Simulated

Observed

EXPLANATION

3,250

3,260

3,270

3,280

3,290

3,300

3,310

1979 1984 1989 1994 1999 2004 2009

Simulated

Observed

E. Well I (station identification number 430027102311801) 

EXPLANATION

3,030

3,040

3,050

3,060

3,070

3,080

3,090

1979 1984 1989 1994 1999 2004 2009

Calendar year Calendar year

F. Well J (station identification number 430757101264701) 

Simulated

Observed

EXPLANATION

Hydraulic head, in feet above North American Vertical Datum of 1988 

Figure 28. Simulated and observed hydraulic heads for the transient simulation for selected observation wells completed in the 

Arikaree aquifer in the study area. A, well E; B, well F; C, well G; D, well H; E, well I; and F, well J.
Numerical Model 55

Table 17. Mean simulated groundwater discharge to stream reaches in the study area for transient simulation, water years 1980–2009.

[--, not applicable]

Stream reach 

identifier 

(table 11; fig. 17)

Description of stream reach

Mean groundwater 

discharge to stream reaches, 

water years 1980–2009 

(cubic feet per second)

Difference between 

mean simulated and 

observed discharge 

(cubic feet per second) Simulated Observed

Stream reach with estimated groundwater discharge

BLCa Bear-in-the-Lodge Creek and Spring Creek tributary. 

Streamgage 06446700 is located at model boundary

12.1 11.7 0.4

LAKE_CRa Lake Creek upstream from streamgage 06447500 16.6 19.3 -2.7

LWR_MRa Little White River upstream from streamgage 06447500 12.9 16.2 -3.3

LWR_VETa Little White River between streamgage 06447500 and 

streamgage 06449100, which includes the part of Lake Creek 

from streamgage 06449000 to mouth at Little White River

20.0 16.8 3.2

MR_CRb Medicine Root Creek 7.9 6.9 1.0

POR_CRb Porcupine Creek 5.0 4.4 0.6

WCC_OGLa White Clay Creek upstream from streamgage 06445980 3.0 3.1 -0.1

WKC_WK_BLb Wounded Knee Creek downstream from streamgage 06446100 

to model boundary

9.8 6.8 3.0

WKC_WKa Wounded Knee Creek upstream from stream-gage 06446100 to 

model boundary

4.8 3.5 1.3

Subtotal 92.1 88.7 3.4

Stream reach without estimated groundwater discharge

COT_CR Cotton Creek 0.6 -- --

CRA_CR Craven Creek 1.7 -- --

EAG_N_CR Eagle Nest Creek 1.9 -- --

GRA_CR Grass Creek 2.9 -- --

LWR_VET_BLW Little White River downstream from stream-gage 06449100 to 

model boundary

3.6 -- --

PASS_CR Pass Creek 1.7 -- --

POT_CR Potato Creek 3.0 -- --

WCC_BL White Clay Creek downstream from stream-gage 06445980 0.3 -- --

Total groundwater discharge to streams 107.8 -- --

a

Discharge calculated from streamflow-gaging records.

b

Discharge calculated from correlation with discharge for nearby gaged stream reaches.
56 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

0

5

10

15

20

25

30

35

40

A. Stream reach WCC_OGL (White Clay Creek) 

Simulated

Observed

EXPLANATION

0

5

10

15

20

25

30

35

40

B. Stream reach WKC_WK (Wounded Knee Creek) 

Simulated

Observed

EXPLANATION

0

5

10

15

20

25

30

35

40

C. Stream reach BLC (Bear-in-the-Lodge Creek) 

Simulated

Observed

EXPLANATION

0

5

10

15

20

25

30

35

40

D. Stream reach LWR_MR (Little White River) 

Simulated

Observed

EXPLANATION

0

5

10

15

20

25

30

35

40

E. Stream reach LAKE_CR (Lake Creek) 

Simulated

Observed

EXPLANATION

0

5

10

15

20

25

30

35

40

1979 1984 1989 1994 1999 2004 2009 1979 1984 1989 1994 1999 2004 2009

Calendar year Calendar year

F. Stream reach LWR_VET (Little White River) 

Simulated

Observed

EXPLANATION

Groundwater discharge, in cubic feet per second 

Figure 29. Simulated and estimated discharge for stream reaches with gaged streamflow in the study area.
Numerical Model 57

Table 18. Water budget for steady-state and transient simulations for selected water years.

[Budget component rates in cubic feet per second; WY, water year]

Budget component Steady state Dry period Wet period

WY 1987 WY 1989 WY 1997 WY 1999

Inflows

Constant head 80 81 87 70 59

From streams 41 38 39 25 29

Recharge 347 240 119 654 1,046

Total 468 359 245 749 1,134

Outflows

Constant head 38 38 35 43 56

Wells 6 10 19 12 11

To streams 141 142 136 178 185

Evapotranspiration 270 271 243 301 368

Total 455 461 427 534 620

Change in storage (inflows 

minus outflows)

0a -102 -182 215 514

a

For the steady state stress period, the change in storage is 0. Inflows minus outflows equals 13 cubic feet per second.

streams accounted for 19 percent (1.9 ft3/s) of the increased 

well withdrawal and decreased evapotranspiration accounted 

for 23 percent (2.3 ft3

/s). After 20 years of pumping, decreased 

discharge to streams accounted for 23 percent (2.3 ft3

/s) of the 

increased well withdrawal and decreased evapotranspiration 

accounted for 51 percent (5.1 ft3

/s). At the end of the 30-year 

increased pumping simulation, decreased discharge to streams 

accounted for about 26 percent (2.6 ft3

/s) of increased well 

withdrawal, and decreased evapotranspiration accounted for 

53 percent (5.3 ft3

/s). The change in aquifer storage represented only about 3 percent (0.3 ft3

/s) of increased well 

withdrawal, and inflow from the overlying Ogallala aquifer 

remained at 18 percent (1.8 ft3

/s) of increased well withdrawal. 

As time progressed, a greater percentage of the pumping 

was accounted for by decreases in discharge to streams and 

evapotranspiration. Most of the decreased discharge to streams 

was realized during the first 10 years of the increased pumping 

simulation, whereas evapotranspiration generally continued to 

decrease throughout the simulation.

A hypothetical drought scenario was simulated using a 

decrease in recharge of 0.2 in. (24 ft3

/s) for each simulated 

water year. The difference in hydraulic head between the 

end of the 30-year calibrated simulation and the end of the 

hypothetical drought simulation ranged from 0 to 10.9 ft 

(fig. 32). The smallest declines in hydraulic head were in the 

stream valleys, and the greatest declines were in upland areas. 

Drawdown generally was smaller in the Arikaree aquifer in 

the southern part of the model area where the Arikaree aquifer 

is overlain by the Ogallala aquifer. Constant-head boundary 

conditions likely affect this simulation, and the actual decline 

in hydraulic head would likely be greater near the southern 

and eastern boundaries with an extended drought.

Decreased recharge to the Arikaree aquifer during the 

hypothetical drought was offset mainly by decreases in aquifer 

storage, discharge to streams, and evapotranspiration (fig. 33). 

In the first year, decreased aquifer storage accounted for 

about 79 percent (17.0 ft3

/s) of the overall decreased annual 

recharge, decreased discharge to streams accounted for about 

5 percent (1.2 ft3

/s) of decreased recharge, and decreased 

evapotranspiration accounted for about 15 percent (3.6 ft3

/s) 

of decreased recharge. Inflow through constant-head cells 

accounted for only about 1 percent (0.2 ft3

/s) of decreased 

recharge, and increased inflow from the Ogallala aquifer 

accounted for less than 1 percent of decreased recharge. After 

10 years hypothetical drought, decreased discharge to streams 

accounted for 17 percent (4.0 ft3/s) of decreased recharge, 

and decreased evapotranspiration accounted for 40 percent 

(9.4 ft3/s). After 20 years of hypothetical drought, decreased 

discharge to streams accounted for 21 percent (4.9 ft3/s) of the 

increased well withdrawal, and decreased evapotranspiration 

accounted for 72 percent (17.2 ft3/s). At the end of 30-year 

hypothetical drought simulation, about 23 percent (5.5 ft3/s) of 

decreased recharge was accounted for from decreased discharge to streams, 72 percent (17.3 ft3

/s) was from decreased 

evapotranspiration, and aquifer storage change represented 0 

percent of decreased recharge. Increased inflow from the overlying Ogallala aquifer accounted for about 2 percent (0.5 ft3

/s) 

of decreased recharge, and inflow through constant-head cells 

accounted for about 3 percent (0.7 ft3/s) of decreased recharge. 

As time progressed, a greater percentage of the reduced 

recharge rate was accounted for by decreased discharge to 

streams and evapotranspiration. Most of the decreased discharge to streams was realized during the first 10 years of the 

hypothetical drought simulation, whereas evapotranspiration 

generally continued to decrease throughout the simulation.
58 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 19. Water budget for transient simulation for dry (1989) and wet (1999) water years by model layer in the 

study area.

[Budget component rates in cubic feet per second; WY, water year]

Budget component WY 1989 WY 1999

Model layer 1

Inflows Constant head 70 46

From streams 35 25

Recharge 54 706

From model layer 2 51 54

Total 210 831

Outflows Constant head 12 28

Wells 9 4

To streams 70 101

Evapotranspiration 156 216

To model layer 2 73 90

Total 320 439

Change in storage (inflows minus outflows) -110 392

Model layer 2

Inflows Constant head 18 13

From streams 3 5

Recharge 65 340

From model layer 1 73 90

Total 159 448

Outflows Constant head 23 28

Wells 10 7

To streams 66 85

Evapotranspiration 86 152

To model layer 1 51 54

Total 236 326

Change in storage (inflows minus outflows) -77 122

Model Limitations

The numerical model adequately simulated flow in the 

Ogallala and Arikaree aquifers in the study area for transient 

and hypothetical future conditions; however, as with any 

conceptual or numerical model, certain limitations should be 

considered when using the model and its results. Model limitations arise from aspects of the conceptual model and from 

simplifications inherent in the construction and calibration of 

the numerical model. These limitations 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 field measurements or estimates were not available; therefore, these parameters were estimated or calculated 

with the data that were available.

The numerical model is limited in its application by simplifying assumptions that were necessary to represent the aquifers mathematically. Aquifer properties were averaged for a set 

of rectangular cells that represented a finite volume of aquifer 

material that could vary substantially within that volume. The 

materials that make up these aquifers were deposited in many 

discontinuous layers that ranged from impermeable clays to 

very permeable sands and gravels. Local hydraulic properties 

could vary substantially from the generalized representation in 

the model. Hydraulic connection between depositional layers 

could be very discontinuous. As a result, the actual response 

of the aquifers to local stress could vary substantially from 

that represented by the model. Ranges of hydraulic conductivity used in the numerical model were based on general ranges 

of previously published values (table 10), but final values 

were determined through model calibration. Model accuracy 

is dependent, primarily, on the accuracy of the estimates of 
Numerical Model 59

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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Medicine Root Creek

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Allen

Martin

Oglala

Tuthill

Wanblee

Manderson

Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

!

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Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Simulated difference in hydraulic head, in feet

0 to 0.5Greater than 0.5 to 1Greater than 1 to 2

Greater than 2 to 5Greater than 5 to10Greater than 10 to 66

Arikaree aquifer boundary (model layer 2)

! Hypothetical well pumping at 0.2 cubic foot per second

Figure 30. Simulated difference in hydraulic head in the Arikaree aquifer in the study area between the end of the calibrated simulation and the end of the 30-year simulation with 50 hypothetical wells completed in the Arikaree aquifer withdrawing 0.2 cubic foot per second.
60 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

0

1

2

3

4

5

6

7

8

9

10

Water budget components, in cubic feet per second 

1980 1985 1990 1995 2000 2005

Water year

Decrease in evapotranspiration

Decrease in discharge to streams

Increase in inflow from Ogallala aquifer

Change in aquifer storage

Figure 31. Change in simulated water 

budget components in the study area based 

on hypothetical additional withdrawals of 

0.2 cubic foot per second at 50 hypothetical 

wells completed in the Arikaree aquifer 

compared to the calibrated simulation.

model input parameters. Nevertheless, calibration of the model 

yielded hydraulic conductivity distributions that were deemed 

acceptable, given the data available. It is reasonable to assume 

that similar hydraulic conductivity distributions could exist 

that also would yield satisfactory model results. Additionally, 

field-verified aquifer properties could help constrain the model 

calibration process, and, as a result, enhance the applicability 

of the model.

Limitations associated with representation of the surfacewater network should be considered. Hydraulic interaction of 

the aquifers with streams likely is much more complex than 

the model can adequately represent. Little information was 

available regarding the streambed properties and how they 

change within the model area. The hydraulic properties of 

streambeds were integrated in the model over several stream 

miles when, in reality, the properties can change drastically at 

the foot scale. Streambed conductance can even be considered 

a transient property, subject to flooding events, which seasonally change the texture and thickness of the riverbed material 

in different stream reaches. In addition, these stream reaches 

could include a range of hydrologic conditions that include 

seeps, springs, and impermeable or very permeable layers. 

Variation in the incision and width of the streams into the 

underlying aquifer could be substantially different on a local 

scale.

Recharge, evapotranspiration, and pumping withdrawals 

also were averaged over time, which limited model calibration 

to these stresses. Calibration data were sparse in several areas, 

which also limited the effectiveness of model calibration. 

Special caution should be exercised when examining the effect 

of simulated stresses at local scales. Analysis of the effects of 

site-specific pumping stresses would require more site-specific 

investigation. The described model limitations should be 

considered when using the model to evaluate stresses on the 

aquifer and in making management decisions.

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 types of calibration targets, transient hydraulic-head measurements and discharge to streams as base flow, were used to 

the extent of available information. Weights were given to calibration targets in an attempt to impose a degree of certainty to 

the calibration process. In other words, calibration targets for 

measurements that had a higher certainty were given a higher 

weight; therefore, calibration targets for hydraulic-head measurements at observation wells with multiple measurements 

completed in the Ogallala and Arikaree aquifers were given 

much more weight when compared to wells with a single 

water-level measurement that had been site visited. Similarly, 

calibration targets for wells with a single water-level measurement that had not been site visited were given the lowest 

weight in the calibration process. For base-flow calibration 

targets, base flow determined along gaged stream reaches was 

given a higher weight when compared to base flow determined 

in ungaged reaches. Calibration targets for hydraulic head and 

base flow also were weighted proportionally in an attempt to 

prevent the model calibration process from becoming biased 

to one calibration target type; therefore, individual targets for 

base flow were given more weight in the calibration process 

compared to individual hydraulic-head targets.

Simulated hydraulic heads at observation wells (figs. 24

and 28) and simulated base flow (fig. 29) generally had less 

seasonal variability when compared with observed or estimated values. For some observation wells, multiple measurements were taken per year, which directly translated to 

multiple calibration targets for some model stress periods. It is 

possible that for locations with multiple calibration targets per 

stress period, some of the model to measurement misfit cannot 

be rectified during the calibration process. Nevertheless, all 

observations available were used during model calibration 

with the assumption that the calibration process would tend 

toward the mean of observations during any give stress period. 

Hydrographs for some observation wells also display a persistent bias. Some of the wells were close to model boundary 

conditions. For example, wells E and H (figs. 26 and 28) are 

close to river cells used to simulate groundwater exchange in 
Numerical Model 61

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BADLANDS

NATIONAL PARK

LACREEK NATIONAL

WILDLIFE REFUGE

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White River

SOUTH DAKOTA

NEBRASKA BENNETT COUNTY

CHERRY COUNTY

PENNINGTON COUNTY

SHERIDAN COUNTY

JACKSON COUNTY

FALL RIVER COUNTY

SHANNON COUNTY

DAWES

COUNTY

TODD COUNTY

MELLETTE COUNTY

27 ¬«

White River

Little Whi et River

Pass Creek

Potato Creek

Porcupine Creek

Wounded Knee Creek

Grass Creek

aL ke Creek

White Clay Creek

Craven Creek

Bear-in-the-Lodge Cree

E

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Spring Creek

Medicine Root Creek

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Tuthill

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Porcupine

Batesland

Harrington

Pine Ridge

Long Valley

Potato Creek

Wounded Knee

Sharps 

Corner

101°30' 102°00' 102°30' 103°00'

43°30'43°00'

Base from U.S. Geological Survey digital data, 2005, 1:100,000Universal Transverse Mercator projection, Zone 14

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Difference in hydraulic head, in feet

0 to 0.5Greater than 0.5 to 1Greater than 1 to 2

Greater than 2 to 3Greater than 3 to 5Greater than 5 to 10.9

Arikaree aquifer boundary (model layer 2)

Figure 32. Difference in hydraulic head in the Arikaree aquifer in the study area between the end of calibrated simulation (nondrought simulation) and the end of the hypothetical 30-year drought simulation.
62 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

0

5

10

15

20

Water budget components, in cubic feet per second 

1980 1985 1990 1995 2000 2005

Water year

Decrease in evapotranspiration

Decrease in discharge to streams

Increase in inflow from Ogallala aquifer

Increase in inflow at boundaries

Change in aquifer storage

Figure 33. Change in simulated water budget 

components for the Arikaree aquifer in the study 

area based on the hypothetical drought simulation 

when compared to the calibrated simulation.

Porcupine Creek and Pass Creek, respectively (fig. 14). The 

proximity of a calibration target to a boundary condition could 

negatively affect the calibration process because the hydraulic head observed in the well may be directly affected by the 

hydraulic head in the boundary condition cell.

The simulated potentiometric surfaces were smoothed 

compared to the generalized potentiometric surfaces based 

on measured values. Simulated groundwater-flow directions 

generally were consistent with the conceptual model; however, at a local scale, groundwater-flow gradients could vary 

substantially compared to those calculated by the model. This 

probably resulted from simulating each aquifer as a single 

layer. The fluvial sediments that make up the aquifers include 

considerable layering of high and low permeability sediments 

that could result in large gradients between wells completed at 

different intervals within the aquifer.

Head-dependent boundary conditions, such as river and 

constant-head cells, for the two hypothetical future stress 

scenarios were assumed to be equivalent to the calibrated 

scenario. For this reason, it is possible that declines in hydraulic head near head-dependent boundary conditions may not 

represent potential declines during these stress scenarios. In 

fact, declines in hydraulic head would likely be greater than 

the model simulated values near head-dependent boundaries 

during extended time periods of increased aquifer stress.

The two-layer model grid with 1,640-ft grid spacing 

was determined to be sufficient spatial discretization, and one 

stress period per year was determined to be sufficient temporal 

discretization, to produce reasonable model results. The chosen discretization of spatially varied aquifer parameters and 

temporally varied aquifer stresses likely resulted in a smoothing of simulated changes in hydraulic head and base flow for 

the study area.

Summary

The Ogallala and Arikaree aquifers are the largest source 

of groundwater on the Pine Ridge Indian Reservation and are 

used extensively for irrigation and public and domestic water 

supplies. To assess the potential for decreased water levels and 

discharge to streams in the Pine Ridge Indian Reservation, 

conceptual and numerical models of groundwater flow in the 

Ogallala and Arikaree aquifers in southwestern South Dakota 

were developed by the U.S. Geological Survey in cooperation 

with the Oglala Sioux Tribe. The study area includes most of 

the Pine Ridge Reservation in Jackson and Shannon Counties and Indian trust lands in Bennett County in southwestern 

South Dakota.

The High Plains aquifer, which includes the Ogallala 

and Arikaree aquifers, generally is less developed in South 

Dakota compared with other areas underlain by this aquifer; 

thus, water levels in the High Plains aquifer in South Dakota 

generally changed less than 5 feet from 1980 to 1999. Despite 

minimal water-level changes in the High Plains aquifer in 

South Dakota, extensive withdrawals of groundwater for irrigation have caused water-level declines in many parts of the 

aquifer and increased concerns about the long-term sustainability; thus, continued or increased withdrawals from the 

aquifer or prolonged drought have the potential to affect water 

levels within the aquifer and discharge to important streams in 

the area. 

Altitude of the land surface ranges from about 4,025 feet 

in the southwestern part of the study area to 2,100 feet in the 

northeastern part of the study area. The Ogallala and Arikaree 

aquifers generally consist of poorly consolidated claystones, 

siltstones, sandstones, and shale deposited in fluvial and 

lacustrine environments. Saturated thickness ranged from 10 

to 314 feet for the Ogallala aquifer and from 10 to 862 feet for 

the Arikaree aquifer. Previous hydraulic conductivity estimates 

ranged from less than 1 to 180 feet per day (ft/d) for the Ogallala aquifer and less than 1 to 13 ft/d for the Arikaree aquifer.
Summary 63

Recharge to the Ogallala and Arikaree aquifers occurs 

from precipitation on the outcrop areas. Discharge from the 

Ogallala and Arikaree aquifers 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.

The generalized groundwater-flow direction in the Ogallala and Arikaree aquifers is to the northeast with local flow 

towards streams. Precipitation for water years 1980–2009 

ranged from about 11 to 39 inches per year (in/yr) and averaged about 19.1 in/yr. Estimated mean recharge for water 

years 1980–2009 was about 17.3 percent of precipitation for 

the Ogallala aquifer and 7.9 percent of precipitation for the 

Arikaree aquifer. The estimated mean maximum evapotranspiration rate for WYs 1980–2009 was about 35 in/yr. The 

estimated mean base flow for gaged streams in the study area 

was about 0.06 cubic foot per second (ft3/s) per square mile of 

drainage area. Estimated mean total water use for water years 

1980–2009 was 5.4 ft3/s from the Ogallala aquifer and 7.1 ft3/s 

from the Arikaree aquifer.

A two-layer numerical groundwater-flow model was 

constructed using MODFLOW–NWT with a uniformly 

spaced grid consisting of 166 rows and 288 columns with 

cells 1,640 feet on a side. The numerical model of the Ogallala and Arikaree aquifers was used to simulate steady-state 

and transient conditions for water years 1980–2009. 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. 

For the numerical model, aquifer boundaries were noflow on the northern and western sides of the model area and 

constant-head on the southern and eastern sides of the model 

area. The mean arithmetic difference between 731 simulated 

and observed hydraulic heads in the Ogallala aquifer (683 

time-series measurements from observation wells and 48 from 

wells with a single water-level measurement) was 1.4 feet. The 

mean arithmetic difference between the 2,754 simulated and 

observed hydraulic heads in the Arikaree aquifer (2,171 timeseries measurements from observation wells and 583 from 

wells with a single water-level measurement) was 9.8 feet. 

For stream reaches with estimated groundwater base flow, the 

simulated total discharge was 92.1 ft3/s compared to estimated 

total discharge of 88.7 ft3/s. 

Calibrated recharge for the transient simulation averaged 

3.3 in/yr for the Ogallala aquifer and 1.1 in/yr for the Arikaree aquifer. The calibrated mean maximum potential evapotranspiration rate was 35.4 in/yr. Streambed conductance for 

perennial stream reaches represented with the River package 

ranged from 101 to 1,360 square feet per day and averaged 

530 square feet per day. Horizontal hydraulic conductivity for 

the Ogallala aquifer ranged from 4 to 70 ft/d and averaged 

27 ft/d. Horizontal hydraulic conductivity for the Arikaree 

aquifer ranged from 0.2 to 8 ft/d and averaged 1.0 ft/d. The 

vertical hydraulic conductivity averaged 1.4 ft/d for the Ogallala aquifer and 0.004 ft/d for the Arikaree aquifer. Specific 

yield for the Ogallala aquifer was 0.15 and averaged 0.027 for 

the Arikaree aquifer. Specific storage for the Arikaree aquifer 

was 1.7x10-6 per foot.

Inflow and outflow for the calibrated steady-state model 

was 459 ft3/s. The percentages of inflows were 17 percent 

from constant-head boundaries, 9 percent from streams, and 

74 percent from recharge. The percentages of outflow were 

8 percent to constant-head boundaries, 1 percent to wells, 

31 percent to streams, and 59 percent to evapotranspiration. 

Simulated net inflow from the Ogallala aquifer to the Arikaree 

aquifer ranged from about 22 ft3/s in dry years to about 37 ft3/s 

in wet years.

Two hypothetical future stress scenarios were simulated 

using the calibrated numerical model. The simulations were 

completed using input from the 30-year simulation of water 

years 1980–2009. The first hypothetical scenario represented 

an increase in groundwater withdrawals from 50 hypothetical 

production wells completed in the Arikaree aquifer. Additional 

withdrawals of 0.2 ft3/s were simulated at each of the 50 hypothetical wells. At the end of the 30-year hypothetical increased 

pumping simulation, water levels declined as much as 66 ft in 

the Arikaree aquifer, decreased discharge to streams accounted 

for about 26 percent (2.6 ft3/s) of increased withdrawals, and 

decreased evapotranspiration accounted for about 53 percent 

(5.3 ft3/s) of increased withdrawals. 

The second hypothetical scenario represented a 30-year 

period of decreased recharge (drought) by decreasing recharge 

by 0.2 in (24 ft3/s) for each water year. At the end of the 

hypothetical drought simulation, water levels declined as 

much as 10.9 ft in the Arikaree aquifer, decreased discharge to 

streams accounted for about 23 percent (5.5 ft3/s) of decreased 

recharge, and decreased evapotranspiration accounted for 

about 72 percent (17.3 ft3/s) of decreased recharge.

The numerical model is a tool that could be used to better understand the flow system of the Ogallala and Arikaree 

aquifers located in the Pine Ridge Reservation area in Bennett, Jackson, and Shannon Counties. Simplifying assumptions were necessary to represent the aquifers mathematically; 

although, field-verified aquifer properties could help constrain 

the model calibration process, and, as a result, enhance the 

applicability of the model. The long-term hydraulic-head measurements were simulated reasonably well using the numerical 

model. Discharge from the Ogallala and Arikaree aquifers to 

rivers, springs, and seeps was simulated using the numerical 

model with reasonable accuracy where data were available. 
64 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

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Appendix 1. Water-Level Data Used to Estimate Generalized Potentiometric Surface of Ogallala Aquifer 67

Appendix 1. Water-Level Data Used to Estimate Generalized Potentiometric 

Surface of Ogallala Aquifer

Selected data for all wells used to estimate the generalized potentiometric surface of the Ogallala aquifer are presented in 

table 1–1.

Table 1–1. Selected data from wells used for generalized potentiometric surface of Ogallala aquifer in the study area.

[USGS, U.S. Geological Survey; NAVD 88, North American Vertical Datum of 1988]

Site 

identifier 

(fig. 8)

USGS station 

identification number Local number

Land surface 

altitude 

(feet above 

NAVD 88)

Water-level period 

of record or date for 

single measurement

Hydraulic head 

(feet above 

NAVD 88)

1 431531101282701 38N35W16CCCC 2,941 1980–2009 2,912a

2 431255101212001 38N34W32DDDD 3,031 1980–2009 2,962a

3 431250101163702 37N34W 1AAAA2 3,114 1980–2003 2,960a

4 431136101200901 37N34W 9AAAA 2,979 1980–2009 2,955a

5 430949101292701 37N35W20CBBA 2,996 1980–2009 2,975a

6 431018101152001 37N33W17CCCC 2,999 1980–2009 2,931a

7 430840101213602 37N34W28CCCC2 2,991 1983–2009 2,909a

8 430825101151801 37N33W32BBBB2 2,961 1981–2009 2,903a

9 430521101223401 36N34W18CCCC (2) 3,072 1980–2009 3,059a

10 430255101291801 36N35W31CDBD 3,201 1983–2009 3,192a

11 430256101160001 36N34W36DBCB 3,051 1981–2009 3,046a

12 425956101424101 35N37W19AADD 3,298 1980–2009 3,293a

13 431555101161201 38N33W18BD 3,117 06/20/1979 3,037

14 431428101221901 38N34W29BB 2,979 02/28/1990 2,945

15 431318101264001 38N35W34CDBC 2,951 10/27/2005 2,938

16 431255101320701 38W36W35DDDD1 3,026 06/05/2007 2,976

17 431235101230801 37N33W 6BD 3,008 08/17/1989 2,942

18 431213101151301 37N33W 5C 3,128 10/17/1977 3,008

19 431201101221701 37N34W 5CCC 3,001 11/30/1980 2,926

20 431148101165001 37N33W 7ABD 3,019 04/30/1981 2,967

21 431144101233401 37N34W 7BC 2,971 10/11/1996 2,957

22 431118101170601 37N33W12DC 3,035 10/28/1996 2,953

23 431022101213601 37N34W17DDDD (2) 2,951 11/02/1978 2,921

24 430928101271601 37N35W21DDDD 2,989 09/29/2009 2,965

25 430807101233001 37N34W31B 3,001 07/25/1977 2,951

26 430716101214801 36N34W 6DBDC 3,021 02/06/1979 2,956

27 430625101303501 36N36W12ACAA 3,016 04/14/1977 3,006

28 430643101242701 36N35W11BDAA 3,055 09/29/2009 3,020

29 430611101460501 36N38W15AA 3,231 10/10/1992 3,201

30 430602101270201 36N35W16BAC 3,051 06/04/1905 3,023

31 430548101205201 36N34W17 3,046 05/21/1996 3,016

32 430532101163301 36N33W13BCC 3,035 05/30/2007 2,965
68 Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers

Table 1–1. Selected data from wells used for generalized potentiometric surface of Ogallala aquifer in the study area.—Continued

[USGS, U.S. Geological Survey; NAVD 88, North American Vertical Datum of 1988]

Site 

identifier 

(fig. 8)

USGS station 

identification number Local number

Land surface 

altitude 

(feet above 

NAVD 88)

Water-level period 

of record or date for 

single measurement

Hydraulic head 

(feet above 

NAVD 88)

33 430519102033101 36N40W20ABBC 3,321 08/03/2004 3,314

34 430518101591001 36N40W23AA 3,397 05/08/1985 3,312

35 430505102022001 36N40W21BCCD 3,355 08/03/2004 3,346

36 430447101495101 36N38W19D 3,341 05/20/1985 3,328

37 430440102072501 36N41W22DD 3,499 12/30/1999 3,439

38 430437101292601 36N35W19C2 3,076 12/12/1990 3,066

39 430431101212901 36N34W19DDD 3,106 05/11/1994 3,048

40 430423101181101 36N34W27A 3,076 09/28/1989 3,034

41 430344101315402 36N36W26CC2 3,201 05/01/1992 3,136

42 430341101383601 36N40W25DD 3,144 04/20/2003 3,104

43 430337101283401 36N35W30DDDD 3,147 08/19/1965 3,140

44 430331101141201 36N33W32BB 3,000 04/01/1972 2,988

45 430247101420501 36N37W32B 3,281 08/01/1974 3,239

46 430306101454101 36N38W35C 3,361 08/01/1974 3,329

47 430300101191301 36N34W33DA 3,159 06/23/2006 3,089

48 430237101523401 35N39W 2BA 3,422 09/19/2007 3,397

49 430234101432601 35N37W 6B 3,251 08/01/1974 3,223

50 430221101350801 35N36W 5BDB 3,225 12/14/2006 3,202

51 430219101253401 35N35W 3 3,161 10/30/1987 3,133

52 430213101221101 35N34W 6BA 3,171 03/21/1990 3,161

53 430211101540301 35N39W 4DA 3,419 06/30/2008 3,414

54 430200101583001 35N40W 1CD 3,458 02/25/1983 3,451

55 430141101295801 35N36W12AAC 3,216 08/16/1991 3,208

56 430104101570501 35N39W 7BDA 3,452 02/23/1983 3,442

57 430123101323101 35N36W10DB 3,251 11/22/1988 3,225

58 430104101353101 35N36W 8CCC 3,251 12/02/1988 3,228

59 430057101384401 35N37W14BA 3,231 05/31/1988 3,216

60 430056102020301 35N40W16BAD 3,504 02/25/1983 3,494

61 430055101300701 35N26W13AB 3,231 06/23/1989 3,223

62 430055101440401 35N38W13AB 3,320 06/16/2004 3,319

63 430055101542101 35N39W16AA 3,458 09/07/2004 3,420

64 430053101183701 35N34W15AB 3,330 08/04/1999 3,172

65 430043101584801 35N40W13BCD 3,461 06/08/2004 3,453

66 430037101372801 35N37W13BD 3,261 05/30/1988 3,238

67 430034101345401 35N36W17DBB 3,241 10/31/1994 3,219

68 430030101495401 35N38W18DB 3,383 09/08/2004 3,377

69 430028101161501 35N34W13AC 3,146 06/17/1991 3,139

70 430015101383601 35N37W14CD 3,271 07/11/2002 3,263

71 430013101290201 35N35W18DC 3,231 07/29/1982 3,229

72 425956101134502 35N33W20ABCC2 3,051 09/14/1993 3,043

a

Value represents mean hydraulic head for period of record.
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Rolla Publishing Service Center 

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/
ISSN 2328–0328 (online)

http://dx.doi.org/10.3133/sir20145241

Davis and others—Conceptual and Numerical Models of Groundwater Flow in the Ogallala and Arikaree Aquifers—Scientific Investigations Report 2014–5241