Scientific Investigations Report 2020–5118

U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the Oklahoma Water Resources Board

Hydrogeology, Numerical Simulation of Groundwater Flow, 

and Effects of Future Water Use and Drought for Reach 1 of 

the Washita River Alluvial Aquifer, Roger Mills and Custer 

Counties, Western Oklahoma, 1980–2015
Front cover: Photograph showing Foss Reservoir and Outlet Works Intake Structure during an 

Annual Site Inspection, June 30, 2016. Photograph by Anna Hoag, P.E., Civil Engineer, Bureau of 

Reclamation. 

Back cover: Photograph showing Foss Reservoir and Outlet Works Intake Structure during the 

Foss Dam Comprehensive Review, March 11, 2015. Photograph by Adam Milligan, Civil Engineering 

Technician, Bureau of Reclamation.
Hydrogeology, Numerical Simulation of 

Groundwater Flow, and Effects of Future 

Water Use and Drought for Reach 1 of the 

Washita River Alluvial Aquifer, Roger Mills 

and Custer Counties, Western Oklahoma, 

1980–2015

By John H. Ellis, Derek W. Ryter, Leland T. Fuhrig, Kyle W. Spears, 

Shana L. Mashburn, and Ian M.J. Rogers

Prepared in cooperation with the Oklahoma Water Resources Board

Scientific Investigations Report 2020–5118

U.S. Department of the Interior

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

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Ellis, J.H., Ryter, D.W., Fuhrig, L.T., Spears, K.W., Mashburn, S.L., and Rogers, I.M.J., 2020, Hydrogeology, numerical 

simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River 

alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015: U.S. Geological Survey Scientific 

Investigations Report 2020–5118, 81 p., https://doi.org/10.3133/sir20205118.

Associated data for this publication:

Ellis, J.H., Ryter, D.W., Fuhrig, L.F., Mashburn, S.L., and Rogers, I., 2020, MODFLOW-NWT model used in simulation of 

groundwater flow, and analysis of projected water use for the Washita River alluvial aquifer, western Oklahoma: U.S. 

Geological Survey data release, https://doi.org/10.5066/P9PKMG6U.

ISSN 2328-0328 (online)
iii

Acknowledgments

This study was conducted as part of the U.S. Geological Survey (USGS) Cooperative Matching 

Funds program in cooperation with the Oklahoma Water Resources Board (OWRB). The authors 

thank Christopher Neel, Geologist, OWRB Water Resources, for help with defining study objectives and providing hydrogeologic and water-use permit data. The authors also thank Daniel 

Clement of Burns & McDonnell Engineering Company, Inc., for providing reports and information 

on the groundwater investigation performed for the City of Clinton, Oklahoma.

The authors thank USGS employees Kyle Rennell and Nicole Paizis, for help in the field and with 

data management.

v

Contents

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

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

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

Purpose and Scope ..............................................................................................................................3

Description of Study Area ...................................................................................................................3

Previous Investigations........................................................................................................................6

Land Cover and Population .................................................................................................................8

Climate....................................................................................................................................................8

Groundwater Use ..................................................................................................................................9

Streamflow Characteristics ..............................................................................................................11

Geologic Units and Hydrogeology of the Study Area ............................................................................12

Hydrogeologic Units ...........................................................................................................................13

Alluvium and Terrace Deposits of Quaternary Age ..............................................................13

Ogallala Formation of Tertiary Age .........................................................................................13

Bedrock Units of Permian Age ................................................................................................13

Groundwater Quality ..........................................................................................................................16

Hydrogeologic Framework of the Washita River Alluvial Aquifer .......................................................19

Aquifer Extent ......................................................................................................................................19

Potentiometric Surface and Groundwater-Level Fluctuations ...................................................21

Textural and Hydraulic Properties ...................................................................................................21

Conceptual Flow Model ..............................................................................................................................25

Water Use ............................................................................................................................................25

Recharge..............................................................................................................................................25

Using the Soil-Water-Balance Code to Estimate Recharge ...............................................27

Using the Water-Table-Fluctuation Method to Estimate Recharge ..................................31

Saturated-Zone Evapotranspiration ................................................................................................33

Streamflow...........................................................................................................................................34

Seepage Runs ............................................................................................................................34

Base Flow ....................................................................................................................................36

Lateral Groundwater Flows ...............................................................................................................37

Lakebed Seepage ...............................................................................................................................38

Conceptual Water Budget .................................................................................................................38

Simulation of Groundwater Flow ...............................................................................................................38

Spatial and Temporal Discretization ................................................................................................38

Hydrologic Boundaries ......................................................................................................................40

Recharge .....................................................................................................................................40

Lateral Groundwater Flow ........................................................................................................40

Streams........................................................................................................................................40

Reservoir .....................................................................................................................................41

Saturated-Zone Evapotranspiration .......................................................................................43

Groundwater Use .......................................................................................................................43

Model Calibration................................................................................................................................43

Calibration Parameters .............................................................................................................45
vi

Calibration Targets .....................................................................................................................45

Groundwater-Level Observations ..................................................................................45

Foss Reservoir Stage Observations ...............................................................................48

Base-Flow and Stream-Seepage Estimates ................................................................48

Calibrated Model Fit ..................................................................................................................48

Groundwater Levels .........................................................................................................49

Base Flow ...........................................................................................................................49

Reservoir Stage and Water Budget ...............................................................................52

Calibrated Water Budget .................................................................................................52

Calibrated Parameter Values ...................................................................................................57

Sensitivity Analysis ....................................................................................................................60

Groundwater-Availability Scenarios.........................................................................................................63

Equal-Proportionate Share ...............................................................................................................63

Projected (50-Year) Groundwater Use ............................................................................................65

Hypothetical (10-Year) Drought ........................................................................................................69

Model Limitations.........................................................................................................................................74

Summary........................................................................................................................................................75

Selected References ...................................................................................................................................77

Figures

1. Map showing locations of hydrological features, observation wells, 

streamgages, climate stations, and cities associated with the study of reach 1 

of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western 

Oklahoma .......................................................................................................................................4

2. Map showing major geographic and surface-water features, 

floodwater-retarding structures, and surface-water diversions in and near the 

Washita River subwatershed, western Oklahoma ..................................................................5

3. Pie graphs showing land cover and crop cover over the Washita River alluvial 

aquifer, western Oklahoma, 2008–18 .........................................................................................9

4. Bar graph showing mean monthly precipitation at the Leedey, Oklahoma, 

climate station for the period 1941–2017, and mean monthly precipitation for 

the dry period 1941–1957 and the wet period 1995–2009 .....................................................10

5. Graph showing wet and dry periods defined as departure of the 5-year 

weighted moving average from the mean annual precipitation, 1920–2017, and 

the number of climate stations with observations ................................................................11

6. Graph showing estimated annual groundwater use and annual precipitation 

from the Leedey climate station during 1967–2015 by category for the Washita 

River alluvial aquifer, western Oklahoma ...............................................................................12

7. Map showing surficial geologic units in the Washita River alluvial aquifer study 

area, western Oklahoma ...........................................................................................................14

8. Stratigraphic chart showing surficial geologic and hydrogeologic units in the 

Washita River alluvial aquifer study area, western Oklahoma ...........................................15

9. Map showing locations of groundwater-quality samples collected from wells in 

the Washita River alluvial aquifer, western Oklahoma, and total dissolved solids 

in groundwater samples collected during July–August 2014 .............................................17
vii

10. Piper diagram showing major cations and anions in groundwater-quality 

samples of produced water from 12 wells open to the Washita River alluvial 

aquifer, western Oklahoma, July–August 2014 ......................................................................18

11. Map showing points and methods used for the interpolation of the aquifer 

thickness of the Washita River alluvial aquifer, western Oklahoma ..................................20

12. Map showing potentiometric-surface contours for March 2017 based on 

groundwater-level altitudes measured in wells and first water reported from 

drillers’ logs completed in the Washita River alluvial aquifer, western Oklahoma .........22

13. Graphs showing annual-mean air temperature, annual-mean precipitation, and 

groundwater-level altitude measured in or near Oklahoma Water Resources 

Board observation wells 2687, 9328, and 2700 completed in the Washita River 

alluvial aquifer, western Oklahoma .........................................................................................23

14. Map showing locations of mean horizontal hydraulic conductivity based 

on lithologic descriptions reported in borehole logs and from aquifer tests, 

Washita River alluvial aquifer, western OklahomaFigure 14. Mean horizontal 

hydraulic conductivity based on lithologic descriptions reported in borehole 

logs and from aquifer tests, Washita River alluvial aquifer .................................................24

15. Map showing locations of permitted groundwater wells and usage categories 

in the Washita River alluvial aquifer, western Oklahoma, 1980–2015 ................................26

16. Graph showing mean annual precipitation and recharge computed by using 

the Soil-Water-Balance code for the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................29

17. Graphs showing monthly mean precipitation and recharge computed by using 

the Soil-Water-Balance code for the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................29

18. Map showing mean annual groundwater recharge computed by using the 

Soil-Water-Balance code for the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................30

19. Graphs showing daily mean groundwater recharge and depth to water at USGS 

observation well WSH01 from April 23, 2015, to March 1, 2017; mean monthly 

changes in groundwater recharge and evapotranspiration at observation 

well WSH01 during 2015–17; and mean monthly groundwater recharge and 

evapotranspiration at observation well WSH02 during 2015–17, Washita River 

alluvial aquifer, western Oklahoma .........................................................................................32

20. Map showing streamflow measurements and gaining and losing reaches from 

calculated base-flow gain or loss from the 2017 seepage runs for the Washita 

River alluvial aquifer, western Oklahoma ...............................................................................35

21. Graph showing total and cumulative streamflow gain or loss (measured 

February 9, 2017) for the Washita River and includes tributary contributions to 

the Washita River........................................................................................................................36

22. Map showing active model area and boundary conditions for the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma .......39

23. Graph showing volume, stage, and surface area for Foss Reservoir in western 

Oklahoma .....................................................................................................................................42

24. Graph showing estimated monthly water demand by groundwater-use type for 

the Washita River alluvial aquifer, western Oklahoma .........................................................44

25. Map showing spatial distribution of pilot points for the Washita River alluvial 

aquifer model, western Oklahoma, 1980–2015 .......................................................................46

26. Graph showing monthly groundwater-level observations as a percentage of 

the total number of groundwater-level observations used for the Washita River 

alluvial aquifer model, western Oklahoma, 1980–2015 .........................................................48
viii

27. Graph showing number of groundwater-level observations per well for wells 

used in the Washita River alluvial aquifer model, western Oklahoma, 1980–2015 ..........48

28. Graphs showing simulated and measured groundwater-level altitude, 

and frequency of hydraulic-head residuals obtained from the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................50

29. Map showing spatial distribution of mean groundwater-level altitude residuals 

for the numerical groundwater-flow model of the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015 .................................................................................................51

30. Graphs showing observed and simulated base flow and total streamflow at U.S. 

Geological Survey streamgages 07316500 Washita River near Cheyenne, Okla.; 

07324200 Washita River near Hammon, Okla.; 07324400 Washita River near 

Foss, Okla.; 07325000 Washita River near Clinton, Okla., used for the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................53

31. Graphs showing observed and simulated stage and storage for Foss Reservoir 

for the numerical groundwater-flow model of the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015 .................................................................................................55

32. Graphs showing annual simulated water budget for Foss Reservoir 

and simulated changes in storage for Foss Reservoir in the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................56

33. Pie graphs showing inflows and outflows for the mean annual calibrated water 

budget for the numerical groundwater-flow model of the Washita River alluvial 

aquifer, western Oklahoma, 1980–2015 ...................................................................................60

34. Graphs showing mean annual simulated groundwater water budget and 

simulated mean annual change in groundwater storage for the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................61

35. Graphs showing mean monthly groundwater inflows and outflows and mean 

monthly change in groundwater storage for the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015 .................................................................................................62

36. Graph showing monthly mean precalibration recharge and monthly mean 

calibrated recharge for the numerical groundwater-flow model of the Washita 

River alluvia aquifer, 1980–2015 ................................................................................................63

37. Graph showing observation group sensitivity by parameter group in the 

numerical groundwater-flow model of the Washita River alluvial aquifer, 

western Oklahoma ......................................................................................................................64

38. Map showing simulated saturated thickness and simulated base flow after 20 

years of continuous equal-proportionate-share groundwater pumping in the 

Washita River alluvial aquifer, western Oklahoma, 1980–2015 ...........................................66

39. Graphs showing changes in simulated groundwater storage during 20 and 40 

years of continuous equal-proportionate-share groundwater pumping in the 

Washita River alluvial aquifer, western Oklahoma, 1980–2015 ...........................................67

40. Graph showing simulated stage and change in simulated storage in 

Foss Reservoir during 20 years of continuous equal-proportionate-share 

groundwater pumping in the Washita River alluvial aquifer, western Oklahoma............68

41. Graph showing change in groundwater storage resulting from a hypothetical 

10-year drought for the Washita River alluvial aquifer, western Oklahoma .....................70
ix

42. Map showing simulated change in saturated thickness after a hypothetical 

10-year drought for the Washita River alluvial aquifer, western Oklahoma .....................71

43. Graphs showing changes in simulated streamflow and base flow for the 

numerical groundwater-flow model of the Washita River alluvial aquifer at U.S. 

Geological Survey streamgages 07316500 Washita River near Cheyenne, Okla.; 

07324200 Washita River near Hammon Okla.; and 07325000 Washita River near 

Clinton, Okla., western Oklahoma, 1980–2007 ........................................................................72

44. Graphs showing changes in stage and storage for Foss Reservoir in response 

to a hypothetical 10-year drought for the Washita River alluvial aquifer, 1980–2007......73

Tables

1. Information for selected continuous-record streamgages in the Washita River 

alluvial aquifer study area, western Oklahoma .......................................................................6

2. Annual-mean streamflow and annual-mean base flow for selected USGS 

streamgages in the Washita River alluvial aquifer study area, 1980–2015 .........................7

3. Mean annual precipitation at selected Mesonet and National Oceanographic 

and Atmospheric Administration cooperative observer climate stations used in 

the analysis of the Washita River alluvial aquifer study area .............................................10

4. Mean annual reported groundwater use in the Washita River alluvial aquifer 

study area, 1967–2015 ................................................................................................................11

5. Conceptual water budget for the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................25

6. Selected climate stations used for assessing the soil-water balance in and 

near the Washita River alluvial aquifer, western Oklahoma ...............................................28

7. Observation group contribution to the objective function for the automated 

calibration of the Washita River alluvial aquifer model, 1980–2015 ...................................44

8. Selected groundwater-level observation wells in and near the Washita River 

alluvial aquifer, western Oklahoma .........................................................................................47

9. Statistical summary of groundwater-level residuals for the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................49

10. Statistical summary of base-flow residuals for the numerical groundwater-flow 

model of the Washita River alluvial aquifer, western Oklahoma, 1980–2015 ....................52

11. Statistical summary of Foss Reservoir stage residuals for the numerical 

groundwater-flow model of the Washita River alluvial aquifer, western 

Oklahoma, 1980–2015 .................................................................................................................55

12. Mean annual calibrated water budget for the numerical groundwater-flow 

model of the Washita River alluvial aquifer, western Oklahoma, 1980–2015 ....................57

13. Annual water budget for the simulation period for the Washita River alluvial 

aquifer, western Oklahoma, 1980–2015 ...................................................................................58

14. Equal-proportionate-share pumping rates for the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015 .................................................................................................64

15. Changes in groundwater storage after 50 years of groundwater use at different 

pumping rates for the Washita River alluvial aquifer, western Oklahoma ........................68

16. Changes in simulated mean annual base flow after 50 years of groundwater 

use at different pumping rates for the Washita River alluvial aquifer, western 

Oklahoma .....................................................................................................................................69
x

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.004047 square kilometer (km2)

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2)

Volume

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

Flow rate

acre-foot per year (acre-ft/yr) 1,233 cubic meter per year (m3/yr)

acre-foot per year (acre-ft/yr) 0.001233 cubic hectometer per year (hm3/yr)

foot per second (ft/s) 0.3048 meter per second (m/s)

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

cubic foot per day (ft3/d) 0.02832 cubic meter per day (m3/d)

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

Hydraulic gradient

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

Transmissivity

foot squared per day (ft2/d) 0.09290 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.

Datum

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

(NAVD 88), unless otherwise noted.

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.
xi

Supplemental Information

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

at 25 °C).

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

or micrograms per liter (μg/L).

Abbreviations

BFI base-flow index

COOP cooperative observer (NOAA station)

DEM digital elevation model

EPS equal-proportionate share

ET evapotranspiration

ETg saturated-zone evapotranspiration

GHB General-Head Boundary

HVSR horizontal-to-vertical spectral ratio

Lidar light detection and ranging

MAY maximum annual yield

NHDPlus National Hydrography Dataset Plus

NOAA National Oceanographic and Atmospheric Administration

NRCS Natural Resources Conservation Service

NWIS National Water Information System

OWRB Oklahoma Water Resources Board

RMSE root-mean-square error

SFR2 Streamflow-Routing Package, version 2

SVD singular value decomposition

SVDA singular value decomposition-assist

SWB Soil-Water-Balance (code)

USGS U.S. Geological Survey

WTF water-table fluctuation

Hydrogeology, Numerical Simulation of Groundwater 

Flow, and Effects of Future Water Use and Drought for 

Reach 1 of the Washita River Alluvial Aquifer, Roger Mills 

and Custer Counties, Western Oklahoma, 1980–2015

By John H. Ellis,1 Derek W. Ryter,1 Leland T. Fuhrig,1 Kyle W. Spears,2 Shana L. Mashburn,1

and Ian M.J. Rogers1

1U.S. Geological Survey.

2Oklahoma State University.

Abstract

The Washita River alluvial aquifer is a valley-fill and 

terrace alluvial aquifer along the valley of the Washita River 

in western Oklahoma that provides a productive source of 

groundwater for agricultural irrigation and water supply. 

The Oklahoma Water Resources Board (OWRB) has designated the westernmost section of the aquifer in Roger Mills 

and Custer Counties, Okla., as reach 1 of the Washita River 

alluvial aquifer; reach 1 is the focus of this report. The OWRB 

issued an order on November 13, 1990, that established the 

maximum annual yield (MAY; 120,320 acre-feet per year 

[acre-ft/yr]) and equal-proportionate-share (EPS) pumping rate 

(2.0 acre-feet per acre per year [(acre-ft/acre)/yr]) for reach 1 

of the Washita River alluvial aquifer. The MAY and EPS were 

based on hydrologic investigations that evaluated the effects of 

potential groundwater withdrawals on groundwater availability in the Washita River alluvial aquifer. Every 20 years, the 

OWRB is statutorily required to update the hydrologic investigation on which the MAY and EPS were based. Because 

30 years have elapsed since the last order was issued, the U.S. 

Geological Survey, in cooperation with the OWRB, conducted 

a new hydrologic investigation and evaluated the effects of 

potential groundwater withdrawals on groundwater flow and 

availability in the Washita River alluvial aquifer.

The Washita River is the primary source of inflow to 

Foss Reservoir, a Bureau of Reclamation reservoir constructed 

in 1961 for flood control, water supply, and recreation. Foss 

Reservoir provides water for Bessie, Clinton, New Cordell, 

and Hobart, Okla. Nearly 98 percent of the total groundwater 

use from the Washita River alluvial aquifer during 1967 to 

2015 was for irrigation; other uses of groundwater in the study 

area include public supply, mining, and agriculture.

A hydrogeologic framework was developed for the 

Washita River alluvial aquifer and included the physical 

characteristics of the aquifer, the geologic setting, the hydraulic properties of hydrogeologic units, the potentiometric 

surface (water table), and groundwater-flow directions at a 

scale that captures the regional controls on groundwater flow. 

The Washita River alluvial aquifer consists of alluvium and 

terrace deposits that were transported primarily by water and 

range from clay to gravel in size. The terrace includes windblown deposits of silt size and, in some cases, contains gravel 

laid down at several levels along former courses of presentday rivers.

A conceptual flow model is a simplified description 

of the aquifer system that includes hydrologic boundaries, 

major inflow and outflow sources of the groundwater-flow 

system, and a conceptual water budget with the estimated 

mean flows between those hydrologic boundaries. During the 

study period 1980–2015, mean annual groundwater withdrawals, predominantly used for agricultural irrigation, totaled 

5,502 acre-ft/yr, or 14 percent of aquifer outflows. When 

applied across the 132-square-mile aquifer area used for 

modeling purposes (84,366 acres), mean annual recharge of 

3.15 inches per year corresponds to a mean annual recharge 

volume of 22,169 acre-ft/yr, or 56 percent of aquifer inflows. 

The annual saturated-zone evapotranspiration outflow was 

11,828 acre-ft/yr for the Washita River alluvial aquifer, or 

about 30 percent of aquifer outflows. For the Washita River 

alluvial aquifer, lateral flow was 17,157 acre-ft/yr, or 44 percent of the aquifer inflows. The conceptual flow model and 

hydrogeologic framework were used to conceptualize, design, 

and build the numerical groundwater-flow model.

A numerical groundwater-flow model of the 

Washita River alluvial aquifer was constructed by using 

MODFLOW-2005. The Washita River alluvial aquifer 

groundwater-model grid was spatially discretized into 

350-foot (ft) cells and two layers. Layer 1 represented the 

undifferentiated alluvium and terrace deposits of Quaternary 
2 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

age, and layer 2 represented the bedrock of Permian age, 

which was given a uniform nominal thickness of 100 ft. The 

groundwater-simulation period was temporally discretized 

into 433 monthly transient stress periods, representing 

January 1980 to December 2015. An initial 365-day steadystate stress period was configured to represent mean annual 

inflows and outflows from the Washita River alluvial aquifer 

for the study period. The groundwater-flow model was calibrated manually and by automated adjustment of model inputs 

by using PEST++. Calibration targets for the Washita River 

alluvial aquifer model included groundwater-level observations and reservoir-stage observations, as well as base-flow 

and stream-seepage estimates.

Three groundwater-availability scenarios were used in 

the calibrated groundwater model to (1) estimate the EPS 

pumping rate that retains the saturated thickness that meets the 

minimum 20-year life of the aquifer, (2) quantify the effects 

of projected pumping rates on groundwater storage over a 

50-year period, and (3) evaluate how projected pumping rates

extended 50 years into the future and sustained hypothetical drought conditions over a 10-year period affect base flow

and groundwater in storage. The results of the groundwateravailability scenarios could be used by the OWRB to reevaluate the established MAY of groundwater from the Washita

River alluvial aquifer.

EPS scenarios for the Washita River alluvial aquifer 

were run for periods of 20, 40, and 50 years. The 20-, 40-, 

and 50-year EPS pumping rates under normal recharge 

conditions were 1.7, 1.6, and 1.6 (acre-ft/acre)/yr, respectively. Given the aquifer area used for modeling purposes 

(84,366 acres), these rates correspond to annual yields of 

142,579, 134,986, and 134,986 acre-ft/yr, respectively. 

Groundwater storage at the end of the 20-year EPS scenario 

was about 281,000 acre-feet (acre-ft), or about 306,000 acre-ft 

(52 percent) less than the starting storage. Considering the 

land-surface area of the Washita River alluvial aquifer and 

using a specific yield of 0.12, this decrease in storage was 

equivalent to a mean groundwater-level decline of about 30 ft. 

The Washita River downstream from Foss Reservoir and most 

of the streams in the study area were dry at the end of the 

20-year EPS scenario. Foss Reservoir stage was below the

dead-pool stage of 1,597 ft after about 7 years of pumping in

the 20-year EPS scenario.

Four projected 50-year groundwater-use scenarios were 

used to simulate the effects of selected well withdrawal rates 

on groundwater storage in the Washita River alluvial aquifer. 

These four scenarios used (1) no groundwater use, (2) groundwater use at the 2015 pumping rate, (3) mean groundwater 

use for the simulation period, and (4) increasing groundwater 

use. Groundwater storage after 50 years with no groundwater 

use was 545,249 acre-ft, or 693 acre-ft (0.1 percent) greater 

than the initial groundwater storage; this groundwater storage 

increase is equivalent to a mean groundwater-level increase 

of 0.1 ft. Groundwater storage at the end of the 50-year period 

with 2015 pumping rates was 543,831 acre-ft, or 723 acre-ft 

(0.1 percent) less than the initial storage; this groundwater 

storage decrease is equivalent to a mean groundwater-level 

decrease of 0.1 ft. Groundwater storage after 50 years with the 

mean pumping rate for the study period was 543,202 acre-ft, 

or 1,349 acre-ft (0.2 percent) less than the initial groundwater 

storage; this groundwater storage decrease is equivalent to a 

mean groundwater-level decrease of 0.1 ft. Groundwater storage at the end of the 50-year period with an increasing demand 

groundwater-pumping rate, which was 38 percent greater than 

the 2015 groundwater-pumping rate, was 542,584 acre-ft, 

or 1,967 acre-ft (0.4 percent) less than the initial storage; 

this groundwater storage decrease is equivalent to a mean 

groundwater-level decrease of 0.2 ft.

A hypothetical 10-year-drought scenario was used to simulate the effects of a prolonged period of reduced recharge on 

groundwater storage in the Washita River alluvial aquifer and 

Foss Reservoir stage and storage. To simulate the hypothetical drought, recharge in the calibrated model was reduced by 

50 percent during the simulated drought period (1983–1992). 

Groundwater storage at the end of the drought period in 

December 1992 was 562,000 acre-ft, or 36,000 acre-ft 

(6 percent) less than the groundwater storage of the calibrated groundwater model (598,000 acre-ft). At the end of the 

hypothetical drought, the largest changes in saturated thickness (as great as 43.5 ft) were in the area upgradient from Foss 

Reservoir, particularly in the terrace at the model boundary. 

Substantial decreases in the Foss Reservoir stage began during the fall of 1985 in conjunction with base-flow decreases 

of up to 100 percent at U.S. Geological Survey streamgage 

07324200 Washita River near Hammon, Okla. These lakestage declines outpaced groundwater-level declines in the 

surrounding aquifer. The minimum Foss Reservoir storage 

simulated during the drought period was 77,954 acre-ft, 

which was a decrease of 46 percent from the nondrought storage.

Introduction

Total water demand in west-central Oklahoma is projected to increase by approximately 38 percent from 2010 

to 2060 because of increasing irrigation demand and oil and 

gas operations, during which surface-water and groundwater 

shortfalls are predicted (Oklahoma Water Resources Board 

[OWRB], 2012b). Because of increasing water demands, 

depletion of water in the High Plains aquifer to the west, 

and recurring droughts, effective water-resource management of surface-water and groundwater resources is essential 

(Gutentag and others, 1984). A priority recommendation of 

the Oklahoma Comprehensive Water Plan (OWRB, 2012a) 

was to complete updates of hydrologic investigations and to 

analyze groundwater and surface-water interactions in selected 

aquifers in Oklahoma. The Washita River alluvial aquifer is 

a valley-fill and terrace alluvial aquifer along the Washita 
Introduction 3

River and its tributaries in west-central Oklahoma (fig. 1). 

The Washita River alluvial aquifer provides water primarily 

for irrigation purposes; other uses of groundwater in the study 

area include public supply, mining, and agriculture. This report 

provides results from an updated hydrogeologic investigation 

for reach 1 of the Washita River alluvial aquifer (fig. 1).

The 1973 Oklahoma Water Law (82 OK Stat § 

82-1020.5) requires the OWRB to conduct hydrologic investigations of the State’s aquifers (called groundwater basins 

in the statutes) to support a determination of the maximum 

annual yield (MAY) for each groundwater basin (Oklahoma 

Senate, 2019). The MAY is defined as the amount of fresh 

groundwater that can be withdrawn annually while ensuring a minimum 20-year life of the aquifer (OWRB, 2017b). 

For alluvium and terrace aquifers such as the Washita River 

alluvial aquifer, the groundwater basin-life requirement is 

satisfied if, after 20 years of MAY withdrawals, 50 percent of 

the groundwater basin retains a saturated thickness of at least 

5 feet (ft). When a MAY has been established, the amount of 

land owned or leased by a well permit applicant determines 

the annual volume of water allocated to that well permit. The 

annual volume of water allocated per acre of land is known as 

the equal-proportionate-share (EPS) pumping rate.

For reach 1 of the Washita River alluvial aquifer, the 

OWRB issued a final order on November 13, 1990, that 

established the MAY (120,320 acre-feet per year [acre-ft/

yr]) and the EPS pumping rate (2.0 acre-feet per acre per 

year [(acre-ft/acre)/yr]) (OWRB, 2012b). The MAY and EPS 

were based on hydrologic investigations by Kent and others 

(1984) that used a numerical groundwater-flow model (hereinafter, “Trescott groundwater model”) from Trescott and 

others (1976) to evaluate the effects of potential groundwater 

withdrawals on groundwater availability in the Washita River 

alluvial aquifer. Every 20 years, the OWRB is statutorily 

required to update the hydrologic investigation on which the 

MAY and EPS were based. Because 20 years have elapsed 

since the 1990 final order was issued, the U.S. Geological 

Survey (USGS), in cooperation with the OWRB, conducted an 

updated hydrologic investigation and evaluated the potential 

effects of groundwater availability by using a new numerical groundwater-flow model. Results of the groundwateravailability model scenarios support efforts by the OWRB to 

reevaluate the MAY of groundwater from the Washita River 

alluvial aquifer.

Purpose and Scope

The purpose of this report is to describe a hydrologic 

investigation of the Washita River alluvial aquifer that 

includes an updated summary of the aquifer hydrogeology 

and results of the simulation of water availability obtained by 

using a numerical groundwater-flow model. A hydrogeologic 

framework of the aquifer was developed from available wateruse data, recharge and evapotranspiration estimates, streamflow data, lateral groundwater flow estimates, and reservoir 

storage and levels for the study area. The groundwater 

transient model was calibrated to observed water-level data, 

reservoir stage, and stream base-flow and seepage data and 

was used to compute a mean annual water budget for the study 

period 1980–2015. This report documents the construction 

and calibration of this groundwater-flow model. Groundwateravailability scenarios were performed by using the calibrated 

groundwater model to (1) estimate the EPS pumping rate 

that could retain a minimum 20-, 40-, and 50-year life of the 

aquifer, (2) quantify the potential effects of projected well 

withdrawals on groundwater storage over a 50-year period, 

and (3) simulate the potential effects of a hypothetical 10-year 

drought on groundwater storage and lake storage.

Description of Study Area

The Washita River alluvial aquifer is one of several 

alluvial aquifers along rivers that cross western Oklahoma, 

including the Canadian River to the north and North Fork 

Red River to the south (fig. 2), and is a source of water for 

various uses. The study area begins at the upstream extent of 

the Washita River where the river and its associated alluvial 

aquifer cross the Texas–Oklahoma border. The study area 

extends across west-central Oklahoma from the Texas border 

for about 65 miles to the southeast part of Custer County, 

Okla., and includes 131 river miles of the Washita River and 

about 10 miles of Foss Reservoir. The altitude of the Washita 

River at the western, upstream end is approximately 2,232 ft 

above NAVD 88, and where the river leaves the study area 

downstream from Clinton, Okla., the altitude of the river is 

1,437 ft. The mean stream gradient for this 141-mile reach of 

the Washita River is approximately 5.6 feet per mile.

The Washita River alluvial aquifer is a long, narrow 

surficial aquifer that underlies the Washita River valley in 

Oklahoma from the western border with Texas southeast to 

near Lake Texoma (fig. 1), covering approximately 110 square 

miles (mi2) (71,000 acres). The aquifer is made up of alluvium and terrace deposits of the Washita River and several 

tributaries, and the extent of the hydrologic investigation area 

includes underlying and adjacent bedrock units of Tertiary and 

Permian ages. The OWRB has designated the westernmost 

section of the aquifer in Roger Mills and Custer Counties, 

Okla. (fig. 1) (reach 1) of the Washita River alluvial and terrace aquifer (OWRB, 2012b) for the MAY and EPS determination. The study area, referred to throughout this report as the 

Washita River alluvial aquifer, has the same extent as reach 1 

of the Washita River alluvial aquifer.

The Washita River is the primary source of inflow to 

Foss Reservoir, a Bureau of Reclamation reservoir constructed 

in 1961 for flood control, water supply, and recreation. Foss 

Reservoir provides 18,000 acre-ft/yr for Clinton, Bessie, New 

Cordell (fig. 2), and Hobart (south of study area, not shown 

on fig. 2) in Oklahoma (OWRB, 2012b). For the study period 

1980–2015, about half of the annual surface-water inflow 

to Foss Reservoir was supplied by base flow. Base flow was 
R

R

R

R

R

R

Leedey

Ara

Clin

Foss

Hammon

Cheyenne

Strong

City

FOSS DAM

Foss

Reservoir

WSH04

WSH03

WSH02

WSH01

WSH05

WSH06

07316500

07324200

07324400

073

2700

2687

9328

Bessie

Cheyenne 6 SW

Leedey, OK US

Hammon

2 SSW Butler Mesonet

Creek

Dead

Warrior

Creek

Washita

River

Croton

Creek

Plum

Creek

East Croton

Creek

Sergeant

Major Creek

Brokenleg

Creek Dry

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

River

Washita

Rush

Creek

Turkey 

Creek Spring Creek

River

Creek

B

C

East

Barnitz

Creek

West

Barnitz

Creek

Comet

Creek

Wild

Horse

Creek

Hay

Creek

Dry Branch

North Branch

Quartermaster

Creek

Quartermaster

Creek

Hines

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

Creek WhiteShield

Turkey

Oak

Little

Kiowa

Creek

Washita

Barnitz Cree k

EXPLANATION

Numerical groundwater-flow  model extent

Washita River alluvial aquifer

Recharge zone for base flow

Contributes to reach upstream  from CheyenneContributes to reach Cheyenne  to Hammon

Streamgage and U.S. Geological Survey (USGS) station  USGS, 2018b)Observation well and nameObservation well with continuous water-level measurClimate station and name (table 3)

Cooperative Observer Station (Oklahoma ClimatologiOklahoma Mesonet Station (Oklahoma Mesonet, 2018Cooperative Observer Station and Oklahoma Mesone Climatological Survey, 2017a; Oklahoma Mesonet, 2

07324400

WSH02WSH05 R

Base from U.S. Geological Survey digital data 1:443,191-scale digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Aquifer boundary modified from Johnson an

Oklahoma Water Reso

100° 99°45' 99°30' 99°15' 99

35°45'35°30'

0 5 10 MILES0 5 10 KILOMETERS

OKLAHOMA

TEXAS

Lake

Texoma

Enlarged

area

TEXAS

OKLAHOMA

ROGER MILLS COUNTY

CUSTER

COUNTY

BECKHAM COUNTY WASHITA COUNTY

DEWEY

COUNTY

ELLIS COUNTY

9328

2687

2700

WSH06

WSH02

Cheyenne

Cheyenne

07316500

R

R

Figure 1. Locations of hydrological features, observation wells, streamgages, climate stations, and cities associated with the study of reWashita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma.
FOSS DA

Foss

Reservoir

Washita River

Canadian River

North Fork Red River

07324200

07324400

07316500

07316500

Foss

Hammon

Leedey

Cheyenne

Strong

City

New 

Cordell

"

ELLIS

COUNTY

OCHILTREE

COUNTY

LIPSCOMB

COUNTY

DEWEY

COUNTY ROBERTS COUNTY HEMPHILL

COUNTY

ROGER MILLS

COUNTY

CUSTER

COUNT

GRAY

COUNTY

WHEELER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

TEXAS

OKLAHOMA

Enlarged

area

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

EXPLANATION

Permitted diversion (Oklahoma Water ResFloodwater-retarding structure (Smith anU.S. Geological Survey streamgage and s number (table 1; U.S. Geological SurveySubwatershed boundary (Smith and EsralStreams (U.S. Geological Survey, 2013)

Washita River alluvial aquifer

l?

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

100°45' 100°30' 100°15' 100° 99°45' 99°30' 99°15' 

36°

35°45'35°30'

0 50 5

10 MILES

10 KILOMETERS

Figure 2. Major geographic and surface-water features, floodwater-retarding structures, and surface-water diversions in and near the subwatershed, western Oklahoma.
6 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

computed at the USGS streamgage 07324200 Washita River 

near Hammon, Okla. [hereinafter referred to as the Hammon 

streamgage] (table 1). Base flow, which is the component 

of streamflow supplied by the discharge of groundwater to 

streams (Barlow and Leake, 2012) was computed by using 

the USGS Groundwater Toolbox (Barlow and others, 2015) 

(table 2); refer to the “Base Flow” section of this report for 

additional details. The total annual base flow and the baseflow index (the ratio of total annual base flow to the total 

annual streamflow) at the Hammon streamgage, upstream 

from Foss Reservoir, generally increased during the study 

period 1980–2015, but a decrease in base flow occurred during 

2012–14 (table 2). The observed increases in base flow are 

likely attributable to increased precipitation (and recharge), 

the several hundred impoundments or floodwater-retarding 

structures that regulate the runoff recession of single storm 

events (Smith and Esralew, 2010; fig. 2) in the Washita River 

subwatershed, or changes in agricultural practices that reduced 

runoff and promoted artificial recharge to the aquifer.

Previous Investigations

A description of the groundwater resources along the 

Washita River in the study area in Leonard and others (1958)

includes descriptions of the alluvial sedimentology, depositional history, and the general characteristics of the groundwater system. The groundwater resources and groundwater 

use in Custer County (fig. 1) are described in Hart (1978). 

The bedrock lithology and stratigraphy for Custer County are 

described in Fay (1978).

Schipper (1983) describes the Washita River alluvial 

aquifer and includes a groundwater management model for 

Roger Mills and Custer Counties. Schipper (1983) provides 

a compilation of hydrologic data for the 1970s and a detailed 

description of the aquifer hydrogeologic framework. Kent and 

others (1984) used information provided by Schipper (1983) to 

estimate the EPS pumping rate for the Washita River alluvial 

aquifer and built a finite-difference groundwater model following the method of Trescott and others (1976).

The groundwater model in Kent and others (1984) has a 

uniform grid with 1,320-ft cells and values estimated for depth 

to water, saturated thickness, transmissivity, and recharge. In 

many places along the narrow aquifer, only three model cells 

cover the width of the aquifer. The numerical model was run 

as a steady-state simulation and was calibrated by using mass 

balance of inflow and outflow; no hydraulic head or flow 

targets were used during calibration. Hydraulic and recharge 

parameters were adjusted to maintain the starting hydraulic 

head field under steady-state flow conditions. The Washita 

River was assumed to be gaining streamflow from groundwater throughout Washita River alluvial aquifer, and this 

gain was assumed to be equal to aquifer recharge. The model 

was then run as a transient simulation for 20 years, and the 

pumping at all cells was varied until the number of cells with 

less than 5 ft of saturated thickness was equal to half of the 

aquifer area.

Kent and others (1984) divided the Washita River alluvial aquifer into three subareas. The first subarea included 

the Washita River alluvial aquifer from the Texas-Oklahoma 

border to about 6 miles (mi) downgradient from Cheyenne 

(fig. 1). The second subarea included the Washita River 

alluvial aquifer from 6 mi downgradient from Cheyenne 

to Foss Reservoir. The third subarea included the Washita 

River alluvial aquifer downgradient from Foss Dam. Separate 

EPS pumping rates were determined for each subarea: 

2.70 (acre-ft/acre)/yr for the area upgradient from Cheyenne 

and 1.75 (acre-ft/acre)/yr for the other two subareas. The 

weighted EPS for the three subareas of the Washita River alluvial aquifer was estimated to be 2.18 (acre-ft/acre)/yr.

Table 1. Information for selected continuous-record streamgages (USGS, 2018b) in the Washita River alluvial aquifer study area, 

western Oklahoma.

[USGS, U.S. Geological Survey; Dates are in month/year format]

USGS station 

number 

(fig. 1)

Station name Short name

Latitude, 

in decimal 

degrees

Longitude, 

in decimal 

degrees

Period of record 

used in this analysis 

(may contain gaps)

Begin End

07316500 Washita River near Cheyenne, Okla. Cheyenne streamgage 35.62644 −99.66840 10/1937 12/2015

07324200 Washita River near Hammon, Okla. Hammon streamgage 35.47310 −100.12095 10/1969 12/2015

07324400 Washita River near Foss, Okla. Foss streamgage 35.65644 −99.30621 3/1956 12/2015

07325000 Washita River near Clinton, Okla. Clinton streamgage 35.42227 −99.96928 10/1935 12/2015
Introduction 7

Table 2. Annual-mean streamflow and annual-mean base flow for selected USGS streamgages in the Washita River alluvial aquifer 

study area, 1980–2015.

[USGS, U.S. Geological Survey; ft3/s, cubic foot per second; acre-ft/yr, acre-foot per year; %, percent; BFI, base-flow index; --, data not available or not applicable; Base-flow values computed by using USGS Groundwater Toolbox (Barlow and others, 2015)]

Year

07316500 Washita River 

near Cheyenne, Okla. 

(Cheyenne streamgage)

07324200 Washita River 

near Hammon, Okla. 

(Hammon streamgage)

07324400 Washita River 

near Foss, Okla. 

(Foss streamgage)

07325000 Washita River 

near Clinton, Okla. 

(Clinton streamgage)

Mean 

streamflow, in 

ft3/s

Mean base flow Mean 

streamflow, in 

ft3/s

Mean base flow Mean 

streamflow, in 

ft3/s

Mean base flow Mean 

streamflow, in 

ft3/s

Mean base flow

ft3/s % (BFI) ft3/s % 

(BFI) ft3/s % (BFI) ft3/s % (BFI)

1980 18.7 11.7 62.7 37.3 14.1 37.7 46.2 9.9 21.3 71.4 31.5 44.1

1981 3.9 2.7 70.3 4.5 1.6 35.3 9.9 7.1 71.6 26.3 14.3 54.5

1982 58.8 13.0 22.0 106.9 19.4 18.2 116.2 49.4 42.5 199.9 103.7 51.9

1983 20.5 13.7 66.9 47.7 29.4 61.6 101.0 57.8 57.3 157.4 89.8 57.1

1984 9.2 7.0 76.2 21.0 13.2 62.9 7.4 6.6 89.1 30.3 24.6 81.1

1985 13.2 7.1 53.6 14.8 8.9 60.1 10.5 9.3 88.8 22.1 16.4 74.2

1986 23.8 11.6 48.8 77.6 32.2 41.4 56.5 12.5 22.0 217.4 60.8 28.0

1987 36.3 23.6 65.1 -- -- -- 246.3 121.4 49.3 336.3 181.6 54.0

1988 23.4 16.9 72.3 -- -- -- -- -- -- 174.7 127.6 73.1

1989 21.1 11.7 55.4 -- -- -- 9.1 8.8 96.7 279.2 177.1 63.4

1990 26.2 11.3 43.2 96.7 44.9 46.5 73.5 32.9 44.7 145.3 100.2 68.9

1991 9.0 5.3 58.6 32.1 20.6 64.0 36.7 11.5 31.3 82.3 44.1 53.6

1992 11.6 8.4 72.2 35.7 26.2 73.3 40.3 12.7 31.5 90.8 53.8 59.2

1993 21.9 15.5 70.9 65.6 46.3 70.6 104.6 53.4 51.0 183.8 123.5 67.2

1994 8.0 4.3 54.0 20.3 13.4 65.8 5.6 4.4 78.8 36.8 20.7 56.3

1995 21.9 8.8 40.4 80.2 31.3 39.0 95.4 40.7 42.6 270.8 119.0 43.9

1996 23.0 12.1 52.5 86.7 49.3 56.9 143.4 60.1 41.9 341.5 173.7 50.9

1997 72.0 42.9 59.6 294.4 184.9 62.8 390.5 188.1 48.2 692.3 471.1 68.0

1998 46.7 32.7 70.0 209.3 153.8 73.5 221.4 106.0 47.9 345.1 222.9 64.6

1999 30.5 19.8 65.0 119.1 88.3 74.1 120.0 53.7 44.7 190.2 114.6 60.3

2000 28.9 17.1 59.1 77.2 51.7 66.9 69.3 24.7 35.6 127.4 71.3 56.0

2001 35.4 26.9 75.9 112.1 68.9 61.5 150.0 73.8 49.2 211.3 150.8 71.4

2002 25.6 15.2 59.5 47.9 28.8 60.1 6.3 5.2 82.4 32.4 21.4 66.0

2003 31.3 19.3 61.7 54.7 32.6 59.6 47.4 14.1 29.7 65.0 35.8 55.0

2004 24.1 15.6 64.7 43.2 26.5 61.3 25.8 11.8 45.7 59.7 29.9 50.1

2005 25.2 17.3 68.5 55.4 37.2 67.2 79.1 29.8 37.6 116.3 70.8 60.8

2006 8.1 4.6 57.0 14.6 9.0 61.6 11.1 10.1 90.7 24.2 19.5 80.4

2007 45.1 24.2 53.6 128.5 57.8 44.9 142.3 52.7 37.1 234.1 101.4 43.3

2008 60.6 30.8 50.8 103.7 55.1 53.1 84.6 18.4 21.7 167.5 80.4 48.0

2009 30.6 24.7 80.8 51.4 38.3 74.5 52.7 13.9 26.4 97.4 46.1 47.4

2010 34.9 22.9 65.6 62.0 35.0 56.4 40.9 18.4 45.0 77.0 46.8 60.8

2011 7.9 6.0 75.9 12.5 10.6 84.6 13.0 12.5 96.0 22.0 19.4 88.0

2012 3.2 1.9 59.1 3.0 0.6 20.0 5.8 5.0 86.2 12.6 8.1 64.0

2013 1.1 0.2 20.0 0.9 0.0 1.1 4.5 3.4 75.8 7.4 4.3 57.8

2014 0.9 0.1 12.2 0.4 0.0 0.0 3.5 2.8 80.0 7.4 3.5 47.7

2015 53.4 23.5 44.0 95.9 34.3 35.7 31.6 4.5 14.2 117.6 28.9 24.6

Mean 25.4 14.7 58.0 67.1 38.3 53.1 74.4 32.8 53.0 146.5 83.6 58.2

Mean, in 

acre-ft/yr

18,421 10,669 48,556 27,725 53,830 23,727 106,045 60,519
8 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Land Cover and Population

Land-use surveys documented in the CropScape database 

indicate that the land cover for the Washita River alluvial aquifer during 2008–18 was mostly rural, undeveloped land and 

that most of the land was used for growing crops (National 

Agricultural Statistics Service, 2019). The CropScape database includes information about land-cover characteristics at 

a 30-meter (98-foot) resolution for land overlying the Washita 

River alluvial aquifer from 2008 to 2018. Developed land 

covered 3 percent of the area, forest covered 2 percent of 

the area, and water, wetland, or barren land covered 9 percent of the area. The majority of the Washita River alluvial 

aquifer area was covered by cropland (56 percent), grass/

pasture (18 percent), and shrubland (12 percent). Winter wheat 

(70 percent) and alfalfa (19 percent) accounted for 89 percent of the crop types over the Washita River alluvial aquifer 

area (fig. 3). Although crop types may change on the basis of 

economic conditions and hydrologic factors such as flooding 

or drought conditions, the percentages of total crop land cover 

and individual crop types only changed by 1–2 percent during 

2008–18 (National Agricultural Statistics Service, 2019).

U.S. Census Bureau information was used to determine 

changes in population in the study area from 2000 to 2015. 

Oklahoma cities and towns closest to the Washita River alluvial aquifer with more than 500 residents include Hammon, 

Arapaho, Cheyenne, and Clinton (fig. 1) (U.S. Census Bureau, 

2017). During 2000–15, the U.S. Census Bureau (2017) noted 

that populations of these four cities and towns increased as 

follows: the population of Hammon increased 19.4 percent 

from 493 to 589; the population of Arapaho increased 9.6 percent from 751 to 823; the population of Cheyenne increased 

9.5 percent from 749 to 820; and the population of Clinton, 

the most populous city near the Washita River alluvial aquifer, 

increased 5.9 percent, from 8,886 to 9,410. The combined 

population of all four cities and towns increased by about 

7 percent from 2000 to 2015.

Climate

The Washita River alluvial aquifer straddles the boundary between the humid subtropical climate of the interior 

lowlands to the east, and the cooler, semiarid midlatitude 

steppe climate of the Great Plains of North America to the 

west (Kottek and others, 2006). Long-term precipitation data 

for the region including the study area were obtained for three 

Oklahoma Mesonet stations and three National Oceanographic 

and Atmospheric Administration (NOAA) cooperative 

observer (COOP) stations (table 3) (Oklahoma Mesonet, 

2018; Oklahoma Climatological Survey, 2017a). Years with 

less than 9 months of rainfall data were not included in this 

analysis. The long-term mean annual precipitation at these six 

stations ranged from 23.2 to 27.8 inches (in.) (table 3), which 

does not represent the extent to which mean annual precipitation varies in the study area. Mean annual precipitation is 

approximately 10 in. greater in the eastern part of the study 

area than in the western part of the study area, and precipitation amounts steadily increase from west to east (Oklahoma 

Climatological Survey, 2017a). Annual precipitation is less 

in the western part of the study area in part because this area 

is affected by a regional orographic rain shadow formed by 

the Rocky Mountains (Tortorelli and others, 1991). May and 

June are normally the wettest months of the year, whereas 

January and February are the months with the least amounts of 

precipitation (fig. 4). During May and June, parts of the study 

area can receive as much as 4 in. of precipitation. In January 

and February, precipitation is typically less than 1 in., some of 

which is snow; annual snow totals typically range from 1 to 

10 in. (Oklahoma Climatological Survey, 2017b).
Introduction 9

Mean annual precipitation for the COOP station in 

Leedey, Okla. (hereinafter referred to as the Leedey COOP station) during 1941–2017 was 24.4 in. (table 3), and total annual 

precipitation at this station varied from as little as 11.8 in. to 

as much as 43.7 in. (Oklahoma Climatological Survey, 2017a). 

Although the Leedey COOP station is about 5 mi north of the 

northern boundary used in the numerical groundwater model 

(fig. 1), it is within the Washita River subwatershed boundary (fig. 2) and was used in this analysis because it provided 

the longest continuous precipitation records among all nearby 

climate stations that included the years 1980–2015.

A long-term mean annual precipitation amount of 24.6 in. 

for 1920 to 2017 was determined from data from the six 

climate stations in or near the study area (fig. 5). A 5-year 

weighted moving mean was used to delineate wet and dry 

periods by combining the available long-term precipitation 

data from the six climate stations. Periods when the 5-year 

moving average was below the long-term mean annual precipitation were classified as dry, and periods above the long-term 

mean annual precipitation were classified as wet (fig. 5).

Between 1920 and 2017, a pattern of consecutive wet 

years followed by consecutive dry years is evident. Some of 

the more noteworthy features in the long-term record include 

the extended dry periods during 1930–40, 1943–56, 1961–72, 

and 2009–14. Wet periods lasting 2–6 years preceded and followed each of these dry periods. From 1969 to 1994 the 5-year 

moving average was relatively stable, during which time 

there were 9 years when the annual precipitation was above 

the long-term mean annual precipitation amount and 17 years 

when it was below that amount (fig. 5). From 1995 to 2004, 

annual precipitation mostly remained above the long-term 

mean, and the greatest annual precipitation total on record 

occurred in 1997, with 43.7 in. recorded at the Leedey COOP 

station (Oklahoma Climatological Survey, 2017a) and 50.5 in. 

at the Butler Mesonet station (Oklahoma Climatological 

Survey, 2017a). After a few years of near-average precipitation from 2005 to 2008, drought conditions returned during 

2009–14, before being alleviated by above-average precipitation during 2015–17 (refer to the “Recharge” section of this 

report for addition details).

Groundwater Use

Groundwater-use data for Oklahoma are self-reported 

annually to the OWRB by permitted users. The OWRB staff 

reviewed groundwater-use data from 1967 to 2015 overlying the Washita River alluvial aquifer for inconsistencies to 

ensure errors in reported data were corrected (Ellis and others, 

2020). Annual groundwater-use categories analyzed for this 

report include agriculture, irrigation, public supply, mining, 

and other. Uses that are also required to be reported to the 

OWRB include thermoelectric power, industrial, commercial, and recreation, fish, and wildlife, but these categories 

accounted for little to none of the groundwater use in the 

Washita River alluvial aquifer study area (table 4). Irrigators 

using more than 5 (acre-ft/acre)/yr must report use parameters 

to the OWRB so that the volume of groundwater used can be 

calculated (OWRB, 2017b). The most complete records for 

this reporting began in 1967; therefore, water-use data in this 

report start in 1967. Reporting requirements have changed at 

various times since permitting began. Prior to 1980, irrigators 

were only required to record crop type, frequency of irrigation, and number of acres irrigated. Since 1980, irrigators have 

been required to include the number of applications and the 

inches of water per application (OWRB 2017b), which allows 

a more precise estimation of the volume of irrigation water 

used. Since annual groundwater-use reporting began in 1967, 

reporting has not been required for domestic water wells, agricultural use less than 5 (acre-ft/acre)/yr, or irrigation applied to 

fewer than 3 acres (OWRB, 2017b).

Shrubland

12 percent

Cropland

56 percent

Grass/Pasture

18 percent

Forest

2 percent

Developed

3 percent

Water/wetland/

barren

9 percent

Land-cover type, 2008–18

Winter wheat

70 percent

Alfalfa

19 percent

Cotton

4 percent

Fallow/idle

1 percent Other

6 percent

Crop cover, 2008–18

(National Agricultural Statistics Service, 2019)

Figure 3. Land cover and crop cover over 

the Washita River alluvial aquifer, western 

Oklahoma, 2008–18.
10 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Temporary permits are issued by the OWRB for a 

groundwater user to extract a set volume of groundwater over 

a 90-day period. Temporary permits started being documented 

in the OWRB database in 1992. From 1992 to 2017, 145 temporary permits were issued in the study area, with water used 

predominantly for oil, gas, and mining, with a combined total 

reported use of 1,427.6 acre-ft/yr (OWRB, 2017b). During 

1992–2017, the year with the largest temporarily permitted 

groundwater use was 2012, with 454.6 acre-ft, all of which 

was used for oil, gas, and mining.

Data from 245 groundwater-use 

permits were categorized by type per year 

from 1967 through 2015 for the Washita 

River alluvial aquifer study area (Ellis 

and others, 2020). The mean annual total 

groundwater use for the period of record, 

1967–2015, was 6,079 acre-ft (fig. 6). 

Nearly 98 percent of the total groundwater 

use reported was for irrigation. Periods 

with below-average precipitation (fig. 5) 

typically correspond to greater reported 

groundwater use. From 1967 to 1980, the 

mean annual use of 7,189.5 acre-ft/yr 

was greater than the mean annual use 

for the period of record, and precipitation totals for 8 of those 14 years were 

below the 76-year mean (fig. 5 and fig. 6

and table 4). Annual groundwater use 

increased from 6,748 acre-ft in 1967 to 

9,599 acre-ft in 1972 before declining during the early 1990s to about 2,000 acre-ft, 

with the exception of 1976 and 1980 when 

reported groundwater use was greater 

than 8,000 acre-ft. Some of these variations in water use could be attributed to 

the differences in reporting requirements for irrigation use. 

After declining to about 2,000 acre-ft/yr in the early 1990s, 

groundwater use increased during 1994–1996, with annual use 

ranging from about 4,000 to 8,000 acre-ft/yr. In 1997 precipitation was well above average, and reported groundwater use 

declined to 2,030 acre-ft/yr (fig. 6). Subsequently, groundwater use increased over the next 2 years before steadily 

declining from 1999 to 2003 (fig. 6). Reported groundwater 

Table 3. Mean annual precipitation at selected Mesonet and National Oceanographic and Atmospheric Administration (NOAA) 

cooperative observer (COOP) climate stations used in the analysis of the Washita River alluvial aquifer study area.

[All precipitation values are in inches per year. --, no data available]

Station name

(fig. 1) Period of record Number of years Mean annual precipitation

Period of record 1930–1988 1989–2008 2009–2014

Bessie (Mesonet)1 1994–2017 23 27.8 -- 29.8 21.0

Butler (Mesonet)1 1994–2017 23 27.3 -- 28.7 20.3

Cheyenne (Mesonet)1 1994–2017 23 27.0 -- 28.8 20.5

LEEDEY (COOP)2 1941–2017 76 24.4 23.1 26.9 20.6

HAMMON 2 SSW 

(COOP)2

1920–2004 84 25.7 24.3 29.2 --

CHEYENNE 6 SW 

(COOP)2

1923–1993 70 23.2 22.9 21.7 --

1Oklahoma Mesonet, 2018.

2Oklahoma Climatological Survey, 2017a.

0

1

2

3

4

5

Jan. Feb. Mar. Apr. May June

Month

July Aug. Sept. Oct. Nov. Dec.

Precipitation, in inches

1941–2017 mean

EXPLANATION

1941–57 mean

1995–2009 mean

Figure 4. Mean monthly precipitation at the Leedey, Oklahoma, climate station for 

the period 1941–2017 (Oklahoma Climatological Survey, 2017b), and mean monthly 

precipitation for the dry period 1941–1957 and the wet period 1995–2009.
Introduction 11

use steadily increased from 4,716 acre-ft in 2008 to more than 

10,000 acre-ft in 2013 and 2014. This pattern of increasing 

groundwater usage (fig. 6) is likely a result of several consecutive years of drought conditions (fig. 5). In 2015, the study 

area received more than 40 in. of precipitation, and reported 

groundwater use decreased more than 5,000 acre-ft from the 

previous year.

Streamflow Characteristics

In addition to data from the Hammon streamgage, daily 

streamflow measurements were available for the period 

1980–2015 for three more USGS streamgages (fig. 1 and 

table 2) near the towns of Cheyenne, Foss, and Clinton, Okla. 

These stations are USGS streamgage 07316500 Washita River 

near Cheyenne, Okla. (hereinafter referred to as the Cheyenne 

0

5

10

15

20

25

30

35

40

45

50

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

0

1

2

3

Precipitation, in inches

Years

2020

Number 

of stations

55

EXPLANATION

Above historical mean (5-year moving mean 1920–2017)

Total annual precipitation

1920–2017 mean annual precipitation (24.6 inches)

Below historical mean (5-year moving mean 1920–2017)

Number of climate stations where precipitation was 

 measured (Locations on fig. 1)

Figure 5. Wet and dry periods defined as departure of the 5-year weighted moving average from the mean annual precipitation, 

1920–2017, and the number of climate stations with observations.

Table 4. Mean annual reported groundwater use in the Washita River alluvial aquifer study area, 1967–2015.

[%, percent]

Period

Mean annual reported groundwater use by use type, in acre-feet per year and percentage of use type for period

Agriculture Irrigation Public 

supply Industrial Thermoelectricpower Mining Commercial

Recreation, 

fish, and 

wildlife

Other Total

1967–1980 0 7,183 6.0 0 0 0.1 0 0 0 7,189.5

0.0% 99.9% 0.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

1981–1993 0.2 3,980 37 0 0 1.0 0 0 0.1 4,018.4

0.0% 99.0% 0.9% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

1994–2003 2.1 4,472 196 0 0 4.3 0 0 126 4,800.0

0.0% 93.2% 4.1% 0.0% 0.0% 0.1% 0.0% 0.0% 2.6%

2004–2015 2.7 7,322 54 0 0 23 0 0 94 7,496.0

0.0% 97.7% 0.7% 0.0% 0.0% 0.3% 0.0% 0.0% 1.3%

1967–2015 1.1 5,814 65 0 0 6.8 0 0 49 5,935.6

0.0% 98.0% 1.1% 0.0% 0.0% 0.1% 0.0% 0.0% 0.8%
12 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

streamgage), USGS streamgage 07324400 Washita River near 

Foss, Okla. (hereinafter referred to as the Foss streamgage), 

and USGS streamgage 07325000 Washita River near Clinton, 

Okla. (hereinafter referred to as the Clinton streamgage) (fig. 1

and table 2) (USGS, 2018b). Mean annual streamflows at the 

Cheyenne and Hammon streamgages were greatest during a 

wet period from 1995 to 2002 (about 72 cubic feet per second 

[ft3/s] and 294 ft3/s, respectively) and were very low (about 0.9 

and 0.4 ft3/s, respectively) during the hydrologic drought from 

2011 to 2014 (table 2) (Shivers and Andrews, 2013).

Streamflow downstream from Foss Dam (fig. 1) was 

controlled by releases from Foss Dam, local precipitation, 

and groundwater base flow. Mean annual streamflow released 

from Foss Dam was approximately 41.1 ft3/s during the study 

period, with greater releases during wet periods and a prolonged period with no releases during dry periods.

Mean annual streamflow (74.4 ft3/s) measured at the Foss 

streamgage includes flow from Oak Creek (fig. 1) and was 

similar to that measured at the Hammon streamgage (67.1 ft3/s) 

(table 2). Streamflow measured at the Clinton streamgage 

includes the inflows from Turkey Creek and more substantial 

inflows from Barnitz Creek, neither of which were measured 

during the period of study. Mean annual streamflow measured 

at the Clinton streamgage for the study period was 146.5 ft3/s. 

Washita River streamflow was not measured downstream from 

the Clinton streamgage in the study area.

Geologic Units and Hydrogeology of the 

Study Area

The Washita River alluvial aquifer is composed of 

alluvium and terrace deposits of Quaternary age that unconformably overlie bedrock units of Permian age (fig. 7) (Fay, 

2010). At the western edge of Roger Mills County, the Washita 

River alluvial aquifer is about 0.25 mi wide and increases to an 

average of 1.5 mi wide at the eastern end of the Washita River 

0

5

10

15

20

25

30

35

40

45

50

0

2,000

4,000

6,000

8,000

10,000

12,000

19671968

19691970

1971

1972

197319741975

1976

1977

197819791980

19811982

19831984

19851986

19871988

19891990

19911992

1993

1994199519961997

1998

1999

20002001

200220032004

200520062007

20082009

2010

201120122013

20142015

Precipitation, in inches per year

Groundwater use, in acre-feet

Year

EXPLANATION

Agriculture

Irrigation

Public supply

Mining

Other

Mean annual groundwater use 1967–2015

Groundwater use by category

Annual precipitation measured at the Leedey 

 Cooperative Observer Station (Oklahoma 

 Climatological Survey, 2017a)

Figure 6. Estimated annual groundwater use and annual precipitation from the Leedey climate station during 1967–2015 by category 

for the Washita River alluvial aquifer, western Oklahoma.
Geologic Units and Hydrogeology of the Study Area 13

alluvial aquifer at Clinton, Okla. (Leonard and others, 1958). 

Alluvium underlies the Washita River from the Texas border 

to near Lake Texoma in south-central Oklahoma. Fay (2010)

and Johnson and others (2003) have mapped alluvium adjacent 

to the Ogallala Formation of the High Plains aquifer near the 

Texas border; field observations and aerial orthophotography (Microsoft Corporation, 2017), however, indicate that 

the Ogallala Formation is separated from the Washita River 

alluvial aquifer by outcrops of the Cloud Chief Formation of 

Permian age and a part of the Cloud Chief Formation that is 

covered by a veneer of eroded Ogallala Formation rocks.

The Washita River alluvial aquifer is located on the 

northern flank of the Anadarko Basin, and beds of Permian 

age dip from 10 to 80 feet per mile to the south (Fay, 1978). 

Although there are many faults in the study area (Holland, 

2015), no substantial offsets are indicated on the maps in 

Johnson and others (2003), and these faults likely do not cut 

across the Washita River alluvial aquifer. The Washita River 

alluvial aquifer was initially delineated where the alluvial and 

terrace deposits are indicated on the geologic map by Heran 

and others (2003). In the “Hydrogeologic Framework of the 

Washita River Alluvial Aquifer” section of this report, the 

alluvium and terrace deposits are further delineated for areas 

that do not have enough saturated thickness to be considered 

a water source (western part of the study area). In the easternmost part of the study area, the terrace deposits overlie the 

Rush Springs aquifer and are considered part of the Rush 

Springs aquifer and not the Washita River alluvial aquifer.

Hydrogeologic Units

A hydrogeologic unit is a continuous unit with consistent hydraulic properties that may or may not coincide with 

a single stratigraphic unit and is hydraulically distinct from 

vertically or laterally adjacent hydrogeologic units in the same 

hydrogeologic system (fig. 8). Each hydrogeologic unit may 

include zones or distinct vertical intervals that are unique but 

are discontinuous and not considered to be distinct hydrogeologic units.

Alluvium and Terrace Deposits of Quaternary 

Age

The hydrogeologic units of the Washita River alluvial 

aquifer consist of alluvium and terrace deposits of Quaternary 

age that were transported primarily by water and range from 

clay to gravel in size (Fay, 2010). The terrace includes windblown deposits of silt-sized material (Wentworth, 1922) and, 

in some cases, contains sand and gravel laid down at several 

levels along former courses of present-day rivers. Although 

Miller and Stanley (2004) and Fay (2010) delineate different 

units of Quaternary age in the study area, the Washita River 

alluvial aquifer is defined in this report as one hydrogeologic 

unit because there is no extensive strata or zone that has 

distinct hydraulic properties. The alluvium is coarsest in the 

western part of the study area where it is closer to the Ogallala 

Formation (fig. 7). Eastward, the amount of coarse sediment 

decreases because more eroded silt and clay from the Cloud 

Chief Formation has entered the valley from tributaries. In 

Custer County, the Rush Springs Formation is adjacent to 

the Washita River alluvial aquifer in the northern part of the 

study area. Erosion of the Rush Springs Formation may have 

introduced more sand to the alluvium downgradient from 

Foss Dam.

Three deposits of Quaternary age delineated in Leonard 

and others (1958) compose the Washita River alluvial aquifer; from youngest to oldest, they are alluvium, low terrace 

deposits, and older terrace deposits. The low terrace deposits 

are connected to the alluvium and are typically coarser in 

texture with higher hydraulic conductivity than the alluvium. 

Leonard and others (1958) described the older terrace deposits 

as topographically higher and disconnected from the alluvium 

and low terrace deposits. Conversely, on more recent geological maps (Johnson and others, 2003; Fay, 2010), the alluvium 

is not differentiated from the terrace deposits. The terrace 

deposits on more recent maps are equivalent to the older terrace deposits described in Leonard and others (1958).

Ogallala Formation of Tertiary Age

Underlying the alluvium and terrace deposits in the far 

western part of the study area is the Ogallala Formation of 

Tertiary age (figs. 7 and 8). The Ogallala Formation consists 

of brown to light tan sediments eroded from the ancestral 

Rocky Mountains and deposited by streams, alluvial fans, and 

wind. The Ogallala Formation is considered a major aquifer 

in Oklahoma and is composed of a fine- to medium-grained 

sand with some clay, silt, gravel, volcanic ash, and caliche 

beds, with some beds locally cemented by calcium carbonate 

(Carr and Bergman, 1976). The Ogallala Formation subcrop 

area below the alluvium and terrace is poorly defined because 

the loosely consolidated materials of the Ogallala Formation 

resemble those of the overlying alluvium and terrace deposits. 

The Ogallala Formation thickness towards the westernmost 

extent in the study area is 320 ft and thins eastward to the 

erosional extent (fig. 7). Reworked sediments of the Ogallala 

Formation are the main source for the coarse alluvial sediment 

in the different alluvial units (Leonard and others, 1958).

Bedrock Units of Permian Age

The units of Quaternary and Tertiary ages are underlain 

by consolidated bedrock units of Permian age. These bedrock 

units are reddish-brown and consist of (from youngest to 

oldest) the Elk City Member of the Quartermaster Formation 

(referred to locally as the Elk City Sandstone [Fay and Hart, 

1978]), the Doxey Shale and Cloud Chief Formations of 

the Foss Group (Fay and Hart, 1978), and the Rush Springs 

Formation of the Whitehorse Group (figs. 7 and 8). The 

Doxey Shale was originally classified as a member of the 
" " " " " S D Pcc Pr Qal To Qt Qds Pdy Pec To Qt Pcc Pdy 

Pr Pec Pdy Qal Qt Ara

Clin

Foss Hammon Leedey Cheyenne Strong City EXPLANATION Washita River alluvial aquifer Surficial geologic unit Qds Tertiary Ogallala Formation Quaternary Alluvium Dune sand Terrace deposits To Qal Qt Permian Rush Springs Formation Cloud Chief Formation Doxey Shale Elk City Member Pr Pcc Pdy Pec Note: The Elk City Member and Doxey Shale are locally referred to as the “Elk City Sandstone” and “Doxey Formation” (Fay and Hart, 1978) ELLIS COUNTY DEWEY COUNTY ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTYDEWEY COUNTY ELLIS COUNTY

TEXAS

OKLAHOMA

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Aquifer boundary modified from Johnson an

Oklahoma Water Reso

Geology from Hera

0 5 10 MILES0 5 10 KILOMETERS

100° 99°45' 99°30' 99°15' 99

35°45'35°30'

FOSS DAM

Washita

River

River

Washita

Foss

Reservoir

Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

River

Rush

Creek

Turkey 

Creek Spring

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

Creek WhiteShield

Turkey

Washita

Figure 7. Surficial geologic units in the Washita River alluvial aquifer study area, western Oklahoma.
System Hydrogeologic Unit Thickness, in feet* Descripti

Quaternary Washita River alluvial aquifer 0–230

Alluvium and terrace depositransported primarily by watto gravel in size. The terrace deposits of silt and sand size contains gravel laid down at former courses of present-d

Tertiary High Plains (Ogallala) aquifer 0–320

Brown to light tan sediments ancestral Rocky Mountains alluvial fans, and wind; fine- grained sand with some clayash, and caliche beds, with cemented by calcium carbo

Elk City Member1 Elk City aquifer 0–50

Confining unitConfining unit

Reddish-brown fine-grained amounts of silt and clay; weiron oxide, calcium carbona

Doxey Shale2 0–195 Reddish-brown silty shale a

0–175

Reddish-brown to orange-brinterbedded with siltstone adolomite and much gypsum

Rush Springs Formation

Orange-brown, fine-grained siltstone component, exhibitmedium- to large-scale crosthe Weatherford Gypsum be

Marlow Formation Orange-brown, cross-bedde

sandstone and siltstone

*Thicknesses and descriptions modified from Carr and Bergman (1976), Fay (1978), and Neel and others (2018).1Referred to locally as the Elk City Sandstone (Fay and Hart, 1978).2The Doxey Shale was originally classified a member of the Quartermaster Formation (Griley, 1933), but Fay and Hart (1978) raised the Doxey Shale to

formation rank and included it in the Foss Group. Fay and Hart (1978) also reclassified the Cloud Chief Formation as a member of the Foss Group.

Rush Springs aquifer

Permian

0–300

Whitehorse Group

Geologic Unit

Alluvium and terrace deposits

Ogallala Formation

Foss Group Quartermaster

Formation

Cloud Chief Formation

Figure 8. Surficial geologic and hydrogeologic units in the Washita River alluvial aquifer study area, western Oklahoma.
16 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Quartermaster Formation (Griley, 1933), but Fay and Hart 

(1978 ) raised the Doxey Shale to formation rank and included 

it in the Foss Group. Fay and Hart (1978) also reclassified 

the Cloud Chief Formation as a member of the Foss Group. 

The Elk City Member consists of fine-grained sandstone 

with minor amounts of silt and clay and with weak cementation of iron oxide, calcium carbonate, and gypsum (Carr and 

Bergman, 1976); the Elk City Member is considered a major 

bedrock aquifer in Oklahoma south of the study area (OWRB, 

2012b). The Doxey Shale is a confining unit in the study area. 

Based on the geologic map (fig. 7), the Doxey Shale and Elk 

City Member do not appear to subcrop below the Washita 

River alluvial aquifer but are located at the surface south 

of the Washita River alluvial aquifer in the study area. The 

Cloud Chief Formation consists of shale, interbedded with 

siltstone and sandstone, and has some dolomite and gypsum; 

the formation underlies much of the Washita River alluvial 

aquifer in the western part of the study area (Hart, 1978; 

Fay, 2010). The Cloud Chief Formation is considered relatively impermeable and likely provides minimal water to the 

Washita River alluvial aquifer. The Rush Springs Formation, 

part of the Whitehorse Group, underlies the Washita River 

alluvial aquifer in the eastern part of the study area. The Rush 

Springs Formation is part of a major bedrock aquifer, the Rush 

Springs aquifer, in Oklahoma, but is not used as an aquifer 

in the western part of the study area underlying the Washita 

River alluvial aquifer, the Ogallala Formation, and the Cloud 

Chief Formation (Neel and others, 2018). The Rush Springs 

Formation is a cross-bedded, fine-grained sandstone with a 

siltstone component and contains the Weatherford Gypsum 

bed (Carr and Bergman, 1976). The Rush Springs Formation 

likely subcrops below the Washita River alluvial aquifer, but 

the extent is difficult to discern from the geologic map (fig. 7). 

The Rush Springs Formation is possibly in direct hydraulic 

connection with the Washita River alluvial aquifer in some 

areas (Hart, 1978), but the quantity of groundwater flowing 

between the Rush Springs Formation and the Washita River 

alluvial aquifer has not been measured. The Rush Springs 

Formation outcrop is exposed on the north side of the Washita 

River alluvial aquifer starting about 4 mi west of Hammon and 

extends eastward to about the middle part of Foss Reservoir. 

Barnitz Creek overlies the Rush Springs Formation and the 

northern margin of the Washita River alluvial aquifer.

Groundwater Quality

Groundwater samples were collected between July 28 

and August 25, 2014, from the Washita River alluvial aquifer as part of the OWRB Groundwater Monitoring and 

Assessment Program (OWRB, 2017a). Groundwater was sampled from 12 wells along the 116-mi reach 1 of the Washita 

River alluvial aquifer (fig. 9). Nine of the wells were in Roger 

Mills County, and 3 were in Custer County. The groundwater 

samples were analyzed for physical properties (water temperature, dissolved oxygen, pH, and specific conductance), major 

ions, dissolved solids, nutrients, and trace metals.

Dissolved-solids concentrations in the groundwater 

samples ranged from 1,760 to 3,650 milligrams per liter 

(mg/L), with a median concentration of 2,895 mg/L and a 

mean concentration of 2,832 mg/L (OWRB, 2017a). The U.S. 

Environmental Protection Agency (2020) has established a 

secondary drinking water standard of 500 mg/L for dissolved 

solids; however, the State of Oklahoma considers water with 

dissolved solids less than 5,000 mg/L to be fresh (OWRB, 

2017a). No groundwater samples had dissolved solids concentrations exceeding the 5,000-mg/L threshold (OWRB, 2017a).

Specific conductance ranged from 2,060 to 3,940 microsiemens per centimeter at 25 degrees Celsius (μS/cm), with 

a median value of 2,925 μS/cm and a mean of 2,988 μS/cm. 

All groundwater samples were classified as hard water, with 

hardness values greater than 180 mg/L of calcium carbonate. The hardness ranged from 1,088 to 1,916 mg/L, with a 

median value of 1,708 mg/L and a mean value of 1,679 mg/L. 

Of the trace metals and elemental constituents analyzed, only 

concentrations of iron, manganese, and uranium exceeded 

the secondary drinking water standards or maximum contaminant levels. Concentrations of iron in samples from 4 of 

the 12 wells exceeded the secondary drinking water standard (300 micrograms per liter [μg/L]; U.S. Environmental 

Protection Agency, 2020), and the median iron concentration 

for all samples was 158 μg/L. Concentrations of manganese in 

samples from 4 of the 12 wells exceeded the secondary drinking water standard (300 μg/L; U.S. Environmental Protection 

Agency, 2020), and the median manganese concentration for 

all samples was 96.5 μg/L. The uranium concentration in 1 

of the 12 wells exceeded the maximum contaminant level 

(30 μg/L; U.S. Environmental Protection Agency, 2020), with 

a value of 40.7 μg/L. The median concentration of uranium for 

all samples was 7.9 μg/L.

Major-ion data from the OWRB Groundwater Monitoring 

and Assessment Program were plotted on a piper diagram 

(Piper, 1944) to determine the sources of the dissolved constituents in the groundwater (fig. 10). Major-ion concentrations 

in the groundwater were fairly similar in samples representing 

different parts of the aquifer, with calcium being the dominant 

cation in all but four groundwater samples and sulfate being 

the dominant anion in all groundwater samples (fig. 10). The 

four groundwater samples in which calcium concentrations 

were lowest were collected from wells located farthest upgradient (fig. 9). These wells were categorized as having no dominant ion type. The percentages of calcium in samples from 

these four wells were less than about 75 percent of the total 

cations, with magnesium and sodium plus potassium each representing about 25 percent of the remaining cations. The concentrations of calcium, magnesium, and sulfate in the groundwater were attributed to the dissolution of gypsum, dolomite, 

and calcite within the Cloud Chief Formation, which underlies 

the sampling extent of the Washita River (Becker and Runkle, 

1998) (figs. 7 and 9). The concentrations of sodium, chloride, 

and potassium in the groundwater samples were likely from 

evaporite deposits in the Rush Springs Formation.
Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

River

Rush

Creek

Turkey 

Creek

Spring

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

Creek WhiteShield

Turkey

Washita 3,650

2,380

3,010

2,780

3,160

3,300

3,250

3,190

2,410

2,700

1,760

EXPLANATION

Groundwater-quality sample collected from  well (OWRB, 2017a); number is total  dissolved solids, in milligrams per liter

Washita River alluvial aquifer

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Foss

Reservoir

100° 99°45' 99°30' 99°15' 

35°45'35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Washita

River

River

Washita

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Figure 9. Locations of groundwater-quality samples collected from wells in the Washita River alluvial aquifer, western Oklahoma, and tsolids in groundwater samples collected during July–August 2014.
18 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Percent

Percent

Percent

Calcium (Ca)

Magnesium (Mg)

Bicarbonate (HCO3

) + Carbonate (CO3

)

Magnesium (Mg)

Calcium (Ca) +

Sodium (Na) + Postassium (K)

Sulfate (SO4

)

Chloride (Cl) + Fluoride (F)

+ Sulfate (SO4

)

Chloride (Cl) + Fluoride (F)

100

80

60

40

20

0

100 80 60 40 20 0

0

20

40

60

80

20

40

60

80

100

0 20 40 60 80 100

100

80

60

40

20

20

40

60

80

0

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

Predominant hydrochemical facies

Cations

Anions

Calcium-sulfate type

Calcium

No dominant cation

Sulfate

EXPLANATION

Figure 10. Major cations and anions in groundwater-quality samples of produced water from 12 wells open to the 

Washita River alluvial aquifer, western Oklahoma, July–August 2014.
Hydrogeologic Framework of the Washita River Alluvial Aquifer 19

Hydrogeologic Framework of the 

Washita River Alluvial Aquifer

The hydrogeologic framework of the Washita River 

alluvial aquifer describes the physical characteristics of the 

aquifer, the characteristics and hydraulic properties of hydrogeologic units, the potentiometric surface, and groundwaterflow directions at a scale that captures the regional controls 

on groundwater flow. The hydrogeologic framework was used 

in the construction of numerical groundwater model of the 

Washita River alluvial aquifer described in this report.

Aquifer Extent

The extent of the Washita River alluvial aquifer was 

modified for this study from the alluvium extent mapped by 

Johnson and others (2003) and Fay (2010) by using existing well lithologic logs (OWRB, 2015) and high-resolution 

orthophotographs (Microsoft Corporation, 2017) to delineate 

alluvium. In many places, the Washita River alluvial aquifer extent was found to be a smaller area than the mapped 

alluvium (fig. 7). Bedrock units of Permian age that underlie the Washita River alluvial aquifer were delineated by 

using mapped outcrops adjacent to the aquifer. Because 

beds of Permian age dip gently to the south, the Cloud Chief 

Formation has been removed by erosion to expose the Rush 

Springs Formation on the north side of the Washita River 

alluvial aquifer; however, the Cloud Chief Formation covers 

the south side of the Rush Springs Formation (fig. 7). The alluvium and terrace deposits were not found to have enough saturated thickness to be considered a water source in the western 

part of the study area, and in the easternmost part of the study 

area, the terrace deposits overlie the Rush Springs aquifer and 

are considered part of the Rush Springs aquifer and not part of 

the Washita River alluvial aquifer.

Lithological borehole logs from the OWRB (OWRB, 

2015), and results from ambient seismic soundings collected 

as part of this study (USGS, 2018b) and available in Ellis and 

others (2020) were used collectively to define the altitude of 

the base of the Washita River alluvial aquifer, which is shown 

in figure 11 as the estimated aquifer thickness. The aquifer 

thickness was determined by using the 60-meter (197-ft) digital elevation model land surface (USGS, 2018a) and the points 

of measured depth to the base of the aquifer. The aquifer thickness was interpolated between points of calculated thickness, 

and the edge of the alluvial aquifer (farthest away from the 

river) was set to zero thickness for use as a control point.

The ambient seismic method described by Lane and others (2008) was used at 45 locations across the Washita River 

alluvial aquifer (fig. 11). Many of the ambient seismic points 

were along lines traversing the Washita River alluvial aquifer 

to show a cross-sectional profile of the aquifer. All ambient seismic sounding locations were published in the USGS 

National Water Information System database (USGS, 2018b) 

and are available in Ellis and others (2020). At each site, a 

Tromino digital seismometer was oriented to geographic north 

and pushed into a flat area of bare ground, allowing the stabilizing spikes on the bottom of the unit to firmly anchor into the 

soil (Tromino, 2012). The Tromino digital seismometer was 

then leveled and set to record for 10–30 minutes, a timeframe 

chosen based on the instrumentation guidelines (Bard and 

SESAME-Team, 2004) and the estimated thickness of the 

alluvial deposits. During that timeframe, the Tromino digital 

seismometer gathered ambient seismic shear waves, measuring the frequency and amplitude of shear waves along two 

horizontal axes and one vertical axis. Unconsolidated alluvial 

deposits have a slower shear-wave velocity than that of the 

consolidated bedrock; this contrast in shear-wave velocities 

causes the horizontal-to-vertical ratio of the velocities to form 

a peak from which a measurable resonant frequency of the 

consolidated bedrock is attained by using Grilla, a postprocessing software package provided by the digital seismometer 

manufacturer (Tromino, 2017). Bedrock depth was estimated 

from this resonant frequency according to the following equation from Tromino (2012):

Z=VS / (4F0) (1)

where

Z is the depth to bedrock, in feet;

VS is the shear-wave velocity of the 

unconsolidated alluvial deposits, in feet per 

second; and

F0 is the resonant frequency of the consolidated 

bedrock, in Hertz.

The Washita River alluvial aquifer likely contains some 

caliche zones. Caliche zones have shear-wave velocities 

similar to those of consolidated bedrock; therefore, these 

zones may have caused a low bias to the depth to bedrock 

as estimated by horizontal-to-vertical spectral ratio (HVSR) 

seismic methods. In general, HVSR seismic methods probably are less accurate than more direct methods of estimating 

the depth to bedrock. Chandler and Lively (2014) collected 

HVSR seismic measurements at 41 control points of known 

depth in Minnesota glacial deposits. About 10 percent of those 

measurements had errors greater than 25 percent, and about 

37 percent of those measurements had errors greater than 

15 percent. The ambient seismic data for this study indicated 

a range in thickness of 0 to 200 ft, with an average of 98 ft to 

the base of the Washita River alluvial aquifer (fig. 11). Many 

of the ambient seismic points were along lines traversing the 

Washita River alluvial aquifer to show a cross-sectional profile 

of the aquifer, and ambient seismic points are published in the 

USGS National Water Information System database (USGS, 

2018b) and are available in Ellis and others (2020).

The aquifer base was interpolated between points of 

measured base-of-aquifer altitude that indicated an ancestral 

valley (erosional surface of bedrock) trending to the southeast. 

Most lithological borehole logs typically noted bedrock that 
Base from U.S. Geological Survey digital data Albers Equal-Area Conic projection; North American Datum 1983 ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY ELLIS COUNTY DEWEY COUNTY Foss Reservoir 100° 99°50' 99°40' 99°30' 99°20' 99°10' 9

35°50' 35°45' 35°40' 35°35' 35°30' 35°25' Aquifer modified from Johnson 

Oklahoma Water Re

0 5 10 MILES 0 5 10 KILOMETERS

TEXAS

OKLAHOMA

FOSS DAM

EXPLANATION

Thickness of Washita River alluvial  aquifer, in feet

0 to 28.9

29.0 to 48.949.0 to 68.969.0 to 88.9

89.0 to 110.7

110.8 to 134.2134.3 to 162.0162.1 to 220.4

Data point and method used to interpolate the  base of the Washita River alluvial aquifer

! U.S. Geological Survey ambient seismic 

 point (U.S. Geological Survey, 2018b)

! Base from lithological log (Oklahoma 

 Water Resources Board, 2015)

Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

River

Rush

Creek

Turkey 

Creek

River

Washita

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Wildcat

Creek

Big

Kiowa

Creek

Turkey

Washita

Washita

River

Figure 11. Points and methods used for the interpolation of the aquifer thickness of the Washita River alluvial aquifer, western Oklahoma.
Hydrogeologic Framework of the Washita River Alluvial Aquifer 21

changed from tan to red. The thickness of the Washita River 

alluvial aquifer as estimated for this report is highly variable, with a mean of 52 ft and a narrow, deep channel that is 

approximately 220 ft thick near the northern part of Roger 

Mills County in the western part of the Washita River alluvial 

aquifer (fig. 11). The mean thickness is biased thin because 

several tributary valleys have alluvium less than 50 ft thick.

Potentiometric Surface and Groundwater-Level 

Fluctuations

Potentiometric-surface maps show the altitude at which 

the groundwater level would have stood in tightly cased 

wells at a specified time; the potentiometric surface is usually 

contoured or spatially interpolated from synoptic water-tablealtitude measurements in many wells across the aquifer extent. 

In this report, the water table is the same as the potentiometric 

surface for the Washita River alluvial aquifer because the 

aquifer is unconfined. Potentiometric-surface maps are used 

to indicate the general directions of groundwater flow in the 

aquifer. Groundwater generally flows perpendicular to potentiometric contours in the direction of decreasing contour altitudes. The potentiometric surface for March 2017 was mapped 

by using groundwater-level measurements from 20 wells, 

(USGS, 2018b) and Ellis and others (2020), and the approximate altitude of the Washita River and Foss Reservoir stages 

(USGS, 2018a and Bureau of Reclamation, 2018) (fig. 12); 

Foss Reservoir had a mean stage of 1,630.6 ft in 2015 (Bureau 

of Reclamation, 2018). The potentiometric surface was also 

approximated and was derived as the difference between the 

60-meter digital elevation model land surface (USGS, 2018a) 

and the measured depth to water.

Methods described in Cunningham and Schalk (2011)

were used to obtain groundwater-level measurements from 

20 domestic and irrigation wells across the Washita River 

alluvial aquifer during March 2017 (USGS, 2018b) and 

Ellis and others (2020). In addition, reports of the depth to 

which driller’s encountered water during drilling, provided 

on well completion reports (OWRB, 2018), for wells in the 

Washita River alluvial aquifer were used to fill in areas with 

few groundwater-level measurements. These two sources 

of measurements were used to determine the potentiometric 

surface for the Washita River alluvial aquifer. The potentiometric surface was interpolated between measured wells and 

contoured using a 20-ft interval (fig. 12). Groundwater in the 

Washita River alluvial aquifer flows generally downgradient 

to the southeast and locally flows toward and discharges to the 

Washita River in most areas. The Washita River is generally 

a gaining stream except for the western part of the Washita 

River in Roger Mills County as evidenced by the mapped 

potentiometric-surface contours that show a “V” pattern that 

point upstream (fig. 12).

The three observation wells with long-term water-level 

data (at least 25 measurements spanning at least 10 years) 

were OWRB wells 2687, 9328, and 2700 (OWRB, 2015) 

(figs. 1 and 13C). All three observation wells were in the 

Cheyenne area, and nearly all water-level measurements were 

made during January–March when irrigation water use is 

minimal.

OWRB observation well 2687 was located approximately 2.5 mi north of the town of Cheyenne on the western 

margin of the Washita River alluvial aquifer (fig. 1). The 

general pattern of slightly increasing groundwater-level 

altitudes is evident from 1987 to 2001 in well 2687 (fig. 13C). 

Groundwater-level altitudes can change markedly during wet 

and dry periods, particularly the dry period during the early 

1980s, the wet period from 1985 to 2002, the erratic wet and 

dry years of 2003–2010, and the drought of 2011–2016. Most 

changes in annual-mean precipitation are attenuated; the lag in 

groundwater-level changes was most likely because the depth 

to water was more than 25 ft below land surface.

OWRB observation well 9328 is located just north of 

Cheyenne, Okla., on a low terrace just above the floodplain of 

the Washita River, and the period of record for groundwaterlevel measurements was from 1980 to 2002 (figs. 1 and 13C). 

The groundwater-level altitude slightly increased from 1983 

to 1988. The groundwater-level record for well 9328 remained 

approximately static during the wet period of 1985–2002; the 

pattern for well 2687 was tempered by the subsequent erratic 

wet and dry years of 2003–2015.

OWRB observation well 2700 is located approximately 

3.75 mi west-northwest from Cheyenne (fig. 1). The period of 

record for groundwater-level measurements was from 1980 to 

1994. An overall pattern of decreasing groundwater-levels in 

well 2700 was evident during the wet period starting in 1985 

(fig. 13C).

Textural and Hydraulic Properties

The Washita River alluvial aquifer is an unconsolidated 

alluvium deposited in a fluvial environment; therefore, the 

horizontal hydraulic conductivity and specific yield of the 

alluvial aquifer can be highly variable. The hydraulic conductivity of the Washita River alluvial aquifer was estimated from 

two aquifer tests reported by Burns & McDonnell Engineering 

Company, Inc. for the City of Clinton, Okla., in the southeast 

end of the Washita River alluvial aquifer (Burns & McDonnell 

Engineering Company, Inc., 2015) and from lithological logs 

for 216 wells registered with the OWRB (fig. 14).

Burns & McDonnell Engineering Company, Inc. conducted two aquifer tests west of Clinton, Okla.; however, the 

details of how the tests were performed are not provided in 

the report. One test was located at well DXN-TH7, and one at 

well M-1 (fig. 14). At both locations, the aquifer was confined 

or leaky confined, and observation wells near the tests ranged 

from unconfined to semiconfined and confined. Transmissivity 

at well M-1 was calculated to be 9,000 gallons per day per 

foot or 1,069 to 1,230 feet squared per day (ft2/d), or hydraulic 

conductivity of 27.3 feet per day (ft/d) over the approximately 

44 ft of saturated thickness at the site. At well DXN-TH7, the 
! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! !! ! !! ! ! ! !! 

! ! ! !! ! ! !!!!!!!! !!!! !! !!!!!! ! !! ! ! 

! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! !! ! ! ! 

! 

! !! ! ! !! ! ! ! !! ! !! ! !! !!! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! !! !! !! !! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! 

! ! ! ! ! ! ! ! ! EXPLANATION Potentiometric-surface contour—shows altitude at which the water level would have stood in a tighty cased well. Contour interval 100 feet. Datum is North American Vertical Datum of 1988 ! Potentiometric-surface data point Washita River alluvial aquifer 2,200 2,100 2,000 1,900 1,800 1,700 1,800 1,600 1,600 ROGER MILLS 1,5

COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY ELLIS COUNTY DEWEY COUNTY 100° 99°50' 99°40' 99°30' 99°20' 99°10' 99

35°50' 35°45' 35°40' 35°35' 35°30' 35°25' Aquifer extent modified from Johnson an

Oklahoma Water Reso

0 5 10 MILES 0 5 10 KILOMETERS

TEXAS

OKLAHOMA

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Figure 12. Potentiometric-surface contours for March 2017 based on groundwater-level altitudes measured in wells and first water repodrillers’ logs completed in the Washita River alluvial aquifer, western Oklahoma.
Hydrogeologic Framework of the Washita River Alluvial Aquifer 23

aquifer behaved as a leaky confined system during a pumping and recovery test. The transmissivity was calculated to be 

30,000 gallons per day per foot (40,104 ft2/d), or a hydraulic 

conductivity of 105.5 ft/d over 38 ft of saturated thickness.

For various locations where subsurface information 

was available, the mean hydraulic conductivity for the total 

aquifer thickness was estimated from lithological borehole 

logs (OWRB, 2015). Mean horizontal hydraulic conductivity 

was then interpolated across the aquifer to provide an initial 

distribution of horizontal hydraulic conductivity by using the 

inverse-distance-weighted interpolation method (Esri, Inc., 

2015), where values nearest the interpolated location have the 

greatest influence on the interpolated value at that location. 

The mean horizontal hydraulic conductivity was estimated 

by assigning a published horizontal hydraulic conductivity 

value to intervals listed in borehole logs and calculating the 

56

57

58

59

60

61

62

63

Annual-mean air temperature, 

in degrees Fahrenheit

10

15

20

25

30

35

40

45

Annual-mean precipitation, 

in inches per year

1,880

1,890

1,900

1,910

1,920

1,930

1,940

1,950

1,960

1,970

Groundwater-level altitude, in feet above 

North American Vertical Datum of 1988

1885 1890 1895 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Wet Period Dry Period

A.

B.

C.

Data for west-central Oklahoma, Climate Division 4 

(National Climatic Data Center, 2018)

Data for west-central Oklahoma, Climate Division 4 

(National Climatic Data Center, 2018)

OWRB well number 2687 - Observed (OWRB, 2015)

OWRB well number 2687 - Simulated

OWRB well number 9328 - Observed (OWRB, 2015)

OWRB well number 9328 - Simulated

OWRB well number 2700 - Observed (OWRB, 2015)

OWRB well number 2700 - Simulated

Annual-mean temperature

EXPLANATION

EXPLANATION

Mean annual temperature for 1895–2017

Loess smoothing

Annual-mean precipitation

EXPLANATION

Mean annual precipitation for 1895–2017

Loess smoothing

Figure 13. A, Annual-mean air temperature, B, annual-mean precipitation, and C, groundwater-level altitude measured in or near 

Oklahoma Water Resources Board (OWRB) observation wells 2687, 9328, and 2700 completed in the Washita River alluvial aquifer, 

western Oklahoma.
Washita River alluvial aquifer EXPLANATION Mean calculated horizontal hydraulic conductivity, in feet per day < 7070 to 100 100 to 130 130 to 160 160 to 190 Hydraulic conductivity data point Aquifer tests (Burns & McDonnell Engineering Company, Inc., 2015) 

" " " " " A

C

Foss HammonLeedey Cheyenne Strong City ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY ELLIS COUNTY DEWEY COUNTY Foss Reservoir 100° 99°45' 99°30' 99°15' 

35°45' 35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

M

DXN-TH7

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Figure 14. Locations of mean horizontal hydraulic conductivity based on lithologic descriptions reported in borehole logs (OWRB, 2015) aquifer tests (Burns & McDonnell Engineering Company, Inc., 2015), Washita River alluvial aquifer, western Oklahoma.
Conceptual Flow Model 25

mean, weighted by the thickness of each interval. To estimate 

horizontal hydraulic conductivity values for intervals described 

in logs, the standard texture class that best matched the log 

texture was assigned to the intervals. The horizontal hydraulic 

conductivity for the texture classification published by the U.S. 

Environmental Protection Agency (1986) was then assigned 

to that interval, and the mean horizontal hydraulic conductivity was determined by weighting each interval by the interval 

thickness (fig. 14). The horizontal hydraulic conductivity 

derived by using lithologic borehole logs is typically less than 

that derived from aquifer tests by approximately 5–10 percent. 

No information was available on specific yield from published aquifer tests in the Washita River alluvial aquifer, so 

that parameter was estimated as described in the "Calibration 

Parameters" and "Using the Water-Table-Fluctuation Method to 

Estimate Recharge" sections of this report.

Conceptual Flow Model

A conceptual flow model is a simplified description of 

the aquifer system that includes the hydrologic boundaries, 

the major inflow and outflow sources of the groundwater-flow 

system, and a conceptual water budget with the estimated mean 

flows between those hydrologic boundaries. The conceptual 

flow model and hydrogeologic framework were used to conceptualize, design, and build the numerical groundwater-flow 

model. The conceptual water budget (table 5) includes estimated mean annual inflows to and outflows from the Washita 

River alluvial aquifer for the period 1980–2015 and includes 

a sub-accounting of mean annual inflows and outflows for the 

parts of the aquifer that were upgradient and downgradient 

from Foss Reservoir. The starting date of 1980 was chosen 

because water-use data were sparse prior to 1980.

Water Use

During the period 1980–2015, groundwater use was estimated for 156 irrigation, mining, and public supply active and 

temporary permits (OWRB, 2018) (fig. 15). Of the 156 permits, 

121 were upgradient from Foss Reservoir, and 35 were downgradient from Foss Reservoir. Mean annual groundwater use 

for the study period totaled 5,502 acre-ft/yr, or about 14 percent 

of aquifer outflows (table 5). Mean annual groundwater use for 

the study period included 4,923 acre-ft/yr and 579 acre-ft/yr 

upgradient and downgradient from Foss Reservoir, respectively 

(table 5). Total groundwater use includes 5,319 acre-ft/yr 

for irrigation (97 percent), 179 acre-ft/yr for public supply 

(3.3 percent), and 4 acre-ft/yr for all other use types (greater 

than 1 percent) (OWRB, 2018).

Reported surface-water use in the Washita River alluvial 

aquifer consists of 69 permitted diversions along the Washita 

River and associated tributaries (fig. 2). The mean annual withdrawal rate for all surface-water permitted diversions during 

the study period was 1,523 acre-ft/yr (OWRB, 2018), including 

919 acre-ft/yr and 604 acre-ft/yr of permitted use upgradient 

and downgradient from Foss Reservoir, respectively. During 

the study period, 27 permitted diversions had mean annual 

withdrawal rates between 2 and 298 acre-ft/yr. This total withdrawal includes all active and temporary permits in the boundaries of the Washita River alluvial aquifer for the study period.

Recharge

For this report, groundwater recharge is defined as the 

amount of water that originates as precipitation and infiltrates 

from the land surface through the unsaturated zone and to the 

top of the water table. Other processes that may be included 

in a broader definition of recharge are stream seepage, lateral 

Table 5. Conceptual water budget for the Washita River alluvial aquifer, western Oklahoma, 1980–2015.

[All units in acre-feet per year unless otherwise specified; %, percent; --, not quantified]

Water-budget category Upgradient from 

Foss Reservoir

Downgradient from 

Foss Reservoir Total Percentage of water budget

Inflow

Recharge 15,370 6,799 22,169 56%

Lateral flow1 2,308 14,849 17,157 44%

Lakebed seepage1 -- -- -- --

Total inflow 17,678 21,648 39,326

Outflow

Stream seepage1 4,676 17,320 21,996 56%

Saturated-zone evapotranspiration 8,079 3,749 11,828 30%

Groundwater use 4,923 579 5,502 14%

Net change in groundwater storage -- -- -- --

Total outflow 17,678 21,648 39,326

1Lakebed seepage, stream seepage, and lateral flow represent net terms.
! ! ! ! ! ! ! 

! ! ! ! ! ! ! ! ! 

! ! ! ! ! ! ! ! 

! ! ! 

! ! ! ! !! ! ! ! ! !! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! 

!! ! ! ! ! ! ! ! ! ! 

! ! ! ! 

! ! ! ! Allocated Groundwater Rights—Permitted wells (Oklahoma Water Resources Board, 2018) ! Irrigation ! Mining ! Public Supply Allocated Groundwater Rights—Dedicated lands (Oklahoma Water Resources Board, 2018) Irrigation Mining Public Supply EXPLANATION Washita River alluvial aquifer ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY DEWEY COUNTY ELLIS COUNTY Foss Reservoir 100° 99°45' 99°30' 99°15' 

35°45' 35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Washita

River

River

Washita

Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

Rush

Creek

Turkey 

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

White

Turkey

Figure 15. Locations of permitted groundwater wells and usage categories in the Washita River alluvial aquifer, western Oklahoma, 198
Conceptual Flow Model 27

groundwater flow from adjacent hydrogeologic units, or 

lakebed seepage, which are accounted for separately in the 

Washita River alluvial aquifer conceptual water budget.

Recharge rates are controlled by several factors, 

including precipitation rates, evapotranspiration (ET) rates, 

unsaturated-zone permeability and moisture capacity, and 

slope of the land surface (Keese and others, 2005). Although 

recharge rates are difficult to measure because of high spatial and temporal variability, methods using a mass-balance 

approach, streamflow-hydrograph techniques, environmental 

tracers, physical measurements, and computer code have been 

used to estimate recharge rates. Estimates of recharge for the 

study area were obtained by using the Soil-Water-Balance 

(SWB) code (Westenbroek and others, 2010) and a watertable-fluctuation method (Healy and Cook, 2002).

Using the Soil-Water-Balance Code to Estimate 

Recharge

Spatially distributed recharge resulting from precipitation and infiltration to the Washita River alluvial aquifer 

was computed for each month of the study period by using 

the SWB code (Westenbroek and others, 2010). The SWB 

code is based on a modified Thornthwaite-Mather method 

(Thornthwaite and Mather, 1957) and uses grids of landscape 

and climate data to provide estimates of spatially distributed 

deep percolation through the soil profile, which is referred to 

as recharge for the purposes of this report. The SWB code uses 

a mass-balance approach to compute gridded recharge as the 

difference between sources and sinks for each grid cell, while 

accounting for the cumulative effects of the change in soil 

moisture. All values in the mass-balance equation (modified 

from Westenbroek and others, 2010) are reported in inches:

R = (P + S + Ri) − (Int + Ro + Pet) − ∆Sm (2)

where

R is recharge,

P is precipitation,

S is snowmelt,

Ri is surface runoff inflow,

Int is plant interception,

Ro is surface runoff outflow,

Pet is potential evapotranspiration, and

ΔSm is the change in soil moisture.

Daily climate data for 21 climate stations (table 6), 

including precipitation and minimum and maximum air 

temperature, were obtained (National Climatic Data Center, 

2018; Oklahoma Mesonet, 2018) and interpolated to a grid 

by using a 350-ft uniform spacing. Soil properties (soil-water 

storage capacity and hydrologic soil group) and land cover 

were derived from the Digital General Soil Map database 

(Natural Resources Conservation Service [NRCS], 2018), 

which is an inventory of generalized soil characteristics at a 

scale between 1:12,000 and 1:63,360. Some precipitation was 

accounted for as snowmelt, based on the daily minimum and 

maximum air temperatures. Surface runoff inflow—whereby 

runoff is routed between cells moving downhill—was calculated by using a flow-direction grid derived from a digital 

elevation model (DEM) (USGS, 2018a) and a runoff curve 

number. For the flow-direction grid, this study used a light 

detection and ranging (lidar) dataset (USGS, 2016) upscaled 

to the model grid. To ensure correct routing of surface runoff 

and to eliminate areas of internal drainage that can result in 

unrealistic amounts of recharge, depressions in the DEM were 

filled. Plant interception occurs when precipitation is captured 

by vegetation prior to reaching the top of the soil profile and 

was specified for each land-cover type during the growing 

season. Surface runoff outflow was calculated by using NRCS 

curve numbers related to the relation between rainfall and 

runoff (Westenbroek and others, 2010). Potential evapotranspiration in the SWB code was calculated by using methods 

from Hargreaves and Samani (1985), discussed further in the 

“Saturated-Zone Evapotranspiration” section of this report.

Root-zone depths represent the maximum depth to which 

various types of vegetation will grow and are classified based 

on land-cover and soil type. Greater plant root-zone depths 

result in the increased uptake of water by roots in the soilmoisture zone, thus decreasing recharge, whereas less rootzone depth results in less soil water uptake and more water 

going to recharge. Winter wheat, the dominant crop type overlying the Washita River alluvial aquifer (National Agricultural 

Statistics Service, 2019; fig. 3), has mean and maximum rooting depths of about 1.0 and 4.6 ft, respectively, in Oklahoma 

(Patrignani and others, 2012; David Marburger, Oklahoma 

State University, written commun., 2018). To account for this 

root-zone depth range, 50 percent of the default values of 

Westenbroek and others (2010) for each land-cover type were 

selected, which resulted in root-zone depths for crops between 

1.0 and 1.7 ft.

An important assumption of the SWB code is that standing water does not persist from day to day and is not available 

to provide recharge to groundwater. Another assumption of the 

SWB code is that if the water on the surface is not snow, then 

it evaporates or runs off after 1 day. The root zone is presumed 

to be above the water table so that the only source of water 

for the soil profile is water percolating from the land surface. 

In parts of the Washita River alluvial aquifer, particularly 

near lakes and streams, plant roots reach the water table, and 

the SWB code overestimates recharge for wet periods during 

the growing season because it calculates actual plant uptake 

according to available soil water and does not include plant 

uptake directly from groundwater. Thus, there is an additional loss through ET that is not accounted for, comparable 

to the difference between the actual and potential ET calculated by the SWB code. This topic is discussed further in the 

“Simulation of Groundwater Flow” section of this report.

The SWB code estimated the mean annual recharge for 

the study period as about 2.5 in. or about 11 percent of the 

mean annual precipitation of 23 in. (fig. 16). The SWB code 

inputs and outputs are available in Ellis and others (2020). 
28 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

The SWB code estimated the minimum and maximum mean 

annual recharge values for the study period as about 0.38 in/yr 

(2014) and 6.8 in/yr (2015), respectively. Monthly mean 

recharge tended to be greatest from March to June and in 

October (fig. 17B). Recharge in these months corresponds 

to between 8 and 16 percent of the monthly mean precipitation for those months (fig. 17A). July and February were the 

months with the least amounts of recharge. Recharge amounts 

in July and February correspond to between 4 and 15 percent 

of monthly mean precipitation for those months.

Even though more precipitation falls on the eastern part 

of the aquifer, landscape characteristics affect recharge enough 

that mean annual recharge for the study period was greatest in 

the western part of the aquifer—generally defined as the area 

west of Cheyenne—where the Washita River alluvial aquifer 

incises the Ogallala Formation (fig. 18). The hydrologic soils 

group assigned to the Washita River alluvial aquifer alluvium 

incising the Ogallala Formation (fig. 7) had a high infiltration capacity, and a low overland flow capacity. The available 

water (holding) capacity for the alluvium west of Rush Creek 

was also smaller than in other areas, indicating a sandier 

soil texture (as opposed to clay), and consequently a greater 

potential for infiltration. Additionally, runoff from the Ogallala 

Formation to the incised Washita River alluvial aquifer 

alluvium increased recharge. Using the Soil-Water-Balance 

code, runoff from one cell in the model is assumed to infiltrate 

into nearby cells. Hence, recharge may be shifted from the 

Ogallala Formation to the thin area of Washita River alluvial 

aquifer alluvium, rather than simulating overland flow to 

surface-water storage (Stanton and others, 2012). Additionally, 

fewer temporal climate data (precipitation and minimum and 

maximum air temperature) were available for the western 

part of the Washita River alluvial aquifer—generally defined 

as the part of the aquifer between the Texas–Oklahoma 

Table 6. Selected climate stations used for assessing the soil-water balance in and near the Washita River alluvial aquifer, western 

Oklahoma.

[SWB, Soil-Water-Balance; dates are in month/day/year format]

Station identifier Station name

Latitude, 

in decimal 

degrees

Longitude, 

in decimal 

degrees

Station period of record 

(may contain gaps) or single 

measurement date

Begin End

Oklahoma Mesonet climate stations (Oklahoma Mesonet, 2018) used for running the SWB code

ARNE Arnett 36.07204 −99.90308 2/1/2009 12/31/2017

BESS Bessie 35.40185 −99.05847 1/1/1994 12/31/2017

BUTL Butler 35.59150 −99.27059 1/1/1994 12/31/2017

CHEY Cheyenne 35.54615 −99.72790 2/1/2009 12/31/2017

PUTN Putnam 35.89904 −98.96038 1/1/1994 12/31/2017

WEAT Weatherford 35.50830 −98.77509 1/1/1994 12/31/2017

National Oceanic and Atmospheric Administration climate stations (National Climatic Data Center, 2018) used for running the SWB code

USC00410157 ALLISON 35.61030 −100.10220 8/1/2001 12/31/2017

USC00340684 BESSIE 4 WNW MESONET, OK US 35.40167 −99.05833 2/1/2009 12/31/2017

USC00411408 CANADIAN 22 SE 35.64670 −100.06570 3/1/2003 2/1/2015

USC00341738 CHEYENNE 35.60000 −99.68330 7/1/1980 12/31/1994

US1OKRM0002 CHEYENNE 18.1 SW 35.86130 −99.78200 2/3/2007 12/31/2017

USC00341909 CLINTON 35.50139 −98.97722 7/31/1936 8/15/2005

USW00003932 CLINTON SHERMAN AIRPORT 35.61030 −100.10220 8/16/1958 12/31/2017

USC00342849 ELK CITY 4 W 35.39250 −99.50639 5/1/1904 12/31/2017

USC00345090 LEEDEY 35.86290 −99.34280 8/1/1941 12/31/2017

USC00345648 MAYFIELD 35.33920 −99.87690 10/4/2010 2/29/2012

USC00347343 PUTNAM 3 N MESONET, OK US 35.89889 −98.96028 2/1/2009 12/31/2017

USC00347579 REYDON 35.62560 −99.91060 1/1/1980 8/18/2005

USC00347952 SAYRE 35.30620 −99.62750 5/31/1936 12/31/2017

USC00348652 SWEETWATER 35.42190 −99.90530 9/17/1982 4/30/2008

USC00349422 WEATHERFORD 35.02580 −99.10580 12/31/1904 12/31/2017
Conceptual Flow Model 29

border and the Cheyenne streamgage—than for the part of 

the aquifer downgradient from Foss Reservoir. SWB code 

calculations indicated greater recharge in the terrace deposits 

than in the alluvium deposits because of a sandier soil type in 

the terrace deposits that had a lower available water capacity 

(Westenbroek and others, 2010; fig. 18).

Mean annual recharge rates estimated by the SWB 

code were compared to published estimates of mean annual 

recharge. Kent and others (1984) estimated a recharge of 

3.72 in/yr, or about 12 percent of a mean precipitation of 

32.2 in/yr, across the Washita River alluvial aquifer that covers the extent of Oklahoma and includes other reaches not 

discussed in this report. Schipper (1983) estimated a recharge 

0

7,000

14,000

21,000

28,000

35,000

42,000

49,000

56,000

0

1

2

3

4

5

6

7

8

19801985199019952000200520102015

Mean annual precipitation, in inches

Mean annual recharge, in acre-feet

Mean annual recharge, in inches

Year

0

6

12

18

24

30

36

42

48

Recharge, in acre-feet per year

EXPLANATION

Annual precipitation

Mean annual precipitation for 1980–2015 (23 inches)

Figure 16. Mean annual precipitation and recharge computed by using the Soil-Water-Balance code (Westenbroek and others, 

2010) for the Washita River alluvial aquifer, western Oklahoma, 1980–2015.

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Monthly mean precipitation, in inches

Month

0

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Monthly mean recharge, in inches

Month

A. B.

Study period (1980–2015) Study period (1980–2015)

EXPLANATION EXPLANATION

Figure 17. Monthly mean A, precipitation and B, recharge computed by using the Soil-Water-Balance code (Westenbroek and 

others, 2010) for the Washita River alluvial aquifer, western Oklahoma, 1980–2015.
ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY DEWEY COUNTY ELLIS COUNTY Foss Reservoir 100° 99°45' 99°30' 99°15' 99

35°45' 35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson an

Oklahoma Water Reso

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Washita

River

River

Washita

Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

Rush

Creek

Turkey 

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

White

Turkey

EXPLANATION

Spatially distributed mean annual recharge, in  inches, 1980–2015, from the Soil-Water-Balance code; recharge was scaled upward (increased)  for use in the numerical groundwater-flow model

0 to 1.46

1.47 to 2.552.56 to 4.024.03 to 5.75

5.76 to 8.138.14 to 13.34

13.35 to 23.30

Figure 18. Mean annual groundwater recharge computed by using the Soil-Water-Balance code (Westenbroek and others, 2010) for the alluvial aquifer, western Oklahoma, 1980–2015.
Conceptual Flow Model 31

of 3.17 in/yr, or 13 percent of precipitation, through calibration of a groundwater model. The Schipper (1983) model 

simulated the Washita River from the Texas–Oklahoma border 

to the southern boundary of Custer County, which is approximately the same downgradient extent as the study area in this 

report. The mean annual recharge rate estimated by using the 

SWB code for the Washita River alluvial aquifer for this study 

(2.5 in/yr) is lower than these published estimates of recharge 

for the Washita River alluvial aquifer. The reason recharge is 

lower than published estimates may be attributable to recharge 

from crop irrigation that was included in the published 

estimates but not included in the mean annual recharge rate 

estimated by using the SWB code. Recharge from crop irrigation (commonly referred to as irrigation return flows) likely 

infiltrates through the unsaturated zone down to the water 

table. Schipper (1983) estimated recharge from crop irrigation 

at 15 to 25 percent of pumping based on a water-budget analysis and ET estimates. Other studies have found that irrigation 

increases groundwater recharge (Roark and Healy, 1998; 

McMahon and others, 2011), and recharge rates are greater 

in irrigated cropland areas compared to natural rangeland or 

non-irrigated cropland (Scanlon and others, 2005). Annual 

recharge in irrigated cropland in Nebraska was 0.13–0.30 in/yr 

greater than annual recharge in non-irrigated cropland and was 

1.3–1.6 in/yr greater than in rangeland (Dugan and Zelt, 2000; 

McMahon and others, 2007; Stanton and others, 2010). To 

account for possible recharge from crop irrigation and to more 

closely match published recharge estimates for the Washita 

River alluvial aquifer, recharge for this aquifer for this study 

was estimated as 3.15 in/yr, or about 14 percent of precipitation, which is a 25-percent increase from the initial estimates 

from the SWB code. Estimates of recharge as a percentage of 

precipitation can vary for different periods analyzed. When 

applied across the 132-square-mile (mi2) aquifer area used for 

modeling purposes (84,366 acres) (modified from Neel and 

others, 2018), the mean annual recharge of 3.15 in/yr 

corresponds to a mean annual recharge volume of about 

22,169 acre-ft/yr, or about 56 percent of aquifer inflows in the 

conceptual water budget (table 5). Following Neel and others 

(2018), the aquifer area for modeling purposes was 132 square 

miles rather than the 110 square-mile land surface area of the 

Washita River alluvial aquifer. The aquifer area for modeling 

purposes was larger than the land-surface area of the alluvial 

aquifer in order to establish the boundary conditions representing locations in the model where water flows into or out of the 

model region.

Using the Water-Table-Fluctuation Method to 

Estimate Recharge

The water-table-fluctuation (WTF) method (Healy and 

Cook, 2002) was used to estimate recharge to the Washita 

River alluvial aquifer (fig. 19). The SWB code method estimates spatial recharge via gridded cells across an area, and the 

WTF method estimates recharge at a specific location over a 

period of time. The WTF method was used as an additional 

method to estimate recharge for this study. The WTF method 

is based on the premise that short-term (hours to 2–3 days) 

rises in continuously recorded groundwater levels in unconfined aquifers are caused by recharge arriving at the saturated 

zone following a period of precipitation. The method is best 

applied to aquifers with shallow water tables that display 

rapid groundwater-level rises and declines in response to 

precipitation. The method cannot distinguish between recharge 

from precipitation and recharge from other sources such as 

irrigation return flow or streambed seepage. Using the WTF 

method, recharge (R) was calculated as the sum of individual 

groundwater-level rises in response to precipitation:

R = Sy × Δh/Δt (3)

where

Sy is the specific yield (dimensionless),

Δh is the change in groundwater-level altitude, in 

feet, and

Δt is the change in time, in hours.

Groundwater recharge was estimated at two observation wells upgradient from Foss Reservoir: WSH01 and 

WSH02 (fig. 1). Continuous readings were collected from 

two additional observation wells, WSH04 and WSH05, but 

groundwater-level readings at these observation wells did not 

react to precipitation, indicating that the water table at those 

locations is not directly connected to landscape hydrological processes. Well screens in WSH04 and WSH05 could be 

located below a local confining unit with recharge occurring 

in an upper sand unit, or the water table could be deep enough 

that plant roots do not intersect the water table and recharge 

from rainfall events is so attenuated that groundwater-level 

changes for discrete events cannot be detected.

The WTF method for recharge uses groundwater-level 

change related to a precipitation event in shallow, unconfined 

aquifers, multiplied by the specific yield of the aquifer to 

calculate the amount of water from that precipitation event 

that became groundwater recharge (eq. 2). If the groundwater 

level was increasing or decreasing before the precipitation 

event, that pattern is extrapolated below the groundwater-level 

peak to remove the effects of these increases or decreases in 

groundwater levels. Optimally, each well site would also be 

instrumented to collect precipitation deposition so that rainfall 

events could be correlated to recharge peaks and the percentage of precipitation that becomes recharge could be estimated. 

None of the well sites in this study area were equipped with 

precipitation gages, and none of the climate stations in the area 

(fig. 1) were close enough to well sites for use in estimating 

precipitation related to recharge peaks.

The WTF method is approximate and relies on infiltration of precipitation reaching the water table within days of 

the rainfall event so that it forms a hydrograph peak. The WTF 

method also requires the groundwater level to not be affected 

by other processes such as pumping wells, surface runoff, or 
32 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

0

0.02

0.04

0.06

0.08

0.10

0.12

0 0.14

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Daily mean recharge, in feet

Depth to water, in feet below land surface

Date

A.

5/1/2015

6/1/2015

7/1/2015

8/1/2015

9/1/2015

10/21/2015

11/1/2015

12/1/2015

1/1/2016

2/1/2016

3/1/2016

4/1/2016

5/1/2016

6/1/2016

7/1/2016

8/1/2016

9/1/2016

10/1/2016

11/1/2016

12/1/2016

1/1/2017

2/1/2017

3/1/2017

4/23/2017

5/1/20176/1/2017

7/1/2017

Note: Daily mean recharge estimated by using the water-table 

fluctuation method described in Healy and Cook (2002)

–0.5

–0.4

–0.3

–0.2

–0.1

0

0.1

0.2

0.3

0.4

Mean monthly groundwater

recharge, in feet

Month

–0.5

–0.4

–0.3

–0.2

–0.1

0

0.1

0.2

0.3

0.4

B.

C.

–0.5

–0.4

–0.3

–0.2

–0.1

0

0.1

0.2

0.3

0.4

–0.5

–0.4

–0.3

–0.2

–0.1

0

0.1

0.2

0.3

0.4

Mean monthly evapotranspiration, in feet

Note: Mean monthly recharge estimated by using the water-table 

fluctuation method described in Healy and Cook (2002);

evapotranspiration method described by White (1932) 

Mean monthly evapotranspiration, in feet

Mean monthly groundwater

recharge, in feet

January

February

March

April

May

June

July

August

September

October

November

December

Figure 19. A, Daily mean groundwater recharge and depth to water at USGS observation well WSH01 (U.S. Geological Survey, 

2018b) from April 23, 2015, to March 1, 2017; B, mean monthly changes in groundwater recharge and evapotranspiration at 

observation well WSH01 during 2015–17; and C, mean monthly groundwater recharge and evapotranspiration at observation 

well WSH02 during 2015–17, Washita River alluvial aquifer, western Oklahoma.
Conceptual Flow Model 33

infiltration from surface water. The groundwater level then 

decreases only as groundwater is redistributed or removed 

from the aquifer by other processes. Thus, the aquifer must be 

unconfined, the water table must be close enough to the land 

surface so that the capillary fringe intersects the root zone, and 

the topsoil and aquifer material must be permeable enough so 

that the infiltration flow rate is greater than the rate at which 

the groundwater dissipates or flows to groundwater sinks. 

The WTF method is used to estimate the groundwater-level 

change, and this change is multiplied by the estimated specific 

yield, which increases the error. For example, observation well 

WSH01 (USGS site number 354529099565501) is an existing well registered with the OWRB (OWRB well 90854). The 

groundwater-levels were measured continuously at 30-minute 

intervals with a pressure transducer. The well is located 

approximately 480 ft south of the Washita River and approximately 3 mi east of the Texas–Oklahoma border (fig. 1). The 

period of groundwater-level records for well WSH01 is just 

over 2 years, from April 23, 2015, to March 1, 2017 (fig. 19A). 

The altitude of the land surface at well WSH01 is 2,197 ft. 

Local land use at the well WSH01 site in 2006 was classified 

as shrubland and grassland/herbaceous (Fry and others, 2011), 

and the well site is located on the valley bottom with little 

slope and silty, sandy soil. During the period of data collection, the water table was between 0.1 and 4.4 ft below land 

surface (fig. 19A).

Numerous recharge peaks were identified in April and 

May 2015, and large, but more isolated, recharge peaks 

occurred during June to August. No recharge took place in 

September 2015, but one recharge peak was identified in 

October followed by several large peaks in November and 

December.

The specific yield of the aquifer at WSH01 was not 

measured but was estimated based on the general soil characteristics from soil survey geospatial data (NRCS, 2018). The 

soil on the western half of the Washita River alluvial aquifer is 

mapped as being silty and has an available water capacity of 

0.86 in. of water per foot of soil. Converting this to a percentage results in a specific yield of 0.071. Assuming a 10-percent 

error results in a range of specific yield of 0.065–0.079. The 

NRCS soils data are only relevant to approximately the uppermost 5 ft of the soil profile, not the entire aquifer thickness. 

Given the mixture of alluvium and eroded bedrock from adjacent units at the surface, it is not unsurprising that the surficial 

specific yield of the aquifer at WSH01 was lower than the 

specific yield of 0.12 that was determined in the “Calibration 

Parameters” section of this report to best represent the 

alluvium of the majority of the aquifer. A groundwater-level 

time series graph for WSH01 (fig. 19A) shows a decrease of 

approximately 3 ft from June to September 2015, most likely 

from plant uptake and little precipitation. All 61 precipitation 

events during the period of data collection were used to calculate recharge, and many of these events lasted more than 1 day.

Mean monthly recharge was estimated for WSH01 and 

WSH02 by using the WTF method. For WSH01, recharge 

was estimated to be greatest during April and May and lowest 

during September and October (fig. 19B). For WSH02, 

recharge was estimated to be greatest during June and 

September and lowest during February and October (fig. 19C). 

ET in the shallow alluvium likely takes up the potential 

precipitation that would become recharge; therefore, when ET 

is high, recharge is likely to be low, unless the precipitation 

exceeds the plant uptake capacity. Once precipitation exceeds 

the plant uptake capacity, the precipitation is available for 

recharging the groundwater. Mean monthly ET, described in 

the “Saturated-Zone Evapotranspiration” section of this report, 

is shown on figures 19B and 19C to illustrate the relation 

between ET uptake of precipitation and groundwater recharge 

in the Washita River alluvial aquifer.

Saturated-Zone Evapotranspiration

Evapotranspiration is the process by which water is transferred to the atmosphere directly by evaporation or indirectly 

by plant transpiration. This process occurs in the saturated and 

soil-moisture (unsaturated) zones, typically in areas where 

the water table is at or near land surface, such as lakes or 

wetlands. The soil-moisture-zone component of evapotranspiration was not considered to be a part of the conceptual 

water budget because it occurs before infiltrating precipitation has become groundwater recharge. For this investigation, 

evapotranspiration by plants from the saturated zone—or 

saturated-zone evapotranspiration (ETg)—was quantified in 

the water budget.

Rates of ETg are difficult to estimate over a large area, 

but should be roughly proportional to (1) the area where the 

saturated zone intersects the plant root zone, (2) the mean 

depth to groundwater in that area during the growing season, 

and (3) the mean rate of transpiration associated with the 

assemblage of plants in that area. The area where the saturated 

zone intersects the plant root zone probably is small (compared to the Washita River alluvial aquifer area) and confined to the 73,584-acre area of active alluvium (Qal, fig. 7) 

along perennial or near-perennial streams. About 16 percent 

(11,828 acres) of the active alluvium area was classified as 

wetland (land area with frequently saturated or flooded soils) 

by the National Wetlands Inventory (U.S. Fish and Wildlife 

Service, 2018). ETg also was assumed to be proportional to 

and no greater than the Pet minus the Aet computed by using 

the Hargreaves and Samani (1985) method as described by 

Westenbroek and others (2010). This assumption resulted in 

the summed components of ETg not exceeding the Pet. ETg 

was assumed to be active for about half the year (182.5 days), 

greatest annually in wet and hot years, and greatest monthly 

in early summer (Scholl and others, 2005) when precipitation 

and temperature are above average.

By using the assumptions previously listed, groundwater 

outflow by ETg could be estimated from daily groundwaterlevel fluctuation data at wells with shallow depths to water 

according to methods of White (1932). This method estimated 

annual ETg rates by using specific yield from soil columns 
34 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

and hourly groundwater-level measurements from a continuous well. This method was applied for undisturbed salt 

grass cover in southwest Utah with a mean depth to water of 

12–24 in. Because ETg rates in the high desert of Utah are 

likely to be greater than those in Oklahoma, an annual ETg 

rate of about 12 in/yr was assumed to be appropriate for the 

Washita River alluvial aquifer, similar to the rate for the North 

Fork Red River alluvial aquifer (Smith and others, 2017). If 

about 16 percent (11,828 acres) of the active alluvium area 

(73,584 acres) had similar cover and depths to water—based 

on the National Wetlands Inventory—this rate would correspond to an annual ETg outflow of 11,828 acre-ft/yr for the 

Washita River alluvial aquifer (table 5).

Streamflow

Daily streamflow data from the Cheyenne, Hammon, 

Foss, and Clinton streamgages (fig. 1; table 2) were used to 

estimate base flow and seepage calibration targets for the 

groundwater model. The Washita River alluvial aquifer is 

also hydraulically connected to the surface water in several 

smaller tributaries, such as Barnitz and Quartermaster Creeks, 

for which streamgaging data were not available during the 

study period.

From the Texas–Oklahoma border to Foss Reservoir, 

there are no permanent flow controls on the Washita River. 

However, 69 surface-water diversions were permitted by the 

OWRB for irrigation upstream from Foss Reservoir (fig. 2). 

Streamflow downstream from Foss Dam (fig. 1) is controlled 

by releases from Foss Reservoir. Mean streamflow released 

from Foss Reservoir was approximately 41.1 ft3/s during the 

study period (Bureau of Reclamation, 2018), with greater 

releases during wet periods and a prolonged period with no 

releases during dry periods such as the hydrologic drought 

from 2011 to 2015 except for October 2013. Additionally, 

31 surface-water diversions are permitted by the OWRB 

downgradient from Foss Reservoir on tributaries of the 

Washita River.

Mean monthly streamflow measured at the Cheyenne 

and Hammon streamgages (fig. 1) is highly variable, and 

the mean daily streamflow was nearly two and a half times 

greater at the Hammon streamgage (67.1 ft3/s) than at the 

Cheyenne streamgage (25.4 ft3/s) for 1980–2015 (table 2). 

Mean daily streamflow values at the Cheyenne and Hammon 

streamgages were greater during a wet period from 1995 to 

2002 (about 36 ft3/s and 128 ft3/s, respectively) and very low 

during the hydrologic drought from 2011 to 2014 (about 3 

and 4 ft3/s respectively) (fig. 5; table 2). The greatest instantaneous streamflow recorded at the Cheyenne streamgage was 

7,050 ft3/s on May 23, 1941 (USGS, 2018b).

Mean annual streamflow measured at the Foss 

streamgage included minor flow from Oak Creek (fig. 1), 

and the mean annual streamflow for the study period was 

74.4 ft3/s, which is similar to that measured at the Hammon 

streamgage. Streamflow measured at the Clinton streamgage 

included the tributary of Turkey Creek and substantial 

streamflow from Barnitz Creek that was not continuously 

measured during the period of study. Mean annual streamflow 

measured at the Clinton streamgage for the 1980–2015 period 

was approximately 146.5 ft3/s (table 2). The Washita River 

streamflow was not continuously measured in the study area 

downstream from the Clinton streamgage.

Seepage Runs

Synoptic streamflow measurements (also known as 

seepage-run measurements) (USGS, 2018b) were collected by 

using the methods of Rantz and others (1982) during a period 

of minimal runoff on February 29 and March 1, 2016, and 

February 9, 2017. A positive difference between the inflow 

and outflow is considered seepage into the stream from an 

underlying aquifer or aquifer system and is indicative of a 

gaining stream. A negative difference between the inflow and 

outflow is considered seepage into the underlying aquifer from 

the stream and is indicative of a losing stream. Both efforts 

measured streamflow at various locations along the Washita 

River and several tributaries during times preceded by periods 

of no recent precipitation. During February and March, riparian vegetation ET is also assumed to be minimal. During the 

2016 seepage-run measurements, diversions for irrigation 

were visually observed between the Cheyenne streamgage and 

White Shield Creek (fig. 1), which potentially affects the interpretation of streamflow gains and losses between these two 

measured sites. Thus, a second seepage run was conducted 

on February 9, 2017, focusing on the Washita River upstream 

from Foss Reservoir. Streamflow measurements were augmented with streamflow data from each USGS streamgage on 

the Washita River in the study area.

Generally, streamflow in the Washita River increased 

from upstream to downstream in the areas upgradient 

and downgradient from Foss Reservoir (figs. 20 and 21). 

Downstream increases in base flow could be caused by 

increased inflows to the stream from the alluvium and terrace 

and from adjoining bedrock aquifers. Average base flow from 

22 named and 24 unnamed tributaries (20 unnamed tributaries 

downstream from site SR1) to the Washita River was estimated based on available data from nearby streamgages and 

by using estimated streamflows from StreamStats (Smith and 

Esralew, 2010).

StreamStats was used during the seepage run on 

February 9, 2017, on the Washita River at the Texas–

Oklahoma border to obtain an estimated streamflow of 

7.4 ft3/s. Streamflow at site SR1, approximately 4 river miles 

east and downstream from the Texas–Oklahoma border, was 

recorded as 11.9 ft3/s (figs. 20 and 21). Streamflow at site SR3, 

approximately 6 mi downstream from site SR1, was 17.6 ft3/s; 

however, 3.0 ft3/s of the streamflow at SR3 is from the Rush 

Creek tributary. Additionally, Turkey Creek in Roger Mills 

county and nine unnamed tributaries may contribute streamflow to the Washita River. Streamflow between site SR3 and 

the Cheyenne streamgage increased from 17.6 to 27.8 ft3/s. 
#

#

#

#

#

#

#

#

##

#

#

#

#

#

# #

East

Barnitz

Creek

West

Barnitz

Creek

Barnitz Cree k

SR1

(11.9)

4.5

SR2

(3)

0

SR3

(17.6)

6.2 SR4

(1)

0

SR6

(4)

0

SR5

(31.4)

5

SR8

(1)

0

SR7

(33.3)

5.9

SR9

(0.6)

0

SR10

(33.6)

4.6

SR11

(0.5)

0

SR12

(6.86)

0

SR1

(11.

0

07316500

(27.8)

9.4

07324200

(42.2)

12.7

07324300

(0)

0

07324400

(6.7)

0

07

(

EXPLANATION

Base-flow gain or loss, February 2017,  in cubic feet per second per mile

–0.75–0.75 to 0.0

0.0 to 0.50.5 to 2.02.0 to 3.0

Washita River alluvial aquifer

# Base-flow estimate from USGS streamgage (top number is station number, 

 number in parentheses is base flow at the streamgage, bottom number is  base flow at the streamgage with tributary flows subtracted; station 07324300  is stage-only streamgage; table 1)

# Washita River base-flow measurement (top number is seepage run [SR] number, 

 number in parentheses is base flow at the streamgage, bottom number is base  flow at the streamgage with tributary flows subtracted; table 1)

07324400

(6.7)

0

SR12

(6.86)

0

Streamflow estimated at the Texas-Oklahoma border as 7.4 cubic feet per second

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

TEXAS

OKLAHOMA

100° 99°45' 99°30' 99°15' 

35°45'35°30'

FOSS

DAM

Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

River

Rush

Creek

Turkey 

Creek

Spring

Creek

Wild

Horse

Creek

Creek HayDry

Branch

Quartermaster

Creek

North

Branch

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek Big

Kiowa

Creek

Creek WhiteShield

Turkey

Washita

Foss

Reservoir

Washita

River

River

Washita

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Figure 20. Streamflow measurements and gaining and losing reaches from calculated base-flow gain or loss from the 2017 seepage runWashita River alluvial aquifer, western Oklahoma.
36 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Some of this increase is probably from streamflow from four 

named tributaries (Croton, Brokenleg, Plum, and Sergeant 

Major Creeks) and three unnamed tributaries located between 

SR3 and the Cheyenne streamgage. Streamflow increased 

from 27.8 to 31.4 ft3/s between the Cheyenne streamgage and 

site SR6. This streamflow includes streamflow measured at the 

Dead Warrior Creek (1.0 ft3/s) and Sandstone Creek (4.0 ft3/s) 

tributaries. Additionally, three named tributaries (Wild Horse, 

Caffey, and Cofer Creeks) and seven unnamed tributaries may contribute streamflow to the Washita River. After 

accounting for measured or estimated streamflow from these 

tributaries, cumulative streamflow decreased between the 

Cheyenne streamgage and SR6. Streamflow increased from 

31.4 to 33.3 ft3/s between sites SR6 and SR7. This increase 

includes streamflow measured at Big Kiowa Creek (0.1 ft3/s). 

Additionally, one unnamed tributary may contribute streamflow to the Washita River in this area. Streamflow increased 

from 33.3 to 33.6 ft3/s between sites SR7 and SR10. This 

increase includes streamflow measured at White Shield Creek 

(0.6 ft3/s). Additionally, Ninemile Creek and two unnamed 

tributaries, located between SR7 and SR10, may contribute 

streamflow to the Washita River. After accounting for measured or estimated streamflow from the White Shield and 

Ninemile Creeks and the two unnamed tributaries, estimated 

base flow was decreased between SR7 and SR10. Streamflow 

increased from 33.6 to 42.2 ft3/s between sites SR10 and 

the Hammon streamgage. This increase includes streamflow 

measured at Quartermaster Creek (5.9 ft3/s). Additionally, one 

unnamed tributary may contribute streamflow to the Washita 

River between SR10 and the Hammon streamgage.

During the 2016 seepage run, Foss Reservoir was 

not releasing streamflow into the Washita River, and the 

streamgage downstream from the Foss Dam streamgage 

(07324300) recorded streamflow of 6.7 ft3/s (fig. 20). This 

streamflow amount represents the cumulative streamflow 

along Oak Creek and the short Washita River segment between 

Foss Dam and the streamgage, a channel length of approximately 1 mi. Between the Foss and Clinton streamgages, 

streamflow in the Washita River increased 27.2 ft3/s, from 

6.7 to 33.9 ft3/s. After subtracting the measured 6.86 ft3/s from 

Turkey Creek and 11.1 ft3/s from Barnitz Creek (fig. 20), the 

total base flow was approximately 15.5 ft3/s along 29.4 river 

miles (between 07324300 and 07325000 streamgages), or 

approximately 0.5 ft3/s per mi. Base-flow amounts per mile for 

Turkey, Beaver, and Turtle Creeks were estimated, although 

the channel lengths contributing to the base flows are approximate. Turkey Creek streamflow was measured about 2 mi 

upstream from the confluence with the Washita River, which is 

1.2 ft3/s per mi over approximately 6 mi of channel. A streamflow of 5.8 ft3/s was measured in Beaver Creek about 3 mi 

upstream from the confluence with the Washita River.

Base Flow

Base flow is the component of streamflow supplied by 

the discharge of groundwater to streams (Barlow and Leake, 

2012) that was quantified over the study period 1980–2015 for 

the study-area streamgages (tables 1 and 2) by using a baseflow index (BFI) computer code to identify the base-flow component of streamflow (Wahl and Wahl, 1995). The BFI code is 

integrated into the USGS Groundwater Toolbox (Barlow and 

SR1

SR3

07316500

SR6 SR7

SR10

SR11

0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50 60

Streamflow, in cubic feet per second

River miles Texas/Oklahoma 

border

67

EXPLANATION

Tributary contributions

Streamflow

Cumulative streamflow

 gain or loss

Figure 21. Total and cumulative streamflow gain or loss (measured February 9, 2017) for the Washita River and 

includes tributary contributions to the Washita River. [See table 1 and fig. 20; SR, seepage run]
Conceptual Flow Model 37

others, 2015). The BFI code is used to calculate the minimum 

streamflow for user-specified n-day moving increments in 

order to compare this streamflow to adjacent minimums to 

determine turning points on a base-flow hydrograph. The ratio 

of base flow to the total streamflow is the base-flow index. 

A base-flow index of 1 indicates that all streamflow is from 

groundwater, and a base-flow index of 0 indicates that none of 

the streamflow is from groundwater.

Several releases from Foss Reservoir to the Washita River 

were recorded during the study period. Base-flow computation 

at regulated streamgages can be complicated by releases from 

large reservoirs and floodwater-retarding structures because 

these releases (and the subsequent bank storage releases associated with these releases) are usually indistinguishable from 

natural base flows. Thus, the BFI code may overestimate base 

flows at regulated streamgages on the Washita River (fig. 1), 

and long-term patterns in base flows may be masked by reservoir releases that are indistinguishable from base flows.

Annual stream seepage during 1980–2015 from the 

Washita River alluvial aquifer into the reach of the Washita 

River upstream from Foss Reservoir was estimated as 

4,676 acre-ft/yr (table 5). This stream seepage estimate was 

based on (1) the difference between base flow at the river’s 

confluence with Foss Reservoir and base flow at the Texas–

Oklahoma border, (2) estimated base flow in tributaries to 

the Washita River, and (3) surface-water diversions. Flow 

in the Washita River at the confluence of Foss Reservoir 

(29,943 acre-ft/yr) was used to determine the flow at the 

Hammon streamgage by adjusting upward by 8 percent for 

the 3.9-mi distance downstream to Foss Reservoir. Flow at the 

Texas–Oklahoma border (5,334 acre-ft/yr) was determined 

as 50 percent of flow at the Cheyenne streamgage based on 

seepage-run data discussed in the “Seepage Runs” section of 

this report. Tributary stream seepage upgradient from Foss 

Reservoir was estimated for 16 named tributaries (fig. 1) for 

a total of 16,072 acre-ft/yr and 12 unnamed tributaries for a 

total of 4,344 acre-ft/yr based on seepage-run data (fig. 20). 

Surface-water diversions totaled 919 acre-ft/yr and are discussed in the “Water Use” section of the report.

For the Washita River downstream from Foss Reservoir, 

the mean annual stream seepage was 17,320 acre-ft/yr 

(table 5). This mean annual stream seepage was based on 

(1) the difference between the base flow at the Custer County 

border and the base flow at the Foss streamgage, (2) releases 

from Foss Reservoir, (3) estimated base flow in tributaries 

to the Washita River, and (4) surface-water diversions. The 

flow at the Custer County border (66,658 acre-ft/yr) was 

used to determine the flow at the Clinton streamgage, adjusting upward by 10 percent for the distance downstream to the 

Custer County boundary. Mean annual stream seepage at the 

Foss streamgage (34,015 acre-ft/yr) was determined as the 

sum of the base flow at this streamgage and releases from Foss 

Reservoir. Tributary stream seepage downgradient from Foss 

Reservoir was estimated for six named tributaries (fig. 1) for 

a total of 13,031 acre-ft/yr and eight unnamed tributaries for 

a total of 2,896 acre-ft/yr based on seepage-run data (fig. 20). 

Surface-water diversions totaled 604 acre-ft/yr and are discussed in the “Water Use” section of the report.

Lateral Groundwater Flows

Estimates of lateral groundwater flow from the Ogallala 

Formation to the Washita River alluvial aquifer are not available in published literature; however, based on the configuration of the potentiometric-surface contours from this investigation (fig. 12) and available groundwater-level measurements 

(USGS, 2018b), some lateral groundwater flow from the 

Ogallala Formation to the Washita River alluvial aquifer 

may occur. For this study, lateral flow was not estimated in 

this area (lateral flow equals zero) because (1) additional 

groundwater-level observations in the Ogallala Formation are 

needed, (2) the Ogallala Formation is likely drained by a few 

tributaries to the Washita River upstream from Wild Horse 

Creek (figs. 1 and 7) that are estimated as a part of streamflow 

in the conceptual flow model, and (3) lateral flow between the 

Washita River alluvial aquifer and the Ogallala Formation may 

be impeded by the presence of the intervening Cloud Chief 

Formation and Doxey Shale, which predominantly contain 

shale and siltstone (fig. 7).

West of the Rush Springs aquifer extent (Ellis, 2018) and 

east of the Ogallala Formation, the surrounding Cloud Chief 

Formation and Doxey Shale bedrock units are predominantly 

composed of shale and siltstone (figs. 7 and 8) (Schipper, 

1983). Concentrations of calcium, magnesium, and sulfate 

in the groundwater in the Cloud Chief Formation come from 

the dissolution of gypsum, dolomite, and calcite (Becker and 

Runkle, 1998). The calcium-magnesium-sulfate-chloridetype water in the Washita River alluvial aquifer (Kent and 

others, 1984) west of the Rush Springs aquifer is most likely 

caused by the inflow of groundwater from the Cloud Chief 

Formation, which is adjacent to the Washita River alluvial 

aquifer. However, because of the fine-grained texture of the 

Cloud Chief Formation and Doxey Shale, the bedrock in these 

units were regarded as impermeable, as done in other investigations (Leonard and others, 1958; Schipper, 1983; Kent and 

others, 1984).

The Washita River alluvial aquifer may drain groundwater in the Rush Springs aquifer (Rush Springs Formation, 

fig. 7), as indicated by potentiometric-surface contours for 

the Rush Springs aquifer that are parallel to the Washita 

River alluvial aquifer, or perpendicular to the direction of 

lateral groundwater flow, in figure 15 of Neel and others 

(2018). Additionally, groundwater-flow simulations of the 

Rush Springs aquifer resulted in a mean annual seepage 

of about 151,000 acre-ft/yr from the Rush Springs aquifer to the Washita River in the Rush Springs aquifer model 

domain—accounting for just 46 percent of total simulated 

seepage to all streams (Ellis, 2018, fig. 38). Much of this 

seepage occurs downstream from Foss Reservoir between the 

Clinton streamgage and the Washita River at Carnegie, Okla., 
38 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

streamgage (07325500) (located east of the study area; not 

shown on map); however, the remaining seepage between Foss 

Reservoir and the Clinton streamgage indicates that lateral 

flow in this area may be a substantial source of inflow to the 

Washita River alluvial aquifer. The seepage-run data from 

2017 indicates an increase in streamflow of approximately 

8.9 ft3/s between site SR7 and the Hammon streamgage—an 

area that approximately corresponds with the areal extent of 

the Rush Springs aquifer where it underlies (or lies adjacent 

to) the Washita River alluvial aquifer upgradient from Foss 

Reservoir. However, most of this increase in streamflow is 

estimated to originate from the four named (Ninemile, White 

Shield, Quartermaster, and Wild Horse) and two unnamed 

creeks between SR7 and the Hammon streamgage. Thus, 

only minimal lateral flow likely occurs from the Rush Springs 

aquifer to the Washita River alluvial aquifer upstream from 

Foss Reservoir.

Lakebed Seepage

Streamflow from the Washita River is the primary source 

of surface-water inflow to Foss Reservoir (fig. 1). The active 

conservation pool (normal pool) storage of Foss Reservoir 

is 168,732 acre-ft (Bureau of Reclamation, 2018), and the 

reservoir has mean annual permitted surface-water withdrawals of about 18,000 acre-ft/yr (OWRB, 2012b). The active 

conservation pool stage is the maximum altitude of a reservoir’s conservation pool (the usable stored water above the 

dead-pool stage). The dead-pool stage is the altitude of the 

water surface below which the water stored in a reservoir will 

not drain by gravity through the outlet of the dam; water in the 

dead pool is not part of the active conservation pool (Water 

Data for Texas, 2020).

Flow to and from Foss Reservoir and the Washita River 

alluvial aquifer (termed “lakebed seepage”) varies seasonally 

with changes in precipitation and water use. Stage in Foss 

Reservoir is generally highest in the early summer after spring 

rainfall and lowest in the fall after the cumulative effects of 

increased evaporation and permitted surface-water withdrawals during summer months (Bureau of Reclamation, 2018). 

Thus, lakebed seepage may occur as an inflow to or an outflow 

from the Washita River alluvial aquifer during various times of 

the year, but it is likely a small amount in terms of an aquifer 

budget and was not quantified for this study.

Conceptual Water Budget

A conceptual water budget for the Washita River alluvial aquifer (table 5) was developed to quantify the amount 

of water that moves between each boundary of the aquifer 

and to guide the construction and calibration of the numerical groundwater-flow model. This water budget provides a 

generalized estimate of mean annual inflows and outflows 

for the Washita River alluvial aquifer during the study period 

1980–2015. Water that flows to the Washita River alluvial 

aquifer from the study area streams is considered an aquifer inflow, whereas the reverse constitutes an outflow from 

the aquifer.

Approximately 56 percent of inflows to the Washita River 

alluvial aquifer occurred as recharge during the study period, 

and net lateral flow was estimated to be 44 percent of the 

aquifer inflow (table 5). Net lakebed seepage at Foss Reservoir 

is likely a relatively small component of the water budget (less 

than 1 percent); thus, this term was not quantified in table 5. 

The largest aquifer outflow (56 percent) was net stream seepage. The remaining aquifer outflows were ETg (30 percent) 

and groundwater use (14 percent).

Simulation of Groundwater Flow

A groundwater model of the Washita River alluvial aquifer was constructed by using MODFLOW-2005 (Harbaugh, 

2005) with the Newton solver (MODFLOW-NWT; Niswonger 

and others, 2011). MODFLOW-NWT uses finite-difference 

methods to solve the three-dimensional groundwater-flow 

equation and includes more advanced capabilities to solve 

nonlinear simulations compared to MODFLOW-2005. In 

the modular design of MODFLOW, each hydrologic boundary, such as stream seepage, recharge, or groundwater use, is 

included as a package that, when activated, adds new inflow 

and outflow terms to the groundwater-flow equation being 

solved. Model space is discretized into orthogonal cells, and 

the cell size is the finest resolution at which spatially varying 

properties may be represented and varied. Model time is discretized into time steps within stress periods. The stress period 

length is the finest resolution at which temporally varying 

inflows and outflows may be represented and varied, and the 

time step length is the finest length of time for which model 

outputs may be written. The groundwater-model inputs and 

outputs are available in Ellis and others (2020).

Spatial and Temporal Discretization

The Washita River alluvial aquifer groundwater-model 

grid was spatially discretized into 384 rows and 927 columns containing 350-ft cells without rotation. Two layers 

and 30,000 active cells were used to represent geologic units 

in the study area, and the model area, shown in figure 22, 

was defined by the hydrologic boundaries discussed in the 

“Hydrologic Boundaries” section of this report. The top layer 

(layer 1) represented the undifferentiated alluvium and terrace 

deposits of Quaternary age with variable thickness determined 

from the hydrogeologic framework, and the bottom layer 

(layer 2) represented the bedrock of Permian age which was 

given a uniform nominal thickness of 100 ft. Areas of the 

terrace deposits outside of the Washita River alluvial aquifer 

extent shown on figure 7 were determined to be unsaturated 

based on an analysis of available well logs and were not 

included in the model extent. All model layers were assigned 
0

07324400

07324200

07316500

07316500

Ar

Cl

Foss

Hammon

Leedey

Cheyenne

Strong

City

U.S. Geological Survey streamgage and station number (table 1)

Wells

Foss Reservoir simulated by using Lake package (Merritt and Konikow, 2000)Extent of streams used for streamflow routing (Streamflow-Routing package, v. 2) (Niswonger and Prudic, 2005)Saturated-zone evapotranspiration simulated by using Evapotranspiration package (Harbaugh, 2005)General-head boundary for simulating flow into and out of the Washita River alluvial aquiferOther active model area and recharge (The edge of the active model area is a no-flow boundary unless  specified otherwise)

EXPLANATION

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Foss

Reservoir

100° 99°45' 99°30' 99°15' 

35°45'35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Figure 22. Active model area and boundary conditions for the numerical groundwater-flow model of the Washita River alluvial aquifer, wOklahoma.
40 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

as a convertible-type layer, whereby each layer can convert 

between confined and unconfined conditions. The model grid 

was oriented approximately parallel to the hydraulic gradient of the aquifer, and the model active area was expanded in 

some areas to ensure that each active cell was in connection 

with at least one other active cell. Conceptually, the aquifer 

could be divided into two models, one each for the areas 

upgradient and downgradient from Foss Reservoir; however, 

the groundwater model described in this report included both 

areas in a single model.

The groundwater-simulation period was temporally 

discretized into 433 monthly transient stress periods with one 

time step each, representing the period of January 1980 to 

December 2015. The monthly transient stress periods were 

used to capture seasonally variable processes such as recharge, 

ETg, and groundwater use. A lack of sufficient water data prior 

to the mid-1970s precluded the establishment of predevelopment groundwater levels and flow conditions; therefore, an 

initial 365-day steady-state stress period was configured to 

represent mean annual inflows and outflows from the Washita 

River alluvial aquifer for the study period.

Hydrologic Boundaries

Hydrologic boundaries in the groundwater model represent the locations where the inflow or outflow of water may 

occur (fig. 22) and include specified-flux and head-dependent 

boundaries. For a specified-flux boundary, a user-specified 

flow rate governs groundwater exchange at that boundary. 

Simulated specified-flux boundaries include groundwater use 

and recharge, as well as the no-flow boundary established at 

the bottom of layer 2. A no-flow boundary was also established at some locations in each layer where adjoining hydrogeologic units do not yield water to the Washita River alluvial 

aquifer, mostly in areas west of the Rush Springs aquifer 

boundary (fig. 13 in Ellis, 2018) (fig. 22). A head-dependent 

boundary simulates flow based on the difference between a 

user-specified groundwater level and the groundwater level 

in model cells. Simulated head-dependent boundaries include 

ETg, lateral groundwater flow, seeps and springs, stream seepage, and lakebed seepage at Foss Reservoir.

Recharge

Areally distributed recharge from the SWB code 

was simulated as a specified-flux boundary by using the 

Recharge package for MODFLOW groundwater-flow models 

(Harbaugh, 2005). The steady-state simulation used a mean 

recharge value calculated for the simulation period, and the 

transient simulation used recharge values calculated for each 

month of the simulation period. Temporal adjustment of 

recharge occurred during the calibration phase to obtain better 

matches between simulated and observed calibration targets 

for 172 monthly stress periods where recharge occurred. 

Recharge was applied to the highest active cell, or layer 1 in 

the model. Where the Washita River alluvial aquifer is missing 

and bedrock is exposed, no recharge was assumed to occur.

Lateral Groundwater Flow

Possible lateral groundwater flows between the Washita 

River alluvial aquifer and the Rush Springs aquifer were simulated as head-dependent boundaries by using the General-Head 

Boundary (GHB) package for MODFLOW groundwater-flow 

models (Harbaugh, 2005) (fig. 22). The GHB package uses 

a linear relation between flux and the water-table altitude (or 

water head), and a user-specified reference groundwater level 

and hydraulic conductivity simulated for the aquifer. For the 

purpose of this report, the term “conductance” is defined as 

the product of hydraulic conductivity of the model cell and 

the cross-sectional area perpendicular to flow, divided by the 

distance between the GHB cell and the model cell. When 

the simulated groundwater level is lower than the reference 

groundwater level, water flows into the groundwater model. 

When the simulated groundwater level is higher than the 

reference groundwater level, water flows out of the groundwater model.

Few groundwater-level observations are available in the 

Rush Springs aquifer adjacent to the Washita River alluvial aquifer (fig. 25 in Ellis, 2018). Therefore, the reference 

groundwater level for each GHB cell simulating flow between 

the Washita River alluvial aquifer and the Rush Springs aquifer was determined from the mean of the nearest simulated 

groundwater levels from Ellis (2018) during the simulation 

period for the Washita River alluvial aquifer.

Streams

The major streams and associated tributaries in the study 

area (fig. 1) were simulated as a head-dependent boundary 

by using the Streamflow-Routing package, version 2 (SFR2) 

designed for use with MODFLOW groundwater-flow models 

(Niswonger and Prudic, 2005). The SFR2 exchanges flow 

between the aquifer and the stream according to Darcy’s Law; 

stream seepage is the product of the streambed conductance 

and the difference between the groundwater level and the 

stream stage. The streambed conductance is the product of 

the hydraulic conductivity of the streambed sediments and the 

area of the stream channel divided by the streambed thickness. 

Stream stage is calculated by using Manning’s equation, in 

which stream stage is a function of flow based on the geometry of the stream channel. Where groundwater levels are lower 

than stream stage, inflow to the aquifer from the stream occurs 

(termed “seepage from streams”). Where groundwater levels 

are higher than stream stage, outflow from the aquifer to the 

stream occurs at a specified streambed conductance rate from 

the aquifer (termed “seepage to streams”).
Simulation of Groundwater Flow 41

Streamflows are calculated for each part of the stream, 

known as reaches, and they are contained in a model cell until 

the end of a segment, or group of reaches with uniform or 

linear hydraulic properties, is reached during each time step. 

A stream-water balance is used to compute the amount of 

water available in each stream reach and the amount of water 

exchanged between the stream and the aquifer in groundwaterflow simulations. Calculation of water exchanges between the 

stream and aquifer repeats downstream in this manner until 

water is routed out of the model active area. Inflows (Qin) to 

each stream reach are calculated by using the following equation (all units are in acre-feet per day):

∑ Qin = Qsp + Qtr + Qro + Qpr − Qgwi (4)

where

Qsp is the specified inflow at the beginning of the 

first reach of a segment,

Qtr is the sum of tributary inflow,

Qro is direct overland runoff,

Qpr is direct precipitation, and

Qgwi is seepage to streams.

Specified inflows (Qsp) at the beginning of each stream 

reach include the estimated base flows at the model boundary 

(Texas–Oklahoma border) from upstream as well as releases 

from Foss Reservoir (Bureau of Reclamation, 2018) to the 

first downstream segment. Tributary inflows (Qtr) are based 

on flow routed from upstream segments, which include the 

small tributaries associated with the alluvium and terrace 

of the Washita River. Tributary inflow rates were set for the 

following tributaries: Rush and Croton Creeks (3.0 ft3/s), 

Sergeant Major Creek (2.0 ft3/s), Dead Indian Creek (1.0 ft3/s), 

Sandstone Creek (4.0 ft3/s), Big Kiowa Creek (0.1 ft3/s), and 

White Shield and Quartermaster Creeks (0.5 ft3/s) (fig. 1). All 

other tributaries at the model boundary were either assumed 

to be intermittent or ephemeral, with no specified inflows. 

Tributaries originating in the model active area were assumed 

to drain the Washita River alluvial aquifer and were simulated 

primarily to route groundwater flow to the Washita River. The 

model is simulated under base-flow conditions; therefore, 

direct overland runoff (Qro) and precipitation (Qpr) were not 

applied to the stream channel. Groundwater discharge from the 

aquifer simulated by using MODFLOW is a negative value; 

thus, the seepage to streams or groundwater inflow (Qgwi) is 

subtracted from the other inflow components. Outflows (Qout) 

from each stream reach are calculated in the following equation (all units are in acre-feet per day):

∑ Qout = Qstr + Qdiv + Qet + Qgwo (5)

where

Qstr is streamflow out of a reach,

Qdiv is simulated diversions,

Qet is evapotranspiration, and

Qgwo is seepage from streams.

Streamflow out of each reach (Qstr) was routed downstream in all areas except for the stream segments directly 

above Foss Reservoir, where streamflow was routed into this 

reservoir, and stream segments located at the boundary of the 

model. During the simulation period, the 69 permitted surfacewater diversions were grouped into 27 simulated diversions 

(Qdiv). Diversions can be simulated only from the last reach in 

any segment; thus, this location may differ somewhat from the 

actual diversion location. The discrepancies between the actual 

and simulated diversion locations were not substantial, however, and the diversion rates represented only a small percentage of flow in the SFR2 cells. Surface-water diversions located 

on unnamed streams—which were considered intermittent or 

ephemeral streams, and thus supplied from surface runoff—

were not simulated in the groundwater model. No evaporative processes (Qet) were applied by using the SFR2 package, 

although ETg is simulated by using the Evapotranspiration 

package (Harbaugh, 2005) for alluvium cells that include 

stream segments.

The extent of the streams used for streamflow routing 

(fig. 22) was modified from the National Hydrography Dataset 

Plus (NHDPlus; Horizon Systems Corporation, 2015), a 

1:100,000-scale geospatial dataset of surface-water features. 

Streams having a stream order (Strahler, 1952) of one—

defined as headwater streams that are dominated by runoff—

were excluded from the stream extent. Differences in stream 

channel location occurred between the DEM (USGS, 2018a) 

and the NHDPlus streamline because of the averaging of 

DEM cells and migration of the stream channel in the alluvial 

valleys over time. To ensure correct surface-water routing in 

the stream, the stream location was adjusted to ensure that the 

stream channel altitude decreased in a downstream direction 

in each segment. For segments where the streambed slope was 

zero, either the upstream altitude was slightly increased, or the 

downstream altitude was slightly decreased.

The SFR2 streambed thickness was set to 2 ft, and a 

rectangular channel was used to define the stream geometry 

in all segments of the model. The streambed altitude was 

derived from a 10-meter (33-ft) DEM, and stream segments 

were incised between 1 and 5 ft in relation to the DEM altitude. Stream channel widths were estimated from 2013 aerial 

photographs (NRCS, 2018) and ranged from 7 to 55 ft for the 

Washita River, and from 5 to 40 ft for the tributaries. Although 

the streambed conductivity varies based on location and discharge rates, the streambed conductivity was set at 5 feet per 

day (ft/d) based on Ellis and others (2017) and Ellis (2018).

Reservoir

Foss Reservoir was simulated as a head-dependent 

boundary by using the Lake package for MODFLOW 

groundwater-flow models (Merritt and Konikow, 2000; 

Niswonger and Prudic, 2005). Lake package cells exchange 

water with adjacent and underlying active model cells based 

on the lakebed leakance and simulated groundwater levels for 

the reservoir and surrounding active model cells. The Lake 
42 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

package computes a water budget independent of MODFLOW 

during each time step for the simulated lake, in units of cubic 

feet and days, but presented in this report in acre-feet and days 

or years, described as

h h t p e rnf w sp Q Q

A l

n ln si so

s

  1        (6)

where

h h l

n ln  1 are lake (reservoir) stage from the current and 

previous time steps, respectively, in feet;

∆t is the time step length, in days;

p is the rate of precipitation applied to the lake, 

in cubic feet per day;

e is the rate of evaporation from the lake, in 

cubic feet per day;

rnf is the rate of surface runoff to the lake, in 

cubic feet per day;

w is the rate of water withdrawals from the lake, 

in cubic feet per day;

sp is the net rate of lakebed seepage between the 

lake (reservoir) and the aquifer, in cubic 

feet per day;

Qsi is the rate of stream inflow to the lake, in 

acre-feet per day;

Qso is the rate of stream outflow from the lake, in 

acre-feet per day; and

As is the surface area of the lake, in square feet.

Foss Reservoir bathymetry and stage-storage relation 

data were digitized from a 2007 sedimentation survey (Ferrari, 

2011) and were used by the Lake package to determine 

reservoir volume and surface area for a given stage (fig. 23). 

Only minor differences between the volume and area relation from the sedimentation study and the relation used in the 

Lake package occurred; thus, the simulated curves are not 

shown in figure 23. Foss Reservoir was simulated by using 

2,216 cells in layer 1; those cells exchange water laterally with 

other cells in layer 1 and vertically with cells in layer 2 that 

are directly under the lakebed. These 2,216 cells correspond 

to a surface area of 6,232 acres (As), which is smaller than the 

active conservation pool surface area of 6,801 acres (Bureau 

of Reclamation, 2018), caused by the discretization caused by 

using square cells. The rate of lakebed seepage (sp)—or the 

quotient of the hydraulic conductivity and thickness between 

the aquifer and lake—was set at 0.5 day−1, similar to the rate 

used in previous models near the study area (Ellis, 2018). This 

leakance rate governs the lakebed seepage between the aquifer 

and simulated reservoir.

The rates of precipitation (p), evaporation (e), and withdrawals (w; which include permitted use and flood-control 

releases) during the simulation period were obtained from 

the Bureau of Reclamation (2018). The mean annual precipitation at Foss Reservoir for the simulation period was 

27.4 in/yr, estimated at Bureau of Reclamation climate stations in the reservoir area. The mean annual precipitation, 

when applied over the area of the Lake package cells, was 

about 14,199 acre-ft/yr. The mean annual evaporation for the 

simulation period was 74.0 in/yr, measured at an evaporation 

pan (Bureau of Reclamation, 2018). The mean annual evaporation, when applied over the area of the Lake package cells, 

was about 26,825 acre-ft/yr. Mean annual withdrawals (w) 

during the simulation period totaled 35,718 acre-ft/yr 

(Bureau of Reclamation, 2018), including permitted use of 

0

4,000

8,000

12,000

16,000

20,000

24,000

0

150,000

300,000

450,000

600,000

750,000

900,000

1,575 1,585 1,595 1,605 1,615 1,625 1,635 1,645 1,655 1,665 1,675 1,685

Reservoir volume, in acre-feet 

Reservoir surface area, in acres

Reservoir stage, in feet above National Geodetic Vertical Datum of 1929

Figure 23. Volume, stage, and surface area for Foss Reservoir in western Oklahoma.
Simulation of Groundwater Flow 43

5,974 acre-ft/yr and releases of 29,744 acre-ft/yr. Some estimated releases were greater than the flow recorded at the Foss 

streamgage (fig. 1; table 1) about 1 mi downstream from the 

reservoir; thus, the reported releases were reduced to the flow 

recorded at this streamgage during these months. Releases 

from Foss Reservoir may occur when the reservoir stage is 

at the top of the active conservation pool (1,642 ft above the 

National Geodetic Vertical Datum of 1929 [NGVD 29]).

Surface runoff (rnf) was estimated as 20,831 acre-ft/yr 

and included BFI code-estimated runoff and overland flows 

entering Foss Reservoir that were not captured by the BFI 

code method (streamflow minus BFI baseflow equals runoff). The BFI code-estimated runoff was calculated by using 

streamflow data from the Hammon streamgage (fig. 1; 

table 2). Stream inflow rates (Qsi) to Foss Reservoir were 

from SFR2 stream segments representing the Washita River 

and from three tributaries that did not have specified inflows. 

Mean annual surface-water inflows to Foss Reservoir during 

the simulation period were estimated at 27,725 acre-ft between 

1980 and 2015. Because the reservoir is managed, releases 

are passed to stream segments downstream from the reservoir; 

therefore, the stream outflow term (Qso) is zero.

Saturated-Zone Evapotranspiration

ETg was simulated as a head-dependent boundary 

by using the Evapotranspiration package for MODFLOW 

groundwater-flow models (Harbaugh, 2005). In this package, saturated-zone evapotranspiration decreases linearly 

with decreases in the simulated groundwater level, and no 

saturated-zone evapotranspiration occurs when the simulated 

groundwater level is below a user-specified root-zone depth. 

The root-zone depth for the groundwater model was set equal 

to the SWB code root-zone depth for each land-cover type. 

Saturated-zone evapotranspiration is unlikely to occur outside 

of the alluvium because depths to groundwater in the terrace 

commonly exceed 15 ft; therefore, the Evapotranspiration 

package was limited to the saturated-zone evapotranspiration 

area defined by wetlands (U.S. Fish and Wildlife Service, 

2018), which are included in the layer 1 alluvium and terrace.

Saturated-zone evapotranspiration rates in the groundwater model were assumed to be proportional to the difference 

between Pet and Aet computed by using the SWB code. The 

variable Pet was calculated by using the method in Hargreaves 

and Samani (1985) and represents the maximum rate at which 

groundwater could be evapotranspired with unlimited soilmoisture availability. The SWB code computes the change in 

soil moisture whereby Pet is subtracted from daily precipitation. If the resulting value is positive, Aet equals Pet. If the 

resulting value is negative, Aet is limited to the change in soil 

moisture and is less than Pet. Because the SWB code computes 

soil-moisture-zone evapotranspiration without regard to the 

location of groundwater levels in relation to land surface, the 

difference between Pet and Aet can be used to approximate 

saturated-zone evapotranspiration in the groundwater model.

Groundwater Use

Well withdrawals were simulated as a specified-flux 

boundary by using the Well package for MODFLOW 

groundwater-flow models (Harbaugh, 2005). Annual reported 

groundwater use for each permit was divided equally among 

each of the wells attached to a permit (figs. 6 and 15). These 

annual well withdrawals were then distributed into monthly 

well withdrawals by using monthly demand distributions 

(fig. 24) from the Oklahoma Comprehensive Water Plan 

(OWRB, 2012b) and spatially discretized into the model 

cells. Annual irrigation well withdrawals were multiplied by 

the monthly irrigation demand (as a percentage of annual 

groundwater use), and annual public-supply well withdrawals were multiplied by the monthly public-supply demand. 

Annual well withdrawals for other purposes were distributed 

evenly to all months of the year. Domestic withdrawals, which 

are not regulated or reported by the OWRB, were not simulated; these withdrawals are likely a minor component of total 

withdrawals.

Groups of wells attached to a single permit were not 

allowed to exceed the permitted annual withdrawal amount. 

Reported annual well withdrawals for 33 irrigation wells 

(21 percent of all simulated wells) were greater than 645 acreft/yr (400 gal/min), but were reduced to 645 acre-ft/yr to avoid 

the simulation of unrealistic pumping rates. Steady-state well 

withdrawals were determined as the mean of withdrawals during the simulation period.

Model Calibration

Model calibration is the process of systematically adjusting initial model input values to improve the fit between 

model-simulated outputs and observed or estimated data 

(calibration targets). During model calibration, the inputs to 

be adjusted are updated to new values that reduce the discrepancy, or residual, between the observed and simulated data. 

Calibration outcomes were evaluated based on the reduction 

of this residual and the fit of the calibrated groundwater-model 

water-budget components to those components of the conceptual water budget. The calibration process for the Washita 

River alluvial aquifer model included (1) manual adjustment 

of model inputs by trial and error, followed by (2) automated 

adjustment of model inputs (parameters) by using the nonlinear regression code PEST++ (Welter and others, 2015). 
44 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

The PEST++ code uses the Gauss-Marquardt-Levenberg algorithm to adjust user-specified parameters to minimize a sum 

of squared weighted residuals, or objective function (table 7). 

The objective function (Φ) is expressed as

i

n

i i i s o

1

2

(7)

where

n is the number of observations,

ωi is the observation weight,

si is the simulated value, and

oi is the observed or estimated value.

PEST++ automates calibration by running 

the model as many times as needed to determine 

the best parameter values while automatically 

updating the parameter values during each step 

of the process. This iterative approach allows 

for the optimal values of many parameters to be 

estimated together with greater speed than that of 

a traditional manual calibration approach. Prior 

to automated calibration, the calibration targets 

were weighted to account for error in each type of 

observation.

The automated calibration approach concurrently applied subspace regularization techniques 

by using singular value decomposition (SVD; 

Tonkin and Doherty, 2005) in conjunction with 

singular value decomposition-assist (SVDA; 

Tonkin and Doherty, 2005) to reduce automated 

calibration run time and ensure calibration stability. SVD was implemented with PEST++ to 

identify combinations of parameters that are most 

responsive to the dataset, thus separating parameters that may be useful for calibration from those 

parameters that are actually useful and have an 

effect on modeled outputs. To decrease the run 

time associated with a large number of parameters, 

SVDA was also implemented with PEST++. SVDA computes 

a user-specified combination of parameters, or “super parameters,” that enables a reduction in the number of parameters 

used during calibration. PEST++ requires that the model be 

run one to two times for either each adjustable parameter or 

super parameter used in the calibration process multiplied by 

typically five to seven parameter optimization iterations. Thus, 

the reduction in the number of parameters by using super 

parameters resulted in substantial time savings during the 

Washita River alluvial aquifer model calibration. To further 

reduce the run time associated with the calibration process, 

0

5

10

15

20

25

30

35

40

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Monthly water demand, as a percentage

of annual groundwater use 

Month

Thermoelectric power

EXPLANATION

Livestock, oil and gas, and 

 self-supplied large industrial

Municipal, industrial, and 

 self-supplied residential

Crop irrigation

Figure 24. Estimated monthly water demand by groundwater-use type for the 

Washita River alluvial aquifer, western Oklahoma. Modified from Oklahoma 

Water Resources Board (2012b).

Table 7. Observation group contribution to the objective function for the automated calibration of the Washita River alluvial aquifer 

model, 1980–2015.

[USGS; U.S. Geological Survey, OWRB; Oklahoma Water Resources Board]

Observation group Source Number of 

observations

Group 

contribution 

(in percent)

Objective 

function 

components

Groundwater-level observations Groundwater-level observations (USGS, 2018b; 

OWRB, 2018)

168 30 10,874

Reservoir-stage observations Foss Reservoir stage observations (Bureau of 

Reclamation, 2018)

433 21 7,514

Base-flow estimates Cheyenne streamgage (table 1; fig. 1; USGS, 2018b) 433 40 14,250

Hammon streamgage (table 1; fig. 1; USGS, 2018b) 409

Foss streamgage (table 1; fig. 1; USGS, 2018b) 409

Clinton streamgage (table 1; fig. 1; USGS, 2018b) 433

Stream seepage estimates Conceptual water budget (table 5) 1 9 3,128

Totals 2,286 100 35,766
Simulation of Groundwater Flow 45

model runs were performed in parallel on a high-performance 

computing cluster by using the HTCondor run management 

software (Condor Team, 2012).

Calibration Parameters

For the Washita River alluvial aquifer model, 8 parameter 

groups representing 1,535 parameters were defined for the 

automated calibration (Ellis and others, 2020). These parameter groups are GHB conductance, recharge-rate multipliers, 

ETg rate and ETg root-zone depth multipliers (1 group), 

streambed conductance, lakebed leakance and surface runoff, 

specific yield, horizontal hydraulic conductivity and vertical 

anisotropy pilot points (1 group), and specific storage.

The GHB cells were grouped into parameter zones for 

the adjustment of conductance values. The 25 GHB parameter 

zones (Ellis and others, 2020) were created to account for 

variations in hydraulic properties of bedrock units adjacent 

to the Rush Springs aquifer. The recharge parameter group 

consisted of temporal recharge-rate multipliers for SWB-codedetermined recharge in 172 of the 433 stress periods; recharge 

was negligible in the remaining stress periods. Rechargerate multiplier parameters were applied uniformly across 

each stress period to adjust recharge. Entire-array multiplier 

parameters were used to adjust the ETg rate and ETg rootzone depth uniformly in each transient stress period. A single 

streambed conductivity parameter was set for all stream 

segments. A single lakebed leakance parameter was adjusted 

within a range of values that improved model stability of the 

reservoir while reducing the stage residual.

Specific yield, horizontal hydraulic conductivity, and 

vertical anisotropy, or the ratio of horizontal-to-vertical 

hydraulic conductivity, were represented by using pilot point 

interpolation in the groundwater model in layer 1 spaced at 

3,500-ft intervals (fig. 25) and directly adjusted during calibration. Pilot points provide a balance between the manipulation 

of values by parameter zones, often defined where values are 

relatively constant, and the manipulation of values in individual model cells, which may require more detailed data than 

are typically available. Specific yield, horizontal hydraulic 

conductivity, and vertical anisotropy values at each pilot 

point were interpolated independently by using exponentially 

weighted kriging.

An initial specific yield of 0.12 was obtained from Ellis 

(2018) and used for the pilot points in layer 1 representing the 

Washita River alluvial aquifer. The specific yield was adjusted 

during calibration to values ranging from 0.07–0.18. It was 

determined the specific yield value of 0.12 provided the best 

calibration results, hence this value was used in the model to 

represent the specific yield value in layer 1 across its entire 

extent. An initial horizontal hydraulic conductivity value of 

30 ft/d was set for pilot points in layer 1, similar to the value 

used for the Washita River alluvial aquifer tributary alluvium 

and terrace in Ellis (2018). The minimum and maximum 

horizontal hydraulic conductivity values for all pilot points 

were set at 6×10–4 and 100 ft/d, respectively. The value of 

6×10–4 ft/d represents the mean of siltstone and claystone values from Morris and Johnson (1967). The maximum horizontal hydraulic conductivity of 100 ft/d represents the fine-gravel 

horizontal hydraulic conductivity value (100 ft/d) used in Ellis 

and others (2017). Pilot point vertical anisotropy values for the 

interpolation zones in both layers were set to an initial value of 

10, indicating a horizontal-to-vertical hydraulic conductivity 

ratio of 10:1.

Values for horizontal hydraulic conductivity in layer 

2 were set based on likely values for adjacent and underlying hydrogeologic units based on lithology of these units. A 

horizontal hydraulic conductivity value of 0.08 ft/d was set 

where the Washita River alluvial aquifer overlies the Cloud 

Chief Formation. A horizontal hydraulic conductivity value 

of 6.6 ft/d from Ellis (2018) was set where the Washita River 

alluvial aquifer overlies the Rush Springs aquifer. Horizontal 

hydraulic conductivity values for the Washita River alluvial 

aquifer in the transition zone between these two hydrogeologic 

units were graded between 0.08 and 6.6 ft/d. The specific storage values for both layers were set as a static value of 1×10–5, 

which was comparable to values used by Ryter and Correll 

(2016) and Ellis and others (2017) for Permian bedrock units 

in Oklahoma. To improve model stability, a horizontal hydraulic conductivity value of 0.5 ft/d was set under Foss Reservoir 

in layer 2 of the model. Because no observations or boundary controls represented the bedrock in layer 2 and because 

calibration targets in layer 1 were not sensitive to parameter 

changes in layer 2, parameters in layer 2 were not adjusted 

during model calibration.

Calibration Targets

Calibration targets for the Washita River alluvial aquifer 

model included groundwater-level (OWRB, 2018; USGS, 

2018b) and reservoir-stage (Bureau of Reclamation, 2018) 

observations, as well as base-flow (table 2) and streamseepage estimates. For the automated calibration, these targets 

were weighted and placed into observation groups of the same 

name (table 7). The observation group contributions to the 

objective function (table 7) were adjusted prior to the start of 

the calibration process to ensure a balance between each group 

so that no single observation group dominated the calibration 

process. The base-flow estimate group was assigned the greatest contribution to the objective function (40 percent) because 

those measurements were more accurate and were collected 

throughout the simulation period. The water-table-altitude 

observation group was assigned the second greatest contribution to the objective function (30 percent) because those measurements were distributed spatially throughout the study area.

Groundwater-Level Observations

The groundwater model was calibrated to 

168 groundwater-level observations at 20 wells in the study 

area; this total included 20 groundwater-level observations 

for the steady-state simulation and 147 groundwater-level 
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 

! ! ! ! ! ! ! ! ! ! 

! ! ! ! ! ! ! 

! ! ! ! ! ! ! ! 

! ! ! ! ! ! ! 

! ! ! ! 

! ! ! ! ! ! 

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 

! ! ! ! ! ! 

! ! ! ! 

! ! ! ! 

! ! ! ! ! ! ! ! 

! ! ! ! ! 

! ! 

! ! 

! EXPLANATION ! Pilot points Active model area ROGER MILLS COUNTY CUSTER COUNTY BECKHAM COUNTY WASHITA COUNTY DEWEY COUNTY ELLIS COUNTY FOSS DAM Foss Reservoir 100° 99°45' 99°30' 99°15' 

35°45' 35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Figure 25. Spatial distribution of pilot points for the Washita River alluvial aquifer model, western Oklahoma, 1980–2015.
Simulation of Groundwater Flow 47

observations for the transient simulation (table 8). Of the 

147 groundwater-level observations for the transient simulation, about half of the observations occurred after 2003; 

therefore, a bias toward this period was incurred during model 

calibration. About 66 percent of the observations were during 

January–March of each year (fig. 26); thus, most observations 

were minimally affected by local groundwater withdrawals for 

irrigation that typically occur between April and September 

(fig. 24). Two-thirds of the wells had less than five observations during the simulation period (fig. 27), and the three wells 

located downgradient from Foss Reservoir had less than four 

groundwater-level observations each. Additionally, the four 

wells with the greatest number of groundwater-level observations (more than 13 observations) were located nearby or 

upgradient from the Hammon streamgage. Therefore, with 

respect to groundwater-level observations, the groundwater 

model had a greater uncertainty from upgradient to downgradient, particularly in the area downgradient from Foss 

Reservoir.

When available, screened-interval data were analyzed to 

ensure that observation wells were completed in the Washita 

River alluvial aquifer. All groundwater-level observations 

were originally collected as depth-to-water measurements; 

groundwater altitudes were calculated by subtracting the measured depth to water from the land-surface altitude specified 

in the National Water Information System (NWIS) (USGS, 

2018b) or OWRB (2018) databases. The land-surface altitude 

specified in the NWIS database was compared to the altitude 

obtained from a DEM, and observations with large landsurface altitude discrepancies were discarded.

Table 8. Selected groundwater-level observation wells in and near the Washita River alluvial aquifer, western Oklahoma.

[OWRB ID, the well identifier used by the Oklahoma Water Resources Board (OWRB); USGS, U.S. Geological Survey; --, not available. Dates are in month/

day/year format. Groundwater-level observations are available for the long-term groundwater-level recorder wells in the Oklahoma Water Resources Board 

well database beyond 2010. The number of groundwater-level observations does not include the period-of-record averaged observation used in the steady-state 

groundwater flow model]

OWRB ID or USGS 

station number 

(15-digit number)

Station name

Latitude, 

in decimal 

degrees

Longitude, 

in decimal 

degrees

Period of record used 

in this analysis 

(may contain gaps)

Well 

or 

hole 

depth, 

in feet

Number of 

groundwaterlevel observations during 

study period Begin End

Groundwater-level observation wells from the Mass Measurement Program (Oklahoma Water Resources Board, 2017a)

2675 14N-23W-10-SW-SW-SW 35.69702 −99.64002 5/6/2014 1/21/2015 141 3

2687 14N-23W-32-SW-SW-SW 35.64623 −99.66896 3/26/1980 1/6/2015 86 36

2809 15N-25W-27-SE-NE-NW 35.75101 −99.84745 7/14/2014 1/6/2015 163 3

20600 14N-20W-28-NW-SW-SW 35.65605 −99.34112 12/15/2011 9/30/2015 100 8

78093 14N-24W-34-SE-SE-SE 35.64007 −99.73162 3/8/2004 1/21/2015 190 13

99059 13N-21W-3-NW-NE-NE 35.63862 −99.42110 5/6/2014 5/13/2015 55 4

107564 14N-23W-9-NE-NE-NE 35.70352 −99.65150 7/14/2014 5/26/2015 70 4

118873 14N-24W-32-NE-SW-SW 35.64200 −99.78078 8/13/2014 9/30/2015 160 4

149263 12N-17W-10-NW-NE-NE 35.53676 −98.97921 8/12/2014 1/13/2015 123 2

149664 12N-18W-8-NW-SE-SW 35.52662 −99.13006 3/7/2013 5/7/2013 126 2

Groundwater-level observation wells (U.S. Geological Survey, 2018b)

353215099004101 12N-17W-09 BBB 1 WSH05 35.53746111 −99.01130556 4/23/2015 11/20/2015 124 3

353626099340901 13N-22W-17 BBD 1 WSH03 35.60734722 −99.56929167 7/14/2014 11/20/2015 50 8

353713099265001 13N-21W-09 BBC 1 35.62051667 −99.44733611 8/6/2014 1/6/2015 -- 2

353715099394501 13N-23W-08 ABD 1 35.62088154 −99.66288278 3/26/1980 3/26/1980 -- 1

353722099400801 13N-23W-08 ABB 1 35.62282596 −99.66927186 3/26/1980 3/20/2002 -- 22

353821099395901 14N-23W-32 DCC 1 WSH02 35.63926389 −99.66654722 3/18/1971 8/23/1995 75 8

353840099435301 14N-24W-34 DDA 2 35.64449233 −99.73177381 3/12/1996 1/27/2010 185 14

353913099352901 14N-24W-18 DDC 1 35.65373333 −99.59156111 7/14/2014 1/6/2015 -- 3

354022099202701 14N-21W-21 CDC 1 WSH04 35.6728 −99.34091389 4/23/2015 11/20/2015 75 2

354518099511601 15N-25W-21 DDD 1 35.75507222 −99.85463889 5/20/2014 5/20/2014 -- 1

354529099565501 15N-26W-22 DCA 1 WSH01 35.75821389 −99.94877222 5/20/2014 11/19/2015 60 4
48 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Foss Reservoir Stage Observations

The groundwater model was 

calibrated to 433 Foss Reservoir stage 

observations (table 7), which included 

432 monthly stage observations (Bureau 

of Reclamation, 2018) and 1 steady-state 

(averaged) stage observation. At active 

conservation pool stage (1,642 ft above 

NGVD 29), Foss Reservoir storage was 

about 168,732 acre-ft; at dead-pool stage 

(1,597 ft above NGVD 29), storage was 

about 8,868 acre-ft. Because the dead-pool 

storage was relatively small, it was not 

removed from estimates of Foss Reservoir 

storage used in this report.

Base-Flow and Stream-Seepage 

Estimates

The groundwater model was calibrated to 1,684 base-flow estimates at 

4 streamgages (table 7), including 

1,680 monthly estimates and 4 steady-state 

(averaged) estimates. Base-flow estimates 

were available during each stress period 

for the Cheyenne and Clinton streamgages. 

Base-flow estimates were available for the 

Foss and Hammon streamgages between 

January 1980 and September 1987 

and between October 1989 and 

December 2015, respectively.

The groundwater model was calibrated to one stream-seepage estimate 

(table 7). The simulated stream seepage 

was determined as the sum of the “Flow 

to Aquifer” column in the SFR2 secondary output file divided by the 433 monthly 

transient stress periods used for simulation 

purposes. Therefore, this value represents 

the mean stream seepage across the simulation period.

Calibrated Model Fit

The calibrated model fit was evaluated based on the reduction of calibrationtarget residuals and the fit of the calibrated 

water-budget components to the components of the conceptual water budget. 

Residuals were calculated as observed 

minus simulated values; positive residuals 

indicate lower simulated than observed 

values (underpredicted), and negative 

0

5

10

15

20

25

30

35

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov.

Month 

Groundwater-level observations, in percent

Dec.

Figure 26. Monthly groundwater-level observations as a percentage of the total 

number of groundwater-level observations used for the Washita River alluvial aquifer 

model, western Oklahoma, 1980–2015.

0

1

2

3

4

5

6

7

8

9

1 to 2 3 to 4 5 to 8 9 to 20 More than 20

Number of wells

Number of groundwater-level observations per well

Figure 27. Number of groundwater-level observations per well for wells used in the 

Washita River alluvial aquifer model, western Oklahoma, 1980–2015.
Simulation of Groundwater Flow 49

residuals indicate higher simulated than observed values 

(overpredicted). The root-mean-square error (RMSE) of 

residuals was calculated by using the following equation:

RMSE

n

o s

i

n

i i

1

1

2

(8)

where

n is the number of observations,

oi is the observed (or estimated) value, and

si is the simulated value.

Groundwater Levels

A good agreement between the observed and simulated 

groundwater-level altitudes (also known as hydraulic heads) 

was indicated as shown on a 1:1 plot, where the values 

generally fall along a straight line (fig. 28A). The combined 

groundwater-level mean residual for steady-state and transient 

simulations was 0.8 ft, indicating that simulated groundwater 

levels were slightly underpredicted (table 9). The combined 

groundwater-level RMSE was 7.5 ft, and 75 percent of residuals were within ±7.9 ft (table 9; fig. 28B). The simulated 

groundwater-level relief was 708 ft (highest groundwater-level 

altitude minus lowest groundwater-level altitude), and the 

combined RMSE as a percentage of this water-table relief was 

1.1 percent (table 9). These results are comparable to those for 

the Canadian River alluvial aquifer (Ellis and others, 2017), 

which has a similar geologic setting.

The overall distribution of groundwater-level residuals 

was reasonable, if not entirely random; wells in some parts 

of the model exhibited positive or negative bias in residuals 

(fig. 29). Groundwater levels generally were underpredicted 

in the alluvium and terrace in areas closer to the surrounding 

bedrock, whereas groundwater levels were overpredicted near 

the stream channel because of the inability to simulate the full 

amount of ETg estimated from the SWB code (refer to the 

“Using the Soil-Water-Balance Code to Estimate Recharge” 

section of this report for additional details). Overpredicted 

groundwater levels also typically occurred in wells downgradient from Foss Reservoir (fig. 29).

The two wells with the greatest residuals (fig. 29) (overpredicted or underpredicted groundwater levels) had only four 

measured groundwater levels each. Groundwater-level observations were measured at these wells during 2014 and 2015; 

therefore, temporal uncertainty may account for these large 

residuals. Additionally, these wells were located at or near a 

model boundary; thus, structural error may also account for 

these residuals. Because of model structural error, the model 

residual may exhibit temporal and spatial correlation structures (Doherty and Hunt, 2010). Simulated groundwater-level 

altitudes were similar to observed groundwater-level altitudes 

for three wells monitored by OWRB, shown in figure 13

hydrographs, but the magnitude of the simulated groundwaterlevel changes was typically less than the observed changes.

Base Flow

The pattern of simulated base flows was similar to that of 

observed base flows at the four streamgages used in the calibration, but mean simulated base flows were generally lower 

than mean estimated base flows (fig. 30). The mean base-flow 

residual was between 16.3 and −1.4 ft3/s for each streamgage 

(table 10). For the four streamgages, the RMSE was less than 

or equal to 9.1 percent of the range in observed base flow, 

and the mean base flow was slightly underpredicted for the 

Hammon, Foss, and Clinton streamgages (table 10).

Base flows were somewhat overpredicted during periods 

of lower base flows (winter and summer months) and underpredicted during periods of higher base flows (fall and spring 

months). Overpredicted base flows were likely the result of 

undersimulated ETg because increases in ETg in the model 

reduced summer low-flow residuals. Underpredicted base 

flows at the Clinton streamgage during high-flow periods 

indicate that observed base flows probably were overestimated 

by BFI because of reservoir releases from Foss Reservoir that 

could not easily be removed from the base-flow estimates. 

Reservoir releases from Foss Reservoir did not occur for 

Table 9. Statistical summary of groundwater-level residuals for the numerical groundwater-flow model of the Washita River alluvial 

aquifer, western Oklahoma, 1980–2015.

[RMSE, root-mean-square error; ±, plus or minus]

Statistic Steady-state simulation Transient simulation Combined value 

(steady state plus transient)

Number of groundwater-level observations 21 147 168

Mean residual, in feet −3.1 1.3 0.8

75th-percentile residual range, in feet ±8.5 ±7.9 ±7.9

RMSE, in feet 7.2 7.6 7.5

RMSE percentage of water-table relief 

(708 feet)

1.0 1.1 1.1
50 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

y = 0.9926x + 13.17

Coefficient of 

determination (R2

) = 0.9972

1,400

1,450

1,500

1,550

1,600

1,650

1,700

1,750

1,800

1,850

1,900

1,950

2,000

2,050

2,100

2,150

2,200

2,250

1,400 1,500 1,600 1,700 1,800 1,900 2,000 2,100 2,200

Simulated groundwater-level altitude (y), in feet 

above North American Vertical Datum of 1988

Measured groundwater-level altitude (x), in feet 

above North American Vertical Datum of 1988

A.

B.

0

5

10

15

20

25

30

35

40

45

50

–26 –22 –18 –14 –10 –6 –2 2 6 10 14 18 22 26

Frequency of residuals, in percent

Hydraulic-head residual (difference between measured and simulated groundwater-level 

altitude), in feet above North American Vertical Datum of 1988

1:1 line

–30

Figure 28. A, Simulated and measured groundwater-level altitude, and B, frequency of hydraulic-head residuals obtained from the 

numerical groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma, 1980–2015.
Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

Rush

Creek

Turkey 

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

White

Turkey

Active model areaMean groundwater-level altitude residual  at wells (observed minus simulated), in  feet, 1980–2015

–16.8 to –13.5–13.4 to –8.1

–8.0 to –5.0

–4.9 to –2.6–2.5 to –2.1

–2.0 to –1.1–1.0 to –0.1–0.0 to 9.1

9.2 to 19.6

EXPLANATION

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Foss

Reservoir

100° 99°45' 99°30' 99°15' 99

35°45'35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson an

Oklahoma Water Reso

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Washita

River

River

Washita

Figure 29. Spatial distribution of mean groundwater-level altitude residuals for the numerical groundwater-flow model of the Washita Rivaquifer, western Oklahoma, 1980–2015.
52 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

about two-thirds of the total number of stress periods. For 

these stress periods when reservoir releases did not occur, the 

RMSE for the Clinton streamgage decreased by 55 percent; the 

75-percent residual range decreased by 35 percent. Thus, the 

model generally simulates patterns in estimated base flow with 

more error present in months in which reservoir releases occur. 

Recharge processes, such as bank storage flow or interflow, 

that mostly operate on a submonthly time scale also could 

contribute to underpredicted base flows. Bank storage flows 

(Chen, 2003), by which floodwater infiltrates the aquifer and 

is released days to weeks after the floodwater recedes, may 

increase base flows during periods of no new recharge. The 

primary source of water to the aquifer is recharge, so large 

positive base-flow residuals also could be caused by underpredicted or incorrectly distributed recharge.

Reservoir Stage and Water Budget

The Foss Reservoir stage mean residual was −0.2 ft 

(table 11), indicating that the mean simulated stage was 

slightly higher than the mean observed stage (fig. 31A). The 

RMSE of Foss Reservoir stage residuals was 1.0 ft, and 

75 percent of the simulated reservoir stage values were within 

±0.9 ft of the observed stage values (table 11). The minimum 

simulated stage was 2 ft greater than the minimum observed 

stage, and the maximum simulated stage was 1 ft lower than 

the maximum observed stage. The largest Foss Reservoir 

stage residuals occurred in late 2014 and early 2015 when the 

observed reservoir stage was relatively low (fig. 31A).

Simulated storage in Foss Reservoir decreased by about 

20,000 acre-ft during the study period (fig. 32B). Storage in 

Foss Reservoir between 2001 and 2007 reflected precipitation 

patterns, where large shifts in precipitation occurred during each subsequent year (fig. 32); thus, the stage and water 

budget in Foss Reservoir for these years tended to oscillate 

on a year-to-year basis more than in other periods. Stage in 

Foss Reservoir dropped to about 1,622 ft in 2014 (fig. 31B), 

or 40 percent of active conservation pool storage (fig. 32B), 

which is the lowest stage since 1965 (Bureau of Reclamation, 

2018). This decrease in stage corresponds with a decrease in 

base flow in the Washita River during this period (table 2). 

More than half of the streamflow in the Washita River 

upstream from Foss Reservoir is from base flow from the aquifer (table 2); therefore, groundwater-level declines in the aquifer upgradient from Foss Reservoir affect stage and storage.

Calibrated Water Budget

The calibrated water budget for the Washita River alluvial 

aquifer model includes mean annual inflows and outflows for 

the simulation period (1980–2015) (table 12; figs. 33, 34A). 

Annual water budgets for the Washita River alluvial aquifer 

model are listed in table 13. A sub-accounting for areas upgradient and downgradient from Foss Reservoir was computed by 

using the ZONEBUDGET utility (Harbaugh, 1990). Simulated 

recharge was the largest inflow (49.0 percent); seepage from 

streams was 22.4 percent; lateral groundwater inflow was 

19.6 percent, and lakebed seepage was 9.0 percent of total 

inflows. Seepage to streams was the largest outflow (57.6 percent); ETg was 28.0 percent, groundwater use was 8.5 percent, 

lakebed seepage was 4.1 percent, and lateral groundwater 

outflow was 1.8 percent of total outflows.

The mean annual recharge for the calibrated water budget 

(25,049 acre-ft/yr; table 12) was about 13 percent greater than 

that of the conceptual water budget (22,169 acre-ft/yr; table 5). 

This difference corresponds to a rate of 0.4 in/yr of recharge 

in the calibrated water budget compared to recharge in the 

conceptual water budget. Mean annual stream seepage for the 

calibrated water budget of 18,084 (shown as −18,084 acre-ft/yr 

in table 12) was about 18 percent smaller than that of the 

conceptual water budget (21,996 acre-ft/yr; table 5). Mean 

annual net lateral groundwater flow for the calibrated model 

Table 10. Statistical summary of base-flow residuals for the numerical groundwater-flow model of the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015.

[Residual is calculated as the observed value minus the simulated value; thus, a negative residual indicates higher simulated than observed values. All units 

are in cubic feet per second except where noted; USGS, U.S. Geological Survey; Min., minimum; Max., maximum; RMSE, root-mean-square error; ±, plus or 

minus]

USGS station number 

(fig. 1)

Short name 

for station 

(table 1; fig. 1)

Observed base flow Simulated base flow Base-flow residuals

RMSE range in 

observed base 

flow, in percent Min. Mean Max. Min. Mean Max. Mean RMSE

75th percentile 

range

07316500 Cheyenne 

streamgage

0.0 14.8 118.0 1.3 16.2 99.2 −1.4 6.8 ±7.0 5.8

07324400 Hammon 

streamgage

0.0 40.0 463.4 0.0 23.7 152.4 16.3 42.0 ±24.0 9.1

07324400 Foss 

streamgage

1.2 45.1 575.9 1.5 41.6 580.7 3.6 11.9 ±5.7 2.1

07325000 Clinton 

streamgage

0.4 83.7 1,052.3 16.2 70.2 613.4 13.5 77.4 ±26.2 7.4
Simulation of Groundwater Flow 53

0

200

400

0

20

40

60

80

100

120

140

160

198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015

Estimated and simulated base flow, 

in cubic feet per second

A.

Measured streamflow, 

in cubic feet 

per second

Measured streamflow, 

in cubic feet 

per second

B.

0

400

800

0

100

200

300

400

500

600

700

Year

No data available

Estimated and simulated base flow, 

in cubic feet per second

EXPLANATION

Estimated base flow

Simulated base flow

Measured streamflow 

 at streamgage

EXPLANATION

Estimated base flow

Simulated base flow

Measured streamflow 

 at streamgage

Figure 30. Observed and simulated base flow and total streamflow at U.S. Geological Survey streamgages A, 07316500 Washita River 

near Cheyenne, Okla.; B, 07324200 Washita River near Hammon, Okla.; C, 07324400 Washita River near Foss, Okla.; D, 07325000 Washita 

River near Clinton, Okla., used for the numerical groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma, 

1980–2015.
54 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Measured streamflow, 

in cubic feet 

per second

C.

No data available

0

900

1,800

0

250

500

750

1,000

1,250

1,500

Estimated and simulated base flow, 

in cubic feet per second

D.

0

900

1,800

0

250

500

750

1,000

1,250

1,500

Year

Estimated and simulated base flow, 

in cubic feet per second

Measured streamflow, 

in cubic feet 

per second

EXPLANATION

EXPLANATION

Releases from Foss Reservoir

Estimated base flow

Simulated base flow

Measured streamflow 

 at streamgage

Releases from Foss Reservoir

Estimated base flow

Simulated base flow

Measured streamflow 

 at streamgage

Figure 30. Observed and simulated base flow and total streamflow at U.S. Geological Survey streamgages A, 07316500 Washita River 

near Cheyenne, Okla.; B, 07324200 Washita River near Hammon, Okla.; C, 07324400 Washita River near Foss, Okla.; D, 07325000 Washita 

River near Clinton, Okla., used for the numerical groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma, 

1980–2015.—Continued
Simulation of Groundwater Flow 55

1,620

1,625

1,630

1,635

1,640

1,645

1,650

1,655

19801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014

2015

Reservoir stage at the end of each month in a

given year, in feet 

Year

19801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014

2015

Year

50,000

75,000

100,000

125,000

150,000

175,000

200,000

225,000

250,000

Reservoir storage, in acre-feet

A.

B.

Observed stage

EXPLANATION

Simulated stage

Active conservation pool (normal pool) stage is

 1,642 feet above the National Geodetic Vertical 

 Datum of 1929 (Bureau of Reclamation, 2018)

Observed storage

Simulated storage

Active conservation pool (normal pool) stage is

 1,642 feet above the National Geodetic Vertical 

 Datum of 1929 (Bureau of Reclamation, 2018)

EXPLANATION

Figure 31. Observed and simulated A, stage and B, storage for Foss Reservoir for the numerical groundwater-flow model 

of the Washita River alluvial aquifer, western Oklahoma, 1980–2015.

Table 11. Statistical summary of Foss Reservoir stage residuals for the numerical groundwater-flow model 

of the Washita River alluvial aquifer, western Oklahoma, 1980–2015.

[NAVD 88, North American Vertical Datum of 1988; RMSE, root-mean-square error; ±, plus or minus; --, not applicable]

Observation Lake stage

Minimum Mean Maximum

Observed, in feet 1,622 1,639 1,648

Simulated, in feet 1,624 1,639 1,647

Mean residual, in feet -- −0.2 --

RMSE, in feet -- 1.0 --

75th percentile residual range, in feet -- ±0.9 --
56 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

(9,117 acre-ft/yr; table 12) was about 47 percent less than 

that of the conceptual water budget (17,157 acre-ft/yr; table 5). 

Mean annual ETg for the calibrated model (14,377 acre-ft/yr; 

table 12) was about 22 percent greater than that of the conceptual water budget (11,828 acre-ft/yr; table 5). Because 

unreasonably long model run times are associated with larger 

ETg areas and rates, the area where ETg was simulated and 

the simulated ETg rate were decreased in the simulation. 

The mean simulated annual groundwater use (4,367 acre-ft/yr; 

table 12) was about 20 percent less than the conceptual 

water budget (5,502 acre-ft/yr; table 5) because of the threshold applied to simulated wells associated with 33 permits.

Simulated groundwater storage at the end of the simulation period (2015) was 587,252 acre-ft, and mean simulated groundwater storage for the simulation period was 

589,423 acre-ft. Because of the difficulty associated with 

estimating total recoverable groundwater—whereby groundwater pumping cannot extract the entire volume of water from 

the aquifer—these simulated groundwater storage values 

represent theoretical volumes. However, these values are useful for comparisons of changes in groundwater storage caused 

by aquifer stresses. For the simulation period, mean annual 

simulated outflows exceeded inflows by 169 acre-ft/yr 

(table 12). This difference corresponds to a cumulative net 

storage decrease of about 6,000 acre-ft (fig. 34B), or a cumulative net groundwater-level decrease of about 0.5 ft.

–240,000

–200,000

–160,000

–120,000

–80,000

–40,000

0

40,000

80,000

120,000

160,000

200,000

240,000

198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015

Annual simulated water budget for 

Foss Reservoir, in acre-feet

A.

Year

Simulated change in annual storage 

for Foss Reservoir, in acre-feet 

B.

Net budget totals are calculated as the difference of outflow

and inflow; positive net totals indicate inflow, and negative 

net totals indicate outflow

–70,000

–80,000

–60,000

–50,000

–40,000

–30,000

–20,000

–10,000

0

10,000

20,000

30,000

40,000

50,000

60,000

Precipitation

EXPLANATION

Runoff

Base flow

Evaporation

Withdrawal

Lakebed seepage in

Lakebed seepage out

EXPLANATION

Change in annual storage

Cumulative change in storage

Figure 32. A, Annual simulated water budget for Foss Reservoir and B, simulated changes in storage for Foss Reservoir in the 

numerical groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma, 1980–2015.
Simulation of Groundwater Flow 57

Simulated annual groundwater storage changes reflect 

climatic patterns during the simulation period (fig. 16). From 

1980 to 1985, cumulative storage was negative (fig. 34B) 

because of a period of generally lower than mean precipitation 

(fig. 16). A relatively long period of above-mean precipitation occurred between 1985 and 1997 (fig. 16), which resulted 

in a cumulative storage increase (fig. 34B). This period was 

followed by a period of generally below-mean precipitation 

between 2001 and 2006 (fig. 16), whereby cumulative storage 

decreased (fig. 34B). The drought conditions between 2009 

and 2014 (fig. 16) resulted in a sustained decrease of groundwater in storage (fig. 34B).

Recharge composes 49 percent of the total simulated 

inflow to the aquifer (fig. 33; table 12). Therefore, precipitation changes—although moderated by the substantial part of 

inflows from lateral groundwater inflows (table 12)—affect 

groundwater storage and the annual water budget, which 

is several times larger in years with substantial precipitation events compared with years of below-mean precipitation. During extended periods of below-mean precipitation, 

groundwater use substantially increased—such as during 

2013 and 2014, when groundwater use was nearly twice the 

mean fig. 6)—which compounded the effects on groundwater storage.

Mean simulated aquifer inflows, primarily from recharge 

and seepage from streams, tended to be greatest during May, 

June, and September (fig. 35A), which generally corresponds 

to months of above-mean recharge (fig. 17B). Mean simulated 

aquifer outflows, primarily from seepage to streams, ETg, 

and groundwater use, were greatest in June, July, and August 

(fig. 35A). During those summer months, seepage to streams 

was reduced by groundwater-level declines from large ETg 

outflows and groundwater use, which was primarily for irrigation. Mean monthly outflows exceeded mean monthly inflows 

in 4 of 12 months (fig. 35B).

Calibrated Parameter Values

The calibrated parameter values for the model represent 

updates to the initial values estimated from available hydraulic 

data or from the conceptual water budget and are available in 

Ellis and others (2020). Calibrated conductance values for the 

25 GHB conductance zones were between 200 and 203 ft2/d, 

respectively. The calibrated ETg rate multiplier was reduced 

to a value of 0.4 (40 percent) from the initial value in all 

areas where ETg was simulated. Although further increases 

in the ETg rate multiplier may have improved the calibration 

to base flows and groundwater levels, larger ETg rates could 

not be simulated without model stability issues. Because of 

Table 12. Mean annual calibrated water budget for the numerical groundwater-flow model of the Washita River alluvial aquifer, 

western Oklahoma, 1980–2015.

[--, not applicable; All units are in acre-feet per year. Net budget totals are calculated as the difference of outflow and inflow; therefore, positive net totals indicate inflow, and negative net totals indicate outflow to the Washita River alluvial aquifer]

Water-budget category Upgradient from 

Foss Reservoir

Downgradient from 

Foss Reservoir

Total 

(acre-feet per year)

Percent of 

water budget

Inflow

Recharge 16,811 8,239 25,049 49.0

Seepage from streams 9,209 2,243 11,452 22.4

Lateral groundwater inflow 33 9,990 10,023 19.6

Lakebed seepage inflow 29 4,570 4,599 9.0

Total inflow 26,082 25,041 51,123 100

Outflow

Seepage to streams 11,276 18,259 29,536 57.6

Saturated-zone evapotranspiration 9,874 4,504 14,377 28.0

Groundwater use 3,984 383 4,367 8.5

Lakebed seepage outflow 1,018 1,088 2,106 4.1

Lateral groundwater outflow 1 904 905 1.8

Total outflow 26,153 25,139 51,292 100

Net water-budget totals

Net stream seepage −2,067 −16,017 −18,084 --

Net lateral flow 32 9,085 9,117 --

Net lakebed seepage −989 3,482 2,493 --

Net change in groundwater storage −71 −98 −169 --
Table 13. Annual water budget for the simulation period for the Washita River alluvial aquifer, western Oklahoma, 1980–2015. [GHB, general-head boundary; ET, evapotranspiration] Year INFLOWS (acre-feet per day) OUTFLOWS (acre-feet per day) Storage GHB Recharge Stream seepage Lake seepage Storage Well withdrawals ET GHB 

1980 21,444 10,266 15,079 10,564 4,760 11,830 5,156 16,046 783 1981 13,988 10,982 11,487 13,276 4,112 9,161 4,843 17,107 645 1982 29,738 9,178 55,954 10,604 4,992 40,298 5,130 16,689 1,122 1983 17,186 10,313 19,215 11,552 4,448 15,461 3,493 13,566 741 1984 14,402 11,096 15,128 12,634 4,099 11,405 4,914 16,907 642 1985 15,777 10,317 18,384 12,027 4,080 13,056 4,765 13,696 789 1986 10,848 9,891 40,389 10,551 5,028 25,359 3,798 11,764 893 1987 20,831 8,842 25,203 8,939 6,183 15,400 3,536 14,168 1,154 1988 22,220 8,451 30,913 10,436 4,562 19,141 3,654 15,650 1,400 1989 22,107 8,643 35,341 9,720 4,569 22,409 3,113 13,458 1,448 1990 10,925 10,307 14,245 11,272 5,658 9,579 3,279 13,980 779 1991 10,703 10,554 23,959 13,046 4,656 17,895 3,173 15,427 711 1992 16,181 9,395 28,362 9,018 4,568 15,296 2,217 14,484 1,066 1993 24,816 8,448 31,187 8,031 4,284 18,107 2,193 13,157 1,534 1994 13,353 11,140 3,646 13,615 4,424 5,056 3,820 16,942 638 1995 16,682 9,144 45,396 10,328 4,944 29,021 5,280 13,817 1,131 1996 18,114 9,417 32,534 11,225 4,963 21,443 5,190 13,680 1,070 1997 29,524 7,041 78,460 5,657 5,119 42,523 1,888 9,676 2,174 1998 31,741 8,965 34,850 10,703 4,590 23,393 4,162 16,819 1,139 1999 19,414 10,109 19,489 10,599 4,594 11,570 4,197 13,397 783 2000 20,140 9,862 27,023 10,737 4,724 19,652 4,617 14,476 833 2001 20,025 9,835 25,435 10,631 4,690 17,706 3,895 15,179 844 2002 10,779 10,996 15,799 12,023 4,941 13,397 3,013 13,620 649 2003 10,609 10,957 3,178 13,358 4,804 3,644 2,932 14,789 632 2004 14,165 10,394 37,901 11,807 4,616 27,122 5,897 13,013 750 2005 21,112 9,807 19,266 10,745 4,411 13,198 4,846 13,771 898 2006 13,824 11,202 6,354 14,131 4,186 7,474 4,364 16,654 638 2007 19,703 9,401 45,499 8,088 5,116 30,364 4,009 10,499 1,002 2008 16,412 9,482 38,220 8,973 4,698 22,222 3,396 13,233 980 2009 15,896 10,419 8,207 12,351 4,715 5,615 4,464 14,571 772 
Table 13. Annual water budget for the simulation period for the Washita River alluvial aquifer, western Oklahoma, 1980–2015.—Continued[GHB, general-head boundary; ET, evapotranspiration]

Year

INFLOWS (acre-feet per day) OUTFLOWS (acre-feet per day)

Storage GHB Recharge Stream seepage Lake seepage Storage Well withdraw- als ET GHB S

2010 11,157 11,011 12,224 13,127 4,941 8,924 4,803 14,222 642 2011 17,719 11,146 11,528 15,046 4,175 12,482 5,873 19,792 626 2012 20,096 11,028 2,828 15,511 3,529 7,143 7,177 17,810 680 2013 14,139 11,556 5,302 15,649 2,935 9,707 7,270 14,467 566 2014 13,839 11,666 3,142 15,427 2,485 7,121 7,167 15,417 551 2015 17,811 9,964 53,610 15,327 6,216 47,814 4,251 11,258 914 Average 17,706 10,034 24,854 11,576 4,606 17,527 4,327 14,533 906 
60 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

these stability issues and extended run times during automated 

calibration, the following changes were made during calibration: (1) the ETg area—originally defined by using National 

Wetlands Inventory data (U.S. Fish and Wildlife Service, 

2018)—was reduced to a narrower zone adjoining the simulated stream channel in the alluvium, and (2) an annual threshold of 95 in/yr was applied to the ETg rate.

Calibrated recharge was increased from the conceptual 

water budget by using recharge multipliers applied during the 

simulation period (Ellis and others, 2020) in approximately 

40 percent of the monthly stress periods. Monthly mean calibrated recharge was greater than monthly mean precalibrated 

recharge for all months except July (fig. 36). With the exception of July, monthly mean calibrated recharge was 18–77 percent greater than the respective monthly mean precalibrated 

recharge. The increase in calibrated recharge was primarily 

used to match the stream base-flow observations at each 

streamgage. The increased recharge also improved the simulated water-table observation residuals in the terrace, which 

were typically less than the observed values.

Surface runoff and withdrawal inputs for Foss Reservoir 

were adjusted manually following the automated calibration. 

Because of the uncertainty inherent in estimating surface runoff to Foss Reservoir—particularly overland flows—surface 

runoff was varied between −30 and +30 percent in 329 of 

432 transient stress periods. Foss Reservoir stage was generally underpredicted during summer months; thus, surface 

runoff was increased during these months. The required 

increase in surface runoff, particularly in May and June when 

precipitation was greatest (fig. 17A), indicates that this input 

was underestimated—or that ETg was overestimated—during 

the generation of inputs to the Lake package. Large reservoir 

releases during 5 of the 432 transient stress periods between 

1997 and 2000 were reduced between 20 and 58 percent 

because of substantial declines in the simulated reservoir stage 

that occurred when the full release amount was simulated.

Sensitivity Analysis

Several analyses were performed to ensure that the 

parameters used were effective in reducing the objective 

function and to evaluate the correlation among parameters 

and identify parameters informed by the calibration process. 

During automated calibration, PEST++ computed the sensitivities of each parameter with respect to all observations by 

using 1-percent changes in parameters, which are contained in 

the Jacobian matrix used to record the response or sensitivity 

of each observation to an adjustment in a parameter. Doherty 

and Hunt (2010, p. 4) explain: “the Jacobian matrix consists of 

the sensitivities of all specified model outputs to all adjustable model parameters; each column of the Jacobian matrix 

contains the sensitivity of all model outputs for a single adjustable parameter. Individual parameters, or combinations of 

parameters, that are deemed to be estimable on the basis of the 

calibration dataset constitute the calibration solution space.” 

These sensitivities are a dimensionless measure of the change 

in residuals affected by adjustments to a parameter; thus, 

calibration-target residuals are more easily reduced by parameters with larger sensitivities. Sensitivities were calculated by 

using the Jacobian matrix output from PEST++ (Ellis and others, 2020) and summed for each parameter group (fig. 37).

Lakebed seepage

outflow 4.1 percent

Lateral groundwater

outflow 1.8 percent

Outflows

Inflows

Seepage from 

streams

22.4 percent

Lateral 

groundwater 

inflow 

19.6 percent

Lakebed 

seepage 

inflow

9.0 percent

Recharge

49.0 percent

Seepage to streams

57.6 percent

Saturated-zone 

evapotranspiration

28.0 percent

Groundwater use

8.5 percent

A.

B.

Figure 33. A, Inflows and B, outflows for the mean annual 

calibrated water budget for the numerical groundwater-flow 

model of the Washita River alluvial aquifer, western Oklahoma, 

1980–2015.
Simulation of Groundwater Flow 61

198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015

198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015

A.

Year

Year

B.

Net budgettotals are calculated asthe difference of outflow

and inflow; positive net totals indicate inflow, and

negative net totals indicate outflow

–80,000

–60,000

–40,000

–20,000

0

20,000

40,000

60,000

80,000

100,000

Annual simulated groundwater budget of the 

Washita River alluvial aquifer, in acre-feet –35,000

–30,000

–25,000

–20,000

–15,000

–10,000

–5,000

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Simulated mean annual change in

groundwater storage, in acre-feet

Recharge

EXPLANATION

Saturated-zone evapotranspiration

Springs, seeps

Well withdrawals

Net stream seepage

Net lateral flow

Net lakebed seepage

EXPLANATION

Change in annual groundwater storage

Cumulative change in groundwater storage

Figure 34. A, Mean annual simulated groundwater water budget and B, simulated mean annual change in groundwater storage 

for the numerical groundwater-flow model of the Washita River alluvial aquifer, western Oklahoma, 1980–2015.
62 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

A.

B.

–40,000

–30,000

–20,000

–10,000

0

10,000

20,000

30,000

40,000

Change in groundwater storage, in acre-feet

Month

–100,000

–80,000

–60,000

–40,000

–20,000

0

20,000

40,000

60,000

80,000

100,000

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Groundwater inflow or outflow, in acre-feet

Month

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Change in groundwater storage

Lakebed seepage out

Well withdrawals

Lateral outflow

Saturated-zone evapotranspiration

Springs and seeps

Seepage to streams

Lakebed seepage in

Lateral inflow

Seepage from streams

Recharge

EXPLANATION

EXPLANATION

Figure 35. A, Mean monthly groundwater inflows and outflows and B, mean monthly change in groundwater storage for the 

Washita River alluvial aquifer, western Oklahoma, 1980–2015.
Groundwater-Availability Scenarios 63

The observation groups were generally most sensitive to 

changes in recharge, ETg, and hydraulic conductivity (fig. 37). 

Recharge was the largest aquifer inflow (table 12), which—

along with the pilot points used to adjust hydraulic conductivity and specific yield—affected the groundwater levels, base 

flows, stream seepage, and reservoir stage throughout the 

model. Estimated base-flow observations (1,684) were more 

numerous than the groundwater-level observations (168) 

(table 7). Therefore, changes in ETg applied to the alluvium 

had a lesser effect than recharge on groundwater-level observations because most of the observations are distant from 

Evapotranspiration package cells compared to base-flow 

observations at the four model-area streamgages. For matching the Foss Reservoir stage observations, the model was 

less sensitive to changes in ETg than to changes in recharge 

because stream inflows contributed a large percentage of 

inflow to this reservoir. The GHB cells in the model were only 

located downgradient from Foss Reservoir (fig. 22); therefore, 

the sensitivity of most observation groups to changes in the 

GHB conductance values was reduced. The reservoir-stage 

observation group typically had the greatest sensitivity of the 

four observation groups; this observation group was most 

sensitive to the lake parameter group but also to recharge and 

least sensitive to GHB conductance (fig. 37).

Groundwater-Availability Scenarios

Three types of scenarios were formulated for the calibrated groundwater model. These scenarios were used to 

(1) estimate the EPS pumping rate that retains a saturated 

thickness that meets the minimum 20-year life of the aquifer, 

(2) quantify the effects of projected groundwater-use rates on 

groundwater storage over a 50-year period, and (3) evaluate 

the effects of projected pumping rates extended 50 years into 

the future and sustained hypothetical drought conditions over 

a 10-year period on base flow and groundwater in storage. 

Additionally, an uncertainty analysis was performed for the 

EPS scenario.

Equal-Proportionate Share

The EPS for the Washita River alluvial aquifer was 

defined as the pumping rate at which fresh groundwater can be 

withdrawn so that, after a minimum of 20 years of continuous 

EPS withdrawals, 50 percent of the aquifer retains a saturated 

thickness of at least 5 ft. To compute the EPS for the Washita 

River alluvial aquifer, a similar approach to that of the model 

calibration was implemented. Whereas automated calibration 

77%

19%

43%

49%

45%

37%

–1%

18%

54%

14%

53% 48%

0

600

1,200

1,800

2,400

3,000

3,600

4,200

4,800

5,400

6,000

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Monthly mean recharge, in acre-feet

Month

Monthly mean precalibrated recharge, 1980–2015

Monthly mean calibrated recharge, 1980–2015

Mean monthly precalibration recharge, 1980–2015

Mean monthly calibrated recharge, 1980–2015

% Percent increase or decrease (–) from precalibrated 

 recharge

EXPLANATION

Figure 36. Monthly mean precalibration recharge and monthly mean calibrated recharge for the numerical 

groundwater-flow model of the Washita River alluvia aquifer, 1980–2015.
64 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

of the Washita River alluvial aquifer model involved the 

adjustment of many model parameters based on available 

calibration targets, the determination of the EPS was based 

only on a uniform pumping rate parameter and an aquifer 

saturated thickness calibration target (5 ft). The EPS pumping 

rate parameter was composed of a hypothetical well placed in 

each active cell in layer 1. During each iteration of the calibration process, the pumping rate parameter was adjusted until 

the objective function was zero—when 50 percent of the basin 

retained a saturated thickness of 5 ft. The EPS was computed 

for time periods of 20, 40, and 50 years into the future. The 

20-year time period was chosen by the OWRB to align with 

the MAY ensuring a minimum 20-year life of the groundwater 

basin. The OWRB also requested analyses for additional time 

periods of 40 and 50 years.

Annual stress periods with calibrated model mean 

stresses were used in the EPS scenarios instead of monthly 

stress periods to (1) shorten transient simulation run times, 

(2) minimize the iterative variability in the EPS pumping 

rate caused by monthly or seasonal stresses, and (3) improve 

model stability. The 2015 simulated water table from the 

calibrated groundwater model was used as the starting water 

table in each EPS scenario. The calibrated model mean annual 

recharge is referred to as “normal recharge.” To account for 

potential climate variability, the EPS scenarios were run with 

recharge alternatively increased and decreased by 10 percent.

The 20-, 40-, and 50-year EPS pumping rates under 

normal recharge conditions were 1.7, 1.6, and 1.6 (acre-ft/

acre)/yr, respectively (table 14). Given the aquifer area used 

for modeling purposes (84,366 acres), these rates correspond 

Table 14. Equal-proportionate-share (EPS) pumping rates for the Washita River alluvial aquifer, western Oklahoma, 1980–2015.

Period (number of years)

EPS pumping rate 

(acre-feet per acre per year)

Normal recharge1 Recharge reduced by 10 percent Recharge increased by 10 percent

20 1.7 1.6 1.8

40 1.6 1.5 1.7

50 1.6 1.5 1.7

1The calibrated model mean annual recharge is referred to as “normal recharge.”

1

10

100

1,000

10,000

100,000

Recharge Saturated-zone

evapotranspiration

Hydraulic

conductivity

General-head

boundary

conductance

Lake Specific yield Specific storage Streambed

conductance

Observation group sensitivity, dimensionless

Parameter group

EXPLANATION

Foss Reservoir stage

Observation Group

Groundwater levels

Base flow

Stream seepage

Figure 37. Observation group sensitivity by parameter group in the numerical groundwater-flow model of the Washita River alluvial 

aquifer, western Oklahoma.
Groundwater-Availability Scenarios 65

to annual yields of about 143,423, 134,986, and 134,986 acreft/yr, respectively. Increasing and decreasing recharge by 

10 percent resulted in 20-year EPS pumping rates of 1.8 

(5.9-percent increase) and 1.6 (acre-ft/acre)/yr (5.9-percent 

decrease), respectively. Increasing and decreasing recharge 

by 10 percent resulted in 40-year EPS pumping rates of 1.7 

(6.2-percent increase) and 1.5 (acre-ft/acre)/yr (6.3-percent 

decrease), respectively. Increasing and decreasing recharge 

by 10 percent resulted in 50-year EPS pumping rates of 1.7 

(6.2-percent increase) and 1.5 (acre-ft/acre)/yr (6.3-percent 

decrease), respectively.

At the end of the 20-year EPS scenario, saturated thickness (figs. 11 and 12) remained unchanged primarily in the 

eastern parts of the aquifer and along the thickest areas of the 

active alluvium near the center of the stream channel (fig. 38). 

Most of the terrace material upland from the alluvial deposits 

was unsaturated except for areas where a shallow hydraulic 

gradient occurred. Streamflow in the Washita River upstream 

from Foss Reservoir was sustained mostly from the inflows 

from the Washita River in Texas. As a result, the Washita 

River alluvial aquifer deposits upgradient from Croton Creek 

remained saturated, whereas most other alluvial deposits 

between this location and Foss Reservoir generally had minimal or no saturation at the end of the EPS scenarios (fig. 38). 

Downgradient from Foss Reservoir, saturated thickness was 

sustained by lateral inflow from the Rush Springs aquifer 

simulated by the general-head boundary cells (fig. 22) and by 

releases from Foss Reservoir. Saturated thickness greater than 

5 ft also remained along Turkey, Barnitz, Beaver, and Turtle 

Creeks, which was sustained by simulated SFR2 inflows.

In the 20- and 40-year EPS scenarios, substantial percentages of groundwater storage were removed by the simulated 

wells in each model cell (fig. 39). Annual EPS groundwater 

pumping decreased as the thinner areas of the aquifer, including most of the alluvium and terrace, were dewatered and 

saturated thickness dropped below 5 ft, or the areas went 

dry (figs. 38 and 39). Annual groundwater storage changes 

decreased as annual EPS groundwater pumping decreased, but 

groundwater storage changes were more moderate during the 

last 3 years of each scenario (fig. 39).

Groundwater storage at the end of the 20-year EPS 

scenario was about 281,000 acre-ft, or about 306,000 

acre-ft (52 percent) less than the starting storage (fig. 39). 

Considering the 84,366-acre area used for modeling purposes 

and using a specific yield of 0.12, this decrease in storage was 

equivalent to a mean groundwater-level decline of about 30 ft. 

This groundwater-level decline was greater than the aquifer 

thickness in some areas of the model where the aquifer was 

dewatered (fig. 38).

At the end of the 20-year EPS scenario, base flow had 

decreased to 0 ft3/s at the Cheyenne and Hammon streamgages 

(fig. 38). Downstream from Foss Reservoir, base flow was sustained at the Clinton streamgage as a result of SFR2 inflows 

from Foss Reservoir releases and GHB inflows from the 

Rush Springs. The groundwater-level altitude in the aquifer 

was below the altitude of the streambed during most of the 

EPS scenarios, thus promoting seepage from streams to the 

aquifer. Except for streams receiving base-flow inflows from 

outside the active model area and except for the Washita River 

downstream from Foss Reservoir, the majority of streams in 

the study area were dry at the end of the 20-year EPS scenario 

(fig. 38).

Foss Reservoir stage was below the dead-pool stage of 

1,597 ft after about 7 years of pumping in the 20-year EPS 

scenario (fig. 40). The loss of any remaining usable water in 

the reservoir in this scenario was caused by (1) the cessation 

of stream inflows from the Washita River—which constituted 

about one-fourth of inflows to Foss Reservoir (fig. 32)—after 

the first year, and (2) the decline of groundwater levels around 

the reservoir compared to the calibrated model (fig. 38), 

resulting in large lakebed seepage outflows to the aquifer. 

Surface-water inflows composed a larger percentage of the 

total reservoir inflow than lakebed seepage; thus, the precipitous decline in reservoir stage in the first 7 years is largely 

the result of the cessation of flow from the Washita River. 

Precipitation and evaporation also decreased as cells representing Foss Reservoir became dry, but these decreases tended 

to offset each other.

Projected (50-Year) Groundwater Use

Projected 50-year groundwater-use scenarios were used 

to simulate the effects of selected well withdrawal rates on 

groundwater storage in the Washita River alluvial aquifer. 

The effects of well withdrawals were evaluated by comparing 

changes in groundwater storage among four 50-year scenarios 

using (1) no groundwater use, (2) groundwater use at the 2015 

pumping rate, (3) mean groundwater use for the simulation 

period, and (4) increasing groundwater use.

The increasing-use scenario assumed a 38-percent 

increase in pumping over 50 years based on 2010–60 demand 

projections for west-central Oklahoma (West Central Region, 

OWRB, 2012b). Model stresses were configured as the mean 

of stresses in each month from the calibrated model, and the 

scenarios assumed that future climate conditions were similar 

to those of the 1980–2015 simulation period. The projected 

storage calculation uses the same method as the EPS scenarios, whereby the model specific yield is multiplied by the 

saturated thickness in each active model cell.

Groundwater storage after 50 years with no groundwater 

use was 545,249 acre-ft, or 693 acre-ft (0.1 percent) greater 

than the initial groundwater storage; this groundwater storage 

increase is equivalent to a mean groundwater-level increase of 

0.1 ft (table 15). Groundwater storage at the end of the 50-year 

period with the 2015 groundwater-pumping rate applied was 

543,831 acre-ft, or 723 acre-ft (0.1 percent) less than the initial 

storage; this groundwater storage decrease is equivalent to a 

mean groundwater-level decrease of 0.1 ft. Groundwater storage after 50 years with the mean pumping rate for the study 

period was 543,202 acre-ft, or 1,349 acre-ft (0.2 percent) less 

than the initial groundwater storage; this groundwater storage 
Base from U.S. Geological Survey digital data Albers Equal-Area Conic projection; North American Datum 1983 Creek Dead Warrior Creek Croton Creek Plum Creek Sergeant Major Creek Brokenleg Creek Wild Horse Creek Cofer Creek Caffey Creek Rush Creek Turkey Creek Wild Horse Creek Quartermaster Creek Ninemile Creek Sandstone Creek Wildcat Creek Big Kiowa Creek

White

Turkey

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Foss

Reservoir

100° 99°45' 99°30' 99°15' 

35°45'35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from John

Oklahoma Wate

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

07324400

07324200

07316500

East

Barni

Creek

West

Barnitz

Creek

Barnitz

Cree k

Washita

River

River

Washita

Simulated base flow, in cubic feet per second,  after 20 years of equal-proportionate-share  groundwater pumping

0 to 0.9

1.0 to 2.52.6 to 4.24.3 to 6.97.0 to 36.0

36.1 to 40.9

Simulated saturated thickness, in feet, after  20 years of equal-proportionate-share groundwater pumping

0 to 10.0

10.1 to 30.931.0 to 52.7

52.8 to 76.1

76.2 to 101.2

101.3 to 133.0133.1 to 168.1168.2 to 213.3

EXPLANATION

Streamgage and USGS station numbe (table 1; USGS, 2018b)

07324400

Figure 38. Simulated saturated thickness and simulated base flow after 20 years of continuous equal-proportionate-share groundwaWashita River alluvial aquifer, western Oklahoma, 1980–2015.
Groundwater-Availability Scenarios 67

decrease is equivalent to a mean groundwater-level decrease 

of 0.1 ft. Groundwater storage at the end of the 50-year period 

with an increasing demand pumping rate was 542,584 acreft, or 1,967 acre-ft (0.4 percent) less than the initial storage; 

this groundwater storage decrease is equivalent to a mean 

groundwater-level decrease of 0.2 ft.

Mean annual base flow simulated at the Cheyenne 

streamgage decreased 0.49 ft3/s (2.4 percent) after 50 years 

with no pumping and decreased 1.7 ft3/s (9.4 percent) after 

50 years of an increasing demand groundwater-pumping rate 

(table 16). Mean annual base flow simulated at the Hammon 

streamgage decreased 0.2 ft3/s (0.6 percent) after 50 years 

with no pumping and decreased 3.6 ft3/s (12.9 percent) after 

50 years of an increasing demand groundwater-pumping rate. 

Mean annual base flow simulated at the Clinton streamgage 

decreased 0.3 ft3/s (0.5 percent) after 50 years with no pumping and decreased 0.6 ft3/s (0.9 percent) after 50 years of an 

increasing demand groundwater-pumping rate (table 16). 

Decreasing base flow and decreasing groundwater storage 

during these projected groundwater use scenarios indicate 

that pumping across the aquifer depletes streamflow before 

groundwater levels and storage are appreciably affected by this 

pumping.

0

10

20

30

40

50

60

70

80

90

100

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Cumulative change in storage, in percent

Simulated groundwater storage, in acre-feet 

Year

0

10

20

30

40

50

60

70

80

90

100

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Cumulative change in storage, in percent

Simulated groundwater storage, in acre-feet 

Year

A.

B.

Simulated groundwater in storage, in acre-feet

EXPLANATION

Starting groundwater storage

Cumulative net change in storage, in percent

Simulated groundwater in storage, in acre-feet

EXPLANATION

Starting groundwater storage

Cumulative net change in storage, in percent

Figure 39. Changes in simulated groundwater storage during A, 20, and B, 40 years of continuous equal-proportionate-share 

groundwater pumping in the Washita River alluvial aquifer, western Oklahoma, 1980–2015.
68 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Table 15. Changes in groundwater storage after 50 years of groundwater use at different pumping rates for the Washita River alluvial 

aquifer, western Oklahoma.

50-year groundwateruse scenario

Groundwater 

storage at 

beginning of 

scenario, in 

acre-feet

Groundwater storage 

for last year of scenario, in acre-feet

Change in groundwater storage, in 

acre-feet

Change in groundwater storage, in percent

Mean change in 

groundwater levels, 

in feet

No groundwater use 544,556 545,249 693 0.1 0.1

2015 groundwaterpumping rate544,554 543,831 −723 −0.1 −0.1

Mean groundwaterpumping rate, 

1980–2015

544,551 543,202 −1,349 −0.2 −0.1

Increasing demand 

groundwaterpumping rate 

(38-percent increase 

compared to 2015)

544,551 542,584 −1,967 −0.4 −0.2

0

20

40

60

80

100

120

140

160

180

200

1,560

1,568

1,576

1,584

1,592

1,600

1,608

1,616

1,624

1,632

1,640

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Change in Foss Reservoir simulated storage, in percent

Simulated stage in Foss Reservoir, in feet above 

National Geodetic Vertical Datum of 1929 during

equal-proportionate-share groundwater pumping 

Year

EXPLANATION

Change in storage in Foss Reservoir

Foss Reservoir stage

Dead-pool stage

Note: Foss Reservoir stage and storage in year zero 

were 1,642 feet above National Geodetic Vertical 

Datum of 1929 and 168,732 acre-feet, respectively 

Figure 40. Simulated stage and change in simulated storage in Foss Reservoir during 20 years of continuous 

equal-proportionate-share groundwater pumping in the Washita River alluvial aquifer, western Oklahoma.
Groundwater-Availability Scenarios 69

Hypothetical (10-Year) Drought

A hypothetical (10-year) drought scenario was used to 

simulate the effects of a prolonged period of reduced recharge 

on groundwater storage in the Washita River alluvial aquifer and Foss Reservoir stage and storage. January 1983 to 

December 1992 was chosen as the drought period because 

mean annual base flows and recharge for that period were 

similar to those of the simulation period. Drought effects were 

quantified by comparing the results of the drought scenario to 

the calibrated model (no drought). To simulate the hypothetical drought, recharge in the calibrated model was reduced by 

50 percent during the simulated drought period. Upstream 

inflows to the Washita River and associated tributaries were 

reduced by 37 percent, which was the mean decrease in annual 

base flow during the drought from 1976 to 1981 (Shivers 

and Andrews, 2013). The simulation was continued 15 years 

past the end of the drought period through 2007 to assess the 

recovery of groundwater storage in the Washita River alluvial aquifer.

The rates of precipitation, evaporation, and surface runoff 

to Foss Reservoir were unchanged from the calibrated groundwater model. Observed reservoir releases for each month 

prior to and during the drought period were included in the 

simulation. To assess the recovery of Foss Reservoir stage following the drought period, reservoir releases were suspended 

until the stage reached the top of the active conservation pool 

(1,642 ft). Once this stage was reached, reservoir releases were 

again included in the simulation.

Groundwater storage at the end of the drought period 

in December 1992 was about 562,000 acre-ft, or about 

36,000 acre-ft (6 percent) less than the groundwater storage 

of the calibrated groundwater model (about 598,000 acre-ft) 

(fig. 41). Based on the 84,366-acre area used for modeling 

purposes and specific yield of 0.12, this change in groundwater storage was equivalent to a mean groundwater-level 

decline of 3.6 ft. By comparison, the drought conditions of 

2009–14 resulted in a mean simulated groundwater-level 

decline of 5.6 ft between January 2009 and December 2014, 

which can be seen in the mean annual change in groundwater 

Table 16. Changes in simulated mean annual base flow after 50 years of groundwater use at different pumping rates for the Washita 

River alluvial aquifer, western Oklahoma.

[ft3/s, cubic foot per second; See table 1 and figure 1 for streamgage information and location]

50-year groundwater-use scenario

Mean base flow for first 

year of scenario 

(ft3/s)

Mean base flow for 

last year of scenario 

(ft3/s)

Change in base flow 

(ft3/s)

Change in base flow 

(percent)

Mean annual base flow at the Cheyenne streamgage (07316500)

No groundwater use 20.2 19.8 0.49 −2.4

2015 groundwater-pumping rate 19.1 18.5 0.69 −3.6

Mean groundwater-pumping rate, 

1979–2015

18.5 17.6 0.9 −4.9

Increasing demand groundwaterpumping rate (38-percent increase 

compared to 2015)

18.5 16.8 1.7 −9.4

Mean annual base flow at the Hammon streamgage (07324200)

No groundwater use 32.5 32.3 0.2 −0.6

2015 groundwater-pumping rate 28.5 27.3 1.1 −4.0

Mean groundwater-pumping rate, 

1979–2015

28.2 26.6 1.6 −5.6

Increasing demand groundwaterpumping rate (38-percent increase 

compared to 2015)

28.2 24.5 3.6 −12.9

Mean annual base flow at the Clinton streamgage (07325000)

No groundwater use 65.3 65.0 0.3 −0.5

2015 groundwater-pumping rate 65.2 64.8 0.4 −0.6

Mean groundwater-pumping rate, 

1979–2015

64.9 64.5 0.4 −0.6

Increasing demand groundwaterpumping rate (38-percent increase 

compared to 2015)

64.9 64.4 0.6 −0.9
70 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

storage in figure 34B. Mean annual recharge during the hypothetical drought (1.3 in/yr) was greater than the mean annual 

recharge during the 2009–14 drought (0.7 in/yr) (fig. 34A).

At the end of the hypothetical drought, the largest 

changes in saturated thickness (as great as 43.5 ft) were 

in the area upgradient from Foss Reservoir, particularly in 

the terrace at the model boundary (fig. 42). Groundwater 

storage in the upgradient terrace was supplied entirely by 

recharge, so decreases in recharge have substantial effects on 

groundwater-level altitudes in the terrace areas. The decreased 

saturated thickness in some areas of the terrace caused a 

reduction in simulated well withdrawals as compared to the 

calibrated groundwater model. The saturated thickness of 

areas near the streams and associated tributaries changed 

little during the hypothetical drought; however, simulated 

base flows decreased at the Cheyenne, Hammon, and Clinton 

streamgages (fig. 43). Downgradient from Foss Reservoir, 

groundwater storage declines were moderated by GHB inflow 

from the Rush Springs aquifer and were typically less than 5 ft 

(fig. 42).

After 12 months of the hypothetical drought, simulated base flows at the Cheyenne, Hammon, and Clinton 

streamgages had decreased by about 45, 57, and 21 percent, 

respectively (fig. 43). At the end of the 10-year hypothetical drought period, simulated base flows at the Cheyenne, 

Hammon, and Clinton streamgages had decreased by about 55, 

73, and 42 percent, respectively. Simulated low-flow conditions in some months may be overpredicted during the drought 

scenario because periods of nearly zero flow periodically 

occur in the simulation period that could not be reproduced in 

the calibrated groundwater model.

Substantial decreases in the Foss Reservoir stage 

began during the fall of 1985 (fig. 44A) in conjunction with 

base-flow decreases of up to 100 percent at the Hammon 

streamgage (fig. 43B). These lake-stage declines outpaced 

groundwater-level declines in the surrounding aquifer. Annual 

lakebed seepage for Foss Reservoir was similar for the first 

5 years of the hypothetical drought compared to the nondrought conditions. The minimum stage in Foss Reservoir 

was 1,623 ft in March 1990 (fig. 44A), near the end of the 

hypothetical drought period, indicating a storage capacity of 

42 percent of active conservation pool storage. The minimum 

Foss Reservoir storage simulated during the drought period 

was 77,954 acre-ft, which was a decrease of 46 percent from 

the nondrought storage. Large precipitation events totaling 

11 in. during April and May 1993 (fig. 5) resulted in a stage 

recovery to 1,632 ft at Foss Reservoir by June 1993 (Bureau of 

Reclamation, 2018). Stage recovery to the top of the conservation pool did not occur until August 1996. Percent change in groundwater storage

Groundwater storage, in acre-feet

Year

55

50

45

40

35

30

25

20

15

10

5

0

–5

520,000 –10

530,000

540,000

550,000

560,000

570,000

580,000

590,000

600,000

610,000

620,000

630,000

640,000

650,000

1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Shaded area = simulated period of a 

hypothetical 10-year drought

EXPLANATION

Percent change in groundwater storage

Drought conditions

Nondrought conditions

Figure 41. Change in groundwater storage resulting from a hypothetical 10-year drought for the Washita River alluvial aquifer, 

western Oklahoma.
Creek

Dead

Warrior

Creek

Croton

Creek

Plum

Creek

Sergeant

Major Creek

Brokenleg

Creek

Wild

Horse

Creek

Cofer

Creek

Caffey

Creek

Rush

Creek

Turkey 

Creek

Wild

Horse

Creek

Quartermaster

Creek

Ninemile

Creek

Sandstone

Creek

Wildcat

Creek

Big

Kiowa

Creek

White

Turkey

Simulated change in saturated thickness, in feet,  after a hypothetical 10-year drought

–7.6 to –2.2

–2.1 to 0.4

0.5 to 2.4

2.5 to 5.2

5.3 to 9.29.3 to 13.4

13.5 to 23.723.8 to 43.5

EXPLANATION

ROGER MILLS 

COUNTY

CUSTER

COUNTY

BECKHAM

COUNTY

WASHITA

COUNTY

DEWEY

COUNTY

ELLIS COUNTY

Foss

Reservoir

100° 99°45' 99°30' 99°15' 

35°45'35°30'

TEXAS

OKLAHOMA

Aquifer boundary modified from Johnson 

Oklahoma Water Re

0 5 10 MILES0 5 10 KILOMETERS

FOSS DAM

Base from U.S. Geological Survey digital dataAlbers Equal-Area Conic projection; North American Datum 1983

Washita

River

River

Washita

Figure 42. Simulated change in saturated thickness after a hypothetical 10-year drought for the Washita River alluvial aquifer, western 
72 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

A.

–240

–210

–180

–150

–120

–90

–60

–30

0

0

15

30

45

60

75

90

105

120

Streamflow, in cubic feet per second

Chnage in streamflow, in percent

Shaded area = simulated period of a 

hypothetical 10-year drought

Shaded area = simulated period of a 

hypothetical 10-year drought

Shaded area = simulated period of a 

hypothetical 10-year drought

B.

–200

–180

–160

–140

–120

–100

–80

–60

–40

–20

0

0

30

60

90

120

150

180

210

240

270

300

Streamflow, in cubic feet per second

Chnage in streamflow, in percent

C.

–90

–75

–60

–45

–30

–15

0

0

200

400

600

800

1,000

1,200

1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Streamflow, in cubic feet per second

Year

Chnage in streamflow, in percent

Base flow, no drought

EXPLANATION

Base flow, drought

Percent change in streamflow

Base flow, no drought

EXPLANATION

Base flow, drought

Percent change in streamflow

No drought

EXPLANATION

Drought

Percent change in streamflow

Figure 43. Changes in simulated streamflow and base flow for the numerical groundwater-flow 

model of the Washita River alluvial aquifer at U.S. Geological Survey streamgages A, 07316500 

Washita River near Cheyenne, Okla.; B, 07324200 Washita River near Hammon Okla.; and C, 07325000 

Washita River near Clinton, Okla., western Oklahoma, 1980–2007.
Groundwater-Availability Scenarios 73

1,620

1,625

1,630

1,635

1,640

1,645

1,650

1,655

Foss Reservoir stage, in feet 

Shaded area = simulated period of a 

 hypothetical 10-year drought

Note: Foss Reservoir stage is stage reported 

on the last day of each month in the year

50,000

75,000

100,000

125,000

150,000

175,000

200,000

225,000

250,000

198019811982198319841985198619871988198919901991199219931994199519961997

Foss Reservoir storage, in acre-feet 

Year

Shaded area = simulated period of a 

 hypothetical 10-year drought

A.

B.

EXPLANATION

No drought

Hypothetical 10-year drought

Active conservation pool

 (normal pool)

Foss Reservoir stage in response to

EXPLANATION

No drought

Hypothetical 10-year drought

Active conservation pool

 (normal pool)

Foss Reservoir storage in response to

Figure 44. Changes in A, stage and B, storage for Foss Reservoir in response to a hypothetical 10-year drought for the Washita 

River alluvial aquifer, 1980–2007.
74 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Model Limitations

The Washita River alluvial aquifer groundwater model is 

a simplification of a complex groundwater-flow system and, 

therefore, incorporates necessary limitations and assumptions. The model contains features such as the StreamflowRouting package, the Lake package, and a grid size that may 

represent localized features, but the model is best used to 

support groundwater management decisions at a regional to 

sub-regional scale. The 36-year simulation period included 

hydrologic and climatic variability; however, results from the 

groundwater model may not be accurately representative of 

the variability found in past hydrologic conditions or representative of future climatic variability.

An uneven spatial and temporal distribution of watertable-altitude observations caused data gaps in the calibration 

data. Although the simulated water table in areas with a small 

number of observations occurs in a likely water-table-altitude 

range, more site-specific and local calibration-target data 

could facilitate a more detailed characterization of water-table 

conditions. Additionally, GHB inflows from the Rush Springs 

aquifer were based on the simulated water table of the Rush 

Springs aquifer (Ellis, 2018), and these inflows could be in 

error because relatively few groundwater-level observations 

were available for the Rush Springs aquifer adjacent to the 

Washita River alluvial aquifer.

The stream network used in the numerical model is a 

simplification of the actual stream geometry and hydraulic 

properties. Refined measurement of the stream channel width 

and streambed conductance at the local scale might improve 

the numerical model calibration because these factors control 

the amount of streambed seepage exchange with the aquifer. 

The numerical model was calibrated primarily to base-flow 

estimates; therefore, collection of more streamflow and baseflow data during other hydrologic conditions also could further 

reduce uncertainty in local-scale simulation results.

Exact amounts of annual groundwater use are unknown 

because groundwater wells are not metered, and groundwateruse data are based on estimates submitted to the OWRB by 

permit holders. Additionally, groundwater use by domestic wells, although assumed to be relatively small, was not 

included in the numerical model.
Summary 75

Summary

The Washita River alluvial aquifer is a saturated sand 

and gravel alluvial deposit along the valley of the Washita 

River in western Oklahoma that provides a productive source 

of groundwater for agricultural irrigation and water supply and is subdivided into reaches for appropriation. The 

Oklahoma Water Resources Board (OWRB) issued an order 

on November 13, 1990, that established the maximum annual 

yield (MAY; 120,320 acre-feet per year [acre-ft/yr]) and equalproportionate-share (EPS) pumping rate (2.0 acre-feet per acre 

per year) for reach 1 of the Washita River alluvial aquifer. The 

MAY and EPS were based on hydrologic investigations that 

evaluated the effects of potential groundwater withdrawals on 

groundwater availability in the Washita River alluvial aquifer. 

Every 20 years, the OWRB is statutorily required to update 

the hydrologic investigation on which the MAY and EPS were 

based. Because 30 years have elapsed since the last order was 

issued, the U.S. Geological Survey (USGS), in cooperation 

with the OWRB, conducted an updated hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the Washita 

River alluvial aquifer.

The Washita River alluvial aquifer is a long, narrow 

surficial aquifer that underlies the Washita River valley in 

Oklahoma from the western border with Texas southeast to 

near Lake Texoma, covering approximately 110 square miles 

(71,000 acres). The OWRB has designated the westernmost 

section of the aquifer in Roger Mills and Custer Counties, 

Okla., as reach 1 of the Washita River alluvial aquifer. 

The Washita River is the primary source of inflow to Foss 

Reservoir, a Bureau of Reclamation reservoir constructed 

in 1961 for flood control, water supply, and recreation; the 

reservoir provides water for Bessie, Clinton, New Cordell, 

and Hobart, Okla. During 1967–2015, nearly 98 percent of the 

total groundwater use from the Washita River alluvial aquifer was for irrigation, while other uses of groundwater in the 

study area include public supply, mining, and agriculture.

A hydrogeologic framework was developed for the 

Washita River alluvial aquifer and included the physical 

characteristics of the aquifer, the geologic setting, the characteristics and hydraulic properties of hydrogeologic units, the 

potentiometric surface, and groundwater-flow directions at a 

scale that captures the regional controls on groundwater flow. 

The Washita River alluvial aquifer consists of alluvium and 

terrace deposits that were transported primarily by water and 

range from clay to gravel in size. The terrace includes windblown deposits of silt size and, in some cases, contains gravel 

laid down at several levels along former courses of presentday rivers. Underlying the alluvium and terrace deposits in the 

westernmost part of the study area, the Ogallala Formation of 

Tertiary age consists of fine- to medium-grained brown to light 

tan sand with some clay, silt, gravel, volcanic ash, and caliche 

beds, with some beds locally cemented by calcium carbonate. 

Underlying the Washita River alluvial aquifer in the eastern 

part of the study area are bedrock units of Permian age that 

are reddish-brown and consist of the Elk City Member, Doxey 

Shale, Cloud Chief Formation, and Rush Springs Formation.

A conceptual flow model is a simplified description of 

the aquifer system that includes hydrologic boundaries, major 

inflow and outflow sources of the groundwater-flow system, 

and a conceptual water budget with the estimated mean flows 

between those hydrologic boundaries. Mean annual groundwater withdrawals (water use), predominantly from agricultural irrigation, during the study period 1980–2015 totaled 

5,502 acre-ft/yr, or 14 percent of aquifer outflows. When 

applied across the 132-square-mile area used for modeling 

purposes (84,366 acres), mean annual recharge of 3.15 inches 

per year corresponds to a mean annual recharge volume of 

22,169 acre-ft/yr, or 56 percent of aquifer inflows. If 16 percent (11,828 acres) of the active alluvium area (73,584 acres) 

had similar cover and depths to water, this rate would correspond to the annual saturated-zone evapotranspiration outflow 

of 11,828 acre-ft/yr for the Washita River alluvial aquifer, 

or about 30 percent of aquifer outflows. For the Washita 

River alluvial aquifer, lateral flow was 17,157 acre-ft/yr, or 

44 percent of the aquifer inflows. Lake seepage between Foss 

Reservoir and the Washita River alluvial aquifer is likely a 

small amount in terms of an aquifer budget and was not quantified for this study. The conceptual flow model and hydrogeologic framework were used to conceptualize, design, and build 

the numerical groundwater-flow model.

A numerical groundwater-flow model of the 

Washita River alluvial aquifer was constructed by using 

MODFLOW-2005. The Washita River alluvial aquifer 

groundwater-model grid was spatially discretized into 

384 rows and 927 columns containing 350-foot (ft) cells. Two 

layers were used to represent geologic units in the study area; 

layer 1 represented the undifferentiated alluvium and terrace 

deposits of Quaternary age with variable thickness determined 

from the hydrogeologic framework, and layer 2 represented 

the bedrock of Permian age which was given a uniform 

nominal thickness of 100 ft. The groundwater-simulation 

period was temporally discretized into 433 monthly transient 

stress periods with one time step each, representing the period 

January 1980 to December 2015. The monthly transient stress 

periods were used to capture seasonally variable processes 

such as recharge, saturated-zone evapotranspiration, and 

groundwater use. An initial 365-day steady-state stress period 

was configured to represent mean annual inflows and outflows 

from the Washita River alluvial aquifer for the study period. 

The groundwater-flow model was calibrated manually and by 

automated adjustment of model inputs using PEST++; both 

processes adjust initial model input values to improve the 

fit between model-simulated data and observed or estimated 

data (calibration targets). Calibration targets for the Washita 

River alluvial aquifer model included groundwater-level and 

reservoir-stage observations, as well as base-flow and streamseepage estimates.
76 Hydrogeology, Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer

Three groundwater-availability scenarios were formulated for the calibrated groundwater model. These scenarios 

were used to (1) estimate the EPS pumping rate that retains the 

saturated thickness that meets the minimum 20-year life of the 

aquifer, (2) quantify the effects of projected pumping rates on 

groundwater storage over a 50-year period, and (3) evaluate 

the effects of projected pumping rates extended 50 years into 

the future and sustained hypothetical drought conditions over 

a 10-year period on base flow and groundwater in storage. The 

results of the groundwater-availability scenarios could be used 

by the OWRB to reevaluate the established MAY of groundwater from the Washita River alluvial aquifer.

EPS scenarios for the Washita River alluvial aquifer 

were run for periods of 20, 40, and 50 years. The 20-, 40-, and 

50-year EPS pumping rates under normal recharge conditions

were 1.7, 1.6, and 1.6 acre-feet per acre per year, respectively. Given the aquifer area used for modeling purposes

(84,366 acres), these rates correspond to annual yields of

about 142,579, 134,986, and 134,986 acre-ft/yr, respectively.

Groundwater storage at the end of the 20-year EPS scenario

was about 281,000 acre-feet (acre-ft), or about 306,000 acre-ft

(52 percent) less than the starting storage. Considering the

84,366-acre model area and using a specific yield of 0.12, this

decrease in storage was equivalent to a mean groundwaterlevel decline of about 30 ft. This groundwater-level decline

was greater than the aquifer thickness in some areas of the

model where the aquifer was dewatered. The groundwaterlevel altitude in the aquifer was below the altitude of the

streambed during most of the EPS scenarios, thus promoting

seepage from streams to the aquifer. The Washita River downstream from Foss Reservoir and most of streams in the study

area were dry at the end of the 20-year EPS scenario. Foss

Reservoir stage was below the dead-pool stage of 1,597 ft

after about 7 years of pumping in the 20-year EPS scenario.

Projected 50-year groundwater-use scenarios were used 

to simulate the effects of selected well withdrawal rates on 

groundwater storage in the Washita River alluvial aquifer. The 

effects of withdrawals from wells were evaluated by comparing changes in groundwater storage among four 50-year 

scenarios using (1) no groundwater use, (2) groundwater use 

at the 2015 pumping rate, (3) mean groundwater use for the 

simulation period, and (4) increasing groundwater use. The 

increasing-use scenario assumed a 38-percent increase in 

pumping over 50 years based on 2010–60 demand projections for west-central Oklahoma. Groundwater storage after 

50 years with no groundwater use was 545,249 acre-ft, or 

693 acre-ft (0.1 percent) greater than the initial groundwater 

storage; this groundwater storage increase is equivalent to a 

mean groundwater-level increase of 0.1 ft. Groundwater storage at the end of the 50-year period with 2015 pumping rates 

was 543,831 acre-ft, or 723 acre-ft (0.1 percent) less than the 

initial storage; this groundwater storage decrease is equivalent 

to a mean groundwater-level decrease of 0.1 ft. Groundwater 

storage after 50 years with the mean pumping rate for the 

study period was 543,202 acre-ft, or 1,349 acre-ft 

(0.2 percent) less than the initial groundwater storage; 

this groundwater storage decrease is equivalent to a mean 

groundwater-level decrease of 0.1 ft. Groundwater storage 

at the end of the 50-year period with an increasing demand 

groundwater-pumping rate, which was 38 percent greater than 

the 2015 groundwater-pumping rate, was 542,584 acre-ft, 

or 1,967 acre-ft (0.4 percent) less than the initial storage; 

this groundwater storage decrease is equivalent to a mean 

groundwater-level decrease of 0.2 ft.

Mean annual base flow simulated at the USGS 

streamgage 07316500 Washita River near Cheyenne, Okla. 

(Cheyenne streamgage) decreased 0.49 ft3/s (2.4 percent) after 

50 years with no pumping and decreased 1.7 ft3/s (9.4 percent) 

after 50 years with an increasing demand pumping rate. Mean 

annual base flow simulated at the USGS streamgage 07324200 

Washita River near Hammon, Okla. (Hammon streamgage) 

decreased 0.2 ft3/s (0.6 percent) after 50 years with no pumping and decreased 3.6 ft3/s (13 percent) after 50 years with 

an increasing demand pumping rate. Mean annual base flow 

simulated at the USGS streamgage 07325000 Washita River 

near Clinton, Okla. (Clinton streamgage) decreased 0.3 ft3/s 

(0.5 percent) after 50 years with no pumping and decreased 

0.6 ft3/s (0.9 percent) after 50 years with an increasing demand 

pumping rate.

A hypothetical (10-year) drought scenario was used to 

simulate the effects of a prolonged period of reduced recharge 

on groundwater storage in the Washita River alluvial aquifer 

and Foss Reservoir stage and storage. Drought effects were 

quantified by comparing the results of the drought scenario to 

the calibrated model (no drought). To simulate the hypothetical drought, recharge in the calibrated model was reduced by 

50 percent during the simulated drought period (1983–1992). 

Upstream inflows to the Washita River and associated tributaries were reduced by 37 percent, which was the mean decrease 

in annual base flow during the drought of 1976–81. The 

simulation was continued 15 years past the end of the drought 

period through 2007 to assess the recovery of groundwater 

storage in the Washita River alluvial aquifer. Groundwater 

storage at the end of the drought period in December 1992 

was 562,000 acre-ft, or 36,000 acre-ft (6 percent) less than the 

groundwater storage of the calibrated groundwater model 

(598,000 acre-ft). This decrease in groundwater storage is 

equivalent to a mean water-table-altitude decline of 3.6 ft. By 

comparison, the drought conditions of 2009–14 resulted in a 

mean simulated groundwater-level decline of 5.6 ft between 

January 2009 and December 2014. At the end of the hypothetical drought, the largest changes in saturated thickness 

(as great as 43.5 ft) were in the area upgradient from Foss 

Reservoir, particularly in the terrace at the model boundary, whereas changes in saturated thickness downgradient 

from Foss Reservoir were moderated by inflow from the 

Rush Springs aquifer. After 12 months of the hypothetical 

drought, simulated base flows at the Cheyenne, Hammon, 

and Clinton streamgages had decreased by about 46, 57, and 

21 percent, respectively. At the end of the 10-year hypothetical drought period, simulated base flows at these streamgages 

had decreased by about 55, 73, and 42 percent, respectively. 
Selected References 77

Substantial decreases in the Foss Reservoir stage began during 

the fall of 1985 in conjunction with base-flow decreases of up 

to 100 percent at the Hammon streamgage. These lake-stage 

declines outpaced groundwater-level declines in the surrounding aquifer.

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Ellis and others—Hydrogeology, Numerical Simulation of Groundwater Flow, and Effects of Water Use and Drought, Washita River Alluvial Aquifer—SIR 2020–5118