Bedrock Bedrock

Groundwater underflow in

Groundwater underflow out

Streamflow-gaging station

Mountain-front

recharge

Mountain-front

recharge

Evapotranspiration Agricultural

withdrawals

Municipal

withdrawals

Water Availability and Use Pilot: Methods

Development for a Regional Assessment of

Groundwater Availability, Southwest 

Alluvial Basins, Arizona

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2011-5071

National Water Availability and Use Pilot Program
FRONT COVER 

Generalized block diagram of typical groundwater budget components in the Southwest Alluvial Basins of Arizona.

BACK COVER

The USGS Groundwater Resources Program includes pilot studies of water availability and use in the two areas highlighted on this map; these are

comprehensive studies of regional water resources, including groundwater and surface-water use and availability.
National Water Availability and Use Pilot Program

Water Availability and Use Pilot: Methods 

Development for a Regional Assessment 

of Groundwater Availability, Southwest 

Alluvial Basins, Arizona

By Fred D Tillman, Jeffrey T. Cordova, Stanley A. Leake, Blakemore E. Thomas, 

and James B. Callegary

Scientific Investigations Report 2011–5071

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

This report and any updates to it are available online at:

http://pubs.usgs.gov/sir/2011/5071/

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment,

visit http://www.usgs.gov or call 1-888-ASK-USGS (1-888-275-8747).

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

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

endorsement by the U.S. Government.

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

copyright owners to reproduce any copyrighted material contained within this report.

Suggested citation:

Tillman, F.D, Cordova, J.T., Leake, S.A., Thomas, B.E., and Callegary, J.B., 2011, Water availability and use pilot: 

methods development for a regional assessment of groundwater availability, southwest alluvial basins, Arizona: U.S. 

Geological Survey Scientific Investigations Report 2011-5071, 118 p.
iii

Contents

Executive Summary.......................................................................................................................................1

Regional Groundwater Budget...........................................................................................................1

Demonstration of a Multibasin Groundwater-Flow Model ............................................................1

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

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

Approach and Scale of this Study ............................................................................................3

Previous Studies ...................................................................................................................................5

Acknowledgments................................................................................................................................5

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

Physiography and Climate..........................................................................................................5

Geology..........................................................................................................................................6

Population Centers and Dynamics............................................................................................6

Surface Water Resources and Management.........................................................................6

Groundwater Resources and Management..........................................................................11

Effects of Development on Groundwater-Reliant Ecological Systems....................11

Water Quality..............................................................................................................................11

Sensitivity of Water Supplies to Climate................................................................................12

SWAB Groundwater Availability Issues...................................................................................................12

Analysis of Groundwater Conditions Using Groundwater-Level Databases.....................................13

Recent Depth to Groundwater..........................................................................................................14

Groundwater-Level Decline ..............................................................................................................14

Groundwater-Level Rise ....................................................................................................................14

Recent Trends in Groundwater Levels ............................................................................................17

Regional Groundwater Budget..................................................................................................................19

Precipitation.........................................................................................................................................21

Methods.......................................................................................................................................21

Results .........................................................................................................................................21

Runoff ..................................................................................................................................................23

Methods.......................................................................................................................................23

Estimation of Runoff from Basin Characterization Model (BCM).............................26

Multiple-Regression Analysis of Runoff .......................................................................26

Results .........................................................................................................................................28

Performance of Regression and BCM Estimates of Runoff.......................................28

Mountain-Front Recharge.................................................................................................................30

Methods.......................................................................................................................................30

SWAB-RASA Empirical Recharge Equation.................................................................30

Recharge Estimates from the Basin Characterization Model...................................31

Results .........................................................................................................................................31

SWAB-RASA Empirical Recharge Equation.................................................................31

Recharge Estimates from the Basin Characterization Model...................................31

Comparison of SWAB-RASA Regression and BCM Recharge Estimates...............33

Evapotranspiration..............................................................................................................................33
iv

Methods.......................................................................................................................................36

Groundwater ET .........................................................................................................................38

Results .........................................................................................................................................38

Groundwater Underflow....................................................................................................................41

Methods.......................................................................................................................................41

Results .........................................................................................................................................43

Groundwater Recharge by Seepage from Streams......................................................................44

Methods.......................................................................................................................................46

Results .........................................................................................................................................46

Irrigation and Public Supply Water Use Data Collection in the Southwest

Alluvial Basins.....................................................................................................................................48

Methods.......................................................................................................................................48

Irrigation.............................................................................................................................48

Public Supply.....................................................................................................................48

Results .........................................................................................................................................50

Irrigation.............................................................................................................................50

Public Supply.....................................................................................................................50

Incidental Recharge from Irrigation Water Use............................................................................50

Methods.......................................................................................................................................50

Results .........................................................................................................................................53

Recharge from the Central Arizona Project ...................................................................................53

Methods.......................................................................................................................................53

Results .........................................................................................................................................53

Artificial Recharge from Treated Effluent.......................................................................................53

Methods.......................................................................................................................................53

Results .........................................................................................................................................55

Change in Aquifer Storage Since Before Development...............................................................55

Methods.......................................................................................................................................55

Results .........................................................................................................................................55

Regional Groundwater Budget Summary.......................................................................................58

Demonstration of a Multibasin Groundwater-Flow Model for South-Central Arizona ....................58

Geohydrologic Conditions in the Model Area................................................................................58

Model Characteristics........................................................................................................................61

Results of Simulation..........................................................................................................................63

Implications for Future Work ............................................................................................................63

Considerations for Assessment of Groundwater Availability...............................................................63

Estimation of Water-Budget Components ......................................................................................66

Natural Groundwater Recharge..............................................................................................66

Anthropogenic Groundwater Recharge ................................................................................66

Natural Groundwater Discharge to the Surface ..................................................................66

Anthropogenic Groundwater Discharge ...............................................................................66

Groundwater Flow Between Basins.......................................................................................66

Simulation of Groundwater Flow......................................................................................................70

References Cited..........................................................................................................................................70

Appendix 1. Supplemental Information—Additional References Organized by Basin....................76
v

Figures

1. Map of Western United States showing the Basin and Range Physiographic Province 

(Fenneman, 1931) and the outline of the Southwest Alluvial Basins Study Area within 

the State of Arizona......................................................................................................................3

2. Basin boundaries and basin names within the study area used in this report.. ..........................4

3. Study area landcover (modified from Multi-Resolution Land Characteristics 

Consortium, 2010) and physiographic provinces (U.S. Geological Survey, 1969) ..............7

4. Map of generalized geology of study area, with classifications simplified from 

Hirschberg and Pitts (2000).........................................................................................................8

5. Reported (U.S. Census Bureau, 2009) and Projected (Arizona Department of Commerce, 

2010) population for the State of Arizona..................................................................................9

6. Location of major cities (yellow dots), the Central Arizona Project (CAP) canal (light blue 

lines), and major rivers (dark blue lines) in the study area..................................................10

7. Depth to groundwater in wells with observations between 2004 and 2006 for basins with 

the most groundwater use (outlined in brown) in the alluvial basins of Arizona (U.S. 

Geological Survey, 2010; Arizona Department of Water Resources, 2007).......................15

8. Pie diagram summarizing depth to groundwater in wells with observations between 2004 

and 2006 in basins with the most groundwater use in the alluvial basins of Arizona 

(U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007).............15

9. Wells indicating declines in groundwater levels of at least 75 ft ending before 1997 (top) and 

continuing after 1997 (bottom) for basins with the most groundwater use (outlined in 

brown) in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007) ..............................................................................................16

10. Pie diagrams summarizing wells indicating water-level decline of at least 75 ft in basins 

with the most groundwater use in the alluvial basins of Arizona (U.S. Geological 

Survey, 2010; Arizona Department of Water Resources, 2007)...........................................17

11. Wells indicating rises in groundwater levels of at least 50 ft ending before 1997 (top) and 

continuing after 1997 (bottom) for basins with the most groundwater use (outlined in 

brown) in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona 

Department of Water Resources, 2007)..................................................................................18

12. Pie diagrams summarizing wells indicating water-level rise of at least 50 ft in basins with 

the most groundwater use in the alluvial basins of Arizona (U.S. Geological Survey, 

2010; Arizona Department of Water Resources, 2007) .........................................................19

13. Trends in groundwater levels in wells for observations between 1997 and 2006 for basins 

with the most groundwater use (outlined in brown) in the alluvial basins of Arizona 

(U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007).............20

14. Pie diagram summarizing trends in water levels in wells for the 1997–2006 time period in 

basins with the most groundwater use in the alluvial basins of Arizona (U.S. Geological 

Survey, 2010; Arizona Department of Water Resources, 2007)...........................................20

15. Average annual precipitation (from the Parameter-elevation Regressions on Independent 

Slopes Model—PRISM) for the Southwest Alluvial Basins study area for 1940–2006 

(PRISM, 2008) ..............................................................................................................................22

16. Decadal average annual precipitation (from the Parameter-elevation Regressions on 

Independent Slopes Model—PRISM) for focus basins in the Southwest Alluvial Basins 

study area for six 10-year and one 7-year time periods from 1940 through 2006 

(PRISM, 2008) ..............................................................................................................................23
vi

17. Precipitation (from the Parameter-elevation Regressions on Independent Slopes 

Model—PRISM) for the Southwest Alluvial Basins study area in 1941, generally 

representing the maximum annual precipitation in the study area between 1940 and 

2006 (PRISM, 2008) .....................................................................................................................24

18. Precipitation (from the Parameter-elevation Regressions on Independent Slopes 

Model—PRISM) for the Southwest Alluvial Basins study area in 1956, generally representing the minimum annual precipitation in the study area between 1940 and 2006 

(PRISM, 2008) ..............................................................................................................................25

19. Runoff regions (colored areas) and drainage basin areas (hachured areas) for 

streamgages used in developing the streamflow regression equation............................27

20. Residual of mean annual flow in 47 streamgaged drainages in the study area, 

calculated as observed value minus regression-equation-estimated value ...................29

21. Average annual mountain-front recharge estimated by the Southwest Alluvial BasinsRegional Aquifer System-Analysis (SWAB-RASA) regression equation and 

Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for the 1940–2006 time period by basin ..................................................32

22. Graph of decadal average annual mountain-front recharge estimated by the Southwest 

Alluvial Basins-Regional Aquifer System-Analysis (SWAB-RASA) regression equation 

and Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation data for focus basins for six 10-year and one 7-year time periods from 

1940 through 2006 .......................................................................................................................33

23. Average annual mountain-front recharge estimated by the Basin Characterization Model 

(BCM) for the 1940–2006 time period, by basin......................................................................34

24. Locations of average annual mountain-front recharge estimated by the Basin 

Characterization Model (BCM) for the 1940–2006 time period ...........................................35

25. Graph of decadal average annual recharge estimated by the Basin Characterization Model 

(BCM) for focus basins for six 10-year and one 7-year time periods from 

1940 through 2006 .......................................................................................................................36

26. Ratio of mountain-front recharge estimates produced by the Basin Characterization 

Model (BCM) to estimates from the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation for the 1940–2006 time 

period, by basin...........................................................................................................................37

27. Examples of data types used to calculate actual evapotranspiration (ET) where (A) is 

MODIS EVI data (Oak Ridge National Laboratory, 2008), (B) is temperature data 

(PRISM, 2008), (C) is mean daily percentage of annual daytime hours based on latitude 

(Brouwer and Heibloem, 1986), and (D) is calculated actual ET 

from all vegetation types ...........................................................................................................39

28. Area classified as primarily groundwater-using vegetation in the Southwest 

Alluvial Basins (SWAB) study area for evapotranspiration (ET) analyses .......................40

29. Seasonal variation in evapotranspiration (ET) for all vegetation types. Each date 

shows the average ET rate for each pixel on that date over the period 2000–2007........42

30. Graphs showing estimated maximum and minimum monthly evapotranspiration (ET) rate 

from groundwater for focus basins from 2000 to 2007 .........................................................43

31. Differences in groundwater basins used in Arizona Department of Water Resources 

(ADWR) and U.S. Geological Survey (USGS) studies ...........................................................45

32. Location of streamflow gages used in analysis of stream seepage and classification of 

runoff/seepage regions in the Southwest Alluvial Basins of Arizona ...............................47

33. Stream reaches in the study area in which infiltration was a significant part of the 

predevelopment water budget (adapted from Anderson and others, 1992).....................49
vii

34. Estimated groundwater withdrawals for irrigation in 1980 and in 2005. Uncolored basins 

have no reported data................................................................................................................51

35. Estimated groundwater withdrawals for public supply in 1980 and in 2005 .............................52

36. Estimated potential incidental recharge from irrigation water use in 1980 and in 2005.........54

37. Estimated potential groundwater recharge from treated effluent in 2005................................56

38. Estimate of change in aquifer storage from before development (circa 1940) to present 

(2000–2006) for the most developed alluvial basins in Arizona...........................................57

39. Summary of independently estimated groundwater budget components for the overall 

Southwest Alluvial Basins study area during predevelopment and 

recent time periods ....................................................................................................................59

40. Map of proof-of-concept model area indicating model boundary and component model 

areas used in creating model framework...............................................................................60

41. Thickness of alluvial sediments in proof-of-concept model area 

(Richard and others, 2007). Model boundary delineated with orange line.......................62

42. Aggregated areas of Basin Characterization Model (BCM) recharge estimates and model 

cell locations where the recharge was applied....................................................................64

43. Hydraulic conductivity (A and B) and transmissivity (C) values for 

the three model layers ...............................................................................................................65

44. Groundwater levels simulated by the uncalibrated steady-state model for model layers 1 

(A), 2 (B), and 3 (C), with comparison to published predevelopment groundwater levels 

from Freethey and Anderson (1986).................................................................................. 67–69

Tables

1. Average annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation estimates for the Southwest Alluvial Basins study area in Arizona for time 

periods indicated ........................................................................................................................78

2. Maximum and minimum annual Parameter-elevation Regressions on Independent Slopes 

Model (PRISM) precipitation by basin between 1940 and 2006..........................................80

3. Characteristics of runoff regions in the Southwest Alluvial Basins of Arizona .........................81

4. Streamflow-gaging stations used for runoff regression analysis ................................................82

5. Characteristics of the Southwest Alluvial Basins of Arizona........................................................83

6. Improvement of fit of multivariate regression equation by additional explanatory variables 

and final form of equation .........................................................................................................84

7. Comparison of streamflow predictions by regression equation to observed data ...................85

8. Comparison of streamflow predictions by regression equation for runoff regions ..................86

9. Observed and estimated mean annual flow at streamflow-gaging stations in the Southwest 

Alluvial Basins of Arizona..........................................................................................................87

10. Comparison of basin runoff estimates using the Basin Characterization Model (BCM) and 

regression equation ...................................................................................................................89

11. Statistics of fit between observed and estimated mean annual streamflow at gaged sites 

for runoff regions in the Southwest Alluvial Basins study area .........................................90

12. Average annual mountain-front recharge estimated by the Southwest Alluvial BasinsRegional Aquifer System-Analysis (SWAB-RASA) regression equation and Parameterelevation Regressions on Independent Slopes Model (PRISM) precipitation data for 

time periods indicated ...............................................................................................................91
viii

13. Average annual in-place recharge and runoff estimated by the Basin Characterization 

Model (BCM). ..............................................................................................................................95

14. Average annual mountain-front recharge estimated by the Basin Characterization Model 

(BCM) for time periods indicated.............................................................................................99

15. Comparison of Basin Characterization Model (BCM) and Southwest Alluvial BasinsRegional Aquifer System-Analysis (SWAB-RASA) regression equation estimates of 

average annual mountain-front recharge for the 1940–2006 time period.......................103

16. Maximum and minimum estimated annual volumes of actual evapotranspiration from 

groundwater, summarized by basin.......................................................................................105

17. Comparison of maximum and minimum estimated annual volume of actual 

evapotranspiration (AET) for the 2000–2007 time period (this study) to predevelopment 

ET and potential ET. ..................................................................................................................107

18. Estimated groundwater inflow to and outflow from alluvial basins in Arizona 

for time periods indicated .......................................................................................................108

19. Streamflow gages used in analysis of aquifer recharge from stream seepage....................110

20. Streams with multiple gages used for analysis of aquifer recharge from stream 

seepage......................................................................................................................................112

21. Estimated volume of mean annual streamflow, which represents water potentially 

available for recharge by seepage from streams for predevelopment (pre-dam) and 

modern (post-dam) time periods in basins of the Soutwest Alluvial 

Basins in Arizona. .....................................................................................................................113

22. Volumes of mean annual streamflow available for recharge by seepage from streams in 

runoff regions of the Southwest Alluvial Basins in Arizona..............................................114

23. Estimates of predevelopment groundwater recharge from and discharge to streams in the 

Southwest Alluival Basins of Arizona. Estimates adapted from SWAB-RASA studies 

(Freethey and Anderson, 1986)...............................................................................................114

24. Estimated annual groundwater and surface-water withdrawals for irrigation in alluvial 

basins in Arizona where data are available for time periods indicated..........................115

25. Estimated annual groundwater withdrawals for public supply for alluvial basins in Arizona 

for time periods indicated .......................................................................................................116

26. Irrigation system efficiencies assumed for the Southwest Alluvial Basins study area .......117

27. Estimated annual recharge from irrigation in alluvial basins in Arizona 

for time periods indicated .......................................................................................................117

28. Estimated annual recharge from treated effluent in alluvial basins in Arizona for 2005 ......118

29. Estimated change in groundwater storage since predevelopment times for the most 

developed basins in the Southwest Alluvial Basins study area.......................................118
ix

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2

) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

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

)

Flow rate

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

gallon per day (gal/d) 0.003785 cubic meter per day (m3

/d)

Hydraulic conductivity

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

Hydraulic gradient

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

Transmissivity

foot squared per day (ft2/d) 0.09290 meter squared per day (m2/d) 
This page left blank intentionally.
Executive Summary

Arizona is located in an arid to semiarid region in the 

southwestern United States and is one of the fastest growing 

States in the country. Population in Arizona surpassed 6.5 

million people in 2008, an increase of 140 percent since 1980 

(U.S. Census Bureau, 2010a), when the last regional U.S. 

Geological Survey (USGS) groundwater study was done as 

part of the Regional Aquifer System Analysis (RASA) program. The alluvial basins of Arizona are part of the Basin and 

Range Physiographic Province (Fenneman, 1931) and cover 

more than 73,000 mi2, 65 percent of the State’s total land area. 

More than 85 percent of the State’s population resides within 

this area (U.S. Census Bureau, 2010b), accounting for more 

than 95 percent of the State’s groundwater use (Tadayon, 

2005). Groundwater supplies in the area are expected to 

undergo further stress as an increasing population vies with 

the State’s important agricultural sector for access to these 

limited resources. 

To provide updated information to stakeholders addressing issues surrounding limited groundwater supplies and 

projected increases in groundwater use, the USGS Groundwater Resources Program instituted the Southwest Alluvial Basins 

Groundwater Availability and Use Pilot Program to evaluate 

the availability of groundwater resources in the alluvial basins 

of Arizona. The principal products of this evaluation of groundwater resources are updated groundwater budget information 

for the study area and a proof-of-concept groundwater-flow 

model incorporating several interconnected groundwater 

basins. This effort builds on previous research on the assessment and mapping of groundwater conditions in the alluvial 

basins of Arizona, also supported by the USGS Groundwater 

Resources Program.

Regional Groundwater Budget

The Southwest Alluvial Basins-Regional Aquifer System 

Analysis (SWAB-RASA) study produced semiquantitative 

groundwater budgets for each of the alluvial basins in the 

SWAB-RASA study area. The pilot program documented in 

Water Availability and Use Pilot: Methods Development 

for a Regional Assessment of Groundwater Availability, 

Southwest Alluvial Basins, Arizona

By Fred D Tillman, Jeffrey T. Cordova, Stanley A. Leake, Blakemore E. Thomas, and James B. Callegary

this report developed new quantitative estimates of groundwater budget components using recent (2000–2007) data and 

methods of data analysis. Estimates of inflow components, 

including mountain-front recharge, incidental recharge from 

irrigation of agriculture, managed recharge from recharge 

facilities, interbasin underflow from upgradient basins, and 

streamflow losses, are quantified for recent time periods. 

Mountain-front recharge is the greatest inflow component 

to the groundwater system and was estimated using two 

methods: a basin characteristic model and new precipitation information used in a previously developed regression 

equation. Annual mountain-front recharge for the study area 

for 1940–2007 estimated by the two methods is 730,000 

acre-ft for the basin characteristic model and 643,000 acre-ft 

for the regression equation, representing 1.5 percent and 1.3 

percent of precipitation, respectively. Outflow components, 

including groundwater withdrawals, evapotranspiration, and 

interbasin flow to downgradient basins, are also presented for 

recent time periods. Groundwater withdrawals accounted for 

the largest share of the water budget, with nearly 2.4 million 

acre-ft per year withdrawn from the study area in recent years. 

Evapotranspiration from groundwater was estimated at nearly 

1.3 million acre-ft per year for the study area using a newly 

developed method incorporating vegetation indices from 

satellite images and land cover information. For water-budget 

components with temporal variation that could be assessed 

from available data, estimates for intervening time periods 

since before development were also developed. An estimate of 

aquifer storage change, representing both gains to and losses 

from the groundwater system since before development, was 

derived for the most developed basins in the study area using 

available estimates of groundwater-level changes and storage 

coefficients. An overall storage loss of 74.5 million acre-ft was 

estimated for these basins within the study area. 

Demonstration of a Multibasin GroundwaterFlow Model

A proof-of-concept regional groundwater-flow model 

was developed to determine if large, multibasin models can 
2 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

be joined and solved, and to test groundwater budget components developed in the first part of this study. This model 

builds upon previous Federal and State agency groundwater investigations in the area completed at differing scales. 

Steady-state groundwater flow was modeled for an area that 

encompasses more than 2,900 mi2, including the corridor of 

connected aquifers extending from the Santa Cruz Basin near 

the Tubac streamgage north of Nogales, Arizona, through 

the Tucson and Pinal Active Management Areas to the north. 

The connected aquifers of Avra and Altar Valleys, the Tucson 

metropolitan area, and the heavily agricultural area of the 

Pinal Active Management Area are all included in the modeled area. Steady-state groundwater flow was modeled using 

information on average in-place recharge and runoff produced 

during the development of the groundwater budgets. Planned 

future model refinements include transient simulations based 

on groundwater-budget components for time periods after 

widespread groundwater development.

Introduction

The southwestern United States is the fastest growing 

region in the country, with Arizona consistently among the 

fastest growing States. The alluvial basins of Arizona contain 

the major population centers for the State and account for 

most of the recent and projected population growth. Additionally, the plentiful sunshine in the south-central part of the State 

has made the area attractive for planned solar-thermal power 

plants that may require considerable amounts of water. Many 

basins contain limited or no surface-water resources, leaving 

groundwater as the principal source of water for all needs. 

Groundwater withdrawals from the alluvial basins in Arizona accounted for about 45 percent of total water use for the 

area in 2003 (Tadayon, 2005; Arizona Department of Water 

Resources, 2006). Competition between agricultural, municipal, and industrial water users over limited water resources, 

along with increasing awareness of the need for ecological 

flows to support rivers and riparian communities, makes the 

need for thorough assessment of water resources of the State 

an ongoing priority. 

The availability of groundwater as a resource is dependent upon many factors, including hydrogeologic setting, 

groundwater quality, amount and timing of precipitation, and 

amount and location of groundwater withdrawals. This study, 

supported by the USGS Groundwater Resources Program, 

investigates groundwater availability and use in the alluvial 

basins of Arizona by presenting updated groundwater budgets 

for the area and by demonstrating a multibasin groundwaterflow model that may indicate a future tool for integrating 

multibasin groundwater management in the area. The updated 

groundwater budgets and proof-of-concept flow model build 

upon previous work done for the Groundwater Resources 

Program to investigate and communicate groundwater conditions in south-central Arizona.

Purpose and Scope

The purpose of this report is to present results from the 

USGS Southwest Alluvial Basins (SWAB) Groundwater 

Availability and Use Pilot Program. The study area comprises 

the alluvial basins of Arizona, roughly the southern two-thirds 

of the State (fig. 1). Forty-five groundwater basins defined by 

the Arizona Department of Water Resources (ADWR) are used 

as the basis for basin-scale investigations and the presentation 

of results in this study (fig. 2). 

The SWAB Groundwater Availability and Use Pilot Program consists of three parts: 

1. Development of methods and indicators for assessment and presentation of regional groundwater conditions in the alluvial basins of Arizona using existing 

databases,

2. Generation of updated regional groundwater budgets 

using the most recent available data and methods of 

data analysis, and

3. Development of a proof-of-concept groundwater-flow 

model of several interconnected basins in an area 

heavily dependent upon groundwater. 

Methods developed for the first part of the study were 

discussed in previous publications (Tillman and others, 

2007; Tillman and others, 2008), and corresponding results 

for the most developed basins of the study area are presented in this report. 

This report presents a description of the study area, 

including important physical, climate, population, and wateruse characteristics that impact groundwater conditions in 

the alluvial basins of Arizona. Issues related to groundwater 

availability and the effects of groundwater use in the SWAB 

region are also discussed. Indicators of regional groundwater conditions produced from analyses of groundwater-level 

databases for the most developed basins in the study area are 

then presented, followed by updated regional groundwater 

budgets for all basins. Groundwater-budget components 

investigated in this report include mountain-front recharge 

from precipitation (including both direct infiltration of 

precipitation into mountain blocks and the infiltration of 

water in drainages along mountain fronts), groundwater 

withdrawals, evapotranspiration, incidental recharge from 

irrigation of agriculture, managed recharge from recharge 

facilities, interbasin underflow, streamflow gains and losses, 

and aquifer storage change. Changes in budget components 

with time are presented for those basins with available temporal data. The purpose of, and results from, the proof-ofconcept groundwater-flow modeling demonstration are then 

described, followed by a discussion of lessons learned from 
Introduction 3

Figure 1. Map of Western United States showing the Basin and Range Physiographic Province (Fenneman, 1931) and the 

outline of the Southwest Alluvial Basins Study Area within the State of Arizona.

the SWAB Groundwater Availability and Use Pilot Program 

and considerations for future work.

Approach and Scale of this Study

The Southwest Alluvial Basins Pilot Project is different 

in approach and scale from many of the concurrent USGS 

Regional Groundwater Availability Studies (Reilly and others, 2008; see also http://water.usgs.gov/ogw/gwrp/activities/

gw-avail.html). Other USGS groundwater availability studies consist of large-area, detailed, calibrated groundwater 

modeling efforts (for example, a 12-layer flow model for the 

Denver Basin study representing 1 alluvial aquifer, 6 bedrock 

aquifers, and 5 claystone confining units; Banta and others, in 

press) investigating areas as large as 174,000 mi2

 in the case 

of the High Plains Aquifer study (Qi and Christenson, 2010). 

The scale of investigation for the present study is limited to 

the alluvial basins of the Basin and Range Physiographic 

Province that lie within the State of Arizona. This study 

focuses on groundwater only and does not address changes in 

surface-water conditions, except through an investigation of 

the streamflow gain and loss groundwater budget component 

125°W 120°W 115°W 110°W 105°W

45°N

40°N

35°N

Basin and Range

Physiographic Province

Arizona New Mexico

Utah Colorado

Study Area

MEXICO

UNITED STATES

Base from U.S. Geological Survey digital data, 

1:11,250,000, 1983 Universal Transverse 

Mercator projection, Zone 12

Colorado River

Green River

Gila River

Salt River

COLORADO

 PLATEAU

 ̄

0 50 100 150 MILES

0 120 240 60 KILOMETERS
4 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 2. Basin boundaries and basin names within the study area used in this report. Temporal information on 

groundwater budget components, where available, is presented for each of the “focus” basins highlighted in 

blue. Focus basins were selected because they represent the variability of climate conditions in the study area 

and have experienced, or are projected to experience, large population growth.

1

1

!.

!.

!.

!.

!.

YUMA

TUCSON

PHOENIX

PRESCOTT

FLAGSTAFF

Study Basin Boundaries

Base from U.S. Geological Survey digital data, 

1:4,000,000, 1983 Universal Transverse 

Mercator projection, Zone 12

UNITED STATES

MEXICO

1

2

3

4

5

6

7

8

9

10

11

12

13

14 15

16

17

18 20

21

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23

24

25 26

28

29

30

31

32

33

34

35

36

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40

41

42 43

44

45

19

27

1 Lake Mohave

2 Detrital Valley

3 Hualapai Valley

4 Meadview

5 Peach Springs

6 Big Sandy

7 Sacramento Valley

8 Lake Havasu

9 Bill Williams

10 Verde River

11 Prescott AMA

12 Agua Fria

13 Upper Hassayampa

14 McMullen Valley

15 Butler Valley

16 Parker

17 Ranegras Plain

18 Harquahala INA

19 Tiger Wash

20 Phoenix AMA

21 Tonto Creek

22 Salt River

23 Morenci

24 Bonita Creek

25 Duncan Valley

26 Safford

27 San Bernardino Valley

28 Douglas INA

29 Douglas

30 Willcox

31 Aravaipa Canyon

32 Dripping Springs Wash

33 Lower San Pedro

34 Upper San Pedro

35 San Rafael

36 Cienega Creek

37 Santa Cruz AMA

38 Tucson AMA

39 Donnelly Wash

40 Pinal AMA

41 San Simon Wash

42 Gila Bend

43 Lower Gila

44 Western Mexican Drainage

45 Yuma

"Focus" Basins

1

2

0 5025 MILES

0 50 100 KILOMETERS

 ̄

1 Active Management Area (AMA) 

2 Irrigation Non-expansion Area (INA)

1

1
Introduction 5

and through use of the streams package in the groundwaterflow simulation. The approach of this study is to investigate 

groundwater budgets for the study area using the most recent 

available data and methods of data analysis. A steady-state, 

proof-of-concept groundwater-flow model is also developed 

to illustrate the possibility and usefulness of such a tool and to 

highlight a potential direction of future work. 

Previous Studies

Investigations into the water resources of the alluvial 

basins of Arizona stretch back to the early part of the 20th 

century, with work by such luminaries as Oscar E. Meinzer in 

Paradise Valley (Meinzer and Ellis, 1916) and Willcox Basin 

(Meinzer and others, 1913), Willis T. Lee in the Salt River 

Valley (Lee, 1905), and G.E.P. Smith throughout the study 

area (Smith, 1938). Since those studies were conducted, the 

USGS, Arizona Department of Water Resources (ADWR), and 

various local, State, and Federal agencies have all completed 

numerous groundwater studies at regional, basin, and subbasin 

scale in the area. A list of additional reading materials that 

includes many of these studies in the most developed basins of 

the study area is presented in appendix A (available electronically) of this report, categorized by basin. The most recent 

USGS regional study of the area, the SWAB-RASA study, is 

summarized briefly here.

The USGS RASA program began in 1978 following a 

congressional directive to the Department of the Interior to 

“...identify the water resources of the major aquifers within 

the United States...” and to “...establish the aquifer boundaries, the quantity and quality of water within the aquifer, and 

the recharge characteristics of the aquifer” (Sun and Johnston, 1994). The USGS identified 28 major regional aquifer 

systems, 25 of which were studied under the RASA program, 

including the Southwest Alluvial Basins. Investigation and 

evaluation of the SWAB basins began in 1979, and study 

results were presented in a series of four USGS Professional 

Papers that describe the geohydrology of the basins (Anderson 

and others, 1992), the geochemistry of groundwater in the 

area (Robertson, 1991), the simulation of groundwater flow 

in selected basins in the area (Anderson and Freethey, 1995), 

and a summary of the information presented in the other three 

reports (Anderson, 1995). The SWAB-RASA studies covered 

roughly the same area as the current investigation, although 

basin boundaries for the SWAB-RASA studies were defined 

somewhat differently from those for the current study and 

extended into California and New Mexico. 

Several geophysical studies were performed during the 

SWAB-RASA project to evaluate basin structure, basin stratigraphy, aquifer hydrologic properties, and depth to the water 

table in the study area. Data from the geophysical studies were 

combined with existing data from various State, Federal, and 

local water-resources agencies to describe the unconsolidated 

alluvial deposits that form the principal aquifers of the area. 

Results of the generalized geologic characterization of the 

principal aquifers were published in USGS Hydrologic Atlas 

663 (Freethey and others, 1986), in addition to Professional 

Paper 1406-B mentioned above. Predevelopment hydrologic 

conditions determined from the study were presented in 

Hydrologic Atlas 664 (Freethey and Anderson, 1986), including predevelopment groundwater-level contours, magnitude 

and direction of interbasin underflow, and relative magnitudes of inflow and outflow groundwater budget components. 

Geochemical results indicated the quality of groundwater in 

much of the study area to be suitable for most uses, although 

dissolved-solids concentrations were high (greater than 

1,000 mg/L) in some areas and trace elements were found 

in exceedance of maximum contaminant levels (MCLs) for 

drinking water in small parts of several basins. Groundwater 

flow was simulated in 12 representative basins in the SWABRASA study area. Model results were analyzed to document 

similarities and differences in basin and regional geohydrology to investigate the feasibility of information transfer from 

modeled basins to those that were not modeled. All basin flow 

models were developed using two layers, with the top layer in 

most basins representing upper basin fill and the lower layer 

representing lower basin fill.

Acknowledgments

Work reflected in this report was supported by the U.S. 

Geological Survey’s Groundwater Resources Program, Water 

Availability and Use Pilot Program. Many individuals contributed to the Southwest Alluvial Basins Water Availability 

and Use Pilot Project, including Doug Rautenkranz, Don 

Pool, Jesse Dickinson, Marilyn Flynn, Kurt Schonauer, and 

Cheryl Partin of the USGS Arizona Water Science Center and 

Ken Hollett, formerly of the USGS. Teri Davis of the Arizona 

Department of Water Resources provided groundwater-level 

data from the State of Arizona.

Description of the Study Area

The Southwest Alluvial Basins study area encompasses a 

wide range of topography, geology, landcover, and precipitation and is located entirely within the boundaries of Arizona. 

It is bounded in the west by the Colorado River and in the 

north by watershed boundaries. In the south it is bounded by 

the U.S.-Mexico border and in the east by the Arizona-New 

Mexico border. The area under consideration is about 73,600 

square miles. Population, land use, and climate strongly 

influence water availability and quality in the study area, with 

regulation provided by a mosaic of local, State, Federal, and 

international laws, compacts, and treaties.

Physiography and Climate

The Southwest Alluvial Basins study area is located in 

the Basin and Range Lowland, Central Highland, and Plateau 

Uplands of Arizona (U.S. Geological Survey, 1969; fig. 3). 
6 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

In the Basin and Range Lowland province, altitudes of the 

alluvial basins range from less than 100 feet above sea level 

along the Colorado River near Yuma to greater than 4,000 feet 

in southeastern Arizona, where some mountains top 10,000 

feet. In the Central Highlands, altitudes range from about 

500 feet in the west along the Colorado River to greater than 

11,000 feet in the east at Mt. Baldy. In the Upland Plateau 

province, altitudes range from about 1,200 feet at the upstream 

end of Lake Mead to over 12,000 feet at Humphreys Peak 

north of Flagstaff. The climate is semiarid, with precipitation 

varying by altitude (Anderson and others, 1992). Precipitation is also strongly seasonal, with substantial summer rainfall 

across the entire study area and substantial winter snow 

accumulation at higher elevations. Snowpack and snowmelt 

are important in the timing of groundwater recharge, surfacewater flow, and reservoir storage volumes (Gottfried and others, 2002; Flint and Flint, 2007b). Annual precipitation ranges 

from about 3 inches in the lower, western deserts to greater 

than 44 inches in the mountains of the Highlands. Precipitation 

varies from summer dominated to winter dominated, depending on location within the study area (Western Region Climate 

Center, 2010). In the northwest, about 60 percent of precipitation occurs in winter. In the southwest and central portions, 

about 55 percent of precipitation occurs in winter, and in the 

southeast, the proportion of precipitation occurring in winter 

falls below 30 percent. Land cover in the study area is primarily classified as shrub/scrub/herbaceous followed by forest, 

then agricultural land use (fig. 3). Groundwater-dependent 

vegetation represents a small fraction of the total land cover.

Geology

The study area is located primarily in the Basin and 

Range Physiographic Province (Fenneman, 1931), but it 

also includes what is known as the Transition Zone, which 

broadly corresponds with the Central Highlands in figure 3 

(Wilson and Moore, 1959). The Transition Zone is a geologically complex region in the northeast portion of the study area 

between the Basin and Range Lowlands Province and the 

(Colorado) Plateau Uplands. Structurally, the Transition Zone 

bears resemblances to both the Basin and Range and Colorado Plateau Provinces (Anderson and others, 1992). This 

zone has undergone episodes of both extension and compression, creating complex faulting as well as severe deformation and uplift. Rocks in the Transition Zone, though highly 

faulted and displaced, consist primarily of the same sedimentary formations as those found in the Colorado Plateau, with 

local additions of Miocene and younger basalts and other volcanics and older sedimentary rocks of Cenozoic age (fig. 4). 

In the Basin and Range Province, the basins were formed by 

downdropping of mountain blocks along high-angle normal 

faults (Freethey and others, 1986). The mountain ranges have 

main axes that typically trend from north-south to northwestsoutheast, and they are separated by broad valleys underlain by Cenozoic alluvium and, in certain basins, evaporite 

deposits (Anderson and others, 1992). Rocks in the mountains 

of the study area are metamorphic, sedimentary, and igneous, 

with ages ranging from Precambrian to Cenozoic. Sediments 

in the basins typically thin to zero thickness at the margins 

and become thicker toward the center. Maximum thickness 

of sediments varies widely but in some basins can exceed 

10,000 feet (Anderson, 1987). Alluvium tends to grade from 

coarse (cobbles and gravel) near mountain fronts to fine (silt 

and clay) near basin centers. 

Population Centers and Dynamics

According to the U.S. Census Bureau, Arizona had the 

second highest population growth rate in the country for the 

period 2000 to 2009 (U.S. Census Bureau, 2010a). The Phoenix 

metropolitan area has a population of more than 4 million, while 

that of Tucson exceeds 1 million. Other population centers 

within or adjacent to the study area include the twin border cities of Nogales, Arizona, and Nogales, Sonora, Mexico (combined population greater than 200,000); the twin border cities 

of Douglas, Arizona, and Agua Prieta, Sonora (about 80,000); 

the twin border cities of San Luis, Arizona, and San Luis Rio 

Colorado, Sonora (about 173,000); Yuma (about 100,000); 

Prescott (about 47,000); and Sierra Vista (about 47,000) (Arizona Department of Commerce, 2010; Institución Nacional de 

Estadística y Geografía, 2010). Population within the study area 

increased from about 10,000 in 1870 to more than 5 million in 

2000, with a projected population of more than 12 million by 

2050 (fig. 5; Arizona Department of Commerce, 2010).

Surface Water Resources and Management

The study area lies entirely within the Colorado River 

Basin, and the Colorado River is the largest surface-water 

resource within the study area. It enters the study area with 

2009 Water Year (10/1/08 to 9/31/09) discharge of more than 

9,200,000 acre-ft at the gage below Hoover Dam (USGS 

Station # 09421500) and exits the study area with 1,400,000 

acre-ft of flow at the Northern International Boundary above 

Morelos Dam (USGS Station # 09522000), the point at which 

accounting for U.S. deliveries of water to Mexico occurs (U.S. 

Geological Survey, 2010; estimates based on mean daily discharge). The Colorado River and its reservoirs are managed by 

the U.S. Bureau of Reclamation (BOR) and the river’s water 

is distributed in the Lower Colorado River Basin to California, 

Nevada, and Arizona via a network of canals and pipelines 

primarily for municipal and agricultural use (U.S. Bureau of 

Reclamation, 2010). The main tributary to the Colorado River 

in the study area is the Gila River (fig. 6). In eastern Arizona, 

the east-to-west flowing Gila River is perennial. The Gila 

River is the largest tributary bringing water into the study 

area, with annual flow of about 116,000 acre-ft for Water Year 

2009 at the gage located at the head of Safford Valley (USGS 

Station # 09448500), about 40 kilometers west of the New 

Mexico border, which forms the eastern boundary of the study 
Introduction 7

Figure 3. Study area landcover (modified from Multi-Resolution Land Characteristics Consortium, 2010) and 

physiographic provinces (U.S. Geological Survey, 1969).

CENTRAL HIGHLANDS

UPLAND PLATEAU

BASIN

AND

RANGE LOWLANDS

EXPLANATION

Physiographic Province boundaries

Open water

Developed

Barren land

Forest

Shrub/Scrub/Grassland

Pasture/Hay/Crops

Woody and herbaceous wetland

YUMA

TUCSON

SAFFORD

KINGMAN

PHOENIX

NOGALES

WILLCOX

PRESCOTT

SIERRA VISTA

SAN LUIS

DOUGLAS

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8 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 4. Map of generalized geology of study area, with classifications simplified from Hirschberg and Pitts (2000). 

Younger sedimentary rocks are of middle Miocene or younger age.

Basin boundaries

Basalt – Miocene and younger

Crystalline non-volcanic

Limestone and/or Dolomite

Older sedimentary rocks

Other volcanic rocks

Unconsolidated alluvium

Younger sedimentary rocks

EXPLANATION

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0 5025 MILES

0 55 110 KILOMETERS
Introduction 9

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

A

RIZ

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N

A P

O

P

ULATIO

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YEAR

Census Population

Projected Population

Figure 5. Reported (U.S. Census Bureau, 2009) and projected (Arizona Department of Commerce, 2010) population for the State of Arizona.

area. From the Ashurst-Hayden Diversion Dam east of Phoenix until it joins the Colorado River a few miles upstream of 

Yuma, the Gila River is ephemeral or effluent-dependent, with 

most of its flow being diverted for agricultural or industrial 

purposes (Arizona Department of Water Resources, 2009d). 

Draining the Central Highlands and tributary to the Gila 

River are the Verde and Salt River systems (fig. 6). The Salt 

and Verde River systems are managed through a series of six 

reservoirs and one diversion dam for the production of power 

and water for the Greater Phoenix metropolitan area, as well 

as for agriculture (Salt River Project, 2010). In southeastern 

Arizona, the San Pedro and Santa Cruz Rivers are the main 

rivers (fig. 6). Both are tributary to the Gila, and both are rivers shared between the United States and Mexico. They are 

now ephemeral or intermittent over much of their length.

Management of surface water in the study area generally falls to State (Arizona Department of Water Resources 

(ADWR)), Federal (BOR) or quasi-governmental (Central 

Arizona Project (CAP); Salt River Project) entities. Much 

of the study area is located within the Gila River Watershed, 

in which the Gila River adjudication (the determination of 

the extent and priority of surface-water rights) is ongoing 

(Judicial Branch of Arizona, 2008). In Arizona, appropriable surface water is defined under Section 45-141 of the 

Arizona Revised Statutes as water “flowing in streams, 

canyons, ravines or other natural channels, or in definite 

underground channels” (Feller, 2007). In the United States, 

entitlements to Colorado River water are decided by the 

U.S. Supreme Court multistate compacts, Congressional 

Acts, and the U.S.-Mexico Treaty of 1944 together with 

its amendments (Arizona Department of Water Resources, 

2006). Together, the compacts, Acts, and the Treaty and its 

amendments are called the “Law of the River.” In Mexico, 

water is considered to be a nationally owned resource and 

is regulated by the Mexican National Water Commission 

(Comisión Nacional del Agua, 2008). Treaty-bound surface 

water crossing the U.S.-Mexico border is regulated by the 

International Boundary and Water Commission, a jointly 

operated agency that is a branch of the U.S. and Mexican 

State Departments. 
10 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 6. Location of major cities (yellow dots), the Central Arizona Project (CAP) canal (light blue lines), and major rivers 

(dark blue lines) in the study area.

!.

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YUMA

TUCSON

PHOENIX

PRESCOTT

FLAGSTAFF

CAP Canal

Bill Williams River

San Pedro River

Santa Cruz River

Colorado River

Colorado River

Verde River

Agua Fria River

Hassayampa River

Salt River

Gila River

Gila River

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Introduction 11

Groundwater Resources and Management 

The primary groundwater resources in nearly all basins 

in the study area are found either within older, unconsolidated 

basin-fill aquifers or recent stream-alluvium aquifers (Arizona 

Department of Water Resources, 2006, 2009a–e). Level of 

groundwater use tends to follow intensity of agriculture and 

population level. Groundwater is not used extensively in mountainous regions or in the large region immediately adjacent to 

the U. S.-Mexico border between the Santa Cruz Basin and the 

Colorado River. This area south of Interstate Highway 8 consists 

primarily of the Tohono O’odham Reservation and Federal lands 

including the Cabeza Prieta National Wildlife Refuge, Organ 

Pipe National Monument, and Barry M. Goldwater Air Force 

Range. By contrast, along the Lower Colorado, Gila, and Salt 

Rivers, where most of the population and agriculture in the State 

is found, groundwater demand is about 1 million acre-ft per 

year (Arizona Department of Water Resources, 2006, 2009a–e). 

With regard to management, the State is the primary regulator of 

groundwater and has three levels of management depending on 

local groundwater conditions (for example, current or potential 

overdraft, a condition in which more water is removed from 

an aquifer than is replenished) (Arizona Department of Water 

Resources, 2010a). The lowest level of management consists of 

rules that apply statewide except where superseded by higher 

levels of management. The next level is applied in Irrigation 

Non-expansion Areas (INA), in which it has been determined 

that there is insufficient groundwater to meet growing irrigation demand (Arizona Department of Water Resources, 2009a). 

There are two INAs in the study area: the Harquahala Basin 

and a portion of the Douglas Basin. The Douglas INA, created 

in 1980, includes the majority of the Douglas Basin in areas of 

highest water use. In the Douglas INA, it is legal to continue 

to irrigate land that was under irrigation at any time between 

January 1, 1975, and January 1, 1980 (Arizona Department of 

Water Resources, 2010b). In the Harquahala INA, which was 

added later, irrigation rights are based on land under irrigation 

between January 6, 1976, and January 6, 1981. The highest level 

of management is applied in Active Management Areas (AMA), 

because these areas have the most severe overdraft conditions. 

There are five AMAs in the study area. These are the Prescott, 

Phoenix, Pinal, Tucson, and Santa Cruz AMAs —locations with 

growing populations, rapidly declining water tables in some 

areas, and/or intensive pumping of groundwater for agriculture 

(Arizona Department of Water Resources, 2009e). 

Effects of Development on Groundwater-Reliant 

Ecological Systems

Some perennial, groundwater-dependent reaches of the 

Santa Cruz, San Pedro, and Gila Rivers, as well as their tributaries, were longer before development than they are currently 

(Webb and others, 2007). The factors that affect baseflow 

and groundwater levels near streams and rivers are complex. 

The actual effects of the interactions among factors such as 

geology, recharge, surface water diversions return flow from 

irrigation, groundwater pumping, and riparian vegetation, are 

difficult to predict in all but the simplest settings. Groundwater 

pumping for agricultural and municipal use has brought about 

water-table declines of as much as hundreds of feet in some 

locations, with concomitant reductions in baseflow in some 

streams and rivers (Logan, 2002; Hoffmann and Leake, 2005; 

Thomas and Pool, 2006). These changes have affected and 

presumably will continue to affect the composition of riparian 

areas and aquatic ecosystems throughout the region, given that 

different plants and terrestrial and aquatic biota have particular 

requirements for flow regime and depth to water (Collins and 

others, 1981; Marchetti and Moyle, 2001; Leenhouts and others, 2006; Lake, 2007).

Water Quality

Water quality in surface water and groundwater in the 

study area varies considerably from good to poor. Some locations heavily affected by human activities have been designated 

as Arizona Water Quality Assurance Revolving Fund sites with 

remediation projects having been implemented in a number of 

areas (Arizona Department of Environmental Quality, 2010). 

Types of contaminants from both human and natural sources 

range from E. coli and pesticides to arsenic and mercury. 

Most contaminated surface water and groundwater lie in and 

downstream of population centers such as Phoenix and Tucson 

(Arizona Department of Water Resources, 2009a–f). Urban 

sources of contaminants include industry, wastewater treatment 

plants, and underground storage tanks. Some contaminated 

surface waters are located in rural areas with sources such as 

agriculture (nitrate or microbes), mining (metals), or natural 

sources such as ore deposits. Exceedances of primary Enviromental Protection Agency drinking-water standards for organic 

chemicals occur in certain reaches of the Gila, Santa Cruz, and 

San Pedro Rivers. Some reaches have been designated by the 

Arizona Department of Environmental Quality as impaired 

for exceedances of E. coli (Arizona Department of Environmental Quality, 2008). In surface water, copper, selenium, low 

dissolved oxygen, and cadmium are the most common causes 

of exceedances of designated use standards, but ammonia, 

mercury, boron, lead, nitrogen, chlorophyll, arsenic, zinc, 

phosphorus, pesticides, pH, turbidity, and sediment exceedances have also been found (Arizona Department of Environmental Quality, 2008; Arizona Department of Water Resources, 

2009a–f). Metal contamination is derived from both natural 

and anthropogenic sources and is present in many areas where 

former mines and tailings piles are common. In groundwater, 

inorganic contaminants such as arsenic and fluoride, which 

are typically from natural sources, are the most common cause 

of exceedances of primary drinking water standards in wells, 

but there are many others. Nitrate from agricultural sources 

is also a problem in groundwater and surface water (Arizona 

Department of Water Resources, 2009a–f). Water exceeding 

the EPA secondary drinking water standard for total dissolved 

solids (TDS) is found in the Colorado, Gila, and Salt Rivers 
12 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

and in portions of nearly every basin-fill aquifer in the study 

area (Anning and others, 2007). The regional problem of 

elevated levels of TDS is underscored by Minute 242, a 1974 

agreement between the United States and Mexico that specifically regulates TDS concentrations in Colorado River water 

delivered to Mexico (Arizona Department of Water Resources, 

2009d). Emerging contaminants (those that may have health 

effects, but are not currently regulated) have been detected in 

the study area at some of the highest levels in the United States, 

but comprehensive sampling has not been done and published 

work indicates that they may be much more widespread than 

previously thought (Barnes and others, 2002; Barnes and 

others, 2008). Emerging contaminants include a wide variety 

of compounds such as flame retardants, pesticides and solvents, drug metabolites including hormones, and antimicrobial 

compounds used in personal care products. In surface water, 

suspended sediment is a problem wherever conditions such as 

construction, vegetation removal, and fire promote erosion and 

transport (U.S. Department of Agriculture, 2000; Pierson and 

others, 2007). Drought, rapid population growth, and development augment the naturally high rates of erosion and sediment 

transport in the study area. Sediment deposition and scour can 

change the permeability of streambed sediments, thereby altering interactions of groundwater and surface water (Schubert, 

2002; Dunkerley, 2008).

Sensitivity of Water Supplies to Climate

Studies of the impact of climate change in the southwestern United States have come to the general conclusion that, as 

global temperature increases, drier conditions will increasingly 

dominate across the region (Garfin and Lenart, 2007). Increased 

evapotranspiration due to rising temperatures will more than 

likely offset any increase in precipitation with respect to water 

availability. It is predicted that rainfall will be more skewed to 

extremes, with the frequency of both large precipitation events 

and periods of drought increasing. Overall, the effects of climate 

change are expected to be decreased baseflow in streams and 

rivers, more catastrophic flooding, and greater erosion, with 

likely effects on groundwater resources as well (Lenart and others, 2004; Serrat-Capdevila and others, 2007). With increased 

evapotranspiration, a decline in precipitation during spring 

months, and consequent decline in surface-water availability, 

irrigated agriculture will likely become increasingly dependent 

on groundwater (U.S. Global Change Research Program, 2010).

SWAB Groundwater Availability Issues

Water use in Arizona is dominated primarily by agriculture and secondarily by growing urban populations (Tadayon, 

2005). Agriculture is a $6.3-billion industry in the State, 

comprising more than 7,500 farms and ranches (University 

of Arizona, 2005). Arizona ranks second in the United States 

in production of head lettuce, leaf lettuce, romaine lettuce, 

cauliflower, broccoli, and lemons; third in production of 

tangerines; and fourth in production of oranges and grapefruit (University of Arizona, 2005). In the study area in 2003, 

agriculture accounted for nearly 5.3 million acre-ft of water 

use, or roughly 70 percent of the total 7.6 million acre-ft of 

water used in the study area (Tadayon, 2005; Arizona Department of Water Resources, 2006). Nearly 46 percent of this 

agricultural water use was supplied by groundwater, with the 

remainder supplied by native surface water (in particular, the 

Colorado River for agriculture near Yuma and in the Parker 

Basin), Central Arizona Project (CAP) water, and wastewater 

treatment plant effluent (Tadayon, 2005; Arizona Department 

of Water Resources, 2006). Nearly all of the agricultural 

land in Arizona is within the SWAB study area, primarily in the Phoenix, Pinal, and Tucson Active Management 

Areas (AMAs); in Harquahala INA; in McMullen Valley and 

Ranegras Plain; along the Gila River in Gila Bend Basin; 

along the Colorado River in Parker and Yuma Basins; and in 

the Douglas, Willcox, and Safford Basins in the eastern part 

of the State (figs. 2, 3). Municipal water use ranks a distant 

second to agriculture in the study area, with nearly 1.5 million acre-ft used in 2003, of which 39 percent was supplied 

by groundwater (Tadayon, 2005; Arizona Department of 

Water Resources, 2006). In the absence of new conservation 

measures, recent and projected population growth in Arizona 

(fig. 5) will most likely result in an increase in municipal 

water use in the State. 

Through the Colorado River Compact of 1922 (approved 

by Arizona in 1944), Arizona is entitled to 2.8 million acre-ft 

of Colorado River water (Colby and Jacobs, 2007). Construction on the CAP canal and associated facilities began in 1973 

and was completed 20 years later at a cost of more than $4 

billion (Central Arizona Project, 2010). The CAP canal (fig. 

6) stretches 336 miles from Lake Havasu just north of Parker 

to Tucson and is designed to deliver 1.5 million acre-ft of 

Arizona’s Colorado River allotment to interior basins (Central Arizona Project, 2010). CAP water is used for municipal, 

industrial, and agricultural purposes and is a source of water 

for six aquifer recharge projects in the State (Central Arizona 

Project, 2010).

Although groundwater in the basin-fill aquifers is a major 

resource for the region, development of this resource can result 

in some undesirable consequences. In addition to declining groundwater levels discussed in the section “Analysis of 

Groundwater Conditions Using Groundwater-Level Databases” 

and loss of groundwater in storage discussed in the section 

“Regional Groundwater Budgets” in this report, major consequences have included land subsidence and associated earth 

fissures and reduction in size or flow of surface-connected 

groundwater features such as streams, springs, wetlands, and 

areas of evapotranspiration of groundwater by riparian plants. 

Land subsidence is the sinking of the land surface. A 

major cause of land subsidence in the Southwest is drainage of 

groundwater from the clay and silt sediments in or next to aquifers (Galloway and others, 1999). As groundwater levels in the 
Analysis of Groundwater Conditions Using Groundwater-Level Databases 13

aquifers decline, the drainage from the clay and silt layers causes 

them to compact, resulting in lowering of the land surface. Land 

subsidence causes many problems, including (1) changes in 

elevation and slope of streams, canals, and drains; (2) damage to 

bridges, roads, railroads, storm drains, sanitary sewers, canals, 

and levees; (3) damage to private and public buildings; and (4) 

failure of well casings from forces generated by compaction of 

fine-grained materials in aquifer systems. Uneven land subsidence also can cause earth fissures. In the study area, earth fissures 

associated with land subsidence have been observed to be more 

than 30 meters deep and several hundred meters in length. One 

extraordinary fissure in central Arizona is more than 9 miles 

long (Carpenter, 1993). These features start out as narrow 

cracks, a few centimeters or less in width. They can intercept 

surface drainage and erode to widths of several meters at the 

land surface. Significant amounts of subsidence, with or without 

associated earth fissures, have been detected in nearly all basins 

in the study area that have experienced historical groundwater 

withdrawals for agriculture. For details on locations of recent 

subsidence detected by satellite imagery, see http://www.azwater.

gov/azdwr/Hydrology/Geophysics/LandSubsidenceMaps.htm

(accessed May 11, 2010). For maps of known earth fissures 

in the study area, see http://www.azgs.state.az.us/EFC.shtml

(accessed May 11, 2010).

Loss of streams, springs, wetlands, and riparian evapotranspiration areas can occur as groundwater withdrawals 

intercept natural groundwater discharge to these features. 

The effects of groundwater withdrawals on these features 

depend on aquifer properties, proximity of withdrawals to the 

features, and time since withdrawals began and normally are 

proportional to the withdrawal rate. When water is initially 

withdrawn from a well, all of the water comes from aquifer storage around the well. A cone of depression develops 

around the well and the gradient of the groundwater head 

is the driving force for movement of water into the well. If 

the aquifer is unconfined, nearly all of the storage change is 

from draining of pore spaces at the water table. As withdrawals continue, the cone of depression will expand to increasing distances from the well. When the cone of depression 

expands to the vicinity of features such as connected streams, 

wetlands, rivers, and lakes, the effect is to change the natural gradients that drive water to or from these features. For 

features that receive groundwater discharge, the effect is to 

decrease the gradients and groundwater flow to these features. 

Some features that once received discharge may actually 

begin to provide recharge. For features that supply water to 

the aquifer, the effect is to increase the gradients and flow 

from these features. In either case, there is a loss of available 

surface water. If the features are riparian areas where plants 

that use groundwater (phreatophytes) are present, the effect is 

to lower the water table and reduce the amount of water available to and consumed by the plants, sometimes causing the 

riparian areas to disappear. 

As previously mentioned, the time over which all or 

nearly all of groundwater withdrawals are supplied by reduced 

flow in connected features is dependent on the proximity of 

the withdrawal wells to features that can supply water and 

the hydraulic properties of the aquifer. In general, wells that 

are close to connected features will receive water from these 

features much faster than more distant wells. In cases where 

wells are tens of miles from connected surface water, the time 

at which depletion of surface features becomes the dominant 

source of water to the well can be decades or even centuries 

after withdrawals begin. If the volume of water withdrawn 

exceeds the supply that can be captured from connected features, the features may become disconnected, resulting in drying of streams, springs, and wetlands and reduction of areas 

of riparian evapotranspiration. In that case, withdrawals in 

excess of the maximum capture will be met by further removal 

of water from storage in the aquifer. This has been the course 

of events in the Tucson Basin, with loss of riparian trees along 

the Santa Cruz River (Webb and others, 2007).

Basin-fill aquifers in the study area that do not have 

connected surface-water features or groundwater evapotranspiration areas are not susceptible to loss of these features as 

a result of groundwater withdrawals. Continued groundwater 

withdrawals in those aquifers will result in possible decrease 

in underflow to downgradient aquifers, increase in underflow 

from upgradient aquifers, continued depletion of groundwater 

storage, or a combination of these effects.

Analysis of Groundwater Conditions 

Using Groundwater-Level Databases

Several indicators of groundwater conditions were developed for the study area using groundwater-level observations 

in existing databases. The development and application of 

these indicators are described in detail in Tillman and others 

(2008). Briefly, computer programs were written to combine 

and analyze different groundwater-level datasets, to produce 

geographic information system (GIS) input files, and to create 

groundwater-level hydrographs for display of groundwater 

conditions (Tillman, 2009). These methods result in indicators 

of groundwater conditions that address different spatial and 

temporal scales of the aquifer systems. Groundwater-level data 

from the USGS National Water Information System (NWIS) 

and the Arizona Department of Water Resources’ Groundwater Site Inventory were used for these analyses. The utility 

of these indicators is that they are based on actual observed 

groundwater levels (not interpolated groundwater surfaces or 

groundwater modeling simulations), are easily understood by 

people with a wide range of backgrounds, and can be presented in a publicly accessible online mapping system (http://

az.water.usgs.gov/projects/azgwconditions/index.html). A limitation of these indicators is that conclusions that can be drawn 

from them are limited by the spatial distribution and temporal 

frequency of available groundwater-level data. For example, 

geographic areas with extensive groundwater development 
14 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

generally have more groundwater-level data than other areas. 

This may lead to a bias toward greater groundwater depths 

for these areas than are presented for other less developed 

basins in the SWAB region. Also, groundwater levels may 

begin to be recorded in a well after groundwater levels in the 

area have already begun to decline or rise. Estimates of actual 

groundwater-level declines or rises based on these observations would therefore be underestimated. 

Temporal information on groundwater-level declines and 

rises is presented by dividing the datasets into two groups: a 

“historical” group with groundwater-level declines or rises 

that cease to be observed before 1997 and a “recent” set with 

declines or rises that continue to be observed between 1997 

and 2006. Wells may only appear in one group or the other. 

Groundwater-level observations flagged as pumping were not 

used in any analysis. Owing to time and budget constraints, 

groundwater indicators for only the 19 basins with the greatest 

historical groundwater withdrawals were developed and are 

presented here. These basins account for more than 96 percent 

of the estimated groundwater withdrawals in the State through 

1987 (Konieczki and Wilson, 1992) and are referred to as the 

“most developed basins” in this section. For each indicator 

presented, with the exception of Recent Depth to Groundwater, hydrographs of all wells meeting the selection criteria were 

visually inspected to ensure a qualitative agreement between 

the groundwater-level data and the indicator. 

Recent Depth to Groundwater

The most recent 2004–06 depth-to-groundwater observations for wells in the most developed basins of the study area 

(fig. 7) indicate that shallow depths to groundwater (0 to about 

50 feet below land surface) are present along the riparian corridors of the San Pedro, Upper Santa Cruz, and Gila Rivers 

(fig. 6). Numerous deeper depth-to-groundwater observations 

(>400 feet) are seen in the agricultural areas of Harquahala 

INA, McMullen Valley, Phoenix AMA, and the western portion of the Tucson AMA. Of the 6,143 wells with one or more 

groundwater-level observations in the 2004–06 time period, 

the majority have depths to groundwater of 200 feet or less, 

with 33 percent from 0 to 100 feet and 23 percent from 100 

to 200 feet (fig. 8). However, 570 wells, or 9 percent of wells 

with observations in this time period, have depths to groundwater of greater than 400 feet. Groundwater may be at greater 

depths in the higher elevation portions of a basin simply 

because of topography, limiting the usefulness of depth-togroundwater as an indicator of groundwater depletion. 

Groundwater-Level Decline

Groundwater development in the study area has caused 

sometimes dramatic groundwater-level declines. Some of 

these recorded groundwater-level declines occurred only 

during past time periods, whereas others have continued until 

more recently. As previously described, two categories of 

groundwater-level decline were defined for the study area: 

declines that ceased to be observed before 1997 and declines 

that continued to be observed from 1997 through 2006 (fig. 9). 

Note that groundwater-level declines in wells may no longer 

be observed for several reasons, including that the well has 

gone dry, that monitoring has ceased at the well, that nearby 

groundwater withdrawals have been reduced, or that nearby 

groundwater levels have risen, among others. For these analyses only wells with maximum observed groundwater-level 

declines of 75 feet or more, with at least three groundwaterlevel observations defining the decline, are presented (Tillman 

and others, 2008). The 75-ft threshold was chosen to minimize 

the presentation of wells with water levels that were oscillating and not truly declining. Significant groundwater declines 

of more than 350 feet before 1997 are evident in wells in the 

agricultural areas of Harquahala INA, central and southeastern Phoenix AMA, and Pinal AMA (fig. 9). Although fewer 

in number, declines of greater than 350 feet continued to be 

recorded between 1997 and 2006 in McMullen Valley, Phoenix and Pinal AMAs, and Safford Basin. Of the 1,962 wells in 

the study area that have at least 75 feet of groundwater-level 

decline in their period of record, 57 percent cease to indicate declines before 1997 (fig. 10). The majority of recorded 

declines for both time periods were in the 75 to 150 ft range, 

with a decrease from 17 to 6 percent of the declines greater 

than 250 ft from the pre-1997 to the 1997-and-after time 

frames (fig. 10). 

Groundwater-Level Rise

Groundwater management actions in the study area, 

including the importation of CAP water from the Colorado 

River to interior basins and the retirement of agricultural 

land, has contributed to rising groundwater levels in wells 

in some areas (fig. 11). For these analyses only wells with 

maximum observed groundwater-level rise of 50 feet or 

more, with at least 3 groundwater-level observations defining the rise, are presented (Tillman and others, 2008). The 

50-ft threshold was chosen to minimize the presentation of 

wells with water levels that were oscillating and not truly 

rising. Some 300 wells indicate a maximum rise in groundwater levels of at least 50 feet before 1997, including 3 wells 

with more than 300 feet of recorded groundwater-level rise 

in Harquahala INA (figs. 11, 12). Many wells in areas with 

significant pre-1997 declines have seen post-1997 groundwater-level rises, including Harquahala INA, eastern Phoenix AMA, and the Maricopa-Stanfield and Picacho Basins 

of Pinal AMA (fig. 11). Of the 1,436 wells that showed 

groundwater-level rise of at least 50 feet during their period 

of record, 1,130, or 79 percent, continued to rise in 1997 

or later (fig. 12). Most of the recorded rise in groundwater 

levels is in the 50 to 150 ft range (92 percent of rising wells 

before 1997 and 85 percent of wells continuing to rise during 

or after 1997).
Analysis of Groundwater Conditions Using Groundwater-Level Databases 15

Figure 7. Depth to groundwater in wells with observations between 2004 and 2006 for basins with the most groundwater use 

(outlined in brown) in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007).

0 to 100 ft

>100 to 200 ft

>200 to 400 ft

>400 ft

33%

23%

n=6,143; max = 900 ft 

35%

9%

Figure 8. Pie diagram summarizing 

depth to groundwater in wells 

with observations between 2004 

and 2006 in basins with the most 

groundwater use in the alluvial 

basins of Arizona (U.S. Geological 

Survey, 2010; Arizona Department 

of Water Resources, 2007).

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UNITED STATES

MEXICO

Observed Depth To 

Groundwater 2004–2006

!.

!.

!.

!.

!.

0 to 50 ft

>50 to 100 ft

>100 to 200 ft

>200 to 400 ft

>400 ft

0 20 40 10 MILES

0 40 80 20 KILOMETERS

Harquahala INA

Phoenix AMA McMullen Valley

Tucson AMA
16 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 9. Wells indicating declines in groundwater levels of at least 75 ft ending before 1997 (top) and continuing after 1997 

(bottom) for basins with the most groundwater use (outlined in brown) in the alluvial basins of Arizona (U.S. Geological 

Survey, 2010; Arizona Department of Water Resources, 2007).

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Pre-1997

Continuing 

1997-2006

UNITED STATES

UNITED STATES

MEXICO

MEXICO

Maximum Observed 

Water-Level Decline

!( 75 to 125 ft

!( >125 to 200 ft

!( >200 to 250 ft

!( >250 to 350 ft

!( >350 ft

0 20 40 10 MILES

0 40 80 20 KILOMETERS

Phoenix AMA

Pinal AMA

Phoenix AMA

Pinal AMA

Safford Basin

Harquahala INA

McMullen Valley
Analysis of Groundwater Conditions Using Groundwater-Level Databases 17

57% Occurred Prior 

17%

Wells Indicating Water-Level Declines

≥75 feet during Period of Record

43% Continued

1997 or after

57% Occurred 

before 1997

n=1,962 wells

Before 1997

n=1,117; max = 524 ft

25% 58%

17%

Continuing 1997 and after

n=845; max = 437 ft

72%

22%

6%

75 to 150 ft

>150 to 250 ft

>250 ft

Maximum Recorded 

Water-Level Decline

A

B C

Figure 10. Pie diagrams summarizing wells indicating water-level decline of at least 75 ft in basins with the most 

groundwater use in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona Department of Water Resources, 

2007). A, Distribution of wells with decline before and after 1997. Maximum recorded water-level declines observed before 

1997 (B) and continuing after 1997 (C).

Recent Trends in Groundwater Levels

Although analysis of the magnitude and location of 

groundwater-level declines and rises in wells is important 

to understanding groundwater conditions, information on 

recent trends in groundwater levels may be a better indicator 

of the current and near-future status of the aquifer system in 

the SWAB study area. A method was developed for computing linear trends in groundwater level data and presenting 

these trends as modified Thiessen polygons for visualization 

(Tillman and others, 2008; Tillman and Leake, 2010). Trends 

in groundwater levels were computed for wells in the most 

developed basins of the study area for the time period 1997 

through 2006, with the trends classified as falling (water 

levels declining more than 1 ft per year), rising (water levels 

rising more than 1 ft per year), or nearly stable (water levels 

between these two categories; fig. 13). Criteria for inclusion 

in the recent trends analysis were no observations flagged as 

pumping, at least three observations during the time period 

of interest (84 percent of the final wells had more than three 

observations), and an R2

 of linear fit at least 0.75. Visual 

inspection of hydrographs for each well in the final trend 

analysis was performed to ensure that the computed linear 

trend in groundwater levels qualitatively represented the 
18 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 11. Wells indicating rises in groundwater levels of at least 50 ft ending before 1997 (top) and continuing after 1997 

(bottom) for basins with the most groundwater use (outlined in brown) in the alluvial basins of Arizona (U.S. Geological 

Survey, 2010; Arizona Department of Water Resources, 2007).

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Pre-1997

Continuing

1997-2006

UNITED STATES

UNITED STATES

MEXICO

MEXICO

!(

!(

!(

!(

!(

50 to 100 ft

>100 to 150 ft

>150 to 200 ft

>200 to 250 ft

>250 ft

Maximum Observed 

Water-Level Rise

0 20 40 10 MILES

0 40 80 20 KILOMETERS

Harquahala INA

Harquahala INA

Phoenix AMA

Pinal AMA
Regional Groundwater Budget 19

79% Continued

1997 or after

21% Occurred 

before 1997

Wells Indicating Water-Level Rise

≥50 ft during Period of Record

n=1,436 wells

Before 1997

n=306; max = 408 ft

6%

92%

2%

Continuing 1997 and after

n=1,130; max = 590 ft

12%

85%

3%

>50 to 150 ft

>150 to 250 ft

>250 ft

Maximum Recorded 

Water-Level Decline

A

B C

Figure 12. Pie diagrams summarizing wells indicating water-level rise of at least 50 ft in basins with the most groundwater 

use in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007). A, 

Distribution of wells with rise before and after 1997. Maximum recorded water-level rise observed before 1997 (B) and 

continuing after 1997 (C).

trend in the data. Of the 1,279 wells with data that fit the 

trend analysis method criteria, 53 percent indicated falling 

groundwater-level trends (fig. 14). Groups of wells with falling groundwater-level trends are particularly evident in central Tucson AMA, northeastern Pinal AMA, central Phoenix 

AMA, Gila Bend Basin, McMullen Valley, Prescott AMA, 

and central Willcox Basin. Areas with rising groundwaterlevel trends include western Tucson AMA, northwestern 

Pinal AMA, southeastern Harquahala INA, and portions of 

eastern Phoenix AMA along the CAP canal (fig. 13; fig. 6). 

Regional Groundwater Budget

A water budget states that the rate of change in the water 

stored in an accounting unit (sample volume) such as an 

aquifer is determined by the rate at which water flows into that 

unit minus the rate at which water flows out of it (Healy and 

others, 2007). A groundwater budget is an accounting of the 

inflow to, outflow from, and storage change in an aquifer for 

a select time period (Hollet and others, 1991). A groundwater 

budget can be used as an indication of whether the aquifer 
20 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Rising water-level trend 

(≥1 ft per year)

26%

53%

n=1,279 wells

21%

Declining water-level trend 

(≥1 ft per year)

Nearly stable water-level

(between ±1 ft per year)

Summary of Water-Level Trends

in Wells with Observations Between 

1997 and 2006

Figure 13. Trends in groundwater levels in wells for observations between 1997 and 2006 for basins with the most groundwater use 

(outlined in brown) in the alluvial basins of Arizona (U.S. Geological Survey, 2010; Arizona Department of Water Resources, 2007).

Figure 14. Pie diagram 

summarizing trends in water 

levels in wells for the 1997–

2006 time period in basins with 

the most groundwater use in 

the alluvial basins of Arizona 

(U.S. Geological Survey, 2010; 

Arizona Department of Water 

Resources, 2007).

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UNITED STATES

MEXICO

Trends in Observed 

Groundwater Levels 

1997-2006

0 20 40 10 MILES

0 40 80 20 KILOMETERS

Falling

Nearly stable

Rising

!

Well location

Pinal AMA

Gila Bend

Willcox

McMullen

 Valley

Harquahala

INA

Phoenix AMA

Prescott AMA

Tucson 

AMA

1997–2006
Regional Groundwater Budget 21

storage is in a deficit, gaining, or stable condition. If aquifer 

inflow equals the outflow, then the aquifer is in a steady-state 

condition or equilibrium, with no change in storage. An aquifer in equilibrium exhibits little or no change in water levels, 

or it may exhibit fluctuations of water levels with no longterm rise or decline. When the total inflow does not equal the 

total outflow, the aquifer is in a transient, or nonequilibrium, 

state and change in the volume of groundwater in storage 

(increasing or decreasing) is reflected by changes in groundwater levels. 

This study presents selected groundwater budget components for the study area related to the groundwater system 

from before development (circa before 1940) to current conditions (2000–2006). The predevelopment period is considered a time period before large-scale human-induced changes 

to the groundwater-flow system occurred. This section begins 

with discussion of precipitation and runoff for the study area. 

Natural groundwater-budget components considered here 

include (1) mountain-front recharge, (2) recharge by seepage 

from streams, (3) evapotranspiration, and (4) underflow. The 

human-affected components of the groundwater budget are 

addressed next, including (1) public-supply withdrawals, (2) 

irrigation withdrawals, (3) incidental recharge from irrigation, and (4) artificial CAP and treated-effluent recharge. 

These four water-use components of the groundwater budget 

are presented for 1980 and for 2005. Groundwater is also 

used for mining and industrial purposes in the study area, but 

on the basis of 1985 and 2005 data from USGS reports, these 

groundwater withdrawals represent less than 5 percent of the 

total groundwater withdrawals in the study area and were 

not included in this study (Solley and others, 1988; Kenny 

and others, 2009). Storage change, a result of imbalances 

between aquifer inflows and outflows, also is addressed.

For this study, several standard and new methods of data 

interpretation were used to independently calculate the components of the groundwater budget. Existing datasets were compiled to estimate the water-use component of the groundwater 

budget. A new method using remote-sensing data was used to 

estimate the evapotranspiration component of the groundwater 

budget, and a distributed parameter water-balance model was 

used to estimate groundwater recharge. 

Seven basins (or, in the case of AMAs, management 

areas) in the study area were designated as focus basins. 

These basins are (1) Detrital Valley, (2) Yuma, (3) Verde 

River, (4) McMullen Valley, (5) Phoenix AMA, (6) Tucson 

AMA, and (7) Safford basins (fig. 2). These basins were 

selected because they represent the variability of climate 

conditions in the study area and have experienced, or are 

projected to experience, large population growth that could 

add stress to the groundwater system. In addition, each of 

these basins has experienced different levels of urban and 

agricultural development. Temporal information on groundwater budget components, where available, is presented for 

each of the focus basins.

Precipitation

Although not strictly a groundwater budget component, 

precipitation is the original source for all inflows to the 

groundwater system. Precipitation may be directly recharged 

to an aquifer through permeable rocks and sediments, may 

become runoff that then infiltrates to become recharge in the 

basin, or may provide flow in streams that become recharge 

sources either as they flow through a basin or as their flow 

is channeled to agricultural fields or recharge facilities (such 

as through the CAP). The change in total volume, intensity, 

and timing of precipitation can have a major impact on the 

amount of recharge reaching an aquifer. An understanding 

of changes in precipitation through time for the study area 

may therefore be considered a first indicator of how inflow 

components to the groundwater system may have changed 

through time. 

Methods

For this study, PRISM (Parameter-elevation Regressions 

on Independent Slopes Model) data were used to analyze 

changes in precipitation in the basins of the study area, as well 

as to provide precipitation input for recharge and runoff estimations (Daly and others, 1994). Briefly, the PRISM system 

calculates monthly and annual precipitation estimates (among 

other climatic parameters) at a 2.49-mi (4-km) grid scale using 

point-measurement data, a digital elevation model (DEM), and 

other spatial datasets (Daly and others, 1994). The 2.49-mi 

grid monthly PRISM precipitation data for the study area were 

summed over each water year (October through September) 

between 1940 and 2006. These annual values were then averaged over 10-year periods and over the 1940–2006 period of 

record, and were summed by basin (table 1)1. 

Results

During the 1940–2006 time period, on average nearly 50 

million acre-ft of precipitation fell annually on the Southwest 

Alluvial Basins study area (table 1). Average annual PRISM 

precipitation for the 1940–2006 time period in individual 

2.49-mi grid cells ranged from a low of 2.8 inches in the 

Yuma Basin to a high of 40.2 inches in the Salt River Basin, 

with most grid cells in the study area falling in the range 

2.8 to 15 in. (fig. 15). Among the focus basins, the average 

decadal and 66-year period-of-record PRISM precipitation indicate the higher elevation Verde River Basin in the 

northern portion of the study area received the most precipitation, whereas the lower elevation Yuma Basin in the southern 

portion of the study area received the least (fig. 16). The 

data indicate that the focus basins, located throughout the 

State, have all experienced similar overall patterns in average decadal precipitation since 1940. During the decades of 

1

 Tables 1–29 are grouped at the end of the report, starting on p.78.
22 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 15. Average annual precipitation (from the Parameter-elevation Regressions on Independent Slopes Model—PRISM) 

for the Southwest Alluvial Basins study area for 1940–2006 (PRISM, 2008).

EXPLANATION

Average Annual Precipitation

in inches per year

2.8 to 7.5

>7.5 to 15

>15 to 25

>25 to 35

>35 to 40

>40
Regional Groundwater Budget 23

0

5

10

15

20

25

1940–1949 1950–1959 1960–1969 1970–1979 1980–1989 1990–1999 2000–2006

Average Annual Precipitation in Basin (inches)

Water Years

DETRITAL VALLEY MCMULLEN VALLEY PHOENIX AMA

SAFFORD TUCSON AMA VERDE RIVER

YUMA 1940–2006 

Average

Figure 16. Decadal average annual precipitation (from the Parameter-elevation Regressions on Independent Slopes Model—PRISM) 

for focus basins in the Southwest Alluvial Basins study area for six 10-year and one 7-year time periods from 1940 through 2006

(PRISM, 2008).

1940–49, 1950–59, and 1960–69, most basins received less 

than average rainfall. From the 1980s through the 1990s, 

most basins experienced greater than average precipitation, 

with a return to below average rainfall for the 2000–2006 

time period. Although the year of maximum and minimum 

annual precipitation in the 1940–2006 time period varies 

somewhat by basin (table 2), for most basins 1941 was the 

wettest year and 1956 was the driest. This is also true for the 

Southwest Alluvial Basins study area as a whole, with more 

than 86 million acre-ft of precipitation in the study area in 

1941 and only 24 million acre-ft in 1956. For comparison, the 

annual PRISM precipitation for 1941 and for 1956 is shown 

in figures 17 and 18, respectively. 

Runoff

As previously discussed, precipitation is the primary 

source of water entering groundwater systems, either directly 

as recharge, as recharge from surface water bodies or conveyances, or as previously recharged underflow from adjacent 

systems. Although the focus of this study is on groundwater 

budget components, runoff in the study area was investigated 

to better understand the potential amount of precipitation 

available for groundwater recharge. 

Methods

Runoff was estimated using two different methods: a 

Basin Characterization Model (BCM; Flint and Flint, 2007a,b) 

and a multiple-regression equation. The two methods provide 

independent estimates for comparison, and the results improve 

the understanding of runoff and general water budgets in the 

SWAB basins of Arizona. The BCM estimates runoff on the 

basis of small-area monthly water budgets. A new multipleregression equation was developed specifically for the study 

area using streamgaging station data and basin characteristics 

such as basin area and elevation. Runoff has been measured 
24 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 17. Precipitation (from the Parameter-elevation Regressions on Independent Slopes Model—PRISM) for the 

Southwest Alluvial Basins study area in 1941, generally representing the maximum annual precipitation in the study area 

between 1940 and 2006 (PRISM, 2008).

>25 to 35

EXPLANATION

Precipitation in 1941

in inches

7.1 to 7.5

>7.5 to 15

>15 to 25

>35 to 40

>40
Regional Groundwater Budget 25

Figure 18. Precipitation (from the Parameter-elevation Regressions on Independent Slopes Model—PRISM) for the 

Southwest Alluvial Basins study area in 1956, generally representing the minimum annual precipitation in the study area 

between 1940 and 2006 (PRISM, 2008).

>25 to 35

EXPLANATION

0 to 7.5

>7.5 to 15

>15 to 25

>35 to 40

>40

Precipitation in 1956

in inches
26 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

at many streamgaging stations in the study area, and data from 

47 streamgaging stations were used in this study to estimate 

runoff. The drainage areas above these streamgaging stations cover a small portion of the study area (13 percent), so 

multiple regression was used as an extrapolation technique to 

estimate runoff throughout the study area. 

Runoff was estimated by using both methods for 28 

groundwater basins and 3 runoff regions in the study area (fig. 

19). Results for the 28 groundwater basins provide detailed 

descriptions of the distribution of runoff, and results for the 3 

runoff regions provide a summary of the regional distribution. 

Runoff regions were classified for the study area on the basis 

of similar physical and runoff characteristics. The 3 runoff 

regions are (1) Western Upland, (2) Central Upland and Northeastern Gila River Basin, and (3) Southeastern Gila River 

Basin (fig. 19; table 3). The boundary between runoff region 

1 (Western Upland) and runoff region 2 (Central Upland and 

Northeastern Gila River Basin) coincides with the drainage 

boundary of the Verde River and is primarily based on residuals of preliminary regressions. The boundary between runoff 

region 2 and runoff region 3 (Southeastern Gila River Basin) 

cuts across some surface-water drainage boundaries and was 

selected on the basis of regression residuals and precipitation 

characteristics. No suitable streamgaging records were located 

in the Western Lowland region.

Estimation of Runoff from Basin Characterization Model 

(BCM)

The BCM estimates runoff and in-place recharge using a 

distributed-parameter water-balance model. The BCM water 

balance was calculated for 885 ft × 885 ft (270 m × 270 m) 

cells throughout the study area. For each cell, monthly values 

of precipitation, maximum and minimum air temperature, and 

potential evapotranspiration were used to calculate monthly 

values of the volume of water potentially available for runoff 

and in-place recharge, together known as available water. 

In-place recharge is calculated in the BCM as the volume of 

water for a given time frame that can drain from the soil zone 

directly into consolidated bedrock or unconsolidated deposits 

(Flint and Flint, 2007b). The BCM water-balance equation 

includes available water (AW), precipitation (P), snowmelt 

(Sm), potential evapotranspiration (PET), snow accumulation 

(Sa), and soil-water storage (Ss) (Flint and Flint, 2007a,b): 

 AW = P + Sm – PET – Sa + Ss (1)

Runoff is calculated as available water in excess of the 

total soil-water storage capacity (soil porosity multiplied by 

soil depth). Temperature and precipitation estimates required 

by the BCM were obtained using PRISM data (Daly and others, 1994). Potential evapotranspiration was estimated with 

latitude, topographic shading, and air temperature using the 

Priestley-Taylor equation corrected for vegetated and bare 

soil areas (Flint and Flint, 2007a). Estimates of the storage 

capacity of a soil were based on soil texture data from the 

State Soil Geographic Database (STATSGO; U.S. Department 

of Agriculture, 1994). The spatial distribution of saturated 

hydraulic conductivity in bedrock and alluvium was determined using geologic maps. During development of the BCM 

for the western United States study area of Flint and Flint 

(2007b), hydraulic conductivity parameters were adjusted to 

produce results similar to some measured or independently 

estimated streamflow data. In this study, the BCM was run and 

results were tabulated; parameters were not further adjusted to 

fit streamflow data.

Results of the BCM analysis were determined for total 

areas and mountain areas (defined by geology at land surface; 

Arizona Geological Survey, 1998) of the 47 streamgaged 

basins and the 3 runoff regions in the study area. Annual runoff 

values were computed for the study area from monthly estimates for the 1940–2006 time period. The annual runoff values 

for the 885 ft × 885 ft grid cells were averaged over the period 

of record to produce a long-term estimate of runoff. The grid 

cell period-of-record runoff estimates were then summed over 

individual streamgage and groundwater basin areas. BCM runoff estimates were also summed over only the mountain areas 

within these areas for comparison with estimates determined 

from the regression-runoff equation. 

Multiple-Regression Analysis of Runoff

An ordinary least squares (OLS) regression analysis 

was used to develop an equation for estimating mean annual 

runoff from available streamflow data. Streamgaging stations 

were selected from areas in Arizona SWAB basins and one 

nearby basin in New Mexico (Mogollon Creek nr Cliff, NM) 

that have sustained runoff from precipitation or snowmelt; the 

streams selected could be intermittent or perennial, but there 

had to have been sustained periods of flow during the winter. 

These areas are generally in the higher elevations of the Arizona SWAB basins, where there is sufficient precipitation and 

lower levels of evapotranspiration. It was beyond the scope of 

this study to attempt to develop equations for estimating mean 

annual runoff in ephemeral streams. Ephemeral-stream runoff 

is extremely variable spatially and temporally. With current 

data and techniques, it would be difficult to develop accurate 

and representative regression equations. 

Runoff observed as mean annual flow at each streamgage 

was the response variable for the regression analysis, and 

basin and climatic characteristics of the drainage area for 

the streamgages were investigated as explanatory variables. 

Streamflow data were obtained from the USGS NWIS database (U.S. Geological Survey, 2010; table 4). Mean annual 

flow was calculated for the full period of record at each site. 

Investigating stationarity or lack of trends in flow is important 

in the application of streamflow statistics (mean flows), especially with the increasing concerns about climate change. To 

determine if there were any significant trends in annual flow 

in the study area, a Kendall tau trend test (Conover, 1980) was 

performed on the data for all 47 streamgages. Results indicate 

no significant trends (p-value <0.05) in all streamflow records 
Regional Groundwater Budget 27

Figure 19. Runoff regions (colored areas) and drainage basin areas (hachured areas) for streamgages used in developing the 

streamflow regression equation. Streamgages are located at the downstream end of the stream in each drainage area.

!.

!.

!.

!.

!.

09499000

09494000

09512500

09489500

09473000

09480500

09444200

09496500

09515500

09504500

09504500

09442680

09507980

09447800

09497800

09502800

09505800

09484500

09481500

09496000

09497980

09446000

09505350

09498870

09489700

09505200

09512600

09480000

09430600

09497900

09485000

09490800

09503000

09489070 09508300

09484000

09510080

09507700

09458200

09470800

09492400

09505250

09505300

09484200

09489200

09510100

09460150

09424200

YUMA

TUCSON

PHOENIX

FLAGSTAFF

(2) Central Upland and

Northeastern Gila River

(1) Western Upland

(3) Southeastern Gila River

Western Lowland

EXPLANATION

Drainage area for streamgages used 

in runoff regression analysis

Streamgage station number
28 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

with the exception of two sites. Sabino Creek near Tucson had 

a significant positive trend (p-value = 0.027) and Cherry Creek 

near Globe had a significant negative trend (p-value = 0.048). 

These two sites were included in the regression analysis 

because there does not appear to be any regional pattern to the 

trends; the sites are located in different parts of the study area 

and they have different trends (positive and negative).

Two physical basin characteristics were investigated for 

the analysis: basin drainage area and mean basin elevation, 

both of which were estimated using geographic information 

system techniques on 98.4-ft (30-m) digital elevation models 

(table 4). Basin climatic information of mean annual precipitation was determined from 2.49-mi PRISM data (PRISM, 

2008) for the 1940–2006 time period (table 5).

The regression model used for the analysis is the multiplicative or log-transform model. All variables were log transformed to make a linear relation between streamflow and basin 

characteristics and to satisfy the assumption of homogeneity 

of variance (homoscedasticity) for the regression analysis. The 

general form of the regression equation is:

 Log Q = a + b×(log A) + c×(log B) +... (2)

where Q is mean annual streamflow, A and B are explanatory 

variables, and a, b, and c are regression coefficients.

Results

An OLS regression equation was developed to estimate 

mean annual runoff for perennial and intermittent streams 

within the Basin and Range Physiographic Province in 

Arizona. An initial model using only basin drainage area as 

an explanatory variable was able to explain 68 percent of 

the variability of mean annual streamflow (R2=0.68; table 6) 

with a standard error of estimate of 0.319 log units (average 

standard error of estimate of 80 percent). The addition of 

basin precipitation and mean basin elevation improved the fit 

of the equation to an R2 of 0.90 and a standard error of 0.183 

log units (table 6). This three-variable model had a good 

overall fit to the data, but an investigation of the spatial distribution of residuals (by plotting them on a map of the study 

area—not shown) revealed a negative bias in two geographic 

areas. The model significantly overestimated flows in the 

northwest and southeast parts of the study area. A geographic 

region variable was added to the model to compensate for 

this bias. The three runoff regions (fig. 19) are represented 

in the model by using two dummy variables (R1 and R2) 

that were coded as follows: region 1 (R1=1, R2=0), region 2 

(R1=0, R2=0), and region 3 (R1=0, R2=1). The final regression equation has a coefficient of determination of 0.92 

and a standard error of estimate of 0.167 log units (average 

standard error of 39 percent; table 6).

The final regression equation (table 6) satisfies all 

the necessary assumptions and requirements of an OLS 

regression analysis (Draper and Smith, 1981). Plots of the 

residuals show that they are independent, homoscedastic, and 

normally distributed. The explanatory variables—drainage 

area, mean annual precipitation, mean basin elevation, and 

geographic region variable R2 (region 3)—are all significant 

at p-values of less than 0.05. The p-value for geographic 

region variable R1 is 0.17, but including it in the equation 

substantially improved the regression performance for the 

4 streamgages in region 1. In actual flow units (ft3

/s), the 

average overestimate of flow was 40 percent for the model 

without an R1 variable, and the average overestimate of flow 

was 10 percent for the model with the R1 variable. Possible 

multicolinearity of the explanatory variables (drainage area, 

mean annual precipitation, and mean basin elevation) was 

evaluated by calculating a variance inflation factor (VIF) for 

all combinations of the variables. Multicolinearity does not 

appear to be a problem in the equation—values of the VIF 

ranged from 1.10 to 1.65, much lower than upper limits of 

5.0 or 10.0 that have been cited as indicating multicolinearity 

problems (Helsel and Hirsch, 1992). 

The performance of the regression model throughout the 

study area was assessed by comparing regression-estimated 

streamflows with observed streamflows for the 47 individual 

streamgaged basins (table 7) and comparing summary results 

for 3 runoff regions (table 8). Residuals from the regression 

equation (observed minus regression-estimated mean annual 

flow) are plotted on a map of the study area (fig. 20). The 

regression equation has no appreciable regional bias; there 

are no geographic clusters of positive or negative residuals 

(fig. 20). The regional precision of the regression equation 

(magnitude of residuals) is mostly evenly distributed, with a 

small area of lower precision (larger residuals) in the lower 

elevations of the Verde River Basin and Salt River Basin 

subregions (fig. 20, table 7). Two summary statistics were 

used to evaluate the regional performance of the regression 

equation in the three runoff regions. The mean residual represents the bias of the estimates and should be near zero to be 

unbiased. The root mean square error (RMSE) represents the 

precision of the estimates, with lower values representing a 

better fit and performance of the method. The mean residual 

for the multiple regression equation for all of the selected 

streamgages in the study area is 0.01 and the RMSE is 0.155 

(table 8). The regression equation has minimal bias in the 

three runoff regions; the mean residual ranges from –0.03 to 

0.07 (table 8). The precision of the regression estimates is 

similar throughout the study area, with just a slightly lower 

precision in the Western Upland region, which has an RMSE 

of 0.195, as opposed to RMSE values ranging from 0.144 to 

0.158 for the other regions and subregions.

Performance of Regression and BCM Estimates of Runoff

Results of the multiple-regression-equation estimates 

and BCM estimates of runoff were compared for the 47 

streamgaged areas, 28 groundwater basins (in which 
Regional Groundwater Budget 29

Figure 20. Residual of mean annual flow in 47 streamgaged drainages in the study area, calculated as observed value minus 

regression-equation-estimated value.

Salt River Basin 

Sub-region

Northeastern Gila River

Basin Sub-region

Verde River

Basin Sub-region

(2) Central Upland and

Northeastern Gila River (1) Western 

Upland

(3) Southeastern Gila River

Western Lowland

EXPLANATION

Residual of Mean Annual Flow 

Estimate (log ft3

/s)

>-8.8 to -6

>-6 to -3

>-3 to 0

>0 to 3

>3 to 6

>6 to 12
30 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

suitable streamgage records were present), and 3 runoff regions 

(tables 9 through 11). The comparison for the 47 streamgaged 

areas provides estimates of the accuracy and representativeness of the two methods, because the estimates are compared to 

observed values at the streamgages. The comparison for the 28 

groundwater basins provides a detailed picture of the distribution of estimated runoff in many parts of the SWAB study area. 

The comparison for the three runoff regions provides a regional 

summary of the results.

Observed mean annual flow, estimates of mean annual 

flow from the regression equation and BCM, and differences 

between observed and estimated flows (residuals) are shown 

in table 9. The 47 streamgages and associated drainage areas 

are all in the higher elevation runoff areas of the study area. 

Residuals, in percent of observed values, range from –79 

to 57 percent for regression estimates and from –155 to 91 

percent for BCM estimates. The fit between observed and 

estimated mean annual flow varies according to region and 

according to the estimation method (regression or BCM) 

(table 9). Because the regression equation was developed 

from the observed flows, it generally has a better fit between 

estimated and observed values than does the BCM.

Comparison of BCM and regression-equation estimates 

for runoff in the 28 groundwater basins indicates that using 

BCM results from only mountainous areas of the basins 

provides more comparable results with the regression equation than using the entire groundwater basin area results 

(table 10). This is because the runoff regression equation was 

developed using data from drainage basins in these higher 

elevation mountain areas. Even comparing mountain-area 

BCM results with regression-equation results, the regression 

equation predicts more runoff than the BCM in 25 of the 28 

basins, most by a factor of 2 or more (table 10).

Two summary statistics were used to evaluate the fit 

or performance of the regression equation and the BCM in 

the runoff regions (table 11). As previously mentioned, the 

mean residual represents the bias of the estimates and should 

be near zero if there is no bias. The mean absolute residual 

represents the precision of the estimates; lower values 

represent a better fit and performance of the method. The 

mean residual for all streamgages was –4.7 percent for the 

regression equation and 28.7 percent for the BCM. The mean 

absolute residual for all streamgages was 29.1 percent for the 

regression equation and 46.5 percent for BCM. The bias of 

estimates from the two methods was appreciably different for 

each of the three runoff regions, with the regression equation 

having lower bias than BCM estimates. 

Mountain-Front Recharge

Although evapotranspiration exceeds precipitation for 

most of the year throughout the SWAB study area, there are 

time periods (particularly during winter months) when evapotranspiration is sufficiently low and locations (particularly in 

mountain areas) where precipitation is sufficiently large to 

allow excess water to become aquifer recharge. Recharge to 

the SWAB aquifer system from precipitation may occur by 

direct infiltration of water through mountain faults and fractures or through permeable pediment or basin sediments and 

drainage channels. The term mountain-front recharge is used 

in this report to identify the recharge of precipitation either 

directly through mountain blocks or infiltration of precipitation runoff in mountain-front drainages. Total aquifer recharge 

includes mountain-front recharge along with agricultural 

return flow, aquifer storage projects, streamflow recharge, and 

groundwater basin underflow. Methods often employed to 

estimate groundwater recharge include observational methods 

such as change in gravity or groundwater levels; monitoring 

stable isotope and other chemical tracers such as chloride; and 

mathematical methods including groundwater-flow models, 

water-balance approaches, and empirical regression relationships (Hogan and others, 2004). In Arizona, the Groundwater 

Management Act of 1980 requires the Active Management 

Areas (AMAs) of the State to achieve equilibrium between 

groundwater withdrawals and total aquifer recharge by 2025 

(Colby and Jacobs, 2007), making the estimation of basinscale recharge a particularly important topic in the study area.

Mountain-front recharge to groundwater was estimated 

for the alluvial basins in the study area using two independent 

mathematical methods. First, an empirical regression equation developed for the USGS SWAB-RASA studies was used 

with new, detailed PRISM precipitation information to update 

recharge estimations using this Maxey-Eakin-type equation 

(Maxey and Eakin, 1949; Flint and others, 2004). Second, 

the BCM was used to produce annual estimates of in-place 

recharge and runoff. Each of these methods is discussed separately, with the results from both methods compared. 

Methods

SWAB-RASA Empirical Recharge Equation

A regression equation relating mountain-front recharge 

and the total annual volume of precipitation on the watershed was produced by the SWAB-RASA studies of the 1980s 

(Anderson and others, 1992). The equation is calibrated from 

recharge values from numerical groundwater models developed during the SWAB-RASA studies, from previous basinscale studies of recharge, and from water-budget analyses of 

individual basins and the entire SWAB-RASA study area. An 

iterative process was employed in which an initial equation 

was used to estimate mountain-front recharge from precipitation for individual basins. These estimates were then adjusted 

to balance the water budget of the individual basins and the 

entire study area, and a new regression equation was produced. After cycles of balancing and modifying, a final equation was produced to estimate mountain-front recharge from 

precipitation (see Anderson and others, 1992, for more details)

 Log Qrech = –1.40 + 0.98 log P, (3)
Regional Groundwater Budget 31

where Qrech = total annual volume of mountain-front recharge 

in a basin (in acre-ft per year) and P = annual basin precipitation (in acre-ft per year) greater than 8 inches per year.

The threshold precipitation value of 8 inches per year 

accounts for water that is lost to soil-moisture deficits and 

evapotranspiration. In applying this equation using the 2.49-mi 

PRISM data, the first 8 inches of precipitation was subtracted 

from each annual PRISM raster cell, with resulting negative 

cell values assigned a value of zero. Basin volume of precipitation was then computed by multiplying the remaining cell 

precipitation by the cell area and summing over individual 

basin boundaries. This volume, converted to acre-ft, was then 

used in equation 3.

Recharge Estimates from the Basin Characterization 

Model

The BCM was used to estimate quantities of water 

available for generating runoff and in-place recharge within 

the SWAB study area. As previously described, the BCM 

estimates these quantities of available water using a waterbalance equation for each 885 ft × 885 ft grid cell in the study 

area. The partitioning of available water into either runoff 

or in-place recharge by the BCM depends on the saturated 

hydraulic conductivity of the bedrock and alluvium. Runoff is 

computed as available water in excess of the total soil-water 

storage capacity (soil porosity × soil depth). In-place recharge 

is computed from the available water remaining after runoff 

minus the field capacity of the soil and occurs at a rate determined by the hydraulic conductivity of the underlying soil 

or rock. The BCM does not estimate which portion of runoff 

becomes recharge.

Results

SWAB-RASA Empirical Recharge Equation

For this study, regression equation 3 was used with 

annual PRISM precipitation data from 1940 through 2006 to 

estimate mountain-front recharge in the alluvial basins of Arizona. Although the original SWAB-RASA regression equation 

was developed using maps of contoured average precipitation 

that were available at the time, using the equation with higher 

resolution PRISM precipitation estimates is not unreasonable 

because both the contour maps and PRISM data are based on 

precipitation measurements. It should be noted, however, that 

had PRISM data been available at the time of its development, 

the final SWAB-RASA regression equation might have differed somewhat from equation 3. 

Changes in recharge on a decadal scale are presented 

(table 12) to demonstrate the effect that changing precipitation regimes, including periodic drought or climatic cycles 

such as El Niño-Southern Oscillation (ENSO) or Pacific 

Decadal Oscillation (PDO), may have on aquifer recharge. 

A 1940–2006 period-of-record average annual estimate of 

mountain-front recharge is also presented that may better 

describe the longer term average for the SWAB basins (table 

12 and fig. 21). Both the decadal and period-of-record averages of recharge are presented in dimensions of length (inches) 

and volume (acre-ft), and as a percent of the total PRISM 

precipitation for the basin (table 12). 

Although not a linear function of precipitation, recharge 

estimated using equation 3 still closely tracks precipitation, with 

respect to both total volumes and temporal variations. Higher 

precipitation areas (fig. 15), including the Salt River and Tonto 

Creek Basins, logically receive the most recharge per unit area, 

whereas drier areas in the western part of the State receive the 

least recharge per unit area (table 12 and fig. 21). For the mostly 

decadal or longer averages in table 12, the percentage of precipitation that becomes recharge is generally less than 2 percent 

throughout the basins of the study area. Patterns in decadal 

recharge in the focus basins (fig. 22) follow precipitation trends 

(fig. 16), with most of the focus basins receiving average or 

below-average recharge in the 1940s through the 1970s, above 

average recharge in the 1980s and 1990s, then below average 

recharge again in the 2000–2006 time period.

Recharge Estimates from the Basin Characterization 

Model

Monthly in-place recharge and runoff grid cell values from 

the BCM were summed over each water year, then averaged by 

decade for the 1940–2006 time period and averaged over the 

entire 1940–2006 period of record. These decadal and periodof-record estimates of in-place recharge and runoff were then 

summed by groundwater basin (table 13). To compute total 

mountain-front recharge for the groundwater basins, 15 percent 

of BCM runoff was added to BCM in-place recharge (table 14 

and fig. 23). Although the amount of runoff that may become 

recharge will vary by basin and season, a value of 15 percent 

was chosen based on similar basin-scale studies in Nevada and 

Utah (Flint and Flint, 2007a,b; Stonestrom and others, 2007). 

Total basin mountain-front recharge is presented in dimensions 

of length (in) and volume (acre-ft), and as a percent of the total 

PRISM precipitation for the basin for both the decadal and 

period-of-record averages (table 14). Results indicate that basins 

with higher precipitation receive more recharge than basins with 

lower precipitation, although the percentage of precipitation 

that becomes recharge varies from a low of 0 percent in several 

basins to a high of more than 6 percent in the Tonto Creek Basin 

for the 1940–2006 average (table 14). For most of the 885 ft 

× 885 ft grid cells in the study area, the BCM calculated that 

there was no available water (equation 1) for runoff or in-place 

recharge. Only in the mainly mountainous areas surrounding 

the alluvial basins was there sufficient precipitation to provide 

excess water for recharge (fig. 24). Decadal results for the focus 

basins (fig. 25) indicate that BCM recharge estimates do not 

directly track changes in precipitation over the same time periods (fig. 16), likely because the BCM estimates are dependent 

on such factors as potential evapotranspiration and soil-water 

storage capacity. 
32 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 21. Average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer System-Analysis 

(SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation data 

for the 1940–2006 time period by basin.

>0.2 to 0.35

EXPLANATION

0 to 0.05

>0.05 to 0.1

>0.1 to 0.2

>0.35 to 0.43

Average Annual Mountain-Front Recharge

in inches per year
Regional Groundwater Budget 33

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

1940 –1949 1950 –1959 1960 –1969 1970 –1979 1980 –1989 1990–1999 2000–2006

Average Annual Mountain-Front Recharge (inches)

DETRITAL VALLEY MCMULLEN VALLEY PHOENIX AMA

SAFFORD TUCSON AMA VERDE RIVER

YUMA

1940–2006 

Average

Water Years

Figure 22. Graph of decadal average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for focus basins for six 10-year and one 7-year time periods from 1940 through 2006.

Comparison of SWAB-RASA Regression and BCM 

Recharge Estimates

Estimates of recharge produced by the SWAB-RASA 

regression equation (equation 3) and the BCM are compared 

for the SWAB basins for the 1940–2006 time period (table 

15). For the 45 groundwater basins in the SWAB study 

area, the SWAB-RASA regression equation estimates more 

recharge than the BCM in 27 of the 45 groundwater basins, 

mostly within a factor or 2.4 or less of the BCM estimate 

(table 15). These 27 basins are mostly in the less mountainous, southern portion of the study area (fig. 24). Ten basins 

have BCM estimates that exceed SWAB-RASA estimates, 

half of these by a factor of two or more (table 15). These 10 

basins are mostly in the more mountainous portion of the 

northern part of the study area (fig. 26). Future refinements 

of the BCM are planned as new information on rock and 

sediment permeability is obtained. Other recharge estimates 

reported in the Arizona Department of Water Resources’ 

(ADWR) multivolume Groundwater Atlas (Arizona Department of Water Resources, 2006, 2009a–e) are also reported 

in table 15 for comparison. Most of the values reported in the 

Groundwater Atlas refer to estimates by the original SWABRASA study (Freethey and Anderson, 1986), which used 

the same regression equation as in this study (equation 3), 

but using different precipitation estimates. Note that some 

ADWR recharge estimates listed in table 15 may include 

other recharge components and may not be directly comparable to the BCM or regression equation results.

Evapotranspiration 

Evapotranspiration (ET) is the set of processes by 

which water is removed by evaporation from surfaces such 

as soil and by transpiration from plants, principally via 

stomata (Hillel, 1998; Mauseth, 1991). In current usage, this 

definition may or may not include evaporation from water; 

however, as defined for this study, open-water evaporation 
34 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Figure 23. Average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for the 1940–2006 time 

period, by basin. BCM estimates of mountain-front recharge include in-place recharge plus 15 percent of runoff.

>0.2 to 0.35

EXPLANATION

0 to 0.05

>0.05 to 0.1

>0.1 to 0.2

>0.35 to 1.0

>1.0 to 1.4

Average Annual Mountain-Front Recharge

in inches per year
Regional Groundwater Budget 35

Figure 24. Locations of average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for the 

1940–2006 time period.

>3.0 to 5.0

EXPLANATION

0.05 to 0.5

>0.5 to 1.5

>1.5 to 3.0

>5.0 to 12.9

Average Annual Mountain-Front Recharge

in inches per year
36 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Average Annual Mountain-Front Recharge (inches)

Water Years

1940-1949 1950-1959 1960-1969 1970-1979 1980-1989 1990-1999 2000-2006

1940-2006 

Average

DETRITAL VALLEY MCMULLEN VALLEY

PHOENIX AMA

SAFFORD TUCSON AMA

VERDE RIVER

YUMA

Figure 25. Graph of decadal average annual recharge estimated by the Basin Characterization Model (BCM) for focus basins for 

six 10-year and one 7-year time periods from 1940 through 2006.

and evaporation from shallow groundwater are not included. 

ET is typically a significant component of most water 

budgets and may be estimated using a variety of methods 

(Freeze and Cherry, 1979; Goodrich and others, 2000). ET 

by wetland and riparian vegetation is an important component of groundwater discharge in arid and semiarid areas and 

was probably the principal discharge component in the study 

area before large-scale human alteration of groundwater 

systems (Anderson and others, 1992). Potential ET (PET) 

is the amount of water that would be removed by ET if the 

soil water available for ET were unlimited. The goal of this 

study was to estimate actual ET (AET) from groundwater on 

an annual basis, but as a step in this process AET was first 

calculated for the entire study area.

Methods

Annual average AET extracted from groundwater was 

estimated for the SWAB study area for the period 2000 to 

2007 and compared to predevelopment values based on work 

by Freethey and Anderson (1986). To calculate AET, satellitebased MODIS (Moderate Resolution Imaging Spectroradiometer) enhanced vegetation index (EVI) grid data (Oak Ridge 

National Laboratory, 2008) were used. Satellite data cover 

large swaths of the land surface with a repeat rate that is high 

enough to allow for reasonable estimates of seasonal and annual 

AET variability (fig. 27). EVI is used because it is a measure of 

greenness to which ET is directly correlated (Nagler and Glenn, 

2009; Nagler and others, 2009). EVI is used instead of more 

traditional products like the Normalized Difference Vegetation 

Index (NDVI) because it does not saturate at high levels of 

greenness (biomass) as does NDVI (Huete and others, 2002). 

Datasets covering the study area were available for each pass of 

the satellite (every 16 days) over the period 2000 to 2007 with 

individual pixel dimensions of 820.21 ft × 820.21 ft (250 m × 

250 m). The EVI datasets for each date were stitched together, 

then substituted into the following equations to calculate AET 

(mm/day) (Nagler and Glenn, 2009; Nagler and others, 2009):
Regional Groundwater Budget 37

EXPLANATION

Ratio of BCM recharge estimate to 

SWAB-RASA regression equation 

estimate

0.05 to 0.5 >0.5 to 0.75

>0.75 to 1.0 >1.0 to 1.25

>1.25 to 1.5 >1.5 to 2.0

>2.0 to 2.5 >2.5 to 2.8

Figure 26. Ratio of mountain-front recharge estimates produced by the Basin Characterization Model (BCM) to estimates from 

the Southwest Alluvial Basins-Regional Aquifer System-Analysis (SWAB-RASA) regression equation for the 1940–2006 time 

period, by basin. BCM estimates of mountain-front recharge include in-place recharge plus 15 percent of runoff.
38 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

AET = 1.22ETo × EVI*, (4)

where ETo is the “reference crop evapotranspiration” (mm/

day) as an average for a period of 1 month and EVI* is the 

scaled EVI. ETo is the evapotranspiration from a standardized 

vegetated surface (Allen and others, 1998). By substitution it is 

meant that in each grid, the value of each variable in each pixel 

was substituted into the appropriate equation using raster mathematics tools in ArcGIS®. ETo

 was calculated using a modified 

Blainey-Criddle relation (Brouwer and Heibloem, 1986):

ETo = p (0.46 Tmean + 8), (5)

where p is mean daily percentage of annual daytime hours and 

Tmean is mean daily temperature, calculated on a monthly basis 

as:

 Tmax+ Tmin Tmean = 2 , (6)

where Tmax and Tmin are defined as:

 Temperature data were obtained from PRISM (2008). EVI

was converted to a scaled value (EVI*) following the method 

of Nagler and others (2005):

EVI* = 1–(0.542–EVI)/(0.542–0.091), (7)

where 0.542 and 0.091 represent maximum and minimum 

EVI values, respectively, from a large dataset of riparian 

plant communities in the southwestern United States (Nagler 

and others, 2005).

These calculations were done for each pass of the satellite over the study area. Passes occurred approximately every 

16 days beginning early in 2000. At the time of download, data 

were available through Julian day 353 of 2007, with a few days 

missing in the period of record. For days on which no EVI data 

were available, estimated AET values were substituted as follows: at the beginning and end of the record, for Julian days 1, 

17, 33, and 49 of year 2000 and day 337 in 2007, the average 

of the same Julian day from years in which data were available 

was used to fill in missing AET values. Values for averaging 

were available for these days in all years, with the exception 

of day 49, which was not available in 2001. Other days missing data, but having EVI data on days before and after, were 

assigned the average of the ET calculated for the preceding and 

following days. This process was done for days 225 and 353 in 

2000; day 49 in 2001; day 305 in 2003; and days 81 and 113 

in 2005. Some computed AET pixel values were outside of the 

expected range of 0 to 0.59 in. per day (15 mm per day; Tolk 

and others, 2006). These occurred mainly over areas where 

snow accumulates for part of the year (values >0.59 in. per day) 

and where open water or sparse vegetation is present (negative 

values). Negative values were converted to zero, whereas values 

>0.59 in. per day were included in basin calculations because 

they had little overall effect on the basin-scale AET values.

Groundwater ET

Calculation of AET was done for all 820.21-ft (250 m) 

grid cells in the study area, with results resampled to 164-

ft (50 m) grid size. For the purposes of calculating basin 

groundwater budgets, the amount of AET being extracted 

only by presumed groundwater-using vegetation was estimated for each basin. Based on an assumption that wetland and other vegetation near surface water primarily use 

groundwater, AET was summed for all nonagricultural areas 

within 164 ft (50 m) of named rivers, streams, tributaries, 

and washes in the study area, as determined from information 

from the Arizona State Land Department (fig. 28; Arizona 

State Land Department, 1993). AET in areas falling outside 

of the 164-feet buffers was also assumed to be from groundwater if land cover in those pixels was classified as woody 

or herbaceous wetland based on the 2001 98.4-ft (30 m) 

Multi-Resolution Land Characteristics Consortium land-cover 

dataset for the study area (fig. 28; Homer and others, 2004). 

Herbaceous woodland is classified as land in which the soil or 

substrate is periodically saturated or inundated with water and 

which is covered by more than 80 percent perennial herbaceous 

vegetation. Woody wetland is classified as land in which the 

soil or substrate is periodically saturated or inundated with 

water and which is covered by more than 20 percent forest or 

shrubland. It was assumed that these land classifications represent those locations at which all or nearly all water extracted by 

plants comes directly from groundwater. 

Direct precipitation on vegetation has the potential to be 

at least a partial source of water for AET in the subset areas 

defined above. A lower bound on estimated groundwater ET for 

each basin in the study area was developed by subtracting out 

precipitation (PRISM, 2008) from ET estimates developed in 

this study.

Results

Minimum and maximum annual volumes of AET from 

groundwater are summarized by basin for the period 2000 

through 2007 in table 16. Maximum values are computed from 

equations 4 through 7, and minimum values are estimated by 

subtracting precipitation from each computed ET raster cell. 

This method of computing minimum AET assumes that all 

Tmax=

sum of all Tmax values during the month

number of days of the month

 number of days of the month

sum of all Tmin values during the month

Tmin=
Regional Groundwater Budget 39

Latitude North Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec

South July Aug Sept Oct Nov Dec Jan Feb Mar Apr May June

60° 0.15 0.20 0.26 0.32 0.38 0.41 0.40 0.34 0.28 0.22 0.17 0.13

55 0.17 0.21 0.26 0.32 0.36 0.39 0.38 0.33 0.28 0.23 0.18 0.16

50 0.19 0.23 0.27 0.31 0.34 0.36 0.35 0.32 0.28 0.24 0.20 0.18

45 0.20 0.23 0.27 0.30 0.34 0.35 0.34 0.32 0.28 0.24 0.21 0.20

40 0.22 0.24 0.27 0.30 0.32 0.34 0.33 0.31 0.28 0.25 0.22 0.21

35 0.23 0.25 0.27 0.29 0.31 0.32 0.32 0.30 0.28 0.25 0.23 0.22

30 0.24 0.25 0.27 0.29 0.31 0.32 0.31 0.30 0.28 0.26 0.24 0.23

25 0.24 0.26 0.27 0.29 0.30 0.31 0.31 0.29 0.28 0.26 0.25 0.24

20 0.25 0.26 0.27 0.28 0.29 0.30 0.30 0.29 0.28 0.26 0.25 0.25

15 0.26 0.26 0.27 0.28 0.29 0.29 0.29 0.28 0.28 0.27 0.26 0.25

10 0.26 0.27 0.27 0.28 0.28 0.29 0.29 0.28 0.28 0.27 0.26 0.26

5 0.27 0.27 0.27 0.28 0.28 0.28 0.28 0.28 0.28 0.27 0.27 0.27

0 0.27 0.27 0.27 0.27 0.27 0.27 0.27 0.27 0.27 0.27 0.27 0.27

A B

D

C

Figure 27. Examples of data types used to calculate actual evapotranspiration (ET) where (A) is MODIS EVI data (Oak Ridge 

National Laboratory, 2008), (B) is temperature data (PRISM, 2008), (C) is mean daily percentage of annual daytime hours based on 

latitude (Brouwer and Heibloem, 1986), and (D) is calculated actual ET from all vegetation types.

precipitation that falls on the presumed groundwater-using 

areas is directly used by vegetation, with no losses from 

runoff or other processes. Most maximum basin AET volumes 

are greater than minimum volumes by a factor of 2 or less 

(table 16). Estimated annual AET volumes from groundwater 

during this time period range from large values in the Salt 

River Basin (maximum of >176,000 acre-ft in 2005) and the 

Verde River Basin (maximum of >142,000 acre-ft in 2005) to 

minimum values of 0 in the Western Mexican Drainage Basin 

for 2002, 2004, and 2007. Average annual volumes of AET 

from groundwater for this period are compared with predevelopment AET values adapted from Freethey and Anderson 

(1986), and with postdevelopment PET values (Flint and Flint, 

2007a; table 17). It is assumed that the values from Freethey 

and Anderson refer to “actual” ET from groundwater and 

that no direct use of precipitation by plants is accounted for, 

although these issues are not discussed in their report. Flint 

and Flint (2007a) calculated PET as described in the “Estimation of Runoff from the Basin Characterization Model (BCM)” 

section using postdevelopment land-cover information. Estimated predevelopment ET volumes are typically smaller than 

AET estimated for this study, but in a few basins along the 

Colorado River and elsewhere, predevelopment ET may be an 

order of magnitude larger than current estimates. Anderson and 
40 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

EXPLANATION

Woody and herbaceous wetland 

landcover plus 50-m buffer 

around surface-water features

Figure 28. Area classified as primarily groundwater-using vegetation in the Southwest Alluvial Basins (SWAB) study area for 

evapotranspiration (ET) analyses. Surface-water features include rivers, streams, and tributary washes defined in geographic 

information system (GIS) coverage (Arizona State Land Department, 1993).
Regional Groundwater Budget 41

others (1992) suggest that conversion of riparian vegetation to 

agricultural fields during development may have considerably 

decreased ET, but the increase in AET in several basins supports 

the findings of Webb and others (2007) that riparian vegetation 

has increased over much of the study area. In cases in which 

predevelopment ET is higher, drought and lowered water tables 

caused by the interception of flow to riparian areas by pumping may also contribute to this difference. PET is, as expected, 

greater than 2000–2007 AET values calculated for all basins. A 

few of the basins in which predevelopment ET is greater than 

PET are along the Colorado River, where there may have been 

extensive wetlands and where currently there is large-scale agriculture. Thus, a large decrease in wetland vegetation between 

predevelopment and postdevelopment (the latter being the 

condition under which PET was estimated) could explain some 

of the differences in these values. 

Total average seasonal AET rates for the entire study area, 

and not just groundwater-using areas, (fig. 29) indicate that, in 

general, the highest rates are found in agricultural areas, with 

slightly lower rates in mountain forests. The deserts in the western and southwestern parts of the study area along the Colorado 

River tend to have the lowest AET rates overall. AET peaks in 

summer, coinciding with yearly highs in temperature and rainfall, but the exact timing varied from basin to basin. In the seven 

focus basins, minimum and maximum daily rates of groundwater-derived AET for the years 2000–2007 (fig. 30) showed 

wide variability, from close to zero on some individual days in 

Detrital Basin to more than 0.14 in/day on some individual days 

in the Yuma Basin. Differences in these rates among basins are 

probably related to basin elevation and length of perennial-river 

reaches within each basin, among other factors. 

Groundwater Underflow

The direction of groundwater flow within a basin is dictated by the hydraulic-head distribution, which is influenced by 

the location and magnitude of aquifer recharge and discharge, 

and by aquifer properties. The quantity of groundwater flow 

between basins depends on each basin’s geometry, the hydraulic gradient between the basins, and the hydraulic conductivity 

of the materials within and separating the basins. The rate of 

groundwater underflow between basins in the study area was 

estimated. For this study it was assumed that the principal aquifers near the basin boundaries were unconfined. 

Methods

As part of the SWAB-RASA study, the rate and direction 

of groundwater underflow under steady-state conditions were 

estimated for the SWAB-RASA groundwater basins for pre-1940 

conditions (Freethey and Anderson, 1986). For the current study, 

these predevelopment underflow volumes and directions were 

disaggregated from SWAB-RASA groundwater basin boundaries to ADWR groundwater basin boundaries (fig. 31). Both 

basin delineations share some common boundaries, with similar 

inflow and outflow locations. The inflows and outflows from 

the SWAB-RASA basins were matched with the corresponding 

inflows and outflows of the ADWR groundwater basins. 

The groundwater underflow component of a groundwater budget can be calculated using a calibrated numerical 

groundwater flow model. Creating a groundwater flow model 

simulating rates of groundwater underflow for the entire study 

area was beyond the scope of this study. As a result a Darcy’s 

Law approach using available groundwater-level data was used 

to calculate volumes of groundwater underflow between the 

basins. For current and recent (circa 1980) conditions, average 

groundwater levels from wells near basin boundaries compiled 

from the USGS and ADWR groundwater databases for 1975–

1980 and 2001–2005 were used to calculate hydraulic gradients 

between the basins for the two time periods. Wells with similar 

depths and groundwater levels for each adjacent basin were 

used in the calculation. The minimum numbers of wells in the 

estimation was two wells in each basin. The ADWR Arizona 

Water Atlases (Arizona Department of Water Resources, 2009a–

e) were used to infer groundwater flow directions in each basin. 

Darcy’s Law is expressed as 

 Q = − KA dG

dL (—) (8)

where

Q = Discharge in ft3/s 

K = Hydraulic conductivity in ft/s

H= Hydraulic head in ft

L = length in ft

A = Cross sectional area of flow in ft2.

Darcy’s Law can also be expressed using transmissivity 

in place of K 

 T = Kb (9)

where 

T = Transmissivity in ft2

/s

b = Aquifer thickness in ft.

Darcy’s Law expressed in the terms of transmissivity becomes

Q = − TW dG

dL (—) (10)

where 

Q = Discharge in ft3/s 

T = Transmissivity in ft2/s

W = Width of flow in ft

For current and recent conditions, it was assumed that 

the transmissivity term T was the same as in predevelopment 

conditions (despite possible water-level decline or rise) and 
42 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Julian Day 113

High: 0.61

Low: 0

EXPLANATION

Julian Day 17

Julian Day 225 Julian Day 305

Evapotranspiration (inches per day)

Figure 29. Seasonal variation in evapotranspiration (ET) for all vegetation types. Each date shows the average ET rate for each pixel on 

that date over the period 2000–2007.
Regional Groundwater Budget 43

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14 DETRITAL VALLEY

PHOENIX AMA SAFFORD

Jan–00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

MCMULLEN VALLEY

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Estimated Evapotranspiration from Groundwater

(inches per day)

Estimated Evapotranspiration from Groundwater

(inches per day)

Estimated Evapotranspiration from Groundwater

(inches per day)

Estimated Evapotranspiration from Groundwater

(inches per day)

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

EXPLANATION

Maximum estimated ET

Minimum estimated ET

Figure 30. Graphs showing estimated maximum and minimum monthly evapotranspiration (ET) rate from groundwater for focus basins 

from 2000–2007. Focus basin locations shown on figure 2.

that the only component of the groundwater underflow equation that changed between the time periods was the hydraulic 

gradient (dH/dL). An estimate of the transmissivity term T was 

back-calculated from the hydraulic gradient (dH/dL) and the 

steady-state discharge value Q from predevelopment estimates 

(Freethey and Anderson, 1986). For current conditions, the new 

hydraulic gradient (dH/dL) was calculated from water levels 

and then used in equation 10. For the Active Management 

Areas that have published groundwater models, the modeled 

values of groundwater inflow and outflow were used for the 

current conditions. Predevelopment estimates for underflow 

were used for current and recent conditions in basins that have 

not experienced significant groundwater development. 

Results

The largest groundwater underflow component from 

the study area during predevelopment and current times was 

underflow out of the Yuma Basin, mainly through subsurface 

flow in the Colorado River channel (table 18). The inflow 

component into the overall SWAB study area did not change 

between predevelopment and current conditions because 
44 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

YUMA

EXPLANATION

Maximum estimated ET

Minimum estimated ET

TUCSON AMA VERDE RIVER

(inches per day)

Estimated Evapotranspiration from Groundwater

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

(inches per day)

Estimated Evapotranspiration from Groundwater

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

(inches per day)

Estimated Evapotranspiration from Groundwater

Jan– 00 Jan– 01 Jan– 02 Jan– 03 Jan– 04 Jan– 05 Jan– 06 Jan– 07

Date

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Figure 30.—Continued.

eastern portions of the Duncan Valley and Morenci basins 

remain undeveloped. Other basins on the study area margins 

remain fairly undeveloped, and the rates of groundwater 

underflow to and from these basins have not changed substantially. A change in the direction of groundwater underflow was 

observed in the Pinal and Phoenix AMAs, which is consistent 

with the observations of Konieczki and English (1979) and 

Anderson (1995).

Groundwater Recharge by Seepage from 

Streams

The interaction of groundwater systems with streams and 

rivers in arid regions is complex and can vary both spatially 

and temporally. Hydrologic controls on flow in rivers and 

streams may come from the timing and location of runoff 

from precipitation, from groundwater entering or exiting the 

stream through the stream channel, from the effects of capture 

from nearby groundwater withdrawals, or from a combination 

of these events. Geology also exerts control on these systems 

because flow in a stream or river may seep into the ground as 

alluvial basins deepen, only to reemerge in the streambed as 

bedrock rises near the land surface at basin boundaries. 

Seepage from streams can be a substantial source 

of recharge in the Southwest Alluvial Basins of Arizona. 

Typically, seepage is estimated using several methods: (1) 

determining maximum amounts of streamflow available for 

downstream seepage from individual streamgaging stations, 

(2) determining differences in streamflow between two or 
Regional Groundwater Budget 45

!.

!.

!.

!.

!.

YUMA

TUCSON

PHOENIX

PRESCOTT

FLAGSTAFF

EXPLANATION

ADWR basin boundaries

USGS basin boundaries

Figure 31. Differences in groundwater basins used in Arizona Department of Water Resources (ADWR) and U.S. Geological 

Survey (USGS) studies.
46 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

more streamgages on the same stream, (3) measuring flow at 

selected locations during baseflow conditions and determining 

the differences in measured flows (gains or losses), (4) directly 

measuring seepage using soil-moisture sensors, and (5) using 

indirect chemical or physical characteristics such as isotopes, 

chemical constituents, electrical conductivity, gravity, or 

temperature (Stonestrom and others, 2007). Methods (1) and 

(2) were used in this study to investigate the potential recharge 

to aquifers by seepage from streams. Methods (3), (4), and (5) 

were beyond the scope of this study.

Methods

Streamflow data from 75 streamgages were evaluated 

for this study to determine if suitable data exist for estimating aquifer recharge from seepage (table 19). Only gages 

on streams and rivers internal to the study area were used 

in this analysis. Flow in the Colorado River was not analyzed owing to the difficulty of determining the effects of 

diversions, dams, and agricultural return flow on total flow 

in the river. The 75 streamgage areas were placed into two 

categories based on estimated flows upstream of the gage 

as a result of topology and geology: (1) gain; flows generally increase in magnitude with distance downstream, and 

(2) loss; flows generally decrease in magnitude as drainage 

area increases (table 19). Aquifer recharge from seepage 

losses are likely minimal on the stream reaches above gages 

classified as gaining, and recharge from seepage losses can 

be substantial on the stream reaches above gages classified as losing. Recharge by seepage from streams was 

evaluated and estimated by comparing streamflow data at 

75 streamgaging stations (table 19). Differences in daily 

mean flows and monthly flows between streamgages were 

calculated for the 18 streams with multiple gages (table 

20). These differences (gains or losses) were evaluated for 

magnitudes and seasonal relations.

Results

The differences in flows (gains or losses) between 

streamgages on all the streams were spatially and temporally 

variable (table 20). Of the 18 streams with multiple gages, 10 

streams had mostly gaining flow between the streamgages, 

indicating minimal or no seepage in those reaches (table 20). 

Four streams (Hassayampa River, Gila River, Santa Cruz 

River, and San Pedro River) had a combination of gains and 

losses between streamgages, and four streams had mostly 

losses between gages (New River, Tanque Verde Creek, 

Pantano Wash, and Rillito River). The differences in daily 

mean flows and monthly flows on these eight streams were 

extremely variable, showing both gains and losses from day to 

day. Runoff from tributaries between streamgages was likely a 

complicating factor. Even in seasons with minimal precipitation and tributary runoff, it was difficult to discern consistent 

losses that could be translated into seepage losses.

Mean annual streamflow was calculated for the 75 single 

streamgage sites and summarized by the region in which 

the runoff and seepage occur (fig. 32). Data from only 28 

downstream streamgages are presented in table 21, because 

these records summarize flow from above the gage. These 

flows were assumed to be the amount of flow that is potentially available for seepage downstream of the streamgage 

and define an upper limit to the volume of aquifer recharge 

from the stream. Some potential reductions in the volume of 

streamflow that could become aquifer recharge include shallow infiltration of streamflow and subsequent evapotranspiration, evaporation from the stream surface itself, impoundment 

by dams, and irrigation diversions. Mean annual volumes of 

flow available for seepage were calculated for two periods: (1) 

a predevelopment period (with no dams or irrigation diversions) and (2) a postdevelopment period, when several dams 

impound water on major streams (table 21).

The study area can be broadly classified into three types 

of runoff and seepage regions: (1) runoff, (2) seepage, and 

(3) runoff/seepage (fig. 32). The high-elevation areas in the 

northern part of the study area have mostly runoff with little 

seepage to groundwater. The low-elevation areas in the central 

and western parts of the State have little runoff and mostly 

seepage. The eastern part of the State has a combination of 

runoff from mountains and seepage in valleys. Most of the 

runoff from the high-elevation regions is accounted for by 

streamgages at the downstream ends of the regions. In the 

internal drainages of regions 1, 3, 4, 7, and 8 (fig. 32), only 

part of the streamflow available for seepage is measured by 

streamgages. Thus, the streamflow available for seepage was 

only estimated in a few basins in these five regions (table 22).

In the postdevelopment period, about 95 percent of the 

runoff from the three runoff regions (fig. 32) is impounded 

and stored behind dams. During the predevelopment period: 

(1) about 108,000 acre-ft of water was available for seepage 

in the lower part of region 2 (table 22), (2) about 1,200,000 

acre-ft of runoff from regions 5 and 6 (table 22) was available for seepage downstream from these regions, and (3) 

about 412,000 acre-ft of runoff from region 7 was available for seepage in region 4 (fig. 32; table 22), presuming 

minimal seepage along rivers before entering region 4. The 

1,555,000 acre-ft of predevelopment available seepage water 

in region 4 that came from outside regions is reduced to 

about 90,000 acre-ft of available water in the postdevelopment period. There are no dams on the internal drainages in 

the other internal regions, so the predevelopment estimate 

of streamflow available for seepage is approximately equal 

to the postdevelopment estimate. Although insufficient data 

were available to estimate aquifer gains or losses from/to 

streamflow on an individual groundwater basin scale, the 

information presented in table 22 provides a useful upper 

bound on aquifer recharge from streamflow for the study 

area. Estimates of predevelopment aquifer recharge from 

streamflow and aquifer discharge to streamflow developed 

by the SWAB-RASA study (Anderson and others, 1992) 

are presented in table 23 for reference for stream reaches in 
Regional Groundwater Budget 47

(1) Seepage

(2) Runoff

(4) Seepage

(5) Runoff

(6) Runoff

(3) Seepage (7) Runoff/Seepage

(8) Runoff/Seepage

EXPLANATION

All streamgage locations

Streamgage locations 

summarized in table 21 

Streamgage station number

!.

!.

!.

09517000

!. !.

!.

!.

!.

!. !.

!. !.

!. !. !. !. !. .!

!.

!.

!.

!. !. !. !.

!. !.

!. !. !.

!. !.

!. !. !. !. !. !.

!. !. !.

!.

!.

!.

!.

!. !.

!.

!.

!.

!.

!.

!.

!.

!.

!. !.

!.!. !.

!.

!.

!.!. !. !. !.

!. !. !.

!.

!.

!. !.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

!.

09512280

09490500

09444500

09484000 09483100

09516500

09513780

09512500 09507980

09506000

09504500

09504000 09504420 09503700

09497980

09497800

09497500

09494000

09489500

09489000

09486055 09485700

09485450

09484550 09482000

09481770

09481740

09480000

09472050

09471550

09470500

09466500

09447800

09447000

09442000

09432000

09424447 09424450

09424900

09425500

09426500

09498800 09515500 09508500 09497900 09512800 09499000

09513800

09513860 09489100

09510200 09513835 09498500

09517000 09468500 09446500 09444000

09448500

09488500 09457000

09472000 09486000

09484500

09482500 09485000

09471800 09535100

09484600

09535300 09486800

09471000

09537500

09480500

EXPLANATION

All streamgage locations

Streamgage locations 

summarized in table 21 

Streamgage station number

!.

!.

!.

09517000

(1) Seepage

(2) Runoff

(4) Seepage

(5) Runoff

(6) Runoff

(3) Seepage (7) Runoff/Seepage

(8) Runoff/Seepage

Figure 32. Location of streamflow gages used in analysis of stream seepage and classification of runoff/seepage 

regions in the Southwest Alluvial Basins of Arizona.
48 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

which infiltration was a significant part of the predevelopment water budget (fig. 33). 

Irrigation and Public Supply Water Use Data 

Collection in the Southwest Alluvial Basins

Anthropogenic water use is a significant component of 

the groundwater budgets in select basins in the study area. 

Information on anthropogenic water use in Arizona was collected historically by the USGS, with the task more recently 

divided between ADWR and USGS. These water-use data 

have been reported in a variety of publications over time. The 

USGS in Arizona collected and compiled water-use data by 

USGS groundwater basins (fig. 31) from the 1900s through 

1991 (Anning and Duet, 1994). More recently, annual groundwater and surface-water withdrawal data for irrigation and 

public supply are collected and compiled in each of the five 

AMAs by ADWR, with the USGS performing the collection 

and compilation for areas outside of the AMAs. Beginning 

in 1950, the USGS, as part of a national program on water 

use, has collected, compiled, and reported groundwater and 

surface-water withdrawals every 5 years. These reports contain withdrawal data for the categories of public supply, irrigation, mining, thermoelectric power, domestic, commercial, and 

industrial uses (Solley and others, 1983, 1988). From 1981 

through 1990, the USGS and ADWR cooperatively prepared a 

series of reports titled “Summary of Ground-Water Conditions 

in Arizona” that summarize the groundwater withdrawal data 

by USGS groundwater basins. Recently, ADWR has published 

these data in Water Atlases (Arizona Department of Water 

Resources, 2006, 2009a–e). Groundwater withdrawals for 

urban turf irrigation were not included in the irrigation analysis because some of these urban turf irrigation withdrawals are 

accounted for in the groundwater withdrawals for public supply. Detailed estimates of turf acreage were also not available 

for the study area.

Methods

Published datasets from the ADWR and the USGS 

were used to estimate the groundwater and surface-water 

withdrawals for irrigation and public supply for 1980 and 

2005 in the SWAB study area. The water-usage tables in the 

ADWR Water Atlases report groundwater and surface-water 

withdrawals since 1971, with projections to 2050. Before 

1990, only one average groundwater and one average surfacewater withdrawal value were presented for each ADWR 

basin for a 5-year period. Starting in 1991, water-usage data 

were subdivided into three categories: municipal, industrial, 

and irrigation. Whereas most ADWR and USGS-delineated 

groundwater basins share similar boundaries, the majority of 

ADWR basins comprise several USGS groundwater basins 

(fig. 31). To make comparisons between the 1980 and 2005 

groundwater and surface-water withdrawals, 1980 withdrawal 

data were disaggregated from USGS basins and reaggregated 

by ADWR groundwater basins. To calculate the 1980 groundwater withdrawals for the same categories available for the 

2005 data, it was assumed that the proportions of water withdrawals in each ADWR basin for each use remained constant 

for the time period 1991 to 1995. The proportional water-use 

categories were then multiplied by the average of the 5-year 

period for 1975 to 1980 to estimate municipal and irrigation 

withdrawals for 1980.

Irrigation

The 1980 groundwater and surface-water withdrawals for irrigation for the study area including the AMAs 

were obtained from the ADWR Water Atlas series (Arizona 

Department of Water Resources, 2006, 2009a–e), with the 

exception of three basins. The Colorado River comprises 

the western boundaries of the Yuma, Parker, and Lower Gila 

basins in the southwest part of the study area, and these three 

basins receive surface water diverted from the Colorado 

River. These surface-water diversions are metered by the 

USGS. Although the surface-water diversions are included in 

the ADWR Water Atlas series (Arizona Department of Water 

Resources, 2006, 2009a–e), the same surface water diversion 

value is reported for each of the three basins, which is highly 

unlikely. As a result, the 1980 surface-water diversions for 

the Yuma, Parker, and Lower Gila basins were obtained from 

USGS-metered surface-water diversions instead of from the 

Water Atlases.

 The 2005 groundwater and surface-water withdrawal 

data for irrigation in the non-AMA ADWR groundwater basins 

were obtained from the USGS Arizona Water Use Program 

Web site (U.S. Geological Survey, 2009a). For the five AMAs, 

groundwater and surface-water withdrawal data were obtained 

from the ADWR Active Management Area Assessment 

Web site (Arizona Department of Water Resources, 2009f). 

Although the focus of this report is on groundwater budgets 

in the study area, surface-water withdrawals for irrigation for 

both time periods were included in the analysis in order to 

estimate incidental aquifer recharge from irrigation (see “Incidental Recharge from Irrigation Water Use” section below).

Public Supply

The 1980 groundwater withdrawal data were obtained 

from the ADWR Water Atlas series (Arizona Department of 

Water Resources, 2006, 2009a–e). The 2005 public-supply 

groundwater withdrawal data from all areas with the exception of the AMAs were obtained from the USGS Arizona 

Water Use Program Web site (U.S. Geological Survey, 2009a). 

For the five AMAs, public-supply groundwater withdrawal 

data were obtained from the ADWR Active Management 

Area Assessment Web site (Arizona Department of Water 

Resources, 2009f). 
Regional Groundwater Budget 49

Gila River

Gila River

Salt River

Colorado River

Verde River

Santa Cruz River

San Pedro River

Bill Williams River

Oak Creek

San Francisco River

Figure 33. Stream reaches in the study area in which infiltration was a significant part of the predevelopment water 

budget (adapted from Anderson and others, 1992). 
50 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Results

Groundwater and surface-water withdrawals for irrigation for 1980 and 2005 are presented in acre-ft in table 24 

for 28 basins in which data were available. Groundwater 

and surface-water withdrawals for public supply for 1980 

and 2005 are presented in acre-ft in table 25 for all 45 basins 

(with Douglas INA data included with the Douglas Basin). 

Withdrawals for some basins are reported as “less than 300 

acre-ft” or “less than 1,000 acre-ft.” Total groundwater and 

surface-water withdrawals reported in the text, figures, and 

tables are the summation of the values greater than 300 

acre-ft or greater than 1,000 acre-ft. The rounding criteria of 

Tadayon (2005) were used to present the groundwater and 

surface-water withdrawal data:

•	 Values from 300 to <1,000 acre-ft are presented to the 

nearest 50 acre-ft. 

•	 Values from 1,000 to <10,000 acre-ft are presented to 

the nearest 100 acre-ft. 

•	 Values from 10,000 to <100,000 acre-ft are presented 

to the nearest 500 acre-ft. 

•	 Values from 100,000 to <1.0 million acre-ft are presented to the nearest 1,000 acre-ft. 

•	 Values of 1.0 million acre-ft and greater are presented 

to the nearest 5,000 acre-ft.

Irrigation

The largest volumes of groundwater withdrawals for 

irrigation during 1980 were in the Phoenix and Pinal AMAs 

(fig. 34 and table 24). Outside of the AMAs, the Lower Gila 

Basin had the largest groundwater withdrawals for irrigation. For 1980, total groundwater withdrawals in the study 

area in basins with groundwater irrigation withdrawals 

greater than 1,000 acre-ft were 3.6 million acre-ft. For 2005, 

total groundwater withdrawals in the study area in basins 

with irrigation groundwater withdrawals greater than 1,000 

acre-ft were 1.9 million acre-ft (fig. 34 and table 24). The 

greatest declines in groundwater withdrawals for the time 

period of 1980 through 2005 were in the Phoenix and Pinal 

AMAs, whereas groundwater withdrawals increased the 

most in the Ranegras Plain Basin. As in 1980, the largest 

groundwater withdrawals for irrigation in 2005 were in the 

Pinal and Phoenix AMAs. Outside of the AMAs, the Gila 

Bend Basin had the largest groundwater withdrawals for 

irrigation purposes.

In 1980 and 2005, the Yuma basin had the greatest 

amount of surface-water withdrawals for irrigation, followed 

by the Phoenix AMA (table 24). Increases in surface-water 

withdrawals for irrigation occurred in the Tucson AMA, Harquahala INA, and Pinal AMA between 1980 and 2005 (table 

24). These increases in surface-water withdrawals from the 

three basins are from the importation of surface water through 

the CAP canal. Surface-water withdrawals have decreased the 

most in the Gila Bend Basin, from 102,000 acre-ft in 1980 to 

55,500 acre-ft in 2005. 

Public Supply

Total withdrawals of groundwater in 1980 for public 

supply in basins with withdrawals greater than 300 acre-ft was 

480,000 acre-ft (table 25). The Phoenix AMA had the greatest public-supply groundwater withdrawals, followed by the 

Tucson AMA and Lake Havasu Basin in 1980 (fig. 35, table 

25). Twenty-nine of the 45 basins had withdrawals less than 

300 acre-ft for public-supply. The Yuma basin had the greatest 

withdrawals for public supply in 1980 outside of the AMAs. 

Total withdrawals of groundwater in 2005 for public 

supply in basins with withdrawals greater than 300 acre-ft 

were 526,000 acre-ft. Lake Mohave had the largest withdrawals for public supply outside of the AMAs in 2005 (fig. 

35 and table 25). The Phoenix AMA was the only basin that 

showed a decrease in public-supply groundwater withdrawals between 1980 and 2005. This decrease in groundwater 

withdrawals is primarily from the increased use of surface 

water from the CAP for public supply in the Phoenix AMA. 

Groundwater withdrawals for public supply in the Prescott 

AMA, Lake Mohave, and Pinal AMA basins each increased 

by 10,000 acre-ft or more between 1980 and 2005. 

Incidental Recharge from Irrigation Water Use

Not all water withdrawn for irrigation purposes is used 

consumptively by plants; some of this water is lost in the 

conveyance system, during deep percolation, and as recharge 

to the aquifer. For this study, potential incidental recharge 

from irrigation is defined as irrigation water that is not used 

by the crop for consumptive use. The irrigation efficiency 

was used to estimate the maximum potential recharge from 

irrigation water use and is defined as the crop consumptive 

water requirement divided by the total quantity of water 

withdrawn for irrigation (Tadayon, 2005). The irrigation efficiencies in the study area differ depending upon the type of 

irrigation system used by the grower. Irrigation efficiencies 

for the SWAB study area are shown in table 26 (S. Tadayon, 

oral commun., 2009). 

Methods

To estimate the quantity of irrigation water that percolates to the aquifer as recharge, total water withdrawals for 

irrigation (from both groundwater and surface water sources) 
Regional Groundwater Budget 51

2005

1980

EXPLANATION

<1,000

>1,000 to 10,000

>10,000 to 20,000

>20,000 to 200,000

>200,000 to 500,000

>500,000 to 908,000

Estimated Groundwater Withdrawals for 

Irrigation, in acre-ft

Figure 34. Estimated groundwater withdrawals for irrigation in 1980 and 2005. Uncolored basins have no reported data.
52 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2005

1980

EXPLANATION

<300

>300 to 2,500

>2,500 to 10,000

>10,000 to 15,000

>15,000 to 100,000

>100,000 to 264,000

Estimated Groundwater Withdrawals for 

Public Supply, in acre-ft

Figure 35. Estimated groundwater withdrawals for public supply in 1980 and 2005.
Regional Groundwater Budget 53

for each basin were first multiplied by an inefficiency coefficient (1 minus the irrigation efficiency). This value represents 

the maximum quantity of water that is available for recharge 

from irrigation.

Information on irrigation system type and irrigation 

volume of water applied was not available for 1980, so 1985 

acreage by irrigation system and volume of water applied 

by eight-digit Hydrologic Unit Code (HUC) were obtained 

from the USGS National Water-Use Data Archive Web 

site (U.S. Geological Survey, 2009b). The eight-digit HUC 

basins are similar to the ADWR basins and were applicable 

for this study. A weighted average for irrigation efficiency 

was computed based on the eight-digit HUC irrigation types 

for acreages of known irrigation systems. Water-use data 

collected by the USGS for irrigation in the ADWR basins 

were used to estimate the maximum potential recharge from 

irrigation water use for 2005. As part of the annual data collection by the USGS, for each ADWR groundwater basin 

outside of the AMAs, the irrigation system, crop type, and 

acreage are reported. For the AMA basins, water withdrawals 

were obtained from the ADWR Water Atlas series (Arizona 

Department of Water Resources, 2006, 2009a–e). For basins 

outside of the AMAs where sufficient data about irrigation 

systems and acreage were available, the losses from each 

type of irrigation system were computed and then summed 

for each basin. For the AMAs, an overall efficiency of 60 

percent was used, assuming that the majority of the irrigated 

fields in the AMAs are flooded. 

For three basins, the Phoenix AMA, Lower Gila Basin, 

and Yuma Basin, there are drainage wells that needed to be 

considered. The main purpose of these drainage wells is to 

keep the water table from rising to the root zone to allow for 

the flushing of excess salts (Tadayon, 2005). In the Phoenix 

AMA, the Lower Gila Basin, and Yuma Basin, the volumes of 

shallow groundwater withdrawn from the drainage wells are 

metered, and these volumes were subtracted from the maximum potential recharge from irrigation for both the 1980 and 

2005 time periods.

Results

The estimates of maximum potential incidental recharge 

from irrigation for 1980 and 2005 are presented in acreft (table 27). In 1980, the greatest estimates of maximum 

potential incidental recharge were for the Phoenix and Pinal 

AMAs (fig. 36 and table 27). The total estimated volume 

of maximum potential incidental recharge to the aquifer 

from irrigation in 1980 in basins with irrigation withdrawals 

greater than 1,000 acre-ft was 2.0 million acre-ft (table 27). 

In 2005, the greatest estimates of maximum potential incidental recharge were also for the Phoenix and Pinal AMAs (fig. 

36 and table 27). The total estimated volume of maximum 

potential incidental recharge to the aquifer from irrigation in 

2005 in basins with irrigation withdrawals greater than 1,000 

acre-ft was 1.6 million acre-ft (table 27).

Recharge from the Central Arizona Project

An additional inflow to the groundwater budgets of 

some alluvial basins is intentional recharge of surface water 

delivered by the Central Arizona Project (CAP) into the 

study area. Construction of the CAP canal began in 1973 

and was completed in 1993. The CAP canal allows Arizona 

to use a portion of its Colorado River allotment in interior 

basins. The water delivered by the CAP canal (CAP water) 

is used for municipal, industrial, and irrigation uses, as well 

as providing water for aquifer recharge and storage facilities in the study area. Storage of CAP water in Underground 

Storage Facilities (USF) or Ground Water Savings Facilities 

(GSF) is administered by the ADWR. CAP water delivered 

to a USF is often recharged to the aquifer by an injection 

well or a percolation basin. Some USFs discharge CAP 

water into ephemeral streambeds for aquifer recharge. CAP 

water is also delivered to GSFs, where it is transferred to 

users such as irrigation districts who would otherwise pump 

groundwater. For more information on the storage of CAP 

water, readers are referred to Colby and Jacobs, 2007.

Methods

Information on the volumes of CAP water delivered to 

GSF and USF facilities is collected by the ADWR for accrual 

of recharge credits. All of the permitted recharge facilities 

for CAP water are located in the Phoenix, Tucson, and Pinal 

AMAs. These three AMAs have a combined annual permitted storage capacity at both USFs and GSFs of 2.1 million 

acre-ft (Arizona Department of Water Resources, 2006, 

2009a–e). 

Results

The annual volume of CAP water delivered to USFs at 

the end of the 2005 calendar year includes delivery of 94,000 

acre-ft to the Phoenix AMA and 141,000 acre-ft to the 

Tucson AMA (D. Kusel, written commun., 2009). This total 

volume of 235,000 acre-ft represents the maximum amount 

of recharge from surface-water deliveries from the CAP to 

USFs. 

Artificial Recharge from Treated Effluent

Another small component of the groundwater budgets in 

several alluvial basins in the study area is treated effluent from 

municipalities that recharges the aquifer. The treated effluent 

can recharge through seepage after its release to an infiltration 

basin or watercourse such as a channel, or it can be recharged 

directly through injection wells.

Methods 

The volumes of treated effluent discharged into unlined 

impoundments or injection wells in alluvial basins in the study 
54 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2005

1980

EXPLANATION

Estimated Incidental Recharge from Irrigation

in acre-ft

<1,000

>1,000 to 5,000

>5,000 to 50,000

>50,000 to 100,000

>100,000 to 300,000

>300,000 to 499,000

Figure 36. Estimated potential incidental recharge from irrigation water use in 1980 and in 2005. Uncolored basins have no reported data.
Regional Groundwater Budget 55

area were provided by ADWR personnel (K. M. Lacroix, 

written commun., 2009). Additional information on the Upper 

San Pedro Basin, Tucson AMA, Santa Cruz AMA, and the 

Prescott AMA was obtained from published reports (table 28). 

The volumes of treated effluent discharge in table 28 represent 

the maximum potential volumes of recharge to the aquifer. 

Although a portion of this treated effluent actually becomes 

aquifer recharge, some portion is also lost to evaporation.

Results

Maximum estimated aquifer recharge from treated effluent was greatest in the AMAs (fig. 37, table 28), with the highest volume being 34,000 acre-ft in the Phoenix AMA. In the 

Phoenix AMA, an additional approximately 140,000 acre-ft of 

treated effluent is delivered to the Palo Verde nuclear power 

station for cooling of the plant’s reactors and is not available 

for recharge (Colby and Jacobs, 2007). The Upper San Pedro 

Basin had the greatest estimated recharge from treated effluent 

outside of the AMAs (fig. 37, table 28).

Change in Aquifer Storage Since Before 

Development

In many basins in the SWAB study area, the imbalance 

between aquifer recharge and aquifer discharge (particularly groundwater withdrawals), has led to large decreases in 

aquifer storage. An estimate of total change in aquifer storage 

between predevelopment times and post-2000 conditions was 

produced using published groundwater-level information and 

depth-to-groundwater data. This method of estimating aquifer 

storage change does not rely on the accuracy of other groundwater budget components and is thus independent of any 

uncertainties in their estimation.

Methods

The change in aquifer storage since before development was estimated for the most developed basins in the 

SWAB area. Although estimates were not developed for 

all 45 groundwater basins in the study area, the 15 basins 

investigated account for more than 85 percent of the total 

historical groundwater withdrawals for the State through 

1987 (Konieczki and Wilson, 1992) and therefore represent 

most of the change in aquifer storage within the study area. 

Estimating the change in aquifer storage since before development for the most developed SWAB basins in Arizona 

involved basic hydrologic analyses of historical and recent 

groundwater-level surfaces. Literature sources for predevelopment groundwater levels in the SWAB basins were 

located. Maps in these reports were scanned and georeferenced into a geographic information system (GIS) and the 

groundwater-level information was digitized. Well records 

also were searched to determine if groundwater-level observations were available for the predevelopment era and if so, 

these data were added to the predevelopment maps in GIS. 

A surface of predevelopment groundwater levels was created 

from all available historical groundwater information using 

interpolation methods such as inverse distance weighting or 

nearest neighbor (Cressie, 1993). Recent groundwater-level 

surfaces were generated in a similar manner using current 

and recent (since 2000) groundwater observations contained 

in the USGS and ADWR databases. A subtraction of the 

current groundwater-level surface from the predevelopment 

surface in GIS produced a layer of groundwater-level change 

since predevelopment times. Storage coefficients were 

obtained from previously published reports. Depending on 

the type of aquifer, the storage coefficients may be specific 

yield or the product of specific storage and thickness. Aquifer 

storage change since before development was then computed 

as the product of the storage-coefficient value and the change 

in water level.

Results

In some areas of the most developed SWAB basins, a 

lack of predevelopment information precluded determination 

of change in groundwater levels and storage since predevelopment times. As previously described, groundwater levels 

from predevelopment reports and maps were augmented with 

observations from the NWIS and ADWR databases, where 

appropriate. In certain areas, however, there was no information on predevelopment conditions and, consequently, no 

estimate of aquifer storage change could be computed. Total 

aquifer storage change since before development for the study 

area, therefore, is probably underestimated.

Aquifer storage change since predevelopment times for 

the SWAB basins of Arizona is presented graphically in units 

of feet of water (fig. 38) and in a table as volume of change 

(table 29). Areas with large declines in groundwater levels, such as the heavily agricultural area of the Pinal AMA, 

have seen accompanying large declines in aquifer storage 

(fig. 38; see fig. 2 for basin names). Some wells in the Pinal 

AMA have recorded declines in groundwater observations of 

more than 500 feet since the mid-1940s (Tillman and others, 

2007). The large land area under development along with 

large amounts of historical groundwater withdrawals in the 

Phoenix AMA have resulted in more than 30 million acre-ft 

of estimated aquifer storage depletion in this basin (table 

29). The computed total volume of 74.5 million acre-ft of 

groundwater lost from storage for the basins covering about

85 percent of recorded groundwater withdrawals through 

1987 is comparable to other published estimates of 92.0 

million acre-ft (Robson and Banta, 1995) and 100 million 

acre-ft (Anderson and others, 1992) for the entire SWABRASA study area through 1980. Comparisons from this study 

with aquifer storage change estimates from recently reported 

modeling results include 5.3 million acre-ft versus 6.9 million acre-ft (Mason and Bota, 2006) for the Tucson AMA 

and 899,000 acre-ft versus 704,000 acre-ft (Pool and others, 

2011) for the Prescott AMA. 
56 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2005

EXPLANATION

<300

>300 to 500

>500 to 1,000

>1,000 to 2,500

>2,500 to 5,000

>5,000 to 48,500

Estimated Groundwater Recharge 

from Effluent, in acre-ft

Figure 37. Estimated potential groundwater recharge from treated effluent in 2005. Uncolored basins have no reported data.
Regional Groundwater Budget 57

EXPLANATION

<-30

-30 to -20

>-20 to -10

>-10 to 0

>0 to 5

>5

Change in Aquifer Storage

in feet since before development

Figure 38. Estimate of change in aquifer storage from before development (circa 1940) to present (2000–2006) for the most 

developed alluvial basins in Arizona. Storage change estimate does not include loss of storage from land subsidence. 

Negative values represent removal of groundwater from aquifer storage and positive values indicate addition of 

groundwater to aquifer storage. Estimation method based on water-level change over period of development and assumed 

storage coefficients. Predevelopment or present-day data unavailable for white areas inside of most developed basins.
58 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Regional Groundwater Budget Summary

The alluvial basins in Arizona have experienced significant 

population growth since the USGS SWAB-RASA studies in 

1980. Currently, groundwater accounts for about 50 percent of 

water used in these alluvial basins (Tadayon, 2005). The stress 

on groundwater supplies in the alluvial basins is expected to 

increase with projected population growth. The USGS Groundwater Resources Program instituted the SWAB Groundwater 

Availability and Use Pilot Program to evaluate the availability of 

groundwater resources in the alluvial basins of Arizona. Updated 

data and new methods of data analysis were used to evaluate 

groundwater budget components for each of the alluvial basins 

in Arizona for predevelopment and modern time periods.

Inflows to the SWAB aquifer system during predevelopment times occurred from three sources: mountain-front 

recharge, streamflow infiltration, and groundwater underflow 

into the study area. The largest components of the predevelopment groundwater budget were mountain-front recharge and 

streamflow infiltration, together accounting for nearly 1.4 

million acre-ft per year (fig. 39). Estimates of mountain-front 

recharge remain roughly the same between predevelopment 

and current conditions (fig. 39). Although inflows into the 

SWAB aquifer system from streamflow infiltration for current 

conditions is reduced owing to damming of rivers and reduced 

streamflow resulting from groundwater pumping, incidental 

recharge from irrigation, effluent, and intentional recharge 

of some of the Colorado River water delivered through the 

CAP canal system has the potential to offset much of this loss. 

Nearly 1.9 million acre-ft of incidental recharge may be available for groundwater in the study area (fig. 39).

Outflow from the SWAB aquifer system for predevelopment times occurred mainly through two processes: evapotranspiration and groundwater underflow out of the alluvial 

basins. Some groundwater discharge to streamflow also probably occurred along reaches of the Bill Williams and Gila 

River that were formerly perennial to the Colorado River. 

Modern conditions in the SWAB aquifer systems are defined 

by the addition of the large human-induced outflow component of groundwater withdrawals. The total annual estimated 

outflow from the SWAB aquifer system for the predevelopment time period is estimated to be about 1.3 million acre-ft 

and for the current time period about 3.7 million acre-ft (fig. 

39). The largest groundwater budget component during either 

time period was groundwater withdrawals for public supply 

and irrigation, estimated to be about 2.4 million acre-ft.

Individual components of the groundwater budget for 

both predevelopment and modern time periods were estimated 

independently of each other, with no attempt made to balance 

inflows and outflows. Differences in the methods and data 

sources, as well as the uncertainty in each of the individual 

groundwater budget components, results in a net imbalance 

during predevelopment time periods, even though groundwater inflow and outflow should be equal during this long-term 

steady-state era. Development of the aquifer systems, however, 

produced an imbalance between inflows and outflows (mainly 

groundwater withdrawals), resulting in an estimated loss of 

aquifer storage of 74.5 million acre-ft between predevelopment 

and modern times for the most developed basins in the study 

area (fig. 39). 

Demonstration of a Multibasin 

Groundwater-Flow Model for SouthCentral Arizona

A proof-of-concept steady-state numerical groundwaterflow model was developed for a large, multibasin area in the 

south-central portion of the SWAB study area (fig. 40). The 

goal in developing this simplified model was to determine if 

reasonable simulation of the hydrologic systems of several 

alluvial basins connected only by narrow constrictions was 

possible and to test the groundwater budget component of 

recharge developed in this study. Basins with areas selected 

for the multibasin proof-of-concept model include Tucson 

and Pinal AMAs, where the most developed areas were 

modeled. All modeling was accomplished using the threedimensional groundwater-flow model MODFLOW 2005 

(Harbaugh, 2005). The model area comprises more than 

2,900 square miles and includes the urban Tucson metropolitan area as well as agricultural areas in the Picacho 

and Maricopa-Stanfield Basins of the Pinal AMA (fig. 40), 

which have seen some of the greatest declines in groundwater levels in the State (fig. 9). The model was constructed 

using existing hydrogeologic frameworks for the Tucson 

and Santa Cruz AMAs, modification of a previously unpublished framework for the Picacho Basin in the Pinal AMA, 

and a new framework developed from limited well logs and 

published geohydrologic reports for the Maricopa-Stanfield 

Basin, also in the Pinal AMA. 

Geohydrologic Conditions in the Model Area

The model study area consists of the Santa Cruz River 

drainage from south of the Santa Cruz River at Tubac, AZ 

streamgage (site 09481740) in the Santa Cruz AMA; the 

Tucson Basin near the City of Tucson and Avra Valley of the 

Tucson AMA; the Picacho and Maricopa-Stanfield Basins 

of the Pinal AMA; and a small portion of the Phoenix AMA 

surrounding the Gila River (fig. 40). The length of the model 

area along the Santa Cruz River is 153 miles, and the total 

area encompasses 2,943 square miles. A roughly 4-mile-wide 

constriction in the basin alluvium between the Silverbell and 

Picacho Mountains separates the model area into two main 

parts at the boundary between the Tucson and Pinal AMAs. 

Basins in the model area consist of alluvial material surrounded 

by mountain bedrock, but only the basin-fill sediments are sufficiently transmissive to groundwater to be considered aquifers 
Demonstration of a Multibasin Groundwater-Flow Model for South-Central Arizona 59

Figure 39. Summary of independently estimated 

groundwater budget components for the overall 

Southwest Alluvial Basins study area during 

predevelopment and recent time periods. Arrow sizes 

for individual components are proportionally scaled to 

largest budget component (groundwater withdrawals), 

with the average value used for components with a 

range. Aquifer discharge to streams not estimated in 

this study or included in this figure, although this may be 

a significant groundwater budget component for some 

basins along the Colorado River.

1

 Adapted from Anderson (1995) for study area.

2

 Predevelopment mountain-front recharge estimate from SWAB-RASA regression equation results for 1940–1949.

3

 Incidental recharge estimate includes the sum of recharge from treated effluent greater than 300 acre-ft per year, maximum potential recharge from 

irrigation greater than 1,000 acre-ft per year, and recharge from CAP deliveries to managed recharge facilities, all for the 2005 calendar year.

4

 Recent mountain-front recharge estimate from SWAB-RASA regression equation results for 2000–2006.

5

 Range of recent streamflow infiltration is 50–100% of streamflow available for recharge in table 21.

6

 Range of recent evapotranspiration from minimum and maximum average 2000–2007 estimates in table 16.

7

 Estimate of total groundwater storage depletion from analysis of groundwater level changes. 

Groundwater Underflow

12,000 acre-ft per yr

Incidental Recharge3

1,930,000 acre-ft per yr

Mountain-Front Recharge4

515,000 acre-ft per yr

Streamflow Infiltration5

137,000 - 275,000 acre-ft per yr

Groundwater Underflow

275,000 acre-ft per yr

Evapotranspiration6

735,000 - 1,293,000 acre-ft 

per yr

Groundwater Withdrawals

2,400,000 acre-ft per yr

Circa 2000–2006 groundwater budget

Predevelopment groundwater budget

Groundwater 

Underflow

12,000 acre-ft per yr

Mountain-Front 

Recharge2

572,000 acre-ft per yr

Streamflow Infiltration1

807,000 acre-ft per yr

Groundwater 

Underflow

151,000 acre-ft per yr

Evapotranspiration1

1,200,000 acre-ft per yr

Estimated Loss of 

Storage Since 

Predevelopment7

74,500,000 acre-ft


60 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Pinal AMA

Tucson AMA

Santa Cruz AMA

Phoenix AMA

Donnelly Wash

San Simon Wash

Santa Cruz River

AVRA VALLEY

ALTAR VALLEY

SILVERBELL

 MTS

PICACHO

 MTS

Rillito Creek

Gila River

Model Boundary Model Boundary

Picacho Basin

Model Area

Maricopa-Stanfield 

Basin

Model Area

Tucson AMA

Model Area

Santa Cruz AMA

Model Area

0 10 20 5 MILES

0 10 20 5 KILOMETERS

City of Tucson

Santa Cruz River at Tubac, AZ

gage 09481740

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

Figure 40. Map of proof-of-concept model area indicating model boundary and component model areas used in creating 

model framework.
Demonstration of a Multibasin Groundwater-Flow Model for South-Central Arizona 61

and only these areas are modeled in this study. Predevelopment 

groundwater flow in the area generally followed the Santa Cruz 

River drainage, with northerly flow in the Santa Cruz AMA and 

most of the Tucson AMA, and northwesterly flow through the 

basins of the Pinal AMA (Anderson and others, 1992). 

Pre-Basin and Range sediments overlie consolidated 

rocks in the basins and are Tertiary in age. These sediments 

consist of moderately to highly consolidated deposits that 

range from silt, clay, and claystone to gravel and conglomerate (Anderson and others, 1992). The Basin and Range 

disturbance in the late Tertiary formed structural basins 

that subsequently filled with erosional material from tens to 

more than 11,000 feet thick (Hanson and Benedict, 1994; 

fig. 41). Deposition of sediments occurred at different rates 

throughout the area, leading to variability in thickness, areal 

extent, and grain size. Basin-fill sediments in the area are 

often divided into two or more units based on grain size, 

color, degree of consolidation or deformation, stratigraphic 

position, clast type, and water-bearing characteristics 

(Anderson and others, 1992). Generally, lower basin-fill 

sediments are more highly consolidated and finer grained 

than the upper basin-fill sediments. In the deeper basins 

they are also more likely to contain mudstone and evaporate 

deposits. Lower basin-fill sediments are generally indicative 

of deposition during a topographically closed-basin period, 

with upper basin fill representing a transition period from 

closed to integrated drainage basins (Anderson and others, 

1992). The lower basin fill comprises the Pantano Formation 

and the lower and middle Tinaja beds in the Tucson area 

(Anderson, 1987). The upper basin fill is generally more 

coarse grained than the lower basin fill, consisting mainly 

of gravel, sand, and clayey silt (Anderson and others, 1992; 

Hanson and Benedict, 1994). The upper basin fill is equivalent to the upper Tinaja beds and Fort Lowell Formation in 

the Tucson area (Anderson, 1987). Stream alluvium overlies basin-fill sediments along the present surface-drainage 

system and generally consists of flood-plain material and 

alluvial-fan deposits (Anderson and others, 1992). More 

detailed descriptions of the hydrogeology of basins in the 

study area are provided in the “Description of the Study 

Area” section of this report.

Annual precipitation in the Tucson and Pinal AMAs 

averages 14.7 and 9.7 inches, respectively, for the 1940–

2006 time period (see table 1), with most rainfall occurring 

in higher elevations. Recharge to the SWAB aquifer system 

from precipitation may occur by direct infiltration of water 

through mountain faults and fractures or through permeable 

pediment or basin sediments and drainage channels. Mountain-front recharge estimates in the Tucson and Pinal AMAs 

are 1.4 and 0.8 percent of precipitation, respectively, for the 

SWAB-RASA regression equation and 0.9 and 0.2 percent of 

precipitation, respectively, for the BCM (see tables 12 and 

13). Major surface drainages in the model area include the 

north-flowing Santa Cruz River, the west-flowing Gila River, 

and their tributaries. 

Model Characteristics

The purpose of this model was to demonstrate the ability 

to reasonably simulate steady-state groundwater conditions in 

multiple, large alluvial basins in the study area connected by 

narrow constrictions and to evaluate the recharge estimate produced during this study. This model was designed as a proofof-concept only, and does not seek to capture all heterogeneity 

in the model area. No calibration was done on the model, and 

existing model input files were combined to create input files 

for much of the model area, as described below. 

The conceptual model for the proof-of-concept model 

is based on interpretations from previous USGS and ADWR 

studies (Hardt and Cattany, 1965; Hanson and others, 1990; 

Hanson and Benedict, 1994; Pool and others, 2001; Mason 

and Bota, 2006). The numerical model uses existing model 

framework input files from the ADWR Tucson AMA model 

(Mason and Bota, 2006), from a portion of the ADWR Santa 

Cruz AMA model (Nelson, 2007), and from an unpublished 

USGS model for the Picacho Basin of the Pinal AMA. To 

develop the model framework for the Maricopa-Stanfield 

Basin of the Pinal AMA, limited available well records and 

hydrogeologic information in Hardt and Cattany (1965) were 

used to estimate breaks between model layers. The numerical 

model for the entire model area uses three layers to simulate 

the aquifer system in the area. From land surface downward, 

model layer 1 represents the Ft. Lowell Formation and recent 

stream alluvium, layer 2 represents the upper and middle 

Tinaja beds, and layer 3 represents the Pantano Formation. 

Layer 1 was modeled as a water table aquifer, layer 2 as 

fully convertible between unconfined and confined aquifer 

conditions, and layer 3 as confined. Areally, the model was 

discretized into 0.386 square mile (1 square km) grid cells, 

requiring 141 vertical columns and 197 horizontal rows to 

cover the model area. 

Boundary conditions for the flow model include 

groundwater underflow into the model area from the south, 

recharge from precipitation estimated by the BCM, and 

internal head-dependent boundaries along streams simulated 

using the Stream Package. Recharge from precipitation in 

the model area was estimated using the 1940–2006 average 

annual in-place recharge estimate from the BCM (see table 

13). Given that most BCM-estimated recharge in the study 

area occurs across areas of mountain bedrock (see fig. 24) and 

that the model area mostly covers the alluvial portions of the 

basins, the BCM-estimated recharge from mountainous areas 

that drain into the model area was applied to the uppermost 

active model cells adjacent to the mountainous areas (fig. 

42). The BCM recharge estimates represent net precipitation that reaches the aquifer, and no direct evapotranspiration 

from groundwater was simulated in the model. Groundwater 

underflow into the model domain occurs from the south in 

two locations: through the Santa Cruz River drainage and 

from Altar Valley into Avra Valley, just west of Tucson (figs. 

40, 42). Underflow of 10,200 and 13,800 acre-ft per year, 
62 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

800

4800

9600

9600

800

800

4800

800

4800

800

800

800

4800

800

800

4800

9600

Santa Cruz River

Rillito Creek

Gila River

EXPLANATION

Depth to bedrock (feet)

0 10 20 5 MILES

0 10 20 5 KILOMETERS

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

Figure 41. Thickness of alluvial sediments in proof-of-concept model area (Richard and others, 2007). Model boundary 

delineated with orange line.
Considerations for Assessment of Groundwater Availability 63

magnitudes taken from the ADWR Tucson and Santa Cruz AMA 

model results (Nelson, 2007; Mason and Bota, 2006), was applied 

to Avra Valley and the Santa Cruz River using the Well Package. 

Four of the model cells where underflow was applied at the Santa 

Cruz River, however, went dry during the simulation, resulting 

in underflow of only 9,200 acre-ft per year instead of 13,800 

acre-ft per year at that location. The Stream Package (STR1; 

Prudic, 1989) was used to simulate interaction of the aquifer with 

the Santa Cruz River, the Gila River, and Rillito Creek (fig. 40). 

Flow between streams and aquifers in the model is computed by 

Darcy’s Law using the difference between the head in the stream 

and the head in the aquifer beneath the streambed (Prudic, 1989). 

Streams may either gain water from or discharge water to the 

aquifer beneath the streambed, depending upon the gradient of the 

head difference. Furthermore, STR1 keeps track of water in the 

stream and allows stream reaches to go dry when all streamflow is 

lost to the aquifer or diverted. Groundwater discharge can result in 

streamflow reaches without flow from upstream reaches. The current channel location of the Santa Cruz River was used from the 

southern end of the model area up through the Tucson AMA. Flow 

in the Santa Cruz River through the Pinal AMA is ephemeral and 

occurs in a mostly undefined channel, although a defined channel 

was present before widespread agricultural development in the 

area. The location of the remaining presently undefined channel of 

the Santa Cruz River through the Pinal AMA was estimated using 

historical topographic maps. A stream network in the model was 

developed using the five segments shown on figure 42. Segments 

are groups of “reaches” of streams in model cells traversed by 

the stream. Streambed top elevation was estimated from a digital 

elevation model at the select control points shown on figure 42. 

Elevation for reaches in between control points were computed 

using linear interpolation of elevation at the two nearest control 

points. Streambed top elevations ranged from 3,215 ft at the upper 

end of segment 1 to 995 ft at the lower end of segment 5. Streambed bottom elevations were assumed to be 3.28 ft below the top 

elevation in each reach. All stream reaches were in connection 

with layer 1 of the model. Streambed conductance for each reach 

varied as a function of the length of the stream reach and assumed 

stream width and streambed vertical hydraulic conductivity. Average streambed conductance values for reaches in segments 1–5 

were 49,300, 46,900, 63,900, 64,900, and 65,800 ft2

/day, respectively. Inflows to Rillito Creek and the Gila River were set at 1 and 

100 cubic feet per second, respectively (fig. 42). With the exception of those described above, all other model boundary conditions 

were simulated as no-flow boundaries.

Existing model parameter input files were rescaled 

and merged to provide input for hydraulic conductivity and 

transmissivity for the ADWR Santa Cruz and Tucson AMAs 

(fig. 43; Nelson, 2007; Mason and Bota, 2006) and for the 

Picacho Basin of the Pinal AMA (unpublished USGS model). 

A different set of uniform hydraulic conductivity and transmissivity values was used for each of the three model layers in the 

Maricopa-Stanfield Basin of the Pinal AMA, based on values 

for the same layer from the deeper portion of the nearby Picacho Basin (fig. 43). Properties for each of these model layers 

in the Maricopa-Stanfield Basin were assigned based on the 

assumptions of homogeneity and isotropy.

Results of Simulation

Simulated hydraulic heads from the uncalibrated, proofof-concept steady-state model were qualitatively compared 

to published predevelopment groundwater-level contours 

(Freethey and Anderson, 1986) and found to be similar in 

magnitude and direction of hydraulic gradients (fig. 44). Use 

of BCM estimates appears to provide sufficient recharge to 

the system. The qualitative satisfactory steady-state solution 

to the simulated system indicates that the narrow constriction 

between multiple, deep alluvial basins does not appear to present numerical challenges. 

Implications for Future Work

The ability of the proof-of-concept groundwater-flow 

model to numerically solve the interconnected aquifer system 

in the model area and the qualitative success of matching predevelopment hydraulic heads indicates that modeling all interconnected basins in the SWAB study area could be feasible. A 

fully calibrated groundwater-flow model of the entire SWAB 

study area capable of transient simulations would allow testing 

of other groundwater budget component estimates developed 

in this study. An integrated, multibasin model could be used 

to provide information on the likely effects of management 

actions (related to groundwater withdrawals or artificial 

recharge, for example) in one basin or management area on 

groundwater levels or streamflow in other connected basins. 

Considerations for Assessment of 

Groundwater Availability

Early studies of groundwater in the area (for example, 

Lee, 1905) were resource assessments intended to provide 

information for development of water supplies in a manner 

that could sustain a growing economy in the region. By the 

latter half of the 20th century, many investigations focused on 

estimating groundwater flow quantities and aquifer properties that could improve understanding of observed aquifer 

response to stress from groundwater withdrawals, and prediction of future responses to continued resource development. 

Water-budget estimates by the SWAB-RASA study (Freethey 

and Anderson, 1986) have been used by a number of subsequent studies and models of individual basins. This study 

updates many of the SWAB-RASA water-budget estimates 

and presents a groundwater model of multiple basins as a 

proof of concept with respect to use of these updated estimates to model groundwater systems and predict responses to 

changing conditions.
64 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

46.4

1.0

0.4

5.0

30.8

6.4

7.5 11.0

19.5

12.3 44.1 8.2

5.4

2.0

1.8

3.7

90.4

15.8

89.5

73.6

251.0

148.4

237.1

14.0

44.2

440.9

127.6

275.4

6,301.7

1,497.1

8,001.9

11,519.4

97.4

85.6

1.6

0.8

1

2

3

4

5

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Santa Cruz River

Rillito Creek

Gila River

EXPLANATION

Locations of model recharge

Locations of model underflow

Stream segment number

44.2

2

Location of control point for determining 

elevation of top of streambed

BCM recharge area (number is recharge 

volume in acre-ft per year)

underflow in: 10,200 

acre-ft per year

underflow in: 13,800 

acre-ft per year

Figure 42. Aggregated areas of Basin Characterization Model (BCM) recharge estimates and model cell locations 

where the recharge was applied, locations of groundwater underflow entering the model area, locations of 

streams and stream segments, and location of control points for determining streambed elevation. Model boundary 

delineated with orange line.
Considerations for Assessment of Groundwater Availability 65 Santa Cruz River

Rillito Creek

Gila River

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Transmissivity

in feet squared per day

>113 to 300

>300 to 1,500

>1,500 to 3,000

>3,000 to 5,000

>5,000

Santa Cruz River

Rillito Creek

Gila River

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Santa Cruz River

Rillito Creek

Gila River

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Hydraulic Conductivity

0.6 to 15

>15 to 30

>30 to 45

>45 to 60

>60 to 75

>75 to 90

>90 to 105

>105 to 120

>120 to 135

>135 to 150

>150

in feet per day

A

Layer 1

B

Layer 2

C

Layer 3

Figure 43. Hydraulic conductivity (A and B) and transmissivity (C) values for the three model layers.
66 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Though many past studies have attempted to estimate 

the amount of recoverable groundwater in storage in basinfill aquifers in the study area, Alley (2007) points out that 

such assessments may not be meaningful in practice with 

respect to water availability. Recovery of the full quantity of 

groundwater in aquifer storage by wells may be infeasible for 

economic and other reasons. Also, deleterious consequences 

of withdrawals, including land subsidence, earth fissures, 

and depletion of surface water, may occur with extraction 

of only a small fraction of the volume of water in storage. 

However, knowledge of water-budget components, including natural and anthropogenic recharge to and discharge from 

groundwater systems, is important in understanding potential 

long-term effects of development of groundwater resources 

in the study area. Some considerations for future work in 

quantifying select water-budget components are given in the 

following section, and considerations for future groundwater 

flow models are given in the section entitled “Simulation of 

Groundwater Flow.”

Estimation of Water-Budget Components

Natural Groundwater Recharge

This component, including mountain-front recharge 

from precipitation and stream seepage, is difficult to estimate in the SWAB study area because it is highly variable 

through space and time. Site-specific studies can be done to 

quantify recharge in select ephemeral channels where most of 

the recharge occurs (Stonestrom and others, 2007), but it is 

difficult to extrapolate meaningful basin-scale budget estimates from site-scale study estimates. Temporal variations in 

recharge occurring on scales ranging from days to multiple 

decades further confound the extrapolation of budget estimates 

from studies spanning a few years. The approach taken by 

this study using the BCM is an improvement over site-scale 

studies in that it is regional in nature and it links climate to 

surface processes (runoff) and subsurface processes (in-place 

recharge). In the study area, however, the pathway for much of 

the recharge to groundwater is from later, downgradient infiltration of runoff. More work is needed to quantify the amount 

of BCM-generated runoff that becomes recharge. Additional 

calibration of BCM-generated runoff using streamflow data 

also would help with future studies.

Anthropogenic Groundwater Recharge

This component includes managed aquifer recharge 

(MAR) for storage in the subsurface, as well as incidental 

recharge from agriculture and other activities. MAR projects 

include generally reasonable estimates of amounts recharged, 

but incidental recharge is more difficult to quantify. Future studies that quantify components such as percolation of excess irrigation water and losses from canals, sewers, and other conveyances will improve future groundwater budget investigations.

Natural Groundwater Discharge to the Surface

This component includes discharge to streams, rivers, 

lakes, springs, wetlands, and plants that use groundwater. 

When the discharge is to surface water features, the possibility exists that some of the discharged water may reenter the 

aquifer in another location, with a net loss by evaporation and 

transpiration while the water was at or near the surface. This 

study used remotely sensed information to estimate actual 

evapotranspiration (AET) from groundwater. A major challenge of using this approach in the study area is that areas of 

groundwater discharge by evapotranspiration often occur in 

narrow bands along watercourses. The width of these bands 

can be smaller than the pixel sizes for remotely sensed data. 

Future improvements in resolution of these data will help in 

quantifying AET in the study area.

Anthropogenic Groundwater Discharge

This component consists mostly of withdrawal of water 

by wells, but in agricultural areas with shallow water tables, 

features such as drainage ditches that intercept shallow 

groundwater have been installed for the purpose of keeping 

the water table below the root zone of crops. In the AMAs 

in the study area, records of withdrawals for nonexempt 

wells (pumping rate of 35 gallons per minute or greater) are 

required. These records have been and will continue to be 

valuable for quantitative groundwater studies. A lack of such 

detailed records outside AMAs complicates groundwater use 

estimates in these areas. Therefore, continued work on water 

use such as has been documented by Tadayon (2005) will be 

important for future assessments.

Groundwater Flow Between Basins

This component, sometimes referred to as “underflow,” 

includes groundwater flow into a basin-fill aquifer from an 

upgradient basin and groundwater flow out to a downgradient 

basin. These components are difficult to estimate with accuracy, but they commonly are thought to be smaller than many 

other components. As indicated in the section “Groundwater 

Underflow,” estimates of this component are sometimes made 

using Darcy’s Law (equation 8). Problems with this approach 

include poorly known terms for use in Darcy’s Law, including the hydraulic gradient, the geometry of the subsurface link 

between basins, and the transmissivity or hydraulic conductivity of that link. In future groundwater models that link multiple 

basins, groundwater flow between the hydraulically connected 

basins will be an internal component that can be computed 

from the model.

Past estimates of many of the components listed here 

have been long-term averages. There is increasing interest in 

the study area to understand how components vary at time 

scales ranging from intraannual to multidecadal. Quantification of variations in components at smaller time scales may 
Considerations for Assessment of Groundwater Availability 67

1600

1300

1500

1400

1200

2500

2400

2600

2700

1800

2300

2900

1900

2800

1700

2000

2200

3000

2100

1400

1500

1300

1500

1400

1200

1400

1300

1200

2600

2500

1500

1100

2300

2700

2400

1800

2800

2200

1000

1900

2100

3000

2000

1700

3200

2000

1200

2800

2600

2100

1900

3000

2300

2200

2400

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Predevelopment groundwater altitude

 in feet above mean sea level

Layer 1 simulated groundwater altitude

 in feet above mean sea level

A

Layer 1

Figure 44. Groundwater levels simulated by the uncalibrated steady-state model for model layers 1 (A), 2 (B), and 3 (C), with 

comparison to published predevelopment groundwater levels from Freethey and Anderson (1986).
68 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2600

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3000

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EXPLANATION

Predevelopment groundwater altitude

 in feet above mean sea level

Layer 2 simulated groundwater altitude

 in feet above mean sea level

B

Layer 2

112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

Figure 44.—Continued.
Considerations for Assessment of Groundwater Availability 69

1500

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112°0' 111°30' 111°0'

33°0'

32°30'

32°0'

31°30'

0 10 20 5 MILES

0 10 20 5 KILOMETERS

EXPLANATION

Predevelopment groundwater altitude

 in feet above mean sea level

Layer 3 simulated groundwater altitude

 in feet above mean sea level

C

Layer 3

Figure 44.—Continued.
70 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

be important for certain studies, such as in understanding the 

functioning of groundwater-dependent ecosystems.

Simulation of Groundwater Flow

Groundwater models have been developed for the AMAs 

as well as for many of the basin-fill aquifers outside of the 

AMAs. The earliest models were made using electrical analog 

methods. Most subsequent models have used finite-difference 

computer model codes, including various versions of MODFLOW (for example, Corkhill and Hill, 1990; Corell, 1992; 

Mason and Bota, 2006; Pool and Dickinson, 2006; Erwin, 

2007; Nelson, 2007). With increasing computer capabilities, 

horizontal discretization has been decreasing from cell sizes of 

about 1 square mile in early models to less than one quarter of 

that size in some more recent models. At least three layers are 

commonly used to represent different hydrogeologic units in 

the basin fill.

Limited testing by this project indicates that linked-basin 

models are feasible. Such an approach may be beneficial in 

the future to understand how development in one basin may 

affect groundwater resources in adjacent basins. Few past 

transient models have included calculations of release of water 

from storage attributed to inelastic compaction of the aquifer 

system (permanent land subsidence), including groundwater 

models of the Tucson Basin (Hanson and Benedict, 1994) and 

Avra Valley (Hanson and others, 1990). The Subsidence and 

Aquifer-System Compaction Package (SUB-WT; Leake and 

Galloway, 2007) for use in simulating water-table aquifers with 

MODFLOW is particularly applicable for groundwater simulations of aquifers in the study area. That package can be used in 

future MODFLOW-based models in which there is a need to 

compute vertical compaction and resulting land subsidence. 

Future models would benefit from the inclusion of 

detailed climate data to better understand how climate variability and climate change may affect groundwater resources. 

Such models could be used to evaluate both direct and indirect 

effects of a different climate. A direct effect might be the reduction of recharge to an aquifer system and an indirect effect 

might be increased groundwater withdrawals because of a 

climate-related shortage of surface-water supplies. These models will likely be less deterministic in nature and take a more 

stochastic approach, investigating a range of potential future 

groundwater withdrawal, recharge, and streamflow scenarios.

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Appendix 1. Supplemental Information—Additional References Organized by 

Basin 

This list of supplemental references is published only electronically, in the online version of this report at http://pubs.usgs.

gov/sir/2011/5071/.
Appendix 1. Supplemental Information—Additional References Organized by Basin 79

Tables 1–29
78 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

1940–49 1950–59 1960–69 1970–79

Basin name (inches) (acre-ft) (inches) (acre-ft) (inches) (acre-ft) (inches) (acre-ft)

AGUA FRIA 15.8 1,064,000 15.5 1,045,000 17.8 1,200,000 17.4 1,170,000 

ARAVAIPA CANYON 16.3 448,000 14.9 412,000 17.3 477,000 17.9 493,000 

BIG SANDY 13.2 1,399,000 12.8 1,354,000 13.7 1,452,000 13.8 1,469,000 

BILL WILLIAMS 12.0 2,139,000 11.4 2,035,000 12.3 2,198,000 12.8 2,287,000 

BONITA CREEK 15.1 368,000 14.7 357,000 16.1 392,000 15.5 377,000 

BUTLER VALLEY 8.0 122,000 6.9 106,000 7.6 116,000 8.4 128,000 

CIENEGA CREEK 17.7 579,000 17.7 581,000 20.0 657,000 19.2 630,000 

DETRITAL VALLEY 7.3 346,000 6.4 304,000 6.7 320,000 8.1 387,000 

DONNELLY WASH 14.7 229,000 13.6 212,000 14.9 233,000 15.6 243,000 

DOUGLAS 13.4 282,000 12.7 267,000 14.1 296,000 14.0 295,000 

DOUGLAS INA 11.8 350,000 10.9 323,000 12.4 367,000 11.9 354,000 

DRIPPING SPRINGS WASH 16.5 333,000 15.7 316,000 17.7 357,000 18.0 363,000 

DUNCAN VALLEY 11.9 348,000 10.0 293,000 12.6 370,000 12.2 359,000 

GILA BEND 7.7 529,000 5.9 406,000 7.4 507,000 7.3 499,000 

HARQUAHALA INA 6.5 266,000 5.8 238,000 6.5 266,000 6.9 283,000 

HUALAPAI VALLEY 9.3 600,000 8.5 553,000 9.1 588,000 9.7 627,000 

LAKE HAVASU 5.4 73,000 4.7 64,000 4.7 63,000 5.9 80,000 

LAKE MOHAVE 5.8 302,000 5.1 265,000 5.1 269,000 6.3 330,000 

LOWER GILA 5.9 2,300,000 4.6 1,787,000 5.5 2,152,000 6.0 2,348,000 

LOWER SAN PEDRO 15.1 1,305,000 14.3 1,235,000 16.1 1,397,000 16.8 1,457,000 

MCMULLEN VALLEY 8.7 300,000 7.6 262,000 8.0 277,000 8.6 297,000 

MEADVIEW 8.9 90,000 7.8 79,000 8.8 89,000 9.9 100,000 

MORENCI 17.6 1,498,000 16.2 1,385,000 18.4 1,569,000 17.3 1,479,000 

PARKER 4.6 546,000 4.0 472,000 4.3 517,000 5.0 591,000 

PEACH SPRINGS 11.7 883,000 11.2 839,000 12.4 933,000 12.9 972,000 

PHOENIX AMA 8.9 2,565,000 8.5 2,452,000 9.4 2,713,000 9.4 2,709,000 

PINAL AMA 8.7 1,909,000 8.6 1,869,000 10.1 2,213,000 9.6 2,104,000 

PRESCOTT AMA 14.7 378,000 15.4 394,000 16.7 427,000 16.0 410,000 

RANEGRAS PLAIN 5.9 287,000 5.3 259,000 5.9 285,000 6.6 321,000 

SACRAMENTO VALLEY 8.7 740,000 8.3 704,000 8.6 729,000 9.4 799,000 

SAFFORD 13.3 3,372,000 11.9 3,008,000 14.1 3,582,000 13.7 3,460,000 

SALT RIVER 20.3 5,659,000 19.1 5,322,000 21.2 5,910,000 21.9 6,113,000 

SAN BERNARDINO VALLEY 14.3 296,000 11.9 245,000 15.0 309,000 14.2 294,000 

SAN RAFAEL 17.8 217,000 17.9 218,000 19.2 234,000 18.6 227,000 

SAN SIMON WASH 10.3 1,251,000 9.6 1,174,000 12.4 1,511,000 11.0 1,346,000 

SANTA CRUZ AMA 15.7 598,000 16.1 614,000 18.4 705,000 17.6 673,000 

TIGER WASH 8.5 34,000 7.3 29,000 7.8 31,000 8.3 33,000 

TONTO CREEK 21.1 1,074,000 20.8 1,059,000 21.9 1,115,000 22.8 1,160,000 

TUCSON AMA 13.1 2,709,000 13.1 2,697,000 15.0 3,093,000 14.7 3,039,000 

UPPER HASSAYAMPA 14.7 618,000 15.1 635,000 15.9 668,000 16.2 678,000 

UPPER SAN PEDRO 13.9 1,343,000 13.6 1,319,000 15.3 1,486,000 15.3 1,479,000 

VERDE RIVER 17.8 5,376,000 17.1 5,158,000 18.2 5,510,000 18.0 5,431,000 

WESTERN MEXICAN DRAINAGE 6.9 225,000 6.0 195,000 7.8 255,000 6.9 224,000 

WILLCOX 14.2 1,443,000 12.8 1,309,000 14.8 1,507,000 14.3 1,455,000 

YUMA 3.3 139,000 2.5 105,000 3.1 130,000 3.9 166,000 

Table 1. Average annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation estimates for the 

Southwest Alluvial Basin study area in Arizona for time periods indicated.
Tables 1–29 79

1980–89 1990–99 2000–2006 1940–2006

Basin name (inches) (acre-ft) (inches) (acre-ft) (inches) (acre-ft) (inches) (acre-ft)

AGUA FRIA 19.6 1,321,000 19.9 1,342,000 14.8 999,000 17.4 1,170,000 

ARAVAIPA CANYON 19.8 546,000 20.7 573,000 14.8 408,000 17.5 483,000 

BIG SANDY 14.6 1,546,000 14.5 1,542,000 11.5 1,218,000 13.5 1,435,000 

BILL WILLIAMS 14.4 2,576,000 14.3 2,562,000 11.7 2,083,000 12.7 2,277,000 

BONITA CREEK 19.0 463,000 17.8 435,000 15.1 368,000 16.2 395,000 

BUTLER VALLEY 9.9 152,000 9.5 145,000 8.6 132,000 8.4 129,000 

CIENEGA CREEK 22.5 738,000 21.1 693,000 17.2 563,000 19.4 638,000 

DETRITAL VALLEY 8.4 399,000 8.5 405,000 6.9 330,000 7.5 357,000 

DONNELLY WASH 16.9 265,000 17.4 272,000 12.0 188,000 15.1 237,000 

DOUGLAS 16.2 340,000 14.8 311,000 12.4 261,000 14.0 295,000 

DOUGLAS INA 14.6 431,000 12.8 378,000 11.1 328,000 12.3 363,000 

DRIPPING SPRINGS WASH 19.4 391,000 20.0 404,000 13.4 271,000 17.4 351,000 

DUNCAN VALLEY 15.2 446,000 14.4 423,000 12.0 351,000 12.6 371,000 

GILA BEND 8.4 576,000 8.4 574,000 6.5 447,000 7.4 508,000 

HARQUAHALA INA 7.6 309,000 7.8 319,000 7.2 294,000 6.9 282,000 

HUALAPAI VALLEY 10.0 649,000 10.2 657,000 8.4 541,000 9.4 605,000 

LAKE HAVASU 7.0 94,000 7.3 98,000 5.9 79,000 5.8 79,000 

LAKE MOHAVE 7.1 371,000 7.3 383,000 6.0 313,000 6.1 319,000 

LOWER GILA 6.0 2,355,000 5.9 2,285,000 5.1 1,986,000 5.6 2,182,000 

LOWER SAN PEDRO 18.9 1,638,000 19.0 1,642,000 13.3 1,153,000 16.3 1,415,000 

MCMULLEN VALLEY 10.7 370,000 9.8 338,000 9.1 313,000 8.9 308,000 

MEADVIEW 9.7 99,000 10.0 101,000 8.3 85,000 9.1 92,000 

MORENCI 21.0 1,791,000 19.9 1,696,000 17.8 1,518,000 18.3 1,564,000 

PARKER 5.9 706,000 5.6 672,000 4.6 544,000 4.9 580,000 

PEACH SPRINGS 12.8 966,000 12.4 929,000 10.6 799,000 12.1 908,000 

PHOENIX AMA 10.9 3,146,000 11.7 3,374,000 8.8 2,524,000 9.7 2,795,000 

PINAL AMA 10.8 2,352,000 10.9 2,382,000 8.7 1,896,000 9.7 2,113,000 

PRESCOTT AMA 18.4 471,000 17.9 458,000 14.3 367,000 16.3 417,000 

RANEGRAS PLAIN 7.4 360,000 6.9 336,000 6.0 291,000 6.3 306,000 

SACRAMENTO VALLEY 10.4 877,000 10.5 888,000 8.3 700,000 9.2 780,000 

SAFFORD 16.3 4,120,000 16.0 4,041,000 12.3 3,113,000 14.0 3,547,000 

SALT RIVER 25.0 6,978,000 23.0 6,425,000 18.7 5,227,000 21.4 5,980,000 

SAN BERNARDINO VALLEY 15.6 322,000 13.7 284,000 11.6 240,000 13.9 286,000 

SAN RAFAEL 21.8 267,000 20.6 252,000 17.8 217,000 19.2 234,000 

SAN SIMON WASH 12.0 1,461,000 11.8 1,438,000 10.5 1,274,000 11.1 1,354,000 

SANTA CRUZ AMA 20.8 793,000 20.3 775,000 16.2 618,000 17.9 685,000 

TIGER WASH 10.3 41,000 9.6 38,000 9.2 36,000 8.7 34,000 

TONTO CREEK 24.6 1,253,000 23.7 1,207,000 18.2 928,000 22.0 1,122,000 

TUCSON AMA 16.9 3,490,000 16.7 3,445,000 13.0 2,693,000 14.7 3,038,000 

UPPER HASSAYAMPA 18.1 758,000 17.8 748,000 13.7 576,000 16.0 673,000 

UPPER SAN PEDRO 17.4 1,689,000 16.1 1,563,000 13.5 1,311,000 15.1 1,462,000 

VERDE RIVER 20.5 6,181,000 20.3 6,145,000 16.5 4,973,000 18.4 5,565,000 

WESTERN MEXICAN DRAINAGE 7.7 250,000 7.9 258,000 6.2 202,000 7.1 231,000 

WILLCOX 17.1 1,749,000 16.8 1,712,000 13.4 1,371,000 14.8 1,513,000 

YUMA 3.5 146,000 3.5 149,000 2.9 125,000 3.3 138,000 

Table 1. Average annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation estimates for the 

Southwest Alluvial Basin study area in Arizona for time periods indicated.—Continued
80 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Basin name Maximum annual precipitation (inches) Year of maximum Minimum annual precipitation (inches) Year of minimum

AGUA FRIA 31.5 1983 7.3 2002

ARAVAIPA CANYON 31.7 1941 9.6 1956

BIG SANDY 24.5 1941 5.0 1996

BILL WILLIAMS 23.8 1941 3.9 1956

BONITA CREEK 26.6 1941 10.0 1947

BUTLER VALLEY 19.0 1941 1.6 1956

CIENEGA CREEK 31.5 1983 12.1 1956

DETRITAL VALLEY 15.7 2005 1.8 2002

DONNELLY WASH 30.1 1941 6.4 2002

DOUGLAS 20.2 1983 7.4 1956

DOUGLAS INA 18.1 1985 5.5 1956

DRIPPING SPRINGS WASH 33.7 1941 7.4 2002

DUNCAN VALLEY 21.3 1941 6.1 1956

GILA BEND 16.5 1941 2.2 1956

HARQUAHALA INA 16.1 1941 0.7 1956

HUALAPAI VALLEY 17.1 2005 2.9 1996

LAKE HAVASU 15.2 2005 0.5 1956

LAKE MOHAVE 15.0 2005 1.0 1956

LOWER GILA 13.2 1941 1.4 1956

LOWER SAN PEDRO 28.3 1941 8.4 2002

MCMULLEN VALLEY 20.7 1941 2.1 1956

MEADVIEW 17.6 2005 2.5 2002

MORENCI 29.5 1941 11.4 1951

PARKER 12.4 2005 0.7 1956

PEACH SPRINGS 20.9 2005 4.1 1996

PHOENIX AMA 21.3 1941 3.6 1956

PINAL AMA 18.1 1941 5.0 2002

PRESCOTT AMA 28.4 1983 7.9 2002

RANEGRAS PLAIN 14.7 1941 1.2 1956

SACRAMENTO VALLEY 18.1 2005 2.3 1956

SAFFORD 23.8 1941 7.5 1956

SALT RIVER 35.7 1941 12.0 2002

SAN BERNARDINO VALLEY 20.2 1941 5.6 1956

SAN RAFAEL 31.0 1983 12.9 1956

SAN SIMON WASH 19.1 1984 4.9 2002

SANTA CRUZ AMA 29.2 1983 10.5 1956

TIGER WASH 20.6 1941 1.7 1956

TONTO CREEK 37.2 1941 8.5 2002

TUCSON AMA 24.8 1984 8.0 1956

UPPER HASSAYAMPA 28.1 1983 6.1 1956

UPPER SAN PEDRO 23.4 1966 9.1 1947

VERDE RIVER 32.2 1941 8.7 2002

WESTERN MEXICAN DRAINAGE 13.8 1979 1.7 2002

WILLCOX 22.6 1966 7.6 1956

YUMA 8.2 1941 0.3 1956

Table 2. Maximum and minimum annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation by basin between 1940 and 2006.
Tables 1–29 81

Table 3. Characteristics of runoff regions in the Southwest Alluvial Basins of Arizona.

Runoff region1

Area, 

in square miles

Mean annual 

precipitation3

Mean elevation,

in feet

Total 

area

Mountain 

area2

Total 

area

Mountain 

area2

Total 

area Mountain area2

Western Upland 8,797 6,557 14 15 4,118 4,331 

Central Upland and Northeastern 

Gila River 22,534 15,853 17 18 4,497 4,824 

Southeastern Gila River 10,460 4,204 15 17 4,525 4,932 

Western Lowlands 31,792 10,112 8 8 1,921 2,413 

1

Runoff regions shown in figure 19.

2

Mountain area in a basin is the higher elevation area composed of bedrock.

3

Mean annual precipitation is from 1940–2006 Parameter-elevation Regressions on Independent Slopes Model (PRISM) data.
82 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Gaging 

station 

number

Gaging station name Period of record Gage 

datum

Drainage 

area

Mean annual 

precipitation1

Mean 

basin 

elevation

Observed 

mean annual streamflow

(ft) (mi2

) (in) (ft) (ft3/s)

1) WESTERN UPLAND RUNOFF REGION

09424200 Cottonwood Wash trib nr Kingman 1964-1978 4,544 139 13.1 5,361 4.7 

09512500 Agua Fria River nr Mayer 1940-2007 3,435 585 14.5 4,938 22.7 

09512600 Turkey Creek nr Cleator 1979-1990 3,140 89 16.5 5,256 19.0 

09515500 Hassayampa River nr Wickenburg 1946-1982 2,238 416 16.1 4,534 24.3 

2) CENTRAL UPLAND AND NORTHEASTERN GILA RIVER RUNOFF REGION

Verde River Basin Sub-region

09502800 Williamson Valley Wash nr Paulden2 1965-2007 4,455 255 12.3 5,135 15.7 

09503000 Granite Creek nr Prescott2 1932-2007 5,203 39 16.5 5,906 6.5 

09504500 Oak Creek nr Cornville 1940-2007 3,471 354 20.2 6,112 86.6 

09505200 Wet Beaver Creek nr Rimrock 1962-2007 4,019 110 20.2 6,555 31.9 

09505250 Red Tank Draw nr Rimrock 1958-1978 3,921 51 19.7 6,083 7.2 

09505300 Rattlesnake Canyon nr Rimrock 1958-1980 4,869 25 21.0 6,453 8.9 

09505350 Dry Beaver Creek nr Rimrock 1961-2007 3,694 144 20.3 6,165 42.4 

09505800 West Clear Creek nr Camp Verde 1965-2007 3,629 241 20.2 6,627 61.1 

09507700 Webber Creek nr Pine 1960-1974 5,531 5 25.6 7,008 2.5 

09507980 East Verde River nr Childs 1962-2007 2,500 327 20.2 5,246 64.1 

09508300 Wet Bottom Creek nr Childs 1968-2007 2,320 36 17.9 4,918 14.1 

09510080 West Fork Sycamore Creek nr Sunflower 1961-1974 3,999 10 21.9 5,322 2.0 

09510100 East Fork Sycamore Creek nr Sunflower 1961-1986 4,140 5 20.5 5,203 1.0 

Salt River Basin Sub-region

09489070 North Fork of East Fork Black River nr Alpine 1965-1978 8,652 39 21.5 9,045 12.7 

09489200 Pacheta Creek at Maverick 1958-1980 7,851 17 24.1 8,596 8.9 

09489500 Black River blw pumping nr Point of Pines 1953-2007 5,725 556 20.6 8,058 202.6 

09489700 Big Bonito Creek nr Fort Apache 1958-1981 5,909 114 24.4 8,074 67.2 

09490800 North Fork White River nr Greer 1965-1978 8,373 41 26.5 9,521 24.6 

09492400 East Fork White River nr Fort Apache 1958-2007 6,050 39 26.3 8,189 34.3 

09494000 White River nr Fort Apache 1958-2007 4,367 630 22.0 7,247 164.1 

09496000 Corduroy Creek nr Show Low 1952-2005 5,000 206 16.6 6,371 23.6 

09496500 Carrizo Creek nr Show Low 1952-2007 4,751 441 16.8 6,325 46.1 

09497800 Cibecue Creek nr Chrysotile 1960-2007 3,199 289 17.2 5,738 43.9 

09497900 Cherry Creek nr Young 1963-1977 4,951 62 21.4 5,991 10.1 

09497980 Cherry Creek nr Globe 1965-2007 3,199 200 19.4 5,538 32.0 

09498870 Rye Creek nr Gisela 1966-1985 2,730 122 16.7 4,281 26.6 

09499000 Tonto Creek abv Gun Creek nr Roosevelt 1941-2007 2,523 672 19.1 5,082 149.6 

Northeastern Gila River Basin Sub-region

09430600 Mogollon Creek nr Cliff, NM 1967-2007 5,440 74 21.8 7,772 30.4 

09442680 San Francisco River nr Reserve, NM 1959-2007 5,279 332 15.6 7,799 25.4 

09444200 Blue River nr Clifton 1968-2007 4,160 505 16.8 6,847 66.0 

09446000 Willow Creek nr Morenci 1945-1967 4,970 155 15.8 6,237 13.7 

09447800 Bonita Creek nr Morenci 1981-2007 3,501 302 13.7 5,246 11.6 

09458200 Deadman Creek nr Safford 1967-1993 4,951 5 15.8 7,372 1.8 

09460150 Frye Creek nr Thatcher 1989-2007 5,581 4 18.7 8,150 1.8 

09473000 Aravaipa Creek nr Mammoth2 1931-2007 2,346 537 14.3 4,570 34.8 

09484000 Sabino Creek nr Tucson2 1932-2007 2,720 35 22.4 6,070 13.4 

09484200 Bear Creek nr Tucson 1959-1974 2,671 17 20.6 6,070 4.7 

09484500 Tanque Verde Creek at Tucson2 1941-2007 2,470 219 16.1 4,377 23.5 

09485000 Rincon Creek nr Tucson 1987-2007 3,120 44 19.7 5,105 6.0 

3) SOUTHEASTERN GILA RIVER RUNOFF REGION

09470800 Garden Canyon nr Fort Huachuca2 1960-2007 5,400 8 16.0 6,237 1.3 

09480000 Santa Cruz River nr Lochiel 1949-2007 4,619 82 15.7 5,089 3.6 

09480500 Santa Cruz River nr Nogales 1931-2007 3,704 511 15.8 4,879 25.4 

09481500 Sonoita Creek nr Patagonia 1930-1972 3,819 207 16.9 4,925 8.1 

1

Mean annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation for 1940–2006.

2

Period of record has some missing years.

Table 4. Streamflow-gaging stations used for runoff regression analysis. 

[See figure 19 for streamflow-gaging station locations and figure 20 for sub-region locations.]
Tables 1–29 83

 

Runoff region1 Basin name2

Area, 

in square miles

Mean annual 

precipitation4

in inches

Mean basin elevation, 

in feet

Total 

area

Mountain 

area3

Total 

area

Mountain 

area3

Total 

area

Mountain 

area3

Western

Upland

Agua Fria 1,263 1,180 17.1 17.3 4,028 4,057

Big Sandy 1,988 1,346 13.3 14.2 4,590 4,947

Bill Williams 3,350 2,432 12.5 13.3 3,238 3,531

Peach Springs 1,409 1,120 11.9 12.0 4,974 4,965

Upper Hassayampa 787 478 15.8 17.2 3,760 4,155

Central Upland and Northeast 

Gila River

Prescott AMA 480 220 16.1 17.9 5,244 5,605

Verde River 5,662 4,564 18.2 19.3 5,272 5,512

Salt River 5,232 4,784 21.2 21.8 5,703 5,922

Tonto Creek 955 774 21.8 22.9 4,745 5,136

Aravaipa Canyon 517 341 17.2 17.9 4,603 4,770

Bonita Creek 457 257 16.1 16.3 5,237 5,431

Donnelly Wash 293 216 14.9 14.8 2,812 2,786

Dripping Springs Wash 378 312 17.1 17.2 3,561 3,668

Lower San Pedro 1,624 901 16.1 17.7 3,667 4,098

Morenci 1,599 1,283 18.2 18.5 6,136 6,264

Safford north 2,980 1,398 15.1 18.1 3,995 4,792

Tucson AMA north 2,356 804 14.0 17.9 2,989 3,909

Southeastern

Gila River

Cienega Creek 615 316 19.2 20.1 4,801 4,972

Douglas 394 275 13.9 14.5 4,866 5,021

Douglas INA 555 10 12.2 13.0 4,210 4,369

Duncan Valley 550 245 12.5 13.6 4,336 4,774

Safford south 1,772 660 13.5 16.5 4,397 5,242

San Bernardino Valley 387 308 13.8 14.1 4,542 4,630

San Rafael 229 88 19.0 20.1 5,368 5,789

Santa Cruz AMA 716 394 17.7 19.1 4,008 4,316

Tucson AMA south 1,515 692 17.4 19.6 3,666 4,120

Upper San Pedro 1,816 567 15.0 17.5 4,642 5,249

Willcox 1,911 648 14.7 17.9 4,936 5,770

Western Lowland

Detrital Valley 892 321 7.4 8.4 2,820 3,417

Hualapai Valley 1,213 484 9.2 9.8 3,490 4,006

Lake Havasu 252 161 5.7 6.2 1,348 1,627

Lake Mohave 980 475 6.0 7.0 1,689 2,363

Meadview 190 60 9.0 10.5 3,598 4,856

Sacramento Valley 1,587 670 9.0 10.3 2,807 3,527

Butler Valley 288 87 8.2 9.6 2,011 2,553

Gila Bend 1,284 518 7.3 8.0 1,289 1,734

Harquahala INA 766 215 6.8 7.5 1,542 1,979

Lower Gila 7,309 2,392 5.5 6.1 1,029 1,378

McMullen Valley 649 181 8.7 9.8 2,344 2,765

Parker 2,229 722 4.8 5.1 1,017 1,349

Ranegras Plain 912 325 6.2 6.6 1,509 1,834

San Simon Wash 2,284 572 11.0 12.1 2,330 2,774

Tiger Wash 74 39 8.6 8.7 2,413 2,596

Western Mexican Drainage 610 276 7.0 6.9 1,262 1,388

Yuma 792 92 3.3 3.8 421 977

Phoenix AMA 5,386 1,597 9.6 12.0 1,693 2,348

Pinal AMA 4,096 925 9.6 10.7 1,893 2,373

1

Runoff region is shown in figure 19.

2

Basins are shown in figure 2.

3

Mountain area in a basin is the higher elevation area composed of bedrock.

4

Mean annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation for 1940–2006.

Table 5. Characteristics of the Southwest Alluvial Basins of Arizona.

[Runoff regression analysis performed on basins in all runoff regions except Western Lowland, where no acceptable gaged 

streams were located.]
84 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Q1 = a b c d e f

Coefficient of 

determination 

(R2

)

s2

(log 

units)

s 

(average 

percent)

A -2.026 0.710 0.68 0.319 80

A + P -11.269 0.869 3.318 0.88 0.194 46

A + P + E -12.782 0.880 2.704 0.957 0.90 0.183 43

A + P + E + 

R1 + R2 -11.508 0.871 2.529 0.727 -0.133 -0.305 0.92 0.167 39

Degrees of freedom Final runoff regression equation1

42 Log Q = -11.508+0.871(logA)+2.529(logP)+0.727(logE)-0.133(R1)-0.305(R2)

1

Form of regression equation is Log Q = a + b×(logA) + c×(logP) + d×(logE) + e×(R1) + f×(R2), where

Q = mean annual flow (m3/s), A = drainage area (km2), P = mean annual precipitation (mm), E = mean 

basin elevation (m), R1 and R2 represent runoff region. 

2

s is the standard error of estimate. 

[Streamflow and basin characteristics at 47 streamflow gages used in the regression analysis.]

Table 6. Improvement of fit of multivariate regression equation by additional explanatory variables and final form of equation.
Tables 1–29 85

Table 7. Comparison of streamflow predictions by regression equation to observed data.

Gaging station name

Mean annual flow

(log ft3/s)

Observed Regression 

estimate

Residual (observed value 

– estimated value)

WESTERN UPLAND RUNOFF REGION

Cottonwood Wash trib nr Kingman 0.67 0.60 0.07

Agua Fria River nr Mayer 1.36 1.48 -0.12

Turkey Creek nr Cleator 1.28 0.92 0.36

Hassayampa River nr Wickenburg 1.39 1.44 -0.05

CENTRAL UPLAND AND NORTHEASTERN GILA RIVER RUNOFF REGION

Verde River Basin Sub-region

Williamson Valley Wash nr Paulden 1.20 1.13 0.07

Granite Creek nr Prescott 0.81 0.78 0.03

Oak Creek nr Cornville 1.94 1.85 0.09

Wet Beaver Creek nr Rimrock 1.50 1.43 0.07

Red Tank Draw nr Rimrock 0.86 1.09 -0.24

Rattlesnake Canyon nr Rimrock 0.95 0.92 0.03

Dry Beaver Creek nr Rimrock 1.63 1.52 0.11

West Clear Creek nr Camp Verde 1.79 1.73 0.05

Webber Creek nr Pine 0.40 0.53 -0.13

East Verde River nr Childs 1.81 1.77 0.03

Wet Bottom Creek nr Childs 1.15 0.79 0.36

West Fork Sycamore Creek nr Sunflower 0.31 0.54 -0.23

East Fork Sycamore Creek nr Sunflower -0.02 0.17 -0.19

Salt River Basin Sub-region

NF of East Fork Black River nr Alpine 1.10 1.21 -0.11

Pacheta Creek at Maverick 0.95 0.99 -0.04

Black River blw pumping nr Point of Pines 2.31 2.13 0.18

Big Bonito Creek nr Fort Apache 1.83 1.72 0.11

North Fork White River nr Greer 1.39 1.47 -0.08

East Fork White River nr Fort Apache 1.53 1.40 0.14

White River nr Fort Apache 2.22 2.22 0.00

Corduroy Creek nr Show Low 1.37 1.47 -0.07

Carrizo Creek nr Show Low 1.66 1.74 -0.08

Cibecue Creek nr Chrysotile 1.64 1.58 0.07

Cherry Creek nr Young 1.01 1.25 -0.24

Cherry Creek nr Globe 1.51 1.56 -0.06

Rye Creek nr Gisela 1.42 1.13 0.30

Tonto Creek abv Gun Creek nr Roosevelt 2.18 1.97 0.20
86 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Northeastern Gila River Basin Sub-region

Mogollon Creek nr Cliff, NM 1.48 1.42 0.07

San Francisco River nr Reserve, NM 1.40 1.62 -0.22

Blue River nr Clifton 1.82 1.82 0.00

Willow Creek nr Morenci 1.14 1.28 -0.14

Bonita Creek nr Morenci 1.07 1.32 -0.25

Deadman Creek nr Safford 0.26 0.00 0.27

Frye Creek nr Thatcher 0.26 0.16 0.09

Aravaipa Creek nr Mammoth 1.54 1.54 0.00

Sabino Creek nr Tucson 1.13 1.09 0.04

Bear Creek nr Tucson 0.67 0.72 -0.05

Tanque Verde Creek at Tucson 1.37 1.32 0.05

Rincon Creek nr Tucson 0.78 0.98 -0.20

SOUTHEASTERN GILA RIVER RUNOFF REGION

Garden Canyon nr Fort Huachuca 0.10 -0.12 0.22

Santa Cruz River nr Lochiel 0.56 0.66 -0.10

Santa Cruz River nr Nogales 1.41 1.34 0.06

Sonoita Creek nr Patagonia 0.91 1.08 -0.17

Gaging station name

Mean annual flow

(log ft3/s)

Observed Regression 

estimate

Residual (observed value – 

estimated value)

Table 8. Comparison of streamflow predictions by regression equation for runoff regions. 

[See figures 19 and 20 for locations of runoff regions and sub-regions.]

Runoff region

Number of 

streamflow 

gages in region

Mean 

residual

(log ft3

/s)

Root mean 

square error

(log ft3/s)

WESTERN UPLAND 4 0.07 0.195

CENTRAL UPLAND AND 

NORTHEASTERN GILA 

RIVER RUNOFF REGION 

Verde River Basin Sub-region 13 0.00 0.158

Salt River Basin Sub-region 14 0.02 0.144

Northeastern Gila River Basin 

Sub-region 12 -0.03 0.148

SOUTHEASTERN GILA RIVER 4 0.00 0.151

all runoff regions 47 0.01 0.155

Table 7. Comparison of streamflow predictions by regression equation to observed data.—Continued
Tables 1–29 87

 

Runoff 

region1

Gaging 

station 

number

Gaging station name

Mean annual flow, 

in cubic feet per second

Residual, 

in percent of

 observed value

ObservedRegression 

estimated2

BCM 

estimated

Regression BCM

Western

upland

09424200 Cottonwood Wash trib nr Kingman 4.67 3.88 1.77 17 62

09512500 Agua Fria River nr Mayer 22.71 30.02 18.43 -32 19

09512600 Turkey Creek nr Cleator 19.06 8.48 11.76 56 38

09515500 Hassayampa River nr Wickenburg 24.35 27.55 27.02 -13 -11

Central 

Upland and 

Northeast 

Gila River

09502800 Williamson Valley Wash nr Paulden 15.75 13.42 3.71 15 76

09503000 Granite Creek nr Prescott 6.45 6.00 0.68 7 89

09504500 Oak Creek nr Cornville 86.67 70.98 111.01 18 -28

09505200 Wet Beaver Creek nr Rimrock 31.91 26.84 24.21 16 24

09505250 Red Tank Draw nr Rimrock 7.24 12.36 8.98 -71 -24

09505300 Rattlesnake Canyon nr Rimrock 8.95 8.12 6.85 9 23

09505350 Dry Beaver Creek nr Rimrock 42.44 33.20 40.81 22 4

09505800 West Clear Creek nr Camp Verde 61.12 54.03 51.53 12 16

09507700 Webber Creek nr Pine 2.50 3.53 1.69 -41 32

09507980 East Verde River nr Childs 64.17 59.33 19.79 8 69

09508300 Wet Bottom Creek nr Childs 14.11 6.00 4.86 57 66

09510080 West Fork Sycamore Creek nr Sunflower 2.04 3.53 2.86 -73 -40

09510100 East Fork Sycamore Creek nr Sunflower 0.96 1.41 0.93 -47 3

09489070 NF of East Fork Black River nr Alpine 12.72 16.24 28.34 -28 -123

09489200 Pacheta Creek at Maverick 8.88 9.89 5.05 -11 43

09489500 Black River blw pumping nr Point of Pines 202.79 134.20 225.55 34 -11

09489700 Big Bonito Creek nr Fort Apache 67.29 52.27 39.89 22 41

09490800 North Fork White River nr Greer 24.65 29.31 30.68 -19 -24

09492400 East Fork White River nr Fort Apache 34.27 25.07 20.67 27 40

09494000 White River nr Fort Apache 164.22 164.92 199.97 -0 -22

09496000 Corduroy Creek nr Show Low 23.58 27.90 28.98 -18 -23

09496500 Carrizo Creek nr Show Low 46.13 55.09 18.49 -19 60

09497800 Cibecue Creek nr Chrysotile 43.93 37.43 8.73 15 80

09497900 Cherry Creek nr Young 10.14 17.66 8.07 -74 20

09497980 Cherry Creek nr Globe 32.02 36.37 14.51 -14 55

09498870 Rye Creek nr Gisela 26.57 13.42 67.82 49 -155

09499000 Tonto Creek abv Gun Creek nr Roosevelt 149.72 94.29 56.46 37 62

09430600 Mogollon Creek nr Cliff, NM 30.39 26.13 (

3

) 14 (

3

)

09442680 San Francisco River nr Reserve, NM 25.37 42.02 (

3

) -66 (

3

)

09444200 Blue River nr Clifton 66.00 66.39 52.99 -1 20

09446000 Willow Creek nr Morenci 13.72 19.07 5.60 -39 59

09447800 Bonita Creek nr Morenci 11.63 20.84 2.81 -79 76

09458200 Deadman Creek nr Safford 1.83 1.06 0.27 42 85

09460150 Frye Creek nr Thatcher 1.81 1.41 0.61 22 66

09473000 Aravaipa Creek nr Mammoth 34.84 34.61 9.21 1 74

Table 9. Observed and estimated mean annual flow at streamflow-gaging stations in the Southwest Alluvial Basins of Arizona. 

 [BCM is Basin Characterization Model.]
88 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Runoff 

region1

Gaging 

station 

number

Gaging station name

Mean annual flow, 

in cubic feet per second

Residual, 

in percent of

 observed value

ObservedRegression 

estimated2

BCM 

estimated

Regression BCM

Table 9. Observed and estimated mean annual flow at streamflow-gaging stations in the Southwest Alluvial Basins of Arizona.—Continued

 

Central 

Upland and 

Northeast 

Gila River

09484000 Sabino Creek nr Tucson 13.42 12.36 4.45 8 67

09484200 Bear Creek nr Tucson 4.69 5.30 1.70 -13 64

09484500 Tanque Verde Creek at Tucson 23.49 20.84 11.36 11 52

09485000 Rincon Creek nr Tucson 6.03 9.53 3.97 -58 34

Southeastern09470800 Garden Canyon nr Fort Huachuca 1.26 0.71 0.12 44 91

09480000 Santa Cruz River nr Lochiel 3.64 4.59 0.42 -26 89

09480500 Santa Cruz River nr Nogales 25.44 22.25 (

3

) 13 (

3

)

09481500 Sonoita Creek nr Patagonia 8.08 12.01 6.07 -49 25

1

See figure 19 for location of runoff regions.

2

See table 6 for description of regression equation.

3

BCM results not available for gaged site.

[BCM is Basin Characterization Model.]
Tables 1–29 89

 

Runoff region1 Basin name2

Runoff from BCM, 

in inches

Runoff from 

regression equation4

,

in inches

Total 

area

Mountain 

area4

Total 

area

Mountain 

area3

Western

upland

Agua Fria 0.78 0.85 --- 0.86

Big Sandy 0.39 0.55 --- 0.59

Bill Williams 0.49 0.68 --- 0.37

Peach Springs 0.15 0.19 --- 0.39

Upper Hassayampa 0.53 0.86 --- 0.97

Central 

Upland and 

Northeast Gila 

River

Prescott AMA 0.20 0.45 --- 2.00

Verde River 1.33 1.64 --- 1.61

Salt River 1.78 1.96 --- 2.30

Tonto Creek 1.04 1.30 --- 2.99

Aravaipa Canyon 0.24 0.35 --- 1.68

Bonita Creek 0.14 0.24 --- 1.51

Donnelly Wash 0.13 0.17 --- 0.75

Dripping Springs Wash 0.40 0.45 --- 1.27

Lower San Pedro 0.26 0.46 --- 1.30

Morenci 0.71 0.87 --- 1.88

Safford north 0.18 0.36 --- 1.44

Tucson AMA north 0.17 0.50 --- 1.30

Southeastern

Gila River

Cienega Creek 0.22 0.42 --- 1.18

Douglas 0.02 0.02 --- 0.53

Douglas INA 0.00 0.00 --- 0.55

Duncan Valley 0.04 0.08 --- 0.44

Safford south 0.18 0.49 --- 0.67

San Bernardino Valley 0.05 0.07 --- 0.45

San Rafael 0.16 0.40 --- 1.54

Santa Cruz AMA 0.20 0.36 --- 0.89

Tucson AMA south 0.14 0.30 --- 0.87

Upper San Pedro 0.04 0.13 --- 0.79

Willcox 0.35 1.00 --- 0.88

 1Runoff region shown on figure 19.

2

Basins shown on figure 2.

3

Mountain area in a basin is the higher elevation area composed of bedrock.

4

Regression equation shown in table 6.

Table 10. Comparison of basin runoff estimates using the Basin Characterization Model (BCM) and 

regression equation. 

[---, not applicable.]
90 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Runoff region1 Number of streamflow gages in region

Mean residual, in percent Mean absolute residual, 

in percent

Regression2 BCM3 Regression2 BCM3

Western Upland 4 6.8 27.1 29.4 32.6

Central Upland and Northeast 

Gila River 39 -5.8 25.6 28.7 47.4

Southeastern Gila River 4 -4.6 68.0 32.8 51.0

all regions 47 -4.7 28.7 29.1 46.5

1

Runoff regions shown in figure 19.

2

Regression residual is observed streamflow minus regression estimated streamflow. Regression equation is shown in table 6.

3

BCM residual is observed streamflow minus BCM estimated streamflow.

Table 11. Statistics of fit between observed and estimated mean annual streamflow at gaged sites for runoff regions in the 

Southwest Alluvial Basins study area.

[BCM is Basin Characterization Model.]
Tables 1–29 91

1940–1949 1950–1959

Basin name

Average annual 

recharge 

(in)

 Average annual 

volume of recharge

(acre-ft)

Percent of PRISM 

precipitation

Average annual 

recharge 

(in)

 Average annual 

volume of recharge

(acre-ft)

Percent of PRISM 

precipitation

AGUA FRIA 0.24 16,000 1.5 0.24 16,000 1.5

ARAVAIPA CANYON 0.26 7,000 1.6 0.22 6,000 1.4

BIG SANDY 0.17 18,000 1.3 0.16 17,000 1.3

BILL WILLIAMS 0.13 24,000 1.1 0.13 23,000 1.1

BONITA CREEK 0.22 5,000 1.4 0.21 5,000 1.4

BUTLER VALLEY 0.04 1,000 0.6 0.02 0 0.3

CIENEGA CREEK 0.30 10,000 1.7 0.30 10,000 1.7

DETRITAL VALLEY 0.03 1,000 0.4 0.02 1,000 0.3

DONNELLY WASH 0.22 3,000 1.4 0.18 3,000 1.3

DOUGLAS 0.17 4,000 1.3 0.15 3,000 1.2

DOUGLAS INA 0.12 3,000 1.0 0.10 3,000 0.9

DRIPPING SPRINGS WASH 0.26 6,000 1.7 0.24 5,000 1.6

DUNCAN VALLEY 0.13 4,000 1.1 0.08 2,000 0.8

GILA BEND 0.04 3,000 0.5 0.01 1,000 0.2

HARQUAHALA INA 0.03 1,000 0.4 0.01 1,000 0.2

HUALAPAI VALLEY 0.06 4,000 0.7 0.05 3,000 0.6

LAKE HAVASU 0.02 0 0.3 0.00 0 0.1

LAKE MOHAVE 0.02 1,000 0.3 0.01 1,000 0.2

LOWER GILA 0.02 9,000 0.4 0.01 2,000 0.1

LOWER SAN PEDRO 0.23 20,000 1.5 0.20 18,000 1.4

MCMULLEN VALLEY 0.06 2,000 0.7 0.04 1,000 0.5

MEADVIEW 0.06 1,000 0.7 0.05 0 0.5

MORENCI 0.29 24,000 1.6 0.25 21,000 1.5

PARKER 0.01 1,000 0.2 0.00 0 0.0

PEACH SPRINGS 0.12 9,000 1.0 0.11 8,000 1.0

PHOENIX AMA 0.06 18,000 0.7 0.05 15,000 0.6

PINAL AMA 0.06 13,000 0.7 0.05 10,000 0.5

PRESCOTT AMA 0.21 6,000 1.5 0.23 6,000 1.5

RANEGRAS PLAIN 0.02 1,000 0.4 0.00 0 0.1

SACRAMENTO VALLEY 0.05 5,000 0.6 0.05 4,000 0.6

SAFFORD 0.17 42,000 1.2 0.13 33,000 1.1

SALT RIVER 0.36 100,000 1.8 0.33 90,000 1.7

SAN BERNARDINO VALLEY 0.20 4,000 1.4 0.13 3,000 1.1

SAN RAFAEL 0.34 4,000 2.0 0.34 4,000 2.0

SAN SIMON WASH 0.08 9,000 0.7 0.07 8,000 0.7

SANTA CRUZ AMA 0.24 9,000 1.5 0.25 10,000 1.5

TIGER WASH 0.05 0 0.5 0.03 0 0.3

TONTO CREEK 0.39 20,000 1.9 0.39 20,000 1.9

TUCSON AMA 0.16 32,000 1.2 0.15 32,000 1.2

UPPER HASSAYAMPA 0.20 8,000 1.3 0.22 9,000 1.4

UPPER SAN PEDRO 0.17 17,000 1.3 0.17 16,000 1.2

VERDE RIVER 0.29 87,000 1.6 0.27 81,000 1.6

WESTERN MEXICAN DRAINAGE 0.02 1,000 0.3 0.01 0 0.2

WILLCOX 0.19 19,000 1.3 0.15 15,000 1.2

YUMA 0.00 0 0.1 0.00 0 0.0

Table 12. Average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for time periods indicated.
92 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

1960–1969 1970–1979

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

0.30 20,000 1.7 0.29 19,000 1.7

0.29 8,000 1.7 0.30 8,000 1.7

0.18 19,000 1.3 0.19 20,000 1.4

0.14 25,000 1.2 0.16 29,000 1.3

0.25 6,000 1.5 0.23 6,000 1.5

0.02 0 0.3 0.05 1,000 0.7

0.37 12,000 1.9 0.35 12,000 1.8

0.02 1,000 0.2 0.05 2,000 0.6

0.22 3,000 1.5 0.25 4,000 1.5

0.19 4,000 1.4 0.18 4,000 1.4

0.14 4,000 1.1 0.12 3,000 1.0

0.30 6,000 1.8 0.31 7,000 1.8

0.15 4,000 1.2 0.14 4,000 1.1

0.03 2,000 0.4 0.03 2,000 0.4

0.01 0 0.2 0.03 1,000 0.4

0.05 3,000 0.6 0.08 5,000 0.8

0.00 0 0.0 0.02 0 0.3

0.00 0 0.1 0.02 1,000 0.4

0.01 5,000 0.2 0.02 6,000 0.3

0.26 22,000 1.6 0.28 24,000 1.7

0.03 1,000 0.4 0.07 2,000 0.8

0.06 1,000 0.7 0.09 1,000 0.9

0.32 26,000 1.6 0.28 23,000 1.6

0.00 0 0.0 0.01 1,000 0.2

0.14 11,000 1.1 0.16 12,000 1.2

0.07 19,000 0.7 0.08 22,000 0.8

0.08 17,000 0.8 0.07 16,000 0.8

0.27 7,000 1.7 0.25 7,000 1.6

0.00 0 0.1 0.02 1,000 0.4

0.04 3,000 0.4 0.08 6,000 0.8

0.19 47,000 1.3 0.17 44,000 1.3

0.39 107,000 1.8 0.41 113,000 1.8

0.22 4,000 1.4 0.20 4,000 1.4

0.39 5,000 2.2 0.37 5,000 2.1

0.13 16,000 1.0 0.10 12,000 0.9

0.32 12,000 1.7 0.30 11,000 1.7

0.02 0 0.2 0.06 0 0.6

0.42 21,000 1.9 0.44 23,000 2.0

0.21 43,000 1.4 0.20 41,000 1.4

0.24 10,000 1.5 0.25 10,000 1.5

0.21 21,000 1.4 0.21 21,000 1.4

0.30 91,000 1.7 0.30 89,000 1.6

0.03 1,000 0.4 0.03 1,000 0.4

0.20 21,000 1.4 0.19 19,000 1.3

0.00 0 0.0 0.00 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 12. Average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for time periods indicated.—Continued
Tables 1–29 93

1980–1989 1990–1999

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

0.36 24,000 1.8 0.37 24,000 1.8

0.36 10,000 1.8 0.39 11,000 1.9

0.21 22,000 1.4 0.21 23,000 1.5

0.20 35,000 1.4 0.20 36,000 1.4

0.34 8,000 1.8 0.30 7,000 1.7

0.07 1,000 0.8 0.07 1,000 0.8

0.45 15,000 2.0 0.41 13,000 1.9

0.04 2,000 0.5 0.05 3,000 0.6

0.29 4,000 1.6 0.30 5,000 1.7

0.25 6,000 1.7 0.21 5,000 1.5

0.21 6,000 1.3 0.15 4,000 1.1

0.35 7,000 1.9 0.37 8,000 1.9

0.23 7,000 1.5 0.20 6,000 1.4

0.05 3,000 0.6 0.05 3,000 0.6

0.03 1,000 0.4 0.04 2,000 0.5

0.07 5,000 0.7 0.09 6,000 0.9

0.02 0 0.2 0.03 0 0.4

0.02 1,000 0.3 0.03 2,000 0.5

0.02 7,000 0.3 0.02 7,000 0.3

0.34 30,000 1.8 0.34 30,000 1.8

0.10 4,000 1.0 0.09 3,000 0.9

0.07 1,000 0.7 0.09 1,000 0.9

0.39 32,000 1.8 0.36 29,000 1.7

0.01 1,000 0.2 0.01 1,000 0.2

0.15 12,000 1.2 0.15 11,000 1.2

0.10 29,000 0.9 0.13 36,000 1.1

0.09 21,000 0.9 0.10 23,000 1.0

0.33 8,000 1.8 0.31 8,000 1.8

0.03 1,000 0.4 0.02 1,000 0.3

0.08 7,000 0.7 0.10 8,000 1.0

0.25 62,000 1.5 0.24 60,000 1.5

0.50 137,000 2.0 0.44 122,000 1.9

0.24 5,000 1.5 0.18 4,000 1.3

0.48 6,000 2.3 0.43 6,000 2.2

0.12 15,000 1.0 0.12 15,000 1.0

0.39 15,000 1.9 0.38 14,000 1.9

0.08 0 0.8 0.08 0 0.7

0.50 25,000 2.0 0.47 24,000 2.0

0.26 54,000 1.6 0.26 53,000 1.5

0.30 12,000 1.6 0.30 12,000 1.6

0.28 27,000 1.6 0.24 23,000 1.5

0.37 111,000 1.8 0.36 110,000 1.8

0.04 1,000 0.5 0.05 1,000 0.5

0.27 28,000 1.6 0.26 27,000 1.6

0.00 0 0.0 0.00 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 12. Average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for time periods indicated.—Continued
94 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2000–2006 1940–2006

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

Average annual 

recharge 

(in)

 Average annual volume 

of recharge

(acre-ft)

Percent of PRISM 

precipitation

0.22 15,000 1.5 0.29 19,000 1.7

0.21 6,000 1.4 0.29 8,000 1.7

0.12 13,000 1.1 0.18 19,000 1.4

0.13 24,000 1.2 0.16 28,000 1.2

0.22 5,000 1.4 0.25 6,000 1.5

0.06 1,000 0.7 0.05 1,000 0.6

0.28 9,000 1.7 0.35 12,000 1.9

0.04 2,000 0.6 0.04 2,000 0.5

0.14 2,000 1.1 0.23 4,000 1.5

0.14 3,000 1.2 0.18 4,000 1.4

0.10 3,000 0.9 0.14 4,000 1.1

0.17 4,000 1.3 0.29 6,000 1.8

0.13 4,000 1.1 0.15 4,000 1.2

0.02 1,000 0.3 0.03 2,000 0.4

0.04 1,000 0.5 0.03 1,000 0.4

0.06 4,000 0.7 0.07 4,000 0.7

0.03 0 0.5 0.02 0 0.3

0.04 2,000 0.6 0.02 1,000 0.3

0.02 6,000 0.3 0.02 6,000 0.3

0.18 15,000 1.3 0.26 23,000 1.6

0.08 3,000 0.8 0.07 2,000 0.7

0.07 1,000 0.8 0.07 1,000 0.7

0.30 24,000 1.6 0.32 26,000 1.6

0.02 2,000 0.4 0.01 1,000 0.2

0.10 8,000 1.0 0.13 10,000 1.1

0.06 18,000 0.7 0.08 23,000 0.8

0.05 11,000 0.6 0.07 16,000 0.8

0.20 5,000 1.4 0.26 7,000 1.6

0.03 2,000 0.5 0.02 1,000 0.3

0.06 5,000 0.7 0.07 6,000 0.7

0.14 35,000 1.1 0.18 46,000 1.3

0.32 88,000 1.7 0.39 109,000 1.8

0.12 2,000 1.0 0.19 4,000 1.3

0.34 4,000 2.0 0.39 5,000 2.1

0.09 11,000 0.9 0.10 12,000 0.9

0.25 10,000 1.6 0.31 12,000 1.7

0.08 0 0.8 0.05 0 0.6

0.31 16,000 1.7 0.42 22,000 1.9

0.15 32,000 1.2 0.20 41,000 1.4

0.18 8,000 1.3 0.24 10,000 1.5

0.17 16,000 1.2 0.21 20,000 1.4

0.25 76,000 1.5 0.31 93,000 1.7

0.02 1,000 0.3 0.03 1,000 0.4

0.17 17,000 1.2 0.21 21,000 1.4

0.00 0 0.1 0.00 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 12. Average annual mountain-front recharge estimated by the Southwest Alluvial Basins-Regional Aquifer 

System-Analysis (SWAB-RASA) regression equation and Parameter-elevation Regressions on Independent Slopes Model (PRISM) 

precipitation data for time periods indicated.—Continued
Tables 1–29 95

1940–1949 1950–1959

Basin name

Average annual 

in-place recharge

(in)

Average annual 

runoff 

(in)

Average annual

 in-place recharge

(in)

Average annual 

runoff

(in)

AGUA FRIA 0.38 0.41 0.23 0.27

ARAVAIPA CANYON 0.17 0.16 0.03 0.08

BIG SANDY 0.20 0.30 0.09 0.19

BILL WILLIAMS 0.17 0.34 0.09 0.27

BONITA CREEK 0.02 0.05 0.01 0.03

BUTLER VALLEY 0.04 0.03 0.01 0.00

CIENEGA CREEK 0.07 0.05 0.11 0.18

DETRITAL VALLEY 0.03 0.04 0.01 0.00

DONNELLY WASH 0.08 0.06 0.01 0.01

DOUGLAS 0.05 0.01 0.02 0.00

DOUGLAS INA 0.00 0.00 0.00 0.00

DRIPPING SPRINGS WASH 0.57 0.21 0.27 0.07

DUNCAN VALLEY 0.01 0.02 0.00 0.00

GILA BEND 0.01 0.01 0.00 0.00

HARQUAHALA INA 0.02 0.01 0.00 0.00

HUALAPAI VALLEY 0.07 0.04 0.03 0.01

LAKE HAVASU 0.04 0.01 0.00 0.00

LAKE MOHAVE 0.02 0.04 0.00 0.00

LOWER GILA 0.00 0.00 0.00 0.00

LOWER SAN PEDRO 0.19 0.18 0.09 0.08

MCMULLEN VALLEY 0.04 0.02 0.01 0.00

MEADVIEW 0.12 0.07 0.04 0.03

MORENCI 0.06 0.59 0.03 0.45

PARKER 0.00 0.00 0.00 0.00

PEACH SPRINGS 0.27 0.16 0.15 0.08

PHOENIX AMA 0.05 0.06 0.02 0.03

PINAL AMA 0.01 0.00 0.00 0.00

PRESCOTT AMA 0.13 0.15 0.08 0.11

RANEGRAS PLAIN 0.00 0.00 0.00 0.00

SACRAMENTO VALLEY 0.08 0.10 0.03 0.02

SAFFORD 0.09 0.10 0.04 0.06

SALT RIVER 0.61 1.40 0.35 1.16

SAN BERNARDINO VALLEY 0.02 0.05 0.01 0.01

SAN RAFAEL 0.13 0.07 0.10 0.09

SAN SIMON WASH 0.01 0.01 0.01 0.00

SANTA CRUZ AMA 0.06 0.04 0.13 0.20

TIGER WASH 0.05 0.00 0.01 0.00

TONTO CREEK 1.11 0.71 0.77 0.61

TUCSON AMA 0.08 0.06 0.08 0.09

UPPER HASSAYAMPA 0.50 0.31 0.36 0.26

UPPER SAN PEDRO 0.04 0.02 0.04 0.02

VERDE RIVER 0.45 1.34 0.27 0.81

WESTERN MEXICAN DRAINAGE 0.01 0.01 0.00 0.00

WILLCOX 0.08 0.23 0.05 0.25

YUMA 0.00 0.00 0.00 0.00

Table 13. Average annual in-place recharge and runoff estimated by the Basin Characterization Model (BCM).
96 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

1960–1969 1970–1979

Average annual 

in-place recharge

(in)

Average annual 

runoff

(in)

Average annual

 in-place recharge

(in)

Average annual 

runoff

(in)

0.35 0.85 0.62 1.17

0.06 0.23 0.28 0.29

0.09 0.29 0.34 0.62

0.12 0.39 0.35 0.70

0.02 0.13 0.08 0.19

0.01 0.02 0.04 0.03

0.12 0.38 0.17 0.23

0.01 0.03 0.05 0.05

0.07 0.21 0.18 0.20

0.05 0.03 0.09 0.01

0.00 0.00 0.00 0.00

0.57 0.68 0.97 0.51

0.02 0.07 0.02 0.04

0.02 0.02 0.01 0.00

0.01 0.01 0.01 0.01

0.03 0.04 0.11 0.07

0.00 0.01 0.03 0.01

0.00 0.01 0.01 0.03

0.00 0.01 0.00 0.00

0.17 0.34 0.33 0.33

0.02 0.03 0.05 0.02

0.12 0.07 0.27 0.12

0.06 0.67 0.11 0.78

0.00 0.00 0.00 0.00

0.14 0.12 0.63 0.20

0.05 0.14 0.09 0.17

0.02 0.04 0.02 0.02

0.10 0.14 0.24 0.36

0.00 0.01 0.00 0.00

0.03 0.05 0.09 0.10

0.10 0.23 0.22 0.26

0.56 1.77 1.11 2.45

0.02 0.13 0.02 0.06

0.21 0.25 0.29 0.16

0.03 0.08 0.03 0.03

0.10 0.31 0.15 0.18

0.02 0.02 0.05 0.01

1.09 1.07 1.65 1.56

0.11 0.23 0.16 0.17

0.44 0.53 0.70 0.71

0.06 0.07 0.09 0.04

0.35 1.18 0.69 1.72

0.01 0.02 0.00 0.00

0.08 0.41 0.10 0.35

0.00 0.00 0.00 0.00

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 13. Average annual in-place recharge and runoff estimated by the Basin Characterization Model (BCM). —Continued
Tables 1–29 97

1980–1989 1990–1999

Average annual 

in-place recharge

(in)

Average annual 

runoff

(in)

Average annual 

in-place recharge

(in)

Average annual 

runoff

(in)

0.49 0.93 0.55 1.39

0.18 0.23 0.43 0.57

0.18 0.33 0.34 0.80

0.22 0.46 0.33 0.94

0.07 0.18 0.12 0.33

0.04 0.05 0.07 0.14

0.23 0.30 0.23 0.34

0.03 0.02 0.05 0.11

0.06 0.07 0.21 0.28

0.04 0.00 0.15 0.05

0.00 0.00 0.00 0.00

0.65 0.27 1.11 0.87

0.01 0.03 0.05 0.08

0.00 0.00 0.04 0.02

0.02 0.02 0.06 0.05

0.05 0.01 0.11 0.14

0.05 0.04 0.12 0.13

0.02 0.03 0.04 0.12

0.00 0.00 0.01 0.01

0.29 0.25 0.45 0.54

0.05 0.06 0.07 0.12

0.10 0.05 0.27 0.16

0.11 1.00 0.13 0.99

0.01 0.01 0.02 0.02

0.23 0.11 0.57 0.23

0.06 0.11 0.11 0.23

0.02 0.01 0.03 0.02

0.17 0.24 0.18 0.30

0.01 0.01 0.02 0.05

0.06 0.06 0.11 0.26

0.14 0.20 0.28 0.36

0.90 2.51 1.01 2.22

0.01 0.03 0.03 0.08

0.36 0.22 0.35 0.24

0.03 0.02 0.04 0.04

0.21 0.26 0.20 0.29

0.07 0.04 0.13 0.17

1.44 1.16 1.54 1.58

0.19 0.18 0.21 0.29

0.55 0.60 0.65 0.97

0.10 0.05 0.12 0.09

0.57 1.61 0.68 1.80

0.00 0.00 0.01 0.01

0.11 0.44 0.15 0.57

0.00 0.00 0.00 0.00

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 13. Average annual in-place recharge and runoff estimated by the Basin Characterization Model (BCM). —Continued
98 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2000–2006 1940–2006

Average annual 

in-place recharge

(in)

Average annual 

runoff

(in)

Average annual

 in-place recharge

(in)

Average annual 

runoff

(in)

0.32 0.48 0.42 0.80

0.03 0.03 0.18 0.24

0.17 0.22 0.20 0.40

0.22 0.41 0.21 0.50

0.01 0.02 0.05 0.14

0.04 0.04 0.04 0.04

0.06 0.09 0.15 0.23

0.04 0.05 0.03 0.04

0.04 0.06 0.09 0.13

0.08 0.02 0.07 0.02

0.00 0.00 0.00 0.00

0.31 0.09 0.65 0.40

0.00 0.01 0.02 0.04

0.00 0.00 0.01 0.01

0.01 0.00 0.02 0.01

0.07 0.04 0.07 0.05

0.02 0.01 0.04 0.03

0.02 0.04 0.02 0.04

0.00 0.00 0.00 0.00

0.08 0.06 0.24 0.26

0.04 0.03 0.04 0.04

0.11 0.06 0.15 0.08

0.06 0.53 0.08 0.72

0.00 0.00 0.00 0.01

0.25 0.15 0.32 0.15

0.05 0.07 0.06 0.12

0.00 0.00 0.01 0.01

0.07 0.11 0.14 0.21

0.00 0.00 0.01 0.01

0.05 0.06 0.06 0.09

0.04 0.04 0.14 0.18

0.42 0.89 0.72 1.81

0.02 0.03 0.02 0.05

0.06 0.05 0.22 0.16

0.01 0.01 0.02 0.03

0.05 0.09 0.13 0.20

0.07 0.02 0.06 0.04

0.75 0.57 1.21 1.06

0.05 0.03 0.13 0.15

0.35 0.31 0.51 0.54

0.04 0.01 0.07 0.04

0.36 0.92 0.49 1.36

0.00 0.00 0.01 0.01

0.05 0.14 0.09 0.35

0.00 0.00 0.00 0.00

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 13. Average annual in-place recharge and runoff estimated by the Basin Characterization Model (BCM). —Continued
Tables 1–29 99

1940–1949 1950–1959

Basin name

Average 

annual 

recharge 

(in)

Average annual 

volume of recharge

(acre-ft)

Percent of 

PRISM 

precipitation

Average 

annual 

recharge 

(in)

 Average 

annual volume 

of recharge

(acre-ft)

Percent of 

PRISM 

precipitation

AGUA FRIA 11.2 30,000 2.8 6.8 18,000 1.7

ARAVAIPA CANYON 4.8 5,000 1.2 1.2 1,000 0.3

BIG SANDY 6.2 26,000 1.9 3.0 13,000 0.9

BILL WILLIAMS 5.7 40,000 1.9 3.3 24,000 1.2

BONITA CREEK 0.7 1,000 0.2 0.5 0 0.1

BUTLER VALLEY 1.1 1,000 0.6 0.2 0 0.1

CIENEGA CREEK 1.9 2,000 0.4 3.6 5,000 0.8

DETRITAL VALLEY 0.9 2,000 0.5 0.2 0 0.1

DONNELLY WASH 2.3 1,000 0.6 0.2 0 0.1

DOUGLAS 1.2 1,000 0.4 0.4 0 0.1

DOUGLAS INA 0.0 0 0.0 0.0 0 0.0

DRIPPING SPRINGS WASH 15.4 12,000 3.7 7.0 6,000 1.8

DUNCAN VALLEY 0.3 0 0.1 0.0 0 0.0

GILA BEND 0.3 1,000 0.1 0.0 0 0.0

HARQUAHALA INA 0.5 1,000 0.3 0.1 0 0.0

HUALAPAI VALLEY 2.0 5,000 0.9 0.7 2,000 0.3

LAKE HAVASU 1.0 1,000 0.7 0.0 0 0.0

LAKE MOHAVE 0.7 1,000 0.5 0.0 0 0.0

LOWER GILA 0.1 1,000 0.0 0.0 0 0.0

LOWER SAN PEDRO 5.4 18,000 1.4 2.7 9,000 0.7

MCMULLEN VALLEY 1.1 2,000 0.5 0.3 0 0.1

MEADVIEW 3.4 1,000 1.5 1.2 0 0.6

MORENCI 3.7 12,000 0.8 2.6 8,000 0.6

PARKER 0.1 0 0.1 0.0 0 0.0

PEACH SPRINGS 7.3 22,000 2.5 4.0 12,000 1.4

PHOENIX AMA 1.4 16,000 0.6 0.7 8,000 0.3

PINAL AMA 0.2 2,000 0.1 0.1 1,000 0.1

PRESCOTT AMA 3.8 4,000 1.0 2.6 3,000 0.7

RANEGRAS PLAIN 0.1 0 0.1 0.0 0 0.0

SACRAMENTO VALLEY 2.5 8,000 1.1 0.9 3,000 0.4

SAFFORD 2.8 28,000 0.8 1.2 12,000 0.4

SALT RIVER 20.8 228,000 4.0 13.4 147,000 2.8

SAN BERNARDINO VALLEY 0.6 1,000 0.2 0.2 0 0.1

SAN RAFAEL 3.6 2,000 0.8 2.9 1,000 0.6

SAN SIMON WASH 0.3 1,000 0.1 0.2 1,000 0.1

SANTA CRUZ AMA 1.6 2,000 0.4 4.0 6,000 1.0

TIGER WASH 1.3 0 0.6 0.2 0 0.1

TONTO CREEK 30.8 62,000 5.8 22.0 44,000 4.2

TUCSON AMA 2.3 19,000 0.7 2.5 20,000 0.7

UPPER HASSAYAMPA 13.9 23,000 3.7 10.1 17,000 2.6

UPPER SAN PEDRO 1.1 4,000 0.3 1.0 4,000 0.3

VERDE RIVER 16.6 197,000 3.7 9.9 118,000 2.3

WESTERN MEXICAN DRAINAGE 0.2 0 0.1 0.0 0 0.0

WILLCOX 2.8 11,000 0.8 2.2 9,000 0.7

YUMA 0.0 0 0.0 0.0 0 0.0

Table 14. Average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for time 

periods indicated.

[Total estimated recharge includes in-place recharge plus 15% of BCM-estimated runoff.]
100 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

1960–1969 1970–1979

Average 

annual 

recharge 

(in)

 Average annual 

volume of recharge

(acre-ft)

Percent of 

PRISM 

precipitation

Average 

annual 

recharge 

(in)

 Average 

annual volume 

of recharge

(acre-ft)

Percent of 

PRISM 

precipitation

12.1 32,000 2.7 20.2 54,000 4.6

2.5 3,000 0.6 8.3 9,000 1.8

3.5 15,000 1.0 11.0 46,000 3.1

4.5 32,000 1.5 11.5 81,000 3.5

1.1 1,000 0.3 2.8 3,000 0.7

0.4 0 0.2 1.2 1,000 0.6

4.6 6,000 0.9 5.1 7,000 1.1

0.3 1,000 0.2 1.4 3,000 0.7

2.5 2,000 0.7 5.3 3,000 1.3

1.5 1,000 0.4 2.3 2,000 0.7

0.0 0 0.0 0.0 0 0.0

17.1 14,000 3.8 26.5 21,000 5.8

0.7 1,000 0.2 0.7 1,000 0.2

0.6 2,000 0.3 0.2 1,000 0.1

0.2 0 0.1 0.3 1,000 0.2

1.0 2,000 0.4 3.2 8,000 1.3

0.1 0 0.1 0.7 0 0.5

0.1 0 0.1 0.4 1,000 0.3

0.1 2,000 0.1 0.1 1,000 0.1

5.7 19,000 1.4 9.7 33,000 2.3

0.5 1,000 0.3 1.3 2,000 0.6

3.3 1,000 1.5 7.4 3,000 3.0

4.1 14,000 0.9 5.7 19,000 1.3

0.0 0 0.0 0.1 1,000 0.1

3.9 12,000 1.2 16.9 50,000 5.1

1.7 20,000 0.7 2.9 33,000 1.2

0.6 6,000 0.3 0.7 6,000 0.3

3.1 3,000 0.7 7.5 8,000 1.8

0.0 0 0.0 0.1 0 0.1

0.9 3,000 0.4 2.8 9,000 1.2

3.3 33,000 0.9 6.5 65,000 1.9

20.9 230,000 3.9 37.5 413,000 6.8

1.0 1,000 0.3 0.7 1,000 0.2

6.3 3,000 1.3 8.0 4,000 1.7

0.9 5,000 0.3 0.9 4,000 0.3

3.8 6,000 0.8 4.4 7,000 1.0

0.6 0 0.3 1.3 0 0.6

31.7 64,000 5.7 48.0 96,000 8.3

3.6 29,000 0.9 4.6 37,000 1.2

13.2 22,000 3.3 20.5 34,000 5.0

1.9 7,000 0.5 2.5 9,000 0.6

13.4 160,000 2.9 24.0 285,000 5.3

0.3 0 0.1 0.1 0 0.1

3.6 14,000 1.0 3.9 16,000 1.1

0.0 0 0.0 0.0 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 14. Average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for time 

periods indicated. —Continued

[Total estimated recharge includes in-place recharge plus 15% of BCM-estimated runoff.]
Tables 1–29 101

1980–1989 1990–1999

Average 

annual 

recharge 

(in)

 Average 

annual volume of 

recharge

(acre-ft)

Percent of 

PRISM 

precipitation

Average 

annual 

recharge 

(in)

 Average annual 

volume of recharge

(acre-ft)

Percent of 

PRISM 

precipitation

16.1 43,000 3.2 19.2 51,000 3.8

5.5 6,000 1.1 13.0 14,000 2.5

5.8 24,000 1.6 11.6 48,000 3.1

7.2 51,000 2.0 11.9 84,000 3.3

2.5 2,000 0.5 4.3 4,000 1.0

1.2 1,000 0.5 2.3 1,000 1.0

7.0 9,000 1.2 7.1 9,000 1.3

0.7 1,000 0.4 1.8 3,000 0.8

1.8 1,000 0.4 6.4 4,000 1.5

1.0 1,000 0.3 3.9 3,000 1.0

0.0 0 0.0 0.0 0 0.0

17.5 14,000 3.6 31.4 25,000 6.2

0.4 0 0.1 1.4 2,000 0.4

0.1 0 0.0 1.0 3,000 0.5

0.6 1,000 0.3 1.6 3,000 0.8

1.3 3,000 0.5 3.3 8,000 1.3

1.5 1,000 0.9 3.4 2,000 1.9

0.5 1,000 0.3 1.6 3,000 0.9

0.0 1,000 0.0 0.3 4,000 0.2

8.4 29,000 1.8 13.4 46,000 2.8

1.5 2,000 0.6 2.2 3,000 0.9

2.6 1,000 1.1 7.4 3,000 2.9

6.7 22,000 1.3 7.1 23,000 1.4

0.2 1,000 0.1 0.5 2,000 0.3

6.1 18,000 1.9 15.3 45,000 4.9

1.9 22,000 0.7 3.5 40,000 1.2

0.5 4,000 0.2 0.7 6,000 0.3

5.3 5,000 1.1 5.7 6,000 1.3

0.2 0 0.1 0.8 2,000 0.5

1.6 5,000 0.6 3.7 12,000 1.4

4.4 44,000 1.1 8.6 86,000 2.1

32.5 357,000 5.1 34.1 375,000 5.8

0.4 0 0.1 1.1 1,000 0.3

9.9 5,000 1.8 9.8 5,000 1.9

0.8 4,000 0.3 1.2 6,000 0.4

6.4 10,000 1.2 6.2 9,000 1.2

1.9 0 0.7 4.0 1,000 1.7

41.1 82,000 6.6 45.1 91,000 7.5

5.6 45,000 1.3 6.5 53,000 1.5

16.3 27,000 3.6 20.1 33,000 4.4

2.7 10,000 0.6 3.3 13,000 0.8

20.7 246,000 4.0 24.2 288,000 4.7

0.0 0 0.0 0.4 1,000 0.2

4.6 18,000 1.1 6.0 24,000 1.4

0.0 0 0.0 0.0 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 14. Average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for time 

periods indicated. —Continued

[Total estimated recharge includes in-place recharge plus 15% of BCM-estimated runoff.]
102 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2000–2006 1940–2006

Average 

annual 

recharge 

(in)

 Average annual 

volume of 

recharge

(acre-ft)

Percent of 

PRISM 

precipitation

Average 

annual 

recharge 

(in)

 Average annual 

volume of 

recharge

(acre-ft)

Percent of 

PRISM 

precipitation

9.9 26,000 2.6 13.8 37,000 3.1

0.9 1,000 0.2 5.4 6,000 1.2

5.1 21,000 1.7 6.7 28,000 2.0

7.1 50,000 2.4 7.3 52,000 2.3

0.3 0 0.1 1.8 2,000 0.4

1.3 1,000 0.6 1.1 1,000 0.5

1.9 2,000 0.4 4.6 6,000 0.9

1.1 2,000 0.6 0.9 2,000 0.5

1.3 1,000 0.4 2.9 2,000 0.8

2.1 2,000 0.7 1.8 1,000 0.5

0.0 0 0.0 0.0 0 0.0

8.3 7,000 2.4 18.0 14,000 4.1

0.1 0 0.0 0.5 1,000 0.2

0.0 0 0.0 0.3 1,000 0.2

0.4 1,000 0.2 0.5 1,000 0.3

1.9 5,000 0.9 1.9 5,000 0.8

0.4 0 0.3 1.1 1,000 0.7

0.7 1,000 0.5 0.6 1,000 0.4

0.0 0 0.0 0.1 1,000 0.1

2.4 8,000 0.7 7.0 24,000 1.7

1.2 2,000 0.5 1.2 2,000 0.5

3.0 1,000 1.4 4.1 2,000 1.8

3.4 11,000 0.8 4.8 16,000 1.0

0.1 0 0.0 0.1 1,000 0.1

6.8 20,000 2.5 8.7 26,000 2.9

1.5 17,000 0.7 2.0 22,000 0.8

0.1 1,000 0.0 0.4 4,000 0.2

2.2 2,000 0.6 4.4 4,000 1.1

0.0 0 0.0 0.2 0 0.1

1.5 5,000 0.7 2.0 7,000 0.9

1.2 12,000 0.4 4.1 41,000 1.2

14.0 154,000 2.9 25.2 277,000 4.7

0.5 0 0.2 0.7 1,000 0.2

1.8 1,000 0.4 6.2 3,000 1.3

0.2 1,000 0.1 0.7 3,000 0.2

1.6 2,000 0.4 4.1 6,000 0.9

1.8 0 0.8 1.6 0 0.7

21.2 43,000 4.6 34.9 70,000 6.3

1.5 12,000 0.4 3.9 32,000 1.0

10.1 17,000 2.9 15.1 25,000 3.7

1.0 4,000 0.3 2.0 7,000 0.5

12.6 150,000 3.0 17.5 209,000 3.8

0.0 0 0.0 0.2 0 0.1

1.7 7,000 0.5 3.6 15,000 1.0

0.0 0 0.0 0.0 0 0.0

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 14. Average annual mountain-front recharge estimated by the Basin Characterization Model (BCM) for time 

periods indicated. —Continued

[Total estimated recharge includes in-place recharge plus 15% of BCM-estimated runoff.]
Tables 1–29 103

Table 15. Comparison of Basin Characterization Model (BCM) and Southwest Alluvial Basins-Regional Aquifer System-Analysis 

(SWAB-RASA) regression equation estimates of average annual mountain-front recharge for the 1940–2006 time period.

[Recharge estimates by Arizona Department of Water Resources (ADWR) also provided for comparison.]

Basin name

BCM average 

annual volume 

of in-place 

recharge

(acre-ft)

SWAB-RASA 

equation 

average an- nual volume of 

recharge 

(acre-ft)

 ADWR estimates 

of annual 

recharge1

(acre-ft)

ADWR ground- water atlas 

volume number

Citation for ADWR estimate

AGUA FRIA 29,000 19,000 9,000 5 Freethey and Anderson, 1986

ARAVAIPA CANYON 5,000 8,000 7,000 - 16,700

7,000

3 Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

BIG SANDY 22,000 19,000 22,000 4 Freethey and Anderson, 1986

BILL WILLIAMS 38,000 28,000 32,000 4 Freethey and Anderson, 1986

BONITA CREEK 1,000 6,000 9,000 3 Freethey and Anderson, 1986

BUTLER VALLEY 1,000 1,000 < 1,000

1,060

7 Freethey and Anderson, 1986

Herndon, 1985

CIENEGA CREEK 5,000 12,000 8,500 - 25,500

11,000

3 Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

DETRITAL VALLEY 1,000 2,000 1,000 4 Freethey and Anderson, 1986

DONNELLY WASH 1,000 4,000 3,000 3 Freethey and Anderson, 1986

DOUGLAS 1,000 4,000 15,5002 3 Anderson and Freethey, 1995

Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

DOUGLAS INA 0 4,000

DRIPPING SPRINGS WASH 13,000 6,000 3,000

9,000

3 Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

DUNCAN VALLEY 0 4,000 14,200

6,000

8,000

3 Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

Arizona Water Commission, 1975

GILA BEND3 1,000 2,000 37,000

10,000

7 Freethey and Anderson, 1986

Arizona Water Commission, 1975

HARQUAHALA INA 1,000 1,000 <1,2004

1,000

<1,0004

7 Anderson and Freethey, 1995

Freethey and Anderson, 1986

Arizona Water Commission, 1975

HUALAPAI VALLEY 4,000 4,000 3,000

2,000 - 2,500

4 Freethey and Anderson, 1986

Remick, 1981

LAKE HAVASU 0 0 35,0005 4 Freethey and Anderson, 1986

LAKE MOHAVE6 1,000 1,000 183,000 4 Freethey and Anderson, 1986

LOWER GILA 1,000 6,000 88,000

>9,000

7 Freethey and Anderson, 1986

Arizona Water Commission, 1975

LOWER SAN PEDRO 21,000 23,000 29,000

25,000

24,000

3 Anderson and Freethey, 1995

Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

MCMULLEN VALLEY 1,000 2,000 1,000

1,000

7 Freethey and Anderson, 1986

Arizona Water Commission, 1975

MEADVIEW 2,000 1,000 4,000 4 Freethey and Anderson, 1986

MORENCI 7,000 26,000 15,000 3 Freethey and Anderson, 1986

PARKER6 1,000 1,000 241,0006 7 Freethey and Anderson, 1986

PEACH SPRINGS 24,000 10,000 not available

PHOENIX AMA 17,000 23,000 24,100 8 Arizona Department of Water 

Resources, 1999a

PINAL AMA 3,000 16,000 82,7508 8 Arizona Department of Water 

Resources, 2004
104 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

PRESCOTT AMA 4,000 7,000 7,000 8 Timmons and Springer, 2006

RANEGRAS PLAIN 0 1,000 5,000

5,500

<1,000

1,000

7 Arizona Department of Water 

Resources, 1994 

Arizona Department of Water 

Resources, 1990

Freethey and Anderson, 1986

Arizona Water Commission, 

1975

SACRAMENTO VALLEY 5,000 6,000 1,000

4,000

4 Rascona, 1991

Freethey and Anderson, 1986

SAFFORD 34,000 46,000 105,000 3 Freethey and Anderson, 1986

SALT RIVER 201,000 109,000 178,000 5 Freethey and Anderson, 1986

SAN BERNARDINO 

VALLEY

0 4,000 9,000 3 Freethey and Anderson, 1986

SAN RAFAEL 3,000 5,000 5,000 3 Freethey and Anderson, 1986

SAN SIMON WASH 3,000 12,000 11,000 7 Freethey and Anderson, 1986

SANTA CRUZ AMA 5,000 12,000 61,0507 8 Arizona Department of Water 

Resources, 1999b

TIGER WASH 0 0 <1,000 7 Freethey and Anderson, 1986

TONTO CREEK 62,000 22,000 17,000

37,000

5 Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

TUCSON AMA 27,000 41,000 60,8007 8 Arizona Department of Water 

Resources, 1999c

UPPER HASSAYAMPA 22,000 10,000 8,000 5 Freethey and Anderson, 1986

UPPER SAN PEDRO 7,000 20,000 35,750 3 Arizona Department of Water 

Resources, 2005

VERDE RIVER 147,000 93,000 197,770 5 Blasch and others, 2006

Arizona Department of Water 

Resources, 1994 

Freethey and Anderson, 1986

WESTERN MEXICAN 

DRAINAGE

0 1,000 1,000 7 Freethey and Anderson, 1986

WILLCOX 9,000 21,000 47,000

46,000

15,000

3 Anderson and Freethey, 1995

Freethey and Anderson, 1986

Arizona Department of Water 

Resources, 1994 

YUMA 0 0 213,0005 7 Freethey and Anderson, 1986

1

 ADWR recharge estimates may include basin underflow, streamflow infiltration, or other components not directly comparable to the SWAB-RASA equation or BCM results.

2

 Includes Douglas and Douglas INA basins.

3

 Includes Gila River flood events and infiltration of water impounded behind Painted Rock Dam (Arizona Department of Water Resources, 1994.)

4

 Includes Tiger Wash Basin.

5

 Presumably includes recharge from Colorado River.

6

 Recharge comes principally from infiltration of Colorado River water.

7

 Includes groundwater inflow.

8

 Primary source of natural recharge is streambed recharge along the Gila and Santa Cruz Rivers.

Table 15. Comparison of Basin Characterization Model (BCM) and Southwest Alluvial Basins-Regional Aquifer System-Analysis 

(SWAB-RASA) regression equation estimates of average annual mountain-front recharge for the 1940–2006 time period. —Continued

[Recharge estimates by Arizona Department of Water Resources (ADWR) also provided for comparison.]

Basin name

BCM average 

annual volume 

of in-place 

recharge

(acre-ft)

SWAB-RASA 

equation 

average an- nual volume of 

recharge 

(acre-ft)

 ADWR estimates 

of annual 

recharge1

(acre-ft)

ADWR ground- water atlas 

volume number

Citation for ADWR estimate
Tables 1–29 105

2000 2001 2002 2003

Basin name Minimum Maximum Minimum Maximum Minimum Maximum Minimum Maximum

AGUA FRIA 23,400 41,200 23,600 40,400 15,900 31,400 24,500 49,400

ARAVAIPA CANYON 5,500 15,500 7,500 15,300 6,300 13,400 7,000 15,200

BIG SANDY 13,800 22,800 14,900 23,800 12,900 20,200 15,900 29,900

BILL WILLIAMS 36,700 56,700 39,700 54,800 31,100 44,100 34,300 62,300

BONITA CREEK 2,400 6,400 3,300 7,400 2,100 6,700 3,300 7,500

BUTLER VALLEY 200 400 400 600 200 300 300 700

CIENEGA CREEK 3,600 9,600 4,000 9,500 3,700 8,700 2,900 8,900

DETRITAL VALLEY 600 1,000 1,100 1,600 600 800 1,200 2,300

DONNELLY WASH 3,900 6,500 5,300 7,600 3,900 5,800 4,100 7,000

DOUGLAS 300 900 300 900 200 700 200 500

DOUGLAS INA 800 2,100 1,000 2,100 800 1,900 600 1,500

DRIPPING SPRINGS WASH 3,400 7,400 4,500 8,400 3,500 6,400 4,200 8,500

DUNCAN VALLEY 3,100 5,600 3,800 6,800 2,600 6,500 3,500 5,400

GILA BEND 24,200 29,300 31,000 29,800 26,200 29,500 21,300 27,600

HARQUAHALA INA 1,500 2,000 2,200 2,400 1,100 1,500 1,800 2,700

HUALAPAI VALLEY 800 1,700 1,300 2,500 700 1,200 1,700 3,500

LAKE HAVASU 1,900 2,400 1,900 2,100 1,900 2,400 1,700 2,700

LAKE MOHAVE 27,900 38,100 30,900 40,200 33,400 40,400 30,100 41,200

LOWER GILA 36,000 47,100 34,900 40,500 34,800 40,800 35,300 51,200

LOWER SAN PEDRO 27,600 54,100 36,200 54,100 31,300 48,500 30,000 50,800

MCMULLEN VALLEY 1,200 1,700 2,000 2,000 900 1,100 1,300 2,100

MEADVIEW 300 600 900 1,200 1,700 2,000 2,300 2,900

MORENCI 17,000 41,200 15,100 40,000 14,800 43,200 16,400 43,700

PARKER 25,700 43,400 27,000 38,900 27,700 44,800 26,200 46,100

PEACH SPRINGS 2,000 3,600 3,000 4,700 2,900 4,400 3,600 6,400

PHOENIX AMA 84,300 106,900 95,000 102,600 80,500 97,500 94,000 125,100

PINAL AMA 42,500 61,500 49,200 60,000 38,600 51,100 44,800 63,300

PRESCOTT AMA 5,100 10,000 5,700 9,200 4,500 8,200 5,200 10,900

RANEGRAS PLAIN 600 800 1,000 1,400 400 500 400 1,000

SACRAMENTO VALLEY 4,600 6,800 6,000 8,900 4,300 6,100 6,800 12,800

SAFFORD 46,300 82,200 54,000 79,200 41,800 71,300 52,800 82,100

SALT RIVER 78,700 164,700 73,400 159,800 67,400 153,000 74,000 172,400

SAN BERNARDINO VALLEY 1,200 3,900 2,000 4,700 1,900 4,800 1,100 3,000

SAN RAFAEL 500 1,400 600 1,500 500 1,300 500 1,400

SAN SIMON WASH 37,600 58,700 41,900 57,500 24,000 36,200 41,700 66,900

SANTA CRUZ AMA 4,400 9,700 4,900 9,400 5,200 9,700 4,200 10,300

TIGER WASH 500 800 600 900 200 400 500 1,100

TONTO CREEK 17,900 31,600 15,900 31,600 15,100 27,600 16,300 34,800

TUCSON AMA 26,900 62,200 31,900 61,000 24,600 53,300 23,300 62,300

UPPER HASSAYAMPA 14,200 24,500 15,700 23,000 10,600 18,000 12,700 26,500

UPPER SAN PEDRO 9,200 22,400 12,100 22,600 10,800 20,500 9,400 19,600

VERDE RIVER 70,300 122,800 71,900 118,400 62,100 107,700 73,300 140,400

WESTERN MEXICAN DRAINAGE 100 300 100 300 0 100 100 300

WILLCOX 10,800 26,100 14,300 27,000 11,800 26,500 13,400 24,500

YUMA 7,900 12,300 7,700 10,400 8,200 12,500 7,700 12,600

Table 16. Maximum and minimum estimated annual volumes of actual evapotranspiration from groundwater, summarized by basin.

Volume of Estimated Actual Evapotranspiration from Groundwater (acre-ft)
106 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

2004 2005 2006 2007

Minimum Maximum Minimum Maximum Minimum Maximum Minimum Maximum

12,500 41,300 30,900 55,700 17,700 37,900 16,700 34,400

5,700 15,600 9,700 18,800 6,900 16,400 8,000 16,700

9,400 23,100 19,400 33,900 15,300 28,100 14,200 25,100

22,100 51,000 43,900 73,700 34,400 59,400 32,700 52,800

2,200 7,200 3,400 8,300 2,600 8,200 3,600 8,800

100 400 800 1,400 400 700 100 300

3,400 8,800 4,100 8,600 3,900 10,100 3,900 10,000

600 1,600 3,700 6,200 1,400 2,500 700 1,200

3,200 6,700 6,200 9,700 4,900 8,200 4,400 7,100

200 700 400 900 200 900 300 1,000

600 1,800 1,200 2,200 800 2,400 1,100 2,700

3,000 7,600 6,200 10,700 4,200 8,400 3,600 7,300

3,000 7,400 4,400 8,500 2,300 7,700 3,500 7,900

10,900 16,000 29,700 36,000 28,700 33,300 25,500 30,100

700 1,800 3,400 5,100 1,400 2,000 900 1,500

800 2,100 5,000 8,100 2,300 4,100 1,600 2,700

1,300 2,400 2,000 3,700 2,000 2,800 1,700 2,400

26,600 38,500 31,800 44,100 27,900 40,100 30,600 39,500

23,600 40,500 58,700 86,100 42,800 57,900 37,500 49,700

26,100 49,900 39,200 61,700 33,100 57,600 36,000 58,500

700 1,400 2,500 3,700 1,500 2,000 1,200 1,700

2,300 3,100 2,900 3,700 2,500 3,200 2,300 2,900

12,000 42,400 16,400 43,900 11,700 43,400 12,900 46,100

21,800 41,500 29,600 54,300 24,200 44,600 21,200 40,100

2,600 5,000 4,500 7,600 3,100 5,700 2,700 5,000

67,600 104,200 104,700 146,300 84,300 110,100 75,900 97,600

36,700 58,200 60,900 86,500 54,800 75,700 49,700 70,700

3,600 8,900 6,500 12,200 4,200 9,900 4,100 8,900

200 800 2,300 3,900 800 1,500 400 800

3,500 7,900 10,900 19,200 6,400 10,500 4,000 6,500

40,200 81,100 58,800 91,600 45,900 85,600 54,100 93,400

52,000 158,200 80,700 176,300 62,800 165,200 61,700 166,300

900 3,900 3,600 7,100 1,800 6,400 1,800 5,800

400 1,400 600 1,400 700 1,700 600 1,600

36,100 63,500 52,600 77,700 40,900 64,100 44,300 68,200

4,200 9,000 5,900 10,900 5,700 11,800 5,000 10,500

200 700 1,000 1,800 700 1,000 400 800

9,400 28,600 17,600 33,900 13,100 29,200 13,100 29,900

21,600 55,100 38,200 73,000 33,500 69,500 32,000 67,100

7,300 21,500 17,100 29,900 12,000 22,400 10,700 21,300

8,700 18,900 12,000 21,600 10,900 25,100 10,700 24,000

46,800 117,800 74,500 142,100 55,900 119,400 56,100 115,500

0 300 400 900 100 300 0 100

8,900 26,700 16,000 30,800 12,100 30,800 12,700 31,000

6,800 11,500 6,700 11,700 7,400 12,300 6,700 11,700

Basin name

AGUA FRIA

ARAVAIPA CANYON

BIG SANDY

BILL WILLIAMS

BONITA CREEK

BUTLER VALLEY

CIENEGA CREEK

DETRITAL VALLEY

DONNELLY WASH

DOUGLAS

DOUGLAS INA

DRIPPING SPRINGS WASH

DUNCAN VALLEY

GILA BEND

HARQUAHALA INA

HUALAPAI VALLEY

LAKE HAVASU

LAKE MOHAVE

LOWER GILA

LOWER SAN PEDRO

MCMULLEN VALLEY

MEADVIEW

MORENCI

PARKER

PEACH SPRINGS

PHOENIX AMA

PINAL AMA

PRESCOTT AMA

RANEGRAS PLAIN

SACRAMENTO VALLEY

SAFFORD

SALT RIVER

SAN BERNARDINO VALLEY

SAN RAFAEL

SAN SIMON WASH

SANTA CRUZ AMA

TIGER WASH

TONTO CREEK

TUCSON AMA

UPPER HASSAYAMPA

UPPER SAN PEDRO

VERDE RIVER

WESTERN MEXICAN DRAINAGE

WILLCOX

YUMA

Table 16. Maximum and minimum estimated annual volumes of actual evapotranspiration from groundwater, 

summarized by basin. —Continued
Tables 1–29 107

Table 17. Comparison of maximum and minimum estimated annual volume of actual evapotranspiration (AET) for 

the 2000–2007 time period (this study) to predevelopment ET and potential ET.

2000–2007 Average annual AET (acre-ft) Predevelopment ET1

(acre-ft)

Potential ET2

(acre-ft)

Basin name Minimum Maximum

AGUA FRIA 20,700 41,500 10,400 150,400

ARAVAIPA CANYON 7,100 15,900 4,800 53,400

BIG SANDY 14,500 25,900 18,400 115,200

BILL WILLIAMS 34,400 56,900 22,600 234,000

BONITA CREEK 2,900 7,600 500 29,700

BUTLER VALLEY 300 600 <100 5,200

CIENEGA CREEK 3,700 9,300 <100 30,200

DETRITAL VALLEY 1,200 2,200 <100 43,100

DONNELLY WASH 4,500 7,300 4,000 24,300

DOUGLAS 300 800 17,000 4,500

DOUGLAS INA 900 2,100 included in Douglas estimate 11,600

DRIPPING SPRINGS WASH 4,100 8,100 9,800 29,100

DUNCAN VALLEY 3,300 7,000 4,300 38,900

GILA BEND 24,700 29,000 35,000 91,000

HARQUAHALA INA 1,600 2,400 100 12,800

HUALAPAI VALLEY 1,800 3,200 <100 35,900

LAKE HAVASU 1,800 2,600 40,400 26,800

LAKE MOHAVE 29,900 40,300 153,800 120,200

LOWER GILA 38,000 51,700 72,300 305,400

LOWER SAN PEDRO 32,400 54,400 25,000 165,700

MCMULLEN VALLEY 1,400 2,000 100 8,600

MEADVIEW 1,900 2,500 <100 9,900

MORENCI 14,500 43,000 16,900 131,800

PARKER 25,400 44,200 233,000 175,100

PEACH SPRINGS 3,100 5,300 1,200 30,300

PHOENIX AMA 85,800 111,300 104,100 334,100

PINAL AMA 47,200 65,900 34,900 219,700

PRESCOTT AMA 4,900 9,800 2,400 30,900

RANEGRAS PLAIN 800 1,300 <100 17,100

SACRAMENTO VALLEY 5,800 9,800 1,000 83,200

SAFFORD 49,200 83,300 104,700 272,100

SALT RIVER 68,800 164,500 37,100 438,400

SAN BERNARDINO VALLEY 1,800 5,000 7,500 27,200

SAN RAFAEL 600 1,500 2,800 4,900

SAN SIMON WASH 39,900 61,600 9,600 191,700

SANTA CRUZ AMA 4,900 10,200 11,100 31,200

TIGER WASH 500 900 <100 5,400

TONTO CREEK 14,800 30,900 6,000 85,800

TUCSON AMA 29,000 62,900 53,200 233,900

UPPER HASSAYAMPA 12,500 23,400 6,000 74,600

UPPER SAN PEDRO 10,500 21,800 21,600 80,800

VERDE RIVER 63,900 123,000 65,200 352,000

WESTERN MEXICAN DRAINAGE 100 300 <100 6,300

WILLCOX 12,500 27,900 45,000 81,700

YUMA 7,400 11,900 54,000 24,900

1

Predevelopment ET values adapted from Freethey and Anderson (1986). 

2

Potential ET values used in Basin Characteristic Model (BCM; Flint and Flint, 2007a). Values are average over

1971–2000 time period and are summed over same area as maximum and minimum ET estimates. 

 
108 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Table 18. Estimated groundwater inflow to and outflow from alluvial basins in Arizona for time periods indicated.

[ Values in acre-ft (rounded). INA, Irrigation Non-Expansion Area; AMA, Active Manangement Area.]

Basin name

Predevelopment Conditions1 2005 Conditions

Data source for 2005 conditions

IN OUT IN OUT

Groundwater 

underflow 

(acre-ft)

Groundwater 

underflow 

(acre-ft)

Groundwater

 underflow 

(acre-ft)

Groundwater 

underflow 

(acre-ft)

AGUA FRIA 0 0 0 0 Arizona Department of Water Resources, 

2009c Freethey and Anderson, 1986

ARAVAIPA CANYON 0 200 0 200 Freethey and Anderson, 1986

BIG SANDY 300 1,000 300 1,000 Freethey and Anderson, 1986

BILL WILLIAMS 1,000 300 1,000 300 Freethey and Anderson, 1986

BONITA CREEK 0 6,300 0 6,300 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986 

BUTLER VALLEY 0 300 0 300 Freethey and Anderson, 1986

CIENEGA CREEK 0 2,300 0 2,300 Freethey and Anderson, 1986

DETRITAL VALLEY 0 700 0 700 Freethey and Anderson, 1986

DONNELLY WASH 0 100 0 100 Freethey and Anderson, 1986

DOUGLAS 0 3,000 0 1,900 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

DOUGLAS INA Included in Douglas Basin Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

DRIPPING SPRINGS WASH 0 200 0 200 Freethey and Anderson, 1986

DUNCAN VALLEY 12,000 200 12,000 200 Freethey and Anderson, 1986

GILA BEND 5,000 2,000 7,500 2,000 Arizona Department of Water Resources, 

2009d Freethey and Anderson, 1986

HARQUAHALA INA 800 800 700 500 Arizona Department of Water Resources, 

2009d Freethey and Anderson, 1986

HUALAPAI VALLEY 300 3,800 300 3,800 Freethey and Anderson, 1986

LAKE HAVASU 600 500 600 500 Freethey and Anderson, 1986

LAKE MOHAVE 0 300 0 300 Freethey and Anderson, 1986

LOWER GILA 2,000 1,000 2,000 600 Arizona Department of Water Resources, 

2009d Freethey and Anderson, 1986

LOWER SAN PEDRO 1,400 0 1,400 0 Freethey and Anderson, 1986

MCMULLEN VALLEY 0 800 0 700 Freethey and Anderson, 1986

MEADVIEW 0 3,800 0 3,800 Freethey and Anderson, 1986

MORENCI 0 200 0 200 Freethey and Anderson, 1986

PARKER 400 200 900 200 Freethey and Anderson, 1986

PEACH SPRINGS 0 0 0 0 Arizona Department of Water Resources, 

2009b Freethey and Anderson, 1986

PHOENIX AMA 28,300 5,000 20,500 30,500 Arizona Department of Water Resources, 

2009e Freethey and Anderson, 1986 

Corkhill and Hill, 1990 

Freihoefer and others, 2009

PINAL AMA 15,000 36,800 54,300 18,800 Arizona Department of Water Resources, 

2009e Freethey and Anderson, 1986 

Corkhill and Hill, 1990 

Freihoefer and others, 2009

PRESCOTT AMA 0 500 0 1,400 Arizona Department of Water Resources, 

2009e Freethey and Anderson, 1986 

Timmons and Springer, 2006

RANEGRAS PLAIN 300 400 300 860 Arizona Department of Water Resources, 

2009d Freethey and Anderson, 1986

SACRAMENTO VALLEY 0 4,000 0 2,000 Anning and others, 2006 Freethey and 

Anderson, 1986
Tables 1–29 109

SAFFORD 9,300 0 6,300 0 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

SALT RIVER 0 0 0 0 Arizona Department of Water Resources, 

2009c Freethey and Anderson, 1986

SAN BERNARDINO VALLEY 0 500 0 500 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

SAN RAFAEL 0 0 1,000 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

SAN SIMON WASH 1,800 500 1,800 500 Arizona Department of Water Resources, 

2009d Freethey and Anderson, 1986

SANTA CRUZ AMA 9,500 13,900 8,100 24,000 Arizona Department of Water Resources, 

2009e Freethey and Anderson, 1986 

Mason and Bota, 2006 Nelson, 2007

TIGER WASH 0 0 0 0 Freethey and Anderson, 1986

TONTO CREEK 0 0 0 0 Arizona Department of Water Resources, 

2009c Freethey and Anderson, 1986

TUCSON AMA 19,000 15,900 26,000 14,500 Arizona Department of Water Resources, 

2009e Freethey and Anderson, 1986 

Mason and Bota, 2006 Nelson, 2007

UPPER HASSAYAMPA 0 500 0 500 Freethey and Anderson, 1986

UPPER SAN PEDRO 0 1,000 0 1,000 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

VERDE RIVER 2,400 0 1,400 0 Arizona Department of Water Resources, 

2009a Arizona Department of Water 

Resources, 2009e 

Freethey and Anderson, 1986 

Timmons and Springer, 2006

WESTERN MEXICAN 

DRAINAGE

0 2,400 0 2,400 Freethey and Anderson, 1986

WILLCOX 0 0 0 0 Arizona Department of Water Resources, 

2009a Freethey and Anderson, 1986

YUMA 1,000 141,000 600 266,000 Freethey and Anderson, 1986 

Dickinson and others, 2006 Hill, 1993

1

 Source for all predevelopment data: Freethey and Anderson (1986).

Table 18. Estimated groundwater inflow to and outflow from alluvial basins in Arizona for time periods indicated. —Continued

[ Values in acre-ft (rounded). INA, Irrigation Non-Expansion Area; AMA, Active Manangement Area.]

Basin name

Predevelopment Conditions1 2005 Conditions

Data source for 2005 conditions

IN OUT IN OUT

Groundwater 

underflow 

(acre-ft)

Groundwater 

underflow 

(acre-ft)

Groundwater

 underflow 

(acre-ft)

Groundwater 

underflow 

(acre-ft)
110 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Table 19. Streamflow gages used in analysis of aquifer recharge from stream seepage.

Runoff/

seepage 

region1

Gaging 

station 

number

Gaging station name Period of 

record

Drainage 

area, in 

square 

miles

Mean annual 

flow, in cubic 

feet per 

second

Gain or 

loss in flow 

above gage

2 09424447 Burro Creek nr Bagdad 1980–2008 611 95.0 gain

2 09424450 Big Sandy River nr Wikeiup 1966–2008 2,742 92.8 gain

2 09424900 Santa Maria River nr Bagdad 1966–2008 1,129 56.2 gain

2 09425500 Santa Maria River nr Alamo 1939–1966 1,439 31.0 gain

2 09426500 Bill Williams River at Planet 1927–1946 5,054 152.0 loss

2 09512500 Agua Fria River nr Mayer 1940–2008 585 22.8 gain

2 09512800 Agua Fria River nr Rock Springs 1970–2008 1,111 81.2 gain

2 09515500 Hassayampa River at box damsite nr 

Wickenburg

1938–1982 417 24.4 gain

2 09516500 Hassayampa River nr Morristown 1938–2008 796 26.5 gain

3 09535100 San Simon Wash nr Pisinimo 1972–2008 569 3.6 loss

3 09535300 Vamori Wash at Kom Vo 1972–2007 1,250 9.9 loss

4 09488500 Santa Rosa Wash nr Sells 1955–1980 1,782 11.0 loss

4 09489000 Santa Cruz River nr Laveen 1940–2008 8,581 18.1 loss

4 09512280 Cave Creek nr Cave Creek 1980–2008 83 6.3 gain

4 09513780 New River nr Rock Springs 1962–2008 68 12.4 gain

4 09513800 New River at New River 1961–1982 83 14.0 loss

4 09513835 New River at Bell Road nr Peoria 1968–1993 185 14.0 loss

4 09513860 Skunk Creek nr Phoenix 1960–2008 65 1.5 loss

4 09517000 Hassayampa River nr Arlington 1959–2008 1,471 62.5 loss

5 09503700 Verde River nr Paulden 1963–2008 2,150 44.7 gain

5 09504000 Verde River nr Clarkdale 1915–2008 3,124 181.0 gain

5 09504420 Oak Creek nr Sedona 1981–2008 233 81.3 gain

5 09504500 Oak Creek nr Cornville 1940–2008 355 86.5 gain

5 09506000 Verde River nr Camp Verde 1934–2008 4,645 408.0 gain

5 09507980 East Verde River nr Childs 1961–2008 331 63.4 gain

5 09508500 Verde River blw Tangle Creek abv 

Horseshoe Dam

1930–2008 5,494 455.0 gain

5 09510200 Sycamore Creek nr Fort McDowell 1960–2008 164 26.3 gain

6 09489100 Black River nr Maverick 1963–1982 315 141.0 gain

6 09489500 Black River nr Point of Pines 1953–2008 560 202.7 gain

6 09490500 Black River nr Fort Apache 1912–2008 1,232 392.0 gain

6 09494000 White River nr Fort Apache 1917–2008 632 164.2 gain

6 09497500 Salt River nr Chrysotile 1924–2008 2,849 646.0 gain

6 09497800 Cibeque Creek nr Chrysotile 1959–2008 295 44.0 gain

6 09497900 Cherry Creek nr Young 1963–1978 62 10.2 gain

6 09497980 Cherry Creek nr Globe 1965–2008 200 32.1 gain

6 09498500 Salt River nr Roosevelt 1910–2008 4,306 877.0 gain

6 09498800 Tonto Creek nr Gisela 1965–1975 430 120.0 gain

6 09499000 Tonto Creek abv Gun Creek nr Roosevelt 1940–2008 675 150.0 gain

7 09430500 Gila River nr Gila, NM 1928–2008 1,864 157.0 gain
Tables 1–29 111

7 09431500 Gila River nr Redrock, NM 1930–2008 2,829 242.0 gain

7 09432000 Gila River blw Blue Creek nr Virden 1927–2008 3,203 211.0 gain

7 09442000 Gila River nr Clifton 1910–2008 4,010 202.0 gain

7 09444000 San Francisco River nr Glenwood 1927–2008 1,653 87.5 gain

7 09444500 San Francisco River at Clifton 1910–2008 2,763 219.0 gain

7 09446500 Eagle Creek nr Double Circle Ranch nr Morenci 1945–1967 377 25.9 gain

7 09447000 Eagle Creek nr Morenci 1944–2008 622 65.4 gain

7 09447800 Bonita Creek nr Morenci 1981–2008 302 11.6 gain

7 09448500 Gila River at Head of Safford Valley 1920–2008 7,896 462.0 gain

7 09457000 San Simon River nr Solomon 1931–1982 2,192 12.0 loss

7 09466500 Gila River at Calva 1929–2008 11,470 372.0 loss

7 09468500 San Carlos River nr Peridot 1930–2008 1,026 59.1 gain

7 09472000 San Pedro River nr Redington 1931–1996 2,927 44.0 loss

7 09472050 San Pedro River at Redington Bridge 1940–2008 3,096 31.6 loss

8 09482500 Santa Cruz River at Tucson 1915–1981 2,222 23.0 loss

8 09483100 Tanque Verde Creek nr Tucson 1960–1996 43 8.9 loss

8 09484500 Tanque Verde Creek at Tucson 1940–2008 219 23.7 loss

8 09484600 Pantano Wash nr Vail 1959–2008 457 6.3 gain

8 09485000 Rincon Creek nr Tucson 1952–2008 45 6.0 gain

8 09484000 Sabino Creek nr Tucson 1932–2008 35 13.4 gain

8 09485450 Pantano Wash nr Broadway 1998–2008 599 3.9 loss

8 09485700 Rillito River at Dodge 1987–2008 871 28.0 loss

8 09486000 Rillito River nr Tucson 1915–1983 918 14.0 loss

8 09486055 Rillito River nr LaCholla 1990–2008 922 13.7 loss

8 09486800 Altar Wash nr Three Points 1966–2008 463 5.4 loss

8 09470500 San Pedro River nr Palominas 1930–2008 737 30.3 gain

8 09471000 San Pedro River nr Charleston 1913–2008 1,234 53.8 gain

8 09471550 San Pedro River nr Tombstone 1967–2008 1,740 49.0 gain

8 09471800 San Pedro River nr Benson 1966–2008 2,490 35.2 loss

8 09480000 Santa Cruz River at Lochiel 1949–2008 82 3.6 gain

8 09480500 Santa Cruz River at Nogales 1931–2008 533 25.3 loss

8 09481740 Santa Cruz River at Tubac 1995–2008 1,192 33.6 loss

8 09481770 Santa Cruz River nr Amado 2003–2008 1,461 14.4 loss

8 09482000 Santa Cruz River nr Continental 1940–2008 1,682 22.7 loss

8 09484550 Cienega Creek nr Sonoita 2001–2008 198 1.9 gain

8 09537500 Whitewater Draw nr Douglas 1916–2008 1,023 9.0 loss

1

Runoff/seepage region shown in figure 32.

Table 19. Streamflow gages used in analysis of aquifer recharge from stream seepage.—Continued

Runoff/

seepage 

region1

Gaging 

station 

number

Gaging station name Period of 

record

Drainage 

area, in 

square 

miles

Mean annual 

flow, in cubic 

feet per 

second

Gain or 

loss in flow 

above gage
112 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Table 20. Streams with multiple gages used for analysis of 

aquifer recharge from stream seepage.

Runoff region1 River

Number of 

gages on 

stream

Gain or 

loss in flow 

between 

gages

Western Upland Santa Maria River 2 gain

Agua Fria River 2 gain

Hassayampa River 3 gain/loss

Western Lowland New River 3 loss

Central Upland 

and Northeastern 

Gila River

Verde River 4 gain

Oak Creek 2 gain

Black River 3 gain

Salt River 2 gain

Cherry Creek 2 gain

Tonto Creek 2 gain

Gila River 6 gain/loss

San Francisco 

River

2 gain

Eagle Creek 2 gain

Tanque Verde 

Creek

2 loss

Pantano Wash 2 loss

Rillito River 3 loss

Southeastern Santa Cruz River 7 gain/loss

Gila River San Pedro River 6 gain/loss

1

Runoff region shown in figure 19.
Tables 1–29 113

Table 21. Estimated volume of mean annual streamflow, which represents water potentially available for recharge by 

seepage from streams for predevelopment (pre-dam) and modern (post-dam) time periods in basins of the Southwest 

Alluvial Basins in Arizona.

[Although 75 streamgages were analyzed in this study, results from only 28 streamgages downstream of the 47 others are presented in this 

table as they integrate flow information from all upstream gages.]

Runoff region1 

(source area) Streamflow gages in runoff basin Seepage region1

(seepage area)

Mean annual streamflow 

available for seepage2

Pre-dam Post-dam

(acre-ft) (acre-ft)

2 Big Sandy River nr Wikeiup (09424450)32 67,200 0

Santa Maria River nr Bagdad (09424900)3 40,700 0

2 Hassayampa River nr Arlington (09517000) 4 45,300 45,300

Agua Fria River nr Rock Springs (09512800)4 58,800 0

3 San Simon Wash nr Pisinimo (09535100) 3 2,600 2,600

Vamori Wash at Kom Vo (09535300) 7,200 7,200

4

Cave Creek nr Cave Creek (09512280)

4

4,600 4,600

New River at New River (09513800) 10,100 10,100

Skunk Creek nr Phoenix (09513860) 1,100 1,100

Santa Rosa Wash nr Sells (09488500) 8,000 8,000

5

Verde River blw Tangle Creek abv 

Horseshoe Dam (09508500)5

4

329,000 0

Sycamore Creek nr Fort McDowell (09510200) 19,000 19,000

6 Tonto Creek abv Gun Creek nr Roosevelt (09499000)6

4 108,600 0

Salt River nr Roosevelt (09498500)6 635,000 0

7

San Carlos River nr Peridot (09468500)7

4

42,800 0

Gila River at head of Safford Valley (09448500)7,8 335,000 0

Aravaipa Creek nr Mammoth (09473000) 25,200 25,200

San Simon River nr Solomon (09457000) 8,700 0

7

San Pedro River nr Redington (09472000)

7

7

32,000 32,000

Pantano Wash nr Vail (09484600) 4,500 4,500

Tanque Verde Creek at Tucson (09484500) 17,100 17,100

Rincon Creek nr Tucson (09485000) 4,400 4,400

Sabino Creek nr Tucson (09484000) 9,700 9,700

Santa Cruz River at Tucson (09482500) 16,700 16,700

8

San Pedro River nr Charleston (09471000)

8

38,900 38,900

Whitewater Draw nr Douglas (09537500) 6,500 6,500

Santa Cruz River nr Nogales (09480500) 18,300 18,300

Altar Wash nr Three Points (09486800) 3,900 3,900

1

Runoff and seepage regions shown in figure 32.

2

The mean annual volumes of streamflow are from measured flows at gaging stations. These values represent the maximum amount of 

water available for seepage downstream of the gage.

3

Streamflow is now stored in Alamo Lake (Alamo Dam built in 1968).

4

Streamflow is now stored in Lake Pleasant (Waddell Dam built in 1920s and raised in 1992).

5

Streamflow is now stored in Horseshoe Reservoir (Horseshoe dam built in 1911).

6

Streamflow is now stored in Theodore Roosevelt Lake (Roosevelt Dam built in 1911).

7

Streamflow is now stored in San Carlos Reservoir (Coolidge dam built in 1928).

8

Runoff in the upper Gila basin includes runoff from the Morenci and Bonita Creek basins in Arizona and the upper Gila basin in New 

Mexico. Runoff becomes seepage in the Safford north basin and the Phoenix AMA basin. 
114 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Table 22. Volumes of mean annual streamflow available for 

recharge by seepage from streams in runoff regions of the 

Southwest Alluvial Basins in Arizona.

Runoff 

region1

(source area)

Seepage region1

(seepage area)

Mean annual streamflow 

available for seepage2

Pre-dam 

(acre-ft)

Post-dam 

(acre-ft)

2 2 (lower watershed) 107,900 0

2 4 52,050 45,300

5 and 6 4 1,091,600 19,000

73 4 411,700 25,200

1

Runoff and seepage regions shown in figure 32. In the internal drainages 

of regions 1, 3, 4, and 8, much of the streamflow available for seepage is not 

measured by streamgages and is thus not summarized in this table.

2

The mean annual volumes of streamflow are from measured flows at 

gaging stations. These values represent the maximum amount of water 

available for seepage downstream of the gage.

3

Presumes most of the flow measured by gage 09448500 on the Gila River 

and flow measured by three tributaries (table 21) flows through the region 

and then seeps into region 4 downstream.

Basin name

Predevelopment 

groundwater recharge 

from streamflow

Predevelopment 

groundwater 

discharge to 

streamflow

acre-ft per year acre-ft per year

Agua Fria 12,880 4,275

Aravaipa Canyon 0 2,000

Big Sandy 0 2,200

Bill Williams 1,000 9,800

Bonita Creek 235 2,115

Butler Valley 0 0

Cienega Creek 0 8,500

Detrital Valley 0 0

Donnelly Wash 900 0

Douglas 0 2,000

Douglas INA estimates included in Douglas Basin

Dripping Springs Wash 7,000 0

Duncan Valley 0 3,250

Gila Bend 31,200 0

Harquahala INA 0 0

Hualapai Valley 0 0

Lake Havasu 37,403 0

Lake Mohave 161,550 0

Lower Gila 128,745 0

Lower San Pedro 4,600 0

McMullen Valley 0 0

Meadview 0 0

Morenci 2,528 19,280

Parker 232,625 0

Peach Springs 0 0

Phoenix AMA 73,730 0

Pinal AMA 21,260 0

Prescott AMA 0 2,225

Ranegras Plain 0 0

Sacramento Valley 8,563 0

Safford 45,470 0

Salt River 2,084 160,220

San Bernardino Valley 0 1,000

San Rafael 175 0

San Simon Wash 0 0

Santa Cruz AMA 700 0

Tiger Wash 0 0

Tonto Creek 0 17,040

Tucson AMA 7,625 0

Upper Hassayampa 0 1,500

Upper San Pedro 1,600 7,000

Verde River 4,056 60,300

Western Mexican Drainage 0 0

Willcox 0 0

Yuma 21,775 0

Table 23. Estimates of predevelopment groundwater recharge 

from and discharge to streams in the Southwest Alluival Basins of 

Arizona. Estimates adapted from SWAB-RASA studies (Freethey 

and Anderson, 1986).
Tables 1–29 115

Table 24. Estimated annual groundwater and surface-water withdrawals for irrigation in alluvial basins in Arizona where data are 

available for time periods indicated.

 [Values in acre-ft (rounded). INA, Irrigation Non-Expansion Area; AMA, Active Manangement Area; < less than; ≥ greater than or equal to; NR, not reported.]

Basin name

1980 Groundwater 

withdrawals 

(acre-ft)

1980 Surface-water 

withdrawals 

(acre-ft)

1980 Total irrigation 

withdrawals 

(acre-ft)

2005 Groundwater withdrawals 

(acre-ft)

2005 Surface-water 

withdrawals 

(acre-ft)

2005 Total irrigation 

withdrawals

 (acre-ft)

Agua Fria 1,500 NR ≥1,500 1,400 NR ≥1,400

Aravaipa Canyon <1,000 <1,000 <1,000 <1,000 <1,000 <1,000

Bill Williams Wash 17,000 NR ≥17,000 5,400 NR ≥5,400

Butler Valley 3,400 NR ≥3,400 9,800 NR ≥9,800

Cienega Creek <1,000 NR <1,000 <1,000 NR <1,000

Douglas1 87,000 NR ≥87,000 40,500 NR ≥40,500

Duncan Valley 20,500 16,000 36,500 7,200 14,500 22,000

Gila Bend 273,000 102,000 375,000 287,000 55,500 343,000

Harquahala INA 110,000 NR ≥110,000 43,500 44,500 88,000

Lake Mohave 14,500 47,000 61,500 26,000 72,500 98,500

Lower Gila 429,000 328,000 757,000 118,000 349,000 467,000

Lower San Pedro 21,500 <1,000 <22,400 10,000 <1,000 <11,000

McMullen Valley 119,000 NR ≥119,000 81,000 NR ≥81,000

Parker <1,000 594,000 <595,000 <1,000 614,000 <615000

Phoenix AMA 908,000 601,000 1,509,000 354,000 632,000 986,000

Pinal AMA 830,000 276,000 1,106,000 370,000 584,000 954,000

Prescott AMA 5,200 3,200 8,400 2,100 1,200 3,300

Ranegras Plain 10,500 NR ≥10,500 27,500 NR ≥27,500

Safford 176,000 86,000 262,000 90,500 103,000 194,000

Salt River <1,000 6,000 <7,000 <1,000 <1,000 <1,000

San Simon Wash 3,500 NR ≥3,500 3,900 NR ≥3,900

Santa Cruz AMA 7,500 NR ≥7,500 12,000 NR ≥12,000

Tonto Creek <1,000 <1,000 <2,000 <1,000 <1,000 <1,000

Tucson AMA 117,000 <1,000 <118,000 68,500 41,000 110,000

Upper San Pedro 13,500 4,300 18,000 14,500 2,300 17,000

Verde River 9,000 16,000 25,000 11,000 18,000 29,000

Willcox 199,000 NR ≥199,000 182,000 NR ≥182,000

Yuma 239,000 689,000 928,000 96,000 729,000 825,000

1

 Withdrawal values include withdrawals from Douglas INA. 
116 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Table 25. Estimated annual groundwater withdrawals for public supply for alluvial basins in Arizona for 

time periods indicated. 

[Values in acre-ft (rounded). INA, Irrigation Non-Expansion Area; AMA, Active Manangement Area; < less than.]

Basin name

1980 Public supply 

groundwater withdrawals 

(acre-ft)

2005 Public supply groundwater withdrawals 

(acre-ft)

AGUA FRIA 1,400 1,800

ARAVAIPA CANYON <300 <300

BIG SANDY <300 <300

BILL WILLIAMS 500 800

BONITA CREEK 2,700 3,300

BUTLER VALLEY <300 <300

CIENEGA CREEK 500 600

DETRITAL VALLEY <300 <300

DONNELLY WASH <300 <300

DOUGLAS1 5,400 5,300

DRIPPING SPRINGS WASH <300 <300

DUNCAN VALLEY 600 600

GILA BEND 800 800

HARQUAHALA INA <300 <300

HUALAPAI VALLEY 4,800 9,100

LAKE HAVASU 13,000 13,500

LAKE MOHAVE 6,000 21,000

LOWER GILA 1,800 1,700

LOWER SAN PEDRO 3,000 2,300

MCMULLEN VALLEY <300 500

MEADVIEW <300 <300

MORENCI 1,000 1,700

PARKER 3,000 3,800

PEACH SPRINGS <300 400

PHOENIX AMA 264,000 226,000

PINAL AMA 11,500 39,500

PRESCOTT AMA 4,600 14,600

RANEGRAS PLAIN <300 400

SACRAMENTO VALLEY 1,000 2,300

SAFFORD 3,000 3,500

SALT RIVER 5,000 4,100

SAN BERNARDINO VALLEY <300 <300

SAN RAFAEL <300 <300

SAN SIMON WASH 900 1,000

SANTA CRUZ AMA 2,500 9,000

TIGER WASH <300 <300

TONTO CREEK 1,600 2,500

TUCSON AMA 103,000 104,000

UPPER HASSAYAMPA 2,200 2,500

UPPER SAN PEDRO 15,000 17,500

VERDE RIVER 10,000 15,500

WESTERN MEXICAN DRAINAGE <300 <300

WILLCOX 2,000 2,800

YUMA 8,600 13,500

1

 Withdrawal values include withdrawals from Douglas INA.
Tables 1–29 117

Table 26. Irrigation system efficiencies assumed for the 

Southwest Alluvial Basins study area.

Irrigation system type Efficiency1

Drip 90%

Sprinkler and Center Pivot 80%

Flood 60%

1

 S. Tadayon, oral commun., 2009. 

Table 27. Estimated annual recharge from irrigation in alluvial 

basins in Arizona for time periods indicated.

 [Values in acre-ft (rounded); INA, Irrigation Non-Expansion Area; AMA, 

Active Manangement Area; < , less than.]

Basin name

1980 Irrigation 

incidental recharge 

(acre-ft)

2005 Irrigation 

incidental recharge 

(acre-ft)

Agua Fria <1,000 <1,000

Aravaipa Canyon <1,000 <1,000

Bill Williams Wash 5,100 2,200

Butler Valley 1,400 2,000

Cienega Creek <1,000 <1,000

Douglas1 22,000 8,500

Duncan Valley 14,500 8,500

Gila Bend 121,000 137,000

Harquahala INA 37,500 31,000

Lake Mohave 27,000 39,500

Lower Gila 19,000 22,500

Lower San Pedro 9,000 2,400

McMullen Valley 40,500 27,500

Parker 238,000 258,000

Phoenix AMA 499,000 347,000

Pinal AMA 442,000 394,000

Prescott AMA 3,400 1,700

Ranegras Plain 2,100 2,800

Safford 105,000 74,000

Salt River 1,400 <1,000

San Simon Wash 1,400 1,600

Santa Cruz AMA 3,000 5,000

Tonto Creek <1,000 <1,000

Tucson AMA 46,500 37,500

Upper San Pedro 6,200 4,900

Verde River 10,000 11,000

Willcox 66,000 41,500

Yuma 230,000 169,000

1

 Includes incidental recharge from Douglas INA.
118 Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability, Arizona

Basin name Storage change 

(acre-ft)

BUTLER VALLEY -159,000

DOUGLAS -92,000

DOUGLAS INA -1,622,000

HARQUAHALA INA -1,984,000

LOWER SAN PEDRO -380,000

MCMULLEN VALLEY -4,413,000

PHOENIX AMA -30,250,000

PINAL AMA -11,047,000

PRESCOTT AMA -899,000

RANEGRAS PLAIN -993,000

SAFFORD -12,089,000

SANTA CRUZ AMA -66,000

TUCSON AMA -5,317,000

UPPER SAN PEDRO -461,000

WILLCOX -4,691,000

Table 29. Estimated change in groundwater storage since 

predevelopment times for the most developed basins in the 

Southwest Alluvial Basins study area.

[Storage change estimate does not include loss of storage from land subsidence. Negative values represent removal of groundwater from aquifer 

storage. Estimation method based on water-level change over period of 

development and assumed storage coefficients.]

Basin name

2005 Estimated 

recharged effluent 

(acre-ft)

Data source

LAKE HAVASU 600 Arizona Department of Water Resources1

LAKE MOHAVE 1,100 Arizona Department of Water Resources1

LOWER SAN PEDRO <300 Arizona Department of Water Resources1

PARKER 400 Arizona Department of Water Resources1

PEACH SPRINGS <300 Arizona Department of Water Resources1

PHOENIX AMA 34,000 Arizona Department of Water Resources1

PINAL AMA 4,000 Arizona Department of Water Resources1

PRESCOTT AMA 2,200 Arizona Department of Water Resources1, 

City of Prescott (2007)

SALT RIVER <300 Arizona Department of Water Resources1

SANTA CRUZ AMA <300 Arizona Department of Water Resources1, 

Pima County (2006)

TUCSON AMA 48,500 Arizona Department of Water Resources1

, 

Pima County (2006)

UPPER HASSAYAMPA <300 Arizona Department of Water Resources1

UPPER SAN PEDRO 3,000 Arizona Department of Water Resources1, 

Upper San Pedro Partnership (2006)

VERDE RIVER 1,100 Arizona Department of Water Resources1

YUMA 600 Arizona Department of Water Resources1

1

K. M. Lacroix, written comun., 2009.

Table 28. Estimated annual recharge from treated effluent in alluvial basins in 

Arizona for 2005.

[AMA, Active Manangement Area; < , less than.]
Produced in the Menlo Park Publishing Service Center, California

Manuscript approved for publication May 12, 2011

Text edited by Peter Stauffer

Layout and design by Judy Weathers
Great Lakes 

Basin

Southwest 

Alluvial Basins

Tillman and others—Water Availability and Use Pilot: Methods Development for a Regional Assessment of Groundwater Availability,  Southwest Alluvial Basins, Arizona–Scientific Investigations Report 2011-5071