Prepared in cooperation with the North Platte Natural Resources District

Simulation of Groundwater Flow and Analysis of the Effects 

of Water-Management Options in the North Platte Natural 

Resources District, Nebraska

Scientific Investigations Report 2015–5093

U.S. Department of the Interior

U.S. Geological Survey
Front cover. Sheep Creek, 2007. Photograph by Steven M. Peterson, U.S. Geological Survey.

Back cover. Canals in western Nebraska, 2012. Photographs provided by North Platte Natural Resources District.
Simulation of Groundwater Flow and 

Analysis of the Effects of WaterManagement Options in the North Platte 

Natural Resources District, Nebraska

By Steven M. Peterson, Amanda T. Flynn, Joseph Vrabel, and Derek W. Ryter

Prepared in cooperation with the North Platte Natural Resources District

Scientific Investigations Report 2015–5093

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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

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as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Peterson, S.M, Flynn, A.T., Vrabel, Joseph, and Ryter, D.W., 2015, Simulation of groundwater flow and analysis of 

the effects of water-management options in the North Platte Natural Resources District, Nebraska: U.S. Geological 

Survey Scientific Investigations Report 2015–5093, 67 p., http://dx.doi.org/10.3133/sir20155093.

ISSN 2328-0328 (online)
iii

Acknowledgments

This study was led as part of the U.S. Geological Survey (USGS) Cooperative Water Program and 

made possible by support provided by the Nebraska Natural Resources Commission Interrelated 

Water Management funds administered by the Nebraska Department of Natural Resources. The 

authors thank the North Platte Natural Resources District Board of Directors, Water Resources 

Committee, J. Berge, General Manager, and R. Cacek, former general manager, for providing 

thoughtful and insightful commentary on this work. 

The authors thank James Cannia (formerly USGS) and Dennis Strauch (Pathfinder Irrigation 

District) for assistance with identifying potential intentional recharge sites. The authors thank 

M. Fienen (USGS) for assistance with parameter estimation and R. Niswonger (USGS) for assistance with the Newton-Rhapson solver. The authors also thank P. Jones and P. Barlow (USGS) for 

constructive reviews of earlier versions of this report and P. Barlow for assistance with application of the Groundwater-Management Process.
iv

Contents

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

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

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

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

Previous Work .......................................................................................................................................2

Description of Study Area ...................................................................................................................4

Hydrogeology.........................................................................................................................................5

Simulation of Groundwater Flow...............................................................................................................12

Groundwater-Flow Model Design....................................................................................................12

Conceptual Model of Groundwater Flow...............................................................................12

MODFLOW Simulation ..............................................................................................................14

MODFLOW Processes Used to Implement the Conceptual Model..........................15

Recharge Estimated with Soil-Water-Balance Model ...............................................15

Inputs to the Soil-Water-Balance Model.............................................................16

Limitations of the Soil-Water-Balance Model ....................................................20

Recharge from Canal Seepage ......................................................................................20

Canal Mass Balance ...............................................................................................20

Estimation of Canal Seepage Potential using Available 

Geophysical Data .......................................................................................20

Combination of Canal Mass Balance Estimates and 

Estimated Seepage Potentials .................................................................22

Groundwater Withdrawals..............................................................................................22

Calibration............................................................................................................................................28

Calibration Approach and Parameters ..................................................................................28

Spatial Multipliers to Recharge......................................................................................30

Horizontal Hydraulic Conductivity Estimated at Pilot Points .....................................30

Temporal Multipliers to Recharge..................................................................................30

Specific Recharge Parameters ......................................................................................30

Calibration Targets.....................................................................................................................30

Groundwater-Level Targets.............................................................................................30

Base-Flow Targets............................................................................................................31

Calibration Results.....................................................................................................................31

Groundwater Levels .........................................................................................................33

Base Flows.........................................................................................................................34

Calibrated Parameters..............................................................................................................36

Spatial Multipliers to Recharge......................................................................................40

Horizontal Hydraulic Conductivity Estimated at Pilot Points .....................................40

Temporal Multipliers to Recharge..................................................................................40

Specific Recharge Parameters ......................................................................................40

Simulated Groundwater Budget.......................................................................................................40

Sensitivity.............................................................................................................................................44

Assumptions and Limitations............................................................................................................45

Post-Audit of Estimated Groundwater Withdrawals ....................................................................47
v

Effects of Water-Management Options ...................................................................................................47

Conceptual Approach ........................................................................................................................48

Construction of Future Period Model ..............................................................................................48

Optimization of the Future Period Model ........................................................................................49

Base-Case Simulations without Management ..............................................................................52

Simulations with Management of Groundwater Withdrawals ...................................................53

Simulations with Management of Groundwater Withdrawal and Intentional Recharge.......58

Analysis Limitations and Potential Areas for Additional Study...................................................60

Summary........................................................................................................................................................63

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

Figures

1. Map showing North Platte Natural Resources District groundwater-flow-model

study area in western Nebraska................................................................................................3

2. Map showing canals and surface-water-irrigated land in the study area, North

Platte River valley, Nebraska......................................................................................................5

3. Graph showing irrigated agricultural acres by irrigation water source and

registered wells within the study area, 1950–2008 .................................................................6

4. Map showing surficial geology of the study area...................................................................7

5. Map showing water-table altitude contours, 1995, North Platte River valley, Nebraska 8

6. Maps showing alluvial aquifer base altitude and saturated thickness, North Platte

River valley, Nebraska .................................................................................................................9

7. Map showing boundary conditions used for the groundwater-flow model as

indicated by model-cell types...................................................................................................13

8. Maps showing potential recharge estimated with the Soil-Water-Balance model

for irrigation seasons of 1958, 1964, and 1982........................................................................17

9. Graph showing annual total precipitation at Scottsbluff, Nebraska, and estimated

canal seepage, 1950–2008.........................................................................................................21

10. Map showing relative canal seepage-potential estimates computed from inversely

modeled OhmMapper resistivity profiles, North Platte River valley, Nebraska and

Wyoming, 2004 and 2007–09 .....................................................................................................23

11. Maps showing Canals within the North Platte River valley, Nebraska, and

distribution of annual canal seepage recharge for selected canals, 1950–2008,

North Platte River valley, Nebraska.........................................................................................24

12. Map showing land certified by North Platte Natural Resources District as irrigated

acres, 2008, North Platte River valley, Nebraska ..................................................................26

13. Graph showing growing season precipitation and estimated groundwater

withdrawals for irrigation, 1950–2008......................................................................................28

14. Graph showing estimated canal seepage and groundwater withdrawals for

irrigation, 1950–2008, North Platte River valley model area, Nebraska.............................29

15. Graph showing relation of pre-1950 model simulated groundwater levels, April

1950, to measured groundwater levels used as calibration targets, 1945–55..................34

16. Map showing spatial distribution of calibration residuals for simulated

groundwater level, April 1950, end of the pre-1950 model...................................................35

17. Graph showing relation of simulated groundwater levels to measured groundwater

levels used as calibration targets for the 1950–2008 model................................................36
vi

18. Map showing spatial distribution of average calibration residuals for simulated

water level for the 1950–2008 model .......................................................................................37

19. Graphs showing simulated and estimated base flow for North Platte River at

Wyoming-Nebraska State line, North Platte River at Bridgeport, Nebraska, Tub

Springs Drain near Scottsbluff, Nebraska, Red Willow Creek near Bayard,

Nebraska, Winters Creek near Scottsbluff, Nebraska, and Gering Drain near

Gering, Nebraska........................................................................................................................38

20. Map showing average calibrated canal seepage recharge rate by model cell,

acre-foot per year, in the calibrated simulation ....................................................................41

21. Map showing calibrated transmissivity, 2008, foot squared per day, and areas of

highest estimated hydraulic conductivity, North Platte River valley, Nebraska..............42

22. Graph showing sensitivity of parameter groups used for calibration ...............................45

23. Graph showing annual total precipitation and decadal-mean annual precipitation

for date ranges used to represent specified precipitation conditions, Scottsbluff,

Nebraska, 1950–2008..................................................................................................................48

24. Map showing North Platte Natural Resources District well-management zones,

analysis wells, intentional recharge sites, and maximum intentional recharge rates,

and streamgage used for optimization of the future period model ....................................50

25. Map showing optimized groundwater withdrawals by zone for the future model

with average precipitation; groundwater withdrawal rate reductions are relative to

the base-case scenario.............................................................................................................54

26. Map showing optimized groundwater withdrawals by zone for the future model

with below-average precipitation; groundwater withdrawal rate reductions are

relative to the base-case scenario..........................................................................................55

27. Map showing optimized groundwater withdrawals by zone for the future model

with above-average precipitation; groundwater withdrawal rate reductions are

relative to the base-case scenario..........................................................................................56

28. Map showing optimized simulated intentional recharge by site and simulated

groundwater withdrawals by well-management zone for the future model with

average precipitation; groundwater withdrawal rate reductions are relative to the

base-case scenario....................................................................................................................59

29. Map showing optimized intentional recharge and groundwater withdrawals by

zone for the future model with below-average precipitation; groundwater

withdrawal rate reductions are relative to the base-case scenario.................................61

30. Map showing optimized intentional recharge and groundwater withdrawals by

zone for the future model with above-average precipitation; groundwater

withdrawal rate reductions are relative to the base-case scenario.................................62
vii

Tables

1. Thirteen canals for which annual recharge rates were estimated ...................................20

2. Summary of estimated base flows used as calibration targets for the 1950–2008

model ............................................................................................................................................32

3. Summary of simulated base flows for streams without streamgages within the

study area, for the 1950–2008 model .......................................................................................33

4. Summary of average simulated annual groundwater budgets for pre-1900, 1900–50,

and 1950–89 and average simulated seasonal budgets for irrigation seasons during

1989–2007 and non-irrigation seasons during 1989–2008 ....................................................43

5. Summary of optimization model results for simulated stream base flow under

below-average, average, and above-average precipitation, with and without

optimized groundwater withdrawals and intentional recharge, September 30, 2018,

from simulation of 2008–19........................................................................................................52

6. Summary of optimization model results for simulated management

scenarios—groundwater withdrawals by management zone and optimized

intentional-recharge rates, September 30, 2018, from simulation of 2008–19..................52

7. Response coefficients of decision variables at time step when the binding

streamflow constraint in the optimization model was evaluated, from simulation of

2008–19 .........................................................................................................................................57
viii

Conversion Factors

Inch/Pound to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2

)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2

)

 acre 0.004047 square kilometer (km2

)

square foot (ft2

) 0.09290 square meter (m2)

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2)

 Volume

cubic foot (ft3

) 28.32 cubic decimeter (dm3)

 cubic foot (ft3

) 0.02832 cubic meter (m3)

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

)

acre-foot (acre-ft) 0.001233 cubic hectometer (hm3

)

 Flow rate

inch per year (in/yr) 2.54 centimeter per year (cm/yr)

inch per day (in/d) 2.54 centimeter per day (cm/d)

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

cubic foot per second (ft3

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

Hydraulic conductivity

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

Transmissivity*

 foot squared per day (ft2

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

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

°C=(°F-32)/1.8
ix

Supplemental Information

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

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

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

Datums

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

(NAVD 88).

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

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

Simulation of Groundwater Flow and Analysis of the 

Effects of Water-Management Options in the North Platte 

Natural Resources District, Nebraska

By Steven M. Peterson, Amanda T. Flynn, Joseph Vrabel, and Derek W. Ryter

Abstract

The North Platte Natural Resources District (NPNRD) 

has been actively collecting data and studying groundwater 

resources because of concerns about the future availability 

of the highly inter-connected surface-water and groundwater 

resources. This report, prepared by the U.S. Geological Survey 

in cooperation with the North Platte Natural Resources District, describes a groundwater-flow model of the North Platte 

River valley from Bridgeport, Nebraska, extending west to 

6 miles into Wyoming. The model was built to improve the 

understanding of the interaction of surface-water and groundwater resources, and as an optimization tool, the model is 

able to analyze the effects of water-management options on 

the simulated stream base flow of the North Platte River. The 

groundwater system and related sources and sinks of water 

were simulated using a newton formulation of the U.S. Geological Survey modular three-dimensional groundwater 

model, referred to as MODFLOW–NWT, which provided 

an improved ability to solve nonlinear unconfined aquifer 

simulations with wetting and drying of cells. Using previously 

published aquifer-base-altitude contours in conjunction with 

newer test-hole and geophysical data, a new base-of-aquifer 

altitude map was generated because of the strong effect of 

the aquifer-base topography on groundwater-flow direction 

and magnitude. The largest inflow to groundwater is recharge 

originating from water leaking from canals, which is much 

larger than recharge originating from infiltration of precipitation. The largest component of groundwater discharge from 

the study area is to the North Platte River and its tributaries, with smaller amounts of discharge to evapotranspiration 

and groundwater withdrawals for irrigation. Recharge from 

infiltration of precipitation was estimated with a daily soilwater-balance model. Annual recharge from canal seepage 

was estimated using available records from the Bureau of 

Reclamation and then modified with canal-seepage potentials 

estimated using geophysical data. Groundwater withdrawals were estimated using land-cover data, precipitation data, 

and published crop water-use data. For fields irrigated with 

surface water and groundwater, surface-water deliveries were 

subtracted from the estimated net irrigation requirement, and 

groundwater withdrawal was assumed to be equal to any 

demand unmet by surface water.

The groundwater-flow model was calibrated to measured 

groundwater levels and stream base flows estimated using the 

base-flow index method. The model was calibrated through 

automated adjustments using statistical techniques through 

parameter estimation using the parameter estimation suite of 

software (PEST). PEST was used to adjust 273 parameters, 

grouped as hydraulic conductivity of the aquifer, spatial 

multipliers to recharge, temporal multipliers to recharge, and 

two specific recharge parameters. Base flow of the North 

Platte River at Bridgeport, Nebraska, streamgage near the 

eastern, downstream end of the model was one of the primary 

calibration targets. Simulated base flow reasonably matched 

estimated base flow for this streamgage during 1950–2008, 

with an average difference of 15 percent. Overall, 1950–2008 

simulated base flow followed the trend of the estimated base 

flow reasonably well, in cases with generally increasing or 

decreasing base flow from the start of the simulation to the 

end. Simulated base flow also matched estimated base flow 

reasonably well for most of the North Platte River tributaries with estimated base flow. Average simulated groundwater 

budgets during 1989–2008 were nearly three times larger for 

irrigation seasons than for non-irrigation seasons. 

The calibrated groundwater-flow model was used with 

the Groundwater-Management Process for the 2005 version 

of the U.S. Geological Survey modular three-dimensional 

groundwater model, MODFLOW–2005, to provide a tool for 

the NPNRD to better understand how water-management decisions could affect stream base flows of the North Platte River 

at Bridgeport, Nebr., streamgage in a future period from 2008 

to 2019 under varying climatic conditions. The simulationoptimization model was constructed to analyze the maximum 

increase in simulated stream base flow that could be obtained 

with the minimum amount of reductions in groundwater 

withdrawals for irrigation. A second analysis extended the 

first to analyze the simulated base-flow benefit of groundwater 

withdrawals along with application of intentional recharge, 

that is, water from canals being released into rangeland areas 

with sandy soils. With optimized groundwater withdrawals 
2 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

and intentional recharge, the maximum simulated stream base 

flow was 15–23 cubic feet per second (ft3

/s) greater than with 

no management at all, or 10–15 ft3

/s larger than with managed 

groundwater withdrawals only. These results indicate not only 

the amount that simulated stream base flow can be increased 

by these management options, but also the locations where 

the management options provide the most or least benefit 

to the simulated stream base flow. For the analyses in this 

report, simulated base flow was best optimized by reductions 

in groundwater withdrawals north of the North Platte River 

and in the western half of the area. Intentional recharge sites 

selected by the optimization had a complex distribution but 

were more likely to be closer to the North Platte River or its 

tributaries. Future users of the simulation-optimization model 

will be able to modify the input files as to type, location, and 

timing of constraints, decision variables of groundwater withdrawals by zone, and other variables to explore other feasible 

management scenarios that may yield different increases in 

simulated future base flow of the North Platte River.

Introduction

The North Platte Natural Resources District (NPNRD, 

fig. 1) has been actively collecting data and studying groundwater resources because of concerns about the future availability of the highly interconnected surface-water and groundwater resources. Development of surface water for irrigation 

by using canal systems primarily took place before 1900 (State 

Board of Irrigation, 1899), and much of the modern groundwater reservoir exists because seepage of water through the 

unlined bottoms of canals caused increases in groundwater 

levels (Verstraeten and others, 2001).

The area experiences low precipitation and was predominantly rangeland through the 19th century. Early in the 20th 

century, the Bureau of Reclamation began the North Platte 

River project to facilitate surface-water irrigation in the North 

Platte River valley. The project supplies surface water for irrigation of approximately 335,000 acres (Autobee, 1996). Seepage of canal water into the subsurface provided substantial 

recharge to the groundwater system, far more than that from 

precipitation alone. By the mid-20th century, groundwater 

withdrawals for irrigation became feasible in the area, and 

developed land area steadily increased to about 470,000 acres 

irrigated with surface water, with groundwater, or with both 

(R. Kern, Nebraska Department of Natural Resources, written 

commun., 2000; J. Sprock, North Platte Natural Resources 

District, written commun., 2010; J. Lawson, Bureau of Reclamation, written commun., 2010). Around 2002, the NPNRD 

enacted a moratorium on development of new wells (North 

Platte Natural Resources District, 2009). During 2001–2007, 

droughts in the area affected streamflows and the amount of 

water available for canal deliveries. Additionally, water supplies in the North Platte River Basin have been declared overappropriated (Nebraska Legislature, 2004), which means that 

under certain conditions, the amount of surface water needed 

for irrigation may exceed what is available. Within Nebraska, 

the NPNRD is at the upstream end of the Platte River system, 

and many downstream water users depend on river discharge 

exiting the NPNRD. A groundwater-flow model will help 

water resource managers better understand the interrelated 

groundwater and surface-water systems and the effects of 

various management strategies on the stream base flow (the 

groundwater-discharge component of streamflow) of the 

North Platte River. To address this need, the U.S. Geological 

Survey (USGS) in cooperation with the North Platte Natural 

Resources District, constructed a groundwater-flow model and 

analyzed simulation results to specifically help the NPNRD 

determine what management activities will provide the largest 

increases to the base flow at the North Platte River at Bridgeport, Nebr., streamgage.

Purpose and Scope

This report describes a groundwater-flow model of the 

North Platte River valley from Bridgeport, Nebr., extending west to 6 miles (mi) into Wyoming (fig. 1). This report 

describes the construction and calibration of the groundwaterflow simulation and the analysis of the effects of watermanagement options on stream base flow for the North Platte 

River valley in western Nebraska. The report also describes 

the inputs for the simulation, calibration approach, and calibration results. Lastly, the report describes the results of simulation-optimization models used to evaluate the effects of reductions in groundwater withdrawals and the addition of water 

diverted from the canals to adjacent sandy rangeland areas 

(referred to as ‘intentional recharge’) on simulated base flow 

at the North Platte River at Bridgeport, Nebr., streamgage.

Previous Work

Previous studies in the area include regional groundwater-flow models, geophysical investigations of aquifer and 

canal properties, and studies of groundwater age and quality. The Cooperative Hydrologic Study (COHYST) Western 

Model Unit (Luckey and Cannia, 2006) published a groundwater-flow model that spanned about 11,300 square miles 

(mi2

) of western Nebraska, from Lake McConaughy (fig. 1) to 

6 mi into Wyoming in the west. The regional model included 

estimated seepage of the canal systems in the North Platte 

River valley. An earlier report for the same study area documented estimated rates of groundwater discharge to streams 

(Luckey and others, 2001).

Canal systems in western Nebraska, including canal 

systems in the study area, have been the focus of multiple 

surface-geophysical resistivity studies (Ball and others, 2006; 

Burton and others, 2009; and Vrabel and others, 2009). Sediment grain-size variations cause variations in seepage (leakage) rates along the canal systems. The resistivity studies were 

aimed at gathering more information on the sediments along 
Introduction 3

Figure 1. North Platte Natural Resources District (NPNRD) groundwater-flow-model study area in western Nebraska.

Kiowa Creek

Winters Creek

Horse Creek

Dry Creek Drain

Sheep

Creek

Dry Sheep

Creek

Dry Spottedtail Creek Spottedtail Creek

Owl Creek

North Platte River North Platte River

Indian Creek

Tub Springs Drain

Ninemile Creek

Horse Creek

NEBRASKA

KANSAS

SOUTH DAKOTA

IOWA

COLORADO

WYOMING

North Platte Natural Resources District boundary

Study area

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTY

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

WYOMING

NEBRASKA

1

2

3

4

5 6

7

8

9

10

11

12

13

EXPLANATION

1. 06674500

2. 06677500

3. 06778000

4. 06679000

5. 06679500

6. 06680000

7. 06681000

8. 06681500

9. 06682000

10. 06682500

11. 06683000

12. 06684000

13. 06684500

Study area

Streamgage used for calibration and map number

Lake

Alice

Lake

Minatare

Melbeta

Drain

Gering

Drain Wildhorse Drain Bayard Drain

104°10’ 104°00’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’ 103°00’

42°10’

42°00’

41°50’

41°40’

Minatare

Henry

Lyman

Gering

Bayard

McGrew

Morrill

Melbeta

Mitchell

Terrytown

Bridgeport

Scottsbluff

Red Willow

Creek

Browns

Canyon

North Platte River at Wyoming-Nebraska State line

Horse Creek near Lyman, Nebraska

Sheep Creek near Morrill, Nebraska

Dry Spottedtail Creek at Mitchell, Nebraska

North Platte River at Mitchell, Nebraska

Tub Springs Drain near Scottsbluff, Nebraska

Winters Creek near Scottsbluff, Nebraska

Gering Drain near Gering, Nebraska

North Platte River near Minatare, Nebraska

Ninemile Creek near McGrew, Nebraska

Bayard Drain near Bayard, Nebraska

Red Willow Creek near Bayard, Nebraska

North Platte River at Bridgeport, Nebraska

12

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

North Platte River

South Platte River

Platte River

Lake McConaughy
4 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

the canal systems to better understand the seepage rates. The 

resistivity studies used geostatistics on the highly detailed 

spatial resistivity data along with lithologic data to determine 

the seepage potential for the surveyed areas. Additionally, 

geophysical studies in the study area also include multiple 

heliborne electromagnetic surveys (Smith and others, 2010).

Additional groundwater studies focused on hydrologic 

characteristics, and groundwater age and quality have been 

researched in the study area (Steele and Cannia, 2003; Steele 

and others, 1998; Steele and others, 2001; Steele and others, 

2002; Verstraeten and others, 1995). Groundwater and surfacewater interaction also was investigated for parts of the study 

area by Verstraeten and others (2001).

Description of Study Area

The study area covers 1,200 mi2 of the North Platte River 

valley in western Nebraska. The western boundary is 6 mi 

west of the Wyoming-Nebraska border, and the eastern boundary is 5 mi southeast of Bridgeport, Nebr. The northern and 

southern boundaries of the study area follow the edges of the 

river valley floor (fig. 1).

The North Platte River runs generally from west to east 

through the study area (fig. 1). Streams flow from the upland 

areas north and south of the river toward the river valley. Flow 

of the North Platte River is affected by releases from reservoirs in Wyoming, by local precipitation, and by gains from 

base-flow streams within the area. Headwaters of the North 

Platte River and Horse Creek are west of the study area, and 

these streams have sustained year-round flow across the western boundary into the study area. The rest of the streams originate inside the study area and discharge as tributaries to the 

North Platte River. Streamgages are shown in figure 1; four 

of the streamgages are on the North Platte River and nine are 

on tributary streams. The tributary streams are Horse Creek, 

Sheep Creek, Dry Spottedtail Creek, Tub Springs Drain, Winters Creek, Gering Drain, Ninemile Creek, Bayard Drain, and 

Red Willow Creek. During 1950–2007, average daily mean 

flow for the North Platte River at the Nebraska-Wyoming State 

line streamgage was about 750 cubic feet per second (ft3

/s), 

ranging from 0 to 9,700 ft3

/s, and average daily mean flow 

for the North Platte River at Bridgeport, Nebr., streamgage, 

near the eastern edge of the study area, was about 1,200 ft3

/s, 

ranging from 60 to 14,500 ft3

/s. The largest tributaries to the 

North Platte River are Ninemile Creek, Red Willow Creek, 

and Horse Creek. Average 1950–2007 daily mean flow was 

110 ft3

/s for Ninemile Creek (streamgage number 06682500), 

91 ft3

/s for Red Willow Creek (streamgage number 06684000), 

and 80 ft3

/s for Horse Creek (streamgage number 06677500). 

During 1950–2007, average daily mean flow for the remainder 

of the tributaries of the North Platte River was about 47 ft3

/s; 

the lowest flow was 24 ft3

/s for Bayard Drain (streamgage 

number 06683000; U.S. Geological Survey, 2012).

The study area receives about 15 inches (in.) of precipitation per year (1895–2008 average; National Climatic 

Data Center, 2009), creating a semiarid environment (Peel 

and others, 2007). Generally, annual precipitation consists of 

rainstorms early in the summer, with scattered storms throughout the summer (National Climatic Data Center, 2009). A 

smaller fraction of the annual precipitation arrives as snow 

throughout the winter. The summer highs can reach more than 

100 degrees Fahrenheit (°F), and winter lows can reach less 

than 10 °F (National Climatic Data Center, 2009). The average 

precipitation does not generally sustain crops in the area (University of Nebraska, 2002). Irrigation was developed to sustain 

agricultural development as population expanded westward 

(State Board of Irrigation, 1899).

Increased agricultural development in the 19th century 

led to the construction of extensive canal systems in the area, 

many as early as 1895 (State Board of Irrigation, 1899). Most 

canals are parallel to the North Platte River and are located on 

the north side of the valley (fig. 2). About three-quarters of the 

study area is irrigated with surface water. The largest canals 

were operational by the beginning of the 20th century, and 

all the canals operating in 2012 were operating before 1950. 

Canals on the north side of the valley are dug into permeable 

silty sand, and a large part of the water diverted into the canals 

is lost through seepage and becomes recharge to groundwater. 

Many canals on the southern side of the valley have been dug 

into silty clay and do not lose as much water to the groundwater system as canals on the north side, based on analysis 

of data collected and presented in Burton and others (2009). 

This difference in seepage is reflected in the assigned seepage 

potential values for this simulation, as discussed in the “Estimation of Canal Seepage Potential using Available Geophysical Data” section of this report. 

Groundwater withdrawals for irrigation have increased 

since the first irrigation well was registered in 1934 (Nebraska 

Department of Natural Resources, 2008). Most registered irrigation wells in the study area were installed after 1950 (fig. 3). 

The number of irrigation wells increased gradually between 

1950 and 1989, as did the amount of agricultural land irrigated with only groundwater (R. Kern, Nebraska Department 

of Natural Resources, written commun., 2000). After 1989, 

the number of irrigation wells increased rapidly, but many of 

these wells were installed to provide supplemental water to 

fields already receiving surface water for irrigation (comingled 

acres). Supplemental irrigation wells allow land managers to 

apply groundwater for irrigation at times when surface water 

might not be available because of shortage or rotational scheduling, though currently (2012) little data exist to indicate how 

frequently the supplemental wells are used. 

Well installation was curtailed by the passage of new 

integrated-management water laws in 2004, commonly 

referred to as Nebraska Legislative Bill 962 (Nebr. Rev. 

Stat 46.2, 46.6, and 46.7). Under the new law, large areas 

of the NPNRD were declared over-appropriated (Nebraska 

Department of Natural Resources, 2004), which means that 

the usage of surface water in the area exceeds the amount 

of water available under certain conditions. The declaration 

further precluded construction of new irrigation wells or other 
Introduction 5

Figure 2. Canals and surface-water-irrigated land in the study area, North Platte River valley, Nebraska.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

Study area

Surface-water irrigated area

Canal

EXPLANATION

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

North Platte River

development of new irrigated acres and required development 

of an Integrated Management Plan by 2010 to address groundwater and surface-water resources in the NPNRD (Nebraska 

Legislature, 2004).

Hydrogeology

Principal surficial geologic units within the study area 

include alluvium and colluvium mixed with alluvium (fig. 4), 

primarily of Quaternary age. These geologic units compose the 

alluvial aquifer, which is the principal hydrogeologic unit in 

the study area. Several older geologic units do not exist within 

the study area but form flow boundaries. The oldest deposits 

in or near the area are fine-grained sediments of the Tertiaryage White River Group, that underlie the alluvial aquifer 

throughout the study area. Just outside the study area, the 

alluvial aquifer that exists in the valley has a limited saturated 

thickness and is laterally adjacent to fine-grained deposits of 

the Brule Formation of the Tertiary White River Group or 

fine-grained deposits of the Tertiary-age Arikaree Group, that 

overlies the Brule Formation where present (Swinehart and 

others, 1985). Tertiary-age Ogallala Group sediments also 

do not exist within the study area, having been completely 

removed through erosion (Lugn, 1935).
6 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Upper-Tertiary sediments present in the alluvial aquifer 

are mainly buried (and hence are not shown in fig. 4) and consist of coarse sand and gravel of the Broadwater Formation. 

The Broadwater Formation does not exist uniformly throughout the study area, but was deposited as channel-fill north 

of the North Platte River (Swinehart and others, 1985). The 

Broadwater Formation can be as much as 150 feet (ft) thick, 

but the upper part is usually unsaturated. 

The alluvium that comprises most of the alluvial aquifer 

in the study area is Quaternary or Upper Tertiary (Pliocene) in 

age, mostly sand and gravel, and chiefly were deposited in a 

fluvial setting (Gutentag and others, 1984; Cannia and others, 

2006; Luckey and Cannia, 2006). Colluvium mixed with alluvium include Quaternary sand, silt, and minor gravel located 

principally on the valley slopes (Swinehart and Diffendal, 

1997). Quaternary alluvium and colluvium inside the study 

area (fig. 4) are hydrologically contiguous and are hereinafter 

referred to as the alluvial aquifer. The alluvial aquifer contains 

small amounts of eolian dune sand and loess deposits, as well 

as isolated silt and clay deposits along the North Platte River 

valley (Verstraeten and others, 2001; Swinehart and others, 

1985). However, the silt and clay units are not continuous 

throughout the area and are only known to exist locally. The 

alluvial aquifer thins and pinches out against the valley walls 

outside the northern and southern boundaries of the study area 

(fig. 4).

The base of the aquifer, which is the surface where 

the oldest sediments composing the alluvial aquifer were 

deposited, is highly irregular and contains paleovalleys and 

ridges parallel or subparallel to the modern-day North Platte 

River. The regional direction of groundwater flow is from 

west-northwest to east-southeast. Locally, groundwater 

generally flows toward the North Platte River and toward the 

tributaries to the North Platte River (fig. 5). However, local 

bedrock topography strongly affects the direction and magnitude of groundwater flow at the local scale (Abraham and 

others, 2012). Paleoridges act as barriers to groundwater flow, 

and groundwater must rise to the altitude of the ridge top to 

resume downgradient flow. Many of the paleo-ridge tops are 

near or at land surface; thus, little aquifer thickness is present 

to transmit the over-topping groundwater (as depicted in Abraham and others, 2012). The paleoridges are not continuous and 

groundwater behind a paleoridge can also move laterally to 

resume downgradient flow to a gap in the paleoridge or to discharge to a tributary of the North Platte River that has eroded a 

channel through the ridge.

A new base-of-aquifer altitude map was generated to 

more accurately simulate the strong effect of the aquifer-base 

topography on groundwater-flow direction and magnitude. 

Aquifer-base-altitude contours from Cannia and others (2006) 

were revised using 925 test-hole logs from the Cooperative 

Hydrology Study (2003a), 33 test-hole logs from the Wyoming State Engineers Office (unpub. data, 2009), and selected 

data from Abraham and others (2012; fig. 6A). The data from 

Abraham and others (2012) are continuous resistivity profiles 

processed into altitude sections derived from airborne electromagnetic (AEM) data. These altitude sections were aggregated 

to a 10-acre spacing aligned with the 40-acre grid used for the 

groundwater-flow model documented in this report, resulting 

in 2,292 point averages of the aquifer-base altitude. Contours also were added at 50-ft intervals to depict the surface 

characteristics in greater detail. The revised contours and 

Figure 3. Irrigated 

agricultural acres by irrigation 

water source and registered 

wells within the study area, 

1950–2008. (Acres served 

by comingled supplies 

primarily use surface water 

for irrigation but also have 

groundwater available).

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0

20,000

40,000

60,000

80,000

100,000

120,000

1949 1959 1969 1979 1989 1999 2009

Total registered wells

Total irrigated land, in acres

Year

EXPLANATION

Lands with comingled water supply

Lands with groundwater supply only

Registered wells
Introduction 7

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTY

WYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Geology

Quaternary deposits

Alluvium and colluvium

Alluvium

Tertiary deposits

Ogallala Group

Arikaree Group

White River Group

Study area

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

aquifer-base-altitude data were used to interpolate a continuous alluvial aquifer-base-altitude map (fig. 6B). The 1995 

water-table altitude contours (fig. 5) and groundwater levels 

measured during 1990–1999 (described in the “Calibration 

Targets” section of this report) were together interpolated to 

construct a continuous surface and compared quantitatively 

to the revised aquifer-base-altitude map (fig. 6B) to generate 

a map of saturated thickness (fig. 6C). The thickest part of the 

aquifer lies along the center of the study area near the modern 

course of the North Platte River, and a discontinuous ridge 

separates the deposits from a second group of thicker deposits 

to the north. Saturated thickness is less than 25 ft in most of 

the rest of the area. Near the edges of the study area, some 

patches with saturated thicknesses exceeding 25 ft are in areas 

with little or no groundwater-level measurements; therefore, 

actual saturated thicknesses in those areas may differ substantially from that depicted in figure 6C. 

Figure 4. Surficial geology of the study area, modified from 

Cannia and others, 2006 and Swinehart and Diffendal, 1997.
8 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

4,050

4,100

4,150

3,800

4,200

3,750

4,300

3,700

4,250

4,400

4,200

4,150

4,300

4,050

4,400

4,100

3,950

4,400

4,000

3,900

4,350

3,850

4,250

4,450

4,350

4,600

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS Study area

COHYST water-level contour—Shows altitude

of water level, 1995. Contour interval 100 feet. 

Datum is North American Vertical Datum of

1988 (NAVD 88)

COHYST water-level contour—Shows altitude

of water level, 1995. Contour interval 50 feet. 

Datum is NAVD 88

UN-L, CSD water-level contour—Shows altitude

of water level, 1995. Contour interval 50 feet. 

Datum is NAVD 88

COHYST, Platte River Cooperative Hydrology

Study (Cooperative Hydrology Study, 2003b);

UN-L, CSD, University of Nebraska-Lincoln, 

Conservation and Survey Division, 2013 

3,750

3,700

EXPLANATION

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

North Platte River

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

Figure 5. Water-table altitude contours, 1995, North Platte River valley, Nebraska.
Introduction 9

Figure 6. Alluvial aquifer base altitude and saturated thickness, North Platte River valley, Nebraska. A) Locations of test holes and 

flight lines for lithologic and airborne electromagnetic (AEM) data used to refine the altitude contour map of the base of the alluvial 

aquifer; revised maps of (B) base of the alluvial aquifer, modified from Cannia and others, 2006; and (C) saturated thickness of the 

aquifer, calculated from an interpolated version of the 1995 water-table altitude contours and the revised map of base of the alluvial 

aquifer.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

Study area

Lithologic log from Platte River 

Cooperative Hydrology 

Study (COHYST)

Lithologic log from Wyoming 

State Engineers Office

Airborne electromagnetic data 

aggregated to 10-acre points 

(Abraham and others, 2012)

A

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)
10 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 6. Alluvial aquifer base altitude and saturated thickness, North Platte River valley, Nebraska. A) Locations of test holes and 

flight lines for lithologic and airborne electromagnetic (AEM) data used to refine the altitude contour map of the base of the alluvial 

aquifer; revised maps of (B) base of the alluvial aquifer, modified from Cannia and others, 2006; and (C) saturated thickness of the 

aquifer, calculated from an interpolated version of the 1995 water-table altitude contours and the revised map of base of the alluvial 

aquifer.—Continued

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS EXPLANATION

Study area

High: 4,626

Low: 3,413

Aquifer-base elevation, in feet 

above North American 

Vertical Datum of 1988

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

Modified from Cannia and others, 2006

B
Introduction 11

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

Study area

Saturated thickness, in feet

Measured water level, 

1990–99

Less than 25

26 to 50

51 to 75

76 to 100

101 to 150

151 to 200

201 to 250

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

C

Figure 6. Alluvial aquifer base altitude and saturated thickness, North Platte River valley, Nebraska. A) Locations of test holes and 

flight lines for lithologic and airborne electromagnetic (AEM) data used to refine the altitude contour map of the base of the alluvial 

aquifer; revised maps of (B) base of the alluvial aquifer, modified from Cannia and others, 2006; and (C) saturated thickness of the 

aquifer, calculated from an interpolated version of the 1995 water-table altitude contours and the revised map of base of the alluvial 

aquifer.—Continued
12 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Simulation of Groundwater Flow

This section of the report describes the simulation of 

groundwater flow for this study area, including the model 

design, model calibration, simulated groundwater budgets, 

model sensitivity to changes in calibration parameters, model 

assumptions and limitations, and a post-audit of estimated 

groundwater withdrawals.

Groundwater-Flow Model Design

This section of the report describes the conceptual model 

of groundwater flow for this study, how the conceptual model 

of flow was represented in the USGS modular three-dimensional groundwater model (MODFLOW) simulation, and 

spatial and temporal discretization of the simulation. This section also describes how selected inputs of the simulation were 

generated, including recharge estimated with a soil-waterbalance model, recharge from canal seepage, and groundwater 

withdrawals.

Conceptual Model of Groundwater Flow

A conceptual model is a narrative and graphical description of the groundwater-flow system being studied and is 

used to design the numerical model (Anderson and Woessner, 

1992). The conceptual model describes the hydrogeologic 

units, important sources and sinks of water, and the lateral and 

vertical extent of the flow system. A conceptual model further 

describes how the system is simplified, although retaining 

enough complexity so that the numerical model reproduces the 

behavior of the natural system. Stated another way, a conceptual model describes how the authors understand groundwaterflow processes in the area, where the water comes from and 

goes to, and what sources and sinks are most or least important 

to groundwater in the study area. A conceptual model is the 

theory of how a particular groundwater-flow system behaves, 

and the resulting numerical model is a test of how those 

theories, implemented in a simulation, reproduce measured or 

estimated hydrologic data representing actual behavior of the 

groundwater-flow system (Hill and Tiedeman, 2007).

Initial numerical models generally do not satisfactorily 

reproduce measured or estimated hydrologic data representing 

the natural behavior of the system (targets) but are improved 

through calibration and through refinement of the conceptual 

model (Hill and Tiedeman, 2007). Calibration means that the 

model inputs are adjusted to improve the match between simulated hydrology and targets. Generally, if an acceptable match 

between simulated flows and targets cannot be achieved with 

model inputs remaining in defensible ranges, an error or omission exists in the conceptual model (Anderson and Woessner, 

1992). If an error or omission exists, the conceptual model 

must be refined and additional data or components added. The 

refined theory is then similarly tested through implementation 

in the numerical model. Evaluation of the numerical model 

and the efficacy of that model in reproduction of measured or 

estimated hydrologic data representing the natural behavior of 

the hydrologic system provides feedback as to the accuracy 

of the theories contained in the conceptual model. As various 

theories are tested, a conceptual model will evolve during the 

course of a modeling study. For this study, the theorized conceptual model is described in this section of the report, and the 

data or estimates supporting these theories are described in the 

“MODFLOW Simulation” section of this report.

With regard to the physical configuration of the flow 

system, as described in the “Hydrogeology” section of this 

report, the alluvial aquifer in the study area is composed of 

Quaternary alluvium and a mixture of Quaternary alluvium 

and colluvium. The alluvial aquifer overlies fine-grained 

sediments of the Tertiary White River Group, most commonly 

the Brule Formation in this area. Research indicates that little 

groundwater flows between the alluvial aquifer and underlying fine-grained sediments of the Tertiary White River Group 

(J. Cannia, oral commun., 2008). The areas where the Brule 

Formation is massive and fractured and can yield water to the 

alluvial aquifer are discontinuous but have been previously 

mapped as part of the COHYST study (Cannia and others, 

2006). Fractured Brule Formation was not included as part 

of the modeled aquifer in this study because of the lack of 

continuity across the study area; therefore, the base of the 

alluvial aquifer is considered to be the base of the conceptual 

flow model.

The alluvial aquifer, shown by active model cells in 

figure 7 (active model cells also underlie the area of simulated 

evapotranspiration in figure 7), is thickest in the paleovalley in the center of the study area, and thins to 10 ft near the 

northern and southern boundaries, where the aquifer adjoins 

fine-grained sediments of the Tertiary White River Group 

or siltstone and volcanic ash of the Tertiary Arikaree Group 

(fig. 4). Because of the thinness of the alluvial aquifer near the 

north and south boundaries and the poor permeability of the 

Arikaree and White River Group sediments, little groundwater 

flow is assumed to cross these boundaries; therefore, the 

boundaries are considered no-flow boundaries as indicated by 

the edges of the active model cells shown in figure 7. Near the 

southeast part of the study area, the boundary is drawn parallel to the primary direction of groundwater flow, as shown in 

figure 5; thus, a no-flow boundary is appropriate in this area 

as well. Also, for most of the western boundary of the area, 

groundwater flow converges from the north and south toward 

the North Platte River, parallel to the boundary; thus, no-flow 

conditions are also appropriate. Near the North Platte River 

along the western boundary of the study area, groundwater 

flow is from west to east, and was represented using a specified water-level boundary (fig. 7). Groundwater inflows across 

the western boundary are limited to a small area and are 

thought to be a small component of the groundwater budget, 

consistent with simulated water budgets of a previous larger 

groundwater-flow model that included the study area (Luckey 

and Cannia, 2006). 
Simulation of Groundwater Flow 13

Figure 7. Boundary conditions used for the groundwater-flow model as indicated by model-cell types.

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Browns

Canyon

EXPLANATION

Study area

Specified water level

Stream

Active model cells

Evapotranspiration

Winters Creek

Kiowa Creek

Horse Creek

Dry Creek Drain

Sheep

Creek

Dry Sheep

Creek

Dry Spottedtail Creek Spottedtail Creek

Owl Creek

North Platte River North Platte River

Indian Creek

Tub Springs Drain

Ninemile Creek

Horse Creek

Melbeta

Drain

Gering

Drain Wildhorse Drain Bayard Drain

Red Willow

Creek

104°00’ 103°00’

42°00’

Unnamed

tributary

The simulation period of this model extends from presurface-water development (pre-1890) through 2008. Few 

hydrologic data exist for the early time periods of the model 

but it was assumed that before surface-water development 

for irrigation, groundwater was in a state of long-term equilibrium. Before 1890, inflows came from a small amount of 

recharge originating from infiltration of precipitation through 

the soil zone and reaching the water table. The assumption 

is that during this time (before development) groundwater 

discharge was primarily to the North Platte River and by 

evapotranspiration of shallow groundwater near the river. 

Most tributaries to the North Platte River were ephemeral and 

received no groundwater discharge before irrigation development (State Board of Irrigation, 1899).

During the 1890s, surface water was developed for irrigation and canals were constructed to deliver the water to agricultural lands. Leakage from the canal systems led to a large 

increase in the amount of recharge to the aquifer (State Board 

of Irrigation, 1899). The increased recharge likely caused 

large groundwater-level rises and an increase of groundwater 
14 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

discharge to the North Platte River. Once the water table rose 

enough to intersect the tributaries, they also likely became 

focal points of groundwater discharge, and many became 

perennial within a few decades of extensive surface-water 

development (Luckey and Cannia, 2006). In more recent 

times, such as 2008, the largest inflow to groundwater was 

recharge originating from water leaking from canals and at a 

rate that is thought to be much larger than that from recharge 

originating from infiltration of precipitation, consistent with 

data presented by Verstraeten and others (2001). The increased 

rate of recharge following canal emplacement caused perennial base flow in the streams that did not take place before 

emplacement of the canals (State Board of Irrigation, 1899). 

Based on interpretations from a 1995 water-table altitude 

map (fig. 5), little groundwater flows across study area boundaries, and only in one area. Groundwater flows across the 

boundary primarily from west to east, a short distance north 

and south of the North Platte River (the area of specified water 

levels in fig. 7). This cross-boundary flow is a far smaller 

source of inflows to the model area than is recharge.

The largest component of groundwater discharge from 

the study area is to the North Platte River and its tributaries, 

with smaller amounts of discharge by evapotranspiration and 

groundwater withdrawals for irrigation. The earliest groundwater wells for irrigation in the study area were drilled before 

1940; however, there were fewer than 200 wells by 1950 

(Nebraska Department of Natural Resources, 2008). Therefore, groundwater withdrawals for irrigation likely were not a 

large component of groundwater discharge by 1950. Groundwater withdrawals for irrigation remained a small component 

of total groundwater outflows in 2008, though they increased 

during 1950–2008 and especially during the 2001–07 drought 

(fig. 3). The hypothesis that groundwater withdrawals for 

irrigation remained a small component of total groundwater 

discharge was subjected to further investigation during this 

study; see the “Groundwater Withdrawals” and “Simulated 

Groundwater Budget” sections of this report for additional 

explanation. Recharge from canal seepage and groundwater 

withdrawals for irrigation takes place primarily during the 

irrigation season, from approximately May 1 through September 30 each year.

MODFLOW Simulation

A newton formulation of the 2005 version of the USGS 

modular three-dimensional groundwater model, MODFLOW–NWT version 1.0.7 (Niswonger and others, 2011), 

was selected as the groundwater-flow modeling code for this 

study. MODFLOW–NWT is a version of MODFLOW with 

an improved ability to solve nonlinear unconfined aquifer 

simulations with wetting and drying of cells by applying the 

Newton-Rhapson linearization approach to solving the flow 

equations (Niswonger and others, 2011). Given the thinness 

of the aquifer near the sides of the valley, the possibility exists 

that the water table would drop to the cell bottom occasionally 

during the simulation, that in prior versions of MODFLOW 

would result in the cell being converted to inactive and being 

removed from the simulation (Harbaugh, 2005). MODFLOW–

NWT avoids this problem and improves convergence and 

computational efficiency for unconfined groundwater-flow 

models with nonlinear features.

A model grid was built to cover the study area. Each 

grid cell was 1,320 by 1,320 ft (40 acres). The grid comprised 

227 rows and 308 columns. Active cells were bounded by 

the edges of the valley and alluvial aquifer to the north and 

south, by a line 6 mi west of the State line to the west, and for 

a small section of the eastern boundary, by a no-flow boundary parallel to the primary groundwater-flow direction. The 

model consisted of one layer, simulated as unconfined, with 

19,170 active cells. Generally, the top altitude of the model 

does not matter in an unconfined simulation; however, the 

top altitude of this model was set to an altitude (500 ft above 

the aquifer base) much higher than the expected water-table 

altitudes to prevent cells from inadvertently being simulated 

as confined flow conditions, particularly during early stages of 

model development.

The two primary development periods in the area were 

each represented by a model; the period before substantial 

groundwater withdrawals (the pre-1950 model) and the period 

of increasing groundwater withdrawals from May 1950 

through April 2008 (the 1950–2008 model). The pre-1950 

model was built with a steady-state stress period and a transient stress period. The steady-state stress period was used to 

simulate long-term equilibrium ending at 1900, slightly after 

surface-water development became widespread in the area. 

The transient stress period, representing 1900–50, was used to 

simulate the period of surface-water irrigation development in 

the area, using 500 time steps, or 10 per year. The 1950–2008 

model was built with 77 stress periods starting in 1950, the 

approximate date when groundwater withdrawals for irrigation began. The 1950–2008 model used annual stress periods 

through 1988 and seasonal (irrigation and non-irrigation) 

stress periods for 1989 into 2008. The seasonal stress periods 

used to simulate 1989 into 2008 allowed for simulation of the 

seasonal differences in recharge that result from canal seepage 

and groundwater withdrawals for irrigation. Generally, canal 

seepage and groundwater withdrawals take place during the 

irrigation season (May 1 through September 30). Seasonal differences in canal seepage and groundwater withdrawals have 

existed throughout the history of irrigation development, but 

the differences were represented using average annual rates for 

stress periods used for 1988 and earlier simulations, also when 

the fewest data were available to calibrate the models. The 

increased temporal detail (seasonal stress periods) were used 

from 1989–2008 to calibrate effects of seasonal differences 

in the model outputs in the simulated period when the most 

calibration-target data were available. 

All stress periods simulated during the 1950–2008 model 

used 30 time steps, which were about 12.2 days each for the 

annual stress periods, 5.1 days per time step for the irrigation 

season stress periods, and 7.1 days per time step for the nonirrigation-season stress periods.
Simulation of Groundwater Flow 15

MODFLOW Processes Used to Implement the Conceptual 

Model

Standard MODFLOW components of the GroundwaterFlow Process that were used in the model included the Basic 

Package, Output Control Option, Discretization File, and 

the List file (Harbaugh and others, 2000). Recharge from 

precipitation and recharge from canal seepage were summed 

and simulated with the Recharge Package. Methods used to 

estimate recharge for the model are described in the “Recharge 

Estimated with the Soil-Water-Balance Model” and “Recharge 

from Canal Seepage” sections of this report. The Upstream 

Weighting Package was used because it is required when using 

the Newton Solver (NWT). The Upstream Weighting Package specifies properties controlling flow between cells, such 

as hydraulic conductivity, anisotropy, specific storage, and 

specific yield. Initial values for hydraulic conductivity were 

from Cannia and others (2006) and ranged from 10 to 350 foot 

per day (ft/d) with a mean of 162 ft/d. Initial hydraulic conductivity was adjusted during calibration as described in the 

“Horizontal Hydraulic Conductivity Estimated at Pilot Points” 

section of this report. Horizontal anisotropy was set to 1.0 (no 

anisotropy). Specific storage was set to 10e-5 ft-1 similar to 

Luckey and Cannia (2006) and was not adjusted during calibration. Specific yield (dimensionless) was from Cannia and 

others (2006), ranged from 0.1 to 0.3 with a mean of 0.18, and 

was not adjusted during calibration. 

The Evapotranspiration Package was used to simulate 

evapotranspiration in areas of active model cells where the 

water table is shallow (fig. 7). The evapotranspiration (ET) 

extinction depth was set to 7 ft (as used by Luckey and Cannia, 2006), and the maximum ET rate was set to 0.004 ft/d, or 

about 17.5 inches per year (in/yr), similar to but slightly larger 

than that used by Luckey and Cannia (2006). The Flow and 

Head Boundary Package was used to simulate specified water 

levels in the small area of cross-boundary groundwater flow 

at the western boundary of the model (fig. 7). Specified water 

levels were derived from the 1995 water-table altitude map 

(fig. 5).

The Streamflow-Routing Package was used to simulate streams, including the North Platte River, Sheep Creek, 

Dry Sheep Creek, Dry Spottedtail Creek, Spottedtail Creek, 

Tub Springs Drain, Winters Creek, Ninemile Creek, Bayard 

Drain, Wildhorse Drain, Red Willow Creek, Indian Creek, 

Horse Creek, Dry Creek Drain, Kiowa Creek, Owl Creek, 

an unnamed tributary in Browns Canyon, Gering Drain, and 

Melbeta Drain (fig. 7). The simulated streams were selected 

to represent the stream reaches coded as long-term average perennial reaches in the National Hydrography Dataset 

(U.S. Geological Survey, 2008). Additional simulated streams 

were selected based on field observations of persons familiar 

with the area (J. Cannia, oral commun., 2007) and based on 

observations of the authors during October 2007 and March 

2009. Horse Creek and the North Platte River are the only 

streams that originate outside the study area; streamflows in 

these two streams at the model boundary were specified on 

the basis of their monthly average streamflows for April (for 

irrigation seasons) and October (for non-irrigation seasons; 

U.S. Geological Survey, 2012). Simulated stream widths 

were estimated using aerial photographs (Dollison, 2010) and 

ranged from 10 to 45 ft for tributaries and from 117 to 346 ft 

for the North Platte River. Streambed hydraulic conductivity was evaluated during initial testing and set to 10 ft/d for 

tributaries and 15 ft/d for the North Platte River. Moderate 

changes in streambed hydraulic conductivity only caused 

small changes in simulated stream base flows, so streambed 

hydraulic conductivity was not adjusted during calibration. 

The Gage Package was used to output simulated stream base 

flows at target locations into separate formatted files.

The Well Package was used to simulate groundwater 

withdrawals for irrigation. Calculation of groundwater withdrawal rates is described in the “Groundwater Withdrawals” 

section of this report.

Recharge Estimated with Soil-Water-Balance Model

The Soil-Water-Balance (SWB) model (Dripps and 

Bradbury, 2007; Westenbroek and others, 2010) was used to 

calculate recharge from precipitation for this study for pre1950 and 1950–2008. The SWB model uses spatially distributed soil and landscape properties with daily weather data to 

calculate spatial and temporal variations in potential recharge. 

The SWB model (Westenbroek and others, 2010) uses a grid, 

in this case the same as that used for the groundwater-flow 

model. Soil properties and daily climate data were assigned to 

each model cell. The SWB model calculates the fractions of 

precipitation and snowmelt that become surface runoff, ET, 

and recharge using a modified Thornthwaite-Mather soil-water 

accounting method to track the soil water in each cell through 

time (Thornthwaite and Mather, 1957; Westenbroek and others, 2010). Potential recharge, represented in the SWB model 

by deep percolation, is surplus water in the soil column, which 

extends from land surface to the bottom of the root zone. Surplus water is calculated by subtracting the sum of the outputs 

(plant interception, surface runoff out of the cell to adjacent 

cells, and ET) from the inputs (precipitation, snowmelt, and 

surface runoff into the cell from adjacent cells) and accounting 

for change in soil moisture:

 R = (P + SNO + ROin) – (Pint + ROout + ET) – ΔSsoil (1)

where 

R is daily potential recharge, 

P is precipitation, 

SNO is snowmelt, 

ROin is surface runoff into the cell, 

Pint is plant interception, 

ROout is surface runoff out of the cell, 

ET is evapotranspiration, and 

ΔSsoil is the change in soil moisture.
16 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Inputs to the Soil-Water-Balance Model

Physical factors that control flow and loss of water on the 

ground surface and within the soil include the available water 

capacity of the soil, soil type (hydrologic group), land use and 

land cover, and direction of surface-water flow, which is used 

for routing runoff. Soil properties were derived from the General Soil Map (STATSGO2; U.S. Department of Agriculture, 

2006). Land-use and land-cover classes assigned to each cell 

included agricultural, urban, forest, and grassland (University 

of Nebraska-Lincoln, 2007). Land cover of the study area is 

heavily dominated by grassland (66 percent) and agricultural 

row crops (30 percent). Characteristics assigned to each cell 

on the basis of land-use and land-cover information included 

the Natural Resources Conservation Service (NRCS) runoffcurve number for estimating the potential for surface runoff, 

precipitation-interception coefficient, and root-zone depth; 

assigned values were obtained from the U.S. Department of 

Agriculture National Engineering Handbook (U.S. Department of Agriculture, 2004), Cronshey and others (1986), and 

Thornthwaite and Mather (1957). 

To calculate the daily soil-water content from precipitation, ET, surface runoff into and from adjacent cells, snowmelt, and potential recharge that passes below the root zone, 

the SWB model (Westenbroek and others, 2010) requires daily 

precipitation and temperature. Data from a single weather station can be applied to the entire model grid, or daily grids of 

weather data can be interpolated from multiple stations across 

and just outside the study area. Because of the small extent 

of the study area, precipitation and temperature data from a 

single weather station near Scottsbluff, Nebr., (fig. 1) were 

used (National Climatic Data Center, 2009). 

Digital elevation models (DEMs; U.S. Geological Survey and Nebraska Department of Natural Resources, 1998) 

were used to determine the surface-water-flow direction for 

each cell as described in Westenbroek and others (2010). 

The DEMs were first resampled to the model grid resolution (1,320 ft) using the mean altitude for each model cell. 

Surface-water runoff in the SWB model was calculated using 

the NRCS curve number method of Cronshey and others 

(1986) and is affected by soil properties and moisture content. If runoff water is routed to a closed surface depression, 

available water can exceed ET and soil-moisture demands. In 

these cases, unrealistic recharge values are possible. To limit 

excessive recharge, the maximum recharge rate was set to 2, 

0.6, 0.24, and 0.12 inches per day for hydrologic soil group A, 

B, C, and D, respectively. The extra water that is not allowed 

to infiltrate was tracked as rejected recharge, and was selectively reviewed for quality assurance. Infiltration and runoff 

also are affected by frozen ground, which was tracked using a 

continuous frozen-ground index (Molnau and Bissell, 1983). 

In the SWB model, precipitation that falls as snow was stored 

on the land surface until daily air temperature indicates that 

the snow would melt (Westenbroek and others, 2010). The rate 

of snowmelt is determined from a temperature-index method 

where 0.0328 in. of snow melts per day per degree Fahrenheit 

that the daily maximum temperature is above the freezing 

point (Westenbroek and others, 2010). Runoff that is transferred among cells is tracked as inflow and outflow.

Several methods are available in the SWB model to estimate ET; the Hargreaves and Samani (1985) method was used 

for this study. The Hargreaves and Samani method uses daily 

maximum and minimum temperatures to calculate potential 

ET (PET), and the method was used for this study because it 

does not require additional input of solar radiation, relativehumidity, or wind-speed data that other methods require; some 

of these data were not collected for the Scottsbluff weather 

station until after 1980. The SWB model then calculates 

actual ET from PET, and the available soil moisture in storage is determined from the nonlinear relation between soil 

moisture and the accumulated potential water loss based on 

soil properties and root-zone depths for vegetation categories 

(Westenbroek and others, 2010). If precipitation exceeds PET, 

actual ET is equal to PET; if PET exceeds precipitation, actual 

ET is equal to the amount of water that can be extracted from 

the soil.

The potential recharge estimated using the SWB model is 

sensitive to root-zone depth (Stanton and others, 2011). Rootzone depths were assigned based on hydrologic soil group and 

land-cover classification because the same vegetation class 

will send roots to different depths in different soil types. 

Initial soil-moisture and snow-cover values for the model 

were estimated by running the model for the year before the 

period of interest. The year 1949 was included in the model 

run to generate the initial soil-moisture and snow-cover values 

for 1950. Examples of potential recharge estimated using the 

SWB model for irrigation seasons of 1958, 1964, and 1982 are 

shown in figure 8. Based on the long-term precipitation record 

(1895–2008; National Climatic Data Center, 2009), 1958 was 

about average, 1964 was drier than average, and 1982 was 

wetter than average. For the irrigation season of 1958, most 

of the potential recharge was near the North Platte River from 

soil water that had first been routed across the land surface 

from uphill (upgradient) areas (fig. 8A). For the drier than 

average 1964 irrigation season (fig. 8B), the meager potential 

recharge was also near the North Platte River. For the wetterthan-average irrigation season of 1982 (fig. 8C), potential 

recharge was at greater rates and across a much wider area 

than for the other example years.
Simulation of Groundwater Flow 17

Figure 8. Potential recharge estimated with the Soil-Water-Balance (SWB) model for irrigation seasons of (A) 1958, (B) 1964, and 

(C) 1982.

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

Study area

1958 irrigation season, 

total inches

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

High: 1.8

Low: 0

104°00’ 103°00’

42°00’

A
18 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 8. Potential recharge estimated with the Soil-Water-Balance (SWB) model for irrigation seasons of (A) 1958, (B) 1964, and 

(C) 1982.—Continued

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

EXPLANATION

Study area

1964 irrigation season, 

total inches

High: 1.8

Low: 0

104°00’ 103°00’

42°00’

B
Simulation of Groundwater Flow 19

Figure 8. Potential recharge estimated with the Soil-Water-Balance (SWB) model for irrigation seasons of (A) 1958, (B) 1964, and 

(C) 1982.—Continued

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

EXPLANATION

Study area

1982 irrigation season, 

total inches

High: 18

Low: 0

104°00’ 103°00’

42°00’

C
20 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Limitations of the Soil-Water-Balance Model

Although the SWB model provides a general accounting 

of the water that infiltrates below the root zone as a function 

of spatial variation in soil properties, land use, and climate; 

model simplifications cause limitations. The following is a list 

of the limitations:

1. The version of the SWB model used for this analysis 

only accounts for precipitation and was not formulated 

to account for other water entering the root zone, such as 

irrigation or shallow groundwater. 

2. In the SWB model used for this study, daily precipitation 

and temperature data are taken from a single weather station but assumed to represent the entire model grid.

3. The NRCS curve-number method was designed to evaluate flood events and may not accurately estimate runoff 

for average rainfall events (Garen and Moore, 2005).

Recharge from Canal Seepage

Recharge from canal seepage is the largest source of 

recharge; therefore, estimating the distribution of this recharge 

on a canal-by-canal and cell-by-cell basis is important. 

The three main steps used in the estimation are as follows: 

(1) computation of canal seepage from a mass balance analysis of flow in each canal, estimated from records of canal 

operation; (2) estimation of seepage potential using available 

surface-geophysical data; and (3) combination of canal mass 

balance and seepage potential to compute spatially distributed 

canal seepage recharge.

Canal Mass Balance

The Bureau of Reclamation manages diversions to 

irrigation canals in the study area. Monthly water-distribution 

reports for 1950–2007 were obtained from the Bureau of 

Reclamation for 13 canals (table 1) including acres serviced, 

diversion, waste, loss, and delivery data in acre-feet per 

year (acre-ft/yr). Evaporation from canal water surfaces was 

assumed to be small, no more than a few percent. Although 

direct measurements of evaporation from canals do not exist, 

a few percent evaporation loss was considered a conservative 

assumption; a canal 50 mi long and 60 ft wide that evaporates 

50 in. of water from May through September with 1,000 ft3

/s 

of flow, would lose only 0.2 percent of flow to evaporation.

Canal seepage recharge annual rates were determined by 

using the amount of loss (calculated as the amount diverted 

from the North Platte River minus deliveries for irrigation and 

waste) multiplied by 97.5 percent (to account for additional 

losses from evaporation along the canal system and transpiration of recently infiltrated recharge) and dividing the value 

by the area of the bottom of the canal in the areas serviced in 

that year, resulting in a seepage rate per canal per unit area per 

year. Three canals (Minatare, Ninemile, and Winters Creek) 

had insufficient data to estimate annual recharge values and 

were assigned specified recharge rates for 1950–2007, based 

on Luckey and Cannia (2006). 

The amount of water available in the canals for seepage 

varied based on climatic conditions. Canals are most heavily 

used during years with low precipitation (fig. 9). However, 

because snowmelt runoff has decreased, the amount of surface 

water available to the irrigation districts has been less during 

most recent years (2000–2008) than before 2000, and has led 

to lower seepage rates (fig. 9).

Estimation of Canal Seepage Potential using Available 

Geophysical Data

In 2004 and during 2007–2009, the USGS led a land 

surface resistivity survey of selected irrigation canals within 

the North Platte River valley in western Nebraska and eastern 

Wyoming (Burton and others, 2009). Approximately 392 mi 

(630 kilometers) of 13 canals and 2 laterals of continuous 

resistivity profiles were collected using the Geometrics OhmMapper capacitively coupled electromagnetic instrument 

(Geometrics, 2009). Typically, an instrument configuration 

using five receivers was used to measure resistivity at five 

depths for an overall penetration of about 26 ft (8 m). The 

measured resistivity data were inverted, meaning that alternative configurations of subsurface physical properties that could 

have produced the geophysical survey measurements were 

evaluated and the most likely was selected. The inversions 

resulted in a set of georeferenced resistivity profiles totaling 

approximately 328,400 point values of simulated electrical 

resistivity.

Electrical resistivity of the earth is strongly related to 

sediment grain size and, hence, soil permeability (Ball and 

others, 2006). For example, fine-grained sediments tend to 

Table 1. Thirteen canals for which 

annual recharge rates were estimated.

Canal name

1. Enterprise Canal

2. Farmers Canal

3. Gering Canal

4. Gering-Fort Laramie Canal

5. Gering-Fort Laramie Laterals

6. Gering Laterals

7. Minatare1

8. Ninemile1

9. Northport Canal

10. Pathfinder Canal

11. Pathfinder Laterals

12. Tri-state Laterals

13. Winters Creek1

1

Fixed recharge rate assigned for 1950–2007 

because of lack of data.
Simulation of Groundwater Flow 21Figure 9. Annual total precipitation at Scottsbluff, Nebraska, and estimated canal seepage, 1950–2008.

302520151050 0

700,000600,000500,000400,000300,000200,000100,000

1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Annual precipitation, in inches

Adjusted canal seepage recharge, in acre-feet per year

Year

EXPLANATION

Canal seepagePrecipitation
22 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

be less resistive than coarser-grained sediments. The relative 

(dimensionless) permeability of the surveyed canal beds can 

be estimated by geostatistical analysis of the resistivity profiles, resulting in a seepage potential. Estimating canal seepage 

potential using capacitively coupled resistivity profiles is 

described in more detail by Vrabel and others (2009). Applying those methods to the inverted resistivity profiles resulted in 

a seepage potential map for the surveyed canals (fig. 10).

The length of each cell side for the groundwater-flow 

model was 1,320 ft, but the mapped estimates of seepage 

potential were on a much smaller scale (as small as one 

measurement point every several feet). In some cases there 

were hundreds of seepage potential estimates for each model 

cell that had to be generalized to a single estimate. A total of 

2,970 model cells were associated with canals, and of these, 

1,862 cells had surveyed resistivity data. In general, a surveyed path did not intersect a model cell uniformly. Factors 

affecting the density and distribution of the survey points 

within a cell included survey-line overlap, data-collection 

gaps, varying collection speed, and asymmetric intersection 

between cell boundary and surveyed line. In consideration 

of this spatial non-uniformity, an area-weighted mean was 

computed from the seepage potentials in each cell to arrive 

at a seepage potential for each cell intersecting a canal. Area 

weighting reduces spatial bias by weighting each point within 

a model cell by its contributing (or percentage) length. In contrast, equal weighting (computed using the simple mean) tends 

to give preference to areas of the cell with denser survey-point 

coverage. To ensure a model cell had a sufficient number of 

data points to estimate a reliable seepage potential, a minimum 

of 10 data points was required to compute an area-weighted 

estimate for the cell. If a cell contained less than 10 point 

values because of survey gaps, the cell’s seepage value was 

computed using the mean aggregate value of the two closest 

cells with adequate survey coverage, defined as 10 or more 

points; this applied to 63 canal cells (3.4 percent of the total).

Resistivity-survey data were not available for 

1,108 model cells associated with canals, precluding direct 

estimation of seepage potential. For these 1,108 cells, seepage 

potential was estimated indirectly using an inverse distanceweighted method. The inverse distance-weighted method 

was used on a canal-by-canal basis (Shepard, 1968). Seepage 

potentials were assigned to each unsurveyed cell in each canal 

by computing the mean of the estimated seepage potential of 

the surveyed cells weighted by the reciprocal of their distances 

to the unsurveyed cell. Estimates for unsurveyed cells are 

more affected by surveyed cells in closer proximity than by 

more distant surveyed cells, so this method tends to preserve 

the areal seepage potential trend better than some other methods, such as an unweighted mean. Because the geology of different canal systems can differ greatly, the indirect estimation 

of seepage potential was done on each canal in isolation (that 

is, estimated seepage potentials of unsurveyed cells were computed using only surveyed cells from the same canal system 

rather than including data from other canals). 

Combination of Canal Mass Balance Estimates and Estimated 

Seepage Potentials

The estimated seepage potentials were used to distribute 

the recharge rates within each canal on a cell-by-cell basis. 

All cells in a canal were assigned the canal’s annual (or seasonal, for simulation periods after 1988) recharge rate scaled 

in proportion to the estimated seepage potential. Cells with 

larger estimated seepage potentials were assigned a higher 

recharge rate, and cells with lower estimated seepage potentials were assigned a proportionally lower recharge rate. The 

resulting recharge rate was multiplied by a constant factor to 

preserve mass balance for the canal. Therefore, the sum of all 

of the cells final recharge rates in a canal equaled the original 

total recharge rate for the canal. Following this procedure, 

all canal cells (except those associated with three canals that 

the recharge rate was specified) were assigned an individual 

recharge rate for each year (or season, depending on the simulated period). These per-cell annual or seasonal recharge rates 

were added to recharge from precipitation to produce total 

estimated recharge for each stress period of the groundwaterflow simulation. All canals within the study area are shown in 

figure 11A, and figure 11B depicts long-term mean canal seepage recharge estimates per irrigation season, distributed by 

seepage potential. In figures 11A and 11B, surveyed cells are 

outlined. Canals in the study area only carry water during the 

irrigation season, so canal seepage recharge in groundwaterflow simulations was only applied to irrigation seasons during 

1989–2007; however, canal seepage recharge was applied 

throughout the year during 1950–89.

Groundwater Withdrawals

Groundwater withdrawals were simulated in the 

1950–2008 model. In this simulation, groundwater withdrawals were limited to withdrawals for irrigation purposes only, 

and municipal and all other uses were assumed to be negligible. In 2008, NPNRD certified irrigated acres to inventory 

the amount of irrigated land in the area. This information was 

obtained in a database containing digital spatial data describing well location, certification number, number of acres 

irrigated by the well, dates the well came online, and digital 

geospatial data for the location and extent of 2008 lands certified by NPNRD as irrigated (J. Sprock, North Platte Natural 

Resources District, unpub. data, 2010; fig. 12). The information in this database was used to determine the amount of 

groundwater needed to irrigate a defined parcel of land. Land 

parcels are tied to a particular canal or a particular irrigation well, or both. Not all wells in the database were used in 

the simulation. Criteria for well use were (1) wells had to be 

certified irrigation wells, servicing greater than 1 acre, (2) the 

screened interval of the well had to be above the revised base 

of the aquifer (fig. 6B), (3) the well had to have at least 5 ft 

of saturated thickness if located outside an area known to be 

underlain by Brule Formation, and (4) the well had to have 

at least 50 ft of saturated thickness if located within an area 

known to be underlain by the Brule Formation. As explained 
Simulation of Groundwater Flow 23

Figure 10. Relative canal seepage-potential estimates computed from inversely modeled OhmMapper resistivity profiles, North 

Platte River valley, Nebraska and Wyoming, 2004 and 2007–09. Dimensionless units represent fractions of the full range of canal 

seepage potential within the study area.

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

Study area

Seepage potential, 

dimensionless

0 to 0.1

0.1 to 0.2

0.2 to 0.3

0.3 to 0.4

0.4 to 0.5

0.5 to 0.6

0.6 to 0.7

0.7 to 0.8

0.8 to 0.9

0.9 to 1.0

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

104°00’ 103°00’

42°00’
24 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

Study area

Canal with calculated seepage potential

Canal name

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

1. Enterprise Canal

2. Farmers Canal

3. Gering Canal

4. Gering-Fort Laramie Canal

5. Gering-Fort Laramie Laterals

6. Gering Laterals

7. Minatare

8. Ninemile

9. Northport Canal

10. Pathfinder Canal

11. Pathfinder Laterals

12. Tri-state Laterals

13. Winters Creek

104°00’ 103°00’

42°00’

A

Figure 11. (A) Canals within the North Platte River valley, 

Nebraska, and (B) distribution of annual canal seepage 

recharge for selected canals, 1950–2008, North Platte River 

valley, Nebraska. For cells without outlines, rates were 

estimated by canal mass balance. For outlined cells, rates were 

estimated by canal mass balance combined with seepage 

potentials calculated using available geophysical data.
Simulation of Groundwater Flow 25

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

104°00’ 103°00’

42°00’

Study area

Canal with calculated seepage potential

Canal seepage recharge, in acre-feet per year

0 to 25

26 to 50

51 to 100

101 to 200

201 to 300

301 to 400

401 to 500

501 to 600

601 to 700

701 to 800

801 to 900

901 to 1,000

EXPLANATION

B

Figure 11. (A) Canals within the North Platte River valley, 

Nebraska, and (B) distribution of annual canal seepage recharge 

for selected canals, 1950–2008, North Platte River valley, 

Nebraska. For cells without outlines, rates were estimated by 

canal mass balance. For outlined cells, rates were estimated by 

canal mass balance combined with seepage potentials calculated 

using available geophysical data.
26 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

in the “Conceptual Model of Groundwater Flow“ section of 

this report, the base of the aquifer was defined by fine-grained 

sediments of the White River Group. In most areas, the Brule 

Formation is the topmost unit in the White River Group. 

The Brule Formation is massive and fractured in areas and, 

therefore, can yield water to the alluvial aquifer. These areas 

have been previously mapped for the COHYST study (Cannia 

and others, 2006). The areas of fractured Brule Formation are 

not continuous; therefore, the areas were not included as part 

of the alluvial aquifer in this study. Wells that had screens that 

started in the alluvial aquifer and penetrated into an area with 

greater than 50 ft of fractured Brule Formation were included 

as production wells in the simulation, based on the assumption that withdrawals from these wells amounts to drainage of 

groundwater stored in fractures in the Brule Formation. The 

water in the fractures in the Brule Formation is in turn replenished by drainage from the overlying alluvial aquifer; hence, 

to simulate Brule Formation withdrawals as withdrawals from 

the alluvial aquifer was assumed reasonable in the simulation. The assumption was made that irrigation wells entirely 

screened at a depth deeper than the base of the aquifer were 

irrigating with water from a deeper aquifer not in hydrologic 

connection with the alluvial aquifer. 

Figure 12. Land certified by North Platte Natural Resources District as irrigated acres, 2008, North Platte River valley, Nebraska.

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

EXPLANATION

Study area

Certified acres (J. Sprock, North Platte

Natural Resources District, unpub.

data, 2010)

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

104°00’ 103°00’

42°00’
Simulation of Groundwater Flow 27

The number of irrigation wells increased from 164 registered irrigation wells in 1950 to 1,206 registered irrigation 

wells in 2008 (Nebraska Department of Natural Resources, 

2008). This number is much larger than the 492 wells in the 

NPNRD certified acres database, but the disparity is likely 

because some registered wells were not in use during the 2008 

acreage certification.

Actual groundwater withdrawals were not recorded at 

each Actual groundwater withdrawals were not recorded at 

each well during 1950–2008; therefore, groundwater withdrawals were calculated per well using effective precipitation, 

crop-irrigation requirement (University of Nebraska, 2002), 

the amount of water delivered by canal systems, land-cover 

class, and the total number of acres irrigated by groundwater 

and by comingled (groundwater and surface-water irrigated) 

supplies.

Precipitation data were used to determine the effective 

precipitation, which is the amount of precipitation available 

for vegetative consumption within each soil type. Soil types 

within the study area were determined using the hydrologic 

group information from the Soils Survey Geographic database 

(Soil Survey Staff, 2004). Each grid cell in the study area 

was assigned a soil type. Daily precipitation for the area was 

compiled from the National Climatic Data Center webpages 

(National Climatic Data Center, 2009). Average precipitation 

was extracted from the weather-station data for each MODFLOW stress period. Effective precipitation for each stress 

period was calculated using the curve number method (Cronshey and others, 1986), which used the average precipitation 

per stress period and soil type.

Groundwater-irrigated land was defined using a dataset 

supplied by NPNRD in the aforementioned certified-acre 

database. Specific crop types were assigned using the University of Nebraska-Lincoln (2007) publication of the Center for 

Advanced Land Management Information Technology’s 2005 

land-use dataset. Land cover was classified by spatially joining 

the certified-acre geospatial dataset to the land-use geospatial dataset. In the event an irrigation parcel was covered by 

two crop types, the majority crop type was used. If the parcel 

contained multiple crop types that appeared equal, the parcel 

was assigned a unique land-cover class for that combination 

of crops. Each land-cover class was assigned the corresponding crop-irrigation requirement as defined by University of 

Nebraska (2002). The certified-acre database defined the initial 

date of groundwater irrigation for each parcel. The assumption 

was made that the parcel was irrigated annually from that initial date through 2007 and that land-cover class did not change 

through time. The net irrigation requirement is defined as the 

amount of water transpired by a given crop, above the amount 

supplied through natural precipitation; therefore, precipitation 

must be supplied by irrigation to prevent crop water stress. 

Net irrigation requirement for each parcel was determined by 

subtracting the effective precipitation from the crop-irrigation 

requirement. Any parcel with a positive difference required 

additional water to satisfy the crop requirement.

The database provided by the NPNRD also defined some 

parcels as irrigated by comingled supplies, meaning that the 

parcel received an amount of surface water to satisfy irrigation needs and also was accessible by an irrigation well. 

Surface-water application rates needed to be determined for 

comingled-irrigation acres. Surface-water application rates 

were determined by compiling surface-water records from irrigation districts and the Bureau of Reclamation. The Bureau of 

Reclamation keeps detailed service records for each irrigation 

district, including the number of acres in each district, amount 

of surface-water diverted, and amount of surface-water 

delivered to lands serviced by the district (J. Lawson, Bureau 

of Reclamation, written commun., 2011). The total amount of 

surface-water delivered was divided by the total acres in the 

district to produce an estimate of the amount of surface-water 

delivered to each acre. The outline of each irrigation district 

was determined from geospatial data (R. Kern, Nebraska 

Department of Natural Resources, unpub. data, 2002). A 

geospatial overlay analysis of the certified-irrigated-acres 

map supplied by the NPNRD, included the outlines of the 

irrigation districts that helped determine the irrigation district 

associated with each comingled parcel. The amount of surface 

water delivered to each parcel of the specific irrigation district 

was then assigned to the corresponding comingled parcel. 

The groundwater withdrawals for a comingled parcel were 

calculated by subtracting the surface-water application from 

the estimated net irrigation requirement. Resulting positive 

differences are the amounts of groundwater needed to satisfy 

the net irrigation demand. Comingled-irrigation acreages 

ranged from 18,200 certified acres in 1950 to 101,300 certified acres in 2008. The average annual 1950–2008 comingled 

groundwater withdrawal was 3,900 acre-ft/yr; the minimum 

annual comingled groundwater withdrawal was 130 acre-ft in 

1954, and the maximum comingled groundwater withdrawal 

was 35,100 acre-ft in 2002.

Land parcels that were not defined as comingled-irrigation acres used only groundwater pumped from wells to 

satisfy the crop demand. The amount of water pumped from 

each well to provide a parcel of irrigated land was determined by subtracting the effective precipitation from the 

crop requirement. Groundwater-only irrigated acres ranged 

from 1,900 certified acres in 1950 to 25,100 certified acres 

in 2008. The 1950–2008 average annual estimated groundwater withdrawal for groundwater-only irrigated parcels was 

9,700 acre-ft/yr. The minimum groundwater-withdrawal was 

988 acre-ft in 1951, and the maximum groundwater withdrawal was 27,200 acre-ft in 2007. Average annual groundwater-withdrawals were lower for comingled-irrigation acres than 

for groundwater-only acres because comingled-irrigation also 

used water from canal diversions. Total estimated groundwater 

withdrawals for irrigation and growing season precipitation 

are shown in figure 13. Groundwater withdrawals for irrigation compensated for infrequent surface-water shortages on 

comingled-irrigation parcels, and groundwater withdrawals 

were largest when surface-water supply (as evidenced by seepage) was smallest (fig. 14).
28 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 13. Growing season precipitation and estimated groundwater withdrawals for irrigation, 1950–2008.

EXPLANATION

0

5

10

15

20

25

30

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

1950 1960 1970 1980 1990 2000 2010

Growing season precipitation, in inches

Estimated groundwater withdrawals for irrigation, in acre-feet per year

Year

Groundwater withdrawals for irrigation

Precipitation

Calibration

When a groundwater-flow model is initially constructed, 

some model inputs, such as the locations of streams or the 

altitude of the land surface, are reasonably well known; 

however, some model inputs, such as hydraulic conductivity 

or recharge, are difficult or impossible to measure directly 

at the scale of the aquifer or study area and, therefore, must 

be estimated. As a consequence of imperfect and incomplete 

information available to characterize aquifers and related 

hydrology, commonly the initial model outputs do not closely 

reproduce observed (measured) hydrologic conditions. Calibration is the process whereby model inputs are adjusted to 

make model outputs more closely match observed hydrologic 

data. For this study, the parameter estimation suite of software 

(PEST) was used for model calibration (Doherty, 2010a). 

Calibration Approach and Parameters

This section of the report briefly describes the approach 

to model calibration through use of PEST (Doherty, 2010a) 

and the parameters that were adjusted to improve model 

calibration. In general, when groundwater-flow models are 

constructed, model inputs such as hydraulic conductivity, 

recharge, and aquifer-base altitudes are either unknown and 

must be estimated or are partially known and must be interpreted spatially and temporally across the simulation area and 

through time. Outputs of the model, such as simulated groundwater levels and groundwater discharge to streams (base 

flow), are then compared against calibration targets––in this 

case, measured groundwater levels and estimated stream base 

flows. These data are described in more detail in the “Calibration Targets” section of this report. Usually the initial model 
Simulation of Groundwater Flow 29

Figure 14. Estimated canal seepage and groundwater withdrawals for irrigation, 1950–2008, North Platte River valley model area, 

Nebraska.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

1950 1960 1970 1980 1990 2000 2010

Estimated groundwater withdrawals for irrigation, in acre-feet per year

Estimated canal seepage recharge, in acre-feet per year

Year

EXPLANATION

Canal seepage

Groundwater withdrawals for irrigation

outputs do not closely reproduce all of the calibration targets 

and, therefore, the model inputs must be adjusted so that the 

outputs more closely match the calibration targets. This process is known as “calibration.” Commonly, the model inputs 

adjusted are inputs that the least is known about or that are the 

most poorly constrained. Conversely, model inputs that the 

most is known about are usually fixed after model construction 

and are not adjusted during calibration. 

Prior to calibration using PEST, randomly-selected model 

inputs from each group described in this section of the report 

were first individually adjusted to evaluate whether selected 

PEST files had been prepared correctly. If changes in a model 

input (written by PEST through template files) caused changes 

in model outputs (read by PEST through instruction files), that 

meant that the PEST files had been prepared correctly. Over 

one-half of the model inputs were tested in this way. All inputs 

were reset to initial values at the conclusion of this testing. 

Subsequently, model calibration was approached using statistical techniques through parameter estimation using PEST 

(Doherty, 2010a). This process generally followed Stanton and 

others (2010, Appendix 2), with parameters discussed in this 

section of the report and targets discussed in the “Calibration 

Targets” section of this report. 

The term “parameters” has a special connotation in this 

report and is defined as model inputs that were potentially 

adjusted by PEST. Many dozens of model inputs exist, but 

only a small number (273) were selected as “parameters” for 

PEST. In general, these parameters consist of the following 

four groups: horizontal hydraulic conductivity (K) estimated 

at pilot points, spatial multipliers to recharge, temporal 
30 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

multipliers to recharge, and specific recharge parameters for 

areas where recharge estimated with the SWB model was 

either particularly low or particularly high. 

Spatial Multipliers to Recharge

The canals were split into four different groups, and canal 

seepage rates were adjusted separately to calibrate the model, 

with a maximum increase or decrease of 25 percent. The four 

groups were (1) canals with variable calculated seepage potential rates located on the north side of the river, (2) canals with 

variable calculated seepage potential rates located on the south 

side of the river, (3) canals with uniform seepage potential 

rates on the north side of the river, and (4) canals with uniform 

seepage potential rates on the south side of the river. Canals 

on the north side of the river were separated from those on 

the south side because canals on the south side are generally 

dug into bedrock; whereas, canals on the north side of the 

river are generally dug into alluvial sediment (see the “Hydrogeology” section of this report). The canals with calculated 

seepage potential rates were assigned a variable recharge by 

cell; whereas, cells that had not been analyzed had little cellby-cell information, so calculated seepage rates were uniform 

for those canals (see the “Canal Mass Balance” section of this 

report). The multiplier used to adjust the canal seepage rates 

was applied to all time periods of the simulations. Estimation 

of seepage potential is explained in more detail in the “Estimation of Canal Seepage Potential Using Available Geophysical 

Data” section of this report.

Horizontal Hydraulic Conductivity Estimated at Pilot Points

Horizontal hydraulic conductivity estimated at pilot 

points comprised the bulk of the parameters (190 of the 273). 

Pilot points are defined as locations where K is estimated, 

rather than either estimating individual K values for every cell 

of the groundwater-flow model or using zones of uniform K. 

Pilot point K estimates are then spatially interpolated to the 

model grid, resulting in a smoothly varying K field (Doherty, 

2003) for every active cell of the groundwater-flow model. 

The 190 pilot points for this study were generally spaced in a 

regular grid across the active model area independent of testhole locations, which are irregularly spaced.

Initial K was used from a previous study (Cannia and 

others, 2006). Cannia and others (2006) estimated hydraulic 

conductivity at test-hole locations based on lithologic descriptions, and produced estimates at every test hole that should be 

correct in magnitude relative to each other, though it was not 

known if the absolute values of the estimates are correct. The 

point hydraulic conductivity estimates of Cannia and others 

(2006) were interpolated from the test-hole locations across 

the entire active model area using inverse-distance weighting. 

The spacing of these test holes is irregular and nearly always 

larger than the 1,320-ft spacing used for the model cells. 

Generally, geologic deposits––including alluvial aquifers such 

as the one in the study area––can change rapidly across short 

distances, certainly within the distances between test holes in 

this study area. Hence the pilot-point network for this parameter estimation was designed using a regular-grid approach.

Individual pilot-point locations were adjusted slightly for 

a few cases where the pilot point was placed too near the edge 

of the active model. Pilot points too near the edge of the model 

could have resulted in incorrect model responses to changes in 

the K estimates and instability during automated calibration. 

The initial values of K at the pilot points were set to the values 

interpolated from the test-hole estimates. Tikhonov regularization was used to provide prior information (Doherty, 2010b) 

and impose a penalty if the K estimated at the pilot points 

deviated from the preferred condition of the initial K estimate. 

Imposing this penalty prevented model over-fitting and, further, honored the initial values that were expected to be relatively correct but are known to be incomplete. More detailed 

explanations of this approach are described by Hunt and others 

(2007), Doherty (2003), and Fienen and others (2009).

Temporal Multipliers to Recharge

Temporal multipliers to recharge were used to adjust 

recharge estimated with the Soil-Water-Balance Model for 

the 77 stress periods of the 1950–2008 model (77 of the 

273 parameters). Recharge and multipliers for 1950–54 were 

also used to generate the recharge applied to the pre-1950 

model and thereby the multipliers for 1950–54 affected the 

pre-1950 and 1950–2008 models.

Specific Recharge Parameters

The remaining two parameters were recharge values 

input to the simulation for areas where the recharge estimated 

with the SWB model was either particularly low (less than 

0.25 in/yr) or particularly high (greater than 5 in/yr).

Calibration Targets

The measured or estimated hydrologic data used in model 

calibration are frequently referred to as “calibration targets,” 

as will be used in this report. The two types of calibration 

targets used for this study were estimated base-flow targets 

and groundwater-level targets. Each calibration target was 

weighted to affect the calibration process. All target weights 

were calculated using error-based weighting (Hill and Teideman, 2007) that used a 95-percent confidence interval and 

expected errors of as much as 5 ft for groundwater levels and 

10 percent for estimated base flows, except where otherwise 

noted.

Groundwater-Level Targets

The data for groundwater-level targets were retrieved 

either from the NWIS database (U.S. Geological Survey, 

2012) or from water-level records collected and provided by 

the NPNRD (Jackie Bishop, North Platte Natural Resources 

District, written commun., 2008). Not many water-level 

records coincided closely with April 1950 (the end of the 
Simulation of Groundwater Flow 31

pre-1950 model), so additional targets through 1955 were 

included, assuming that those water levels would still 

adequately represent the period before major groundwater 

development. All measured water levels within the study area 

were considered to be used as a calibration target if sufficient 

information indicated that the well was screened in the alluvial 

aquifer. Wells were eliminated from consideration based on 

proximity to each other and based on their period of record. If 

a well was located within 3,280 ft of another well, the records 

of the two wells were compared, and the well that had the longer period of record was retained to be used as a water-level 

target. The water-level altitudes used as calibration targets 

were determined by subtracting the recorded water-level depth 

from the DEM-derived altitude (U.S. Geological Survey and 

Nebraska Department of Natural Resources, 1998) at the 

location. The well altitude recorded in each database was 

compared to the DEM altitude to help determine if any well 

locations were recorded incorrectly, by comparing the reported 

well altitude to the sampled DEM altitude at the well location. 

The well altitude was subtracted from the DEM altitude. If the 

difference was greater than 5 ft, the authors further reviewed 

the records to determine if the well was not located correctly, 

or if locally steep slopes could have caused an inaccurate 

DEM altitude estimate. Wells were discarded if the altitude 

could not be verified. Other water levels were considered 

suspect (that is, the targets were based on a possibly erroneous 

altitude) and were given a weight of zero. Wells within half a 

mile of the model boundary were not used to prevent interpolation artifacts from causing misleading results. This process 

resulted in 126 water-level targets used for calibration of the 

pre-1950 model and 5,101 water-level targets used for calibration for the 1950–2008 model. The total number of water-level 

targets per stress period for the 1950–2008 model ranged from 

1 in stress periods 5 and 8 to 225 in stress period 76; during 1950–2008, the number of water-level targets generally 

increased. Water-level targets for the pre-1950 model were 

associated with a 10-ft expected error range because of the 

wider temporal range of measurements used as water-level 

targets (actual groundwater level is within plus or minus 5 ft 

of recorded groundwater level), resulting in a lower weight 

than water-level targets for the 1950–2008 model.

Base-Flow Targets

Streamflow at a given point consists of base flow and 

runoff. Base flow is the amount of water that is discharged to 

a stream from groundwater, and runoff is the water contributed to the stream from precipitation and return flows from 

irrigation. Base flow for the pre-1950 model was estimated 

using the base-flow index (BFI) method (Wahl and Wahl, 

2007). Daily streamflow data were compiled from the USGS 

National Water Information System (NWIS; U.S. Geological Survey, 2012) and the Nebraska Department of Natural 

Resources (2013). Average estimated base flow for April 1950 

was selected as the pre-1950 base-flow target. April 1950 was 

considered a time of equilibrium after surface-water irrigation 

had been in place for several decades but before widespread 

groundwater withdrawals for irrigation began. In addition, 

most canals do not divert water during April, so the base-flow 

separation should be relatively free from the effects of canal 

diversions. The flow targets are those reported for selected 

streamgage locations within the study area. This process 

resulted in 13 pre-1950 base-flow targets, of which 4 were for 

the North Platte River and 9 were for tributaries. 

Base-flow targets for the 1950–2008 model also were 

determined using the BFI method. The target locations are 

the same as the pre-1950 model target locations. The average 

April estimated base flow for the respective year was used as 

the base-flow target. Average April estimated base flows were 

used because those base-flow values generally were free of the 

effects of early spring lowland snowmelt runoff, the effects 

of vegetative transpiration of stream water, and the effects of 

canal diversions. The 1950–2008 model base-flow targets and 

the calibrated simulated base-flow results are summarized in 

table 2 and discussed in the “Calibration Results” section of 

this report. Because of the importance of the calibration of 

estimated base-flow for analysis with the simulation-optimization model, the base-flow target weights were doubled for 

streamgages along the North Platte River.

Some streams did not have streamgages during 

1950–2008, so a base flow target could not be estimated 

(table 3). Simulated stream base flow was also tracked for 

some streams that do not have streamgages to gain a better understanding of the flow system. Additionally, not all 

streamgages in the study area had a continuous record. Calibration targets corresponding to streams without a streamgage 

in the study area and to time periods without streamflow 

records were assigned a calibration weight of zero. Base-flow 

targets with a weight of zero did not affect the calibration 

process, but the simulated discharges from those streams were 

reviewed to ensure consistency with the conceptual model.

Calibration Results

The closeness of fit of simulated base flow and 

groundwater levels to estimated base-flow and measured 

groundwater-level targets indicates how closely the simulation 

reproduced historical conditions. Differences between simulated results and calibration targets are referred to as residuals and were calculated as the target (measured or estimated) 

value minus the simulated value. Therefore, when the target 

value is larger than the simulated value (underestimation), the 

residual has a positive sign, and when the simulated value is 

larger than the target value (overestimation), the residual has a 

negative sign. The mean residual, the mean absolute residual, 

and the root-mean-squared (RMS) residual were calculated for 

all water-level targets and also for subsets representing specific 

time periods of the pre-1950 model and the 1950–2008 model. 

The mean residual was calculated as the sum of residuals of 

each group. The mean absolute residual was calculated as the 

sum of the absolute value of the residuals of each group. The 

RMS residual was calculated as:
32 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska Table 2. Summary of estimated base flows used as calibration targets for the 1950–2008 model. Streamgage Streamgage number Estimated base flow (cubic feet per second) Number of estimated values averaged Simulated base flow (cubic feet per second) Average residual (cubic feet per second) Average percent difference Minimum Maximum Average Minimum Maximum Average North Platte River at Nebraska- Wyoming State line 06674500 3 3,885 557 58 46 3,069 355 202 77 Horse Creek near Lyman, Nebraska 06677500 4 186 27 58 21 44 35 -8 -58 Sheep Creek near Morrill, Nebraska 06678000 2 81 58 58 45 114 78 -20 -32 Dry Spottedtail Creek at Mitchell, Nebraska 06679000 11 58 22 43 13 42 28 -6 -26 North Platte River at Mitchell, Nebraska 06679500 164 4,893 751 58 164 3,268 556 195 27 Tub Springs Drain near Scottsbluff, Nebraska 06680000 0 33 23 57 12 34 25 -4 -8 Winters Creek near Scottsbluff, Nebraska 06681000 21 47 37 58 10 35 26 11 34 Gering Drain near Gering, Nebraska 06681500 11 33 22 58 15 47 37 -15 -52 North Platte River near Minatare, Nebraska 06682000 277 4,893 865 58 249 3,431 730 136 13 Ninemile Creek near McGrew, Nebraska 06682500 11 84 59 58 29 69 51 8 8 Bayard Drain near Bayard, Nebraska 06683000 0 22 9 58 10 17 13 -3 -58 Red Willow Creek near Bayard, Nebraska 06684000 17 63 47 58 29 74 53 -6 -15 North Platte River at Bridgeport, Nebraska 06684500 340 4,900 1,100 58 338 3,546 868 215 15
Simulation of Groundwater Flow 33

( )

0.5

2

1

1

 

n

m s i

i

RMS h h

n =

  = −     ∑ (2)

where 

n is the number of measurements, 

hm is the measured groundwater level, and 

hs is the simulated groundwater level (Anderson 

and Woessner, 1992). 

The mean residual was calculated for the base-flow targets; however, mean residuals across targets of different sizes 

is not meaningful, and base-flow targets range in size from 

less than 10 to 1,100 ft3/s from the smallest streams to the largest in the study area. An average of the percentage difference 

between simulated base-flow and base-flow targets for each 

streamgage location was calculated as:

1 ( ) *100 /

/ 2

n BFE BFS

Average percent difference n BFE BFS

− = +

      ∑ (3)

where 

n is the number of targets, 

BFE is the estimated base flow, and 

BFS is the simulated base flow. 

Groundwater Levels

Comparisons of plotted measured groundwater-level targets and simulated groundwater levels for the end of the pre1950 model are shown in figure 15. Also, figure 15 shows a 

1:1 line; if all simulated groundwater levels perfectly matched 

groundwater-level targets, all points would have lain on the 

1:1 line. Generally, the points in figure 15 are spaced equally 

small distances above and below the 1:1 line, demonstrating 

that although the levels did not perfectly match, simulated 

groundwater levels were equally balanced above and below 

groundwater-level targets. Only for groundwater level targets 

below about 3,850 ft altitude, simulated water levels tended to 

be near the line but slightly above the groundwater-level targets, as evidenced by their position slightly above the 1:1 line. 

The mean residual for the pre-1950 model water levels was 

-2.3 ft, with a range from -66 ft to 92 ft. The negative value 

for the mean residual indicates that on average the simulated 

groundwater levels are slightly higher than measured groundwater levels. The mean absolute April 1950 groundwater-level 

residual was 13.9 ft, and the RMS residual was 21.1 ft. The 

April 1950 simulated groundwater levels were within 25 ft of 

the measured groundwater levels for 108 of the 126 measured 

groundwater levels (86 percent). The simulated groundwater 

level for April 1950 (end of the pre-1950 model) was within 

50 ft of the measured groundwater level for 120 of the targets 

(95 percent). The wells with extremely high or extremely 

low residuals were not spatially concentrated (fig. 16), that 

is, simulated water levels were not biased particularly high 

or low in any region of the study area. Fewer groundwaterlevel targets are south of the North Platte River than north of 

the river, but evaluation of chi-squared statistics used to test 

for independence (Helsel and Hirsch, 2002) indicated that 

there is likely no correlation between residuals being negative 

or positive north of the river compared to south of the river. 

Similarly, correlation is unlikely between residuals either north 

or south of the river being the largest or smallest 10 percent of 

the residuals.

Measured groundwater levels (targets) and simulated 

groundwater levels for the 1950–2008 model are compared 

in figure 17. Also, figure 17 shows a 1:1 line; if all simulated 

groundwater levels perfectly matched groundwater-level 

targets, all points would have lain on the 1:1 line. Generally, 

the points in figure 17 are spaced equally small distances 

above and below the 1:1 line, demonstrating that although 

the points did not perfectly match, simulated groundwater 

levels were equally balanced above and below groundwaterlevel targets. Only for groundwater level targets below about 

3,850 ft altitude, simulated water levels tended to be near 

the line but slightly above the groundwater-level targets, as 

evidenced by their position slightly above the 1:1 line. The 

simulated groundwater level was within 25 ft of the measured 

groundwater level for 4,788 of the 5,101 targets (94 percent). 

The simulated groundwater level was within 50 ft of the target 

at 5,039 targets (99 percent). For the 1950–2008 model, the 

mean residual for the water levels was -5.7 ft with a range 

from -108 to 140 ft. The mean absolute groundwater-level 

residual was 10.5 ft, and the RMS residual was 15.1 ft. The 

wells with extremely high or extremely low residuals were 

not spatially concentrated (fig. 18), that is, for the 1950–2008 

model simulated water levels were not particularly biased 

beyond the local scale.

Table 3. Summary of simulated base flows for streams without 

streamgages within the study area, for the 1950–2008 model.

Stream name

Simulated base flow 

(cubic feet per second)

Minimum Maximum Average

Dry Creek 5 10 8

Dry Sheep Creek 1 18 9

Indian Creek 2 11 6

Kiowa Creek 4 9 7

Melbeta Drain 0 3 1

Owl Creek 20 38 31

Spottedtail Creek 42 65 56

Wildhorse Drain 13 31 23

Unnamed tributary in 

Browns Canyon

0 6 2
34 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

1:1 line

Groundwater level

EXPLANATION

3,600

3,700

3,800

3,900

4,000

4,100

4,200

4,300

4,400

3,600 3,700 3,800 3,900 4,000 4,100 4,200 4,300 4,400

Simulated groundwater level, in feet

Measured groundwater level, in feet

Figure 15. Relation of pre-1950 model simulated groundwater levels, April 1950, to measured groundwater levels used as calibration 

targets, 1945–55.

Base Flows

For the pre-1950 model, simulated base flows were about 

the same as estimated base flows. For the four North Platte 

River streamgages, the mean residual base flow was 41 ft3

/s 

with a range from -32 ft3

/s to 94 ft3/s. For the nine tributary 

streamgages, the mean residual baseflow was 7 ft3

/s with a 

range from -25 ft3

/s to 11 ft3/s. 

The 1950–2008 model simulated base flows followed 

the overall trend of the estimated base flows reasonably well 

(increasing or decreasing base flow from the start of the simulation to the end), though simulations indicate some deviations 

for individual years. The spikes in the streamgage hydrographs 

along the North Platte River were caused by large reservoir 

release events in Wyoming, upstream from the study area 

(figs. 19A and 19B). Although these reservoir releases usually 

were not during April and, thus, did not affect the base-flow 

separation used for calibration target data, for a few years the 

reservoir releases were earlier than normal, and base-flow 

separation approaches are generally not able to distinguish 

those reservoir releases from steady groundwater discharge 

into the stream. 

Overall, average 1950–2008 simulated base flow was 

about 185 ft3

/s lower than estimated base flow for the four 

North Platte River streamgages in the study area (table 2). 

However, because the estimated base flow of the North Platte 

River approximately doubles from the upstream end of the 

study area to the downstream end, the percentage difference 

between estimated and simulated base flow is much smaller 

at the downstream end (15 percent) as opposed to the upper 

end (77 percent). Measurement error at streamgages commonly ranges from 5 to 8 percent or greater (Rantz and others, 

1982) and base-flow separation probably has at least that much 

uncertainty; therefore, the authors considered the difference 

between estimated and simulated base flow at the downstream 

end of the study area to be approaching the aggregate uncertainty of streamflow measurement and base-flow estimation. Simulated base flow was less than the estimated base 

flow for the North Platte River at the Nebraska-Wyoming 
Simulation of Groundwater Flow 35

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

Study area

Water-level residual, in feet

Less than -25

-25 to -15

-15 to -5

-5 to 5

104°00’ 103°00’

42°00’

5 to 15

15 to 25

Greater than 25

Simulated groundwater levels below 

measured groundwater-level targets

Simulated groundwater levels above 

measured groundwater-level targets

Simulated groundwater levels about the same 

as measured groundwater-level targets

Figure 16. Spatial distribution of calibration residuals for simulated groundwater level, April 1950, end of the pre-1950 model.
36 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

State-line streamgage (77 percent difference, table 2) but 

indicated generally the same trend (fig. 19A). Simulated base 

flow matched estimated base flow more closely (15 percent 

difference, table 2) for the North Platte River at Bridgeport, 

Nebr., streamgage, the focus of the optimization scenarios 

(fig. 19B, table 2). Simulated base flow for most tributaries 

closely matched estimated base flow for many time periods, 

as demonstrated by Tub Springs Drain (-8 percent difference, 

table 2; fig. 19C) and Red Willow Creek (-15 percent difference, table 2; fig. 19D). The two streams that simulated base 

flow matched estimated base flow less closely are Winters 

Creek (34 percent difference, table 2; fig. 19E) and Gering 

Drain (-52 percent difference, table 2; fig. 19F). Winters Creek 

simulated base flow was about 11 ft3

/s less than estimated base 

flow at the beginning of the simulation period, and though the 

simulated base flow had the correct temporal trends, simulated 

base flow remained about 11 ft3

/s lower than estimated base 

flow for the duration of the simulation. Gering Drain simulated 

base flow was about 15 ft3

/s more than the calibration target 

at the beginning of the simulation and roughly approximated 

the correct temporal trend of estimated base flow, though the 

simulated base flow remained too high until the last stress 

period of the simulation. The simulated base flows for streams 

in the study area that did not have streamgages are listed in 

table 3. Though no measured data were available to compare 

to the simulated flows, the simulated flows were generally 

smaller than the gaged streamflows in the area and are considered reasonable until data are available or collected to indicate 

otherwise.

Calibrated Parameters

As described in the “Calibration Approach and Parameters” section of this report, initial parameter values are 

adjusted manually and through automated parameter estimation using PEST (Doherty, 2010a) so that the outputs more 

Figure 17. Relation of simulated groundwater levels to measured groundwater levels used as calibration targets for the 1950–2008 

model.

1:1 line

Groundwater level

EXPLANATION

Simulated groundwater level, in feet

Measured groundwater level, in feet

3,600

3,700

3,800

3,900

4,000

4,100

4,200

4,300

4,400

3,600 3,700 3,800 3,900 4,000 4,100 4,200 4,300 4,400
Simulation of Groundwater Flow 37

Figure 18. Spatial distribution of average calibration residuals for simulated water level for the 1950–2008 model.

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

EXPLANATION

Study area

Average water-level residual, in feet

104°00’ 103°00’

42°00’

Less than -25

-25 to -15

-15 to -5

-5 to 5

5 to 15

15 to 25

Greater than 25

Simulated groundwater levels below 

measured groundwater-level targets

Simulated groundwater levels above 

measured groundwater-level targets

Simulated groundwater levels about the same 

as measured groundwater-level targets
38 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska Figure 19. Simulated and estimated base flow for (A) North Platte River at Wyoming-Nebraska State line; (B) North Platte River at Bridgeport, Nebraska; (C) Tub Springs Drain near Scottsbluff, Nebraska; (D) Red Willow Creek near Bayard, Nebraska; (E) Winters Creek near Scottsbluff, Nebraska; and (F ) Gering Drain near Gering, Nebraska. 0 500 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1,000

Base flow, in cubic feet per second

Estimated Simulated

EXPLANATION

0

 6,000 5,000 4,000 3,000 2,000 1,000

 5 0

 40 35 30 25 20 15 10

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

Date

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

Date

0

 80 70 60 50 40 30 20 10

A. 06674500, North Platte River at Wyoming-Nebraska State line B. 06684500, North Platte River at Bridgeport, NebraskaC. 06680000, Tub Springs Drain near Scottsbluff, Nebraska D. 06684000, Red Willow Creek near Bayard, Nebraska
Simulation of Groundwater Flow 39

Figure 19. Simulated and estimated base flow for (A) North Platte River at Wyoming-Nebraska State line; (B) North Platte River at Bridgeport, Nebraska; (C) Tub Springs Drain near Scottsbluff, Nebraska; (D) Red Willow Creek near Bayard, Nebraska; (E) Winters Creek near Scottsbluff, Nebraska; and (F ) Gering Drain near Gering, Nebraska.—Continued

Base flow, in cubic feet per second

Estimated Simulated

EXPLANATION

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

Date

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

Date

E. 06681000, Winters Creek near Scottsbluff, Nebraska F. 06681500, Gering Drain near Gering, Nebraska

50

504540353025201510

50

504540353025201510
40 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

closely match the calibration targets. Calibrated parameter values were inspected for gross errors or anomalous values that 

would indicate that the conceptual model had been violated or 

that some part of the automated parameter estimation process 

using PEST had produced erroneous results.

Spatial Multipliers to Recharge

Multiplier parameters applied to canal seepage recharge 

rates to improve model calibration were intended to account 

for imprecision or inaccuracy in canal seepage estimates and 

to correct for this imperfect knowledge of the system. The 

calibrated multiplier parameter for the canals with calculated 

seepage potential on the north side of the river was 0.96, or 

a decrease of 4 percent; and the calibrated multiplier for the 

canals with calculated seepage potential on the south side of 

the river was 0.80, or a decrease of 20 percent. The calibrated 

multiplier for the canals without calculated seepage potential on the north side of the river was 0.98, or a decrease of 

2 percent; and the calibrated multiplier for the canals without 

calculated seepage potential on the south side of the river was 

0.96, or a decrease of 4 percent. The calibrated multipliers, 

mainly at small deviations from unity, are considered reasonable, and even the largest adjustment of a decrease of 20 percent was within the uncertainty range of the canal flow data. 

The average calibrated canal seepage recharge rate is shown in 

figure 20. 

Horizontal Hydraulic Conductivity Estimated at Pilot Points

PEST was allowed to decrease or increase hydraulic conductivity at the pilot points for calibration of the simulation. 

In three locations (purple rectangles on fig. 21), calibrated 

hydraulic conductivity reached more than 450 ft/d; however, 

the high values were detected primarily in a few areas where 

few data were available to describe the aquifer-base altitude, 

being beyond the depth of investigation of the AEM (Abraham 

and others, 2012). MODFLOW does primary flow calculations 

based on transmissivity, the product of saturated thickness 

and hydraulic conductivity; therefore, equivalent transmissivities can be obtained by having a larger saturated thickness 

and smaller hydraulic conductivity or by having a smaller 

saturated thickness and larger hydraulic conductivity. A large 

horizontal hydraulic conductivity estimated during the parameter estimation could be a result of locally poorly constrained 

aquifer-base altitude. In addition, unpublished aquifer tests in 

the area resulted in estimated horizontal hydraulic conductivity of 463 ft/d near Mitchell in the northwest part of this area 

(fig. 1; as reported by Verstraeten and others, 2001), and this 

estimated K is comparable to calibrated K values of more than 

450 ft/d. The authors considered it more appropriate, however, 

to review the patterns and values of calibrated transmissivity 

across the entire area, calculated as the calibrated hydraulic 

conductivity multiplied by the simulated saturated thickness of 

the aquifer (fig. 21). Transmissivity is strongly controlled by 

the aquifer thickness (fig. 6C) and is largest in the center of the 

valley where the aquifer is not only the thickest but consists of 

the coarsest deposits. 

Temporal Multipliers to Recharge

Temporal multipliers to recharge were used to adjust 

recharge estimated with the Soil-Water-Balance Model for 

the 77 stress periods of the 1950–2008 model, and to adjust 

recharge estimated the Soil-Water-Balance Model for the 

pre-1950 model. The mean calibrated temporal multiplier was 

0.96, and the range was from 0.78 to 1. The mean multiplier 

near unity indicates that in combination with other parameters, 

recharge estimated with the Soil-Water-Balance Model did not 

need to be adjusted very much for model calibration. 

Specific Recharge Parameters

The remaining two parameters were recharge values 

input to the simulation for areas where the recharge estimated 

with the SWB model was either particularly low (less than 

0.25 in/yr) or particularly high (greater than 5 in/yr). For areas 

where recharge was particularly low, the calibrated recharge 

was 0.19 in/yr, or just slightly lower than the initial value 

of 0.25 in/yr. For areas where recharge estimated with the 

SWB model was particularly high, the calibrated recharge 

was 3.0 in/yr. This indicates that in combination with other 

parameters, decreases in areas where the SWB-estimated 

recharge was high, improved model calibration. This parameter was limited to a lower value of 3.0 in/yr, so it is possible 

that further reductions in this parameter might have further 

improved model calibration, though to what extent was uncertain. However, as described in the ”Sensitivity” section of this 

report, model outputs were less sensitive to changes in specific 

recharge parameters than to changes in other inputs, so model 

outputs may not have changed greatly with additional reductions in areas where recharge estimated with SWB was high.

Simulated Groundwater Budget

Average groundwater budgets for various simulated 

periods are shown in table 4. The mass balance of inflows 

and outflows was appropriately maintained because inflows 

approximately equal outflows (to within 1 ft3

/s) for all simulated periods except the irrigation seasons during 1989–2007. 

For the irrigation seasons during 1989–2007, total average 

simulated outflows were slightly larger than total average 

simulated inflows, but this difference was only about 1 percent 

of the total water budget, and, therefore, not considered as a 

concern. 

During pre-1900, 66 percent of simulated inflow was 

recharge from precipitation and 34 percent was groundwater 

inflows from the west (simulated as specified water levels; 

table 4). Simulated outflow was to ET (90 percent) and 10 percent was outflow to streams (table 4). 

During 1900–50, 90 percent of simulated inflow was 

from recharge from canal seepage and 7 percent was recharge 
Simulation of Groundwater Flow 41

GOSHEN

COUNTY

SIOUX

COUNTY

BOX BUTTE

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

104°00’ 103°00’

42°00’

EXPLANATION

Study area

Average calibrated canal seepage, 

in acre-feet per year

0 to 25

26 to 50

51 to 100

101 to 200

201 to 300

301 to 400

401 to 500

501 to 600

601 to 700

701 to 800

801 to 900

901 to 1,000

Figure 20. Average calibrated canal seepage recharge rate by 

model cell, acre-foot per year, in the calibrated simulation.
42 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 21. Calibrated transmissivity, 2008, foot squared per 

day, and areas of highest estimated hydraulic conductivity, 

North Platte River valley, Nebraska.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

Study area

Transmissivity, in feet 

squared per day

Area of high estimated 

hydraulic conductivity

0 to 1,000

1,001 to 2,500

2,501 to 5,000

5001 to 7,500

7,501 to 10,000

10,001 to 15,000

15, 001 to 25,000

25,001 to 50,000

50,001 to 70,000

70,001 to 90,000 

104°00’ 103°00’

42°00’
Simulation of Groundwater Flow 43

Table 4. Summary of average simulated annual groundwater budgets for pre-1900, 1900–50, and 1950–89 and average simulated seasonal budgets for irrigation seasons during 1989–2007 and non-irrigation seasons during 1989–2008.[--, no data or not available; <, less than. Modflow outflows were subtracted from inflows and only net flows of each budget term are displayed. Values in parentheses (negative) indicate simulated outflows of the groundwater system, and positive numbers indicate simulated inflows to the groundwater system.]

Water budget 

component

Pre-1900 period 1900–50 period 1950–89 period 1989–2007 1989–2008

Quantity, 

average 

(cubic feet 

per second)

Relative 

quantity, as 

percentage of 

total budget

Quantity, 

average 

(cubic feet 

per second)

Relative 

quantity, as 

percentage of 

total budget

Quantity, 

average 

(cubic feet 

per second)

Relative 

quantity, as 

percentage of 

total budget

Irrigation 

season 

quantity, 

average 

(cubic feet 

per second)

Relative 

quantity, as 

percentage of 

total budget

Non-irrigation 

season 

quantity, 

average 

(cubic feet 

per second)

Relative 

quantity, as 

percentage of 

total budget

Inflows

Recharge -- -- -- -- -- -- -- -- -- --—from canal seepage 0 0 720 90 686 88 1,385 92 0 0

—from precipitation 60 66 60 7 77 10 93 6 74 13

Groundwater inflows 

simulated as specified water levels

31 34 21 3 21 3 23 2 22 4

Storage -- -- -- -- -- -- -- -- 462 83

Outflows

Storage 0 0 -- <1 -1 <1 -555 37 -- --

Evapotranspiration -82 90 -162 20 -164 21 -336 22 -28 5

Wells 0 0 0 0 -15 2 -95 6 0 0

Stream base flow -9 10 -638 80 -603 77 -531 35 -531 95

Total inflows 91 100 801 100 784 100 1,501 100 558 100

Total outflows (91) 100 (801) 100 (784) 100 (1,517) 101* (559) 100

*The sum of all inflow components equals the sum of all outflow components for each time period, though small differences may exist primarily because of rounding.
44 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

from precipitation (table 4). Simulated outflow was to streams 

(80 percent) and 20 percent was outflow to ET (table 4). 

During 1950–89, 88 percent of simulated inflow was 

recharge from canal seepage, and 10 percent was recharge 

from precipitation (table 4). Simulated outflow was to streams 

(77 percent) and 21 percent was outflow to ET (table 4). 

Later stress periods of the simulation were divided into 

irrigation season and non-irrigation season. During 1989–2007 

irrigation seasons, 92 percent of simulated inflow was from 

recharge from canal seepage and 6 percent was recharge from 

precipitation (table 4). Simulated outflow was to water entering storage (37 percent), discharges to streams (35 percent), 

and to ET (22 percent; table 4). 

During 1989–2008 non-irrigation seasons, 83 percent of 

simulated inflow was from water leaving storage and 13 percent was from recharge from precipitation (table 4). Simulated 

outflow during 1989–2008 non-irrigations seasons was mostly 

discharges to streams (95 percent; table 4).

Several observations can be made from table 4. First, 

simulated groundwater budget components from pre-1900 

match the conceptual model of groundwater flow, but appreciable pre-1900 data do not exist to compare with simulated 

groundwater budget components. Therefore, it cannot be 

determined how well the simulated values match the actual 

values during that time period, for example, how well 

simulated stream base flow matches actual values. Second, 

recharge from canal seepage was the largest average inflow 

for most simulation periods, except during the pre-1900 period 

and the 1989–2008 non-irrigation seasons when recharge from 

canal seepage was zero (table 4). 

Another aspect indicated in table 4 is that discharge to 

streams was nearly always the largest simulated groundwater outflow, except during pre-1900 when discharge to ET 

constituted most of the outflow and during the 1989–2008 

irrigation seasons when outflow to water entering storage was 

slightly greater than outflow to streams. As discussed in the 

“Conceptual Model” section of this report, before the development of surface-water irrigation, most tributary streams to the 

North Platte River were not perennial, and most groundwater 

discharge (outflow) to streams during this time would have 

been to the North Platte River. Historical measurements that 

could be used to calibrate this aspect of the groundwater-flow 

simulation or even to indicate what groundwater budget components were dominant do not exist —for example, if outflow 

to ET was larger than outflow to streams such as the North 

Platte River. Indications are, however, that simulated outflow 

to streams increased greatly during 1900–50, 1950–89, and 

1989–2008 as a response to the increased recharge from canal 

seepage. The recharge from canal seepage appears to be largest during irrigation seasons from 1989 to 2007, but the simulation used annual stress periods to represent 1950–1989; thus, 

the canal seepage was applied throughout the entire simulation year. From 1989 to 2008, the stress periods more closely 

represent the contrasting hydrology between irrigation and 

non-irrigation seasons. Thus, even if the seepage volume were 

the same before and after 1989, applying the same volume 

of water during a 5-month irrigation season instead of during 

an annual stress period (12 months) results in a higher rate of 

recharge during the shorter period.

Similarly, when comparing simulated seasonal groundwater budgets during the 1989–2008 non-irrigation seasons, the 

summary of total inflows and outflows indicates that during 

the irrigation seasons, the average simulated groundwater 

budget is nearly three times the size of the budget than during 

the non-irrigation seasons (table 4). This increase is largely an 

effect of recharge from canal seepage that occurred at an average simulated rate of 1,385 ft3

/s during the irrigation season. 

Other inflows, such as recharge from precipitation and from 

groundwater inflow, are relatively similar for irrigation and 

non-irrigation seasons (table 4). Recharge from canal seepage 

also causes a change in sign in the simulated flows to and from 

storage for irrigation and non-irrigation seasons. During the 

irrigation season, groundwater flows into storage (also referred 

to as water entering storage) are model outflows, as indicated 

by the negative sign, and can be related to groundwater-level 

rises that take place during the summer when the canals are 

full of water. During the non-irrigation season, groundwater 

flows from storage (water leaving storage) are inflows to the 

groundwater model, as indicated by the positive sign. This 

change in storage can be related to water-level declines that 

take place throughout the non-irrigation season, when the 

canals are empty. The changes in storage and water levels further correspond with hydrographs for many streams that also 

indicate periods of increasing base flow, primarily during the 

irrigation season (May through September), and declining base 

flows from the time the canals are drained of water in the fall 

until the time the canals are refilled before the next irrigation 

season (U.S. Geological Survey, 2012). 

Sensitivity

The sensitivity of a model is generally characterized by 

the effect that a change in a parameter has on the residuals, 

calculated herein as the calibration targets minus the simulated 

equivalents, whether for either base flows or groundwater 

levels. The sensitivity metric was extracted from the Jacobian 

matrix generated by using the PEST automated calibration 

process (Doherty, 2010a) and then multiplying each residual 

by weight of the corresponding observation. Sensitivities 

were summed by same parameter groups used for calibration, including horizontal hydraulic conductivity estimated at 

pilot points; spatial multipliers to recharge; temporal multipliers to recharge; and specific recharge parameters. Larger 

sensitivities indicate that changes in those parameter groups 

had a larger effect on the size of residuals. Sensitivities were 

extracted from the Jacobian matrix after each calibration run 

to determine the parameters that had the largest effect on the 

calibration target residuals. Calibration targets that sensitivities were analyzed for included the following four groups: 

water-level targets for the pre-1950 model (126 weighted 

observations), estimated base-flow targets for the pre-1950 
Simulation of Groundwater Flow 45

model (13 weighted observations), water-level targets 

for the 1950–2008 model (5,101 weighted observations), 

and estimated base-flow targets for the 1950–2008 model 

(738 weighted observations).

There were many more weighted targets for the 

1950–2008 model than for the pre-1950 model; therefore, 

target observations for the 1950–2008 model had a larger 

effect on the calibration process than did the pre-1950 model. 

Changes in parameters that had a large effect on the calibration to 1950–2008 targets, therefore, also had the largest 

sensitivities. The two parameter groups that the 1950–2008 

model calibration (hence, weighted-residuals) was most sensitive to were the canal-seepage spatial multipliers and hydraulic 

conductivity (fig. 22). Canal seepage recharge was the largest 

source of recharge (inflow) to the groundwater-flow model 

and directly affected water levels and groundwater discharge 

to stream base flow. Multipliers adjusting that large inflow of 

water, therefore, had a large effect on simulated groundwater 

levels and simulated stream base flows. Hydraulic conductivity controls the rate of groundwater flow through the aquifer; 

consequently, hydraulic conductivity also directly affected 

water levels and aquifer discharge. 

Assumptions and Limitations

Important assumptions that affected construction of the 

simulation model and, therefore, the results of the simulations 

are included in the following list:

1. Groundwater flow in the study area is dominantly horizontal, and the water table is unconfined. As of 2012, 

little evidence is available to suggest that long-term 

vertical gradients, persisting at longer than seasonal time 

scales, were an important component of flow at the spatial scale of the study area. Therefore, it is appropriate to 

simulate horizontal flow in the aquifer, using one vertical 

layer, and to disregard vertical flow.

2. Groundwater flow is minimal between the alluvial aquifer represented in the model and other aquifers underlying or laterally adjacent to the alluvial aquifer. The 

alluvial aquifer overlies fine-grained silts and clays of 

the Brule Formation of the White River Group (Cannia 

and others, 2006). Hydraulic conductivity of the alluvial 

aquifer is much greater than that of the Brule Formation 

and little flow is thought to take place between the two 

aquifers; therefore, to assume this flow to be negligible 

is appropriate. Laterally, the alluvial aquifer is adjacent 

to the Brule Formation across most of the study area 

(fig. 4), so this assumption is appropriate horizontally, as 

well. In limited areas along the southern boundary, the 

Figure 22. Sensitivity of parameter groups used for calibration.

1

10

100

1,000

10,000

100,000

Temporal multipliers to recharge Spatial multipliers to recharge Hydraulic conductivity estimated

 at pilot points

Specific recharge parameters

Observation group sensitivity to changes in parameter group, 

dimensionless

Parameter group EXPLANATION

Pre-1950 estimated base flow

1950–2008 estimated base flow

Pre-1950 groundwater levels

1950–2008 groundwater levels
46 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

alluvial aquifer may pinch out (thin southward) adjacent 

to very fine to fine-grained sandstones of the Arikaree 

Group; however, little flow is thought to take place 

between the two aquifers. 

3. Sources and sinks that are important to represent in the 

model, such as streams, irrigation wells, and recharge, 

can be appropriately simulated using cells that are 

1,320-ft by 1,320-ft. An inherent assumption when using 

MODFLOW is that aquifer properties and other model 

inputs must be uniformly assigned to each model cell 

(Harbaugh, 2005). Similarly, when a stream is represented in a MODFLOW cell, the stream effectively 

occupies the entire model cell, even if the actual dimensions of the stream are much smaller (or larger). Interaction of that stream with groundwater flow is simulated 

through calculations that represent the center of the 

model cell, regardless of the actual position of the stream 

within the cell or of how much of the cell the stream 

overlies. Stream channel dimensions affect the interaction of simulated streamflow with groundwater but are 

not related to cell dimensions. 

4. Water that leaks from canals and eventually reaches the 

water table can appropriately be simulated as recharge. 

This assumption may not be true for short time periods 

or for small areas; however, the assumption is appropriate for the stress-period lengths and spatial resolution 

used in this model.

5. The largest and most important hydrologic processes 

affecting the groundwater system within the study area 

are represented appropriately in the simulation. As the 

calibration results indicate that the simulation approximately represents the calibration targets, an assumption 

can be made that all the important processes have been 

identified, estimated appropriately, and represented in 

the simulation; or that unrecognized or unrepresented 

processes are too small to have an important hydrologic 

effect; or that average effects of these unrecognized 

processes are included indirectly through adjustments to 

calibration parameters. 

6. Net irrigation-requirement calculations for registered 

irrigation wells using published crop water requirements 

accurately represent actual groundwater withdrawals for 

irrigation. Groundwater withdrawals were only calculated for cells having irrigation wells registered with 

the Nebraska Department of Natural Resources, and the 

assumption was that no other additional wells exist. Further, another assumption was that the amount of groundwater withdrawn from the aquifer was only the amount 

needed to meet the crop-growth requirement as defined 

in University of Nebraska (2002), less the effective 

precipitation that fell during the growing season. Additionally, in the areas where surface water was applied in 

addition to groundwater, the assumption was that surface 

water would be applied first, and groundwater withdrawals would supplement supplies during time periods 

when surface water and precipitation did not satisfy the 

defined crop requirements.

7. Stream base flows estimated for April of each simulated year, using base-flow separation methods with 

streamgage data, represent the actual amount of groundwater discharge in the stream. Base-flow separation is 

largely a signal-processing technique, but the base-flow 

separation results are commonly used as though indicative of base flow (Santhi and others, 2007). Upstream 

regulation, such as reservoir releases or diversions that 

are between streamgages, can obscure the actual stream 

base flow. Beaver activity, ice effects, or freezing conditions can produce inaccurate or estimated streamflow 

records, and ET could directly or indirectly remove base 

flow from the stream before the base flow is measured 

by a streamgage. The month of April, however, is usually free from reservoir releases or diversions and ice or 

substantial ET.

The simulation documented in this report was primarily calibrated to 1950–2008 estimated stream base flows and 

groundwater levels. If the simulation would properly reproduce hydrologic responses for conditions beyond what took 

place during the calibration period is unknown; therefore, the 

hydrologic responses could not be measured or tested within 

the timeframe of this study. Users should be cognizant of the 

risk of using this model for analyses relating to different conceptual models of groundwater flow than for what this model 

was designed and calibrated. As an example, the entire modelcalibration period included recharge from canal seepage as the 

largest component of inflow to groundwater, and few or no 

groundwater levels or streamflow measurements exist before 

the development of canals and the start of canal seepage. The 

simulation, therefore, could not have been calibrated to those 

conditions, and if the model would accurately simulate scenarios where the canals are no longer in operation is unknown. 

As a second example, during 1950–2008, if precipitation was 

much lower than the lowest precipitation or much higher than 

the highest precipitation, groundwater withdrawals for irrigation, recharge from precipitation, and recharge from canal 

seepage could all change and could likely be well beyond the 

range of the calibrated simulation. Because measured water 

levels and stream base flows under those conditions do not 

exist in the historical record, the model could not have been 

calibrated to those conditions, and performance of simulations 

for scenarios including these conditions cannot be assessed.

As an additional limitation, results are affected by simulated As an additional limitation, results are affected by simulated stream inflows and use of base-flow targets for the North 

Platte River. The North Platte River in western Nebraska is 

a complex system featuring upstream reservoir releases and 

diversions into many canal systems that take place inside and 

outside of the study area but, nonetheless, affect the estimated 

base flow and simulated inflows used in this study. Estimated 
Effects of Water-Management Options 47

base flows for April were used for base-flow targets for the 

North Platte River and for simulated routed streamflows at the 

western edge of the model area in Wyoming (fig. 7), which 

also included estimated base flows for October. April and 

October base flows were assumed to be free of the effects 

of early spring snowmelt runoff, the effects of vegetative 

transpiration of stream water, and the effects of canal diversions that usually take place during May through September 

each year. Average base flows spanning each season were not 

used because they would have been affected by all of these 

processes, which are not represented in the simulation. Current 

(2015) techniques such as GSFLOW (Markstrom and others, 

2008), FMP2 for MODFLOW (Schmid and Hanson, 2009) 

or MODFLOW–OWHM (Hanson and others, 2014) would 

allow for a more detailed and comprehensive simulation of 

precipitation, runoff, base flow, and canal operations (among 

other related processes), but these approaches were beyond the 

scope of this study.

Post-Audit of Estimated Groundwater 

Withdrawals

After the groundwater-flow simulation calibration was 

complete, the NPNRD supplied the USGS with metered 

groundwater-withdrawal data (collected using flowmeters 

attached to wells) for 2009 and 2010 that were beyond the 

time period simulated in the model (1950–2008). Other known 

data do not exist for well withdrawals in the study area for use 

in a quality-assurance check of either simulated withdrawals 

or against the NPNRD flowmeter data. The authors, however, 

developed estimates of 2009 groundwater withdrawals based 

on the groundwater-flow model, using methods described next 

in this report, to enable comparison with the recorded withdrawals (flowmeter data) as a post-audit check on the accuracy 

of the groundwater withdrawal estimation method.

For the 2009 estimate, the amount of groundwater applied 

to each field was determined using the process described in 

the “Groundwater Withdrawals” section of this report, but 

using 2009 precipitation. The surface-water delivery data were 

compiled for 2009, used to satisfy crop-irrigation requirements on these fields as the first source of irrigation, and the 

remaining crop-irrigation requirement was considered, as 

before, to be the groundwater withdrawals for irrigation. The 

resulting total 2009 groundwater withdrawal was compared to 

the flowmeter values that were provided for metered locations 

within the simulation study area. The 2009 estimated groundwater withdrawal for cells irrigated with groundwater in the 

simulation area was 17,000 acre-ft, and the 2009 flowmeter 

reading was 13,000 acre-ft for the same wells. Not all of these 

wells used in the estimation had flowmeter readings for 2009, 

either because the well was not equipped with a flowmeter 

or the amount of water used was not recorded in the NPNRD 

database.

A similar comparison was made for fields irrigated with 

surface water and groundwater, also referred to as comingled 

irrigation. Comingled-irrigation groundwater withdrawals for 

2009 were estimated using the same process as described in 

the “Groundwater Withdrawal” section of this report, that is, 

the reported surface-water irrigation deliveries were subtracted 

from the total irrigation demand to estimate the remainder that 

would have been supplied through groundwater withdrawals. 

The 2009 flowmeter readings for wells supplying fields with 

comingled irrigation totaled 22,000 acre-ft. The estimated 

2009 total groundwater withdrawal in comingled areas was 

2,000 acre-ft. Several possible reasons exist for this difference, 

which amounts to less than 2 percent of the post-1950 average groundwater budget (table 4). Groundwater withdrawals 

for irrigation have been increasing since the 1950s and were 

likely high because of drought in the early to mid-2000s. 

Though 2009 growing-season precipitation was only an inch 

less than the 1950–2008 average for the area, the 1999–2008 

average growing season precipitation was 5 in. less than the 

1950–2008 average (National Climatic Data Center, 2009); 

thus, irrigators probably had been routinely pumping much 

more groundwater for the entire decade preceding 2009. Also, 

irrigation practices in the study area could have changed 

during the 2001–2007 drought, wherein more irrigators were 

using groundwater withdrawals to supplement surface-water 

usage to satisfy crop demand. This change could be caused 

by more acres being irrigated than was previously thought, by 

irrigator preference to reduce surface-water consumptive use, 

or by different crops being planted. More detailed analysis, 

beyond the scope of this study, would be required to ascertain 

the exact cause or causes of the difference between estimated 

and metered groundwater withdrawals for comingled irrigation and to determine how to adjust the 1950–2008 simulated 

withdrawals for comingled irrigation.

Effects of Water-Management Options

The calibrated groundwater-flow model was used to 

build a simulation-optimization model to help the NPNRD to 

better understand how certain management decisions could 

affect stream base flows after the calibration period, during 2008–19. The simulation-optimization model was built 

using the Ground-Water Management Process (GWM) for 

the USGS modular groundwater model, (MODFLOW–2000; 

Ahlfeld and others, 2005). The simulation-optimization model 

was constructed to analyze if selected management activities 

would increase the simulated flow of the North Platte River 

at Bridgeport under varying climatic conditions. Management activities analyzed include (1) reductions in groundwater 

withdrawals for irrigation and (2) reductions in groundwater 

withdrawals for irrigation combined with application of intentional recharge. Included in this analysis were three different 

future climate conditions.
48 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Conceptual Approach

The simulation-optimization models simulate 11 years 

beginning at the end of the calibration period groundwaterflow simulation (April 30, 2008, to April 30, 2019). The model 

used two stress periods per year: one for the irrigation season 

and one for the non-irrigation season. The simulation-optimization model inputs were constructed to simulate the following three different future climatic conditions: (1) a period of 

average precipitation conditions, (2) a period of above-average 

precipitation conditions, and (3) a period of below-average 

precipitation conditions. From the historical record, 10-year 

periods were identified that fit these criteria. During the historical record (1895–2008; National Climatic Data Center, 2009), 

the study area received an average of 14.8 in. of precipitation 

per year. The 10-year moving average of precipitation was 

computed and compared to the historical record average. The 

10-year period with the highest average precipitation was from 

1986 to 1995, with an average annual precipitation during 

that period of 18.0 in. The 10-year period with the average 

precipitation closest to the historical average was from 1961 

to 1970, with an average annual precipitation during that time 

period of 14.7 in. The 10-year period with the lowest average 

precipitation was from 1999 to 2008, with the average annual 

precipitation during that period of 13.6 in. (fig. 23).

Construction of Future Period Model

The simulation-optimization model in this study was constructed as an 11-year future period model (2008–19) based 

on the calibrated historical groundwater-flow model. The files 

used to build the future period groundwater-flow model were 

modified from the calibrated groundwater-flow model files 

and from data used to construct the calibrated groundwaterflow model from the identified climatic conditions. That is, the 

mean annual data for the decades with the identified climatic 

conditions were applied to every year of the future period 

simulation. The same MODFLOW packages were used with 

GWM as were used for the calibration model, except that 

GWM did not support the NWT solver, which was replaced 

with the Geometric Multigrid (GMG) solver (Wilson and 

Naff, 2004). The change to the GMG solver also necessitated 

replacement of the Upstream Weighting Package with the 

similar Layer-Property Flow Package. Most GWM packages 

stayed the same for each climatic condition. The StreamflowRouting, Recharge, and Well Packages varied by climatic 

Figure 23. Annual total precipitation and decadal-mean annual precipitation for date ranges used to represent specified precipitation 

conditions, Scottsbluff, Nebraska, 1950–2008.

EXPLANATION

0

5

10

15

20

25

30

1949 1959 1969 1979 1989 1999 2009

Annual precipitation, in inches

Year

Precipitation

Mean annual for decade with lowest precipitation

Mean annual for decade with average precipitation

Mean annual for decade with highest precipitation
Effects of Water-Management Options 49

condition. The aquifer characteristics (for example, aquiferbase altitude, hydraulic conductivity, and specific yield) were 

the same as the calibrated inputs to the calibration period 

model, though only hydraulic conductivity was adjusted during calibration.

The Streamflow-Routing Package was used to simulate 

stream base flow. The North Platte River and Horse Creek are 

the only streams in the model that originate outside the study 

area (fig. 7); inflow from these streams was estimated based 

on the time periods corresponding to the identified climatic 

conditions, and other inputs to the Streamflow-Routing Package were identical to those streams from the calibrated model 

inputs for those time periods. Horse Creek inflows remained 

the same throughout all stress periods in the simulation-optimization model and were specified as the same input used in 

the calibrated model. North Platte River inflows were determined by averaging the April inflows for the corresponding 

historical 10-year period for the irrigation season inputs and 

by averaging the October inflows for the non-irrigation season 

inputs. In other words, mean annual April and October inflows 

from the corresponding 10-year period were used for all 

seasons of the same type; irrigation seasons or non-irrigation 

seasons.

Groundwater recharge for the optimization-flow model 

was created by calculating the average (calibrated) SWB 

recharge during the 10-year period corresponding to each 

selected climatic condition and adding the calibrated canal 

recharge for the same period. The average of the calibrated 

SWB recharge for non-irrigated conditions was used for 

non-irrigation seasons in the simulation-optimization model. 

Recharge, therefore, was the same for all seasons of the same 

type; irrigation seasons or non-irrigation seasons. 

Groundwater withdrawals necessary to meet the full net 

irrigation requirement for the analysis period were estimated 

in a similar way as for the calibration period withdrawals. 

The procedure is described in the “Groundwater Withdrawals” section of this report, and assumes no future changes in 

the land-cover mosaic. The amount of water needed to satisfy 

crops in each cell was estimated from the same land-cover 

classification used for 2008 in the calibration model and the 

University of Nebraska’s crop water-use publication (University of Nebraska, 2002). The mean irrigation-season effective 

precipitation was calculated for the years that correspond to 

each climatic condition. All 492 active wells in the certifiedacres database described in the “Groundwater Withdrawals” 

section of this report were used in the calculations, whether 

they supplied crops irrigated with groundwater only or if they 

supplied crops irrigated with surface water and groundwater. 

Withdrawals, however, were only optimized for wells supplying crops irrigated with groundwater only, as described 

in the “Optimization of the Future Period Model” section of 

this report. Canal delivery to comingled-irrigation acres was 

estimated as the mean delivery for each decadal period specified for selected climatic conditions. The total groundwater 

withdrawal from a well was estimated by subtracting the mean 

effective precipitation and mean surface-water delivery (where 

applicable) from the crop demand. The calculated groundwater-withdrawal values were applied to all irrigation seasons of 

the simulation-optimization model and varied only between 

climatic conditions because of the change in average precipitation during the specified climatic condition (fig. 23).

Optimization of the Future Period Model

The Groundwater-Management Process for the 2005 

version of the USGS modular three-dimensional groundwater 

model (GWM-2005) is designed to minimize or maximize a 

sum of decision variables representing groundwater-management approaches, simultaneously attempting to maintain a 

series of constraints (Ahlfeld and others, 2005). For the first 

analysis, GWM-2005 was used to maximize groundwater 

withdrawals to as much as the full net irrigation requirement, 

and also to maintain the simulated streamflow constraints of 

the North Platte River at the Bridgeport, Nebr., streamgage. 

Groundwater withdrawals were maximized (to the maximum 

of the full net irrigation requirement) because they represent 

the beneficial use of irrigation water needed to successfully 

grow crops. The GWM-2005 decision variables were well 

pumping rates grouped by zone for groundwater-irrigated 

crops. The specified streamflow constraint was successively 

increased until GWM-2005 could not determine a feasible 

solution—that is, no groundwater-withdrawal reduction 

strategy could be determined to meet that specified constraint 

value. The maximum allowed reduction in groundwater 

withdrawals was 50 percent, or one-half the net irrigation 

requirement.

Groundwater withdrawals for groundwater-only irrigated 

crops were grouped using eight well-management zones 

named W1 through W8 (fig. 24). Groundwater-withdrawal 

management zones were delineated by NPNRD and based 

on land-use zones generated for a surface-water model used 

within the NPNRD (T. Kuntz, written commun., July 2010). 

The proportion of discharge assigned to each well in each zone 

was relative to the amount of withdrawal necessary to meet 

full irrigation demand for cropland supplied by that well relative to other wells in the zone, and the proportion of discharge 

assigned to each well remained the same relative to other wells 

in the zone as maximum withdrawals were adjusted by GWM2005. For example, if a well-management zone contained two 

wells and the total withdrawals for the zone were 100 acre-ft 

for an irrigation season, and each well withdrew 50 percent 

of the total, that percentage would be maintained, even if in 

subsequent iterations the total pumpage was decreased by 

one-half to 50 acre-ft; withdrawals for each well would then 

be only 25 acre-ft (or one-half of the original 50 acre-ft). The 

same well-management zones were used for all future climatic 

conditions selected, though the amounts of withdrawals were 

different for each climatic condition.

For the second analysis, GWM-2005 was used to maximize groundwater withdrawals and also to minimize the use 

of intentional recharge at as many as 18 sites, and also to 
50 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 24. North Platte Natural Resources District well-management zones, analysis wells, intentional recharge sites, and maximum 

intentional recharge rates, and streamgage used for optimization of the future period model.

W1

W2

W3

W4

W5

W6

W7

W8

I1

I2 I3

I4

I5

I6

I7

I8

I9

I10

I11

I12

I13

I14 I15

I17

I18

I19

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

104°00’ 103°00’

42°00’

Intentional recharge site and identifier

Maximum intentional recharge rate, in cubic 

feet per second

North Platte River at Bridgeport, Nebraska, 

streamgage

Analysis well

W8

I19

Study area

Well-management zone and identifier

0 to 5

5 to 10

10 to 15

15 to 20
Effects of Water-Management Options 51

maintain the varied constraint of a specified simulated streamflow of the North Platte River at the Bridgeport streamgage. 

The GWM-2005 decision variables were well pumping rates 

for groundwater-irrigated crops by well-management zone 

(8 decision variables) and injection rates of hypothetical wells 

representing intentional recharge sites (18 decision variables). 

Similar to the first analysis, the streamflow constraint was 

successively increased until GWM-2005 could not determine 

a feasible solution. Intentional recharge was minimized so that 

only sites that helped meet the streamflow constraint would be 

used in the solution.

Sites suitable for intentional recharge were defined in 

GWM-2005 to be managed on an individual basis (instead of 

by zone). Conceptually, intentional recharge was envisioned 

as the delivery of canal water into a specified unused field 

with the intention of letting the water seep into the ground to 

recharge the aquifer. Intentional recharge sites were selected 

using aerial photographs (Dollison, 2010). Sites selected were 

sandy rangeland fields that were close in proximity to canals. 

Intentional recharge sites were represented as injection wells 

in the simulation-optimization model, which had the same 

effect on simulated hydrology as water being applied at land 

surface that instantaneously reached the water table. The maximum rate of intentional recharge was specified as 0.5 ft3

/s per 

cell, multiplied by the number of cells per site, and multiplied 

by 0.45 to account for losses to ET and other environmental 

losses; this loss ratio was similar to canal losses in the calibration model. Selected sites ranged from 400 to 2,800 acres, and 

maximum simulated intentional recharge rates ranged from 

680 to 4,800 acre-ft per season (2–16 ft3

/s per site, fig. 24); 

with a maximum potential recharge of 113 ft3

/s for all sites 

combined. Simulated intentional recharge was only applied 

during the irrigation season. As of 2012, the canals do not 

carry water during the non-irrigation season; thus, no water 

would be available for intentional recharge during the nonirrigation season. For these simulations, the managed pumping 

and intentional recharge variables were active for all irrigation 

stress periods.

In addition to the files needed to simulate groundwater 

flow, control files are needed to define the GWM configuration and solution approaches for the stated problem. The 

GWM files used for these optimization scenarios are objective 

function, variable constraint, decision variable, streamflow 

constraint, and solution. The objective-function file was the 

same for each management scenario (well management or 

well management plus intentional recharge) and specified the 

objective function to be maximized as well as coefficients for 

each decision variable. 

The decision-variable and variable-constraint files were 

used together to define the characteristics of the well decision 

variables for each optimization scenario. The decision-variable 

file specified what portion of the total groundwater withdrawals came from each well in a zone, the location of each well, 

and the stress periods that these variables were active. For the 

scenarios that also used intentional recharge, the decisionvariable file also contained information about the location of 

intentional-recharge sites. The variable-constraint file specified 

the minimum and maximum rate of groundwater withdrawals 

allowed for each zone, which ranged from 50 to 100 percent of 

the calculated irrigation requirement for each climatic condition. For the scenarios that also used intentional recharge, the 

variable-constraint file also specified the allowed minimum 

and maximum rate of application of intentional recharge that 

ranged from 0 to 113 ft3

/s for all sites and from 2 to 16 ft3/s for 

the 18 potential sites.

The streamflow-constraint file specified the minimum 

base flow at a given stream segment, corresponding to the 

North Platte River at Bridgeport streamgage. The streamflowconstraint value was increased by 5 ft3

/s during each iteration. 

Simulations iteratively determined the maximum base-flow 

discharge at the Bridgeport streamgage under the specified 

scenario’s constraining decision variables, until GWM-2005 

could not determine a feasible solution that satisfied all 

constraints applied. For below-average precipitation conditions, the streamflow constraint was applied to every irrigation season during 2009–18; however, preliminary testing for 

below-average precipitation conditions indicated that irrigation season streamflows declined during 2009–18. The last 

irrigation season for 2018 had the lowest simulated stream 

base flow; therefore, when the constraint for the irrigation 

season of 2018 was met, so were the streamflow constraints 

for irrigation seasons during 2009–17. For average and aboveaverage precipitation conditions, the streamflow constraint 

was applied to the last five irrigation seasons of the future 

period, corresponding to 2014–18. Preliminary testing for 

average and above-average precipitation conditions indicated 

increases in simulated stream base flow for irrigation seasons 

during 2009–18. Under these conditions, when the earliest 

stream base-flow constraint was met, so were the constraints 

for following irrigation seasons.

The solution file was the same for each optimization scenario applying the future model. The solution file determines 

the solver and specified settings to be used in determining the 

best possible solution for the problem. Many different solution 

settings exist that can be applied to the model. For the specific problems of the studied scenarios, the linear-programing 

solution of GWM-2005 was used. The sequential linear-programing solution was also tested but produced nearly the same 

result and increased the computation time for each analysis; 

therefore, the linear-programing solution was used for all 

analyses.
52 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Base-Case Simulations without Management

The baseline simulations, or base case, involved no managed decreases in groundwater withdrawals (no management 

through optimization). With average precipitation, the basecase future model simulated a maximum discharge of 425 ft3

/s 

at the Bridgeport streamgage at the end of the 2018 irrigation 

season (table 5). Groundwater withdrawals for each management zone ranged from 1 ft3

/s in zone 7 to 16 ft3/s in zone 2 

(table 6). With below-average precipitation in the future model 

and no management through optimization, the future model 

simulated a maximum discharge of 302 ft3

/s at the Bridgeport 

streamgage at the end of the 2018 irrigation season (table 5). 

Groundwater withdrawals for each zone ranged from 1 ft3/s 

in zone 7 to 17 ft3/s in zone 2 (table 6). With above-average 

precipitation in the future model and no management through 

optimization, the future model simulated a maximum discharge of 556 ft3

/s at the Bridgeport streamgage at the end of 

the 2018 irrigation season (table 5). Groundwater withdrawals 

for each zone ranged from 1 ft3/s in zone 7 to 16 ft3/s in zone 2 

(table 6).

Table 5. Summary of optimization model results for simulated stream base flow under below-average, average, and above-average 

precipitation, with and without optimized groundwater withdrawals and intentional recharge, September 30, 2018, from simulation of 

2008–19.

[Streamflows correspond to simulated results for the North Platte River at Bridgeport, Nebraska, in cubic feet per second]

Precipitation 

condition

Maximum 

streamflow with 

full pumpage 

(base case)

Maximum 

streamflow with 

reduced 

pumpage

Maximum streamflow 

with reduced 

pumpage and 

intentional recharge

Maximum rate for all 

intentional recharge sites 

(cubic feet per second)

Optimized rate for all 

intentional recharge sites 

(cubic feet per second)

Below average 302 310 325 113 69

Average 425 430 440 113 22

Above average 556 560 575 113 37

Table 6. Summary of optimization model results for simulated management scenarios—groundwater withdrawals by management 

zone and optimized intentional-recharge rates, September 30, 2018, from simulation of 2008–19.

[Results are given in cubic feet per second. na, not applicable]

Wellmanagement 

zone 

(fig. 24)

Above-average precipitation conditions Average precipitation conditions Below-average precipitation conditions

No 

optimization 

(base case)

Optimized 

pumpage

Optimized 

pumpage and 

intentional 

recharge

No 

optimization 

(base case)

Optimized 

pumpage

Optimized 

pumpage and 

intentional 

recharge

No 

optimization 

(base case)

Optimized 

pumpage

Optimized 

pumpage and 

intentional 

recharge

W1 12 7 6 12 6 6 13 7 7

W2 16 16 8 16 16 10 17 11 9

W3 6 3 3 6 3 3 6 3 3

W4 5 5 2 5 4 3 5 3 3

W5 3 3 2 3 2 2 3 2 2

W6 2 1 1 2 1 1 3 2 2

W7* 1 0 0 1 0 0 1 0 0

W8 6 6 3 7 7 7 7 7 3

Sum 51 41 25 52 39 32 56 34 28

Intentional 

recharge

na na 37 na na 22 na na 69

*Reduction for W7 was 50 percent but appears to be 100 percent because of rounding.
Effects of Water-Management Options 53

Simulations with Management of Groundwater 

Withdrawals

The first approach used for optimization of the future 

model was to determine the maximum stream base flow that 

could be sustained at the North Platte River at Bridgeport 

streamgage in the 2018 irrigation season by reducing groundwater withdrawals within each of eight management zones. 

The following paragraphs describe the results for each climatic 

condition.

For average precipitation conditions, the maximum base 

flow attainable at the Bridgeport streamgage by optimizing 

managed groundwater withdrawals was 430 ft3

/s, which is 

5 ft3

/s larger than for the base case (table 5). Managed groundwater withdrawals were about 13 ft3

/s smaller than for the 

base case (table 6), and decreases relative to the base case 

varied among management zones as shown in figure 25. At a 

specified base-flow constraint of 435 ft3

/s, no solution to the 

problem was feasible; the streamflow constraint could not be 

met with the maximum (50-percent) reduction in groundwater 

withdrawals in all eight management zones. 

For below-average precipitation conditions, the maximum flow at the Bridgeport streamgage with managed groundwater withdrawals was 310 ft3

/s, which is 8 ft3/s larger than 

for the base case (table 5). Managed groundwater withdrawals 

were about 22 ft3

/s smaller than for the base case (table 6). 

At 315 ft3

/s, no solution to the problem was feasible; the 

streamflow constraint could not be met with the maximum 

(50-percent) reduction in groundwater withdrawals in all eight 

management zones.

For above-average precipitation conditions, the maximum 

flow at the Bridgeport streamgage with managed groundwater withdrawals was 560 ft3

/s, which is 4 ft3/s larger than for 

the base case (table 5). Managed groundwater withdrawals 

were about 10 ft3

/s smaller than for the base case (table 6). 

At 565 ft3

/s, no solution to the problem was feasible; the 

streamflow constraint could not be met with the maximum 

(50-percent) reduction in groundwater withdrawals in all eight 

management zones.

The optimized solution determined by GWM-2005 also 

indicates how management of the withdrawals in each zone 

benefits, or does not benefit, simulated stream base flow of 

the North Platte River at the Bridgeport streamgage. For 

instance, with average precipitation, to meet a 430 ft3

/s simulated stream base flow constraint, withdrawals were reduced 

by the maximum amount of 50 percent of the net irrigation 

requirement for zones W1, W3, W6, and W7 (table 6). This 

means that reductions in withdrawals in these zones produced 

increased simulated base flow of the North Platte River at the 

Bridgeport streamgage. Meanwhile, withdrawals were reduced 

by less than 50 percent (W4 and W5) or were not reduced in 

the remaining zones (W2 and W8), indicating that within the 

simulation period analyzed, withdrawal reductions in those 

zones were not as beneficial to increasing the simulated stream 

base flow within the analysis period. Reductions in withdrawals for future simulations with below-average precipitation 

(fig. 26) and above-average precipitation (fig. 27) can be 

interpreted similarly. Also, in these three scenarios, withdrawals were never reduced in area W8, indicating that reducing 

withdrawals in that area did not increase stream base flow 

within the future model period. Generally, simulated base flow 

was best optimized by reductions in groundwater withdrawals 

north of the North Platte River and in the western half of the 

area.

Further insight into the benefit of managed withdrawals 

by zone can be gained by inspection of response coefficients 

(table 7). Response coefficients output by GWM-2005 represent the ratio in the value of stream base flow (or water level) 

at each constraint location to a change in the decision variable 

flow rate (Ahlfeld and others, 2009). Response coefficients for 

management zones W1–W8 (table 7) represent the amount of 

stream base flow decline at the constraint location (the North 

Platte River at Bridgeport), for increases in withdrawals above 

the 50 percent minimum withdrawal baseline (with no managed withdrawals). GWM-2005 outputs response coefficients 

for all constraint locations and times. Constraints for this study 

were always located at the North Platte River at Bridgeport 

but distributed in time through at least the last five irrigation 

seasons of the future period. For this study, simulated stream 

base flow increased relative to streamflow at the end of the 

calibration period (338 ft3

/s; fig. 19) during the future period 

for average and above-average precipitation conditions and 

decreased during the future period for below-average precipitation conditions. In this case, therefore, when the earliest 

stream base flow constraint was met, all the other constraints 

later in time would also be met. Under below-average precipitation conditions, the latest (last) streamflow constraint 

was binding, and when that last constraint was met, the earlier 

constraints were also met. Binding constraints can be thought 

of as the constraints that were hardest to meet in this optimization analysis, and that had the largest effect on the optimal 

pumping rates; therefore binding constraint response coefficients (table 7) are the most valuable to understand.

For example, if withdrawals were increased by 1 ft3/s 

for management zone W1 under average precipitation conditions, table 7 indicates that that response coefficient is 0.38 at 

the time of the binding streamflow constraint (stress period 

13), and simulated stream base flow at the constraint location would decline by 0.38 ft3

/s (1 ft3/s multiplied by 0.38). 

Response coefficients are largest for management zones 

W6 and W7 (table 7), indicating that increases in managed 

withdrawals within those zones caused the largest declines in 

simulated streamflow at the constraint location. Alternately, 

response coefficients are smallest for management zones W2 

and W8, indicating that increases in managed withdrawals in 

those zones had a much smaller effect on simulated stream 

base flow at the constraint location. In fact, as noted in the 

“Simulations with Management of Groundwater Withdrawals” section of this report, to meet the maximum of 430 ft3

/s 

streamflow at the constraint location under average precipitation conditions (table 5), withdrawals were reduced by the 

maximum amount in management zones W1, W3, W6, and 
54 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 25. Optimized groundwater withdrawals by zone for the future model with average precipitation; groundwater withdrawal 

rate reductions are relative to the base-case scenario.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

Pumping rate reduction, in 

cubic feet per second

W8

Study area

Well management zone and 

identifier

Analysis well

1 to 2

3 to 4

Greater than or equal to 5

No reduction

104°00’ 103°00’

42°00’
Effects of Water-Management Options 55

Figure 26. Optimized groundwater withdrawals by zone for the future model with below-average precipitation; groundwater 

withdrawal rate reductions are relative to the base-case scenario.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

Pumping rate reduction, in 

cubic feet per second

W8

Study area

Well management zone and 

identifier

Analysis well

1 to 2

3 to 4

Greater than or equal to 5

No reduction

104°00’ 103°00’

42°00’
56 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Figure 27. Optimized groundwater withdrawals by zone for the future model with above-average precipitation; groundwater 

withdrawal rate reductions are relative to the base-case scenario.

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000 EXPLANATION

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

Pumping rate reduction, in 

cubic feet per second

W8

Study area

Well management zone and 

identifier

Analysis well

1 to 2

3 to 4

Greater than or equal to 5

No reduction

104°00’ 103°00’

42°00’
Effects of Water-Management Options 57

W7 (table 6). Zones W1, W3, W6, and W7 also have the 

largest response coefficients (table 7); therefore, reductions in 

withdrawals in those zones caused more increases in simulated 

stream base flow at the constraint location than did reductions 

in withdrawals in other zones. 

Through the optimization of managed groundwater 

withdrawals, the simulated future base flow of the North Platte 

River at the Bridgeport streamgage increased by 4–8 ft3/s 

in the irrigation season of 2018 across various precipitation conditions. Though this may only be a small part of 

base flow passing the North Platte River at Bridgeport, 

Nebr., streamgage, different results, such as larger base-flow 

increases, are possible. Results presented in this report are 

one set of answers given the particular timing and location 

of constraints and decision variables used to construct the 

simulation-optimization model as a tool for analysis. Future 

users of the simulation-optimization model will be able to 

modify the input files to alter constraints, to alter time periods 

that the constraints are applied to, to alter decision variables 

constraining groundwater withdrawals by zone, and to alter 

other variables to explore other feasible management scenarios 

that may yield larger increases in simulated future base flow of 

the North Platte River. 

Table 7. Response coefficients of decision variables at time step when the binding streamflow 

constraint in the optimization model was evaluated, from simulation of 2008–19.

[<, less than. Shading indicates intentional recharge sites that were used in the optimized solution at the maximum 

possible simulated stream base flow.]

Wellmanagement 

zone 

(fig. 24)

Above-average 

precipitation conditions

(response coefficient)

Average precipitation 

conditions

(response coefficient)

Below-average 

precipitation conditions

(response coefficient)

W1 0.37 0.38 0.38

W2 0.25 0.26 0.28

W3 0.40 0.41 0.42

W4 0.32 0.33 0.33

W5 0.37 0.37 0.41

W6 0.59 0.58 0.55

W7 0.59 0.52 0.62

W8 0.16 0.15 0.16

Intentional recharge site

I1 0.01 0.01 0.02

I2 <0.01 <0.01 0.01

I3 <0.01 <0.01 <0.01

I4 <0.01 <0.01 0.02

I5 0.28 0.28 0.30

I6 0.70 0.70 0.67

I7 0.02 0.02 0.06

I8 0.33 0.32 0.34

I9 0.04 0.03 0.04

I10 0.30 0.32 0.35

I11 0.22 0.22 0.29

I12 0.20 0.19 0.28

I13 0.19 0.19 0.22

I14 <0.01 <0.01 <0.01

I15 <0.01 <0.01 <0.01

I17 0.07 0.07 0.13

I18 <0.01 <0.01 <0.01

I19 0.28 0.28 0.26
58 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

Simulations with Management of Groundwater 

Withdrawal and Intentional Recharge

The second analysis used for optimization of the future 

model was to determine the maximum simulated stream base 

flow at the Bridgeport streamgage by managing groundwater 

withdrawals and intentional recharge rates. Groundwater withdrawals were again grouped by the eight management zones 

shown in figure 24, and the proportion of discharge assigned to 

each well in the zone remained the same whereas the groundwater withdrawals were maximized within the range from 50 

to 100 percent of the net irrigation requirement. Intentional 

recharge was minimized at 18 sites, managed individually; 

therefore, individual intentional recharge sites were only used 

if the sites helped satisfy the streamflow constraints. 

For average precipitation conditions, the maximum flow 

at the Bridgeport streamgage with managed groundwater 

withdrawals and intentional recharge was 440 ft3

/s, which 

is 15 ft3

/s larger than for the base case (table 5). Managed 

groundwater withdrawals were reduced in seven of the 

management zones to about 20 ft3

/s smaller than for the base 

case (table 6), and 5 of the 18 possible intentional recharge 

sites were used (fig. 28), with a combined recharge rate of 

22 ft3

/s. The five intentional recharge sites used were located 

across the model area, with three of the five close to the North 

Platte River and two closer to the northern boundary of the 

area (fig. 28). The five sites used in the optimized solution 

also had the five largest response coefficients (table 7), and 

because every site was optimized to apply recharge at the 

maximum recharge rate, the differences in applied recharge 

rates were proportional to the size of the sites (larger sites had 

larger rates). Of the five sites used, four are relatively close 

to streams, which may partially explain the larger response 

coefficient. 

In addition, several sites (I1–I4, I14, I15, and I18) had 

low response coefficients, less than or equal to 0.01 (table 7); 

therefore, if 10 ft3

/s of intentional recharge were applied at 

one of these sites, simulated stream base flow at the constraint 

location would increase by a maximum of 0.1 ft3

/s. Combined, 

at 10 ft3

/s of intentional recharge per site across the seven 

sites, simulated stream base flow at the constraint location 

would increase by a maximum of 0.7 ft3

/s. In some cases, 

sites with small response coefficients are located in poorly 

transmissive areas of the aquifer or are near model boundaries. 

Conversely, site I6 is also in an area of moderately low transmissivity (fig. 21) and was not near streams (fig. 24); however, 

site I6 had a larger response coefficient and was used in the 

optimized solution (table 7). The possibility exists that site I6 

had a larger response coefficient because it is up-gradient of 

a gap in the ridge separating the two thickest parts of alluvial 

valley-fill deposits in the area. The responses of the groundwater system to changes in decision variables, such as withdrawals or intentional recharge, are complex.

These results are subject to the availability and location 

of intentional recharge sites as well as the timing and location 

of the streamflow constraints specified for these analyses. For 

a base-flow constraint of 445 ft3

/s, no solution to the problem 

was feasible; the streamflow constraint could not be met even 

with the addition of intentional recharge and using the maximum (50-percent) reduction in groundwater withdrawals in all 

eight zones.

For below-average precipitation conditions, the maximum flow at the Bridgeport streamgage with managed groundwater withdrawals and intentional recharge was 325 ft3

/s, 

which is 23 ft3

/s larger than for the base case (table 5). Managed groundwater withdrawals were reduced in all eight of 

the management zones to the maximum 50-percent reduction, 

about 28 ft3

/s smaller than for the base case (table 6), and 13 

of the 18 possible intentional recharge sites were used (fig. 29) 

at a combined rate of 69 ft3

/s (table 6). Of the intentional 

recharge sites that were used, eight sites are located in the 

upstream (western) end of the area and are relatively near the 

North Platte River, two sites are near the North Platte River 

but in the downstream (eastern) end of the area, and three 

sites are located in the central part of the area but closer to 

the northern boundary (fig. 29). The 13 intentional recharge 

sites that were used in this solution had the 13 largest response 

coefficients (table 7). At 330 ft3

/s, the problem was infeasible; 

the streamflow constraint could not be met with the addition 

of intentional recharge and with the maximum (50-percent) 

reduction in groundwater withdrawals in all eight zones.

For above-average precipitation conditions, the 

maximum flow at the Bridgeport streamgage with managed groundwater withdrawals and intentional recharge 

was 575 ft3

/s, which is 19 ft3/s larger than for the base case 

(table 5). Managed groundwater withdrawals were reduced 

in all eight of the management zones to the maximum 

50-percent reduction, about 26 ft3

/s smaller than for the base 

case (table 6), and 9 of the 18 possible intentional recharge 

sites were used (fig. 29) at a combined rate of 37 ft3

/s (table 6). 

The nine sites used had the nine largest response coefficients 

(table 7). More than 50 percent (five of nine) of the intentional 

recharge sites used were near the upstream end of the area and 

relatively near the North Platte River, and two of the nine sites 

used were near the North Platte River but in the downstream 

half of the area (fig. 30). At 580 ft3

/s, the problem was infeasible; the streamflow constraint could not be met with the addition of intention recharge and with the maximum (50-percent) 

reduction in groundwater withdrawals in all eight zones.

Through the optimization of maximized groundwater 

withdrawals and minimized application of intentional 

recharge, simulated stream base flow for the North Platte 

River at Bridgeport increased by 15–23 ft3

/s above the basecase simulation with no optimization, or about 10–15 ft3

/s 

larger than the tests with optimized groundwater withdrawals only. For the scenario with managed intentional recharge 

also included, the authors noted that because the application 

of intentional recharge was minimized, only the sites where 

simulated intentional recharge was applied, as shown in 

figures 28–30, produced increased simulated base flow of the 

North Platte River at the Bridgeport streamgage subject to 

the time and location of the constraints applied. Conversely, 
Effects of Water-Management Options 59

GOSHEN

COUNTY

MORRILL

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SCOTTS BLUFF

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BANNER

COUNTY

LARAMIE

COUNTYWYOMING

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104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

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41°50’

41°40’

0 3 6 9 12 MILES

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Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

EXPLANATION

Not used

2 to 5

5 to 8

Pumping rate reduction, in cubic feet 

per second

W8

Study area

Well management zone and identifier

Analysis well

Intentional recharge site

Intentional recharge rate, in cubic feet 

per second

1 to 2

3 to 4

Greater than or equal to 5

No reduction

104°00’ 103°00’

42°00’

Figure 28. Optimized simulated intentional recharge by site and 

simulated groundwater withdrawals by well-management zone 

for the future model with average precipitation; groundwater 

withdrawal rate reductions are relative to the base-case scenario.
60 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

groundwater withdrawals were reduced the most in the 

management zones with the largest response coefficients. 

The intentional recharge sites that were used tended to be 

slightly biased towards being closer to the North Platte River 

(figs. 29–30), but not in all cases (fig. 28). Sites closer to the 

river likely cause a quicker increase in groundwater discharge 

to the North Platte River from nearby intentional recharge 

sites than for sites further from the North Platte River. Different intentional recharge sites might be selected for use in the 

optimal solution if the timing or location of the constraints 

were changed. Further, five of the sites were used for optimized intentional recharge regardless of the precipitation conditions in the future model (figs. 28–30). Common use of these 

sites indicates that application of intentional recharge at those 

locations increased simulated base flow of the North Platte 

River at the Bridgeport streamgage regardless of whether the 

future climate was wetter, drier, or the same as past climate. 

Response coefficients indicate the relative effect of each decision variable change on the binding streamflow constraint 

from these analyses, and for intentional recharge, the sites 

that had the largest coefficients were used first (table 7). In 

addition, five intentional recharge sites were not used in this 

optimization analysis regardless of future precipitation condition (I2, I3, I14, I15, and I18 [fig. 24; table 7]). Those five 

sites have small response coefficients and are located in poorly 

transmissive areas of the aquifer or near model boundaries. 

Less than 1 percent of the simulated intentional recharge 

applied at these sites would result in increases in simulated 

stream base flow of the North Platte River at Bridgeport.

Analysis Limitations and Potential Areas for 

Additional Study

The optimization analysis results presented in this report 

are dependent on the accuracy of the calibrated groundwaterflow model, the assumptions inherent to the groundwater-flow 

and simulation-optimization models, and the assumptions 

inherent in estimated simulation inputs for the future time 

periods for conditions of below-average, average, or aboveaverage precipitation. The results are further dependent on the 

specifications used in the optimization setup, the timing and 

location of the constraints and decision variables applied, and 

the specified minimum and maximum rates for each decision 

variable. These results are not intended to catalog every possible set of circumstances but rather to provide a demonstration of how this model can be used as a tool to investigate the 

effects of water-management options on the base flow of the 

North Platte River at Bridgeport streamgage. Changes in any 

of the aspects mentioned before would likely generate different results and differences could be substantial. For example, 

in the analysis documented in this report, the streamflow constraints for the average and above-average precipitation conditions were applied for the last 5 years of the analysis period, 

at the end of irrigation season only. If constraints were applied 

to a different subset of the analysis period, perhaps only to 

the last year, a different amount of simulated stream base flow 

might be sustainable.

Additionally, an assumption was made concerning the 

use of injection wells to simulate intentional recharge in the 

optimization analysis. Intentional recharge can be adequately 

simulated using injection wells because the depth to the 

groundwater is small and the sandy areas selected as potential 

sites have high permeabilities. In these areas, the transit time 

of intentional recharge applied at land surface to reach the 

water table would be small, and therefore similar to that when 

using an injection well for artificial recharge.

In addition to the mentioned limitations, differences 

existed between estimated and metered groundwater withdrawals for comingled irrigation, which were beyond the 

scope of this study to resolve. If future studies determine 

the cause of these differences and an approach to adjust the 

simulated withdrawals is used in the calibration model to more 

closely match metered co-mingled withdrawals, the previous 

calibration may no longer be valid. The calibration could then 

be re-evaluated and the effects of water-management options 

could be re-checked. Similarly, new data and simulation 

approaches have become available since most of the work on 

this study was completed; those data and approaches could be 

considered for future addition to this model and may improve 

or further refine the results.

With respect to new data, new aquifer altitude-base data 

from Abraham and others (2012) could be used to further 

refine the base-of-aquifer surface used in this model; only 

part of the data from that study were complete at the time of 

interpretation of an aquifer base for this model; therefore, only 

part of those data were incorporated into the aquifer base for 

the simulation documented in this report. Also, approaches 

such as the Farm Process Version 2 for MODFLOW–2005 

(MF–FMP2, Schmid and Hanson, 2009) or the One-Water 

Hydrologic Flow Model (MODFLOW–OWHM, Hanson and 

others, 2014) would (1) allow for a comprehensive, simulation 

of landscape (surface) hydrology fully coupled with groundwater hydrology, (2) provide for a means to simulate base flow 

and runoff, (3) allow for more realistic simulation of subirrigation of crops with shallow groundwater and the apportionment 

of water through surface-water delivery and supplemental 

groundwater withdrawal, (4) allow groundwater and surfacewater irrigation to be driven by supply and demand concepts, 

(5), allow for an improved calibration to raw measured streamflow data as opposed to processed stream base-flow data, 

and (6) would provide an opportunity to calibrate the simulation using the metered groundwater withdrawal data. All 

these improvements in data and methodology could provide 

additional insight into the estimation of comingled groundwater withdrawal and difference from metered comingled 

groundwater withdrawal.
Effects of Water-Management Options 61

GOSHEN

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MORRILL

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SCOTTS BLUFF

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BANNER

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LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

EXPLANATION

Not used

2 to 5

5 to 8

Greater than 8

Pumping rate reduction, in cubic feet 

per second

W8

Study area

Well management zone and identifier

Analysis well

Intentional recharge site

Intentional recharge rate, in cubic feet 

per second

1 to 2

3 to 4

Greater than or equal to 5

104°00’ 103°00’

42°00’

Figure 29. Optimized intentional recharge and groundwater 

withdrawals by zone for the future model with below-average 

precipitation; groundwater withdrawal rate reductions are 

relative to the base-case scenario.
62 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

GOSHEN

COUNTY

MORRILL

COUNTY

SCOTTS BLUFF

COUNTY

BANNER

COUNTY

LARAMIE

COUNTYWYOMING

NEBRASKA

104°10’ 103°50’ 103°40’ 103°30’ 103°20’ 103°10’

42°10’

41°50’

41°40’

0 3 6 9 12 MILES

0 3 6 9 12 KILOMETERS

Base from U.S. Geological Survey digital data, 1:633,000

Lambert Conformal Conic projection

Standard parallels 41°30’ N and 42°20’ N

Central meridian 103°04’ W

Horizontal coordinate information is referenced 

to the North American Datum of 1983 (NAD 83)

SIOUX

COUNTY

BOX BUTTE

COUNTY

W1

W2

W3

W4

W5 W6

W7

W8

EXPLANATION

Not used

2 to 5

5 to 8

Pumping rate reduction, in cubic feet 

per second

W8

Study area

Well management zone and identifier

Analysis well

Intentional recharge site

Intentional recharge rate, in cubic feet 

per second

1 to 2

3 to 4

Greater than or equal to 5

104°00’ 103°00’

42°00’

Figure 30. Optimized intentional recharge and groundwater 

withdrawals by zone for the future model with above-average 

precipitation; groundwater withdrawal rate reductions are 

relative to the base-case scenario.
Summary 63

Summary

The North Platte Natural Resources District (NPNRD) 

has been actively collecting data and studying groundwater 

resources because of concerns about the future availability 

of the highly interconnected surface-water and groundwater resources. This report, prepared by the U.S. Geological 

Survey in cooperation with the North Platte Natural Resources 

District, describes a groundwater-flow model of the North 

Platte River valley from Bridgeport, Nebraska, extending west 

to 6 miles into Wyoming. The model was built to improve the 

understanding of the interaction of surface-water and groundwater resources and as an optimization tool able to analyze the 

effects of water-management options on the simulated stream 

base flow of the North Platte River. Previous studies in this 

area include regional groundwater-flow models, geophysical investigations of aquifer and canal properties, and studies 

of groundwater age and quality. Agricultural production in 

the semiarid study area is sustained through irrigation that 

was developed primarily from surface water before 1900 and 

from surface water and groundwater during 1950–2008. In 

2012, about three-quarters of the study area was irrigated with 

surface water. The principal hydrogeologic unit within the 

study area is Quaternary age and includes alluvial deposits and 

colluvial deposits mixed with alluvial deposits. The base-ofaquifer, which is the surface where the oldest sediments composing the alluvial aquifer were deposited, is highly irregular 

and contains paleovalleys and ridges parallel or subparallel to the modern-day North Platte River. Using previously 

published aquifer-base-altitude contours in conjunction with 

newer test-hole and geophysical data, a new base-of-aquifer 

altitude map was generated because of the strong effect of the 

aquifer-base topography on groundwater-flow direction and 

magnitude. Groundwater flow is generally west to east but 

also to the North Platte River and its tributaries. The alluvial 

aquifer is thickest in the paleovalley in the center of the study 

area and thins to 10 feet (ft) near the northern and southern 

boundaries where the aquifer adjoins fine-grained sediments 

of Tertiary age. The largest inflow to groundwater is recharge 

originating from water leaking from canals, and is much 

larger than recharge originating from infiltration of precipitation. The largest component of groundwater discharge from 

the study area is to the North Platte River and its tributaries, 

with smaller amounts of discharge to evapotranspiration and 

groundwater withdrawals for irrigation. Groundwater withdrawals for irrigation increased during 1950–2008, but were 

a relatively small component of total groundwater outflows 

in 2008. 

The groundwater system and related sources and sinks 

of water were simulated using MODFLOW–NWT, a newton formulation of the 2005 version of the U.S. Geological 

Survey modular three-dimensional groundwater model with an 

improved ability to solve nonlinear unconfined aquifer simulations with wetting and drying of cells. The single-layer model 

of unconfined intergranular flow was built as two sequential 

models with stress periods ranging from months to decades to 

represent the system before substantial groundwater development for irrigation (pre-1950 model), and during groundwater 

development for irrigation through April 2008 (1950–2008 

model). Potential recharge (deep percolation) from infiltration 

of precipitation was estimated with a daily soil-water-balance 

model. Annual recharge from canal seepage was estimated 

with available records from the Bureau of Reclamation and 

then modified with canal-seepage potentials estimated from 

geophysical data. Groundwater withdrawals were estimated 

using land-use and land-cover data, precipitation data, and 

published crop water-use data. For fields irrigated with surface 

water and groundwater, surface-water deliveries were subtracted from the estimated net irrigation requirement, and 

groundwater withdrawal was assumed to be equal to any 

demand unmet by surface water. Initial aquifer hydraulic conductivity was assigned to the groundwater-flow model based 

on published data. 

Because many of the inputs were unknown and had to 

be estimated, the groundwater-flow model was calibrated to 

ensure that the simulated groundwater levels and groundwater 

discharge to streams reasonably reproduced measured conditions. Calibration was evaluated by comparison of simulated 

conditions against calibration targets comprised of base flows 

estimated using the base-flow index method and measured 

groundwater levels. The parameter estimation suite of software (PEST) was used for model calibration, to perform 

automated parameter adjustments using statistical techniques. 

PEST was used to adjust hydraulic conductivity of the aquifer, spatial multipliers to recharge, temporal multipliers to 

recharge, and two specific recharge parameters; for a total of 

273 parameters. Tikhonov regularization was used to stabilize the parameter estimation solution process and prevent 

over-fitting. 

Most simulated groundwater levels and stream base 

flows were reasonably near the calibration targets at the end 

of the pre-1950 model. The mean difference between pre1950 model simulated and groundwater levels and targets was 

-2.3 ft. The mean residual for more than 5,100 groundwater 

levels spanning 1950–2008 was -5.7 ft, and simulated groundwater levels were within 25 ft from measured groundwater 

levels for 94 percent of those targets. The streamgage on the 

North Platte River at Bridgeport is near the eastern end of 

the model and accumulates all the base flow that is simulated 

everywhere else in the model; simulated base flow reasonably matched estimated base flow for this streamgage during 

1950–2008, with an average difference of 15 percent. Base 

flow simulated by the 1950–2008 model followed the overall 

trend of the estimated base flow reasonably well, with generally increasing or decreasing base flows from the start of the 

simulation to the end. Simulated base flow also matched estimated base flow reasonably well for most of the North Platte 

River tributaries with estimated base flow. 

Simulated groundwater budgets for the 1950–2008 model 

featured large inflows from recharge from canal seepage, 

with a small component of recharge from precipitation. About 

98 percent of groundwater outflows were accounted for by 
64 Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska

discharge to streams (77 percent) and by evapotranspiration 

(21 percent). Less than 2 percent of groundwater outflow was 

to groundwater withdrawals for irrigation. Average simulated 

groundwater budgets for 1989–2008 were nearly three times 

larger for irrigation seasons than for non-irrigation seasons. 

The calibrated groundwater-flow model was used to 

build a simulation-optimization model to provide a tool for 

the NPNRD to better understand how water-management 

decisions could affect stream base flows in a future period 

from 2008 to 2019, under varying climatic conditions. The 

simulation-optimization model was constructed to analyze the 

minimum amount of reductions in groundwater withdrawals 

for irrigation that would be necessary to increase simulated 

stream base flow of the North Platte River at Bridgeport. A 

second analysis extended the first to analyze the simulated 

base-flow benefit of groundwater withdrawals along with 

application of intentional recharge. Using GWM-2005, the 

groundwater withdrawals were grouped into eight management zones, and groundwater withdrawals were maximized 

between 50–100 percent of the net irrigation requirement. 

The analysis was iterated to solve for the maximum simulated stream base flow for the North Platte River at Bridgeport 

streamgage. Depending on future precipitation conditions, 

with no reductions in groundwater withdrawals, maximum 

simulated stream base flow ranged from 302 to 556 cubic feet 

per second (ft3

/s); whereas, with optimally managed groundwater withdrawals, simulated stream base flow was increased 

by 4 to 8 ft3

/s. Simulated base flow was best optimized by 

reductions in groundwater withdrawals north of the North 

Platte River and in the western half of the area. A second 

iterative analysis was completed to investigate the maximum 

simulated stream base flow attainable if intentional recharge 

was applied at as many as 18 sites with sandy soils. Using 

the Groundwater-Management Process for the 2005 version 

of the U.S. Geological Survey modular three-dimensional 

groundwater model (GWM-2005) to optimize groundwater 

withdrawals and intentional recharge, the maximum simulated stream base flow was 15–23 ft3

/s greater than with no 

management at all or 10–15 ft3

/s larger than with managed 

groundwater withdrawals only. 

Optimization results indicate not only the amount that 

simulated stream base flow can be increased by applying 

these management options but also the locations where the 

management options provide the most or least benefit to the 

simulated stream base flow. For instance, when groundwater 

withdrawals were optimized, withdrawals in one of the eight 

management zones were not reduced under any of the precipitation conditions, indicating that those reductions would not 

provide a benefit to maximum simulated base flow within the 

future model period at the North Platte River at Bridgeport 

streamgage. Of the 18 intentional recharge sites, five of the 

sites provided benefit to simulated base flow across all future 

precipitation conditions considered. For above-average or 

below-average precipitation conditions, intentional recharge 

sites used in the optimized results were commonly closer to 

the North Platte River and slightly biased towards the western 

end of the area. These results are subject to the availability and 

location of intentional recharge sites as well as the timing and 

location of streamflow constraints specified in these analyses. 

Optimization results presented in this report are one set of 

answers given the particular timing and location of constraints 

and decision variables used to construct the simulationoptimization model as a tool for analysis. Future users of the 

simulation-optimization model will be able to modify the 

input files as to constraints, time periods that the constraints 

are applied to, decision variables of groundwater withdrawals 

by zone, and other variables to explore other feasible management scenarios that may yield different increases in simulated 

future base flow of the North Platte River.

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Peterson and others—Simulation of Groundwater Flow and Water-Management Options in the North Platte Natural Resources District, Nebraska—SIR 2015–5093

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20155093