Muscoy plume

Newmark plume

Fault San Andreas

Redlands plume

(1900)

Former

marshland

Crafton

Hills

Seven Oaks

Dam

Redlands

San Bernardino

Mill

River

The

Zanja

Santa

Ana

Lytle Creek

Cr

San Bernardino Mountains

Yucaipa Basin

Hydrology, Description of Computer Models, and

Evaluation of Selected Water-Management Alternatives

in the San Bernardino Area, California

In cooperation with the

San Bernardino Valley Municipal Water District

U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

U.S. Geological Survey Open-File Report 2005-1278

Pending release as USGS Professional Paper 1734
Cover. Oblique view showing the San Bernardino Mountains rising above the Bunker Hill and Lytle Creek basins. The 

area simulated with the ground-water flow model is outlined in white. Also shown are selected water-management 

issues including the former marshland, Seven Oaks Dam, and the Newmark, Muscoy, and Redlands plumes.
Hydrology, Description of Computer 

Models, and Evaluation of Selected 

Water-Management Alternatives 

in the San Bernardino Area, California

By Wesley R. Danskin, Kelly R. McPherson, and Linda R. Woolfenden

In cooperation with the San Bernardino Valley Municipal Water District

Open-File Report 2005-1278

Pending release as USGS Professional Paper 1734

U.S. Department of the Interior

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

Dirk Kempthorne, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2006

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

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

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

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 materials contained within this report.

Suggested citation:

Danskin, W.R., McPherson, K.R., and Woolfenden, L.R., 2006, Hydrology, Description of Computer Models, and 

Evaluation of Selected Water-Management Alternatives in the San Bernadino Area, California: U.S. Geological 

Survey Open-File Report 2005-1278, 178 p. and 2 pl.
iii

Contents

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

Introduction.....................................................................................................................................................3

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

Description of Study Area ...................................................................................................................7

Previous Investigations........................................................................................................................9

Acknowledgments..............................................................................................................................14

Hydrology ......................................................................................................................................................15

Surface-Water System ......................................................................................................................15

Sources of Inflow and Outflow................................................................................................19

Gaged Runoff.....................................................................................................................19

Ungaged Runoff ................................................................................................................24

Local Runoff.......................................................................................................................26

Imported Water.................................................................................................................29

Wastewater Discharge....................................................................................................29

Ground-Water Discharge into Warm Creek.................................................................31

Diversions....................................................................................................................................32

Ground-Water System .......................................................................................................................32

Description of Valley-Fill Aquifer.............................................................................................33

Recharge and Natural Discharge ...........................................................................................35

Recharge from Gaged Streamflow ................................................................................35

Recharge from Ungaged Runoff.....................................................................................39

Recharge from Direct Precipitation...............................................................................40

Recharge from Local Runoff ...........................................................................................40

Artifical Recharge from Imported Water......................................................................41

Return Flow from Pumpage.............................................................................................41

Underflow...........................................................................................................................42

Ground-Water Discharge into Warm Creek.................................................................46

Evapotranspiration. ...................................................................................................................46

Pumpage......................................................................................................................................47

Ground-Water Storage .............................................................................................................52

Ground-Water Budget...............................................................................................................53

Ground-Water Movement ........................................................................................................56

Ground-Water Quality ...............................................................................................................59

Computer Models.........................................................................................................................................61

Ground-Water Flow Model................................................................................................................61

Conceptual Model .....................................................................................................................63

Relation to Previous Flow Model ............................................................................................64

Design and Discretization ........................................................................................................64

Aquifer Parameters ...................................................................................................................69

Recharge and Discharge..........................................................................................................70

Calibration...................................................................................................................................76

Evaluation....................................................................................................................................81
iv

Sensitivity Analysis....................................................................................................................81

Use and Limitations ...................................................................................................................82

Constrained Optimization Model......................................................................................................84

General Characteristics............................................................................................................85

Representation of the Ground-Water Flow System.............................................................89

Mathematical Form of Objectives and Constraints..............................................................95

Objective Function............................................................................................................96

Constraints.........................................................................................................................98

Water Supply and Water Distribution ..................................................................98

Ground-Water Level ................................................................................................98

Ground-Water Quality .............................................................................................99

Economic.................................................................................................................100

Bounds..............................................................................................................................100

Use and Limitations .................................................................................................................101

Evaluation of Selected Water-Management Alternatives..................................................................103

Water-Management Issues ............................................................................................................104

Description of Water-Management Alternatives........................................................................107

Simulated Scenarios ........................................................................................................................109

Selection and Design of Scenarios ......................................................................................109

Scenario 1: Average Recharge and Discharge, 1999–2030 ..............................................109

Scenario 2: Annual Variations in Recharge and Discharge, 1999–2030 .........................111

Scenario 3: Increased Recharge Made Possible by Seven Oaks Dam, 1999–2030......114

Scenario 4: Increased Pumpage Using Existing Wells, 1999–2030 .................................115

Scenario 5: Optimal Hydraulic Containment of Contaminated Ground 

Water in the Newmark Area.....................................................................................120

Scenario 6: Optimal Pumpage Using New Wells to Control Ground-Water 

Levels in the Former Marshland ..............................................................................123

Discussion..........................................................................................................................................129

Suggestions for Future Work ...................................................................................................................131

Data.....................................................................................................................................................133

Concepts.............................................................................................................................................133

Models................................................................................................................................................ 134

Management......................................................................................................................................134

Summary and Conclusions.......................................................................................................................135

Ground-Water Recharge .................................................................................................................135

Ground-Water Discharge ................................................................................................................135

Ground-Water Storage ....................................................................................................................136

High Ground-Water Levels..............................................................................................................136

Liquefaction .......................................................................................................................................136

Land Subsidence...............................................................................................................................136

Water Quality.....................................................................................................................................136

Basin Yield..........................................................................................................................................136

Meeting Future Demand for Water................................................................................................138

Models................................................................................................................................................138

References Cited........................................................................................................................................138

Additional Tables........................................................................................................................................147
v

Figures

Figure 1. Map showing location of the San Bernardino area in the Santa Ana River 

 drainage basin, southern California ........................................................................................4

Figure 2. Map showing geographic setting of the San Bernardino area, California.......................5

Figure 3. Diagram showing major components and flow of information in this study 

 of the San Bernardino area, California. ..................................................................................6

Figure 4. Photograph showing view of the San Bernardino area, California, looking 

 northwest across the Bunker Hill basin, 2004............................................................................8

Figure 5. Map showing generalized surficial geology of the San Bernardino area, 

 California ....................................................................................................................................10

Figure 6. Map showing average annual precipitation in the San Bernardino area, 

 California, 1928–98....................................................................................................................11

Figure 7. Graph showing cumulative departure from average annual precipitation at 

 San Bernardino, California, 1871–1998..................................................................................12

Figure 8. Maps showing changes in land use in the San Bernardino area, California, 

 1933–90 .......................................................................................................................................13

Figure 9. Map showing historical hydrologic conditions in the San Bernardino area, 

 California, circa 1880................................................................................................................16

Figure 10. Photograph showing Urbita Springs area, 1903..................................................................17

Figure 11. Map showing general features of the surface-water system in the 

 San Bernardino area, California, 1998...................................................................................18

Figure 12. Pie chart showing average annual discharge of gaged streams flowing 

 into the San Bernardino area, California, 1945–98..............................................................19

Figure 13. Graphs showing linear-regression relations used to estimate annual stream 

 discharge in the San Bernardino area, California...............................................................20

Figure 14. Graph showing cumulative probability of annual gaged surface-water inflow 

 for the San Bernardino area, California, 1945–98................................................................21

Figure 15. Graph showing cumulative gaged surface-water inflow and outflow in the 

 San Bernardino area, California, 1945–98 ............................................................................22

Figure 16. Graph showing relation between discharge in the Santa Ana River at the 

 base of the mountains and total inflow to the San Bernardino area, 1945–98...............23

Figure 17. Map showing ungaged areas bordering the Bunker Hill and Lytle Creek basins

 in the San Bernardino area, California..................................................................................25

Figure 18. Graph showing components of precipitation on the Bunker Hill and Lytle 

 Creek basins in the San Bernardino area, California, 1945–98 .........................................27

Figure 19. Graph showing water imported for artificial recharge into the 

 San Bernardino area, California, 1972–98 ............................................................................28

Figure 20. Map showing location of major wastewater treatment facilities in the 

 San Bernardino area, California.............................................................................................30

Figure 21. Graph showing relation between discharge in Warm Creek and ground-

 water level in the San Bernardino area, California.............................................................33

Figure 22. Map showing areal extent of the valley-fill aquifer, boundary conditions, and 

 direction of ground-water flow in the San Bernardino area, California..........................34

Figure 23. Representative geologic section A−A’ and stratigraphic column of the 

 San Bernardino area, California............................................................................................36

Figure 24. Section A−A’ showing major hydrogeologic units, geophysical logs, and 

 direction of ground-water flow in the San Bernardino area, California..........................38
vi

Figure 25. Graph showing annual ground-water pumpage for the San Bernardino area, 

 California, 1945–98....................................................................................................................41

Figure 26. Map showing average underflow from permeable sediment near the 

 Crafton fault into the San Bernardino area, California, 1945–98......................................43

Figure 27. Graph showing estimated underflow from San Timoteo Canyon and 

 Sand Canyon into the San Bernardino area, California ....................................................44

Figure 28. Graph showing the relation between water level in the Heap well (1S/4W-3Q1)

 and underflow across the San Jacinto fault near the Santa Ana River.........................45

Figure 29. Photograph showing the Heap well (1S/4W-3Q1) in the San Bernardino area, 

 California ....................................................................................................................................46

Figure 30. Graph showing ground-water discharge into Warm Creek in the 

 San Bernardino area, California, 1943–98 ...........................................................................47

Figure 31. Maps showing areal distribution of average pumpage in the 

 San Bernardino area, 1945–98...............................................................................................48

Figure 32. Graphs showing regression equations used to estimate pumpage 

 in the San Bernardino area, California, 1945–46 ................................................................51

Figure 33. Pie charts showing average recharge, discharge, and change in storage 

 for the valley-fill aquifer in the San Bernardino area, California, 1945–98.....................55

Figure 34. Map showing location of wells in the San Bernardino area, California, 1945 ...............57

Figure 35. Graphs showing measured water level in multiple-depth cluster wells in 

 the San Bernardino area, California, 1990–2000.................................................................58

Figure 36. Map showing areas with poor ground-water quality in the San Bernardino 

 area, California, 1997...............................................................................................................60

Figure 37. Section A–A’ showing relation between hydrogeologic units and layers 

 of the ground-water flow model in the San Bernardino area, California........................62

Figure 38. Graphs showing general relations among field data, conceptual model, 

 and ground-water flow model of the San Bernardino area, California..........................65

Figure 39. Map showing location, orientation, and boundary conditions of the ground-

 water flow model of the San Bernardino area, California.................................................67

Figure 40. Maps showing areal distribution of calibrated hydraulic parameters of the 

 ground-water flow model of the San Bernardino area, California...................................71

Figure 41. Photographs showing major surface-water features in the 

 San Bernardino area, California.............................................................................................73

Figure 42. Map showing measured ground-water levels and simulated hydraulic 

 heads for the unconfined part of the valley-fill aquifer in the San Bernardino 

 area, California, 1945...............................................................................................................78

Figure 43. Map and hydrographs showing results of calibration of the ground-water 

 flow model of the San Bernardino area, California, 1945–98 ...........................................79

Figure 44. Graph showing comparison between measured and simulated surface-water 

 outflow from the San Bernardino area, California, 1945–98.............................................80

Figure 45. Graph showing estimated change in ground-water storage in the 

 San Bernardino area, California, 1945–98 ...........................................................................81

Figure 46. Graphs showing solutions for a simple constrained optimization model .......................87

Figure 47. Tableau arcane showing objective function, constraint equations, decision 

 variables, and RHS of a simple constrained optimization model.....................................88

Figure 48. Diagram showing sequence of steps involved in design and use of a 

 constrained optimization model to solve a ground-water management 

 problem......................................................................................................................................90
vii

Figure 49. Map and graphs showing representative response of simulated hydraulic 

 head to recharge in the San Bernardino area, California..................................................92

Figure 50. Graphs showing superposition of response functions .......................................................39

Figure 51. Diagram showing water-management solutions...............................................................101

Figure 52. Diagram showing water-management puzzle....................................................................102

Figure 53. Graph showing cumulative probability of annual runoff in the Santa Ana River, 

 San Bernardino area, California, for selected time periods, 1913–98............................103

Figure 54. Photographs showing major water-management issues in the San Bernardino 

 area, California, 1998..............................................................................................................105

Figure 55. Map showing major water-management issues in the San Bernardino area, 

 California, 1998 ........................................................................................................................106

Figure 56. Map and hydrographs showing results from water-management scenario 1 

 in the San Bernardino area, California, 1999–2030 ...........................................................112

Figure 57. Map and hydrographs showing results from water-management scenario 2 

 in the San Bernardino area, California, 1999–2030 ...........................................................113

Figure 58. Map and hydrographs showing results from water-management scenario 3

 in the San Bernardino area, California, 1999–2030 ...........................................................116

Figure 59. Map and hydrographs showing results from water-management scenario 4 

 in the San Bernardino area, California, 1999–2030 ...........................................................117

Figure 60. Graph and map showing excess pumping capacity in the San Bernardino 

 area, California, 1994–98........................................................................................................119

Figure 61. Map and graph showing results from water-management scenario 5 in 

 the San Bernardino area, California, 1999–2030................................................................121

Figure 62. Graph showing minimum annual pumpage needed to control hydraulic 

 head gradients along the southern edge of contamination in the Newmark 

 area, San Bernardino, California, 1999–2030 .....................................................................122

Figure 63. Map showing design of water-management scenario 6 in the San Bernardino 

 area, California, 1999–2030....................................................................................................124

Figure 64. Maps and graph showing infeasible head constraints for scenario 6..........................126

Figure 65. Graph showing the minimum and maximum pumpage for scenario 6 for

 the San Bernardino area, California....................................................................................128

Figure 66. Diagram showing elsewhere the general process of scientific inquiry ........................131

Figure 67. Map showing water-management sites in the San Bernardino area, 

 California, 1998 ........................................................................................................................132

Figure 68. Photographs showing Bunker Hill dike in the San Bernardino area, 

 California, circa 1904 and 2004 .............................................................................................137

Plates

Plate 1. Major components of the surface-water system in the San Bernardino area, 

 California, 1998..........................................................................................................................15

Plate 2. Routing diagram of surface-water flow in the San Bernardino area, California, 

 1998..............................................................................................................................................15
viii

Tables

Table 1. Annual discharge for gaged streams in the San Bernardino area, 

California, 1945–98....................................................................................................................148

Table 2. Percent of long-term average annual runoff for the Santa Ana River, 

California, 1945–98......................................................................................................................24

Table 3. Average annual runoff from ungaged areas bordering the Bunker Hill and 

Lytle Creek Basins in the San Bernardino area, California, 1928–98 ...............................155

Table 4. Precipitation components for the San Bernardino area, California, 1945–98.................156

Table 5. Distribution, quantity, and use of water imported into the San Bernardino

area, California, 1972–98..........................................................................................................158

Table 6. Major wastewater treatment facilities in the San Bernardino area,

California ....................................................................................................................................161

Table 7. Annual wastewater discharge to the Santa Ana River and Warm Creek

in the San Bernardino area, California, 1945–98 .................................................................162

Table 8. Annual ground-water discharge into Warm Creek in the San Bernardino area, 

California, 1945–98......................................................................................................................32

Table 9. Annual underflow for the San Bernardino area, California, 1945–98...............................164

Table 10. Annual ground-water pumpage in the San Bernardino area, California, 1945–98 ........167

Table 11. able 11. Ground-water budget for the San Bernardino area, California, 1945–98..........................54

Table 12. Comparison between past and present ground-water flow models of 

the San Bernardino area, California......................................................................................170

Table 13. Coordinates of the ground-water flow model of the San Bernardino area, 

California ......................................................................................................................................66

Table 14. Computer programs (packages) used with the ground-water flow model 

of the San Bernardino area, California ...................................................................................68

Table 15. Simulated ground-water budget for the valley-fill aquifer in the San

Bernardino area, California, 1945–98 ....................................................................................172

Table 16. Simulated streambed characteristics in the San Bernardino area, 

California ......................................................................................................................................72

Table 17. Source of parameters, recharge, and discharge estimates and their 

relative adjustment during calibration of the ground-water flow model 

of the San Bernardino area, California ...................................................................................77

Table 18. Sensitivity of the ground-water flow model of the San Bernardino area, 

California ......................................................................................................................................83

Table 19. Description of water-management scenarios simulated by the groundwater flow and constrained optimization models for the San Bernardino 

area, California..........................................................................................................................175

Table 20. Recharge and discharge components for scenarios 1–6 for the San 

Bernardino area, California, 1999–2030 ................................................................................177
ix

Multiply By To obtain

acre 4,047 square meter (m2)

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

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

foot (ft) 0.3048 meter (m)

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

foot per foot (ft/ft) 1 meter per meter (m/m)

foot per minute (ft/min) 0.3048 meter per minute (m/min)

foot per second (ft/s) 0.1894 meter per second (m/s)

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

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

inch (in.) 25.4 millimeter (mm)

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

mile (mi) 1.609 kilometer (km)

square mile (mi2) 2.590 square kilometer (km2) 

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

 °C=(°F-32)/1.8

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

(NGVD 29).

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

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

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

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

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

or micrograms per liter (μg/L).

Conversions, Vertical Datum, Abbreviations, 

and Acronyms

Pound/SI
x

Abbreviations and Acronyms

ABot altitude of the bottom of the aquifer (L);

ATop altitude of the land surface (L);

BLow lower bound for a decision variable (units of the decision variable);

BUp upper bound for a decision variable (units of the decision variable);

CImpWater

iar, k cost of imported water distributed to basin iar, during time 

 period k ($/L3/T);

ce unit cost of electricity ($/L/L3);

ci concentration of fluoride in well i (M/L3);

D matrix of total drawdown at all control locations, at all time 

 periods (L);

DTarget

o, to target drawdown observed at control location o during time 

 period to (L);

DBCP dibromochloropropane

dGrad

p

 distance between the inside and outside control points for 

 gradient pair p (L);

do, to total drawdown from managed and unmanaged stresses and from 

 initial and boundary conditions, at observation location o, 

 during time period to (L);

ei efficiency of the well pump and motor for well i (decimal fraction);

GTarget

p

 target gradient for gradient pair p (L/L);

GAMS General Algebraic Modeling System

GIS geographic information system

GPS global positioning system

HLimitLo

o, to lower limit of hydraulic head at location o, during time period to (L);

HLimitUp

o, to upper limit of hydraulic head at location o, during time 

 period to (L);

HMan matrix of managed hydraulic heads (L);

HInitial matrix of initial hydraulic heads (L);

h hydraulic head (L);

ho, to, s, ta simulated hydraulic head observed at control location o, at the end 

 of time period to, resulting from recharge or discharge (stress) s, 

 applied at time ta (L);

hGradIn

p

 hydraulic head on the inside of gradient pair p (L);

hGradOut

p

 hydraulic head on the outside of gradient pair p (L);

hHeap, k simulated hydraulic head for the ground-water flow model cell 

 containing the Heap well (row 70, column 79, layer 1) for time

 period k (L);

hIbc

o, to hydraulic head resulting from initial and boundary conditions, 

 observed at control location o, at the end of time period to (L);

hMan managed hydraulic head (L);

hInitial

o

 initial hydraulic head, observed at control location o (L);

hHeap simulated hydraulic head for the model cell containing the Heap 

 well (row 70, column 79, layer 1), referenced to mean sea level (L);

InSAR interferometric synthetic aperture radar;

i location index;

iar index for a specific artificial-recharge basin;

Kp horizontal hydraulic conductivity between inside and outside 

 control points for gradient pair p (L/T);

Kz vertical hydraulic conductivity (L/T);
xi

k time index; LInitiali

 initial lift at well i (L); 

LMan

i total lift at well i resulting from all managed stresses, in feet;

L

S

i, j

 lift at well i caused by recharge or discharge (stress) at location j (L);

LTotal

i

 total lift at well i (L);

ln natural logarithm;

log logarithm; ML Richter or local magnitude for an earthquake (dimensionless);

MCM middle confining member;

MODFLOW ground-water flow model;

MODMAN computer program used with MODFLOW;

MINOS optimization software;

MPS input dataset;

na not applicable

nar number of artificial-recharge basins; 

ndv number of decision variables (managed stresses) having 

 response functions;

nio 

nol number of observation locations;

ntp number of time periods simulated in the management horizon;

nw number of wells;

ny number of years in a water-management period; o index indicating the location where simulated hydraulic head is 

 observed, represented in the ground-water flow model by

 a single model cell;

PCE perchloroethylene; pep

 effective porosity between inside and outside control points for 

 gradient pair p (dimensionless); PImpWaterk percentage deliverable imported water compared to the maximum 

 entitlement, for calendar year k (percent); PSARROk

 percentage runoff in the Santa Ana River measured at USGS station

 11051501 for calendar year k, compared to the long-term average 

 annual runoff (discharge) at the same station for 1928–98 (percent); QArtRech

iar, k quantity of water distributed to artificial-recharge basin iar 

 during time period k (L

3

/T);

QGagedRO

i, k gaged discharge in stream i during time period k (L

3

/T);

QGagedRO

SAR, 1928–98 average gaged discharge in the Santa Ana River during 

 1928–98 (L

3

/T);

QImportedWater

i, k imported water for area i during time period k (L

3

/T);

QPump

i, k pumpage for well i during time period k (L

3

/T);

QPump

Total total pumpage (L

3

/T);

QPumpNP

k

 total non-plaintiff pumpage for calendar year k (L

3

/T);

QPumpP

k

 total plaintiff pumpage for calendar year k (L

3

/T);

QRisingGW

WarmCreek, k ground water rising into Warm Creek during year k (L

3

/T); 

QUngagedRO

i, k ungaged runoff from area i during time period k (L

3

/T);

QUngagedRO

i, 1928–98 average ungaged runoff from area i during 1928–98 (L

3

/T);

QUnderflow

i, k underflow for area i during time period k (L

3

/T);

Q

z

 vertical leakance (L/T);

Q matrix of managed stresses (L

3

/T);

qs, ta managed stress s, represented in the ground-water flow model by 

 recharge or discharge for a model cell or group of model cells, 

 observed at the end of time period ta (L

3

/T);
xii

R matrix of unit responses, at all control locations, at all time 

 periods (L/L3/T);

RIbc matrix of responses, at all control locations, at all time periods, 

 resulting from initial and boundary conditions and from all 

 unmanaged stresses (L); 

RHS right-hand side;

r

Ibc

o, to response of simulated hydraulic head from initial and boundary 

 conditions and from all unmanaged stresses, observed at control 

 location o, at the end of stress period to (L);

r

o, s unit drawdown response observed at control location o that results 

 from a unit stress applied at location s (L/L3/T);

rriar, k recharge rate for artificial-recharge basin iar during time period k 

 (decimal fraction);

r

2 coefficient of determination for a regression equation;

S storage coefficient (dimensionless);

STR1, STR2 streamflow routing package;

SWP California state water project;

s index indicating a managed stress;

T transmissivity (L2/T);

TCE trichloroethylene;

t time (T);

ta index indicating the time period when the managed stress is 

 applied, represented in the ground-water flow model by a 

 pumping period;

to index indicating the time period when the response is 

 observed, calculated in the ground-water flow model at the 

 end of a pumping period;

USandCanyon, k underflow in the vicinity of Sand Canyon for calendar year k (L3/T);

USanTimoteo, k underflow in the vicinity of San Timoteo Canyon for 

 calendar year k (L3/T); 

USAR, k underflow across the San Jacinto fault near the Santa Ana River 

 for calendar year k (L3/T); 

UCM upper confining member;

UTM Universal Transferse Mercator coordinate system;

UWB upper water bearing;

VTarget

p

 target velocity between inside and outside control points for gradient 

 pair p (L/T);

W combination of sources and sinks (L/T);

WlHeap water-level altitude in the Heap well (1S/4W–3Q1) (L);

x, y, z cartesian coordinates (L);

Z objective ($, L3/T).

Organizations

SBVMWD San Bernardino Valley Municipal Water District

SBVWCD San Bernardino Valley Water Conservation District

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey
xiii

Well-Numbering System

Wells are identified and numbered according to their location in the rectangular system for 

the subdivision of public lands. Identification consists of the township number, north or south; 

the range number, east or west; and the section number. Each section is divided into sixteen 

40-acre tracts lettered consecutively (except I and O), beginning with “A” in the northeast corner of the section and progressing in a sinusoidal manner to “R” in the southeast corner. Within 

the 40-acre tract, wells are sequentially numbered in the order they are inventoried. The final 

letter refers to the base line and meridian. In California, there are three base lines and meridians; Humboldt (H), Mount Diablo (M), and San Bernardino (S). All wells in the study area 

are referenced to the San Bernardino base line and meridian (S). Well numbers consist of 15 

characters and follow the format 001S004W-003Q001. In this report, well numbers are abbreviated and written 1S/4W-3Q1. Wells in the same township and range are referred to only by their 

section designation, -3Q1. The following diagram shows how the number for well 1S/4W-3Q1 

is derived.

D C B A

E F G H

M L K J

N P Q R

6 5 4 3 2 1

7 8 9 10 11 12

18 17 16 15 14 13

19 20 21 22 23 24

30 29 28 26 25

31 32 33 34 35 36

27

R2W R1W

T1S

T1N

T2N

R3W

RANGE

TOWNSHIP

R5W R4W

T2S

T3S

Approximately

6 miles

Approximately

1 mile

Approximately

1/4 mile

R4W

Well-numbering diagram

SECTION 3

T1S

1S/4W-3Q1

BASE LINE
xiv
Abstract

The San Bernardino area of southern California has 

complex water-management issues. As an aid to local water 

managers, this report provides an integrated analysis of the 

surface-water and ground-water systems, documents groundwater flow and constrained optimization models, and provides 

seven examples using the models to better understand and 

manage water resources of the area. As an aid to investigators and water managers in other areas, this report provides an 

expanded description of constrained optimization techniques 

and how to use them to better understand the local hydrogeology and to evaluate inter-related water-management problems.

In this report, the hydrology of the San Bernardino area, 

defined as the Bunker Hill and Lytle Creek basins, is described 

and quantified for calendar years 1945–98. The major components of the surface-water system are identified, and a routing diagram of flow through these components is provided. 

Annual surface-water inflow and outflow for the area are tabulated using gaged measurements and estimated values derived 

from linear-regression equations. Average inflow for the 54-

year period (1945–98) was 146,452 acre-feet per year; average 

outflow was 67,931 acre-feet per year. The probability of 

exceedance for annual surface-water inflow is calculated using 

a Log Pearson Type III analysis. Cumulative surface-water 

inflow and outflow and ground-water-level measurements 

indicate that the relation between the surface-water system 

and the ground-water system changed in about 1951, in about 

1979, and again in about 1992. Higher ground-water levels 

prior to 1951 and between 1979 and 1992 induced groundwater discharge to Warm Creek. This discharge was quantified 

using streamflow measurements and can be estimated for other 

time periods using ground-water levels from a monitoring well 

(1S/4W–3Q1) and a logarithmic-regression equation. Annual 

wastewater discharge from the area is tabulated for the major 

sewage and power-plant facilities.

The ground-water system consists of a valley-fill aquifer 

and a much less permeable bedrock aquifer. The valley-fill 

aquifer, which is the focus of this study, is composed primarily 

of highly transmissive unconsolidated and poorly-consolidated 

deposits. The bedrock aquifer is composed of faulted and fractured igneous and metamorphic rock. The valley-fill aquifer is 

underlain by the bedrock aquifer and and is bounded laterally 

by the bedrock aquifer and by faults with varying capabilities 

to transmit ground water. Some underflow occurs across faults 

in the valley-fill sediment, particularly beneath the Santa Ana 

River. Essentially no underflow occurs from the surrounding 

bedrock. Hydrogeologic units were defined for the valley-fill 

aquifer using driller’s logs, geophysical logs, and hydrographs 

from multiple-depth piezometers. These units are shown on 

a detailed hydrogeologic section constructed along Waterman Canyon Creek. A large-scale aquifer test demonstrated 

the continuity of the hydrogeologic units and their hydraulic properties in the center of the Bunker Hill basin. Gross 

annual pumpage from the valley-fill aquifer for 1945–98 was 

compiled from reported and estimated data, and then used 

to estimate extraction from the upper and lower layers of the 

valley-fill aquifer and return flow to the upper layer. Annual 

values of the major components of recharge and discharge 

for the valley-fill aquifer are calculated for 1945–98. Average 

recharge occurs primarily from gaged streamflow (67 percent), 

ungaged mountain-front runoff (9 percent), and pumpage 

return flow (16 percent); average discharge occurs primarily as 

pumpage (88 percent).

Hydrology, Description of Computer Models, and 

Evaluation of Selected Water-Management Alternatives 

in the San Bernardino Area, California

By Wesley R. Danskin, Kelly R. McPherson, and Linda R. Woolfenden

“And it never failed that during the dry years the people forgot about the rich years, and during the wet years they lost 

all memory of the dry years. It was always that way.” John Steinbeck, East of Eden
Computer models, including a ground-water flow model 

and a constrained optimization model, are described. The 

ground-water flow model includes the Bunker Hill and Lytle 

Creek basins and simulates three-dimensional ground-water 

flow in the valley-fill aquifer using finite-difference techniques. The model consists of an upper layer representing 

the upper unconfined/semi-confined hydrogeologic unit and 

a lower layer representing a combination of several lower 

confined hydrogeologic units. The vertical connection between 

the model layers is approximated by Darcian flow. The 

flow-impeding effect of faults within the valley-fill aquifer is 

simulated by a horizontal flow-barrier package. The model 

also includes a streamflow-routing package that simulates the 

interaction of a complex network of streams with the valleyfill aquifer. Calibration of the flow model was for 1945–98.

The constrained optimization model uses linear programming to calculate the minimum quantity of recharge from 

imported water and pumpage from wells necessary to solve 

various water-management problems. A description of linearprogramming techniques and a simplified example problem 

are provided. The optimal quantity of recharge or pumpage is determined by their availability and by constraints on 

ground-water levels and ground-water quality. The response 

of ground-water levels to recharge and pumpage is calculated 

by the ground-water flow model. The mathematically optimal 

solutions derived from the optimization model, in concert with 

field data and hydrogeologic concepts, can be used to guide 

water-management decisions.

Selected water-management alternatives for the San Bernardino area were evaluated with the aid of the ground-water 

flow and constrained optimization models. Seven scenarios 

were designed to answer specific water-management questions 

and to demonstrate key hydrogeologic characteristics of the 

area. A 32-year simulation period, 1999–2030, with annual 

values of recharge and pumpage, was used for each scenario. 

The scenarios include: (1) average historical conditions; (2) 

annually varying historical conditions; (3) additional artificial 

recharge provided by construction of Seven Oaks Dam; (4) 

increased ground-water pumpage; (5) optimal pumpage from 

barrier wells designed to prevent further spread of contamination from the Newmark U.S. Environmental Protection 

Agency superfund site; (6) optimal pumpage needed to control 

ground-water levels in an area with potential liquefaction and 

land subsidence; and (7) optimal recharge and pumpage to 

control ground-water levels and to prevent migration of the 

Newmark contamination.

Results of the evaluation include the following conclusions. Additional pumpage in the vicinity of the former marshland is needed to prevent a reoccurrence of dangerously high 

ground-water levels similar to those experienced in 1945 and 

1980. High ground-water levels are a water-management concern because they indicate soil is saturated near land surface 

and is susceptible to liquefaction during an earthquake. The 

optimal location of additional pumpage is near Warm Creek in 

an area of historically rising ground water. The high groundwater levels occur primarily during short periods following 

abundant natural recharge. About 15,000 acre-feet per year of 

additional, areally distributed pumpage are needed to control 

the high ground-water levels.

Demand for water in the San Bernardino area is projected 

to increase during the next 25 years by as much as 50,000 

acre-feet per year. Part of this increased demand can be met by 

additional pumpage needed to prevent a rise in ground-water 

levels (15,000 acre-feet per year) and part by increased local 

supply (3,000 acre-feet per year) resulting from construction 

of a conservation pool behind Seven Oaks Dam. As much 

as 70,000 acre-feet of additional pumpage is theoretically 

available from existing wells using excess pumping capacity. 

However, additional pumpage greater than about 15,000 acrefeet per year likely will result in a longterm decline in groundwater levels such as occurred during the 1960’s, a decline 

which prompted land subsidence. To meet future demand 

for water in excess of about 15,000 acre-feet per year and to 

prevent a reoccurrence of land subsidence, imported water 

probably will need to be used, either for direct delivery or for 

recharge of the ground-water system.

Much of the recharge to the valley-fill aquifer occurs 

during years with unusually abundant runoff, which occurs 

on average about once every 5 to 10 years. Maintaining and 

enhancing capabilities to artificially recharge native runoff 

are likely to be necessary to meet increased demand for water 

from the valley-fill aquifer. Since 1945, significant fluctuations in ground-water storage have become common because 

of the abundant, but highly variable, recharge combined with 

relatively constant ground-water pumpage. Annual fluctuations in ground-water storage from 50,000 to 100,000 acrefeet are common. Cumulative fluctuations in ground-water 

storage greater than 500,000 acre-feet in a 10-year period also 

are common, but this magnitude will not significantly affect 

the availability of ground water, as long as historic recharge 

capacities are maintained or enhanced.

Hydraulic control of the Newmark contamination site 

is unlikely to occur using only the five planned extraction 

(barrier) wells; another four wells may be needed, each with a 

capacity of about 3.5 cubic feet per second. Without additional 

extraction wells, contaminated ground water tends to migrate 

around the barrier wells, especially to the west. Minimum total 

pumpage at nine barrier well sites, located across the leading 

edge of the contamination, needs to be at least 14,000 acre-feet 

per year, based on results from the optimization model.

2 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Control of maximum and minimum ground-water levels 

in the vicinity of the former marshland does not require 

significant additional recharge of imported water, but does 

require additional pumpage. Additional pumpage from as 

many as 29 potential production wells located along the proposed eastern and southern extensions of the Baseline feeder 

pipeline is unlikely to sufficiently control high ground-water 

levels. Additional pumpage needs to be areally distributed in 

the vicinity of Warm Creek, just north of the San Jacinto fault. 

Extraction needs to occur from the highly permeable deposits 

of the upper water-bearing unit to prevent an upward hydraulic 

gradient and from the less permeable near-surface deposits 

that remain saturated even as hydraulic head in the underlying 

production zone is declining. 

The high probability of a major earthquake on either the 

San Jacinto fault or San Andreas fault in the San Bernardino 

area makes control of high ground-water levels a pressing 

economic concern. Significant mitigation of this threat by 

additional extraction of ground water is possible, especially if 

a use can be found for the surplus water. Reoccurrence of land 

subsidence is a continuing concern and can be monitored with 

multiple-depth piezometers, extensometers, and satellite-borne 

interferometry, particularly if pumpage near the former marshland is increased. Contamination of the valley-fill aquifer is 

widespread both areally and vertically. Plans for clean up will 

be aided by continued mapping of the hydrogeologic units, 

which strongly influence ground-water flow paths. The large 

magnitude of proposed ground-water extraction to clean up 

several areas of contamination suggests that these plans need 

to be coordinated with plans to prevent liquefaction and land 

subsidence.

Introduction

During the past 100 years, water management in the San 

Bernardino area of southern California (figs. 1 and 2) has 

become increasingly complex. Water purveyors in this area, as 

in other parts of the world, have applied a variety of techniques to solve their water-supply and water-quality problems. 

They have adjusted ground-water pumpage both areally and 

seasonally; enhanced recharge of native water along streams; 

redistributed water with canals and aqueducts; artificially 

recharged aquifers using imported water; treated, blended, and 

reused water; and employed various forms of water sales and 

exchanges. Although most water purveyors rely on conjunctive use of surface and ground waters, seldom is there optimal 

management of the entire system. Much of the management 

is by trial and error in response to crisis situations, such as 

floods, droughts, and contamination problems. Often, management options are limited by relatively inflexible court-imposed 

plans that are the outgrowth of litigation between competing 

purveyors or water-use interests.

A comprehensive understanding of the hydrology of the 

San Bernardino area combined with prudent use of groundwater flow and constrained optimization models can aid in the 

effective management of such a complex and changing system. 

A ground-water flow model incorporates a spatial and temporal discretization of recharge, discharge, and aquifer characteristics and can simulate the historical operation of the groundwater system and the effect of proposed water-management 

decisions on ground-water levels, recharge, and discharge. 

Results of such simulations commonly provide an improved 

understanding of a ground-water system as well as specific 

guidance in making future water-management decisions. A 

constrained optimization model can combine predicted results 

from a ground-water flow model with other water-management issues, such as cost of operations. Results of the optimization model identify the mathematically optimal solution 

to a water-management question that can involve literally 

hundreds or thousands of ground-water-level, water-quality, 

and economic constraints. Although constrained optimization 

techniques have been used in a variety of technical fields for 

more than 50 years, applications to surface-water/groundwater systems have been limited (Bachmat and others, 1980; 

Gorelick, 1983; Rogers and Fiering, 1986; B.J. Wagner, 1995). 

Most of these applications have been academic studies applied 

to hypothetical basins; the few applications to real basins 

typically have not involved a close interaction with the actual 

individuals and agencies responsible for implementing watermanagement decisions.

This study was initiated with two major objectives. 

The first objective was to analyze the water resources of the 

San Bernardino area and provide quantitative guidance to 

local water purveyors on how to better manage their water 

resources. Achieving this objective required a close interaction 

with the more than 20 local purveyors and regulatory agencies. 

Hydrologic understanding and computer models developed 

as part of this study will be used by the purveyors to enhance 

their ability to analyze and manage future water-management 

problems. The second major objective of this study was to 

demonstrate the successful use of optimization techniques in a 

basin with a large number of water problems, purveyors, and 

vested interests. Major components of the study and flow of 

information between the components is shown diagrammatically in figure 3.

Purpose and Scope

The purpose of this report is to present the hydrology of 

the San Bernardino area, California; to describe ground-water 

flow and constrained optimization models that were developed 

for analysis of local water-resource operations; and to evaluate selected water-management alternatives using results from 

the computer models and an improved understanding of the 

hydrologic system.

Introduction 3
Figure 1. Location of the San Bernardino area in the Santa Ana River drainage basin, southern California.

4 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

15

91

15

10

10

605

215

405

Pacific Ocean 5

COASTAL

ANA BASIN

SANTA

BASIN

INLAND

BASIN

SAN JACINTO BASIN

San Jacinto Mts

San Bernardino Mts

San Bernardino

County

Riverside County

Los Angeles County

San Bernardino

Chino Hills

Orange

County

Los Angeles

San Diego

 San

Francisco

Santa Ana

Basin

California

Riverside

San Gabriel Mts

Santa Ana Mts

Big Bear

Lake

San Jacinto

River

0 10 20 MILES

0 10 20 KILOMETERS

45' 30' 15'

45'

Base from U.S. Geological Survey digital elevation data, 1:100,000, 1981-89; 

Universal Transverse Mercator projection, zone 11. Shaded relief base from

1:250,000-scale digital elevation model; sun illumination from northwest at

30 degrees above horizon

Santa

Ana

Ana

Ana

River

River

Santa

Santa

Yucaipa

Area of figure 2

118 00' 117 00' 116 45'

34 15'

34 00'

33 30'
Figure 2. Geographic setting of the San Bernardino area, California.

Introduction 5

BASIN

CHINO

BASIN

BUNKER

HILL

RIALTO - COLTON

BASIN

YUCAIPA BASIN

San Andreas

Fault

San

Jacinto

Fault

Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood

Lake

Cajon

Cable Cr

Cr

River

River

Zanja

City

Warm

Plunge

Cr

The

Cr

Cr

Santa

Santa

Ana

Ana

Mill

Cr

 Lytle Cr

San Timoteo

Cr

Seven Oaks Dam

20' 15' 10'

10'

EXPLANATION

San Bernardino Mountains

Crafton Hills

0 6 KILOMETERS

0 6 MILES Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Norton Air 

Force Base

Badlands

Shandin

Hills

Perris Hill

Gabriel

Mts

San

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray comprise

the San Bernardino area, as defined in this report

Former marshland

15

215

10

215

San Bernardino Mountains

Gabriel

Mts

San

15

Redlands Redlands

San Bernardino San Bernardino Highland Highland

CREEK

LYTLE

BASIN

Fault or ground-water barrier-May be concealed or approximately located

Artificial-recharge basin

Boundary of Santa Ana

River drainage basin

34

15'

34

05'

117 25' 117 05'
The scope of this report includes the Bunker Hill and 

Lytle Creek basins that compose the San Bernardino area 

(fig. 2). The hydrologic system consists of a surface-water 

system and a ground-water system. The surface-water system 

includes stream courses, canals, ditches, and reservoirs; the 

ground-water system consists of the valley-fill aquifer, which 

includes all saturated materials from land surface down to 

igneous and metamorphic basement rocks. 

This report includes analysis of data from 1871 through 

1998, and review of publications from 1888 through 2000. 

Hydrologic interpretations were based primarily on data for 

calendar years 1945–98 for both the surface-water and groundwater systems. Data for calendar years 1928–98 were used 

whenever possible, in particular for analysis of precipitation 

and surface-water runoff. Calendar years are used throughout 

this report, unless otherwise stated, primarily because they had 

been adopted as part of adjudication of the area for reporting 

pumpage and surface-water allocations.

Background information for this report included a thorough literature review of published and unpublished geologic 

and hydrologic reports, streamflow records, surface-water 

routing diagrams, water-quality data, ground-water-level 

measurements, pumpage data, aquifer-test data, driller’s logs, 

geophysical logs, hydrogeologic sections, and reports from 

local water agencies and consultants. Data collected include 

ground-water-level measurements, in particular from multipledepth well sites. Data from these sites, which were equipped 

with pressure transducers and data loggers to monitor groundwater-level changes every 60 minutes, were used to refine 

concepts of ground-water flow in the valley-fill aquifer and 

to provide real-time data via satellite. A 50-foot-deep well 

(1S/4W-22D7) was drilled to monitor ground-water-level 

fluctuations in saturated near-surface deposits that are susceptible to liquefaction during an earthquake. An areally extensive 

aquifer test was conducted to document the hydraulic properties of the aquifer. Map data were organized and interpreted 

using a geographic information system (GIS) developed for 

this project.

Figure 3. Major components and flow of information in this study of the San Bernardino area, California.

6 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Data Hydrologic concepts

Watermanagement

issues

Conceptual model

of aquifer

Description of

surface-water

system

Surface-water

routing model

Ground-water

flow model

Constrained

optimization model

Ground-water

levels,

recharge, and

discharge

Monitoringmanagement

wells

Surface-water

discharge

 Basinwide management

Watermanagement

decisions

Computer models

Secondary path of information 

Primary path of information

EXPLANATION
A previously developed numerical ground-water flow 

model by Hardt and Hutchinson (1980) was revised in order 

to simulate the ground-water flow system more accurately and 

to include key recharge-discharge relations explicitly in the 

model. Both previous and revised models simulate transient 

ground-water flow in the valley-fill aquifer of the Bunker Hill 

and Lytle Creek basins, using two model layers and annual 

stress periods. Revisions include use of a more flexible numerical code (McDonald and Harbaugh, 1988); interpolation of 

prior parameter data sets to conform to the new discretization; conversion from lumped, average values of recharge and 

discharge to discrete, annually varying values that represent 

different physical processes; extension of the historical simulation to include calendar years 1945–98; and addition of a 

streamflow-routing package (Prudic, 1989). The streamflowrouting package permits simulation of interaction between 

the surface-water and ground-water systems and includes an 

accounting of flow in the streams. All model parameters were 

included in the GIS.

Development of a constrained optimization model 

required identifying the major water-management issues in 

the San Bernardino area. These issues involve water supply, 

ground-water levels, ground-water quality, and cost of supplying water. The issues are formulated as mathematical equations and are combined with information from the groundwater flow model to form the constrained optimization model. 

This model, which uses linear-programming techniques, can 

be used to define the mathematically optimal solution to a 

variety of water-management questions, such as “What is the 

minimum pumpage necessary to dewater the high-groundwater area near downtown San Bernardino?” Manageable 

items (decision variables) in the optimization model include 

recharge of imported water, additional pumpage near areas 

of contaminated ground water, and additional pumpage in an 

area with unacceptably high ground-water levels. Constraint 

equations set limits on: quantities of recharge and pumpage; 

ground-water gradients near areas of ground-water contamination; ground-water levels in different areas of both basins; and 

costs of distributing surface water or pumping ground water.

Selected water-management alternatives for the San 

Bernardino area were evaluated using the ground-water flow 

and optimization models. To aid in the evaluation process 

and to provide the necessary quantitative information, six 

scenarios were developed and simulated. Each scenario was 

designed to answer specific water-management questions and 

to demonstrate key hydrogeologic characteristics of the basins. 

A 32-year simulation period, 1999–2030, and annual values 

of recharge and pumpage were used for each scenario. The 

scenarios include simulation of average future conditions with 

no change in basin management, annual variations in recharge 

and pumpage, increased recharge and pumpage to meet 

increased demand, and redistribution of pumpage to control 

ground-water gradients and levels. The primary water-management objectives were to satisfy local demand, to prevent 

further migration of contaminated ground water from the 

Newmark superfund site, and to reduce the risk of liquefaction 

of saturated materials near the land surface during an earthquake. Simulated results from the six scenarios were combined with other hydrologic data and interpretations in order to 

evaluate possible changes in water management necessary to 

meet each objective.

Description of Study Area

The San Bernardino area is a semiarid inland valley 

of about 120 square miles in southwestern San Bernardino 

County, about 60 miles east of Los Angeles, in the upper 

part of the Santa Ana River drainage basin (fig. 1). The San 

Bernardino area was defined by Dutcher and Garrett (1963) as 

a northwest-trending area between the San Andreas and San 

Jacinto faults (fig. 1). The area is bordered on the northwest by 

the San Gabriel Mountains, on the northeast by the San Bernardino Mountains, on the south by the badlands and Crafton 

Hills, and on the southwest by a low, east-facing escarpment 

of the San Jacinto fault. Alluvial fans extend from the base of 

the mountains and hills that surround the valley and coalesce 

to form a broad, sloping alluvial plain in the central part of the 

valley (fig. 4). Altitude ranges from about 1,000 feet (ft) near 

the city of San Bernardino to more than 10,000 ft in the San 

Bernardino Mountains. In this report, the San Bernardino 

area is defined as the Bunker Hill and Lytle Creek basins 

(fig. 2), which also is the area simulated by the ground-water 

flow model described in this report.

The generalized geology of the San Bernardino area is 

shown in figure 5. Unconsolidated material that fills the basins 

includes river-channel deposits and younger alluvium of 

Holocene age, and older alluvium of Pleistocene age. Undifferentiated deposits of younger and older alluvium are present 

near Redlands and north of Perris Hill. Sedimentary rocks of 

Quaternary and Tertiary age crop out in the badlands mostly 

as the San Timoteo Formation, and north of the San Andreas 

fault mostly as the Potato Sandstone. A basement complex 

of Precambrian to Tertiary igneous and metamorphic rocks 

underlies the basin fill and crops out in the surrounding mountain ranges (Dutcher and Garrett, 1963). The San Bernardino 

area, which is located along the San Andreas fault zone, contains numerous sub-parallel faults including the San Andreas 

and San Jacinto faults (fig. 5). The area is tectonically active 

as indicated by numerous, nearby earthquakes—many with a 

magnitude greater than 5ML (Richter or local magnitude) (Yerkes, 1985). During 1992, for example, the nearby Landers and 

Big Bear earthquakes measured 7.3ML and 6.1ML, respectively 

(Roeloffs and others, 1995).

Introduction 7
Introduction 8

Climate in the San Bernardino area is characterized by 

relatively warm, dry summers and cool, wet winters. Temperatures range from daytime highs of about 90o

F in summer to 

night-time lows of about 40oF in winter. Precipitation is

nearly always in the form of rain in the lower elevations 

and mostly in the form of snow above an altitude of about 

6,000 ft in the surrounding San Bernardino and San Gabriel 

Mountains. Mean annual precipitation ranges from less than 

about 15 inches over much of the valley floor, to about 20 

inches along the base of the San Bernardino Mountains, to 

more than 30 inches along the crest of the mountains (fig. 6). 

Precipitation recorded at the city of San Bernardino from 1871 

to 1998 indicates that a period of below-average precipitation 

can last more than 30 years, such as a dry period that extended 

from 1947 to 1977 (fig. 7). Periods of above-average precipitation have tended to be shorter with a few, very wet years.

The San Bernardino area is located in the upper part of 

the Santa Ana River drainage basin (fig. 1). Runoff, particularly from the San Bernardino Mountains, flows in several 

small streams, Lytle Creek, and the Santa Ana River (fig. 2). 

The streams merge mostly within the San Bernardino area, 

flow southwest through Riverside and Orange Counties, and 

eventually empty into the ocean (fig. 1). Seepage from the 

streams replenishes the valley-fill aquifer, which provides 

most of the water used within the San Bernardino area.

Population and land use in the San Bernardino area have 

changed significantly since its development as an important 

citrus-growing area of southern California in the early 1900s. 

Beginning in about 1940, the urban population began to 

steadily increase as a result of increased growth in the defense 

industry and an increased awareness of the southern Californian climate and lifestyle as depicted in Hollywood films 

(California Department of Water Resources, 1971, fig. 19). 

The progressive conversion of vacant and agricultural land to 

urban land is shown in figure 8. In 1980, population of the 

San Bernardino area exceeded 225,000, an increase of about 

30 percent since 1960. In the year 2000, the population was 

about 320,000 and is projected to increase to more than 

380,000 by the year 2020 (California Department of Water 

Resources, 1986, table 4).

A land-use survey of the upper Santa Ana River drainage 

area was conducted by the California Department of Water 

Resources (1985). The most extensive land use in the San Bernardino area in 1984 was urban, which accounted for approximately 50 percent of the land area. Unused land accounted for 

approximately 25 percent; citrus agriculture approximately 

20 percent; and other uses approximately 5 percent. In the 

upper Santa Ana River drainage area, urban land use increased 

23 percent between 1975 and 1984; acreage used for agricultural purposes decreased approximately 31 percent during 

the same period (California Department of Water Resources, 

1985, p. 9). A similar pattern of changing land use has 

occurred in the San Bernardino area (Duell and Schroeder, 

1989, p. 17).

The combination of increasing population, changing land 

and water use, and frequent tectonic activity has resulted in 

a large number of complex water-management issues. Local 

water purveyors are concerned about the reliability of the 

water supply and the quality of ground water. Near the base 

of the San Bernardino Mountains, ground-water levels rise 

and fall dramatically in response to changes in recharge from 

streams. During times of drought and increased pumping, 

ground-water levels fall as much as 200 ft and limit the ability 

of water purveyors to supply sufficient ground water to meet 

demand.

Figure 4. View of the San Bernardino area, California, looking northwest across the Bunker Hill basin, 2004. Photo by W. R. Danskin.

8 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

San Jacinto Mt. Jurupa fault

San Gabriel Mountains

Former

marshland

Cajon Pass Shandin Hills
In the area where the Santa Ana River crosses the San 

Jacinto fault (fig. 2), ground-water levels also fluctuate though 

not as dramatically. During a period of extensive ground-water 

extractions from 1950 to 1970, ground-water levels fell as 

much as 100 ft and induced land subsidence of as much as 1 

ft (Miller and Singer, 1971). After 1970, both natural and artificial recharge increased so that by 1980, ground-water levels 

had risen to within a few ft of land surface (Hardt and Freckleton, 1987). This increase in hydrostatic pressure in a former 

marshland caused a variety of problems, including buckled 

foundations, damaged flood-control structures, and severed 

utility lines (Danskin and Freckleton, 1992). The increase in 

pressure also creates the potential for liquefaction of nearsurface earth materials as a result of ground-shaking during a 

severe earthquake (Matti and Carson, 1991).

The shift from agricultural to municipal water use and 

the increasingly restrictive public drinking-water standards 

(U.S. Environmental Protection Agency, 1994; California 

Department of Water Resources, 1995a) have caused considerable concern about ground-water quality. Between 1985 and 

1994, more than 40 municipal supply wells were closed, at 

least temporarily, because concentration of a constituent in 

ground water exceeded public health standards (NBS/Lowry, 

1994). The water-quality constituents cited most frequently 

as exceeding standards include nitrate, organic solvents (TCE 

and PCE), pesticides (DBCP), and radioactivity.

Previous Investigations

The earliest study of the hydrogeology of the San Bernardino area includes maps showing surface-water courses, 

swamps, and irrigated land (Hall, 1888). The earliest comprehensive hydrogeologic analyses of the valley and region were 

made by Lippincott (1902a,b) and Mendenhall (1905, 1908). 

The hydrogeology and basin storage of California’s south 

coastal basins, including the San Bernardino area, were summarized by Eckis (1934). Other studies of the hydrogeology 

of the San Bernardino area include those by Troxel (1954), 

California Department of Water Resources (1957, 1970, 1971, 

1978, and 1979), Dutcher (1956), Dutcher and Burnham 

(1960), Burnham and Dutcher (1960), Dutcher and Garrett 

(1963), and Dutcher and Fenzel (1972).

Geologic mapping of the area was done by Dutcher 

and Garrett (1963), Morton (1974), Matti and others (1985), 

Burtugno and Spittler (1986), and Matti and Carson (1991). 

More recently, a geologic reinterpretation of the area has been 

initiated by D.M. Morton (U.S. Geological Survey, oral commun., 1993).

Geologic hazards of the area were mapped at a scale 

of 1:48,000 by Fife and others (1976). This information and 

additional earthquake data were compiled by Ziony (1985) 

in a comprehensive volume summarizing earthquake hazards 

in southern California and including an extensive discussion 

of specific hazards in the San Bernardino area. The probable 

damage to urban facilities that would result from an earthquake with magnitude 6ML or greater in the San Bernardino 

area was assessed by the California Division of Mines and 

Geology (1993). Land subsidence in the area for the period 

1935–70 was measured by Lofgren (1969) and Miller and 

Singer (1971). Detailed mapping of near-surface sediments in 

the San Bernardino area was done by Matti and others (1985) 

in order to calculate the susceptibility of these sediments to 

earthquake-induced liquefaction (Matti and Carson, 1991).

Figure 4.—Continued.

Introduction 9

Perris Hill San Bernardino Mountains Keller Peak Crafton Hills

Seven Oaks Dam San Andreas fault Norton Air Force Base
Figure 5. Generalized surficial geology of the San Bernardino area, California, adapted from Morton (1974) and Dutcher and Garrett 

(1963).

10 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Basement complex of 

igneous and metamorphic

rocks

bc

bc

bc

bc

bc bc

bc

bc

bc

bc

bc

bc

QTc Sedimentary rocks

QTc

Qoal Older alluvium

Qoal

Qoal

Qoal

Qoal

Qoal

Qoal

Qoal

Qoal

Qual

Qual

Qual Qual

Qrc River-channel deposits

Fault

Oak Glen Fault

Crafton Fault

Fault

Fault L

Fault K

Fault

Redlands

San

Andreas

Fault or ground-water

barrier-May be concealed or

approximately located

Barrier

J

Barrier

J

Barrier

H

Bryn Mawr

Barrier Mentone

Barrier

Barrier G

A

B F

Fault

Fault Loma Linda

Fault

Loma Linda Loma Linda

Fault Rialto-Colton

San

C D

Banning(?)

Barrier

E

Jacinto

Seven

Oaks

Dam

Cajon

Cr

River

River

Cr

Plunge

Warm

Santa

Santa

Ana

Ana

San Timoteo Cr

Cr Cr

City

Mill

 Cr

Waterman

Canyon

Creek

Devil

Canyon

Creek

Lytle

Creek

Geologic contact

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Shandin

Hills

Perris Hill

Gabriel

Mts

San

0 6 KILOMETERS

0 6 MILES

Undifferentiated younger 

 and older alluvium

Younger alluvium

Quaternary Quaternary and Tertiary

Tertiary and Pre-Tertiary

GEOLOGIC UNITS MAP UNITS

EXPLANATION

Qyal

Qyal

Qyal

Qyal

20' 15' 10'

A

A A'

A'

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Norton Air Force

Base

Badlands

CR

Line of section-See figures 23, 24, 37

Fault

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Boundary of Santa Ana

River drainage basin

34

10'

34

05'

117 25' 117 05'
Figure 6. Average annual precipitation in the San Bernardino area, California, 1928–98. Data from the San Bernardino County 

Flood Control District (SBVFCD, 2000) with minor modifications to estimate missing monthly values.

Introduction 11

BASIN

CHINO

BUNKER

HILL

RIALTO - COLTON

BASIN

YUCAIPA BASIN

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake Arrowhead

Silverwood Lake

Cajon

Cable Cr

Cr

River

Cr

Plunge

Warm

Santa

Ana

Cr Cr

City

Mill Cr

Lytle Cr

San Timoteo

Cr

Artificial-recharge basin

Line of average annual precipitation (1928-98)-Interval

5 inches per year

The Zanja

Seven Oaks

Dam

15

215

10

215

15

26.86

16.83 16.89

19.83

16.91

14.11

14.39

13.21 13.80

17.75

13.40

41.83 42.24

12.49

2,017

2146 47723

2166

2194

2286

3058

3144 47306

3162

3273

5140 44671

2027

12.49

2027

San Andreas Fault

San Jacinto Fault

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

15

15

20

25

25

25

30

35

40 35

20

EXPLANATION

San Bernardino Mountains

Crafton Hills

0 6 KILOMETERS

0 6 MILES

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Shandin

Hills

Perris Hill

Gabriel

Mts

San

Fault or ground-water barrier-May be concealed or approximately located

Former marshland

San Bernardino Mountains

Gabriel

Mts

San

Redlands Redlands

San Bernardino San Bernardino

CREEK

LYTLE

BASIN

Data point-Precipitation (top number), in inches and

San Bernardino County Flood Control District station

identifier (bottom number)

20

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Highland Highland

BASIN

River

Santa Ana

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'
Ground-water-quality studies, particularly relating to 

nitrate problems, were done by Eccles and Bradford (1977), 

Eccles and Klein (1978), and Eccles (1979). Studies to quantify and delineate the distribution of nitrate and other forms of 

nitrogen in the unsaturated zone were done by Klein and Bradford (1979) for the Redlands area and by Klein and Bradford 

(1980) for the Highland area (fig. 2). The URS Corporation 

(1986) compiled a list of possible sources of perchloroethylene (PCE) and trichloroethylene (TCE) in the northwest part 

of the Bunker Hill basin and identified areas of contamination 

from analysis of soil-pore gas. Duell and Schroeder (1989) 

conducted an appraisal of ground-water quality in the San 

Bernardino area and analyzed for concentrations of inorganic 

constituents, nitrates, and volatile organic compounds. A map 

report delineating areas of ground-water contamination and 

listing municipal production wells with concentrations of volatile organics, pesticides, nitrate, or radiation exceeding public 

health standards was prepared by NBS/Lowry (1994). The isotopic character of ground water along a section from the base 

of the San Bernardino Mountains near East Twin Creek to the 

I-10–I-15 freeway interchange was investigated by Izbicki and 

others (1998) using depth-dependent sampling methods.

Two areas of ground-water contamination in the San Bernardino area—the Newmark Operable Unit north and east of 

Shandin Hills and the Muscoy Operable Unit south of Shandin 

Hills—are being investigated by the U.S. Environmental Protection Agency (USEPA) under the federal superfund cleanup 

program (URS Corporation, 1993, 1994, 1996). Ground-water 

contamination on, and immediately southwest of Norton Air 

Force Base is being investigated as part of the Installation 

Restoration Program (IRP) as required prior to base closure 

(CDM Federal Programs Corporation, 1997). An additional 

area of ground-water contamination north of Redlands is being 

studied by Lockheed Corporation at the request of the California Regional Water Quality Control Board (1994).

Artificial recharge to the valley-fill aquifer has been studied by Moreland (1972), Warner and Moreland (1972), and 

Schaefer and Warner (1975). Studies of specific aspects of the 

hydrologic system include analysis of geothermal resources 

(Young and others, 1981), generalized streamflow relations 

(Busby and Hirashima, 1972), and rising ground water (San 

Bernardino Valley Municipal Water District, 1981a).

Figure 7. Cumulative departure from average annual precipitation at San Bernardino, California, 

1871–1998. Data from the San Bernardino County Flood Control District, station 47723.

12 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

1870

50

40

30

20

10

0

-10

-20

-30

-40

-50

1880

Average

Period

Average

Period

Dry

Period

Dry

Period

Dry

Period

Wet

Period

Wet

Period

Wet

Period

Wet

Period

1890 1900 1910 1920 1930 1940

YEAR

CUMULATIVE DEPARTURE FROM

AVERAGE ANNUAL PRECIPITATION, IN INCHES

1950 1960 1970 1980 1990 2000
Figure 8. Changes in land use in the San Bernardino area, California, 1933–90.

Introduction 13

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

0 6 KILOMETERS

0 6 MILES

1949

EXPLANATION

Land use

Basin boundary-For Bunker Hill

and Lytle Creek ground-water basins

Urban

Non-urban

Not mapped

1933

1963

1957

1984

1975

1990

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River

Redlands

San Bernardino Mountains

Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Santa Ana River
Numerical simulation of the valley-fill aquifer system 

began with a simplified well-response model developed 

by Durbin (1974) and Durbin and Morgan (1978). A more 

complex ground-water flow model was developed by Hardt 

and Hutchinson (1980) in order to simulate aquifer response 

to the combined effects of natural recharge, artificial recharge 

using imported water, and ground-water pumping. This model 

was used by Hardt and Freckleton (1987) to simulate groundwater-level response to projected recharge and pumping 

through the year 2015. A regional salt-balance model was 

developed for the upper Santa Ana River watershed, including the San Bernardino area (Water Resources Engineers, 

Inc., 1969), and has been used and modified several times to 

answer questions about salt accumulation and nitrate loading 

(Wildermuth, 1991). A two-dimensional simulation of heat 

and ground-water transport through the igneous-metamorphic 

bedrock underlying the unconsolidated deposits in the San 

Bernardino area was done by Hughes (1992).

Several water-management studies have been done for the 

Santa Ana River drainage area and for the San Bernardino area 

in particular. A comprehensive assessment of water demands 

through the year 2015 was made by the California Department of Water Resources (1970, 1971, 1972). At about the 

same time, a detailed safe-yield study (San Bernardino Valley 

Municipal Water District, 1970) was done as part of the adjudication of water resources in the San Bernardino area (State 

of California 1969a,b). During the 1970s, water-management 

studies were required by the State of California to identify the 

amount of land subsidence that had occurred in the previous 

two decades and to estimate the additional subsidence that 

might occur if specific water-management plans were adopted 

in order to meet the projected increases in water demand (Lofgren, 1969; Miller and Singer, 1971). For example, implementation of one plan (A) would satisfy increased demand, but the 

proposed significant increase in pumpage would cause a permanent decline in ground-water levels of more than 300 ft and 

would induce an additional 6 ft of land subsidence (California 

Department of Water Resources, 1970, p. 62).

By about 1980, a new set of water-management studies 

was prompted by an overly full ground-water basin caused 

by increased recharge of abundant native runoff and imported 

water. These studies focused on removing ground water from 

the urbanized marshland in order to halt ongoing damage from 

increased hydrostatic pressure and to prevent damage from liquefaction in the event of a major earthquake. The quantity of 

recharge and pumpage needed to tilt the water table—keeping 

it high in the alluvial fan area and low in the marshland—was 

identified by S.S. Papadopulos and Associates, Inc. (1985) 

using constrained optimization techniques. Using similar 

techniques, but taking into account the nonlinear response of 

ground-water levels to evapotranspiration, Danskin and Freckleton (1992) identified the minimum pumpage from existing 

and proposed wells needed to solve the high ground-water 

problem while maintaining acceptably high ground-water 

levels near municipal and agricultural wells.

Previous investigations described most of the major geologic and hydrologic features of the area and presented potential solutions for some water-management issues. Despite this 

wealth of information, the present study was prompted by the 

complexity of solving multiple water-quantity and water-quality problems simultaneously and by the lack of an integrated 

understanding of the surface-water and ground-water systems.

A draft version of this report was completed in 1997, 

and following review, important revisions were made to the 

ground-water data and ground-water flow model. These revisions included increasing the areal extent of the ground-water 

flow model, extending the period of data analysis and simulation from 1994 to 1998, revising ground-water pumpage 

and return flow, modifying conductance values of streams to 

better simulate recharge in very wet years, revising underflow 

along the basin perimeter, changing the method of simulating 

ground-water outflow across the San Jacinto fault from a constant value to a head-dependent value, and adding an analysis 

of precipitation on the ground-water basin and how it contributes to surface-water outflow and ground-water recharge. 

Despite these several changes, performance of the groundwater flow model and hydrogeologic conclusions from the 

study remain remarkably similar. It is likely, however, that the 

credibility of both the model and conclusions were enhanced 

by the more rigorous, integrative analysis.

Acknowledgments

A large group of individuals from a variety of agencies 

aided in this study by providing data, interpretations, and valuable personal observations about the San Bernardino area. The 

authors especially thank Michael H. Lowe, Joseph F. Stejskal 

(retired), and James G. Dye (previously with), City of San 

Bernardino; Michael L. Huffstutler (retired), City of Redlands; 

David V. Garcia, Babs Makinde-Odusola, and Zahra Panahi, 

City of Riverside; Robert E. Martin, East Valley Water District; Hooite Rugge, Fontana Union Water Company; Eugene 

P. McMeans, Riverside-Highland Water District; Kenneth J. 

Mashburn and Kenneth A. Miller, San Bernardino County 

Flood Control; D. Burnell Cavender, William J. Hiltgen, Peter 

J. Russer (deceased), and Nereus L. Richardson and Douglas 

Headrick both previously with the San Bernardino Valley 

Water Conservation District; Kevin P. Mayer, U.S. Environmental Protection Agency; Steven E. Mains, Western Municipal Water District; and Anthony W. “Butch” Araiza and Ira B. 

Pace, West San Bernardino County Water District. 

14 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Several consultants provided important technical information and an ongoing review of our work. These include 

Richard W. Corneille and Donald J. Schroeder, Camp Dresser 

& McKee, Inc.; Dennis E. Williams and Johnson Yeh, Geoscience Support Services, Inc.; Dennis L. Bane and Natalyn Ala, 

URS Consultants; Eric A. Hodder, Lockheed Martin Corporation; Dennis B. Jamison and Roy J. Marroquin, Hydro-Search, 

Inc.; Robert B. “Barry” Bierschbach, formerly with NBS/

Lowry; and Mark J. Wildermuth, Wildermuth Environmental. 

John F. Mann (deceased), a long-time friend and colleague, improved the work considerably with his insightful 

questions and comments. Douglas M. Morton and Tien-Chang 

Lee at the University of California at Riverside and Jonathon 

C. Matti at the University of Arizona provided important 

insights about the geology of the San Bernardino area. Gary 

A. Maxwell (deceased), J. Carlos Hernandez, and, Kimball 

L. Stumpf, each with the U.S. Geological Survey, provided 

the expertise and persistence to install real-time ground-water 

monitoring equipment.

The authors deeply appreciate the considerable aid, 

advise, and patience provided by the Board of Directors, management, and staff of the San Bernardino Valley Municipal 

Water District, including G. Louis Fletcher (retired), Robert 

L. Reiter, Randy Van Gelder, Samuel H. Fuller, and Robert 

M. Tincher, and previous employees Stephen P. Stockton 

and Marisue P. Meza. Typing, drafting, editing, layout, and 

technical review were provided by U.S. Geological Survey 

colleagues Anna C. Borlin, R. R. “Phil” Contreras, Devin L. 

Galloway, Charles A. Kaehler, Alice I. McCracken, Eric G. 

Reichard, Laurel L. Rogers, Claire Tiedeman, Carol A. Sanchez, and Jerrald A. Woodcox, contract editor. 

Hydrology

Historical hydrologic conditions in the San Bernardino 

area in the late 1880’s are shown in figure 9. Important characteristics of the hydrologic system at that time include intermittantly flowing streams, marshlands, and an extensive artesian 

area. These characteristics, except an intermittantly flowing 

Santa Ana River, represent pre-development conditions that 

probably existed for hundreds or thousands of years prior to 

human intervention.

As depicted in figure 9, streams emanate from the San 

Bernardino Mountains but do not flow continuously across the 

land surface, except during the largest floods. Rather they stop 

after a short distance, having lost all flow as recharge to the 

ground-water system. Then, further downstream, flow resumes 

as a result of ground water, restricted from flowing across the 

less permeable San Jacinto fault, rising to the land surface and 

reestablishing flow in the streams. This intermittant condition was true for all streams except for Lytle Creek and for 

the Santa Ana River, prior to diversions in the mid 1800s. Of 

equal historical importance are the extensive, but somewhat 

discontinous marshlands, including bogs and swamps. These 

areas are generally proximal to the lower stream reaches and 

likely also result from the rising ground water, similar to the 

formation of cienagas in other semiarid basins. The nearly 

continuous marshland between the Santa Ana River and Warm 

Creek limited human development in that area until groundwater levels declined during the drought of the 1950s and 

1960s (fig. 7). During wetter periods, such as during the early 

1900s and 1940s, the marshland between the two streams 

upstream of the San Jacinto fault had standing water, was a 

favorite area for bird-watching, and was used by residents for 

boating (fig. 10). 

Also noteworthy is the large artesian area which covers 

nearly one-third of the Bunker Hill basin and extends nearly 

to the base of the San Bernardino Mountains in the vicinity of 

Perris Hill. This extensive area of upward ground-water flow 

results from infiltration of surface water to the ground-water 

system immediately adjacent to the mountain front, ponding of 

the ground-water system by the San Jacinto fault, and minimal 

development of the ground-water system by the late 1800’s.

Surface-Water System

The surface-water system in the San Bernardino area 

includes several natural streams and many structures designed 

to convey or recharge surface water (fig. 11). These structures 

include canals, ditches, and pipelines; the California Aqueduct that conveys imported water from northern California; 

flood-control, sewage-effluent, and debris basins; artificialrecharge basins for enhancing recharge of diverted streamflow 

and imported water; and the Seven Oaks Dam on the Santa 

Ana River. Major components of the surface-water system are 

identified on plate 1. The routing of water among these components is shown diagrammatically on plate 2.

Modifications to the natural surface-water system began 

in the early 1800s. In about 1810, the first diversion from 

the Santa Ana River was made to supply water for irrigation (Scott, 1977). In 1848, widespread irrigation began and 

prompted an equally rapid increase in water use (Scott, 1977). 

Many water agencies were formed to divert surface flow from 

the Santa Ana River and its tributaries and to organize delivery 

of the water throughout the surrounding area, primarily to 

irrigate citrus crops.

Hydrology 15
Figure 9. Historical hydrologic conditions in the San Bernardino area, California, circa 1880. Adapted from Hall (1888), Mendenhall 

(1905), and Fife and others (1974).

16 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Streams surveyed in 1880-90's

Approximate artesian area in the early 1900's

BASIN

CHINO

BASIN

BUNKER

HILL

RIALTO - COLTON

BASIN

YUCAIPA BASIN

San Andreas

Fault

San

Jacinto Fault

117o25' 20' 15' 10' 117o05'

34o

15'

34o

10'

34o

05'

EXPLANATION

San Bernardino Mountains

Crafton Hills

0 6 KILOMETERS

0 6 MILES Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Shandin

Hills

Perris Hill

Gabriel

Mts

San

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

Bog, swamps, and marshlands

15

215

10

215

San Bernardino Mountains

Gabriel

Mts

San

15

Redlands Redlands

San Bernardino San Bernardino Highland Highland

CREEK

LYTLE

BASIN

Fault or ground-water barrier-May be concealed or approximately located Boundary of Santa Ana

River drainage basin

Warm

Cr
As irrigation increased, the Santa Ana River flowed intermittantly and conservation measures became necessary. Artificial-recharge basins (fig. 11) were constructed on the major 

streams in order to increase the effective yield of the combined 

surface-water and ground-water systems. During periods of 

surplus runoff, the excess water was routed to the basins in 

order to recharge the ground-water system. During subsequent 

periods of low runoff and during periods of high demand, such 

as summer, the recharged water was extracted from wells.

After the mid-1940s, water use for irrigation decreased; 

however, rapid urbanization of agricultural land (fig. 8) caused 

an increase in water use for municipal purposes (Scott, 1977). 

This increase in water use and declining runoff prompted a 

lawsuit filed in 1963 by the Orange County Water District 

against other users of surface water in the Santa Ana River 

watershed. The suit, along with a related one regarding 

ground-water use, was settled in 1969 with a stipulated judgement that defined surface-water rights and created a watermaster to monitor surface-water use in the Santa Ana River watershed (State of California, 1969a,b). In 1972, major pipelines 

were completed that allowed surface water from northern California to be imported into the San Bernardino area. Although 

this external source provided additional flexibility for local 

water managers, it was not used to significantly increase the 

local supply of water, perhaps because of the relatively high 

cost of imported water. The net result of these various changes 

has been that total water use in San Bernardino has changed 

little since about 1960.

Concurrent with the development of agriculture and the 

increasing population of southern California, hydroelectric 

power production was begun on the Santa Ana River, Mill 

Creek, Lytle Creek, and Devil Canyon Creek. More than 

50 percent of the average annual inflow from these streams is 

diverted from the channels into penstocks and used to generate 

hydroelectric power. Typically, a gaging station is present on 

the natural stream channel and on any upstream diversions. As 

a result, stream discharge is reported as uncombined discharge 

(flow in the natural stream channel) and combined discharge 

(flow in the natural stream channel plus measured discharge 

for all upstream diversions, most of which are used to generate hydroelectric power). The adjudication of surface-water 

rights has ensured that most streamflow into and out of the 

San Bernardino area is measured continuously and is reported 

annually by the local watermaster.

Figure 10. Urbita Springs area, 1903. An extensive marshland (cienaga) formed by ground water rising to the land 

surface between the Santa Ana River and Warm Creek, just upstream of the San Jacinto fault, was augmented for 

recreation by artesian flow from the Urbita Springs well.

Hydrology 17
Figure 11. General features of the surface-water system in the San Bernardino area, California, 1998.

18 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

FAULT

SAN

ANDREAS East

Twin

Cr

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Creek

River

River

Cr

Plunge

Warm

Santa

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

San Bernardino Mountains

Gabriel

Mts

San

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

EXPLANATION

Crafton Hills

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Shandin

Hills Perris Hill

San Bernardino Mountains

Rialto-Colton Basin

California Aqueduct

Gabriel

Mts

San

Redlands Redlands

San Bernardino San Bernardino

2

1

5

3

6

7

4

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Fault or ground-water

barrier-May be concealed

or approximately located

Basin boundary-Bunker

Hill and Lytle Creek groundwater basins shaded in darker

gray

Major pipeline

Boundary of Santa Ana

River drainage basin

Stream, canal, or ditchBottom may be native earth

or concrete

Artificial-recharge basin

and number-Refer to 

table 5

2

Highland Highland

0 6 KILOMETERS

0 6 MILES

Baseline

feeder

Foothill pipeline

Lytle pipeline

d

e

D

a B

C

A

I

J

K

L

f

c

H

G

F

Gaging stations-Continuous Gaging stations-Discontinued

11054001

11051501 Santa Ana River near Mentone

Mill Creek near Yucaipa

Plunge Creek near East Highlands

East Twin Creek near

Arrowhead Springs

Devil Canyon Creek near

San Bernardino

11058500

11063680

11062001

11065000

11059300

11060400

Lone Pine Creek near

Keenbrook

Lytle Creek near Fontana

Lytle Creek at Colton

Santa Ana River at E Street

Warm Creek near San Bernardino

Cajon Creek below Lone Pine Creek,

near Keenbrook

11063510

11063000

11065801

11066050 Santa Ana River at Colton

San Timoteo Creek

near Redlands

11057000

11058600 Waterman Canyon Creek

near Arrowhead Springs

Cajon Creek near

Keenbrook

Warm Creek near Colton

11055501

11063500

b

a

d

c

e

f

I

A

H

G

E

F 11055801 City Creek near Highland

D

C

K

L 11057500 San Timoteo Creek near Loma Linda

J

B

E

b

The Zanja

Seven Oaks Dam
Seven Oaks Dam on the Santa Ana River was completed 

in 1999. The primary purpose of this massive earthen structure 

is to control flood water and to prevent damage to downstream 

agricultural and urban land such as occurred in 1938. A 

secondary benefit of the dam is to provide a conservation pool 

with about 50,000 acre-ft of storage that is used to augment 

local water supplies. Without the conservation pool, some of 

this water would flow out of the area and be unavailable for 

either ground-water recharge or direct delivery to a watertreatment plant.

Sources of Inflow and Outflow

Most surface-water flow in the San Bernardino area 

originates as runoff into streams and creeks that drain the San 

Gabriel and San Bernardino Mountains and as runoff from the 

hills bordering San Timoteo Creek (fig. 11 and pl. 1). Runoff 

into major streams is measured at several gaging stations operated by the U.S. Geological Survey (USGS) (fig. 11). A lesser 

quantity of runoff is ungaged and enters the area as flow in 

small creeks and as sheetflow from the surrounding mountains. Other sources of surface-water flow include: local runoff 

from precipitation on the land surface of the Bunker Hill and 

Lytle Creek basins; water imported from northern California 

in the California Aqueduct; wastewater discharge from the 

Redlands and the San Bernardino sewage-treatment plants and 

from the California Edison steam power-generation plant; and 

ground-water seepage into Warm Creek during periods of high 

ground-water levels in the vicinity of the former marshland 

(fig. 2).

Gaged Runoff

As required by the adjudication of water rights in the area 

(State of California, 1969a,b), nearly all surface water that 

enters or leaves the Bunker Hill and Lytle Creek basins is measured. Between 1945 and 1998, inflow was measured routinely 

at eleven continuous-recording gaging stations along the base 

of the San Bernardino and San Gabriel Mountains (fig. 11). Of 

the total gaged inflow, almost 80 percent occurs in the three 

largest streams—the Santa Ana River, Lytle Creek, and Mill 

Creek (fig. 12). Outflow from the basins is measured at three 

continuous-recording gaging stations on the Santa Ana River, 

Warm Creek, and Lytle Creek.

Total gaged inflow and outflow for the San Bernardino 

area for 1945–98 are shown in table 1. During this 54-year 

period, total gaged inflow averaged about 146,000 acre-ft/yr, 

with a minimum of about 36,000 acre-ft in 1990 and a 

maximum of about 674,000 acre-ft in 1969. Total gaged 

outflow averaged about 68,000 acre-ft/yr with a minimum 

of about 12,000 acre-ft in 1968 and a maximum of about 

370,000 acre-ft in 1980.

Figure 12. Average annual discharge of gaged streams flowing into the San Bernardino area, California, 1945–98.

Hydrology 19

Devil Canyon Creek

Santa Ana River

Lytle Creek

Cajon Creek

9,134

6.2%

Mill Creek

27,693

18.9%

Average annual discharge,

 in acre-feet per year Percent of total average

annual discharge

(146,742 acre-feet per year)

San Timoteo Creek

Waterman Canyon Creek

32,917

22.4%

8,431

5.7%

6,323

4.3%

East Twin Creek

3,799

2.6%

2,506

1.7%

2,187

1.5%

1,237

0.8%

52,513

35.8%

City Creek

Plunge Creek
Figure 13. Linear-regression relations used to estimate annual stream discharge in the San Bernardino area, California. Annual data 

points are shown; values are in thousands of acre-feet per year.

20 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

0

0 50 100 150 200 250

0

0 50 100 150 200 250

0

0 50 100 150

SANTA ANA RIVER NEAR MENTONE,

COMBINED DISCHARGE (11051501)

EAST TWIN CREEK

NEAR ARROWHEAD SPRINGS (11058500)

SANTA ANA RIVER NEAR MENTONE,

COMBINED DISCHARGE (11051501)

LYTLE CREEK NEAR FONTANA,

COMBINED DISCHARGE (11062001)

WATERMAN CANYON CREEK

NEAR ARROWHEAD SPRINGS (11058600)

LYTLE CREEK NEAR FONTANA, 

COMBINED DISCHARGE (11062001)

TOTAL BASIN INFLOW 

CAJON CREEK

NEAR KEENBROOK (11063000) 

TOTAL BASIN OUTFLOW 

SANTA ANA RIVER

AT E STREET (11059300) 

TOTAL LYTLE CREEK INFLOW

SANTA ANA RIVER 

AT E STREET (11059300)

LYTLE CREEK AT COLTON (11065000)

SAN TIMOTEO CREEK 

NEAR LOMA LINDA (11057500)

SAN TIMOTEO CREEK

NEAR REDLANDS (11057000)

SANTA ANA RIVER

NEAR MENTONE (11051500)

SANTA ANA RIVER

AT RIVERSIDE NARROWS (11066500)

SANTA ANA RIVER NEAR MENTONE,

COMBINED DISCHARGE (11051501)

SAN TIMOTEO CREEK

NEAR REDLANDS (11057000)

PLUNGE CREEK NEAR EAST HIGHLANDS, 

COMBINED DISCHARGE (11055501)

MILL CREEK NEAR YUCAIPA,

COMBINED DISCHARGE (11054001)

SANTA ANA RIVER NEAR MENTONE,

COMBINED DISCHARGE (11051501)

50

25

0

20

15

 5

10

0 5 10 15 20

0

250

200

150

100

50

0 50 100 150 200 250

0

50

25

75

0 50 100 150 200

50

100 150

100

0 100 200 300 0 100 200

0

2

1

400

200

100

300

0 100 200 0 1 2 0 50 100 150 200 250

0

300 400

300

50

150

250

100

200

10

 6

 8

 2

 4

0 0

300

100

200

0

100

50

25

75

C

H

B

D E

I

A

J K L

G

F

LONE PINE CREEK

NEAR KEENBROOK (11063500)

LYTLE CREEK NEAR FONTANA, 

COMBINED DISCHARGE (11062001)

0

2

6

10

4

8

0 40 80 120 160

y = 0.136x - 826

r = 0.92

y = 0.611x - 135

r = 0.99

y = 0.663x - 1,566

r = 0.87

y = 0.288x - 1,310

r2 = 0.71

y = 0.468x - 14,837

r2 = 0.92

y = 1.07x + 772

r2 = 0.87

y = 1.40x + 15,647

r2 = 0.86

y = 0.559x - 1,644

r2 = 0.80

2 2

2

y = 0.041x - 934

r2 = 0.74

y = 1.06x - 41,465

r2 = 0.95

(Includes measured data from the Santa Ana R., 

 Mill Cr., Plunge Cr., City Cr., San Timoteo Cr.,

 East Twin Cr., Waterman Canyon 

 Cr., Lytle Cr., Cajon Cr., Warm Cr.,

 and Devil Canyon Cr.) 

y = 0.244x - 4,359

 = 0.88 r2

(Includes measured data from Lytle Cr.,

 Cajon Cr., and Lone Pine Cr.)

2

y = 0.053x - 313

r = 0.87
Although measured inflow and outflow records for 

1945–98 are nearly complete, estimation of some discharge 

values was required. For gages with only 11 months of data, 

the 12th month was estimated using qualitative comparisons 

with adjacent streams. In most cases, discharge during the 

missing months probably was zero. For longer periods of 

missing record, estimated annual streamflow values were calculated using linear-regression equations. Typically, discharge 

at gaging stations with missing record was estimated using 

data from the Santa Ana River gage, which has a complete 

record for 1945–98. Discharge at some gaging stations with 

missing record, such as the Waterman Canyon Creek gage 

(table 1), was estimated using data from a nearby gaging station with a similar drainage area, in this case from the East 

Twin Creek gage. For Cajon Creek, different combinations of 

gaging-station measurements and regression equations were 

needed to compile a complete record.

Graphs of the annual streamflow data used for the linear 

regressions, the equations themselves, and the related r2

values are shown in figure 13. The r2 value is a measure of the 

goodness-of-fit of the data to the regression equation. If the 

equation (line) is a good estimator of the data, the r2 value will 

be near 1.0; if it is a poor estimator, the value will be near zero 

(Davis, 1986, p. 182).

Total gaged surface-water inflow (table 1) varies greatly 

from year to year, depending on local weather conditions. 

This variability and the uncertainty of inflow for a given year 

can be described in a cumulative probability graph (fig. 14). 

The graph, developed using data for total gaged surface-water 

inflow (table 1) and a Log Pearson Type III analysis (Linsley 

and others, 1975, p. 343), shows the likelihood of different 

quantities of annual inflow. For example, 50 percent of the 

time, total inflow will be less than about 100,000 acre-ft/yr; 

only 10 percent of the time will total inflow exceed about 

290,000 acre-ft/yr. Selected years are labeled to show the 

probabilities of total inflow associated with above-average 

(wet) years (1969, 1983, 1998) and below-average (dry) years 

(1964, 1976, 1990). The deviation for very wet years between 

measured data and the theoretical distribution (fig. 14) is not 

well understood, but may result from either the type of precipitation (rain versus snow) or from the intensity of precipitation 

(many, small storms versus a few, large storms).

The relation between cumulative gaged surface-water 

inflow and outflow for 1945–98 is shown in figure 15. The 

slope of the double-mass curve indicates the quantity of inflow 

leaving the basin and the quantity retained within the basin. 

During four time periods between 1945 and 1998, the slope of 

the curve remains relatively constant. During period I 

(1945–51), 60 percent of the inflow left the basin and 40 percent remained; during period II (1952–79), 37 percent left and 

63 percent remained; during period III (1980–92), 64 percent 

left and 36 percent remained; during period IV (1993–98), 

43 percent left and 57 percent remained. Using a similar 

graphical analysis for years 1945–80, Hardt and Freckleton 

(1987) identified slopes for periods I and II and suggested that 

the marked difference in slope might be related to the height 

of ground-water levels in the southwestern part of the Bunker 

Hill basin.

When ground-water levels in the former marshland are 

above land surface, ground-water rises into Warm Creek and is 

discharged out of the basin. This additional discharge effectively decreases the percentage of inflow retained in the basin. 

This type of condition was present during periods I and III. 

During these two periods, ground-water levels were relatively 

high and a similar percentage of inflow was retained (40 and 

36 percent, respectively). In contrast, during periods II and 

IV, ground-water levels declined, particularly in the former 

marshland between Warm Creek and the Santa Ana River near 

the San Jacinto fault. Ground water rising into Warm Creek 

decreased to zero, and the percentage of inflow retained in the 

basin (63 and 58 percent, respectively) was about 50 percent 

greater than for periods I and III.

Figure 14. Cumulative probability of annual gaged surfacewater inflow for the San Bernardino area, California, 

1945–98. Values of inflow are listed in table 1.

Hydrology 21

1,000

 500

 400

 300

 200

 100

 50

 40

 30

 20

99

99

95

95

98

98

90

90

80

80

70

70

60

60

50

50

40

40

30

30

20

20

10

10

5

5

2

2

1

1

PROBABILITY THAT INFLOW WILL BE GREATER

TOTAL ANNUAL GAGED INFLOW, IN THOUSANDS OF ACRE-FEET PER YEAR

PROBABILITY THAT INFLOW WILL BE LESS

EXPLANATION

Total gaged inflow-Selected years (1990) are

identified

Theoretical distribution-Based on Log Pearson

Type III distribution of the natural log values

1969

1945

1993

1980

1978

1977

1976

1990 1961

1964

1995

1983

1998

1979

1990
Figure 15. Cumulative gaged surface-water inflow and outflow in the San Bernardino 

area, California, 1945–98.

22 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

EXPLANATION

Slope of line segment-Value of 0.64 means that 64 percent of gaged inflow

left the San Bernardino area as outflow during time period III 

Line segment-Indicates time period when the percent of inflow retained in

the area remained relatively constant

4 5 6 7 8

CUMULATIVE GAGED INFLOW, IN MILLIONS OF ACRE-FEET

Time period-Identified by I, 1945-51; II, 1952-79; III, 1980-92; IV, 1993-98

Data point-Selected calendar year (1980), plotted at end of annual inflow

5

4

2

1

0

CUMULATIVE GAGED OUTFLOW,

IN MILLIONS OF ACRE-FEET

0 1 2 3

III

0.64

3

1980

I II III IV

0.60 0.37 0.64

1945

1969

1978

1979

1983

1980

1992

1998

1951

1952

0.43
Urbanization has been suggested as a possible explanation for the change in percentage of inflow leaving the San 

Bernardino area. During the period II, urban acreage began 

increasing, rising sharply during 1957–63 (fig. 8). In 1962, 

urban acreage exceeded irrigated acreage for the first time 

(California Department of Water Resources, 1985). A likely 

consequence of increased urban acreage is an increased acreage of impervious surfaces, which in turn would increase the 

quantity of inflow leaving the area. The percentage of inflow 

leaving the area during period II, however, is less than during 

period I, not more as would be expected if urbanization had a 

major affect on basin outflow. Similarly, the percentage of outflow during period IV is less than in the immediately preceeding period III, not more.

Urbanization, however, may produce a modest increase in 

basin outflow for time periods with similar depths to ground 

water. Comparing periods I and III shows a slightly greater 

percentage of inflow leaving the basin during the more recent, 

more urbanized period (60 increased to 64). Similarly for 

periods II and IV, the percentage of inflow leaving the basin 

increased from 37 to 43. 

Discharge for the Santa Ana River itself is a reliable indicator of runoff to the San Bernardino area, both for individual 

streams (fig. 13) and for total inflow (fig. 16) . Since 1896, 

the river has been gaged continously where it flows out of the 

mountains. Discharge data used in this report for the Santa 

Ana River include all upstream diversions and is referred to as 

the combined-flow record (USGS station number 11051501). 

Some discharge data, particularly during the earliest years and 

during the floods of 1916 and 1927, are missing. Since 1928, 

however, the record is complete and comprises one of the most 

important hydrologic datasets in the San Bernardino area. 

As a predictor of total gaged inflow for the San Bernardino area, the Santa Ana River is remarkably accurate. For 

the period 1945–98, only 1978 appears to be anomalous, with 

discharge for both Lytle and Cajon Creeks being unusually 

high (fig. 16; table 1). In most years, total gaged inflow to 

the San Bernardino area is about three times discharge in the 

Santa Ana River at the base of the mountains. 

In order to estimate other sources of gaged and ungaged 

inflow, the longterm average discharge for the Santa Ana River 

for 1928–98 was used to calculate annual values, expressed 

as a percent of longterm average runoff (table 2). The long, 

gaged record used to develop these percentages and the high 

correlation between the Santa Ana River and other surfacewater inflows make the annual values in table 2 exceptionally 

useful both for historical analysis and for future management 

scenarios.

Figure 16. Relation between discharge in the Santa Ana River at the base of the mountains (USGS station 11051501) and total 

inflow to the San Bernardino area, 1945–98. Values are listed in table 1. During calendar year 1978, inflow for Lytle and Cajon 

Creeks was unusually high.

Hydrology 23

y = 2.8718x

r2 = 0.9472

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

0 50,000 100,000 150,000 200,000 250,000

DISCHARGE IN THE SANTA ANA RIVER AT MENTONE, IN ACRE-FEET PER YEAR

TOTAL INFLOW TO THE SAN BERNARDINO AREA,

IN ACRE-FEET PER YEAR

(1978)
Ungaged Runoff

Ungaged runoff in the San Bernardino area is derived 

largely from triangular areas between gaging stations in the 

San Gabriel and San Bernardino Mountains (fig. 17). Some 

ungaged flow also runs off Crafton Hills, the badlands, and 

small bedrock outcrops within the Bunker Hill basin, such as 

Shandin Hills. Ungaged runoff occurs as flow in small creeks 

and as sheetflow from steep bedrock surfaces. Several small 

debris basins have been constructed at the base of the San Bernardino Mountains to capture ungaged runoff and related sediment and to prevent damage to nearby homes (pl. 1; California 

Department of Water Resources, 1970, fig. 11).

The quantity of ungaged runoff for 1928–98 was estimated for each area shown in figure 17. Similar ungaged areas, 

defined by the Western−San Bernardino Watermaster (1972, 

plate 26), were renumbered and modified slightly to conform 

to the present study-area boundaries. Acreage (fig. 17) and 

mean precipitation for 1928–98 (fig. 6) were calculated for 

each area using the GIS. The product of these two values is 

potential ungaged runoff (table 3). Evapotranspiration, however, consumes most of this potential runoff, leaving a much 

smaller amount that actually enters the Bunker Hill and Lytle 

Creek basins. 

Determining this amount is much more problematic and 

commonly is done using a rainfall-runoff relation developed 

for a nearby gaged drainage. This technique was used by the 

California Department of Water Resources (1971, p. 133) to 

estimate total ungaged runoff entering the Bunker Hill, Lytle 

Creek, and Yucaipa basins. For water years 1935–60, total 

estimated ungaged runoff into these three basins averaged 

21,420 acre-ft/yr. This amount is about 25 percent of the total 

potential runoff for this larger area. Based on these previous studies, the percentage of potential runoff for ungaged 

areas bordering the San Bernardino area was assumed to be 

25 percent (table 3). A slightly lesser value of 20 percent was 

assumed for runoff from the more permeable deposits in or 

near the badlands (areas 10 and 11, fig. 17). Using these values, average ungaged runoff into the San Bernardino area for 

1928–98 was estimated to be about 17,000 acre-ft/yr (table 3). 

Uncertainty in estimating average annual ungaged runoff, 

however, can be quite high—possibly as great as 50 percent. 

For example, the calculations of ungaged runoff made by the 

California Department of Water Resources (1971, p. 133) 

for water years 1935–60 yielded values about 35 percent 

greater than those calculated by J.C. Hanson (Western−San 

Bernardino Watermaster, 1972, p. 545–554). Such variability 

can result from different estimates for ungaged area, precipitation, infiltration, or evaporation.

Table 2. Percent of long-term average annual runoff for the 

Santa Ana River, California, 1945–98.

[Annual values calculated as a percent of long-term average annual discharge 

(53,947 acre-feet) for calendar years 1928–98 for the Santa Ana River near 

Mentone (station number 11051501, table 1); average for years 1945–98]

Calendar 

year

Percent of 

long-term 

average runoff

1945 121

1946 93

1947 62

1948 59

1949 63

1950 49

1951 45

1952 106

1953 50

1954 80

1955 51

1956 50

1957 48

1958 128

1959 49

1960 46

1961 29

1962 62

1963 32

1964 33

1965 76

1966 121

1967 113

1968 55

1969 401

1970 70

1971 58

1972 43

Calendar 

year

Percent of 

long-term 

average runoff

1973 105

1974 69

1975 58

1976 57

1977 43

1978 204

1979 190

1980 407

1981 62

1982 114

1983 302

1984 72

1985 57

1986 80

1987 45

1988 39

1989 33

1990 24

1991 49

1992 73

1993 315

1994 66

1995 231

1996 86

1997 66

1998 216

 Average 97

24 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 17. Ungaged areas bordering the Bunker Hill and Lytle Creek basins in the San Bernardino area, California.

Hydrology 25

8

12

10

9

YUCAIPA BASIN

Crafton Hills

Crafton Fault

East

Twin

Cr

Cajon

Cable Cr

Cr

Cr

Plunge

Warm

 Cr

Cr City

Lytle

Cr

San Timoteo

Cr

River

River

Santa

Santa

Ana

Ana

Mill

Mill

 Cr

 Cr

Devil

Canyon

Creek

Waterman

Canyon

Creek

Lake Arrowhead

Silverwood

Lake

Zanja The

Seven Oaks Dam

4

5

6

8

12

10

11

7

12

2

1

3

12

YUCAIPA BASIN

Crafton Hills

Badlands

EXPLANATION

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Shandin

Hills

Perris Hill

Inset A. Ungaged runoff area 9.

See inset A

Redlands Redlands

San Bernardino San Bernardino

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Artificial-recharge basin

Selected gaging stations

Discontinued

Continuous

Fault or ground-water barrier-May be concealed

or approximately located

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

1 Boundary of area of estimated ungaged runoffNumber corresponds to table 3 

Mts

Badlands

Gabriel San

San Bernardino Mountains

Boundary of Santa Ana River drainage basin

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

0 6 KILOMETERS

0 6 MILES
Average ungaged runoff for 1945–98 was calculated 

using mean precipitation data for San Bernardino (San Bernardino County Flood Control District, station 47723). The 

ratio of mean precipitation for the two periods (1945–98 and 

1928–98) was 0.946 with 1928–98 being somewhat wetter. 

Therefore, average ungaged runoff for the 1945–98 period was 

about 16,000 acre-ft/year. 

Annual values of ungaged runoff were calculated for each 

area for 1945–98 using an annual runoff index (PSARRO

k

) based 

on discharge in the Santa Ana River (table 2). This method 

can be summarized as:

QUngagedRO

i, k = QUngagedROi, 1928–98 (QGagedROSAR, k / QGagedROSAR, 

1928–98) (1a)

or more simply as

QUngagedRO

i, k = QUngagedROi, 1928–98 (PSARRO k) , (1b)

where

PSARRO

k is average annual runoff for the Santa Ana River 

for calendar year k, compared to longterm 

average runoff for 1928–98, in percent;

QUngagedRO

i, k is ungaged runoff from area i for calendar year 

k, in acre-ft /yr;

QUngagedRO

i, 1928–98 is average annual runoff from ungaged area i for 

calendar years 1928–98, in acre-ft/yr;

QGagedRO

SAR, k is gaged discharge for the Santa Ana River for 

calendar year k, in acre-ft/yr; and

QGagedRO

SAR, 1928–98 is average annual discharge for the Santa Ana 

River for calendar years 1928–98, in 

acre-ft/ yr.

Annual values of ungaged runoff during 1945–98 ranged from 

about 4,000 acre-ft in 1990 to about 68,000 acre-ft in 1980. 

In most years, it is unlikely that any ungaged runoff flows 

all the way through the basins and becomes part of gaged 

outflow (table 1). Rather, ungaged runoff probably follows the 

pattern of streamflow described by Mendenhall (1905) and 

illustrated in figure 9—water flows only a short distance from 

the mountain front before disappearing into the soil. Some 

additional evapotranspiration may occur from the unconsolidated deposits bordering the basins, but most ungaged runoff 

probably recharges the ground-water system.

Local Runoff

Local runoff in the San Bernardino area occurs from precipitation falling on the unconsolidated deposits and urbanized 

areas within the Bunker Hill and Lytle Creek basins. This runoff is in addition to the gaged and ungaged runoff that occurs 

as a result of precipitation in the surrounding mountains. 

As in other semiarid basins, the potential evapotranspiration in the San Bernardino area is high, averaging more than 

76 inches per year, nearly five times the average annual precipitation (San Bernardino County Flood Control District, 1975). 

As a result, most precipitation, which falls almost exclusively 

as rain on the basins, is evaporated or transpired before it can 

infiltrate or run off. However, also typical of a semiarid basin, 

many storms in the San Bernardino area have a short duration 

and high intensity, which means these events are less affected 

by evapotranspiration and may produce some runoff. During exceptionally wet years, such as 1969 and 1993 (fig. 14), 

precipitation greatly exceeds daily evapotranspiration, and 

a significant quantity of local runoff is evident—streets are 

flooded, small ditches are overtopped by flow, and normally 

dry catchment basins are full.

Estimates of local runoff were made by the California Department of Water Resources (1971) using measured 

precipitation at 28 stations in and adjacent to the San Bernardino area. During water years 1935–60, precipitation on 

the water-bearing materials, defined essentially as the nonmountainous part of the area, averaged 1.47 ft/yr (17.6 in/yr). 

Consumptive use was assumed to account for about 86 percent 

of this precipitation, and the remaining 14 percent (0.20 ft/yr) 

was assumed to be available for either runoff or ground-water 

recharge. For the San Bernardino area, this latter percentage equals about 15,000 acre-ft/yr of either local runoff or 

recharge from local runoff. Percolation of direct precipitation 

within the San Bernardino area was estimated by the California Department of Water Resources (1986, tables 17,18) to 

average about 8,400 acre-ft/yr for water years 1935–60. Using 

these estimates of precipitation and percolation, an average 

of about 6,600 acre-ft/yr of local runoff (15,000 minus 8,400) 

would be expected to leave the area as a result of direct precipitation on the unconsolidated valley-fill materials.

The quantity of local runoff, however, can vary greatly 

from one year to another, as a result of different quantities of 

annual precipitation, different intensities of precipitation for 

individual storms, and changes in land use. For example in 

1980, when precipitation was much greater than average, percolation of direct precipitation was estimated to be about five 

times the average quantity, or about 42,000 acre-ft/yr (California Department of Water Resources, 1986, tables 17,18); 

undoubtedly, local runoff during 1980 also was much greater 

than average.

Local runoff is an important part of the hydrology of 

the San Bernardino area because it influences interpretations 

of surface-water inflow and outflow (fig. 15) and because 

it affects estimates of surface water retained in the area as 

ground-water recharge. Because no measurements of local 

runoff are available and because no intermediate stream gages 

are present within the San Bernardino area, estimates of local 

runoff have relied on precipitation measurements, estimated 

evapotranspiration, and estimated ground-water recharge.

26 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
 To calculate annual values of local runoff for 1945–98, 

a methodology was used similar to that described above to 

calculate longterm average values. Annual precipitation at the 

San Bernardino gage (San Bernardino County Flood Control 

District station 47723) was divided into four components: 

evapotranspiration, direct recharge, local runoff, and recharge 

from local runoff. These components, shown in figure 18, 

are assumed to remain fairly contant as a percentage of total 

precipitation from one year to another. In all but the wettest 

years, evapotranspiration was assumed to be 80 percent of precipitation; local runoff, 15 percent; recharge from local runoff, 

5 percent; and direct recharge of precipitation, 0 percent. In 

the wettest years, evapotranspiration dropped to 75 percent 

and direct recharge increased to 5 percent. Annual volumes 

for each component of precipitation were calculated using 

the areal distribution of mean annual precipitation shown in 

figure 6, scaled by annual precipitation data for station 47723. 

The implicit assumption that the areal distribution remains 

relatively constant each year seems reasonable because of the 

persistent direction of most storms from the northwest and the 

strong orographic effect of the San Gabriel and San Bernardino Mountains.

The relative percentages for each component of precipitation were based on previous investigations and a desire to create a simple tool that embodies basic hydrologic concepts for 

a semiarid, partly urbanized basin. A controlling assumption 

was that no direct recharge occurs in most years; evapotranspiration is simply too large, even in an area of highly permeable 

surficial deposits. In the exceptionally wet years, however, 

precipitation overwhelms the capacity of both vegetation and 

the soil to retain and evapotranspire water, and some percolation occurs. 

An equally important assumption is that a small quantity of local runoff occurs in even the driest of years. High 

intensity rainfall is common, even in these years, and it results 

in runoff that is routed onto streets or into adjacent borrow 

ditches, then into unlined ditches and canals, and eventually 

into concrete-lined, flood-control channels (fig. 11; pl. 1). 

This routing provides the opportunity for modest precipitation to generate local runoff that leaves the area and becomes 

part of gaged outflow from the area. Routing of local runoff 

into unlined ditches and canals also provides the opportunity 

for some ground-water recharge, even in years with minimal 

precipitation.

Additional concepts used in creating figure 18 include: 

more precipitation should prompt more evapotranspiration, 

as a quantity if not as a percentage; the change in slope of 

total annual precipitation occurring at about 23 in/yr seemed 

a reasonable threshold to begin adding direct recharge as a 

non-zero component; and recharge from local runoff should be 

a relatively small compared to local runoff. 

Figure 18. Components of precipitation on the Bunker Hill and Lytle Creek basins in the San Bernardino area, 

California, 1945–98. Precipitation measured at San Bernardino County Flood Control District station 47723. Selected 

years are identified.

Hydrology 27

Direct recharge

COMPONENTS

Evapotranspiration

Local runoff

Recharge from local runoff

1983

1969

1978

1998

1980

1993

Years

with direct

recharge: Total annual

precipitation

5

0

10

15

20

25

30

35

40

PRECIPITATION COMPONENT,

IN INCHES PER YEAR

INCREASING TOTAL ANNUAL PRECIPITATION
 Development of the four components of precipitation 

and their relative percentages, as illustrated in figure 18, was 

an iterative process. In addition to data from previous investigations and the hydrologic concepts described above, the 

ground-water model described later in this report was used 

to evaluate the estimated quantities of direct recharge and 

recharge from local runoff. Outflow simulated by the groundwater flow model was compared to gaged surface-water outflow less local runoff, less wastewater discharge. This evaluation process did not significantly alter the initial assumptions 

about precipitation components, but did help to confirm the 

reasonableness of the estimates. The final data used to calculate the values shown in figure 18 are listed in table 4.

During 1945–98, total precipitation on the Bunker Hill 

and Lytle Creek basins averaged about 109,000 acre-ft/yr, 

and ranged from a minimum of about 41,000 acre-ft to a maximum of about 236,000 acre-ft (table 4). Local runoff averaged 

about 16,000 acre-ft/yr, and annual values ranged from about 

6,000 acre-ft to about 35,000 acre-ft. Recharge from local 

runoff averaged about 5,000 acre-ft/yr, and annual values 

ranged from about 2,000 acre-ft to about 12,000 acre-ft. 

Evapotranspiration averaged about 86,000 acre-ft/yr, 

and annual values ranged from about 33,000 acre-ft to

about 177,000 acre-ft. Direct recharge averaged about 

1,000 acre-ft/yr, and annual values ranged from zero to about 

12,000 acre-ft. Because of the method of estimating annual 

values, the maximum values occurred in 1983 and minimum 

values occurred in 1947.

Despite relatively simple assumptions, the methodology 

for calculating the four components of precipitation seemed 

to be useful and capture much of the hydrologic impact of 

precipitation on the basins. Undoubtedly, the real physical 

processes are much more complex, and, depending on antecedent conditions, actual component values may not be the 

same, even in years with the same annual precipitation. For 

example, it seems likely that increasing urbanization (fig. 8) is 

having some effect on local runoff. The California Department 

of Water Resources (1971, fig. 27) estimated that local runoff 

would double between 1965 and 1995, increasing outflow 

from the basin by about 10 percent. Although not visually 

apparent from a graphical analysis of cumulative gaged outflow (fig. 15), this estimated change may help to explain the 

increase in outflow from period II (0.37) to period IV (0.42), 

an increase of about 10 percent. Subsequent investigators may 

want to revisit the effect of urbanization on local runoff and 

ground-water recharge from local runoff, and consider adding 

a temporal adjustment to the percentages used in this report.

Figure 19. Water imported for artificial recharge into the San Bernardino area, California, 1972–98.

28 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998

CALENDAR YEAR

WATER IMPORTED FOR ARTIFICIAL RECHARGE, 

IN ACRE-FEET PER YEAR
Imported Water

Beginning in 1972, water has been imported into the San 

Bernardino area to augment local supplies. This water, which 

originates as runoff into northern California streams, is collected by the State Water Project, conveyed south in the California Aqueduct, and distributed to member agencies of the 

State Water Project for use in central and southern California. 

As the local representative of the State Water Project, the San 

Bernardino Valley Municipal Water District has an entitlement 

to import as much as 102,600 acre-ft/yr (U.S. Bureau of Reclamation, 1989, table 1). In some years with abundant runoff 

in the Sierra Nevada, this entire quantity can be delivered. 

However, major facilities planned in 1963 to become 

part of the State Water Project were still not complete as of 

1998. As a result, the longterm average quantity of imported 

water that can be delivered is significantly less than the 

maximum entitlement—probably less than 50 percent of the 

102,600 acre-ft/yr (Camp Dresser and McKee, 1991, p. 2–4). 

By the end of the 7-year drought from 1986 to 1992, which 

affected water supplies throughout California, the maximum 

quantity of imported water available for the San Bernardino 

area was about 12,000 acre-ft/yr.

Water that is imported by the San Bernardino Valley 

Municipal Water District arrives at the Devil Canyon power 

plant (fig. 11; pl. 1), is kept separate from native runoff in a 

lined afterbay, and is distributed to local purveyors such as 

other water districts and nearby cities. From the afterbay, 

water can be diverted either east into the Foothill pipeline or 

west into the Lytle Creek pipeline and then can be released 

at any of the several artificial-recharge basins located mostly 

along the foot of the San Bernardino Mountains (fig. 11).

Prior to 1983, most imported water was used to recharge 

the Bunker Hill ground-water basin (table 5). After 1983, 

most of the imported water was used for agriculture in the 

Bunker Hill basin as part of the San Bernardino exchange plan 

(San Bernardino County, 1976). Under this plan, water from 

the Santa Ana River is diverted east to the Mill Creek area, 

or water from the Santa Ana River or Mill Creek is diverted 

out of the Bunker Hill basin to the Yucaipa basin (fig. 2). In 

exchange, the same quantity of water is imported and delivered to those, primarily in agriculture, who would have used 

the native runoff. 

This marked change in the quantity of imported water 

used for artificial recharge is illustrated in figure 19. The 

reduction also was prompted by rising ground-water levels 

in the former marshland. By 1984, ground water had flooded 

the basement of the San Bernardino Valley Water District 

(located about equidistant between gaging stations J and K 

on fig. 11) and had damaged equipment in the post office 

across the street. In 1986, the city of San Bernardino sued the 

San Bernardino Valley Water Conservation District alledging excessive artificial recharge caused the high ground-water 

levels and related damage to public infrasture. Since 1983, a 

small quantity of imported water has been delivered within the 

San Bernardino area for direct municipal use. Imported water 

delivered outside the San Bernardino area has been used primarily for ground-water recharge in the adjacent Rialto-Colton 

basin (fig. 11; Woolfenden and Kadhim, 1997). 

The quantities, distribution, and use of imported water 

for 1972–98 are summarized in table 5. Average annual values 

for imported water are listed for the period of water deliveries 

(1972–98) and for the primary water-budget period (1945–98). 

The total quantity of imported water averaged about 10,000 

acre-ft/yr for 1972–98 and 5,000 acre-ft/yr for 1945–98. The 

quantity of water imported for artificial recharge in the Bunker 

Hill and Lytle Creek basins averaged about 60 percent of the 

total: about 6,000 acre-ft/yr for 1972–98 and about 3,000 acreft/yr for 1945–98. 

The economic aspects of imported water are complex 

and highly variable, but essentially involve an annual fixed 

cost for the entitlement to import water from the State Water 

Project and a variable cost for the quantity of water imported. 

In 1998, the fixed cost was $14,300,000. The variable cost is 

based on a net energy requirement of 3,236 kilowatt-hours to 

bring 1 acre-ft of water from San Francisco Bay into the San 

Bernardino area via the Devil Canyon powerplant. In 1998, 

electricity purchased from the State Water Project cost $0.03 

per kilowatt-hour, or about one-third the retail cost. At this 

reduced electrical rate, the variable cost was about $100 per 

acre-foot of imported water. As illustrated by this basic example, costs for importing water often are more complicated than 

for using native water because (1) electrical costs vary depending on when, how, and from whom the electricity is obtained; 

(2) reimbursements can be obtained from either local water 

purveyors or through increased property-tax assessments; and 

(3) distribution of water may involve a paper transfer of water 

rights, not a physical conveyance.

Wastewater Discharge

Since the 1930’s, at least 4,000 acre-ft/yr of wastewater 

has been discharged into the San Bernardino area from 13 

facilities (San Bernardino Valley Municipal Water District, 

c1977). Locations of these facilities are shown on figure 20, 

and their general characteristics are listed in table 6. Most of 

the smaller facilities treat industrial waste from a local business or sewage waste from a hospital or campus, and then discharge the waste to nearby evaporation or percolation ponds.

The city of Redlands also disposes of treated sewage 

effluent to a percolation pond, but the quantity is much greater 

(table 6). Although the pond is close to the Santa Ana River, 

overflow from the pond into the river has never occurred 

(M.L. Huffstutler, Redlands Water Department, oral commun., 

1996). It is not known how much of the wastewater discharge 

to the pond evaporates and how much recharges the underlying 

ground-water system.

Hydrology 29
Figure 20. Location of major wastewater treatment facilities in the San Bernardino area, California.

30 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

The Zanja

Seven Oaks Dam

BASIN

CHINO

RIALTO - COLTON

BASIN

YUCAIPA BASIN

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Cr

River

River

Cr

Plunge

Warm

Santa

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Basin boundary-Bunker Hill and Lytle Creek Artificial-recharge basin ground-water basins shaded in darker gray

EXPLANATION

San Bernardino Mountains

Crafton Hills

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Norton Air 

Force Base

Badlands

Shandin

Hills

Perris Hill

Gabriel

Mts

San

Former marshland

15

215

10

215

San Bernardino Mountains

Gabriel

Mts

San

15

Redlands Redlands

San Bernardino San Bernardino

CREEK

LYTLE

BASIN

Highland Highland

Boundary of Santa Ana

River drainage basin

20' 15' 10'

Fault or ground-water barrier-May be concealed or approximately located

34

15'

34

10'

34

05'

117 25' 117 05'

0 6 KILOMETERS

0 6 MILES

1

13

3

12

6

RIX

4

2

9

7

11

8

10

5

1

Wastewater facility and number-Refer to table 6.

Locations approximate

Rapid infiltration and extraction (RIX) facilityLocation of City of San Bernardino wastewater

discharge beginning in 1996

RIX
Four facilities have discharged wastewater into streams 

or canals that are tributary to the Santa Ana River. Annual 

discharge from these facilities for the period 1945–98 is 

listed in table 7. The city of San Bernardino plant 1, which 

discharged directly into Warm Creek, closed in 1972 and all 

treatment was shifted to plant 2. In 1965, wastewater from the 

Loma Linda Sanitation District also was shifted to plant 2. 

As much as 25 percent of the discharge from plant 2 is used 

for landscape irrigation (1992); however, most of the treated 

wastewater is discharged directly into the Santa Ana River. 

Beginning in 1996, all wastewater from plant 2 was piped to 

a Rapid Infiltration-Extraction (RIX) facility downstream of 

the San Jacinto fault (fig. 20). Wastewater from the Southern 

California Edison, San Bernardino plant also is discharged 

into the Santa Ana River or to nearby canals that convey water 

to the Riverside area (pl. 1).

In the semiarid climate of the San Bernardino area, 

most wastewater discharged to small evaporation or percolation ponds probably evaporates or is transpired by vegetation. Initial pond design and subsequent siltation minimize 

percolation to the ground-water system. Some wastewater 

discharged to streams or canals is evapotranspired or recharges 

the ground-water system, but most probably flows out of the 

San Bernardino area. The relatively short distance from the 

largest discharge facilities (1 and 2, fig. 20) to the edge of the 

San Bernardino area limits their recharge potential. Percolation also is limited in this area by relatively high ground-water 

levels. During time periods when the water table is high, 

potential recharge is rejected; during periods when the water 

table falls below the stream stage, such as during the 1960’s, 

some ground-water recharge can occur.

Since 1945, continued urbanization of the San Bernardino 

area has resulted in an increased volume of municipal sewage. For example, wastewater discharge from the city of San 

Bernardino has increased steadily from about 7,000 acre-ft/yr 

in 1945, to more than 48,000 acre-ft/yr in 1998 (table 7). Prior 

to 1996, most of this wastewater was discharged immediately 

upstream from gaging stations that measure outflow from the 

San Bernardino area (fig. 11 and table 1).

To determine whether the increasing wastewater discharge affects the analysis of surface-water inflow and outflow 

presented in figure 15, the total quantity of wastewater discharge (table 7) was subtracted from total basin outflow

(table 1), and the data in figure 15 were replotted. Results 

indicate that the curve remains similar in shape, indicating that 

another, persistent hydrologic process controls much of the 

relation between surface-water inflow and outflow. Increasing urbanization, local runoff, and wastewater discharge likely 

affect the quantity of basin outflow, but how much surfacewater inflow is retained in the basin likely is related to the 

depth to ground water.

Ground-Water Discharge into Warm Creek

Until about 1959 and between about 1980 and 1990, 

Warm Creek flowed perennially in the reach from south of 

Perris Hill to the San Jacinto fault (figs. 2 and 9). Much of the 

discharge resulted from ground water seeping into the creek 

channel whenever the water table was sufficiently high. During the period from about 1980 to 1990, ground water was 

observed flowing up through cracks and holes in the concretelined, flood-control channel of Lytle Creek near its confluence 

with Warm Creek (fig. 11; pl. 1). Not surprisingly, this quantity of discharge was observed to be significantly less than the 

discharge in the earthen channel of Warm Creek. Curiously, no 

ground-water discharge was observed in the Santa Ana River 

(J.C. Bowers, U.S. Geological Survey, oral commun., 1992).

In an effort to determine the quantity of “rising ground 

water,” the California Department of Water Resources (1971, 

p. 150, table 22, column 1) measured discharge in Warm 

Creek and other discharges to, and withdrawals from, the 

creek. The resulting quantity of ground-water discharge 

was shown graphically to correspond to water levels in a 

nearby well (1S/4W–1M1) (California Department of Water 

Resources, 1971, fig. 7). This relation between ground-water 

level and discharge has been quantified by fitting a nonlinear 

regression equation to the discharge data and water levels in a 

nearby well (1S/4W–3Q1), referred to locally as the Heap 

well (fig. 21). The Heap well was used for the analysis 

because it has a longer period of record. As shown in 

figure 21, water-level measurements made in spring (March or 

April) were plotted against the corresponding annual discharge 

data calculated for water years 1943–59. The resulting regression equation is

WlHeap, k = 919.63 + 30.529 log (QRisingGW

WarmCrk, k) (2a)

or transposed

QRisingGW

WarmCrk, k = 10[(WlHeap, k - 916.63)/30.529] (2b)

where

WlHeap, k is average water-level altitude in the Heap well 

(1S/4W–3Q1) during year k, in ft, and

QRisingGW

WarmCrk, k is discharge of ground water into Warm Creek 

during year k, in acre-ft/yr.

Equation 2b can be used to estimate likely values of annual 

ground-water discharge into Warm Creek for a range of 

ground-water levels in the Heap well. Discharge to the creek 

decreases to zero when ground water falls below an altitude of 

about 1,008 ft. When ground water rises to an altitude of about 

1,065 ft, as it did in 1945, ground-water discharge rises to 

more than 40,000 acre-ft/yr. Estimated values of ground-water 

discharge for the period 1945–98 are listed in table 8.

Hydrology 31
Diversions

Since the 1800s, canals and pipelines have been constructed to divert water from streams in the San Bernardino 

area. Typically, diversions are located near the mountain front, 

and flow is distributed to lower altitudes for agricultural and 

municipal use (pl. 1). For example, flow from the Santa Ana 

River is diverted to the city of Redlands and to farmlands 

between the river and the San Bernardino Mountains. Much of 

the flow in streams emanating from the San Bernardino Mountains is diverted into nearby spreading ponds to control floods 

and to enhance recharge of the ground-water system (fig. 11).

The Foothill pipeline follows the edge of the San Bernardino Mountains and typically conveys water east from the 

California Aqueduct (fig. 11). Because of its dual-end, gravity 

design, however, the Foothill pipeline can convey water west 

in the opposite direction. Capacity of the pipeline to convey 

water east is about 290 ft3/s; capacity to convey water west 

is about 100 ft3/s, or about the average flow in the Santa Ana 

River. As of 1998, water from the Santa Ana River can be 

transported west to artificial-recharge basins (pls. 1 and 2), 

though it rarely is. When Seven Oaks Dam was completed in 

1999, the quantity of water available to transport to the west 

was increased, subject to legal decisions, as a result of storage 

behind the dam. 

The numerous diversions in the San Bernardino area are 

shown planemetrically on plate 1 and schematically on 

plate 2. These illustrations were prepared from detailed 

information obtained during 1990–94. Except for Seven Oaks 

Dam, which was being planned at the time of the research, the 

information on plates 1 and 2 is believed to accurately represent conditions in 1998. The two plates document the surfacewater operation of the basin, and provide detailed information 

for constructing a numerical model that routes surface-water 

through the San Bernardino area.

Ground-Water System

Ground water in the San Bernardino area occurs primarily in the valley-fill sediment. The small quantity of ground 

water that is found in, or moves through, consolidated and 

crystalline rocks surrounding and underlying the valley fill 

was assumed to be negligible for purposes of this report.

Table 8. Annual ground-water discharge into Warm Creek in the San Bernardino area, California, 1945–98.

[Annual values estimated (e) using data from the California Department of Water Resources (1971, table 22, column 1, p. 150) and calculated (c) from a 

regression equation (fig. 21); average for 1945−98]

Calendar

 year

Ground-water 

discharge 

(acre-feet)

1945 42,000e

1946 38,200e

1947 35,600e

1948 28,500e

1949 24,000e

1950 17,800e

1951 13,500e

1952 14,300e

1953 8,700e

1954 5,600e

1955 3,800e

1956 1,700e

1957 1,200e

1958 1,300e

Calendar

 year

Ground-water 

discharge 

(acre-feet)

1959 500e

1960 0e

1961 200c

1962 100c

1963 100c

1964 0c

1965 0c

1966 0c

1967 0c

1968 0c

1969 0c

1970 0c

1971 0c

1972 0c

Calendar

 year

Ground-water 

discharge 

(acre-feet)

1973 0c

1974 100c

1975 100c

1976 100c

1977 100c

1978 100c

1979 200c

1980 1,000c

1981 2,400c

1982 5,100c

1983 8,500c

1984 10,100c

1985 9,400c

1986 6,700c

Calendar

 year

Ground-water 

discharge 

(acre-feet)

1987 4,300c

1988 2,500c

1989 1,200c

1990 900c

1991 300c

1992 100c

1993 100c

1994 100c

1995 100c

1996 200c

1997 200c

1998 200c

Average 5,393

32 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Description of Valley-Fill Aquifer

The valley-fill aquifer in the San Bernardino area was 

defined initially by Dutcher and Garrett (1963) and redefined 

for purposes of numerical simulation by Hardt and Hutchinson 

(1980). The extent of the valley-fill aquifer, as defined in this 

study and shown in figure 22, includes the Bunker Hill and 

Lytle Creek basins as defined by Dutcher and Garrett (1963, 

pl. 4). Boundary conditions for the valley-fill aquifer and 

the general direction of ground-water flow also are shown in 

figure 22.

The valley-fill aquifer includes both unconsolidated 

deposits and sedimentary rocks. The unconsolidated deposits, 

which constitute the primary reservoir for storing large quantities of water, are composed of gravel, sand, silt, and clay. This 

sediment was formed mostly by alluvial fans coalescing along 

the mountain front, and by the Santa Ana River and Lytle 

Creek reworking and redepositing these materials. Near the 

mountain front, the unconsolidated deposits tend to be coarse 

grained and poorly sorted, becoming finer grained and better 

sorted downstream from the mountains. Zones of well sorted 

sand and gravel, where saturated, yield copious quantities of 

water to wells. Yields of 4 ft3/s are common from municipal 

wells ranging in diameter from 14 to 20 inches.

The unconsolidated deposits have been divided further 

by Dutcher and Garrett (1963, pl. 1) into older (Pleistocene) 

and younger (Holocene) alluvium and Holocene river-channel deposits (fig. 5). The older alluvium (Qoal) consists of 

continental, fluvial deposits ranging in thickness from a few 

tens of ft to more than 800 ft. The younger alluvium (Qyal) 

is about 100-ft thick, composed mainly of flood-plain deposits. The thin river-channel deposits (Qrc) are among the most 

permeable sediments in the San Bernardino area and cause 

large seepage losses from streams. Hydraulic conductivity 

for these deposits ranges from about 40 to 100 ft/d (Dutcher 

and Garrett, 1963, p. 51–56). These stratigraphic units are 

described more fully in figure 23, which includes a representative geologic section and stratigraphic column for the San 

Bernardino area.

The sedimentary rocks (QTc) crop out mainly in the 

southern part of the San Bernardino area between the San 

Jacinto fault and Crafton Hills and underlie unconsolidated 

deposits in the vicinity of Redlands (fig. 5). In the badlands, 

these sedimentary rocks are referred to as the San Timoteo 

Formation and are composed of partly lithified, non-marine, 

alluvial and lacustrine sediment, ranging in age from late 

Tertiary to early Quaternary (fig. 23). Well yields are moderate from the more permeable layers—generally less than 1 

ft3/s; hydraulic conductivity ranges from 7 to 29 ft/d (Dutcher 

and Garrett, 1963; Dutcher and Fenzel, 1972). Small areas of 

sedimentary rocks also are present along the edge of the San 

Bernardino Mountains, but in these areas the deposits are not 

considered to be part of the aquifer system because they probably are mostly unsaturated and are underlain by less permeable consolidated rock.

The greatest thickness of water-bearing, unconsolidated 

deposits and sedimentary rocks in the valley-fill aquifer is 

more than 1,200 ft and occurs adjacent to the northeast side of 

the San Jacinto fault between the city of San Bernardino and 

the Santa Ana River (Fife and others, 1976). This area coincides with the former marshland (fig. 2). Upslope from the former marshland, the valley-fill deposits become progressively 

thinner northwest toward the San Gabriel Mountains, north 

toward the San Bernardino Mountains (fig. 23), and northeast 

toward Crafton Hills (Hardt and Hutchinson, 1980).

The valley-fill aquifer has been divided by Dutcher and 

Garrett (1963, pl. 7) into six hydrogeologic units: an upper 

confining member (UCM), an upper water-bearing zone 

(UWB), a middle confining member (MCM), a middle waterbearing zone (MWB), a lower confining member (LCM), and 

a lower water-bearing zone (LWB). These hydrogeologic units 

are shown in figure 24, using the same section (A–A’) as in 

figure 23. The hydrogeologic interpretation in this report is 

similar to that suggested by Dutcher and Garrett (1963), but 

relies on new data from lithologic logs (fig. 23), geophysical 

logs (fig. 24), and multiple-depth piezometers. This additional 

data gives increased accuracy and reliability to the hydrogeologic interpretation of the valley-fill aquifer compared to the 

work of Dutcher and Garrett (1963), who had to rely almost 

exclusively on lithologic data from driller’s logs and waterlevel data from production wells.

Figure 21. Relation between discharge in Warm Creek and 

ground-water level in the San Bernardino area, California.

Measured discharge data for water years 1943−59 from 

California Department of Water Resources (1971, table 22, 

column 1, p. 150). Measured water levels for the Heap well 

(1S/4W-3Q1) from the USGS.

Hydrology 33

1,070

1,060

1,050

1,040

1,030

1,020

1,010

1,0000 10,000 20,000 30,000 40,000 50,000

ALTITUDE OF WATER LEVEL IN THE HEAP WELL, 

IN FEET ABOVE MEAN SEA LEVEL

DISCHARGE OF GROUND WATER INTO WARM CREEK, 

IN ACRE-FEET PER YEAR

Land surface

y = 919.84 + 30.386 log (x)

r = 0.974 2
Figure 22. Areal extent of the valley-fill aquifer, boundary conditions, and direction of ground-water flow in the San Bernardino 

area, California.

34 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Boundary of the valley-fill aquifer-Bunker Hill and

Lytle Creek ground-water basins shaded in darker gray. 

Solid line indicates no underflow. Dashed line indicates

area of minor underflow; arrows indicate area with more

than 1,000 acre-feet per year of underflow and point in

the direction of ground-water flow to or from adjacent

permeable materials

Former marshland

Fault L

Fault K

Fault

Fault

Fault Oak Glen

Crafton

Redlands

Barrier

J

Bryn Mawr

Barrier Mentone

Barrier

Fault

Loma Linda

Fault

San

San Andreas

Jacinto

Fault

Banning(?)

Fault

Loma Linda

Santa Ana River

RIALTO - COLTON

BASIN

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Cr

River

Cr

Plunge

Warm

Santa

Ana

Cr Cr

City

Mill Cr

Lytle Cr

Gabriel

Mts

San

Zanja The

Seven Oaks Dam

15

215

10

215

15

San Bernardino Mountains

EXPLANATION

Crafton Hills

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Shandin

Hills Perris Hill

Gabriel

Mts

San

San Bernardino Mountains

Redlands Redlands

San Bernardino San Bernardino

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Fault

Fault or ground-water barrier-May be concealed or

approximately located

Generalized direction of groundwater flow-Within the valley-fill

aquifer

Artificial-recharge basin

Boundary of Santa Ana

River drainage basin

Highland Highland

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

0 6 KILOMETERS

0 6 MILES
The upper confining member is a near-surface deposit 

with low hydraulic conductivity. The member is thin and 

discontinuous, and may be absent, thinner, or much more 

permeable near Warm Creek (Dutcher and Garrett, 1963). In 

the area between Warm Creek and the Santa Ana River, the 

upper confining member acts to restrict vertical flow, causing 

semi-confined conditions in the upper 50 to 100 ft of saturated 

materials. As shown in figure 24, the upper confining member 

is effectively at land surface between the San Jacinto fault and 

the Banning (?) fault.

In places, the upper confining member appears to have 

been eroded by streamflow and replaced with coarse sand 

and gravel. Boreholes drilled to a depth of about 50 ft below 

land surface in the vicinity of the Santa Ana River and the 

San Jacinto fault indicate a predominance of coarse sand and 

gravel, not fine-grained silt and clay. In these locations, the 

coarse material is essentially part of the upper water-bearing 

unit, vertical ground-water flow is less restricted, and unconfined conditions are likely to be present throughout the upper 

100 to 200 ft of valley-fill sediment.

North of the Banning (?) fault, the slope of the land 

surface increases and a more permeable deposit, considered 

to be part of the upper water-bearing zone, overlies the upper 

confining member. This overlying deposit appears to be the 

result of aggrading alluvial fans being deposited over the finergrained upper confining member (fig. 24).

The upper and middle water-bearing zones provide most 

of the water to municipal and agricultural wells. In the central 

part of the San Bernardino area, these zones are separated 

by as much as 300 ft of interbedded silt, clay, and sand (the 

middle confining member). This middle confining member 

produces confined conditions over the central part of the basin, 

but thins and becomes less effective toward the margins of the 

basin (Dutcher and Garrett, 1963). In the area where the middle confining layer is effective, it is referred to locally as the 

confined area (Mendenhall, 1905; Dutcher and Garrett, 1963; 

fig. 1). The areal extent of the confined area is approximately 

the same as the areal extent of flowing wells mapped by 

Mendenhall (1905) and also about the same as the areal extent 

of the upper confining member (fig. 24). The similarity among 

these three areas has caused several previous publications to 

cite them incorrectly or to use them interchangeably. Analysis 

of most hydrologic conditions, particularly those described in 

this report, requires that each area be considered separately.

Although not as permeable as the adjacent water-bearing 

zones, the middle confining member does yield significant 

quantities of water to wells. As a result, most production 

wells have casing that is open opposite one or both of the 

water-bearing zones, and open opposite the middle confining 

member. As suggested by well yields and geophysical logs 

(fig. 24), relatively continuous zones of silt and sand are present in the middle confining member. Perhaps because of its 

name, some previous studies have tended to characterize the 

middle confining member as a impermeable mass of clay and 

silt, which it is not.

The lower confining member and lower water-bearing 

zone are not penetrated by most production wells and play 

a lesser role in the valley-fill aquifer. When penetrated by 

a production well, the lower confining member is used to 

increase the yield of the well. Measurements of vertical flow 

within three such production wells distributed along section 

A–A', however, showed that very little water was contributed 

to the any of the three wells from the lower confining member 

(Izbicki and others, 1998, fig. 3).

The lower water-bearing zone rarely is tapped by production wells, mainly because it is much slower to drill through 

than the overlying deposits. The lower water-bearing zone may 

be composed of poorly consolidated or partly cemented older 

alluvium (Qoal), or may be composed solely of even older 

sedimentary rocks (QTc). In either case, the top of the lower 

water-bearing zone forms the effective bottom of the groundwater flow system within the valley-fill aquifer, at least in the 

vicinity of section A–A'.

Recharge and Natural Discharge

Sources of recharge in the San Bernardino area are seepage from gaged streams, seepage from ungaged runoff, direct 

infiltration of precipitation, recharge from local runoff that 

originates as precipitation on the Bunker Hill and Lytle Creek 

basins, artificial recharge of imported water, return flow from 

pumpage, and underflow from adjacent ground-water areas. 

Ground water is discharged naturally by subsurface underflow 

out of the area, by ground water flowing into the lower reaches 

of Warm Creek, and by evapotranspiration.

Recharge from Gaged Streamflow

Seepage from gaged streams is the major source of 

recharge in the San Bernardino area. Recharge occurs both 

in the stream channels and in nearby artificial-recharge 

basins (fig. 11). The exceptionally coarse and highly permeable materials in the stream channels increase the percentage 

of streamflow that recharges the valley-fill aquifer. Equally 

important for enhancing recharge is the standard operation of 

routing streamflow through each artificial-recharge basin in a 

serpentine pattern designed to maximize residence time in the 

basin (K.J. Mashburn, San Bernardino County Flood Control, 

oral commun., 1990). Commonly, large earthen dikes are used 

to form the sides of a basin and effectively contain streamflow 

within the basin. Smaller earthen dikes, locally referred to as 

“sugar” dikes, are bulldozed into a series of rows that impede 

low-to-average streamflow and create the serpentine pattern of 

flow. During higher flows when stream stage reaches a certain 

altitude, the sugar dikes are designed to break apart, “dissolving” like sugar into the higher flow. Flood water then is 

conducted safely straight through the artificial-recharge basin 

and back into the main stream channel.

Hydrology 35
Figure 23. Representative geologic section A−A’ and stratigraphic units in the San Bernardino area, California.

36 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

}ws

wc

} ws

wc

}

wc }

ws

g

San Jacinto Fault

Banning Fault ?

San Andreas Fault

 Fault L

 Fault K

Perris

Hill

uplift

? ?

?

? ? ? ?

?

?

?

?

?

Loma Linda Fault

?

10B2-4

22D2,4-7

2D6-8

34G4

27R

27B1

23R2-4

14P1

D6 D6

D7

D8

R4

R3

D7 R2

D2

D5

D4 B2

B3

B4

?

?

?

?

?

?

?

?

0 16,000 FEET

4,000 METERS

Vertical scale greatly exaggerated

0

A

FEET

Sea level

2,000

600

400

200

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

A'

Warm Creek

Warm Creek

Santa Ana River

Warm Creek

Baseline Road

Highland Road

40th Street

I-15/I-10 Interchange

Mill Street

5th Street

T1S

T1S

T1N

T1N

R4W

R4W

Qyal Qyal

Qoal

Qoal

Qyal

Qyal

Qoal

Qoal

Qoal

Qrc Qrc

Qrc

QTc ?

QTc ?

bc

bc

bc

bc

bc bc

bc

bc

bc

bc

bc

bc

Historical extent of 

flowing wells

 Artificialrecharge basin

Qoal?QTc?

A

Perris

Hill

San Bernardino

Shandin

Hills

A'

Loma Linda Fault

Banning (?) Fault

San Jacinto

Fault

Andreas Fault

San

Warm

Creek

Santa Ana

River

Section A-A' San Bernardino area.

27R

27B1

22D2,4-7

34G4

23R2-4

14P1

2D6-8

10B2-4
Figure 23.—Continued.

Hydrology 37

Perforated casing

Lithologic log

White sand

White clay

ws

wc

?

Fault-Dashed where inferred; queried where

uncertain. Arrows indicate relative movement

Well and abbreviated state well numberMultiple numbers (D6-8) represent piezometers 

at selected depths

D6

D7

D8

2D6-8

Contact between stratigraphic unitsDashed where approximately located, queried

where uncertain 

Hard rock or hard drilling

Lithologic log composition-Queried where

uncertain

33 66

0 100

50

PERCENT

Gravel

Sand

Clay or silt

EXPLANATION FOR FIGURE 23

River-channel deposits

Stratigraphic units and their water-bearing characteristics

Well design and lithologic units 

Unconsolidated coarse gravel, sand, and silt in major river channels, generally becoming finer grained at greater

distance from the San Bernardino and San Gabriel Mountains. Highly permeable, but largely unsaturated except

near the San Jacinto Fault. Large quantities of water seep into these deposits from streams during runoff.

Younger alluvium

Unconsolidated coarse gravel, sand, and clay, forming of a fine-grained and coarse-grained member, which in

places are indistinguishable. Largely unsaturated near the mountains. Where present, the fine-grained member,

which is 60 to 90 feet thick and composed mostly of silt and clay, overlies and confines the coarse-grained 

member. The coarse-grained member is composed mostly of gravel and sand, is highly permeable, and yields 

water copiously to wells.

Older alluvium

Unconsolidated coarse gravel, sand, silt, and clay of continential, largely fluvial origin. In places, deeply

weathered with red and yellow soil zones; often contains easily broken pebbles of dioritic and granitic gneiss;

marker beds include a white clay and white sand at about 800 feet below land surface. Locally unconformably

overlies crystalline bedrock; fractured by numerous faults and in places slightly folded. Contains thick, finegrained silt and clay beds which confine underlying permeable members; some lower members are partly

cemented. More permeable members yield water copiously to wells.

Upper members are poorly consolidated to compacted gravel, sand, silt, and clay, locally containing a 

mammalian fauna and broken by numerous faults. Lower members are predominately brown to blue-green 

calcareous, indurated clays with locally discontinuous lenses of sand. Tertiary rocks, also non-marine, include 

compacted, cemented calcareous units, in places laminated with beds of conglomerate. Upper members 

yield water in moderate quantities to wells that penetrate permeable members; lower members are essentially 

non-water-bearing.

Quaternary and Tertiary sedimentary rocks

Basement complex 

Consolidated metamorphic and igneous rocks. Essentially non-water-bearing, though small quantities of water, 

including geothermal fluids, flow in fractures.

RECENT PLEISTOCENE

QUATERNARY TERTIARY PRE-TERTIARY

PLIOCENE

LOCAL UNCONFORMITY

LOCAL UNCONFORMITY

LOCAL UNCONFORMITY

UNCONFORMITY

QTc

Qyal

Qoal

Qrc

bc
Figure 24. Section A–A’ showing major hydrogeologic units, geophysical logs, and direction of ground-water flow in the 

San Bernardino area, California.

38 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

}ws

g wc

} ws

wc

}

}wc

ws

g

g

g

San Jacinto Fault

Banning Fault ?

San Andreas Fault

 Fault L

 Fault K

Perris

Hill

uplift

? ?

?

? ? ? ?

?

?

?

?

?

Loma Linda Fault

?

?

?

?

?

?

? ?

D6

D2

D6

D7

D8

R4

R3

R2

D7

D5

D4 B2

B3

B4

10B2-4

22D2,4-7

34G4

27R

27B1

23R2-4

14P1

LWB

LWB

LWB

LCM

LCM

LCM

MWB

MWB

MWB

MCM

MCM

UWB

UWB

UWB

UCM

MCM

Historical extent of 

flowing wells

 Artificialrecharge basin

0 16,000 FEET

4,000 METERS

Vertical scale greatly exaggerated

0

A

FEET

Sea level

2,000

600

400

200

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

A'

Warm Creek

Warm Creek

Santa Ana River

Warm Creek

Highland Road

40th Street

I-15/I-10 Interchange

Mill Street

5th Street

Outside

study area

QTc ?

QTc ?

bc

bc

bc

bc

bc bc

bc

bc

bc

bc

bc

bc

A

Perris

Hill

San Bernardino

Shandin

Hills

A'

Loma Linda Fault

Banning (?) Fault

San Jacinto

Fault

Andreas Fault

San

Warm

Creek

Santa Ana

River

Section A-A' San Bernardino area.

27R

27B1

22D2,4-7

34G4

23R2-4

14P1

2D6-8

10B2-4

T1S

T1S

T1N

T1N

R4W

R4W

2D6-8

Baseline Road
As a result of the highly permeable river-channel deposits 

(Qrc, fig. 5) and the artificial-recharge operations (fig. 11), 

nearly all flow in the smaller gaged streams (Devil Canyon, 

Waterman, East Twin, Plunge, and San Timoteo Creeks) is 

recharged to the aquifer close to the mountain front (fig. 9; 

Mendenhall, 1905, p. 48). During floods, the major streams 

(Santa Ana River, Mill Creek, and Lytle Creek) transmit large 

volumes of water in a short time, and some flow leaves the San 

Bernardino area, passing the outflow gages (fig. 11). 

 Recharge from all gaged streamflow can be estimated by 

subtracting total gaged surface-water outflow from total gaged 

surface-water inflow (table 1), then adding rising ground water 

(table 8), estimated local runoff (table 4), and wastewater discharge (table 7). This is not an ideal calculation because some 

of the rising ground water and wastewater discharge originated 

as seepage from gaged streams, but it does give a reasonably good estimate, especially for longer periods. Equally 

important, the calculation recognizes that gaged outflow is 

composed of at least four components: through-flowing gaged 

inflow, rising ground water, local runoff, and wastewater 

discharge. This means that if any of the components change 

over time, such as is likely for both local runoff and wastewater discharge, the perceived change in gaged surface-water 

outflow or in net gaged inflow minus outflow (table 1) can 

be misleading. An apparent increase in surface-water outflow 

may not result from a decrease in seepage of gaged surfacewater inflow, or a decrease in ground-water recharge.

For 1945–98, estimated recharge from gaged inflow, as 

calculated above, averages about 116,000 acre-ft/yr (146,452 

− 67,931 + 5,393 + 16,377 + 15,873). During this period estimated recharge from gaged inflow ranges from a minimum of 

about 27,000 acre-ft in 1961 to about 423,000 acre-ft in 1969.

Recharge from Ungaged Runoff

Recharge from ungaged runoff is of lesser importance 

because the total quantity of ungaged runoff is estimated to 

be only about 10 percent of gaged runoff (tables 1 and 3). 

However, virtually all ungaged runoff that flows into the San 

Bernardino area is assumed to recharge the valley-fill aquifer. Both the hard, impermeable surface of the surrounding 

bedrock and the short distance between the bedrock and the 

valley-fill aquifer minimize potential losses of ungaged runoff 

to evapotranspiration or to percolation into the bedrock. 

For 1945–98, recharge from estimated ungaged runoff 

averaged about 16,000 acre-ft/yr (16,647 times 0.946; table 3). 

Because annual runoff from each ungaged area is assumed to 

vary linearly with gaged flow in the Santa Ana River (table 2), 

ungaged recharge also varies linearly with gaged flow in the 

Santa Ana River. 

Figure 24.—Continued.

Hydrology 39

Perforated casing

Geophysical log-Single point electrical 

resisitivity, increasing to the right; g, indicates

a high reading from the natural gamma log

Increasing resistivity

White sand

White clay

ws

wc

?

Fault-Dashed where inferred; queried where

uncertain. Arrows indicate relative movement

Well and abbreviated state well numberMultiple numbers (D6-8) represent piezometers 

at selected depths

D6

D7

D8

2D6-8

Potentiometric surface-Spring 1992

Water table

Composite hydraulic head for hydrogeologic

units beneath UWB

Underflow to adjacent permeable deposits

Ground-water movementArrow indicates general direction of groundwater flow

Hydrogeologic units-Determined by lithology,

geophysical logs, and hydraulic-head measurements. Naming convention follows Dutcher and

Garrett (1963)

Upper confining member

Hydrogeologic unit

Upper water bearing

Middle confining member

Middle water bearing

Lower confining member

LWB Lower water bearing

LCM

MWB

UWB

UCM

MCM

QTc Sedimentary rocks

Contact between hydrogeologic units-Dashed

where approximately located, queried where

uncertain

EXPLANATION FOR FIGURE 24

Unconsolidated deposits-Outside study area

Bedrock basement complex of igneous and

metamorphic rocks-Composed of virtually

impermeable rocks

bc
A significant quantity of ungaged recharge occurs as a 

result of ungaged runoff from the San Gabriel and San Bernardino Mountains, from Crafton Hills, and from the badlands 

(fig. 17; table 3). A much lesser quantity of recharge occurs 

as a result of ungaged runoff from bedrock outcrops within 

the ground-water basins, such as from Shandin Hills. Some 

ungaged runoff, such as from Crafton Hills and the badlands, 

may actually enter the valley-fill aquifer as underflow from 

adjacent ground-water areas. Although some previous investigators have lumped recharge from ungaged runoff with 

underflow (California Department of Water Resources, 1971; 

Dutcher and Fenzel, 1972; Hardt and Hutchinson, 1980), the 

two components are considered separately in this report.

Recharge from Direct Precipitation

Recharge from precipitation falling directly on the 

Bunker Hill and Lytle Creek basins probably is minimal in 

this semiarid region. In years of average and below-average 

precipitation, little or no recharge of this type occurs because 

of high potential evapotranspiration (Young and Blaney, 1942; 

Hardt and Hutchinson, 1980, p. 34). Even the small amount 

of precipitation that may infiltrate to the unsaturated zone is 

evaporated or transpired by vegetation. In exceptionally wet 

years, such as 1969 and 1983 (fig. 14), some direct recharge 

from precipitation probably does occur, although the quantity 

is unknown. 

In other semiarid basins, researchers have estimated that 

infiltration of direct precipitation ranges from zero to about 

0.05 ft/yr (Eychaner, 1983, p. 10; Danskin, 1988, 1998; Hollett 

and others, 1991, p. B59; Hanson and others, 1994, p. 41). 

For the San Bernardino area, a value of 0.05 ft/yr would be 

equivalent to about 4,000 acre-ft/yr. Nearly twice that value

(8,400 acre-ft/yr) was estimated by the California Department 

of Water Resources (1986, tables 17,18). These values, particularly that by the California Department of Water Resources, 

likely include recharge from local runoff that was generated 

by direct precipitation.

As part of the process of determining local runoff for 

the San Bernardino area (refer to this report, pages 26–28), 

direct recharge from precipitation was estimated as a separate component of precipitation (table 4). During 1945–98, 

direct recharge is assumed to occur in only 6 years (1969, 

1978, 1980, 1983, 1993, 1998). For 1945–98, this infrequent 

recharge equates to an average rate of about 1,000 acre-ft/yr. 

On the one hand, this amount is nearly inconsequential for 

the 54–year period; on the other hand, it accounts for about 

30,000 acre-ft of recharge during 1978–83. If purchased from 

the State Water Project in 1998, this amount of water would 

have cost more than $3 million.

Recharge from Local Runoff

Recharge also occurs from local runoff generated from 

precipitation falling on the Bunker Hill and Lytle Creek 

basins. Precipitation, particularly that falling on impermeable 

urban surfaces, runs off, forming small creeks, pools, and 

ponds. Several small catchment basins have been constructed 

to collect this type of runoff from streets, railroad corridors, 

and university lands (San Bernardino County Flood Control 

District, 1987). This accumulation of precipitation into localized areas offers a greater potential for recharge than from 

direct precipitation. It seems likely that much of the recharge 

from direct precipitation, estimated by the California Department of Water Resources (1986, tables 17,18) to average 

8,400 acre-ft/yr, actually is recharge from local runoff resulting from direct precipitation. Similarly, the significant 

recharge from direct precipitation during above-average 

runoff years, estimated by the California Department of Water 

Resources (1986, tables 17,18) to exceed 42,000 acre-ft/yr in 

1980, probably is mostly recharge from local runoff. 

These estimates of recharge were based on all precipitation falling on the land surface within the Bunker Hill 

and Lytle Creek basins (fig. 1) and on the ratio of pervious and impervious surfaces (California Department of 

Water Resources, 1971, p. 291). As urbanization of the San 

Bernardino area continues, the quantity of local runoff is 

estimated to double as a result of an increase in impervious 

surfaces, but the quantity of recharge from local runoff is 

expected to remain relatively constant (California Department 

of Water Resources, 1971, fig. 27; California Department of 

Water Resources, 1986, tables 17,18).

As described on pages 26–28, of this report, recharge 

from local runoff was estimated as a one of the components 

of precipitation (fig. 18 and table 4). This methodology of 

separating different physical processes makes comparisons 

to previous estimates more problematic, but it facilitiates 

simulating the processes as part of a surface-water and (or) 

ground-water model.

For 1945–98, recharge from local runoff averaged 

about 5,000 acre-ft/yr. Annual values ranged from a minimum of about 2,000 acre-ft in 1947 to a maximum of about 

12,000 acre-ft in 1983. Based on these estimates, total 

recharge from precipitation during 1945–98 averaged about 

6,000 acre-ft/yr (1,000 acre-ft/yr of direct recharge from 

precipitation plus 5,000 acre-ft/yr of recharge from local 

runoff). This combined value compares well with the estimate 

(8,400 acre-ft/yr) by the California Department of Water 

Resources (1986, tables 17,18) for a slightly larger area that 

includes the Yucaipa basin (fig. 2). The combined value also 

compares well with the estimate (4,000 acre-ft/yr) based on 

research in other semiarid basins, which uses an equivalent 

rate of 0.05 ft/yr (refer to �"Recharge from Direct Precipitation"

earlier on this page

40 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Artifical Recharge from Imported Water

Artificial recharge of imported water in the San Bernardino area began in 1972 and has occurred sporadically 

since then (fig. 19; table 5). Because of the extremely permeable sand and gravel deposits beneath the artificial-recharge 

basins, the maximum instantaneous recharge rates are high, 

generally 1 to 2 ft3/s per acre of water surface, or about 2 

to 4 ft/d. As a result, nearly all of the imported water probably percolates to the valley-fill aquifer. The percentage of 

percolation was estimated from previous recharge studies by 

Moreland (1972), Schaefer and Warner (1975), and Warner 

and Moreland (1972) and from personal observations by G.L. 

Fletcher (San Bernardino Valley Municipal Water District, 

oral commun., 1994). Based on this information, a recharge 

rate of 90 percent was assumed for all artificial recharge of 

imported water—relatively high compared to recharge rates 

for native runoff. This higher rate results from having a more 

controllable supply with lower turbidity. Based on the assumed 

recharge efficiency of 90 percent, the total quantity of artificial 

recharge from imported water in the Bunker Hill and Lytle 

Creek basins averaged about 6,000 acre-ft/yr for 1972–98 and 

about 3,000 acre-ft/yr for 1945–98. 

In 1973, total recharge was much greater, exceeding 

30,000 acre-ft/yr. An even greater quantity of imported water 

could be recharged along the base of San Bernardino Mountains because of the sizeable acreage of the several artificialrecharge basins and the exceptionally permeable materials. For 

example, the maximum recharge rate for the two large artificial-recharge basins on the Santa Ana River (fig. 11) exceeds 

1,200 ft3/s (California Department of Water Resources, 1971, 

table 46). 

Whether these high recharge rates could be maintained 

for an extended period, particularly along the Santa Ana River, 

is not known. Nearby gravel pits likely would become flooded 

and might prompt a change in recharge operations. Also, it is 

not known whether large volumes of water recharged in the 

artificial-recharge basins would simply resurface as flow in 

the nearby Santa Ana River. Despite these caveats, the San 

Bernardino area is unusual compared to other semiarid basins: 

a large quantity of water can be imported from outside the area 

(table 5) and can be recharged in highly permeable artificialrecharge basins scattered across the valley-fill aquifer (fig. 22). 

This capability makes imported water a much more valuable 

source of recharge than its meager historical average of 

3,000 acre-ft/yr might imply.

Return Flow from Pumpage

Return flow from pumpage is the quantity of total pumpage that is returned to the ground-water system. Water is 

returned as a result of percolation from agricultural irrigation 

and from some domestic and municipal uses. Although ground 

water is extracted from many different zones within the valleyfill aquifer depending on the construction of individual wells, 

return flow occurs only to the top of the aquifer via percolation 

from the land surface. The downward movement of return flow 

is restricted by the presence of fine-grained deposits, such as 

the upper confining member (UCM, fig. 24). These conditions 

near a production well can create a hydrologic paradox where 

water is pumped from lower zones of the aquifer at the same 

time that net recharge is occurring to the uppermost zone. 

Figure 25. Annual ground-water pumpage for the San 

Bernardino area, California, 1945–98.

Hydrology 41

200,000

220,000

180,000

160,000

140,000

120,000

100,000

80,000

60,000

40,000

20,000

0

PUMPAGE, IN ACRE-FEET PER YEAR

YEAR

1940195019601970198019902000

Gross pumpage-Measured and estimated discharge 

from wells using verified data from the local watermaster 

(Western-San Bernardino Watermaster, written commun., 2000)

Return flow-Estimated quantity of pumpage returning

as recharge to the upper layer of the valley-fill aquifer.

Calculation of return flow made for each well

Net pumpage-Estimated discharge from upper and

lower layers of the valley-fill aquifer. Calculations based

on perforated interval of each well. Gross pumpage for

the upper layer is reduced by return flow. Additional

description of calculations and layering of the aquifer

can be found on page__and in figure 24

Upper layerHydrogeologic

units UCM and

UWB

Lower layerHydrogeologic

units MCM, MWB,

LCM, and LWB

EXPLANATION

Net pumpage lower layer

Net pumpage upper layer

Return flow

Gross pumpage
Return flow was estimated by Hardt and Hutchinson 

(1980, p. 35) to be 30 percent of total pumpage except for 

wells that export ground water directly out of the San Bernardino area, such as wells along Gage Canal near the confluence of the Santa Ana River and San Timoteo Creek (pl. 1). 

Wells used for export were assumed to have zero return flow. 

Annual values of return flow for 1945–98 were calculated for 

each well in the valley-fill aquifer using measured or estimated 

pumpage and an estimated percentage of return flow based on 

the work of Hardt and Hutchinson (1980) and on advice from 

the local watermaster (R.L. Reiter, San Bernardino Valley 

Municipal Water District, written commun., 2000).

Total values of gross pumpage, return flow, and net 

pumpage for each year for the San Bernardino area are shown 

in figure 25. For 1945–98, return flow averaged about 28,000 

acre-ft/yr. Annual values ranged from about 20,000 acre-ft/yr 

to about 37,000 acre-ft/yr. Estimation of net pumpage, including net pumpage from upper and lower layers of the valley-fill 

aquifer, is described in greater detail in the following section 

entitled “Pumpage.”

Underflow

Underflow into the San Bernardino area occurs across 

the Crafton fault and through the poorly transmissive materials comprising the badlands (fig. 22). The short section of 

permeable deposits between the Crafton Hills and the San 

Bernardino Mountains is assumed to be a ground-water divide 

and to transmit essentially no underflow to or from the adjacent Yucaipa basin. Any underflow into the area from the San 

Bernardino or San Gabriel Mountains, such as that estimated 

by the California Department of Water Resources (1971), is 

assumed to be accounted for in recharge from either gaged or 

ungaged runoff. Underflow from the surrounding and underlying consolidated rock (basement complex, fig. 23) is assumed 

to be negligible. 

Underflow across the Crafton fault and through the 

badlands as defined by Dutcher and Fenzel (1972, p. 29) 

averaged approximately 6,000 acre-ft/yr for 1945–65. As a 

result of increased pumpage east of the San Bernardino area in 

the Yucaipa basin (fig. 2), underflow across the Crafton fault 

decreased progressively from 8,150 acre-ft/yr in 1927 to 5,350 

acre-ft/yr in 1967. More than half this underflow was assumed 

to occur in the vicinity of San Timoteo Creek. Underflow from 

the badlands was less than 300 acre-ft/yr. No underflow was 

estimated to occur north of Crafton Hills.

To develop annual values of underflow for use in the 

present study, prior estimates of underflow in the vicinity 

of the Crafton fault were re-evaluated and extended in time. 

Included in this re-evaluation were estimates done by the 

San Bernardino Valley Municipal Water District (1970, vol. 

IV, task 10–SY–6), by the California Department of Water 

Resources (1971), and by Dutcher and Fenzel (1972). As an 

aid in calculating underflow in a geologically complex area, 

Dutcher and Fenzel (1972, fig. 2) defined areas of underflow 

that represent eroded canyons and faulted subbasins between 

the Bunker Hill and Yucaipa basins. During the re-evaluation, 

these areas were used substantially as originally defined, but 

the actual location of underflow was moved to coincide with 

the boundary of the valley-fill aquifer as defined in this present 

study (fig. 26). 

As described by Dutcher and Fenzel (1972, fig. 7), underflow for three areas (Reservoir Canyon, Redlands Heights, and 

the badlands) did not appear to change from 1927 to 1967. 

Average underflow was 450 acre-ft/yr for the Reservoir Canyon area, 300 acre-ft/yr for the Redlands Heights area, and 280 

acre-ft/yr for the badlands. The assumption of constant underflow was based on Dutcher and Fenzel (1972) who observed 

virtually no change in ground-water levels in a few wells. The 

re-evaluation assumed that no further change in ground-water 

levels occurred after 1967; if it did, then some modification to 

the assumption of constant underflow is warranted. The quantity of underflow from the three areas is minimal, however, 

and any increase or decrease is unlikely to significantly affect 

ground-water flow in the Bunker Hill basin. 

Underflow in two areas, San Timoteo Canyon and Sand 

Canyon, was assumed by Dutcher and Fenzel (1972) to 

decrease from 1927 to 1967. For San Timoteo Canyon, the 

decrease was nearly 50 percent; for Sand Canyon, the decrease 

was about 25 percent. For both areas, the decreased underflow 

was attributed to a steady decline in ground-water levels in the 

Yucaipa basin caused by pumpage. To account for continually 

changing underflow, prior estimates for San Timoteo Canyon 

and Sand Canyon (Dutcher and Fenzel, 1972; San Bernardino 

Valley Municipal Water District (1970, vol. IV, task 10–SY–6) 

were replotted and regression equations were fit to the values. 

These prior estimates and newly fitted equations are shown in 

figure 27. The equations are described below. Annual values of 

underflow calculated using these equations are listed in table 

9.

In the vicinity of San Timoteo Creek, underflow can be 

estimated as 

QUnderflow

SanTimoteo, k = e [-29.309 ln (k) + 230.4] (3)

where

QUnderflow

SanTimoteo, k is underflow in acre-ft/yr in the vicinity of San 

Timoteo Canyon for calendar year k.

Underflow in the vicinity of San Timoteo Creek calculated 

from equation 3 averaged about 3,000 acre-ft/yr for 1945–98, 

and decreased from a maximum of almost 5,000 acre-ft/yr in 

1945 to about 2,000 acre-ft/yr in 1998.

In the vicinity of Sand Canyon, underflow can be estimated as

42 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 26. Average underflow from permeable sediment near the Crafton fault into the San Bernardino area, 

California, 1945–98.

Hydrology 43

Artificial-recharge basin

River

Cr

Plunge

Warm

Santa

Ana

City Cr

Cr

Mill

Cr

San Timoteo

Cr

Seven Oaks Dam

Sand Canyon

Badlands

Reservoir Canyon

San Timoteo Canyon

Redland Heights

Underflow-Estimated average underflow into the San

Bernardino area for 1945–98 shown in parentheses.

Bracketed values show decline in annual underflow from

1945 to 1998; refer table 9. Values in acre-feet per year

Sand Canyon (966)

[1,165–768]

Badlands

(280) YUCAIPA BASIN

Redlands

Heights (300)

San Timoteo

Canyon (3,184)

[4,605 – 2,095]

Reservoir

Canyon (450)

San Bernardino Mountains

Crafton Hills

San Bernardino San Bernardino

0 4 KILOMETERS

0 4 MILES

EXPLANATION

Former marshland

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

Perris Hill

Badlands

BASIN

BUNKER

HILL

Boundary of the valley-fill aquifer-Bunker Hill and

Lytle Creek ground-water basins shaded in darker gray. 

Solid line indicates no underflow. Dashed line indicates

area of minor underflow; arrows indicate area with more

than 1,000 acre-feet per year of underflow and point in

the direction of ground-water flow to or from adjacent

permeable materials

Fault or ground-water barrier-May be concealed or

approximately located.

Crafton

Crafton

Fault

Fault
QUnderflow

SandCanyon, k = –7.5k + 15,756 (4)

where

QUnderflow

SandCanyon, k is underflow in acre-ft/yr in the vicinity of 

Sand Canyon for calendar year k.

Underflow in the vicinity of Sand Canyon calculated from 

equation 4 averaged about 1,000 acre-ft/yr for 1945–98. Total 

decrease from 1945 to 1998 was about 400 acre-ft. Both 

approximations of underflow defined by equations 3–4 will 

remain valid for future years only if ground-water levels in the 

Yucaipa basin continue to decline.

Total underflow into the San Bernardino area for 1945–

98 averaged about 5,000 acre-ft/yr (table 9). Annual values 

declined from a maximum of about 7,000 acre-ft in 1945 to 

about 4,000 acre-ft in 1998.

Underflow out of the San Bernardino area occurs across 

the San Jacinto fault and Barrier E in two locations—near the 

Santa Ana River and near Barrier J where Lytle Creek emerges 

from the San Gabriel Mountains (figs. 5 and 22) (Lu and Danskin, 2001). 

Underflow near the Santa Ana River occurs only in the 

younger alluvium, which is about 100 ft thick (fig. 23). The 

river has eroded and redeposited these materials, removing 

most of the restriction to ground-water flow caused by movement of the San Jacinto fault (Dutcher and Garrett, 1963, p. 

101). In the older, deeper deposits, fault gouge and offset of 

permeable zones restrict ground-water flow. For the period 

1936–49, underflow ranged from 14,300 to 23,700 acre-ft/yr 

(Dutcher and Garrett, 1963, table 5). During water years 

1935–60, underflow estimated using a mathematical model 

decreased from 16,900 acre-ft/yr in water year 1935 to 3,900 

acre-ft/yr in water year 1960 (California Department of Water 

Resources, 1971, table 4). Average underflow for the period 

1945–74 was about 15,000 acre-ft/yr (Hardt and Hutchinson, 

1980, table 5).

Underflow near the Santa Ana River is mostly dependent 

on ground-water levels in the Bunker Hill basin. As groundwater levels in the Bunker Hill basin rise, more ground water 

is forced out of the basin as underflow. As ground-water levels 

fall, less ground water leaves the basin as underflow. Changes 

in ground-water levels in the Rialto-Colton basin appear to 

have a much lesser effect. Attempts in this study to correlate 

estimated values of underflow, such as those by the California 

Department of Water Resources (1971, table 4), to groundwater levels near the Santa Ana River in the Rialto-Colton 

basin, were largely unsuccessful. Instead, the estimated underflow correlates well with ground-water levels in the Bunker 

Hill basin, as illustrated in figure 28. 

The Heap well (1S/4W–3Q1; refer p. 31) has a long 

period of record and is relatively shallow (fig. 29). The 

water-level record extends from 1942 to 1998 and the well is 

reported to be 200 ft deep. Most likely, this well senses only 

ground-water levels in the UCM and UWB hydrogeologic 

units (fig. 24), not in lower confined units. The well also does 

not appear to be affected by nearby pumpage or recharge. 

These characteristics make the Heap well a good predictor of 

underflow from the UCM and UWB units in the Bunker Hill 

basin across the San Jacinto fault. 

In order to estimate underflow for 1945–98, a nonlinear 

regression equation was fitted to measured ground-water levels 

in the Heap well and estimated underflow from the California 

Department of Water Resources (1971, table 4). This equation 

is 

QUnderflow

SAR, k = 96.876 log (WlHeap, k) + 663.136 (5)

where

QUnderflow

SAR, 

k

is underflow across the San Jacinto fault near the 

Santa Ana River during year k, in acre-ft/yr; and 

WlHeap is average ground-water level measured in the Heap 

well during year k, in ft above sea level.

 

Equation 5 does a good job (r2 = 0.937) of predicting historical underflow, as simulated by the regional ground-water 

flow model developed by the California Department of Water 

Resources (1971). Using equation 5, estimated underflow 

near the Santa Ana River averaged about 4,000 acre-ft/yr for 

1945–98, and ranged from about 12,000 acre-ft in 1945 to 

about 1,000 acre-ft in the mid 1960’s (table 9). 

Figure 27. Estimated underflow from San Timoteo Canyon 

and Sand Canyon into the San Bernardino area, California.

44 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

6,000

5,000

4,000

3,000

2,000

1,000

1920 30 40 50 60 70 80 90 2000 10 20 30

0

YEAR

UNDERFLOW, IN ACRE-FEET PER YEAR

= e

= 0.940

= -7.5x + 15,756

[-29.309 ln(x) + 230.4] y

y

Data from Dutcher and Fenzel (1972)

EXPLANATION

Sand Canyon

San Timoteo Canyon

Regression line

r 2
Figure 28. Relation between water level in the Heap well 

(1S/4W–3Q1) and underflow across the San Jacinto fault 

near the Santa Ana River.

Underflow estimated by Dutcher and Garrett (1963) 

using Darcy’s law is not as well predicted by equation 5 

(fig. 28). In general, the estimates by Dutcher and Garrett are 

slightly greater and are tightly grouped, falling within a narrow range of ground-water levels and underflow. It is possible 

that the California Department of Water Resources (1971) 

underestimated the true underflow, or that Dutcher and Garrett (1963) overestimated the true underflow. A ground-water 

flow model will tend to produce smoothly varying values of 

underflow as shown in figure 28, but how well these values 

match real underflow is rarely, if ever, known. Using Darcy’s 

law to estimate underflow can be equally problematic. Both 

hydraulic conductivity and cross-sectional area of underflow 

must be estimated. Uncertainty in these individual estimates 

can result in estimated underflow varying by a factor of two or 

more. Despite these caveats, equation 5 produces hydrologically reasonable values of underflow that vary in a predictable 

way within the general range of underflow values estimated by 

other investigators.

Underflow near Barrier J and across Barrier E, which is 

often mapped as part of the San Jacinto fault, was estimated

by Dutcher and Garrett (1963, p. 107). Although limited 

data were available, estimated underflow was about 

4,000 acre-ft/yr during 1952. Underflow estimated using a 

mathematical model ranged from 2,700 to 4,200 acre-ft/yr 

during water years 1935–60 (California Department of Water 

Resources, 1971, table 4). Discharge in Lytle Creek and 

nearby ground-water levels were examined by D.E. Williams 

(Geoscience Support Services Inc., 1992, 1994), who concluded that underflow to the Rialto-Colton basin averaged 

about 6,800 acre-ft/yr for 1978–93. 

Underflow near Barrier J was investigated by Woolfenden 

and Kadhim (1997) using ground-water chemistry, though 

no new estimates of underflow were provided. Subsequent 

numerical simulation of ground-water flow in the RialtoColton basin, however, involved estimating underflow from 

the Lytle Creek basin to the Rialto-Colton basin near Barrier J 

(L.R. Woolfenden, U.S. Geological Survey, written commun., 

2000). These estimates were calculated from discharge measurements of Lytle Creek where it flows out of the San Gabriel 

Mountains (fig. 11). Estimated underflow was 35 percent of 

discharge in Lytle Creek for most years, and 15 percent during 

very wet years. Using these assumptions, underflow near 

Barrier J averaged about 8,000 acre-ft /yr, and ranged 

from about 2,000 acre-ft/yr to about 19,000 acre-ft/yr 

(table 9). Final calibration of the ground-water flow model 

for the Rialto-Colton basin (Woolfenden and Koczot, 2001) 

slightly altered these initial estimates, but generally substantiated their reasonableness.

An important characteristic of the estimated values of 

underflow near Barrier J is that they vary greatly from one 

year to the next (table 9). More commonly, underflow varies somewhat smoothly, increasing and decreasing based on 

fluctuations in nearby ground-water levels (figs. 27 and 28). 

Ground-water levels do fluctuate markedly in the Lytle Creek 

and Rialto-Colton basins (Geoscience Support Services, Inc. 

1992, 1994; Woolfenden and Kadhim, 1997). Whether these 

fluctuations are sufficient to cause the variations in underflow 

is not known. 

One possible mechanism that could lend crediblity to 

large annual variations in underflow would be the uplifted 

bedrock shelf north of Barrier J. If it is sufficiently dissected 

and extends past Barrier E, then much of what is attributed 

to be underflow from the Lytle Creek basin, may actually 

be recharge from Lytle Creek routed via a subsurface drainage directly into the Rialto-Colton basin. Underflow south 

of Barrier J, estimated to be about 3,000 acre-ft/yr (Geoscience Support Services, Inc., 1994), would be more traditional 

underflow, fluctuating minimally from one year to the next 

depending on relative ground-water levels in the Lytle Creek 

and Rialto-Colton basins. Seismic or ground-penetrating-radar 

studies might be useful to test this theory.

Hydrology 45

950

0 5,000 10,000 15,000 20,000

975

1,000

1,025

1,050

1,075

UNDERFLOW, IN ACRE-FEET PER YEAR

WATER LEVEL, IN FEET ABOVE MEAN SEA LEVEL

y = 96.876log(x) + 663.136

r 2 = 0.937

Data from Dutcher and Garrett (1963), not used

in regression

Data from California Department of Water

Resources (1971)

EXPLANATION

Regression line
Total estimated underflow into and out of the San Bernardino area for 1945–98 is listed in table 9. Total estimated 

underflow into the San Bernardino area averaged about 

5,000 acre-ft/yr for 1945–98, and ranged from about 

4,000 acre-ft/yr to about 7,000 acre-ft/yr. Total estimated 

underflow out of the San Bernardino area averaged about 

13,000 acre-ft/yr for 1945–98, and ranged from about 

4,000 acre-ft/yr to about 25,000 acre-ft/yr. If a constant value 

of 3,000 acre-ft/yr as estimated by Geoscience Support 

Services, Inc. is assumed for outflow across the San Jacinto 

fault in the vicinity of Barrier J, then total underflow out 

of the San Bernardino area would have averaged about 

7,000 acre-ft/yr for 1945–98, and would have ranged from 

about 4,000 acre-ft/yr to about 15,000 acre-ft/yr. With this 

assumption, net underflow for 1945–98 would have averaged 

about 2,000 acre-ft/yr flowing out of the San Bernardino area.

Ground-Water Discharge into Warm Creek

Ground water discharges into the lower reaches of Warm 

Creek when nearby ground water rises above the bottom of the 

stream channel (refer p. 31 in this report). As ground-water 

levels rise higher than this threshold, discharge increases. 

For 1945–98, annual values of ground-water discharge into 

Warm Creek were determined in two ways. Annual values for 

1945–59 were interpolated from water-year data calculated by 

the California Department of Water Resources (1971, table 22) 

using measured streamflow. Annual values for 1960–98 were 

estimated using a nonlinear regression equation derived from 

that measured data (fig. 21). As shown in figure 30, estimated 

ground-water discharge varies considerably. Maximum discharge for 1945–98 exceeded 40,000 acre-ft/yr, and minimum 

discharge was zero for 16 consecutive years, from 1963 to 

1978. Average discharge was about 5,000 acre-ft/yr. 

Evapotranspiration

Evapotranspiration from the valley-fill aquifer occurs 

whenever ground water approaches land surface. As depth 

to the water table decreases, the evapotranspiration rate 

increases. When the water table is more than about 15 ft below 

land surface, the evapotranspiration rate is essentially zero. No 

detailed evapotranspiration studies have been done in the San 

Bernardino area in order to correlate evapotranspiration rates 

and depth to ground water. However, a maximum evapotranspiration rate of 1.0 x 10-7 ft/s (38 in/yr) was used by Hardt 

and Hutchinson (1980) in order to simulate evapotranspiration from the valley-fill aquifer in areas where the water table 

occasionally coincides with land surface, such as between 

Warm Creek and the Santa Ana River (fig. 22). The maximum 

rate of 38 in/yr is approximately 50 percent of the evaporation 

rate observed from a class-A evaporation pan in the San Bernardino area (San Bernardino County Flood Control District, 

1975). 

Simulated results from Hardt and Hutchinson (1980, 

figs. 16 and 18, table 3) show that as ground-water levels in 

the former marshland declined, evaporation declined from a 

maximum of about 30,000 acre-ft/yr in 1945, to zero from 

1954 until the model simulation ended in 1974. Using the 

same maximum evapotranspiration rate and an estimated depth 

to ground water, evapotranspiration was estimated to average 

about 7,000 acre-ft/yr for 1945–98. Evapotranspiration ranged 

from a maximum of about 26,000 acre-ft in 1983 to about 

1,000 acre-ft/yr in the mid 1960’s and late 1980’s.

Figure 29. Heap well (1S/4W–3Q1) in the San Bernardino area, California. Heap well, being measured by USGS Hydrologic 

Technician Kimball Stumpf and located on the edge of the former marshland, is used to estimate ground water rising into Warm 

Creek (fig. 21) and underflow from the Bunker Hill basin (fig. 28).

46 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Heap well

Heap well

Photographs by W.R. Danskin, 2005
Figure 30. Ground-water discharge into Warm Creek in the 

San Bernardino area California, 1943–98.

Additional evapotranspiration occurs from the unsaturated zone as a result of moisture that does not percolate to 

the saturated ground-water system. This moisture originates 

chiefly as direct precipitation on the valley-fill deposits 

(fig. 22) and was estimated to average about 86,000 acre-ft/yr 

(table 4). This additional evapotranspiration is important for 

the health and growth of vegetation, but it is not discussed 

further in this report because the unsaturated zone is not considered to be part of the valley-fill aquifer. Similarly, evapotranspiration resulting from native or imported water applied 

to agricultural fields or to urban areas is not quantified in this 

report, nor included in any of the reported evapotranspiration 

values.

Pumpage

Ground-water pumpage in the San Bernardino area is 

used for agricultural, municipal, and industrial purposes. As 

the area has become urbanized, the quantity of agricultural 

pumpage has declined considerably, particularly since about 

1957 (California Department of Water Resources, 1971, table 

49; Camp Dresser and McKee, 1991, p. 6). By 1992, agriculture accounted for less than 20 percent of total pumpage.

Gross pumpage, defined as total pumped water without 

accounting for any consumptive use losses or return flow, 

increased markedly between the mid-1940’s and the early 

1960’s (fig. 25). Prior to 1940, gross pumpage in the San Bernardino area typically was less than 110,000 acre-ft/yr (California Department of Water Resources, 1971, table 58). After 

1960, gross pumpage commonly exceeded 170,000 acre-ft/yr, 

and occasionally exceeded 200,000 acre-ft/yr. For 1945–98, 

gross pumpage averaged about 175,000 acre-ft/yr, and ranged 

from about 123,000 acre-ft in 1945 to about 215,000 acre-ft in 

1996 (table 10).

Gross pumpage has remained relatively constant since 

about 1960 primarily because of a lawsuit filed in 1963. In it, 

the Western Water District, representing residents generally 

west and downstream of the San Bernardino area, claimed 

that their extractions were in jeopardy because of unregulated 

extraction by others including the city of San Bernardino. The 

suit, which originally had five plantiffs and more than 4,000 

defendants, was settled in 1969 with a stipulated judgement 

that defined ground-water rights and created a watermaster to 

monitor ground-water use in the San Bernardino area (State of 

California, 1969b). 

Settlement of this lawsuit, referred to as the Western 

Judgement, was contemporaneous with settlement of a related 

lawsuit by the Orange County Water District that focused 

on similar surface-water issues (State of California, 1969a). 

Cooperative settlement of both lawsuits involved extensive 

technical investigations of water availability and use (California Department of Water Resources, 1970, 1971; San 

Bernardino Valley Municipal Water District, 1970). Much of 

these historical data, especially ground-water pumpage, was 

critically important in preparation of this present study.

Typically, more than one-fourth of the gross annual 

ground-water pumpage is exported out of the San Bernardino 

area, mostly to the nearby city of Riverside (fig. 1). As part 

of the Western Judgement, the city of Riverside is entitled to 

pump and export as much as 52,199 acre-ft/yr of ground water 

from the San Bernardino area. Since 1981, this pumpageexport limit has been increased by about an additional 

10,000 acre-ft/yr in an attempt to reduce high ground-water 

levels in the former marshland (San Bernardino Valley 

Municipal Water District, 1981b, 1985).

Most pumpage, as shown in figure 31, is located near 

the Santa Ana River, Lytle Creek, and the smaller tributary 

streams. This areal distribution of pumpage probably results 

from the exceptionally permeable deposits that underlie the 

stream channels and from the abundant nearby recharge. As 

the San Bernardino area has urbanized, some water purveyors 

have begun installing new wells higher on the alluvial fans, 

closer to the mountains and closer to the new urban demand 

(fig. 8). This new location permits the extraction of ground 

water at a higher head in the valley-fill aquifer. As a result, 

less additional lift is required for distribution, and pumping 

costs are reduced. The city of San Bernardino, which pumps 

nearly 20 percent of the ground water extracted in the San Bernardino area, has followed this philosophy in siting new wells 

since about 1975 (J.F. Stejskal, city of San Bernardino Water 

Department, oral commun., 1992).

Centroids of gross pumpage were calculated for each 

decade between 1945 and 1998 to quantify any changes in 

the areal distribution of pumpage. The centroids, shown in 

figure 31, indicate a small shift to the northwest of about 2 mi 

as would be expected by the increased pumpage by the city 

of San Bernardino near Shandin Hills. This shift occurred in 

about 1970, but probably has not had a significant effect on 

the overall ground-water flow system. The shift, however, 

may have had some effect on the migration of ground-water 

contamination, particularly any contamination flowing near 

the centroids of pumpage.

Hydrology 47

Estimated from regression equation 2b

 (fig.21)

Calculated by California Department of

 Water Resources (1971, table 22, col.1

 p.150)

Ground-water discharge

80

60

40

20

 0

1940 1950 1960 1970 1980 1990 2000

GROUND-WATER DISCHARGE,

 IN THOUSANDS OF ACRE-FEET 

YEAR
Figure 31. Areal distribution of average pumpage in the San Bernardino area, 1945–98.

48 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

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Lytle Cr

.

River

Santa

Ana

River

Santa

Ana

River

Santa

Ana

River

Santa

Ana

River

Santa

Ana

River

Santa

Ana

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

Seven

Oaks

Dam

San Bernardino Mountains

Crafton Hills

BadlandsBadlands

BadlandsBadlands

BadlandsBadlands

Mts

Gabriel San

Mts

Gabriel San

Mts

Gabriel San

Mts

Gabriel San

Mts

Gabriel San

Mts

Gabriel San

San Bernardino Mountains

Crafton Hills

0 10 KILOMETERS

0 10 MILES

0 10 KILOMETERS

0 10 MILES

0 10 KILOMETERS

0 10 MILES

0 10 KILOMETERS

0 10 MILES

0 10 KILOMETERS

0 10 MILES

0 10 KILOMETERS

0 10 MILES

San Bernardino Mountains

Crafton Hills

San Bernardino Mountains

Crafton Hills

San Bernardino Mountains

Crafton Hills

San Bernardino Mountains

Crafton Hills

Pumpage-Average gross pumpage per well for 

selected time periods. Values in acre-feet per year; 

average includes years with zero pumpage

> 0 - 1,000

1,000 - 2,500

2,500 - 5,000

Aquifer

boundary

1990-98

1980-89

1970-79

1960-69

1950-59

1945-49

EXPLANATION

Shandin

Hills

Shandin

Hills

Shandin

Hills

Shandin

Hills

Shandin

Hills

Shandin

Hills

0 2 KILOMETERS

0 2 MILES

Location of pumpage

centroid-For

selected time period

1990-98

1980-89 1970-79

1950-59

1945-49 1960-69

Santa

Ana River
The gradual change from many small wells in the San 

Bernardino area, to fewer large wells also is illustrated in 

figure 31. Part of this change is caused by the installation of 

new, large-capacity wells, but part of the change is more hours 

of pumping per year when agricultural wells are converted 

to municipal use. Note, values of average gross pumpage per 

well shown in figure 31 were calculated as if the well were in 

operation each year. Zero pumpage was assigned for any years 

that the well did not pump or did not exist.

Compilation and estimation of pumpage values used to 

prepare table 10 and figure 31 was a long, detailed procedure 

involving the Western–San Bernardino watermaster, staff from 

the San Bernardino Valley Municipal Water District, and cooperation of many other water purveyors in the San Bernardino 

area. The objective was to create a computerized pumpage 

database that includes all wells in the San Bernardino area 

for 1945–98. The database needed to be consistent with data 

maintained by the watermaster, match watermaster recordation 

numbers with state well numbers, have all wells located with 

a global positioning system (GPS), and incorporate selected 

characteristics necessary for development of the ground-water 

flow model, such as return-flow percentage. 

The end-result of this 3-year effort is a database maintained and annually updated by the Western–San Bernardino 

watermaster (State of California, 1969b). Compilation of prior 

watermaster data was done by R.L. Reiter (San Bernardino 

Valley Muncipal Water District) and S.E. Mains (Western 

Municipal Water District). Correlation of data maintained by 

the watermaster using a recordation number, with data maintained by the State of California using a state well number, 

was done by staff of the San Bernardino Valley Municipal 

Water District, in particular, S.H Fuller and R.W. Peterson. 

Prior to this effort, recordation numbers were not necessarily 

correlated to specific wells. In some cases, a single recordation number referred to different wells in different years. And 

a few recordation numbers actually referred to surface-water 

diversions.

Individual wells were identified in the field by a person 

who was familiar with that specific well, typically someone 

from the water district or municipality maintaining the well 

and using the pumped water. During that site visit, latitude and 

longitude of the well were determined using global positioning 

equipment. Error in locating each well is believed to less than 

about 20 ft.

Return-flow percentage for each well was defined using 

estimates from Hardt and Hutchinson (1980) and knowledge 

from the Western–San Bernardino watermaster (R.L. Reiter, 

oral commun., 2000) about the fate of water pumped from 

individual wells. If water from a well was exported from the 

San Bernardino area in either a pipe or concrete-lined channel, 

then a zero return-flow percentage was assigned. For all other 

wells, a return-flow percentage of 30 was assigned. These percentages were held constant for 1945–98 because wells used 

for export rarely were used for local supply.

The vertical distribution of gross pumpage between layers of the aquifer (model) was calculated for individual wells 

using original data sheets developed by W.F. Hardt (U.S. 

Geological Survey, written commun., 1980). The original 

estimates from Hardt were based on the perforated interval 

of a well and the hydraulic conductivity of deposits adjacent 

to the perforated interval. For new wells, a similar calculation was made to define the ratio of extraction from the upper 

and lower layer. Since 1980, when extensive ground-water 

contamination by volatile organics was discovered, many new 

wells have been installed with perforations only in the lower 

layer. As shown in figure 25, an approximately equal quantity 

of pumped water is withdrawn from the upper and lower layers of the valley-fill aquifer. 

The upper layer is defined as hydrogeologic units UCM 

and UWB; the lower layer is defined as hydrogeologic units 

MCM, MWB, LCM, LWB, and QTc (fig. 24). These are 

exactly the same definitions used for the upper and lower layers of the ground-water flow model. Estimating the percentage extraction from upper and lower layers has a significant 

limitation. For nearly all wells, the hydraulic conductivity of 

the deposits adjacent to the perforated interval is not known 

and must be estimated from lithologic descriptions found in 

driller’s logs. Typically, these descriptions do not have detailed 

information about the compaction, cementation, or sorting of 

the deposits. Especially for unconsolidated deposits, this technique can over-estimate the amount of extraction from lower 

deposits which may be described as being very similar to 

overlying, younger deposits. But in reality the lower deposits 

are much older, more consolidated, possibly partly cemented, 

may be deeply weathered, and are likely much less permeable 

than when they were younger and higher in the stratigraphic 

column, despite having very similar lithologic descriptions on 

driller’s logs. 

Flowmeter testing of three production wells using a 

spinner tool showed that most of the extraction came from the 

shallow, younger deposits (Izbicki and others, 1998). In some 

cases, virtually no water was contributed to the well from the 

deepest perforated intervals. These measurements suggest that 

the estimated percentages of extraction from upper and lower 

layers may be in error, and may overestimate the amount of 

water extracted from the lower layer. What effects this error 

has on understanding the ground-water system are difficult 

to determine, but the effects are likely to be important. For 

example, the relative quantity of extraction from different 

hydrogeologic units would change interpretations of where 

and how fast a contaminate is transported. Flowmetering of 

as many wells as possible in the San Bernardino area would 

aid in re-evaluating the estimates of the vertical distribution 

of extraction used in this report, and likely would aid in better 

understanding of critical ground-water issues.

Hydrology 49
Although most pumpage data was provided by the watermaster, some additional processing was necessary to prepare 

a complete dataset for 1945–98 (table 10). To understand this 

processing, some background information is needed. Each 

calendar year, anyone who pumps more than 25 acre-ft in the 

adjudicated area, which includes the entire Bunker Hill and 

Lytle Creek basins, is required to report this pumpage to the 

State of California. The watermaster then obtains this filed

data and verifies that it is correct. As an official officer of the 

court, the watermaster is legally entitled to obtain electrical 

records, crop use, tax data, and other information needed to 

verify that the reported pumpage is reasonable. If it is not, then 

the watermaster adjusts the data for a specific well.

These verified data are summarized for plaintiffs and nonplaintiffs in the Western Judgement. Because there are only 

seven plaintiffs (Western Municipal Water District, city of Riverside, Gage Canal Company, Aqua Mansa Water Company, 

Meeks and Daley Water Company, Riverside-Highland Water 

Company, and the Regents of the University of California), 

most adjustments are for non-plaintiffs. Typically, the total 

value of pumpage for the seven plaintiffs changes by less than 

1 or 2 percent. The total value of pumpage for the hundreds 

of non-plaintiffs changes by less than about 5 percent, and is 

usually an increase. 

If the watermaster is aware of any pumpage that has not 

been filed, then the amount is estimated and is added to the 

dataset. These values are referred to as non-filed pumpage, and 

occur only for non-plaintiffs. At the end of this entire process, 

the pumpage data for a year is deemed verified and is published.

Verified pumpage data has been available since 1970, the 

year following the Western Judgement. Verified data also are 

available for a 5-year period (1959–63) that was used for a 

safe-yield analysis done as a result of the adjudication (Western–San Bernardino Watermaster, 1972). Records of reported, 

but non-verified pumpage began in 1947, although non-filer 

pumpage was not recorded until 1958. No pumpage values per 

well were available prior to 1947. In order to create a complete pumpage dataset for 1945–98, some pumpage values per 

well needed to be estimated for selected time periods. These 

estimates are described below and are referenced in table 10 as 

E1 through E5.

Use of non-verified, plaintiff and non-plaintiff pumpage 

for 1947–58 and 1964–69.—Pumpage data for both plaintiffs 

and non-plaintiffs for 1947–58 and 1964–69 are available only 

as non-verified pumpage. These two time periods preceded 

adjudication of the San Bernardino area, and although pumpage data were reported, it was never verified. Pumpage for the 

interim period, 1959–63, was verified only because it was analyzed as part of adjudication. Because pumpage for 1947–58 

and 1964–69 will never be verified, the non-verified pumpage 

was deemed adequate for this study. Non-plaintiff non-filer 

pumpage was estimated separately for the two periods, as 

described below. 

Analysis of verified and non-verified pumpage for both 

plaintiffs and non-plaintiffs for 1970–97 showed that the nonverified pumpage was generally less than verified pumpage. 

This difference is less than about 1 percent for plaintiff pumpage and less than about 3 percent for non-plaintiff pumpage. 

No reliable method was identified to modify non-verified 

pumpage for 1947–58 and 1964–69 to account for this likely 

difference; therefore, no adjustment was made. 

Estimation of plaintiff pumpage, 1945–46 (E1).—Plaintiff 

pumpage for 1945–46 was estimated using a set of average 

values scaled by a linear regression. The set of average values 

was calculated using plaintiff pumpage for 1947–52, averaged 

for each well. Zero pumpage was assumed for any well for any 

year with no pumpage, or if the well may have been destroyed 

or may not yet have been installed. The linear regression equation,

 QPumpP

k

 = -166.38 PSARRO

k

 + 59,244 (6)

where

QPumpP

k is plaintiff pumpage for calendar year k, in acre-ft/yr; 

and

PSARRO

k is average annual runoff for the Santa Ana River measured at USGS station 11051501 for calendar year 

k, compared to longterm average runoff at the same 

station for 1928–98, in percent,

was determined from total annual plaintiff pumpage for 1947–

52 (fig. 32). The plaintiff pumpage for 1945–46 was calculated 

by multiplying the set of average pumpage values determined 

for 1947–52 by the total annual pumpage determined from 

equation 6.

Estimation non-plaintiff pumpage, 1945–46 (E1).— Nonplaintiff pumpage for 1945–46 was estimated in the same 

way as plaintiff pumpage for 1945–45, using a different, but 

similarly derived regression equation,

QPumpNP

k

 = -388 PSARRO

k

 + 117,891 (7)

where

QPumpNP

k is total non-plaintiff pumpage for calendar year k, in 

acre-ft/yr; and

PSARRO

k is average annual runoff for the Santa Ana River measured at USGS station 11051501 for calendar year 

k, compared to longterm average runoff at the same 

station for 1928–98, in percent.

50 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Note, the annual values used to develop equation (7) are 

slightly different from those in table 10. The initial pumpage 

data included a few wells, whose total pumpage was less than 

about 500 acre-ft/yr. These wells ultimately were excluded 

from the analysis because they were not located in the valleyfill, but the regression equation and values for 1945–46 were 

not redone. The net effect of this decision was deemed to be 

insignificant. 

Estimation of non-plaintiff, non-filer pumpage, 1945–58 

(E3).—No data were available for non-plaintiff non-filer 

pumpage for 1945–58. Therefore, non-filer pumpage for the 

subsequent safe–yield period (1959–63) was analyzed to 

detect any changes in the areal distribution of pumpage or any 

temporal trend. The areal distribution of non-filer pumpage 

was approximately the same for 1959, 1960 and 1961–63, 

implying the same wells or nearly the same wells were used 

during each time frame. No new non-filer pumping centers 

had been created or destroyed. The average non-filer pumpage 

for 1959–63 (12,825 acre-ft/yr) was almost exactly the same 

as for 1959 (12,824 acre-ft/yr). Therefore, it seemed reasonable to use the exact values of non-filer pumpage for 1959 for 

each year during 1945–58.

A caveat in this assumption is that non-filer pumpage 

generally decreased from 1959 to 1998. It is possible that nonfiler pumpage was greater during 1945–58 than in subsequent 

periods, but no corroborating data were found. Attempts to 

correlate non-filer pumpage with annual values of precipitation, runoff in the Santa Ana River, or total reported pumpage 

were unsuccessful.

Figure 32. Regression equations used to estimate pumpage in the San Bernardino area, California, 

1945–46. All data for 1947–52; refer tables 2 and 10. Runoff data for U.S. Geological Survey gaging 

station 11051501; long-term average runoff for 1945–98. Plaintiff and non-plaintiff (filed) pumpage 

data from the Western−San Bernardino Watermaster.

Hydrology 51

PUMPAGE, ACRE-FEET PER YEAR

ANNUAL RUNOFF IN THE SANTA ANA RIVER, PERCENT OF LONG-TERM AVERAGE

Non-plaintiff

pumpage

Plaintiff

pumpage

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

110,000

0 20 40 60 80 100 120

y = -388x + 117,891

y = -166.38x + 59,244

r2 = 0.84

r2 = 0.55
Estimation of non-plaintiff, non-filer pumpage, 1964–69 

(E4).—No data were available for plaintiff non-filer pumpage for 1964–69. Therefore, annual non-filer pumpage for 

the prior safe–yield period (1959–63) and for the subsequent 

verified period (1970–97) were analyzed to detect any changes 

in the areal distribution of pumpage or any temporal trend. 

This analysis showed that annual non-filer pumpage before 

1964–69 averaged about 12,000 acre-ft, and after 1964–69, 

decreased from about 8,400 acre-ft to less than 3,500 acreft (table 10). Attempts to correlate this decline with annual 

values of precipitation, runoff in the Santa Ana River, or total 

reported watermaster pumpage failed to identify a reliable 

relation. The simplest and seemingly best method of estimating annual non-filer pumpage for 1964–69 was to linearly 

decrease total non-filer pumpage from the value in 1963 

(12,599 acre-ft/yr) to the value in 1970 (8,416 acre-ft/yr).

Analysis of the areal distribution of annual non-filer 

pumpage showed noticeable differences in the 2 years before 

1964–69 (1962–63) and the 2 years after 1964–69 (1970–71). 

In general, more non-filer wells were present in the former 

marshland and along Warm and City Creeks. Differences in 

the areal distribution of non-filer wells between 1962 and 1963 

were minor, as were differences between 1970 and 1971. 

To determine a representative areal distribution of nonfiler wells and pumpage for 1964–69, the 4 proximal years 

(1962–63, 1970–71) were selected. For this 4-year period, 

pumpage was summed, then averaged for each non-filer well. 

Zero pumpage was assumed for any well for any year with 

no pumpage, even if the well may have been destroyed or 

may not yet have been installed. Next, these average values of 

non-filer pumpage were summed for the San Bernardino area, 

and the total (10,071 acre-ft/yr) was used to calculate annual 

values of non-filer pumpage for each well for 1964–69. This 

calculation multiplied the 4-year average pumpage at each 

non-filer well by NFPi

Total/10,071 acre-ft, where NFPiTotal is the 

total non-filer pumpage, in acre-ft, for a specific year i, which 

was estimated by a linear decrease in total non-filer pumpage 

from 12,599 acre-ft in 1963 to 8,416 acre-ft in 1970 (table 10).

Estimation of non-plaintiff, non-filer pumpage, 1998 

(E5).—Plaintiff non-filer pumpage for 1998 was unavailable 

at the time of preparation of this report; therefore, non-filer 

pumpage for 1997 was used verbatim. This assumption is 

unlikely to have a significant effect on total pumpage from 

the San Bernardino area because recent non-filer pumpage 

is small. Since 1961, non-filer pumpage had decreased by a 

factor of three to less than 4,000 acre-ft/yr in 1997 (table 10). 

Any error associated with using 1997 data for 1998 is likely to 

be minimal, probably less than 500 acre-ft. 

Use of non-verified, plaintiff and non-plaintiff pumpage 

for 1998.—Pumpage data for both plaintiffs and non-plaintiffs 

for 1998 were available only as non-verified pumpage at the 

time of this study; therefore, the non-verified data were used. 

Since 1970, the difference between verified and non-verified 

pumpage has become progressively smaller. The difference for 

1998 is likely to be insignificant, although any update of this 

study should consider revising table 10 and the ground-water 

flow model with verified pumpage for 1998 and subsequent 

years.

Ground-Water Storage

The first comprehensive change-in-storage calculations 

for the greater San Bernardino area were done by the California Department of Water Resources (1971, table 61) for water 

years 1935–60. Two methods were used to calculate change in 

storage. The first relied on a detailed accounting of recharge 

and discharge. The second used the technique of multiplying 

the annual change in the water table by specific yield. The two 

methods were used together to estimate an average decrease 

in storage of about 24,000 acre-ft/yr for the 26-year period. 

The study area for this analysis included the Yucaipa basin; 

therefore, the decrease in storage for the Bunker Hill and Lytle 

Creek basins was likely somewhat less. 

A few years later, Hardt and Hutchinson (1980, p. 38) 

calculated the change in storage for calendar years 1945–74. 

Partly with the aid of a ground-water model of the Bunker 

Hill and Lytle Creek basins, these investigators estimated an 

average decrease in storage of about 33,000 acre-ft/yr for the 

30-year period. This rate equates to a total storage depletion of 

almost 1 million acre-ft. For the same period, but only for the 

Bunker Hill basin, the San Bernardino Valley Municipal Water 

District (1977) estimated a total storage depletion of about 

700,000 acre-ft, or about 23,000 acre-ft/yr. This analysis used 

the technique of multiplying the annual change in the water 

table by specific yield. Computational limitations restricted 

the calculation to nine subareas of the Bunker Hill basin; each 

subarea was assumed to have a single value of specific yield 

and change in water table.

More recently, annual change in storage for 1934–98 

was calculated by the San Bernardino Valley Municipal Water 

District (2000) for an area slightly larger than the Bunker Hill 

and Lytle Creek basins. The technique used a GIS with annual 

measurements of ground-water levels and areally distributed 

estimates of specific yield. Ground-water-level measurements 

were chosen to represent the lowest levels observed during fall 

of each year and were selected from wells that were believed 

to represent the unconfined part of the valley-fill aquifer. Contours of specific yield were digitized from Eckis (1934, map 

E). A GIS gridding program was used to interpolate groundwater levels and specific yield for thousands of small grid 

cells. Interpolation was done independently for nine subareas 

bounded by faults in order to avoid interpolation errors associated with abrupt changes in ground-water levels or specific 

yield across a fault. 

Annual change in storage for 1934–98 was calculated 

for each grid cell as the annual change in ground-water level 

multiplied by specific yield. Values for individual cells were 

summed specifically for the area of the valley-fill aquifer 

(fig. 22), which is a subset of the area analyzed by the San 

Bernardino Valley Municipal Water District (2000). 

52 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Based on these data, significant changes in ground-water 

storage occurred during 1945–98. Although the total quantity of ground water in storage is not known, the maximum 

cumulative change in storage was greater than 900,000 acre-ft 

from 1945 to 1966 and greater than 500,000 acre-ft for several 

10-year periods. The annual change in storage commonly 

ranged from 50,000 to 100,000 acre-ft. The average change in 

storage for 1945–98 was about 4,000 acre-ft/yr. This decrease 

is significantly less than for other estimates described above, 

but may result from greater recharge from local runoff during 

recent years, as well as recharge from imported water. 

Potential errors in this calculation of storage are likely to 

be minor, but may include: (1) inaccurately estimating specific 

yield, (2) selecting of a well that includes a confined response 

rather than only the desired water-table response, and (3) not 

calculating change in storage for the confined part of the aquifer. Errors associated with item 1 were mitigated somewhat 

by using the careful mapping of specific yield by Eckis (1934, 

map E). Errors associated with item 2 were avoided as much 

as possible by reviewing construction data and hydrographs 

for all wells used for ground-water levels. The review helped 

ensure that the wells sensed only the water table. Commingling of a water-table and confined response would overestimate changes in storage. Because of large ground-water-level 

changes from 1934 to 1998, the goal of sensing only the water 

table may not have been achieved perfectly. 

Errors associated with item 3 can be addressed by estimating the additional change in storage that occurred in the 

confined part of the valley-fill aquifer. The difference between 

specific yield and confined storage coefficient in the San Bernardino area is about a factor of 1,000—an average of about 

0.10 for specific yield compared to about 0.0001 for confined 

storage coefficient. Change in water-level for a confined 

system is probably less than 10 times the change in water-level 

for an unconfined system. These assumptions mean that the 

approximate change in storage for the confined part of the San 

Bernardino valley-fill aquifer is about 100 times less than for 

the unconfined system, or about 40 acre-ft/yr.

Ground-Water Budget

A ground-water budget for the valley-fill aquifer 

(fig. 22) for 1945–98 is listed in table 11, and a piechart of 

these values is shown in figure 33. The budget is derived 

mostly from measured or estimated values of the various components of recharge and discharge. Detailed descriptions are 

included in two previous sections of this report, “Recharge and 

natural discharge” and “Pumpage.” Evapotranspiration values 

for the budget were derived with the aid of the ground-water 

flow model, described in a later section of this report, because 

no annual valleywide estimates of evapotranspiration have 

been made.

Minimum and maximum annual values for 1945–98 also 

are listed in table 11. These values, many of which are much 

different from the average value, give an indication of the 

possible uncertainty in the average values, and demonstrate 

the wide range in recharge and discharge that can be expected 

to occur absent a major change in either climatic conditions or 

human water-management decisions.

The relatively large annual fluctuations in ground-water 

storage—indicated by a 400,000 acre-ft/yr difference between 

minimum and maximum values—mirror the large fluctuations 

in runoff from the surrounding mountains. Recharge from 

gaged streams ranges from less than 30,000 acre-ft/yr to 

more than 400,000 acre-ft/yr (table 11). By comparison, 

gross pumpage is relatively static, varying less than about 

50 percent of the average value, or about 50,000 acre-ft/yr. 

The maximum variation in recharge of imported water is only 

30,000 acre-ft/yr. Values in table 11 illustrate that although 

some water has been imported for artificial recharge and 

pumpage varies somewhat, replenishment of the valley-fill 

aquifer depends mostly on recharge from local sources.

A residual term, which reflects the cumulative error 

in estimating recharge, discharge, and change in storage, is 

included explicitly in the ground-water budget. This approach 

is rare in water-budget analyses, but was chosen for this study 

in order to maintain the veracity of each of the components 

of the water budget. Many of the components were calculated 

from a rare abundance of measured data, or were estimated 

with great care. How the residual term should be distributed 

amongst the various components is not known, but an estimate 

is provided as part of table 11. 

The largest component of the residual term is underflow 

across the San Jacinto fault near Barrier J. Underflow in this 

area was the subject of lengthy investigation and debate during this study, but no clear understanding emerged. Increased 

recharge from gaged streams and a greater change in storage for the unconfined part of the valley-fill aquifer also are 

relatively large components of the residual term. The reasonableness of values chosen for these three components of the 

residual resulted from review of a simulated water budget 

for the ground-water flow model. Seepage from the bedrock 

aquifer surrounding and underlying the valley-fill aquifer 

commonly is assumed to be zero, as it was in the conceptual 

model used for this study. But a heat-transport model suggested that as much as 15,000 acre-ft/yr of water could be 

contributed to the valley-fill aquifer from the bedrock aquifer 

(Hughes, 1992). A value of 6,000 acre-ft/yr was used to parse 

the residual and recognize that the seepage is certainly greater 

than zero, though how much greater is unknown.

Hydrology 53
Component Minimum Average 

value Maximum Comment

Recharge

 Direct precipitation 0 1,000 12,000

 Gaged runoff 27,000 116,000 423,000

 Ungaged runoff 4,000 16,000 68,000

 Local runoff 2,000 5,000 12,000

 Imported water 0 3,000 30,000

 Underflow 4,000 5,000 7,000

 Return flow from pumpage 20,000 28,000 37,000

 Total 57,000 174,000 589,000

Discharge

 Pumpage 123,000 175,000 215,000

 Underflow 4,000 13,000 25,000

 Evapotranspiration 1,000 7,000 26,000

 Rising ground water 0 5,000 42,000

 Total 128,000 200,000 308,000

Change in storage −143,000 −4,000 289,000

Residual na −22,000 na

Sources of water to compensate for residual

 Recharge from gaged runoff 0 4,000 5,500 Simulated values are 5,500 acre-feet per year greater 

than original estimate, which required many assumptions.

 Recharge from ungaged runoff 0 500 500 Original estimate is highly uncertain.

 Recharge from local runoff 0 500 500 Roundoff error of original estimate is 500 acre-feet 

per year.

 Seepage from bedrock aquifer 0 6,000 15,000 Some underflow from bedrock is likely, and has been 

estimated using a heat-transport model to be as 

much as 15,000 acre-feet per year.

 Change in storage, unconfined part of 

the valley-fill aquifer

0 3,000 7,500 Ground-water flow model suggests a greater change 

in storage occurred.

 Change in storage, confined part of 

the valley-fill aquifer

0 100 500 Original estimate for change in storage did not account for the confined aquifer.

 Water released during land subsidence 0 500 1,000 Some inelastic release of water from storage likely 

occurred, but the quantity is unknown.

 Reduced evapotranspiration 0 1,000 2,000 Model may overestimate evapotranspiration.

 Reduced underflow out of aquifer 0 6,400 6,400 Simulated value for underflow near Barrier J is 

6,400 acre-ft/yr less than original estimate.

 Total na 22,000 na

Table 11. Ground-water budget for the San Bernardino area, California, 1945–98.

[Values in acre-feet per year; −, indicates a decrease in ground-water storage; na, not applicable; average values are well researched from measured and

 estimated data; values to compensate for calculated residual are speculative]

54 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 33. Average recharge, discharge, and change in storage for the valley-fill aquifer in the San Bernardino area, California, 

1945–98. Values in acre-feet per year; individual components also shown as approximate percent of total recharge or discharge. 

Annual values listed in table 8. Residual represents difference between recharge, discharge, and change in storage; components 

of the residual are rough estimates.

Hydrology 55

Recharge

174,000

acre-feet per year

Residual

22,000

acre-feet per year

1,000

1%

Direct precipitation

3,000

2%

Imported water

16,000

9%

Ungaged runoff

5,000

3%

Underflow

5,000

3%

Local runoff

28,000

16%

Return flow

5,000

3%

Rising ground water

7,000

4%

Evapotranspiration

6,400

29%

Underflow

500

2%

Land

subsidence

Local

runoff

Ungaged

runoff

500

2%

500

2% Evapotranspiration

1,000

5%

Storage

3,100

14%

Gaged runoff

4,000

18%

6,000

27%

Bedrock seepage

13,000

7%

Underflow

116,000

67%

Gaged runoff

175,000

88%

Gross Pumpage

200,000

acre-feet per year

Change in storage

(depletion)

4,000

acre-feet per year

Discharge
Ground-Water Movement

In all aquifers, ground water flows from areas of recharge 

to areas of discharge. In the San Bernardino area, the overall 

pattern of ground-water flow is controlled primarily by the 

relatively large areas of recharge, and to a lesser degree, by 

the more localized areas of discharge and by the location of 

faults that impede ground-water movement. The areal pattern 

of ground-water movement—from areas of recharge along the 

base of the San Bernardino Mountains, south toward areas of 

discharge where the Santa Ana River crosses the San Jacinto 

fault—has remained similar from historical times prior to 

ground-water development (fig. 9; Mendenhall, 1905, pl. 8) to 

the present (fig. 22; Duell and Schroeder, 1989, fig. 5).

The vertical pattern of ground-water flow, however, has 

been changed significantly by ground-water development. 

Historically, ground water moved vertically down through 

the aquifer materials in recharge areas, then horizontally 

through the more permeable layers of the valley-fill aquifer, 

and eventually vertically up through fine-grained materials 

to be discharged as underflow across the San Jacinto fault, as 

evapotranspiration from the marshland, and as rising water 

into Warm Creek. A downward vertical gradient was present 

in the recharge areas, and an upward vertical gradient was 

present in the discharge area. This pattern of flow and vertical 

distribution of ground-water head is typical of an undeveloped 

ground-water basin (Freeze and Cherry, 1979, p. 196). Withdrawal of water from the earliest hand-dug wells, which were 

less than 100 ft deep, did not significantly alter ground-water 

levels or the pattern of ground-water flow.

As ground-water production increased, first for agricultural and then for urban uses, ground water was withdrawn 

from increasingly deeper parts of the valley-fill aquifer. Natural discharge to the land surface was replaced by discharge to 

pumping wells within the aquifer. Hydraulic head within the 

aquifer changed to reflect the change in ground-water flow 

patterns, and the upward vertical gradient was reduced or 

reversed. The extent of this change is shown in figure 24 for a 

representative section of the valley-fill aquifer. By 1992, the 

entire extent of historically flowing wells from the San Jacinto 

fault to Highland Road showed a downward, not upward, 

vertical gradient.

The abundance of wells, in particular abandoned wells, 

in the San Bernardino area also has affected vertical groundwater flow. Between 1939 and 1945, Horace Hinckley 

inventoried and mapped more than 2,500 wells in the San 

Bernardino area; over 800 of these wells were identified as 

being destroyed (fig. 34). Most likely, some of the wells identified by Hinckley as destroyed, in addition to some of the wells 

abandoned in the succeeding 55 years, were perforated, or 

have been corroded opposite permeable layers of the valleyfill aquifer. Many of these wells would have been filled in, at 

least partly, with dirt or debris, but some lengths of open hole 

or casing probably remain open. In addition, gravel packing 

in the annulus of a well may span less permeable zones of the 

aquifer. Together the well casing and adjacent gravel pack can 

act as an exceptionally permeable vertical conduit, shunting 

ground water either up or down through the valley-fill aquifer, 

at many times the rate that is possible through the native aquifer materials. The same effect occurs in non-pumping production wells. Video logging of such wells has shown ground 

water flowing vertically at several feet per minute even during 

unpumped conditions (J.F. Stejskal, City of San Bernardino, 

written commun., 1992). The rate and direction of vertical 

flow through aquifer materials or abandoned wells is governed 

by vertical gradients in the aquifer.

Ground-water-level data from a multiple-depth monitoring site (1S/4W–22D2, 4–7; fig. 24) show the complexity 

of vertical gradients and how the gradients between hydrogeologic units change throughout the year (fig. 35). At this 

monitoring site, ground water during summer flows up and 

down to a major pumping zone at 160–200 ft below land surface. During winter, when pumpage is reduced and recharge to 

the valley-fill aquifer increases, ground water flows from this 

zone to underlying zones. During the entire year, ground water 

flows from the uppermost zone (10–45 ft) to the 160–200 ft 

zone. This complexity of vertical ground-water movement 

probably is typical of conditions in the valley-fill aquifer at 

distances of as much as 1 mile from significant ground-water 

pumping (fig. 31).

In 1990, a large-scale aquifer test was conducted using a 

newly installed, high-capacity production well (Ninth Street 

well, 1S/4W–4E8) and four multiple-depth monitoring wells 

(figs. 24 and 35). Additional monitoring wells with a single 

screened interval also were used. The Ninth Street well 

was pumped continuously at about 7 ft3/s for about 7 days. 

Response in ground-water levels occurred much further away 

and in a much more predictable way than was expected. At 

the Meadowbrook site (1S/4W–10B3), more than 8,000 ft 

from the pumping well, the ground-water-level decline was 

about 4 ft in the middle confining member (MCM; fig. 24) 

after 7 days of pumping. Even a very small response (0.05 

ft) was observed after 1 day more than 15,000 ft away in the 

water-table piezometer (1S/4W–22D7) at the SBVMWD site. 

Subsequent aquifer-test analyses (Theis, 1935) confirmed 

the continuity of the hydrogeologic units and their hydraulic 

properties in the center of the Bunker Hill basin. Approximate 

values of transmissivity and storage coefficient from this test 

were 17,000 ft2/d and 0.001, respectively.

56 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 34. Location of wells in the San Bernardino area, California, 1945.

Hydrology 57

FAULT

Oak Glen Fault

SAN

ANDREAS

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Seven Oaks Dam

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EXPLANATION

Crafton Hills

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Water well-One of about 2,000 wells visited and mapped between

1939 and 1945 by H.P. Hinckley (San Bernardino Valley Water

Conservation District, written commun., 1945). About 800 of these

wells were identified as having been destroyed by 1945. Another 434

wells, listed in U.S. Geological Survey Bulletin 142, were noted by

Hinckley as having been destroyed, but are not included on either his

map or this illustration

Fault or ground-water

barrier-May be concealed

or approximately located

San Bernardino Mountains

Gabriel

Mts

San

Boundary of Santa Ana

River drainage basin

.

Artificial-recharge basin

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

0 6 KILOMETERS

0 6 MILES

Basin boundary-Bunker Hill

and Lytle Creek ground-water

basins shaded in darker gray
Figure 35. Measured water level in multiple-depth cluster wells in the San Bernardino area, California, 1990–2000.

58 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Meadowbrook Park wells

Land surface altitude 1,015 feet

1S/4W-10B3

900

910

920

930

940

950

960

970

980

 990

1,000

300-320

1S/4W-2D8

170-190

1S/4W-2D8

170-190

1S/4W-2D7

340-400

1S/4W-2D6

520-530

1S/4W-10B4

100-120

1S/4W-10B2

680-700

900

910

920

930

940

950

960

970

980

990

1,000

WATER LEVEL, IN FEET ABOVE MEAN SEA LEVEL 

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

YEAR

900

910

920

930

940

950

960

970

980

990

Well number and perforated interval-Lower

number is perforated interval, in feet below land 

surface

Potential direction of vertical ground-water movement-

 As indicated by decreasing ground-water level

1,000

1S/4W-22D7

10-45

1S/4W-22D4

650-655

San Bernardino Valley Municipal

Water District backyard wells

Land surface altitude 975 feet

Sierra High School wells

Land surface altitude 1,077 feet

1S/4W-22D2

160-200

1S/4W-22D6

388-398
As of 1998, the longterm trend in ground-water development continues; ground water is preferentially withdrawn 

from hydrogeologic units deeper than UWB (figs. 24–25). 

Many large municipal production wells have perforations 

only below a depth of 200 to 300 ft below land surface. This 

change in construction, done largely to avoid ground-waterquality problems near the land surface, has further altered the 

vertical movement of ground water. With additional deeper 

extractions, the hydraulic head in the deeper hydrogeologic 

units (MWB, LCM) will decline. If this decline is significant, 

compared to historical declines, then land subsidence, which 

occurred from 1950 to 1970, may resume (Miller and Singer, 

1971; California Department of Water Resources, 1986). In 

addition, a decline of hydraulic head in the deeper hydrogeologic units will induce some ground-water flow to the pumped 

zones from the poorly permeable LWB unit, through faults and 

fractures, and possibly from the surrounding and underlying 

bedrock aquifer.

Ground-Water Quality

Ground water in the San Bernardino area generally is a 

sodium-calcium-bicarbonate type, containing equal amounts 

(on an equivalents basis) of sodium and calcium in shallow 

ground water and an increasing predominance of sodium in 

water from deeper parts of the valley-fill aquifer. Concentrations of both sodium and chloride are higher in the lower confining member (LCM) and lower water-bearing unit (LWB) 

(fig. 24). Mean dissolved-solids concentration was about 400 

milligrams per liter (mg/L) in the upper part the valley-fill 

aquifer and about 200 mg/L in the deeper parts of the valley-fill aquifer where confined conditions are present (fig. 24) 

(Duell and Schroeder, 1989, p. 56).

The inorganic composition of ground water varies areally 

in the valley-fill aquifer depending on the part of the watershed contributing runoff and recharge (Dutcher and Garrett, 

1963). Runoff from igneous and metamorphic rocks tends to 

have a lower dissolved-solids concentration than runoff from 

sedimentary rocks or unconsolidated deposits (fig. 5). The 

largest sources of runoff and recharge—the Santa Ana River, 

Lytle Creek, and Mill Creek (figs. 11 and 12)—have calciumbicarbonate water. The smaller creeks in the middle of the San 

Bernardino area—East-Twin, City, and Plunge Creeks— have 

higher equivalent concentrations of sodium (Dutcher and Garrett, 1963, fig. 2).

The inorganic composition of ground water also may be 

affected by small quantities of geothermal water emanating 

from faults and fractures in the bedrock surface underlying the 

valley-fill aquifer (Eccles and Klein, 1978). Geothermal water 

typically has high concentrations of metal ions (Hem, 1985, p. 

31) and an elevated temperature. Ground water suggesting a 

geothermal origin has been found near Faults L and K (Eccles 

and Klein, 1978), near the westernmost extension of the Banning (?) fault (Geoscience Support Services, Inc., 1990), and 

near the Loma Linda fault just west of the Santa Ana River 

(Young and others, 1981). This last area, which is within 

about 2,000 ft of the Loma Linda fault, has been identified 

as a localized geothermal zone, and as of 1996 is being used 

to provide geothermal energy for the city of San Bernardino 

(Cuniff and Gross, 1984).

The inorganic quality of most native ground water in 

the San Bernardino area is suitable for both agricultural and 

municipal uses (Duell and Schroeder, 1989). Concentrations 

of fluoride that exceed the public drinking-water standard, 

however, have limited the use of ground water extracted near 

some faults in the area and from some deeper parts of the 

valley-fill aquifer. Ground water with an unacceptably high 

concentration of fluoride or an elevated temperature generally 

can be blended with other ground water in order to achieve an 

acceptable quality for either agricultural or municipal use.

Agricultural and urban development have caused additional water-quality problems, primarily contamination of 

the native ground water by nitrogen species, pesticides, and 

volatile (purgeable) organic compounds. Since about 1980, 

detection of these ground-water contaminants has become 

widespread (fig. 36), and more than 40 public-supply wells 

have been closed. As more wells are contaminated and as the 

legally acceptable concentrations of contaminants are lowered 

(California Department of Water Resources, 1995a), local 

water-supply agencies have become increasingly concerned 

about the source and movement of ground-water contaminants. To ensure continued use of the valley-fill aquifer, the 

agencies have funded additional data collection, enlisted the 

aid of the state and federal governments to provide groundwater treatment facilities, and sought improved methods for 

managing ground water.

Nitrate concentrations, measured as nitrogen (NO3–N), 

have equaled or exceeded the public drinking-water standard 

of 10 mg/L in some parts of the valley-fill aquifer for much of 

the past 20 years (Duell and Schroeder, 1989, fig. 12). Closure 

of public-supply wells prompted several detailed field investigations (Eccles and Bradford, 1977; Eccles and Klein, 1978; 

Eccles, 1979; Klein and Bradford, 1979, 1980; Peter Martin, U.S. Geological Survey, written commun., 1980). Early 

investigations attempted to correlate the presence of nitrate to 

land use and the observed increase in nitrate concentrations to 

rising ground-water levels. Rising ground-water levels were 

believed to remobilize nitrogen species in the unsaturated 

zone. A followup investigation by Duell and Schroeder (1989, 

p. 1) failed to discern any consistent relation between land use 

and nitrate concentration and did not detect any areal trend 

in nitrate concentrations since 1955. As found by previous 

investigators (Eccles and Bradford, 1977, p. 25), nitrate concentration was observed to generally decrease with increasing 

depth below land surface (Duell and Schroeder, 1989, fig. 

11). For example, in the central part of the Bunker Hill basin, 

mean concentrations of nitrate as nitrogen in the upper and 

lower layers of the valley-fill aquifer were 14.0 and 3.2 mg/L, 

respectively (Duell and Schroeder, 1989, table 5).

Hydrology 59
Figure 36. Areas with poor ground-water quality in the San Bernardino area, California, 1997.

60 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Artificial-recharge basin

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Cr

River

River

Plunge

Zanja The

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Cr

Warm

Seven Oaks Dam

Areas of poor ground-water quality-Includes

USEPA (United States Environmental Protection 

Agency) superfund sites and Norton Air Force Base

IRP (Investigation and Restoration Program) site.

Mapping by Engineering Resources of Southern

California, Inc. (written commun., 1998)

Muscoy

Santa Fe 

USEPA superfund

Newmark

USEPA superfund

Norton AFB 

Redlands

IRP site

EXPLANATION

Redlands

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

Badlands

Shandin

Hills Perris Hill

Gabriel

Mts

San

Redlands

San Bernardino

15

215

10

215

15

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

San Bernardino Mountains

Crafton Hills

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

Santa

Highland Highland

Boundary of Santa Ana

River drainage basin

Fault or ground-water barrier-May be concealed

or approximately located

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

0 6 KILOMETERS

0 6 MILES
The most prevalent pesticide that contaminates ground 

water in the San Bernardino area is dibromochloropropane 

(DBCP), a soil fumigant no longer used in the area. As with 

nitrate contamination, little is known about the occurrence 

and transport of DBCP in the valley-fill aquifer. The extensive agricultural lands, particularly near Redlands, were used 

for growing citrus crops (Duell and Schroeder, 1989, p. 17). 

Application of DBCP was a routine part of citrus production 

for more than 30 years. As land was converted from agricultural to urban use, wells were converted from agricultural to 

municipal supply, and additional wells were drilled. Testing 

of ground water from many of the wells converted to municipal supply revealed the presence of contaminants, such as 

nitrate and DBCP. These contaminants may have been present 

previously, but would not have been considered a problem in 

ground water used solely for agricultural purposes.

Contamination of ground water in the San Bernardino 

area by volatile (purgeable) organic priority pollutants was 

first discovered in 1980 (Duell and Schroeder, 1989, p. 6). 

The most commonly found organic contaminants in the area 

are trichloroethylene (TCE) and tetrachloroethylene (PCE). 

As a result of this contamination, pumping from 14 municipal 

water-supply wells was discontinued as early as 1981. Since 

that time several additional wells have been closed and many 

more are threatened with closure (fig. 36). Continued groundwater-quality sampling has been done by local water purveyors, the California Regional Water Quality Control Board, the 

California Department of Health Services, the U.S. Environmental Protection Agency, Ecology and Environment, Inc. 

(1987), URS Corporation, and the U.S. Geological Survey.

As a result of the extensive data collection, two areas 

of ground-water contamination have been identified and 

designated by the U.S. Environmental Protection Agency as 

operable units (Newmark and Muscoy on fig. 36) of a federal 

superfund site. The source or sources of contamination for 

the Newmark and Muscoy operable units are not known, and 

the extent of contamination for the Muscoy operable unit has 

been identified only schematically (URS Corporation, 1994). 

A third area of ground-water contamination by volatile organic 

compounds is referred to locally as the Redlands plume (fig. 

36). In 1994, the California Regional Water Quality Control 

Board (1994) required Lockheed Corporation to begin investigations to quantify the areal extent of ground-water contamination and to design a remediation plan. A fourth area of 

significant contamination by volatile organic compounds is on 

and adjacent to Norton Air Force Base (fig. 36). Contamination in this area involves radionucleides and metals in addition 

to volatile organic contaminants. Investigations of groundwater contamination on and near Norton Air Force Base were 

begun in 1984 as part of the federal base closure program. The 

cleanup part of the base closure is referred to as the Investigation Remediation Program (IRP). As of 1996, ground-water 

monitoring was continuing and contamination by TCE and 

PCE was being cleaned up using a combination of extraction 

and injection wells (CDM Federal Programs Corporation, 

1997).

Water that is imported into the area is generally of good 

quality, but has a higher concentration of dissolved solids than 

the native ground water. The export of native ground water 

with a low concentration of dissolved solids and the use and 

reuse of imported water with a higher concentration of dissolved solids has prompted concern by local water purveyors 

that dissolved solids (salts) in ground water will increase (San 

Gorgonio Pass Water Agency, 1993). Desalting facilities have 

been installed in nearby ground-water basins in an attempt to 

reduce the increasing concentration of dissolved solids (Santa 

Ana Watershed Project Authority, 1980), and construction of a 

similar facility for the San Bernardino area has been a topic of 

ongoing discussions by local water purveyors.

Since about 1980, the increased concern about various 

types of ground-water contamination and ground-water degradation has prompted several changes in ground-water use and 

management. Some municipal wells are no longer used or no 

longer used as much because of recurring contamination problems. Commonly, water from some municipal wells must be 

blended to achieve an acceptable quality. New or refurbished 

wells often are designed to extract ground water preferentially 

from the lower hydrogeologic units in the valley-fill aquifer. 

Ground water extracted from the upper water-bearing zone 

(UWB, fig. 24) typically has a higher concentration of dissolved solids than the middle water-bearing zone (MWB), 

particularly in the vicinity of the former marshland (fig. 2). 

Concentrations of nitrate, pesticides, and volatile organic compounds also tend to be higher in the upper water-bearing zone, 

sometimes in excess of safe drinking-water standards (Duell 

and Schroeder, 1989).

Some multiple-depth well sites, such as those shown 

in figures 24 and 33, have been installed near the Newmark, 

Muscoy, and Norton Air Force Base areas of contamination. 

Ground-water-level measurements and ground-water-quality 

samples from these monitoring sites are being used to identify the source and movement of ground-water contaminants. 

Installation and monitoring of additional multiple-depth well 

sites throughout the San Bernardino area would facilitate 

extending the three-dimensional knowledge gained at the 

existing sites to the rest of the valley-fill aquifer.

Computer Models

Ground-Water Flow Model

A ground-water flow model of the valley-fill aquifer was 

developed to provide quantitative information to aid in managing water resources in the San Bernardino area. This information can be used independently or can be combined with the 

constrained optimization model, described later in this report, 

to address more comprehensive questions of water use.

Computer Models 61
62 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Figure 37. Section A–A’ showing relation between hydrogeologic units and layers of the ground-water flow model in the 

San Bernardino area, California.

62 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives San Jacinto Fault Banning Fault ? San Andreas Fault Fault L Fault K

Perris

Hill

uplift

? ?

?

? ? ? ?

?

?

?

?

?

Loma Linda Fault

?

LWB

LWB

LWB

LCM

LCM

LCM

MWB

MWB

MWB

MCM

MCM

UWB

UWB

UWB

UCM

MCM

1

1

2

2

Historical extent of 

flowing wells

 Artificialrecharge basin

?

?

?

?

?

? ?

D6

D2

D6

D7

D8

R4

R3

R2

D7

D5

D4 B2

B3

B4

10B2-4

22D2,4-7

34G4

27R_

27B1

23R2-4

T1S

14P1

T1S

T1N

T1N

R4W

R4W

0 16,000 FEET

0 4,000 METERS

A

FEET

Sea level

2,000

600

400

200

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

A'

Warm Creek

Warm Creek

Santa Ana River

Warm Creek

Highland Road

40th Street

I-15/I-110 Interchange

Mill Street

5th Street

QTc

Outside

model area

QTc ?

QTc ?

bc

bc

bc

bc

bc bc

bc

bc

bc

bc

bc

bc

Vertical scale greatly exaggerated

Section A-A' San Bernardino area.

A

Perris

Hill

San Bernardino

Shandin

Hills

A'

Loma Linda Fault

Banning (?) Fault

San Jacinto

Fault

Andreas Fault

San

Warm

Creek

Santa Ana

River

27R

27B1

22D2,4-7

23R2-4

14P1

2D6-8

10B2-4

2D6-8

Baseline Road

34G4
The ground-water flow model is a mathematical representation of ground-water flow through the valley-fill aquifer. 

In order to solve the equations that constitute the model, it is 

necessary to make simplifying assumptions about the valleyfill aquifer and the physical processes governing ground-water 

flow. The most important of these assumptions are embodied 

in the conceptual model of the valley-fill aquifer. Although the 

ground-water flow model cannot be as detailed or as complex 

as the real system, the model is useful in at least four ways: (1) 

the model integrates and assures consistency among aquifer 

properties, recharge, discharge, and ground-water levels; (2) 

the model can be used to estimate flows and aquifer characteristics for which direct measurements are not available; (3) 

the model can be used to simulate response of the valley-fill 

aquifer under hypothetical conditions; and (4) the model can 

identify sensitive areas where additional hydrologic information could improve understanding.

Conceptual Model

The conceptual model, which is the basis for the numerical ground-water flow model, is derived mostly from the 

hydrogeologic setting and hydrogeologic units described by 

Dutcher and Garrett (1963). Essentially the same conceptual 

model was used by Hardt and Hutchinson (1980) to develop a 

previous ground-water flow model of the San Bernardino area.

The unconsolidated and poorly-consolidated sediments 

filling the Bunker Hill and Lytle Creek basins compose the 

valley-fill aquifer and are considered to be the permeable part 

of the ground-water system. Igneous and metamorphic rocks 

underlying and surrounding the valley-fill aquifer are assumed 

to be impermeable (fig. 22). Sedimentary rocks that bound the 

southwestern edge of the valley-fill aquifer are assumed to be 

poorly permeable and to transmit only small amounts of water 

to the valley-fill aquifer. Part of the perimeter of the valley-fill 

aquifer is defined by faults, each with a somewhat different 

capability for transmitting ground water. The transmissive 

character of the bounding and internal faults also varies with 

depth (fig. 24).

The valley-fill aquifer is conceptualized as having two 

highly transmissive layers: an upper layer composed of hydrogeologic units UCM and UWB; and a lower layer composed 

of hydrogeologic units MCM, MWB, LCM, LWB, and QTc. 

This conceptualization of hydrogeologic units and model 

layers is shown in figure 37. Most ground-water flow in the 

upper and lower layers occurs in the UWB and MWB units, 

respectively. Flow between the two layers is restricted by 

numerous, fine-grained deposits, found mostly in the MCM 

unit, that act as a confining bed. Near the mountain front, the 

fine-grained deposits thin to extinction, and the two layers act 

as one. The transmissivity and storage coefficient of each layer 

are assumed to remain constant over time.

Figure 37.—Continued.

Computer Models 63

?

Fault – Dashed where inferred; queried where

uncertain. Arrows indicate relative movement

Well and abbreviated state well number –

Multiple numbers (D6-8) represent piezometers 

at selected depths

D6

D7

D8

2D6-8

Perforated casing

Potentiometric surface – Spring 1992

Water table

Composite hydraulic head for hydrogeologic

units beneath UWB

Underflow from model area to adjacent

permeable deposits

Ground-water movement – 

Arrow indicates general direction of groundwater flow within model area

Hydrogeologic units – Determined by lithology,

geophysical logs, and hydraulic-head measurements. Naming convention follows Dutcher and

Garrett (1963)

Upper confining member

Hydrogeologic unit Model layer

Upper

Lower

1

2

Upper water bearing

Middle confining member

Middle water bearing

Lower confining member

LWB Lower water bearing

LCM

MWB

UWB

UCM

MCM

QTc Sedimentary rocks

Contact between hydrogeologic units – Dashed

where approximately located, queried where

uncertain

EXPLANATION FOR FIGURE 37

Unconsolidated deposits – Outside model area

Bedrock basement complex of igneous and

metamorphic rocks – Excluded from the groundwater flow model because it is composed of

virtually impermeable rocks

bc
Hydrogeologic unit UCM, which is a fine-grained and 

discontinuous deposit, can create locally semi-confined or 

perched conditions near the land surface. This unit is particularly important in water management because it retains water 

at the land surface and is susceptible to liquefaction during an 

earthquake. An alternate conceptualization of the valley-fill 

aquifer could have identified UCM as a separate layer; however, this approach would have required using two layers for 

UWB because it vertically spans UCM (fig. 37). Also, threedimensional mapping of UCM is insufficient to adequately 

characterize UCM as a separate layer.

The primary source of recharge to the aquifer is runoff 

from the surrounding mountains; the primary discharge is to 

pumped wells. Important, but lesser quantities of ground water 

flow into and out of the valley-fill aquifer through some sections of the bounding faults (fig. 22). Evapotranspiration and 

ground-water discharge to Warm Creek (fig. 21) also affect 

ground-water flow when ground-water levels are near land 

surface.

The conceptual model is the basis for formulating the 

numerical ground-water flow model. Although the conceptual 

model is a simplification of the real system, additional hydrogeologic information not included in the conceptual model can 

be combined with results from the ground-water flow model 

to achieve an improved, more quantitative understanding of 

the ground-water system (fig. 3). Relations among field data, 

the conceptual model, and the numerical model are shown 

schematically in figure 38.

Relation to Previous Flow Model

The ground-water flow model documented in this report 

is a revision and an update of the ground-water flow model 

described by Hardt and Hutchinson (1980). General characteristics of the two models are compared in table 12. Both models simulate ground-water flow in essentially the same area 

surrounding the city of San Bernardino, and both models were 

designed using similar hydrogeologic concepts of how ground 

water flows through the valley-fill aquifer. Both models also 

use the same vertical discretization of the aquifer.

The primary reason for revising the previous model was 

to improve simulation of recharge and discharge. The computer code used for the previous model required that most 

recharge and discharge components be combined into a single 

dataset (Durbin, 1978). This approach made identifying or 

modifying specific recharge or discharge components difficult 

or impossible. The present model uses a modular computer 

code (McDonald and Harbaugh, 1988) specifically designed 

to overcome these limitations. Each module or package is a 

set of computer subroutines designed to calculate a separate 

part of the model. Recharge and discharge components can be 

separated into different packages and readily critiqued, modified, or updated. In addition, simulation of some recharge and 

discharge components was improved by using a more realistic 

approximation of the actual physical process. For example, a 

streamflow-routing package was used to simulate the interaction between streams and ground water (Prudic, 1989). This 

package explicitly calculates not only the quantity of water 

exchanged, but also the quantity of water remaining in each 

stream—an important feature in an area of intermittently flowing streams. Use of this package can aid in developing linked 

water budgets for both the surface-water and ground-water 

systems.

Other reasons for modifying the previous model were to 

increase spatial resolution by using a finer areal discretization, correct an inappropriate use of specific yield in the lower 

model layer, and update the model to more recent (1998) 

conditions. To improve simulation of ground-water flow near 

the numerous faults in the area, a horizontal-flow-barrier 

package was included in the revised model. This package by 

Hsieh and Freckleton (1993) does not require reductions in the 

transmissivity of selected cells in order to simulate a fault, as 

was required in the previous model. Finally, the revised model 

grid was registered to latitude and longitude in order to take 

advantage of GIS databases.

Design and Discretization

The conceptual model of ground-water flow in the valleyfill aquifer was converted into a numerical model in the following way. The aquifer is approximated by an upper, unconfined model layer and a lower, confined model layer (figs. 37

and 38). Transmissivity and storage coefficients within each 

layer are assumed to vary spatially, but not temporally. Horizontal flow within the layers is described by 

 (8)

S dh

dt ------

d

dx ------ T x

dh

dx   ------   = ddy------ T y

dh

dy   ------   W QZ + + +

where

h is hydraulic head (L);

Qz is vertical leakance (L/T);

S is storage coefficient (dimensionless);

t is time (T);

T is transmissivity (L2/T);

W is a combination of sources and sinks (L/T); and

x, y are cartesian coordinates (L).

Flow between the upper and lower model layers is assumed 

to be vertical. The rate of flow is affected by the presence of 

intervening fine-grained deposits, which reduce the vertical 

hydraulic conductivity. This linkage between the upper and 

lower model layers is described by

64 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 38. General relations among field data, conceptual model, and ground-water flow model of the San Bernardino 

area, California.

Computer Models 65

San Jacinto Fault

Banning Fault ?

San Andreas Fault

 Fault L

 Fault K ?

Loma Linda Fault

San Jacinto Fault

San Andreas Fault

?

A A'

A A'

FEET

Sea level

2,000

400

400

800

1,200

1,600

Santa Ana River

L

L

M

M

U M L

U

L

L

M

M

U

0 16,000 FEET

4,000 METERS

Vertical scale greatly exaggerated

Vertical scale greatly exaggerated

0

0 16,000 FEET

0 4,000 METERS

A A'

FEET

Sea level

2,000

400

400

800

?

1,200

1,600

Santa Ana River

P P P P P P P P

P P P P P P P P

U

AR

UG

E

AR

SR

U

RF

P

UG

LR

LR LR LR LR LR LR LR LR

RF RF RF RF RF RF RF RF

E E E E E

SR SR SR SR SR SR SR SR

Upper

Model

layer

(U)

Lower

Model

layer

(M, L)

Ground-water flow model

EXPLANATION

Silt or clay

Conceptual model

Field data

Sand or gravel

Granitic or metamorphic rock

Arrow indicates general direction of 

ground-water flow within model area

Underflow to adjacent permeable deposits

Geophysical log

Fault-Dashed where inferred; queried

where uncertain. Arrows indicate relative

movement

Ground-water movementGround-water movement-Arrow indicates 

general direction of ground-water flow 

Hydraulic characteristics

Contact between hydrogeologic unitsDashed where approximately located,

queried where uncertain

Geologic materials

Hydrogeologic units-Determined by

lithology, geophysical logs, and hydraulichead measurements. Naming convention

follows Dutcher and Garrett (1963)

Recharge and discharge

Upper (U), middle (M), or lower (L)

Fine-grained unit

Coarse-grained unit

Bedrock

Underflow

Stream recharge or discharge

Return flow of pumpage

Artificial recharge of imported water

Evapotranspiration

Pumpage

Recharge of ungaged runoff

Recharge of local runoff

Reduced conductivity across layer or fault

No flow
 (9)

Qz K z

dh

dz ------ = –

where

Kz is vertical hydraulic conductivity (L/T); and

z is a cartesian coordinate (L).

Equations 8 and 9 were solved using the modular, threedimensional, finite-difference computer code developed by 

McDonald and Harbaugh (1988). 

Use of finite-difference techniques requires discretization of the valley-fill aquifer into a geometrically simplified 

form, or model grid. The grid used for the San Bernardino area 

consists of 112 rows and 184 columns of individual cells, each 

with a uniform areal dimension of 250 m by 250 m (about 

820 ft by 820 ft). Each model cell covers about 15 acres of 

land. Only cells inside the boundaries of the valley-fill aquifer 

(fig. 22) are used in the actual simulation.

The vertical dimension of the valley-fill aquifer was 

approximated by two model layers (fig. 37), which are synonymous with the upper and lower layers of the valley-fill aquifer. 

The model layers are superimposed exactly, one on top of the 

other. Each model layer has the same origin, the same areal 

extent, the same configuration of active cells, and the same 

number of active cells (3,844). Vertical flow between the 

model layers is restricted wherever intervening fine-grained 

deposits are present. Where the fine-grained deposits are 

absent, such as near the base of the mountains, flow between 

the model layers is not restricted, and the two layers act effectively as one.

The orientation and dimension of the model grid were 

chosen so that the grid would align precisely with the Universal Transverse Mercator (UTM) coordinate system (Synder, 

1985, 1987). The UTM coordinate system is derived from a 

rectilinear projection of latitude and longitude and is displayed 

on most topographic and geologic maps. UTM measurements 

are in meters north of the equator and meters east or west of 

a base meridian, in this case 117oW. To avoid negative values, 

the base meridian is given a value of 500,000 m.

The model grid and active model cells are shown in 

figure 39. Selected coordinates of the model grid are listed 

in table 13. Transformation from one coordinate system to 

another (latitude/longitude, UTM, model) can be done using 

standard computer programs (Synder, 1985, 1987; Environmental Systems Research Institute, 1992). The model grid also 

was designed sufficiently large so that the Rialto-Colton area 

to the southwest (Woolfenden and Koczot, 2001) could be 

added readily to the present model. The model grid also can 

be extended to the east to include the Yucaipa area (fig. 37). 

Both areas are the subject of ongoing investigations, which are 

developing sufficient hydrogeologic knowledge to extend the 

simulation of ground-water flow throughout the San Bernardino, Rialto-Colton, and Yucaipa areas.

The computer code selected for the ground-water flow 

model was chosen largely because of its flexible design 

(McDonald and Harbaugh, 1988). Not only can individual 

recharge and discharge components be simulated by individual 

packages, but new packages can be added to the model code. 

The several packages that are used in the ground-water flow 

model of the San Bernardino area are described in table 14. 

Eight new packages (ART1, GHB2, LOC1, MAN1, PUM1, 

RFL1, UND1, UNG1) were developed as part of this study to 

aid in simulating specific recharge and discharge components; 

creation of these packages required only minor modifications 

of existing packages (REC1, WEL1). A new streamflow routing package was developed (STR2) from the existing package 

(STR1 by Prudic, 1989); these modifications are more complex and are documented as part of a separate study (Danskin 

and Hanson, 2003). 

Corner of 

model grid

Model coordinates Latitude Longitude UTM coordinates, zone 11 

(meters)

X (columns) Y (rows) (Decimal value in parentheses) X (east) Y (north)

Northwest 0.00 0.00 34o 15’ 55.40”

(34.265388)

117o 29’ 58.78”

(117.499662)

454,000. 3,791,500.

Northeast 184.00 0.00 34o 15’ 59.06”

(34.266407)

117o 00’ 00.00”

(117.000000)

500,000. 3,791,500.

Southwest 0.00 118.00 33o 59’ 57.62”

(33.999338)

117o 29’ 53.16”

(117.498099)

454,000. 3,762,000.

Southeast 184.00 118.00 34o 00’ 01.25”

(34.000347)

117o 00’ 00.00”

(117.000000)

500,000. 3,762,000.

Table 13. Coordinates of the ground-water flow model of the San Bernardino area, California.

[Model grid is aligned with the Universal Transverse Mercator (UTM) coordinate system; coordinates below are calculated at the outside edge of the model grid 

using the North American Datum of 1927; each model cell is 250 meters by 250 meters]

66 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 39. Location, orientation, and boundary conditions of the ground-water flow model of the San Bernardino area, California.

Computer Models 67

3

0

10

20

30

40

50

ROWSROWS

COLUMNS

COLUMNS

60

70

80

90

100

110

10

0

20

30

40

50

60

70

80

90

100

110

10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170

3 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170

BASIN

CHINO

RIALTO - COLTON

BASIN

YUCAIPA BASIN

Generalized direction of ground-water flow

within the valley-fill aquifer

Artificial-recharge basin

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Cajon

Creek

River

River

Cr

Plunge

Warm

Santa

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Seven Oaks Dam

San Bernardino Mountains

Crafton Hills

Mts

San

San Bernardino San Bernardino

0 6 KILOMETERS

0 6 MILES

EXPLANATION

Single cell of the ground-water flow modelModel finite-difference grid is registered to latitude

and longitude (table 10)

Former marshland

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

CREEK

LYTLE

BASIN

Gabriel

Shandin

Hills

Perris Hill

Badlands

BASIN

BUNKER

HILL

Boundary of the valley-fill aquifer-Bunker Hill and

Lytle Creek ground-water basins shaded in darker gray. 

Solid line indicates no underflow. Dashed line indicates

area of minor underflow; arrows indicate area with more

than 1,000 acre-feet per year of underflow and point in

the direction of ground-water flow to or from adjacent

permeable materials

Fault or ground-water barrier-May be concealed or

approximately located.
Computer program (package) Function Reference

Basic code

Primary computer code Setup and solve equations simulating a basic 

ground-water flow problem.

McDonald and Harbaugh (1988).

Preconditioned conjugate gradient solver 

(PCG2)

Improved solution of ground-water flow 

equations; requires convergence of heads 

and (or) flowrates.

Hill (1990).

Aquifer parameters

Horizontal flow barrier package (HFB1) More localized simulation of faults so that 

model transmissivity values are not affected by simulation of faults.

Hsieh and Freckleton (1993).

Recharge and discharge

Precipitation recharge package (REC1) Simulates distributed recharge from precipitation to the uppermost model layer.McDonald and Harbaugh (1988).

Local recharge package (LOC1) Simulates distributed recharge from local 

runoff in the same manner as the original 

recharge package (REC1).

Minor modification of McDonald and Harbaugh (1988).

Artificial recharge of imported water (ART1) Simulates specified recharge or discharge in 

the same manner as the original well package (WEL1).

Minor modification of McDonald and Harbaugh (1988).

Pumpage package (PUM1) ditto ditto

Return flow package (RFL1) ditto ditto

Underflow package (UND1) ditto ditto

Ungaged recharge package (UNG1) ditto ditto

Management package (MAN1) Simulates additional recharge or pumpage 

for water-management scenarios in the 

same manner as the original well package 

(WEL1).

Minor modification of McDonald and Harbaugh (1988).

Well package (WEL1) Simulates additional recharge or pumpage 

for constrained optimization scenarios.

McDonald and Harbaugh (1988).

Evaporation package (EVT1) Simulates head-dependent evaporation from 

the upper layer of the ground-water flow 

model.

McDonald and Harbaugh (1988).

General head package (GHB2) Simulates head-dependent underflow beneath 

the Santa Ana River based on a nonlinear 

regression equation and calculated head at 

the Heap well (1S/4W–3Q1).

Minor modification of McDonald and Harbaugh (1988).

Streamflow-routing package (STR2) Improved simulation of surface-water and 

ground-water interaction; routes and massbalances streamflow.

Original streamflow routing package by Prudic (1989) was modified by Danskin and 

Hanson (2003) to allow for different types 

of diversions.

Table 14. Computer programs (packages) used with the ground-water flow model of the San Bernardino area, California.

68 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Several additional packages have been created that offer 

powerful simulation capabilities, including the transient 

release of water from storage (TLK1) (Leake and others, 

1994); permanent loss of storage and compaction of the aquifer (ISB1 and CHD1) (Leake and Prudic, 1988); and rewetting 

of a dewatered model cell (BCF2) (McDonald and others, 

1991). Although powerful and potentially applicable to the 

San Bernardino area, these packages generally require threedimensional data not available for the permeable hydrogeologic units or create hydraulic non-linearities that cause major 

difficulties in use of the constrained optimization model. As 

additional hydrogeologic data become available, the present 

model could be modified to include one or more of these packages. Adding new capabilities to the present model is aided 

by the model’s modular design and facilitates an evolutionary 

modeling process.

Aquifer Parameters

Simulation of the upper and lower model layers requires 

defining a transmissivity and storage coefficient for each 

active model cell in each model layer. Commonly, these values 

are derived from aquifer tests and from concepts about the 

depositional history of the aquifer materials (Hollett and others, 1991).

In the San Bernardino area, aquifer-test data are limited; 

as a result, the California Department of Water Resources 

(1971, p. 64–69, 85–98) used more than 1,000 driller’s logs to 

estimate values of transmissivity and storage coefficient. The 

procedure was as follows. Initial transmissivity values were 

calculated from specific-capacity tests, divided by the total 

length of perforations as indicated on the driller’s log of that 

well, and then multiplied by an estimate of the entire saturated thickness of the aquifer in that area. These initial values 

were contoured and used to select values for the mathematical, ground-water flow model of the area developed by the 

California Department of Water Resources (1971). The initial 

transmissivity values were modified later during calibration of 

that model. Specific-yield values were calculated from driller’s 

logs using defined values for each type of aquifer material 

found in the driller’s description, for example 0.03 for clay 

and 0.35 for medium sand. Average specific-yield values were 

calculated only for that part of the well log that was variably 

saturated during water years 1935–60. As in the calculation 

of transmissivity, the initial specific-yield values were used to 

select model values of specific yield, which subsequently were 

modified during calibration. The final specific-yield values 

ranged from 0.048 to 0.35 with a mean of 0.13 (California 

Department of Water Resources, 1971, table 7).

Values of transmissivity and storage coefficient developed by the California Department of Water Resources (1971) 

were used by Hardt and Hutchinson (1980) in developing their 

ground-water flow model. Transmissivity values were divided 

between the upper and lower model layers. Values of storage 

coefficient for the confined lower aquifer were estimated from 

aquifer tests in the San Bernardino area and in other areas 

with similar sediments. Calibration of the ground-water flow 

model by Hardt and Hutchinson (1980, p. 15) resulted in some 

modification of the initial values of both transmissivity and 

storage coefficient.

Development of the present ground-water flow model 

used the final values of transmissivity from Hardt and 

Hutchinson (1980, p. 72–80). Values for each layer of the new 

model grid were obtained by interpolating the previous values 

using an inverse distance-squared weighting. Because design 

of the Hardt and Hutchinson (1980) model required using a 

reduced value of transmissivity to simulate the effect of a fault, 

these reduced values were not used in the interpolation. Other 

methods of interpolation including kriging were tested, but 

these produced minimal change in the values. Use of original values of transmissivity obtained from aquifer tests and 

calculated by the California Department of Water Resources 

(1971) from driller’s logs may have been preferable in revising 

the present model, but most of these values were no longer 

available.

Values of storage coefficient for the upper and lower 

model layers were changed substantially from those used by 

Hardt and Hutchinson (1980, p. 72–80). The changes were 

required for two reasons. First, the storage coefficient of some 

cells in the lower model layer of Hardt and Hutchinson (1980) 

inappropriately reflects unconfined conditions. A review of 

historical ground-water levels failed to identify any periods 

when unsaturated conditions were present at the top of both 

the upper and lower layers. In the San Bernardino area with 

the present model formulation, only the upper model layer 

should have an unconfined value of storage (specific yield). 

The lower layer, even if it directly underlies an unconfined 

body of water, should have a storage coefficient based only 

on expansion of water and compression of aquifer material, 

not on actual dewatering of the aquifer. Second, the storage 

coefficient of some cells in the upper model layer of Hardt and 

Hutchinson (1980) reflects confined conditions. The fluctuations in ground-water levels during 1945–98 in the area of the 

former marshland indicates that the upper model layer was 

actually dewatering, not simply depressurizing, as the confined 

storage coefficients of Hardt and Hutchinson (1980) would 

indicate.

The upper model layer, conceptualized as unconfined, 

was assigned specific-yield values from Eckis (1934, map E). 

Eckis’ map E shows contours of specific yield for a uniform 

thickness of the aquifer, 50 ft above and 50 ft below the water 

table in 1933. The specific-yield contours were digitized, rasterized, and gridded using ARCINFO software (Environmental 

Systems Research Institute, 1992) in order to calculate a specific-yield value for each model cell. Some small areas of the 

model were outside the original contours by Eckis. For these 

areas, which included most of the former marshland, depositional concepts were used to extend the original contours. 

Computer Models 69
The lower model layer, conceptualized as confined or not 

physically dewatered, was defined as having a storage coefficient of 0.0001, a value typical of a 500- to 700-ft thickness of 

unconsolidated sediment (Driscoll, 1986, p. 210). Distribution 

of storage coefficients that vary within the lower model layer 

would require three-dimensional data on thickness and specific 

storage for hydrogeologic units MCM, MWB, and LCM, and 

possibly LWB (fig. 37). As of 1998, these data were not available except for selected parts of the San Bernardino area.

Two model layers in a quasi-three-dimensional simulation, such as in the previous model by Hardt and Hutchinson 

(1980) and in this revised model (eqs. 8 and 9), are connected 

hydraulically by a leakance coefficient or vertical conductance. Leakance coefficients from Hardt and Hutchinson 

(1980, p. 72–80) were interpolated in the same way as the 

transmissivity values in order to develop vertical-conductance 

values for the new model cells. The original leakance coefficients were derived largely by trial-and-error during calibration (Hardt and Hutchinson, 1980, p. 17, 45). The assumptions 

and appropriate application of vertical conductance (leakance 

coefficient) are described in detail by McDonald and Harbaugh (1988, p. 2–29 to 2–35).

The restriction in ground-water flow caused by the several faults and barriers in the area (fig. 5) was simulated by the 

horizontal-flow-barrier (HFB) package of Hsieh and Freckleton (1993). This package calculates flow across a horizontal 

barrier, such as a fault, using a horizontal conductance term 

that applies to only one side of a model cell. Other methods, 

such as used by Hardt and Hutchinson (1980), require reducing the transmissivity of an entire model cell to simulate the 

effect of a fault or barrier. Use of the HFB package results 

in a more accurate simulation of ground-water levels near 

faults and barriers. This improvement is especially apparent 

in model cells with significant recharge or discharge, such as 

from streams or pumped wells. Reduced values of transmissivity used by Hardt and Hutchinson (1980, p. 72–80) to simulate 

faults and barriers were used directly as values of horizontal 

conductance for the HFB package. Locations of the faults 

were taken from recent mapping by Matti and Carson (1991, 

pl. 1), and locations of barriers were taken from Dutcher and 

Garrett (1963, p. 1).

Transmissivity for both model layers, vertical conductance between layers, and specific yield for the upper layer 

are illustrated in figure 40. In general, the highest values of 

transmissivity in both layers are near the center of the Bunker 

Hill basin and along the stream channels of Lytle Creek, East 

Twin Creek, and the Santa Ana River (fig. 11). In these areas, 

the geologic structure and depositional history of the basin 

have combined to produce deposits that are thick, coarse, and 

well-sorted.

Reduced values of transmissivity are present in the lower 

model layer between the San Jacinto and Loma Linda faults 

where the more permeable valley-fill deposits are thinner 

(fig. 37). Vertical ground-water flow is impeded only where 

vertical conductance is less than about 0.01 per day-1 (fig. 40). 

The area of impediment is the confined area identified by 

Hardt and Hutchinson (1980, fig. 3) and is the approximate 

area of flowing wells identified by Mendenhall (1905, pl. 8) 

and shown in figures 9 and 37. 

In other areas of the Bunker Hill and Lytle Creek basins, 

such as near the base of the San Bernardino and San Gabriel 

Mountains, vertical-conductance values are sufficiently high 

(greater than 0.01 per day-1) that vertical flow is unrestricted. 

In these areas, measured ground-water levels for both the 

upper and lower aquifer layers are nearly the same, as are 

simulated hydraulic heads for the upper and lower model layers. Values for specific yield range from less than 0.05 near 

the former marshland, to greater than 0.15 in the middle of the 

Bunker Hill basin. Compared to the specific-yield values used 

by Hardt and Hutchinson (1980, fig. 10), the present values 

along the mountain front are generally lower and the present 

values in the former marshland are generally higher.

Recharge and Discharge

Most recharge and discharge components in the groundwater flow model were changed in some way from the 

previous work by Hardt and Hutchinson (1980). In so far as 

possible, each physical type of recharge or discharge, such as 

recharge from gaged runoff or discharge from wells, is simulated with a discrete model package. In this way, recharge and 

discharge processes can be simulated more realistically, and 

the values can be updated as new information is obtained or as 

human actions alter hydrologic characteristics of the streams, 

wells, or valley-fill aquifer. The various recharge and discharge components included in the ground-water flow model 

are summarized in table 12. A more complete description of 

each component along with measured and estimated values 

can be found in the section of this report entitled “Hydrology.” A generalized ground-water budget of average values 

for 1945–98 is listed in table 11, and a piechart of the values 

is shown in figure 33. Also listed in table 11 are the maximum 

and minimum annual values for comparision.

The following discussion describes only the numerical 

approximations necessary to represent the physical processes 

and related values in the model. Simulation of some recharge 

and discharge components included modifications to standard computer packages by McDonald and Harbaugh (1988); 

these changes are summarized in table 14. Simulated annual 

recharge and discharge values for 1945–98 are listed in

table 15.

70 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 40. Areal distribution of calibrated hydraulic parameters of the ground-water flow model of the San Bernardino area, 

California: A, transmissivity of the upper model layer; B, transmissivity of the lower model layer; C, specific yield of the upper model 

layer; D, vertical conductance between model layers; E, hydraulic characteristic of faults in the upper model layer; and F, hydraulic 

characteristic of faults in the lower model layer. Storage coefficient for the lower model layer equals 0.0001.

Computer Models 71

0 6 KILOMETERS

0 6 MILES

0 6 KILOMETERS

0 6 MILES

0 6 KILOMETERS

0 6 MILES

0 6 KILOMETERS

0 6 MILES

0 6 KILOMETERS

0 6 MILES

0 6 KILOMETERS

0 6 MILES

A B

Units-Transmissivity in feet squared per day;

vertical conductance in per day; specific

yield is dimensionless; hydraulic characteristic

of faults in feet per day

Basin boundary-For Bunker Hill and Lytle Creek

ground-water basins

EXPLANATION

> 20,000

5,000-20,000

1,000-5,000

< 1,000

> 20,000

5,000-20,000

1,000-5,000

< 1,000

C

B

C

> 0.15

0.10-0.15

0.05-0.10

< 0.05

E F

D

> 0.01

0.001-0.01

< 0.001

< 5

5-15

> 15

< 5

5-15
Direct recharge of precipitation.—The standard recharge 

package (RCH1) by McDonald and Harbaugh (1988, p. 7–1) 

was used to simulate recharge that results from infiltration of 

direct precipitation on the unconsolidated deposits of the San 

Bernardino area. Although the quantity is undoubtedly small 

because of the semiarid climate, some infiltration to the water 

table probably occurs during extremely wet periods

(fig. 18). The significant depth to ground water, especially near 

the base of the mountains (fig. 37), suggests that most recharge 

migrates slowly through the unsaturated zone, possibly taking 

years to reach the water table. In areas near the former marshland, infiltrated precipitation probably arrives sooner, but still 

essentially at a constant rate. 

To simulate this small quantity of recharge from precipitation, the map of average precipitation throughout the San 

Bernardino area (fig. 6) was used to develop a model input 

array. Precipitation contours in figure 6 were digitized, rasterized, and gridded using ARCINFO software (Environmental 

Systems Research Institute, 1992) in order to calculate a 

recharge value for each model cell in layer 1. This array of values was scaled to total 1,137 acre-ft/yr, the quantity of direct 

recharge estimated to occur from precipitation for 1945–98 

(fig. 18; p. 40). This technique for developing a model array 

from contoured data is the same as that used to develop a 

specific-yield array (p. 69). These assumptions and method 

of simulating direct recharge of precipitation are comparable 

to methods used successfully in other semiarid ground-water 

basins (Yates, 1988, p. 14; Bright and others, 1997, p. 41; 

Danskin, 1998).

Recharge and discharge of gaged streamflow.—The 

streamflow-routing package of Prudic (1989) with modifications by Danskin and Hanson (2003) was used to simulate 

interaction between the major streams (fig. 2) and the valleyfill aquifer. Annual discharge at the mountain-front gage 

(fig. 11; table 1) was used as inflow to each stream. Streamflow was routed down the stream channels, through the 

artificial-recharge basins, and past the outflow gages near the 

San Jacinto fault (fig. 41). Interaction between the stream and 

the valley-fill aquifer was simulated with a Darcian relation 

that calculates flow to or from the aquifer based on head in the 

aquifer, head in the stream, and conductance of the streambed 

(Prudic, 1989, p. 7). 

Five different types of streambeds were simulated in the 

streamflow-routing model (table 16). Two types represent 

natural stream channels with earthen bottoms: one for wide 

streams (Santa Ana River, Lytle Creek, and Mill Creek) and 

one for narrow streams (Cajon Creek, Cable Creek, East Twin 

Creek, Warm Creek, City Creek, Plunge Creek, and Zanja). A 

third type represents artificial-recharge basins, where streamflow generally is wider than in the natural channel and is 

routed through the basin in a serpentine fashion to maximize 

recharge. A fourth type represents concrete-lined channels or 

pipes that have minimal leakage. The fifth type represents a 

logical connection that has no real length or recharge, but is 

necessary for routing.

 Conductance for each type of streambed was calculated 

based on the average wetted width of the stream and on the 

estimated vertical hydraulic conductivity and thickness of the 

streambed deposits. The average wetted width of each stream, 

even the three largest streams (fig. 12), is less than the width 

of a single model cell (about 820 ft). Under most conditions 

and in most years, the wetted width remains relatively constant 

and the stream stage varies with discharge. However, during unusually wet years with major floods such as occurred 

in 1969 and 1998 (fig. 14), flow overtops the main stream 

channel and covers a much larger width of the entire braided 

stream channel. This condition is most apparent for the Santa 

Ana River, Lytle Creek, and Mill Creek. The maximum wetted 

width of these streams is indicated by the width of the riverchannel deposits shown in figure 5. 

Type of streambed

Simulated streambed conductance for 

different types of runoff years 

(feet per second)

Percentage increase in 

simulated streambed 

conductance from dry or 

normal year to unusually 

wet runoff year

Comment

Dry or 

normal year

Unusually 

wet year

Natural channel, wide 0.075 0.375 500 Includes Santa Ana River, Mill 

Creek, and Lytle Creek.

Natural channel, narrow 0.05 0.15 300 All other streams.

Spreading basin 0.15 0.3 200 Artificial-recharge basin.

Concrete 0.00005 0.00005 100 Concrete-lined channel, or pipe.

Logical 0.000001 0.000001 100 No length, only a logical 

connection.

Table 16. Simulated streambed characteristics in the San Bernardino area, California.

[Unusually wet runoff years are 1958, 1969, 1978, 1979, 1980, 1983, 1993, and 1998]

72 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 41. Major surface-water features in the San Bernardino area, California.

Computer Models 73

Seven Oaks Dam, April 1999. Photo courtesy of David

Lovell, San Bernardino County.

A

E

F

Santa Ana River, January 2005.

C

D

Ungaged mountain-front runoff, January 2005.

Warm Creek natural channel, September 2004.

Warm Creek bypass channel, September 2004.

Santa Ana River artificial-recharge basins, May 1930.

Photo courtesy of San Bernardino Valley Water

Conservation District.

B
Also during wet years, increased streamflow remobilizes and removes fine-grained materials that previously were 

deposited on the streambed. This removal increases vertical 

hydraulic conductivity, and hence streambed conductance. 

This mechanism likely accounts for the dramatic increase in 

streambed conductance for large streams (500 percent), compared to narrow streams (300 percent) and spreading basins 

(200 percent) (table 16).

The version of the streamflow-routing package (STR2) 

used for this report does not have the capability of simulating an increased wetted perimeter involving additional model 

cells. Therefore, any additional recharge that occurs as a 

result of unusually large runoff and the concurrent increase in 

stream width needs to be simulated as an increase in streambed conductance (table 16). Perhaps because the ground-water 

model simulates annual recharge and discharge, this limitation 

does not appear to be significant in this present study. For a 

situation where simulated effects close to the major streams 

are important, especially after wet years with abundant runoff, 

then the lack of increasing stream width by adding more 

model cells may be a significant limitation.

Recorded discharge at the outflow gages (table 1) was 

used in combination with estimates of local runoff (table 4), 

measured wastewater discharge near the outflow gages 

(table 7), and the estimated quantity of rising ground water 

(fig. 30; table 8) to evaluate the performance of the streamflow 

package. Simulated values of recharge from gaged mountainfront runoff for 1945–98 are listed in table 15. Also listed is 

simulated discharge to the gaged streams, also referred to as 

rising ground water.

During development of the ground-water flow model, a 

much more complex version of simulating the surface-water 

system was tested using the revised streamflow-routing package (STR2). Essentially all surface water in the San Bernardino area (pl. 1), both gaged and ungaged, in streams and 

in pipes, was routed as shown on plate 2. Four different types 

of surface-water diversions were simulated using STR2. The 

more complex routing of surface water worked well, but the 

ground-water flow model became numerically unstable during 

periods of low runoff. As a result, this version of streamflow 

routing was not used in the final ground-water flow model. If 

the numerical instability can be resolved, the more complex 

surface-water routing package would be an important enhancement to the present model.

Recharge of ungaged runoff.—Ungaged runoff from 

the surrounding mountains and from the few, small bedrock 

outcrops within the San Bernardino area was estimated using 

average precipitation (fig. 6), drainage areas, an effective 

percentage of runoff (table 3), and the annual runoff index for 

the Santa Ana River (table 2). Because virtually all ungaged 

runoff was assumed to recharge the valley-fill aquifer, annual 

values of ungaged recharge equal the estimated average 

ungaged runoff multiplied by the annual runoff index for the 

Santa Ana River (refer eq. 1). These annual values were used 

directly in the ground-water flow model.

Recharge from ungaged runoff was simulated in the 

ground-water flow model as an annual specified flux using 

a modified version (UNG1) of the standard well package 

(WEL1) by McDonald and Harbaugh (1988, p. 8–1). The only 

modifications to the WEL1 package were changes in variable 

names in order to prevent conflicts in referencing. The total 

quantity of recharge for each area shown in figure 17 was distributed evenly in model cells along the perimeter of the model 

boundary that coincides with the boundary of the ungaged area 

(figs. 17 and 39). Annual values of recharge from ungaged 

runoff for 1945–98 are listed in table 15.

Recharge of imported water.—Surface water imported 

into the San Bernardino area can be recharged in several 

artificial-recharge basins located near the head of alluvial fans 

(fig. 11; table 5). Some of the imported water may evaporate 

or may be transpired by native vegetation in the artificialrecharge basins; however, nearly all (90 percent) is assumed to 

recharge the valley-fill aquifer.

Recharge from imported water is simulated in the 

ground-water flow model as an annual specified flux using 

a modified version (ART1) of the standard well package 

(WEL1) by McDonald and Harbaugh (1988, p. 8-1). The only 

modifications to the WEL1 package were changes in variable names in order to prevent conflicts in referencing. Data 

requirements include: the measured quantity of imported water 

for each basin (table 5); the area of recharge within each basin, 

which was identified from topographic maps and aerial photographs; and the percentage of imported water in each basin 

that actually recharges the valley-fill aquifer. Annual values of 

recharge of imported water for 1945–98 are listed in table 15.

Gross pumpage and return flow.—Pumpage from wells is 

the major component of discharge from the valley-fill aquifer 

(table 11). Most of this pumped water is used consumptively; 

a lesser quantity returns as recharge (return flow) to the upper 

layer of the valley-fill aquifer (fig. 25).

Values of gross pumpage and return flow for individual 

wells were developed from data from the local watermaster 

(Western−San Bernardino Watermaster, 2000). A pre-processing program used these data and characteristics about each 

well to calculate the quantity of gross pumpage from each 

model layer and the quantity of pumpage returned as recharge 

to the upper model layer. These calculations are described in 

greater detail in the section of this report entitled “Pumpage.” 

Annual values of gross pumpage and return flow for 1945–98 

are listed in table 15.

74 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Gross pumpage and return flow are simulated using separate, but virtually identical model packages. The rationale for 

this accounting practice is that each quantity (gross pumpage 

from layer 1, gross pumpage from layer 2, and return flow to 

layer 1) is kept separate and can be compared and analyzed 

individually. A common practice in previous hydrologic studies is to analyze and report net pumpage, defined as gross 

pumpage minus return flow. Caution is warranted, therefore, 

when comparing pumpage values from this report with those 

in prior reports to ensure that both are either gross or net, not a 

mixture of the two.

Gross pumpage is simulated in the model using a modified version (PUM1) of the standard well package (WEL1) by 

McDonald and Harbaugh (1988, p. 8–1). The only modifications to the WEL1 package were changes in variable names 

in order to prevent conflicts in referencing. Return flow also 

is simulated using a modified version (RFLl) of the standard 

well package (WEL1) by McDonald and Harbaugh (1988, p. 

8–1). Similarly, the only modifications to the WEL1 package 

were changes in variable names in order to prevent conflicts in 

referencing.

Evapotranspiration.—Evapotranspiration is assumed to 

occur from the valley-fill aquifer whenever the water table is 

sufficiently close to land surface. Field studies in similar environments have identified this distance to be about 15 ft or less, 

depending on the type of vegetation and soil characteristics 

(Lee, 1912; Robinson, 1958; Sorenson and others, 1991; Danskin, 1998). A maximum evapotranspiration rate is reached 

when the water table is at land surface.

These conditions for evapotranspiration were simulated 

using the standard evapotranspiration package (EVT1) by 

McDonald and Harbaugh (1988, p. 10–1). In this package, a 

depth-dependent relation is used to calculate the quantity of 

evapotranspiration from the upper layer of the ground-water 

flow model. The relation assumes that at land surface, the 

evapotranspiration rate is a maximum; at a specified depth 

below land surface (extinction depth), the evapotranspiration 

rate is zero; in between, the evapotranspiration rate decreases 

linearly from the maximum to zero. 

Because no spatial data were available for the type of 

vegetation or soil characteristics, a maximum evapotranspiration rate of 38 in/yr and an extinction depth of 15 ft were 

used uniformly for the entire model area. These are the same 

values used by Hardt and Hutchinson (1980), who used the 

same depth-dependent relation to simulate evapotranspiration. 

In the previous modeling study, however, the evapotranspiration relation was used to simulate both evapotranspiration 

and discharge of ground water into Warm Creek. As a result, 

the simulated evapotranspiration values reported by Hardt 

and Hutchinson (1980, table 3) are generally higher than 

those simulated by the revised ground-water flow model and 

reported in table 15.

Underflow.—Underflow occurs across several sections 

of the boundary of the ground-water flow model (fig. 39). In 

these sections, underflow is mostly through the unconsolidated 

deposits with a much lesser quantity through the sedimentary 

rocks of the badlands. Detailed analysis of the underflow 

across each section resulted in estimated annual values for 

1945–98 (table 9); these values were used directly in the 

ground-water flow model. The only exception to this is underflow across the San Jacinto fault near Barrier J. A constant 

value of 2,000 acre-ft/yr ultimately was used for this section 

because the values in table 9 produced a poor match between 

simulated hydraulic heads and measured ground-water levels 

in nearby wells. Additional description of underflow near Barrier J is in the section “Underflow” on page 45.

Underflow recharge and discharge were simulated in the 

ground-water flow model as annual specified fluxes using 

a modified version (UND1) of the standard well package 

(WEL1) by McDonald and Harbaugh (1988, p. 8–1). The only 

modifications to the WEL1 package were changes in variable 

names in order to prevent conflicts in referencing. Annual values of underflow for 1945–98 were summed as either recharge 

or discharge and are listed in table 15.

For simulation after 1998, or for any hypothetical simulation, underflow across the San Jacinto fault near the Santa Ana 

River used a minor modification to the head-dependent relation illustrated in figure 28 and described in equation 5. Simulated head in the model cell containing the Heap well (1S/4W–

3Q1) was used instead of measured ground-water level for 

that well. This change ensures that the simulated underflow 

responds appropriately to variations in recharge and discharge 

that are different from those that actually occurred during 

1945–98. This head-dependent relation was simulated in the 

ground-water flow model using a modified version (GHB2) 

of the standard general head boundary package (GHB1) by 

McDonald and Harbaugh (1988, p. 8–1). The only modifications to the GHB1 package were changing the standard linear 

equation for calculating underflow to the non-linear equation 

QUnderflow

SAR, k = 96.876 log (hHeap, k) + 663.136 (10)

where

QUnderflow

SAR, k

is underflow across the San Jacinto fault near 

the Santa Ana River for time period k, in 

acre-ft/yr; and 

hHeap, k is simulated hydraulic head for the model cell 

containing the Heap well (row 70, column 

79, layer 1) for time period k, in ft above 

mean sea level.

For use in the GHB2, the units in equation 10 were 

converted to ft and seconds. The value of hHeap, k was calculated 

for the same timestep as QUnderflow

SAR, k. Although the value of 

QUnderflow

SAR, k changes more rapidly than it would if a linear 

head-dependent relation were used in the standard GHB1 

package, no numerical problems were encountered in use of 

the modified GHB2 package. 

Computer Models 75
Calibration

Calibration of the ground-water flow model involved 

simulating a historical period (calendar years 1945–98) and 

assuring that the simulated hydraulic heads, recharge, and discharge reasonably matched the measured and estimated data. 

Steady-state conditions were assumed and simulated for 1945. 

During this year, ground-water levels in most parts of the valley-fill aquifer remained virtually constant and ground-water 

recharge and discharge were approximately equal. Simulating 

steady-state conditions for 1945 also assured that the transient 

simulation of 1945–98 began with stable initial conditions, an 

important numerical consideration. During the transient simulation, recharge and discharge were simulated using annual 

values, and hydraulic head was calculated at the end of each 

year for each active model cell in each model layer. 

Model solutions were obtained using the preconditioned 

conjugate-gradient solver (PCG2) by Hill (1990). One hundred 

timesteps were used for each 1-year stress period; a time-step 

multiplier of 1.2 was used to improve accuracy of the solution. 

Convergence criteria for both steady-state and transient conditions were 0.01 ft and 0.01 ft3

/s for head and flux, respectively. 

The residual mass balance error typically was less than or 

equal to 0.01 percent and always was less than 0.03 percent. 

During model development and use, some combinations of 

recharge and discharge resulted in convergence failure such 

as that described by Kuniansky and Danskin (2003). These 

failures typically occurred during simulation of a drought, but 

occasionally occurred from very small changes in recharge or 

discharge.

Calibration involved a trial-and-error adjustment of 

model parameters. Simulated hydraulic heads were compared 

to measured ground-water levels for about 100 wells in the 

San Bernardino area. Of equal importance, individual recharge 

and discharge components that are calculated by the groundwater flow model were compared to estimated and measured 

recharge and discharge. Model calculations of ground-water 

flow from one model cell to another (cell-by-cell fluxes, 

McDonald and Harbaugh, 1988, p. 3–19) were used to evaluate the spatial distribution of recharge and discharge.

Only a limited amount of calibration was necessary, probably because a previous ground-water flow model (Hardt and 

Hutchinson, 1980) had been calibrated for transient conditions in nearly the same area (table 12). Some model parameters, including components of recharge and discharge, were 

unchanged from initial estimates, or changed very little. A few 

model parameters, such as transmissivity and conductance 

across faults, were essentially the same as those used in the 

previous model by Hardt and Hutchinson (1980). The model 

parameters and the relative amount of adjustment during calibration are summarized in table 17. 

The philosophy of model calibration, particularly when 

using a trial-and-error technique, plays a critical role in 

determining the final form of a numerical model. For example, 

the previous model by Hardt and Hutchinson (1980) was 

calibrated with the goal of matching ground-water levels 

near the former marshland; matching ground-water levels 

near the mountain front was of lesser importance (Hardt and 

Hutchinson, 1980, p. 47). During calibration of the present 

ground-water flow model, all simulated areas were weighted 

about equally, and calibration was guided most by the regional 

nature of the conceptual model. Matching ground-water levels 

at each individual well was desirable, but not mandatory. 

Of greater importance was simulating each distinct 

recharge and discharge process and maintaining a relatively 

simple model with as few parameters as possible—essentially the philosophy of Albert Einstein who said, “A model 

should be as simple as possible, but no simpler.” By following this philosophy, the effect of each model parameter on 

model results can be understood more readily. This philosophy prompted some parameters to be grouped together. For 

example, a single value of conductance was chosen for all 

narrow streams (table 16). This value was changed as necessary during calibration, for all narrow streams. Adjustment 

of individual parameters for individual model cells was done 

rarely, if ever.

Results of the calibration are shown in figures 42, 43, 44, 

and 45. Figure 42 shows the match between measured groundwater levels and simulated hydraulic heads for 1945—the 

period used for the steady-state simulation, which, in turn, 

was used as initial conditions for the transient simulation of 

1945–98. The match between steady-state levels and heads 

is reasonably good over most of the San Bernardino area 

and indicates that the model can be used to simulate regional 

ground-water flow in the Bunker Hill basin. Ground-water 

flow through the Lytle Creek basin is simulated less reliably, 

probably because of the numerous internal faults and groundwater barriers in that basin. Although the model does transport 

ground water through the Lytle Creek basin and calculates reasonable heads immediately downgradient of the basin, results 

of the model within the Lytle Creek basin itself should be used 

with caution.

The match between levels and heads during the transient 

simulation is shown in figure 43 for selected wells scattered 

throughout the San Bernardino area. The wells were chosen to 

be areally distributed and to give an indication of the relative 

quality of the calibration. This relative quality (good, fair, or 

poor) was determined qualitatively for the 62 wells used in the 

model calibration and is shown on a map inset in figure 43. 

The most important criteria for the hydrograph match were 

having a symmetrical pattern of deflections, maintaining a 

uniform vertical offset, if any, and having a similar magnitude 

of multiple-year vertical deflections. The model appears to 

simulate ground-water levels best in the middle of the Bunker 

Hill basin. At some wells, the hydrograph match is remarkably 

good over the entire 54-year transient simulation and probably reflects accurate recharge and pumpage data more than a 

conscious effort at site-specific calibration. The quality of the 

match along the model boundaries is fair to poor, a characteristic common to many regional ground-water flow models.

76 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Model parameter, 

recharge, 

or discharge

Source

Relative adjustment 

during 

model calibration

Simulated area Hardt and Hutchinson (1980). Minor; model area extended to match bedrock 

boundaries.

Transmissivity Hardt and Hutchinson (1980). Minor; values required for new model area.

Storage Eckis (1934). Moderate; values from Eckis (1934) are generally 

lower than those used by Hardt and Hutchinson 

(1980).

Conductance (horizontal hydraulic 

conductivity) of faults

Hardt and Hutchinson (1980). None.

Recharge from precipitation Estimates based on values from Hardt and 

Hutchinson (1980) and Danskin (1998) 

and on an isohyetal map of long-term 

average precipitation (this study).

Minor; switched from uniform precipition to 

areally distributed values.

Streamflow Gaged values of runoff. Substantial re-evaluation of the quantity and timing of runoff; adjusted streambed conductance 

(vertical hydraulic conductivity) based on 

quantity of runoff.

Recharge from ungaged runoff Estimated values using drainage areas and 

runoff quantities from Webb and Hanson 

(1972) and recharge rates from this study.

Minor adjustment to recharge rates.

Recharge of local runoff Values from estimating individual components of annual precipitation (evaporation, 

direct recharge, local runoff, recharge from 

local runoff).

Minor; not included initially, but no adjustment 

after values were added to model.

Recharge of imported water Quantity of imported water (Randy Van 

Gelder, San Bernardino Valley Municipal 

Water District, unpub. data, 1999) and 

estimated recharge rates (this study).

Minor adjustment to some recharge rates.

Pumpage Western–San Bernardino Watermaster (S.E. 

Mains, Western Water District, and R.L. 

Reiter, San Bernardino Valley Municipal 

Water District, unpub. data, 2000).

Moderate; more complete pumpage data were 

obtained for individual wells for the period 

1947–98. New data included verified extractions 

and production by non-filers. Annual pumpage 

is 0–15 percent greater than initial values, which 

were nearly identical to those used by Hardt and 

Hutchinson (1980).

Return flow Hardt and Hutchinson (1980); and Western–

San Bernardino Watermaster (R.L. Reiter, 

San Bernardino Valley Municipal Water 

District, unpub. data, 2000).

Return-flow percentage verified for all wells used 

for export. Net result is somewhat more export 

and less return flow.

Evapotranspiration Hardt and Hutchinson (1980). None.

Underflow Multiple sources, including Dutcher and 

Garrett (1963), California Department of 

Water Resources (1971), and Dutcher and 

Fenzel (1972).

Moderate for most areas of underflow. Significant 

change to underflow beneath the Santa Ana 

River; many annual values are much less than 

those used by Hardt and Hutchinson (1980).

Table 17. Source of parameter, recharge, and discharge estimates and their relative adjustment during calibration of the groundwater flow model of the San Bernardino area, California.

Computer Models 77
Figure 42. Measured ground-water levels and simulated hydraulic heads for the unconfined part of the valley-fill aquifer in the 

San Bernardino area, California, 1945. Measured contours adapted from unpublished map by F.B. Laverty (San Berndardino Valley 

Municipal Water District, written commun., 1998).

78 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

15

215

10

215

15

Former marshland

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake Arrowhead

Silverwood

Lake

Cajon

Cable Cr

Cr

River

Plunge

Santa

Ana

 Cr

Mill

Cr

Lytle

Cr

Seven Oaks Dam

Artificial-recharge basin

Simulated hydraulic-head contour-For the

upper layer of the ground-water flow model.

Altitude in feet above mean sea level

1,400

1,000

1,100

1,200

1,300

1,400

1,500

1,600

1,200

1,300

1,400

1,600

1,800

1,800

1,200

1,300

1,400

2,000

2,000

2,000

2,200

2,200

2,200

2,400

2,600

2,700

Measured ground-water-level contour-For the

unconfined part of the valley-fill aquifer. Altitude

in feet above mean sea level

1,400

1,000

1,050

1,100 1,150

1,150

1,200

1,200

1,200

1,300

1,300

1,400

1,400

1,500

1,600

1,600

1,800

1,800

2,000

2,000

2,200

EXPLANATION

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Gabriel

Mts

San

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

San Bernardino Mountains

Crafton Hills

Fault or ground-water barrier-May be concealed or approximately located

Boundary of Santa Ana River drainage basin

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Highland Highland

Redlands Redlands

San Bernardino San Bernardino

0 6 KILOMETERS

0 6 MILES

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'
Figure 43. Results of calibration of the ground-water flow model of the San Bernardino area, California, 1945–98.

Computer Models 79

1,200

1,300

1,400

1,500

1,600

1,700

40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30

1,300

1,200

1,100

800

900

1,000

1,500

1,600

1,400

1,300

1,100

1,200

2,300

2,200

2,100

1,800

1,900

2,000

1,300

1,200

1,100

800

900

1,000

ALTITUDE, IN FEET ABOVE SEA LEVEL

1,300

1,200

1,100

800

900

1,000

1,200

1,100

1,000

700

800

900

1,500

1,400

1,300

1,000

1,100

1,200

1,400

1,300

1,200

1,000

1,100

1,900

1,800

1,700

1,400

1,500

1,600

1,300

1,200

1,100

800

900

1,000

1,500

1,400

1,300

1,000

1,100

1,200

1,300

1,200

1,100

800

900

1,000

900

1940-99 2000-30 1940-99 2000-30 1940-99 2000-30

Calibration wells-Estimated quality of match between

measured ground-water levels and simulated hydraulic

heads indicated for each well used in calibration of the

ground-water flow model

Good

Fair

Poor

Seven Oaks 

Dam

0 6 KILOMETERS

0 6 MILES

Redlands Crafton Hills

San Bernardino

Badlands

Mts

Gabriel San

Basin

boundary

San Bernardino Mountains

Shandin

Hills

Ana River

Santa

EXPLANATION

Graphs Map

Calibration

period

1945-98

1999-2030

1940

Measured ground-water level

Land surface

Simulated hydraulic head-For each

layer of the ground-water flow model

Upper layer

Lower layer

Devil

Canyon 2

1N/4W-7F1

USGS

2N/5W-33J4

WSB 13-Raynor 4

1S/4W-6H1

Heap

1S/4W-3Q1

Thorn 10

1S/4W-22B3

Redlands 32

1S/3W-21H1

Tri-City

1S/3W-9E2

W. Cram

1S/3W-2J1

Happe Mutual

Well Co.

1S/2W-29M1

Bryn Mawr Water Co.

1S/3W-31A3

WSB 1

1N/5W-23P4

Newmark 4

1N/4W-16E4

Meacham

1N/4W-35L1
A comparison between measured and simulated surfacewater outflow from the basin is shown in figure 44. Outflow 

from the basin is measured at five gages (table 1; figure 11). 

Simulated outflow is a combination of outflow calculated by 

the ground-water model (STR2 package), plus local runoff 

(table 4), plus wastewater discharge (table 7). In general, 

the match between measured and simulated outflow is quite 

good—both as a long term trend and for most years. An 

important limitation of the ground-water flow model may be 

illustrated by figure 44. The model appears to be too responsive to some sequences of above-average runoff. In some wet 

years (1969, 1980, 1983), simulated outflow exceeds measured. Then following the wet period (1984–87), simulated 

outflow is less than measured outflow. This pattern suggests 

that water is routed through the simulated ground-water system too quickly. Perhaps via the STR2 package, surface water 

is not recharged in a sufficiently broad area so that it drains 

back to the stream system more slowly. A more complex surface-water routing package that incorporates a way to expand 

a simulated stream into adjacent model cells during periods of 

high runoff may help solve this issue. 

A comparison of the change in ground-water storage for 

the transient calibration period 1945–98 is shown in figure 45

using results from the ground-water flow model and from a 

similar storage calculation made with a GIS. The GIS method 

of calculation, which is described on p. 52, can yield a more 

accurate estimate of the actual change in ground-water storage 

because the method uses annually measured ground-water 

levels. Simulated heads calculated by the ground-water flow 

model are based on previously calculated heads and can 

accumulate errors over the simulation period. The primary 

errors associated with the GIS method are in selecting wells 

that reflect an unconfined change in ground-water levels. Both 

methods used the same values for specific yield. As shown in 

figure 45, the two sets of calculated values track surprisingly 

well over the 54-year period. This similarity tends to confirm 

the reasonableness of the ground-water flow model as well 

as of the observed wells chosen for the GIS calculation. The 

maximum change in ground-water storage during 1945–98 for 

the San Bernardino area was calculated by either method to be 

about 900,000 acre-ft; the annual change in ground-water storage commonly exceeded about 70,000 acre-ft.

Overall, as illustrated in figures 42−45, the linked surface-water/ground-water model performs well for the calibration period 1945–98. The model matches measured data and 

independent estimates for surface-water outflow, ground-water 

levels, and changes in ground-water storage. The model 

responds in realistic ways to a range of hydrologic conditions 

for an extended period of time. These features suggest that the 

model is well calibrated and can be used cautiously to investigate other hydrologic conditions. 

Figure 44. Comparison between measured and simulated surface-water outflow from the San Bernardino area, California, 

1945–98.

80 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

-50,000

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1945

19501955196019651970197519801985199019952000

YEAR

BASIN OUTFLOW, IN ACRE-FEET PER YEAR

Measured

Simulated
Evaluation

In the development of some ground-water models, a 

historical period that is not part of the model calibration is 

used to critique the model. This type of evaluation, commonly 

called verification of the model, uses updated recharge and 

discharge values, but unchanged parameter values, to verify 

that the model can perform reasonably well for a different 

period of time with different stresses. Although this type of 

evaluation can be helpful in identifying problems with the 

model, the evaluation by itself does not confirm that the model 

is an accurate representation of the physical system. 

In this study, no such evaluation or verification period 

was used, at least in the conventional sense. In some respects, 

the period 1975–98 can be viewed as an evaluation because 

the original model developed by Hardt and Hutchinson (1980) 

was calibrated for the preceeding period 1945–74. The key 

hydraulic parameters of transmissivity, vertical conductance, 

and conductance of faults were unchanged from the original 

model. 

Inspection of results from the present model (figs. 42–45) 

suggests that the model performs reasonably well in both time 

periods, 1945–74 and 1975–98. The two periods are hydrologically fairly different. The first period has a remarkably long 

sequence of mostly dry years resulting in significant storage 

depletion (figs. 7 and 18). The second period has both a recovery of that storage depletion and a shorter wet-dry sequence. 

The second period also has many extremely wet years, which 

is uncharacteristic of the first period (fig. 14). Despite these 

hydrologic differences, the present model simulates both periods equally well. This capability suggests that the magnitude 

and distribution of hydraulic values, developed originally by 

Hardt and Hutchinson, are reasonable and allow the present 

model to simulate a variety of hydrologic conditions. 

Sensitivity Analysis

A sensitivity analysis of a ground-water flow model 

involves observing the relative change in model output caused 

by a change in model inputs. Those inputs (aquifer characteristics, recharge, and discharge) that produce the greatest 

change in output (hydraulic heads and computed recharge, 

discharge, and cell-by-cell fluxes) are the most sensitive. An 

improvement in the most sensitive inputs will produce the 

greatest improvement in the ground-water flow model. This 

improvement may be an important goal to enhance the predictive capability of the model, but it does not necessarily mean 

that the simulation model becomes a more realistic representation of the system. The capability of a simulation model to 

represent a real system is more closely related to the compatibility among the real system, the conceptual model, and the 

simulation model (fig. 38).

Figure 45. Estimated change in ground-water storage in the San Bernardino area, California, 1945–98. 

Methods of calculating values with a geographic information system and with the ground-water flow 

model are described on pages 52−53.

Computer Models 81

-200,000

-100,000

100,000

200,000

300,000

400,000

194519501955196019651970197519801985199019952000

Geographic information system 

Ground-water flow model

0

CHANGE IN STORAGE, IN ACRE-FEET

YEAR
Results of the sensitivity analysis are summarized in 

table 18. The range of variation selected for each model value 

was based on the estimated uncertainty in the value. Attempts 

to test some values, such as a decrease in fault or streambed 

conductance, resulted in the model failing to numerically 

converge. 

Recharge from streams and discharge from wells were 

found to exert the most influence on the simulated system as 

would be expected by their prominence in the water budget. 

Variations in the quantity or spatial distribution of these large 

inputs (table 11) create important changes in hydraulic heads 

and simulated recharge and discharge. Transmissivity and storage coefficient of the valley-fill aquifer are of lesser importance. Faults and ground-water barriers within the simulated 

area are critical in maintaining hydraulic head (water table) in 

areas outside the former marshland, particularly near Redlands. Without these barriers, the simulated water table in the 

outlying areas drops farther and faster.

The head-dependent relations used to approximate both 

evapotranspiration and the stream-aquifer interaction exert a 

controlling influence in the model, as demonstrated during 

calibration and sensitivity analysis of the model. These relations dampen fluctuations in hydraulic heads by adjusting the 

quantity of simulated recharge or discharge. The sensitivity 

analysis demonstrated that seemingly static hydraulic heads 

may mask substantial changes in ground-water flow rates, 

especially in the vicinity of the former marshland (table 18).

Increased streambed conductance during years with 

unusually large runoff was found to be critically important in 

providing sufficient recharge to match ground-water levels 

following 1965. Temporally constant values tested as part of 

the sensitivity analysis produced ground-water levels as much 

as 100 ft lower by the end of the 54-year simulation. Pumpage 

return flow is a significant component of the water budget, 

each year. Reducing return flow from 30 to 15 percent of gross 

pumpage at selected wells resulted in ground-water levels as 

much as 50 ft lower, even in the vicinity of the former marshland.

Use and Limitations

As designed and calibrated, the ground-water flow model 

can be used most appropriately for answering regional-scale 

questions about the valley-fill aquifer and for calculating 

boundary conditions for smaller-scale models. Development 

of the ground-water flow model focused mostly on general 

hydrogeologic themes found in the Bunker Hill and Lytle 

Creek basins, not on specific data from small areas encompassing a few hundred or a few thousand ft. Therefore, localscale questions may not be answered well by using results 

from this model. The model, however, does integrate many 

different aspects of the valley-fill aquifer, and model results 

will reflect this complexity. The model will be particularly 

useful for issues involving the geometry, boundary conditions, storage, and water budget of the valley-fill aquifer. The 

model also will be useful in identifying regional directions and 

changes in direction of ground-water flow and differences in 

hydraulic head between upper and lower layers of the valleyfill aquifer. Regional issues of water use and distribution, in 

particular artificial recharge and ground-water extraction, can 

be analyzed with the aid of the model.

An important limitation of the ground-water flow model 

is that it is does not simulate the transport of chemical contaminants in the valley-fill aquifer; it is not a solute-transport 

model, nor should it be used as one. Rather, the ground-water 

flow model transports water from areas of recharge to areas of 

discharge through two highly generalized model layers 

(fig. 37). As of 1998, knowledge of the three-dimensional 

character of the valley-fill aquifer and human modifications 

to the aquifer is insufficient to develop a rigorous conceptual model of chemical transport in the aquifer, much less a 

numerical solute-transport model. For example, the specific 

flowpath of a chemical constituent through the valley-fill 

aquifer could be through a 10-ft-thick sand layer, along an 

erosional surface, on top of a fine-grained deposit, or through 

an abandoned well casing. Knowing which of these flowpaths 

is the real one may not be particularly important in simulating 

regional ground-water flow, but such knowledge is likely to be 

critical in understanding, tracking, and successfully mitigating 

a ground-water contaminant. 

An area of caution in use of the ground-water flow model 

involves the upper confining member (UCM, fig. 37). This 

50- to 100-ft thick, mostly fine-grained hydrogeologic unit 

is present in at least part of the former marshland (figs. 2 and 

24). Within the ground-water flow model, UCM is simulated 

as a part of the upper model layer with a storage coefficient 

corresponding to a water-table condition. For most hydrologic 

conditions, this approximation works well, in particular for 

interaction with streams and for storage depletion lasting a few 

years. Anecdotal information and ground-water-quality data 

for UCM, however, suggest that UCM is a perchable unit that 

can remain saturated even as the rest of the upper model layer 

is dewatering (W.J. Hiltgen, San Bernardino Valley Water 

Conservation District, oral commun., 1988). Because the 

hydraulic complexity of UCM is only partly simulated with 

the ground-water flow model, some questions involving this 

zone may be addressed best by site-specific investigations or 

by more detailed ground-water flow models.

82 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Model parameter, 

recharge, or discharge

Amount or type 

of change Sensitivity

Model parameters

Fault conductance Increase conductance to remove any restriction to flow.Areal ground-water levels are surprisingly similar to calibrated values except on the east side 

of the model near the city of Redlands.

Transmissivity Increase by a factor of two. Minimal change in ground-water levels over 

most of the Bunker Hill basin, except near 

the former marshland where levels rise an 

additional 10−20 feet.

Specific yield Set all values to 0.10 (dimension less). Minor change in hydrographs except along 

model boundaries where ground-water levels 

increase moderately.

Storage coefficient of lower model layer Change from a constant value of 0.0001 to 

0.001 (dimension less).

Minor change in hydrographs of lower model 

layer; no discernible change in hydrographs 

for upper model layer.

Recharge

Streambed conductance Use a constant value for all years. Recharge is insufficient; ground-water levels fail 

to rise sufficiently during 1970–80.

Recharge from ungaged runoff Decrease by a factor of two. Most hydrographs are similar; slight decrease in 

evapotranspiration.

Recharge from local runoff Set to zero. Minimal change in hydrographs, but insufficient 

gains to streams during wettest periods.

Pumpage return flow Decrease return flow from 30 to 15 percent. Minimal change in hydrographs, but significantly less evapotranspiration and gains to the 

streams.

Underflow across the Crafton fault Decease by a factor of two. Ground-water levels on the east side of the 

Bunker Hill basin fall dramatically and do not 

recover.

Discharge

Evapotranspiration rate Decrease maximum rate from 38 to 18 

inches per year.

Total evapotranspiration decreased by about 

half. Ground-water levels rise too high, but 

increased gains to the streams compensate for 

much of the decrease in evapotranspiration.

Pumpage Increase pumpage by 10 percent. Ground-water levels decline too far and fail to 

recover sufficiently following the 1960’s.

Underflow beneath the Santa Ana River Use previous rate of 15,000 acre-feet per 

year.

Ground-water levels decline too low near the 

former marshland and fail to recover sufficiently during 1980’s; evapotranspiration is 

too low.

Table 18. Sensitivity of the ground-water flow model of the San Bernardino area, California.

Computer Models 83
Changes in saturated thickness in the upper layer of the 

valley-fill aquifer (UCM and UWB, fig. 24) were assumed to 

cause relatively localized changes in transmissivity, mostly 

near the base of the mountains. The ground-water flow model 

uses a time-invariant transmissivity, which causes simulated 

hydraulic heads near the mountain front to fluctuate somewhat 

less than if the model used a time-varying transmissivity. Calculation of transmissivity as a function of saturated thickness 

likely would improve the simulation, but would require data 

about the three-dimensional configuration of the valley-fill 

aquifer that were not available. A time-varying transmissivity also creates a hydraulic nonlinearity that significantly 

increases the complexity of the constrained optimization 

model and would require as much as 10 to 200 times as much 

computational time to solve a typical water-management 

problem for the San Bernardino area (Danskin and Gorelick, 

1985).

The streamflow-routing package (STR2) simulates the 

average interaction between a stream and the valley-fill aquifer 

during a whole year. This is a considerable simplification of 

an actual stream in a semiarid environment. Discharge in real 

streams is much more variable and commonly occurs over a 

period of days or months, not an entire year. Nevertheless, 

the streamflow-routing package does add important capabilities and potential uses of the ground-water flow model. First, 

the package facilitates development of linked water budgets 

between the surface-water and ground-water systems. Second, 

the package is likely to be useful in evaluating changes in 

streamflow and ground-water recharge and discharge caused 

by changes in streambed conductance. For example, the package could be used to identify the likely result of installing a 

concrete liner in a stream channel or increasing the size of an 

artificial-recharge basin. Future modifications to the groundwater flow model may benefit from including more of the 

actual complexity of the surface-water system, in particular 

adding diversions from major streams (pl. 2).

Additional future modifications to the ground-water flow 

model could include simulation of historical land subsidence 

(Miller and Singer, 1971). Although the quantity of inelastically released ground water from the area of the former marshland is not likely to be significant, simulating historical land 

subsidence may provide additional insight about the hydrogeologic setting and structure of the valley-fill aquifer.

Modification of pumpage return flow may provide an 

important improvement to the flow model. Presently, return 

flow is calculated using a constant percentage of pumpage per 

well, and is returned to the same location as the pumpage. Ideally, return flow could be calculated using an understanding of 

water distribution, land use (fig. 8), and climatic factors, such 

as potential evapotranspiration.

A time-consuming, but probably beneficial modification to the ground-water flow model would be to use shorter 

stress periods, either quarters or months, in order to simulate 

seasonal variability in streamflow, pumpage, and ground-water 

levels. Adding model layers or decreasing model grid size are 

unlikely to significantly improve the flow model until more 

hydrogeologic information is known about the three-dimensional structure of the valley-fill aquifer. 

Constrained Optimization Model

The large number of complex, interrelated water-management issues in the San Bernardino area requires a quantitative 

evaluation of water-management alternatives. Some of this 

evaluation can be done with field data, and some can be done 

with the ground-water flow model described in this report. 

Much of the evaluation, however, involves answering watermanagement questions that are too complex to be analyzed 

using only these methods.

Constrained optimization techniques, as a subset of the 

field of operations research (H.M. Wagner, 1975; Hillier and 

Lieberman, 1980; Winston, 1987), were developed to analyze 

precisely this type of situation. Use of the techniques involves 

development of a constrained optimization model, which is 

a set of equations that defines a management problem. The 

equations mathematically describe management objectives and 

constraints, and the mathematical solution of the equations 

(optimization model) identifies the most efficient allocation of 

a scarce resource, such as water or money. Multiple issues can 

be considered simultaneously, and alternate solutions can be 

compared quantitatively.

Since the initial research and development in the 1940’s, 

constrained optimization techniques have been applied to 

many scientific and business problems, such as finding the 

most efficient design of a nationwide telephone system, the 

greatest revenue from mixing multiple-grade iron ores, the 

fewest number of planes to service an area, and the cheapest 

arrangement of irregularly shaped patterns on a bolt of cloth. 

Application of the techniques to hydrologic problems has been 

limited, although many research studies have been conducted 

(Gorelick, 1983; Rogers and Fiering, 1986; B.J. Wagner, 

1995).

Overtime, however, the use of optimization techniques 

to solve applied ground-water management problems has 

increased as the techniques have been taught more widely, as 

ground-water flow models have been developed for hundreds 

of basins, and as computer codes and computational power 

have improved. Recent examples of optimization techniques 

applied in various hydrogeologic settings include Reichard 

(1995), Nishikawa (1998), Barlow and Dickerman (2001), 

Czarnecki and others (2003a,b), Danskin and others (2003), 

Eggleston (2003), Phillips and others (2003), Reichard and 

others (2003), Bexfield and others (2004), and McKee and 

others (2004).

84 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
The optimization model documented in this report is 

based on well-developed techniques (Gorelick and others, 

1993; Ahlfeld and Mulligan, 2000) and extends previous work 

by integrating surface-water, ground-water, and water-quality 

issues in an actual field area, and by working closely with the 

more than 20 water managers in the San Bernardino area who 

are actively seeking solutions to complex water-management 

questions.

General Characteristics

The particular constrained optimization techniques used 

to evaluate water-management alternatives in the San Bernardino area are referred to as linear and quadratic programming. Within the optimization model, the management objective is expressed as a linear or quadratic equation (objective 

function). Other equations in the model represent management 

constraints that must be met. The mathematical form of the 

optimization model is to maximize or minimize

the objective equation (11a)

subject to

all the constraint equations. (11b)

Items to be managed, such as recharge or pumpage at 

specific sites, are represented by decision variables in the 

equations. When combined with a physical model, such as 

a ground-water flow model, the optimization model may 

include state variables, such as heads, that indicate the state 

of the physical system. In applying optimization techniques to 

ground-water problems, state variables commonly are included 

in the optimization model as decision variables. Other variables and parameters can be added to the optimization model 

to link the decision variables to each other or to perform necessary calculations, such as determining total recharge, lift at a 

well, or cost of operations.

The use of constrained optimization techniques to solve a 

hydrologic problem is best illustrated by a simple example. In 

1990, two production wells—the Ninth Street well (1S/4W–

4E8) and the Perris Street well (1S/4W–4F4)—were installed 

to provide municipal water via the Baseline feeder pipeline 

(fig. 11) (Geoscience Support Services, Inc., 1990). Both 

wells were installed to a depth of about 1,000 ft below 

land surface and were designed to extract ground water 

mostly from the MCM and MWB hydrogeologic units 

(fig. 24). Initial testing of ground water pumped from the wells 

indicated that water from well 1S/4W–4E8 had an elevated 

temperature (> 80o F) and a fluoride concentration of about 

1.8 mg/L, which exceeded the safe drinking-water standard 

defined by the State of California (California Department of 

Water Resources,1995a). Although this unusual temperature 

and ground-water quality helped to identify the likely location 

of the Banning (?) fault (fig. 5), the elevated values created a 

problem in supplying water of acceptable quality for municipal use. To solve the water-quality problem, ground water 

pumped from the two wells has been blended prior to distribution.

This water-management problem of trying to maximize 

production while providing acceptable water quality and not 

exceeding capacity of the wells can be solved by formulating 

it as a simple optimization model. For example, if a watermanagement goal is to maximize the production of water from 

two wells, then an objective function (Z) can be written as

maximize Z = QPump

1

 + QPump

2

 , (12)

where the value of Z is to be maximized and the decision variables QPump

1

 and QPump

2

 represent pumpage, in ft3/s, at wells 1 

and 2, respectively. In this example, well 1 is the Ninth Street 

well that has an unacceptably high concentration of fluoride, 

and well 2 is the Perris Street well that has less fluoride.

Constraints to the production of water involve the maximum capacity of wells and the necessary blending of water 

to achieve an acceptable quality. The constraints, which are 

formulated as inequalities or sometimes equalities, restrict the 

possible values of the decision variables (QPump

1

, QPump

2

), which 

in turn restrict the possible value of Z. In this example, Z is 

subject to

QPump

1 ≤ 6.2 ft3

/s (13a)

QPump

2 ≤ 5.5 ft3

/s (13b)

QPump

1

 + QPump

2

 = QPump

Total (13c)

c1 QPump

1

 + c2 QPump

2 ≤ (1.4 mg/L) (QPumpTotal) (13d)

where c1, c2 are concentrations of fluoride, in mg/L, of water 

pumped from wells 1 and 2, respectively. For this problem, 

values of c1 and c2 are 1.8 and 0.6, respectively. QPump

Total is 

total pumpage from wells 1 and 2.

Equations 13a and 13b are capacity constraints that 

restrict the pumpage from wells 1 and 2 to physically realistic 

values. Equation 13c is a mass-balance constraint that helps 

formulate equation 13d. Equation 13d is a water-quality constraint that assures blended water pumped from wells 1 and 2 

does not exceed the water-quality standard for fluoride of 1.4 

mg/L. Water temperature for municipal use is not regulated, 

but will be controlled reasonably well if the fluoride standard 

is met. As in this example, values on the right-hand side (RHS) 

of the equations are often capacities or target values.

Computer Models 85
Mathematical solution of the optimization model requires 

that the unknown values (decision variables) be written on 

the left-hand side of the equation and that the known values 

(constants) be written on the right-hand side. By reorganizing 

terms, constraint equations 13a–d become,

QPump

1 ≤ 6.2 ft3

/s (14a)

QPump

2 ≤ 5.5 ft3

/s (14b)

QPump

1

 + QPump

2

 - QPump

Total = 0 (14c)

c1 QPump

1

 + c2 QPump

2

 - (1.4 mg/L) (QPump

Total) ≤ 0 . (14d)

Non-negativity constraints,

QPump

1

, QPump

2

, QPump

Total ≥ 0 (14e)

usually are included, sometimes implicitly by the optimization 

computer program, to make solving the problem mathematically more efficient. Equation 14e also is a constraint on the 

physical operation of the wells, ensuring that they are used 

only for extraction of water, not injection. Together, equations 

12 and 14 constitute the optimization model. Equation 12 is 

the objective function; equations 14a−e are the constraints.

The simple optimization problem described by equations 

12 and 14 is a linear-programming problem that can be solved 

by hand or graphically, as shown in figure 46A. A graphical 

solution is possible when an optimization problem has three or 

fewer independent decision variables, each represented by the 

x, y, or z axis. The example problem with two decision variables (QPump

1

 and QPump

2

) is represented by a two-dimensional 

graph (fig. 46A). The variable QPump

Total is a linear combination 

of the two decision variables and, therefore, does not require 

an additional dimension for the solution. Constraint equations 

define regions of the graph where a solution is either feasible

or infeasible. The optimal solution for a linear-programming 

problem is always found at a corner or along an edge of the 

feasible region; other points within the feasible region will 

satisfy all constraints, but will not be optimal. In the example 

problem, the optimal value of Z is 11.7 ft3/s. Equations 14a 

and 14b are binding constraints that determine the value of Z. 

Equation 14d is a non-binding or loose constraint that can be 

eliminated from the optimization model without altering the 

value of Z. If the value of c1 were greater, such as 5.1 mg/L, 

which is the concentration measured in the lowest part of the 

well, then the feasible solution space would be much smaller 

as shown in figure 46B. Equation 14d revised with the larger 

concentration values then becomes a binding constraint, 

equation 14a becomes a loose constraint, and the value of Z 

decreases to 6.9 ft3/s.

Optimization models used to solve real problems 

typically require tens or hundreds of decision variables and 

hundreds or thousands of constraints. In order to more easily 

describe an optimization model, particularly a large or complex model, a tableau format can be helpful. Such a tableau for 

the simple optimization model described above (eqs. 12 and 

14) is shown in figure 47.

If the objective of the example problem were to minimize pumping costs, then the optimization model would be 

an example of a quadratic-programming problem. Pumping 

cost is a function of pumpage and lift; lift is also a function of 

pumpage; therefore, pumping cost is proportional to pumpage 

squared. Assuming a single time period of constant pumpage, 

equation 11a can be rewritten for well 1 and well 2 as

minimize Z = ce e1 QPump

1

 L1

Total + ce

 e2 QPump

2

 L2

Total , (15a)

where

ce is the unit cost of electricity, in dollars per foot of lift 

per cubic foot of water;

ei is the efficiency of the well pump and motor for well 

i, expressed as a decimal fraction, commonly about 

0.60;

LTotal

i is the total lift at well i, in ft;

QPump

i is pumpage from well i, in cubic ft; and

Z is total pumping cost, in dollars.

Total lift at a well is composed of an initial fixed lift and a 

variable lift that is proportional to additional pumpage. Substituting these terms, the objective becomes,

minimize Z = ce e1 QPump

1

 (LInitital

1

 + LS

1

) + 

 ce e2 QPump

2

 (LInitial

2

 + LS

2

) , (15b)

where

LInitial

i is initial lift at well i, in ft; and

LS

i is additional lift at well i caused by pumpage (stress) at 

all other wells, in ft.

The additional lift can be calculated using an aquifer-response 

relation derived from a specific-capacity test, an aquifer test, 

or a ground-water flow model. For an aquifer where drawdown is a linear function of pumpage, the objective equation 

can be expanded to

 minimize Z = ce e1 QPump

1

 (L1

Initial + 

 r1, 1 QPump

1

 + r1, 2 QPump

2

) + ce e2 QPump

2

 (L2

Initial +

 r2, 1 QPump

1

 + r2, 2 QPump

2

) , (15c)

where

r

o, s is the unit drawdown response observed at location o 

that results from a unit pumping stress applied at 

location s, in ft per cubic ft per second.

86 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 46. Graphical solution of a simple constrained optimization model. Graphs A and B show optimal 

solutions for fluoride concentrations in well 1 of 1.8 and 5.1 milligrams per liter, respectively.

Computer Models 87

A

B

PUMPAGE AT WELL 2 (

Q2 ), IN CUBIC FEET PER SECOND

PUMPAGE AT WELL 1 (Q1 ), IN CUBIC FEET PER SECOND

Feasible region

Infeasible region

Infeasible region

Objective

EXPLANATION

Maximize Z = Q1 + Q2

C1 = 1.8

C2 = 0.6

Q1 b 6.2

Q2 b 5.5

Optimal

solution

(Z = 11.7)

1.8 Q1 + 0.6 Q2 b 1.4 QT

1.8 Q1 + 0.6 Q2 b 1.4QT

5.1

Q1 + 0.6 Q2 b 1.4QT

Q1 + Q2 = QT

Constraints

Fluoride concentration, in

milligrams per liter

Objective

EXPLANATION

Maximize Z = Q1 + Q2

C1 = 5.1

C2 = 0.6

5.1 Q1 + 0.6 Q2 b 1.4 QT

Constraints

Fluoride concentration, in

milligrams per liter

0 0

2

4

6

8

2 4 6 8

Z = 4

Z = 8

Z =

PUMPAGE AT WELL 2 (

Q2 ), IN CUBIC FEET PER SECOND

PUMPAGE AT WELL 1 (Q1 ), IN CUBIC FEET PER SECOND

Q1 b 6.2

Q2

Z = Q1 + Q2 = QT

b 5.5

Optimal

solution

(Z = 6.9)

0 0

2

4

6

8

2 4 6 8

Z = 4

Feasible

region
This formulation of an aquifer-response relation is appropriate for a single management period, such as a steady-state 

analysis. The next section of this report, “Representing the 

ground-water flow system,” includes a more in-depth discussion of how to include response of an aquifer in an optimization model.

Additional constraints may be desired to restrict drawdown at each well, for example,

L1

Total ≤ maximum allowable drawdown at well 1, in ft; 

 (16a)

and

L2

Total ≤ maximum allowable drawdown at well 2, in ft. 

 (16b)

The revised optimization problem (model) uses a quadratic 

objective function (eq. 15c) with linear constraints (eq. 14a–e 

and 16a,b).

A specialized computer program is required to solve 

essentially all realistic optimization models. The program 

identifies the mathematically optimal value of Z and the 

optimal values for all variables and equations in the optimization model. Additional information provided by the computer 

program includes the marginal value of the decision variables 

(dZ/dQ1, dZ/dQ2) and an identification of which constraint 

equations restrict the value of Z (binding constraints) and 

which are superfluous constraint equations (loose constraints). 

Effective use of the optimization model involves not only 

obtaining the value of the objective function (Z), but also 

analyzing the additional information. This analysis enables the 

user to better understand the relative importance of different 

variables and equations, and in some cases, to identify previously unknown relations between the equations. For management of a complex physical system, gaining this understanding 

is at least as important as obtaining the optimal value of Z 

(H.M. Wagner, 1975, p. 942–943).

The constrained optimization model developed to evaluate water-management alternatives for the San Bernardino 

area uses either linear or quadratic programming. Objective 

equations are linear or quadratic; all constraint equations are 

linear. Decision variables represent recharge, pumpage, and 

costs; and objective equations include different combinations 

of these decision variables. Constraint equations include both 

decision variables and state variables representing groundwater levels at selected locations in the valley-fill aquifer. Use 

of the optimization model involves combining a single-objective equation with appropriate constraint equations in order to 

answer a specific water-management question. Much of the 

power of constrained optimization techniques is derived from 

the ease of reformulating a model by using a different objective equation with a different set of constraint equations. Technically, each combination of an objective and set of constraints 

is itself an optimization model. For purposes of simplicity in 

this report, however, all objectives and constraints for water 

management in the San Bernardino area are referred to collectively as the constrained optimization model of the San 

Bernardino area. Different combinations of equations can be 

used to analyze a specific water-management problem, such 

as scenarios 5 and 6 that are described later in this report. Scenarios 1–4 were analyzed using only the ground-water flow 

model, not any optimization techniques.

Figure 47. Objective function, constraint equations, decision variables, and RHS of a simple constrained optimization model.

88 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Objective function

and constraints Pumpage (Right-Hand Side

of equations)

RHS Equality

condition

Q1

(z) 1

1

5.5

1

1

1

1 0

6.2

1.8

1 0

0.6 0

1 0

-1.4

-1

1 0

<=

=

<=

>=

<=

>=

>=

Q2 QT

Decision variables

Objective function

Capacity

Capacity

Mass balance

Water quality

Non negativity

Non negativity

Non negativity

Units for pumpage are cubic feet per second and for fluoride concentration used in the water-quality constraint are milligrams per liter. 

The water-management problem solved by the optimization model is described in equations 12 and 14 (a-e) and is shown in figure 46. Constraints
Setting up and solving the optimization model of the

San Bernardino area involves a number of steps, listed in 

figure 48. At the outset, the major water-management issues 

need to be identified. Objectives and constraint equations are 

written in commonly used words, and then the word equations 

are transformed into algebraic equations. A computer software 

program or set of programs is chosen to solve the equations 

and write out the optimization results. Finally, the optimal 

results are obtained and reviewed with the local water managers to ensure the results are credible and useful.

For the San Bernardino optimization model, two sets of 

computer programs were used. The first set used the MODMAN (Greenwald, 1993) program to run the MODFLOW 

ground-water flow model and automatically create an MPS 

input dataset, which was then solved using the optimization 

software MINOS (Murtagh and Saunders, 1983). Although the 

MPS format is an industry standard for optimization models, 

it is exceptionally cumbersome to create manually, hence the 

need for MODMAN. MINOS can be used to solve a quadratic 

optimization problem, but it requires additional FORTRAN 

subroutines written for the specific problem. LINDO software 

(LINDO Systems Inc., 1994) was used occasionally instead of 

MINOS because LINDO has a better interface with MODMAN. In particular, MODMAN can automatically retrieve 

optimization results from LINDO and rerun the ground-water 

flow model using the optimal values of decision variables. 

Re-running the ground-water flow model is important to 

quantify the difference between the optimal solution, which is 

based on an assumption that the ground-water flow model is 

strictly linear, and the simulated results from the San Bernardino ground-water flow model, which has mildly nonlinear 

features, such as evapotranspiration. Although less convenient 

for re-running the ground-water flow model, MINOS was 

found to be more cost effective for solving large optimization 

problems. This set of programs (MODFLOW, MODMAN, and 

MINOS) was used to solve scenarios 5 and 6 described later in 

this report. LINDO was used during development of scenario 

5 to efficiently assess hydraulic non-linearity.

The second set of computer programs combines use of 

the MODFLOW ground-water flow model with the General 

Algebraic Modeling System (GAMS) developed by the World 

Bank (Brooke and others, 1988). The MODFLOW program 

was used to calculate the response of simulated hydraulic head 

to recharge and discharge. These data were entered manually into the input file for GAMS, which then required having 

both definitions and documentation of the optimization model 

in a single computer input file. The GAMS format is highly 

flexible and uses extensive free formatting of text and values. 

Solving a quadratic problem using GAMS involves simply 

writing the objective equation in words. GAMS software then 

solves the optimization problem internally by using one of 

several optimization solvers, including MINOS. This set of 

programs (MODFLOW and GAMS) was used during initial 

development of the ground-water flow and optimization models. The high degree of flexibility and customization offered 

by GAMS was helpful during the formative steps of identifying decision variables, interacting with decision makers, and 

defining the likely feasibility space of scenario 6.

Representation of the Ground-Water Flow 

System

Quantitative evaluation of water-management alternatives 

in the San Bernardino area requires a method of predicting 

the response of ground-water levels to different quantities 

of recharge and pumpage. The ground-water flow model 

is an excellent way to calculate this response because the 

flow model simulates the physical process and incorporates 

much of the complexity of the aquifer system. The calculated 

response can be incorporated in the optimization model using 

the technique of response functions (Maddock, 1972; Gorelick, 1983; Gorelick and others, 1993, p. 145–153; Ahlfeld and 

Mulligan, 2000).

A response function is the simulated response of hydraulic head to recharge or discharge. The recharge or discharge 

can be defined for actual or hypothetical conditions, and the 

effect on head can be observed at any location in the flow 

model and after any length of time during the simulation. The 

response function is in effect an encapsulated form of the 

ground-water flow model and includes the combined effects of 

geometry, boundary conditions, aquifer parameters, and other 

model fluxes. Response functions are an effective and commonly used method of linking a ground-water flow model to a 

constrained optimization model (Gorelick, 1983; Lefkoff and 

Gorelick, 1987; Greenwald, 1993). The other method of combining a ground-water flow model with an optimization model 

is referred to as embedding. This technique requires that all 

equations defining the ground-water flow model be included 

as constraints in the optimization model (Gorelick, 1983). This 

approach, however, becomes computationally too large for 

nearly all realistic problems.

Development of the constrained optimization model for 

the San Bernardino area required creating a unit response 

function for each of the decision variables representing 

recharge to, or discharge from the valley-fill aquifer. Because 

a calibrated ground-water flow model was available, it was 

used to calculate the unit response functions—a representative 

set of which is shown in figure 49. Each graph is created by 

simulating a unit stress of recharge or discharge and observing the unit response in simulated hydraulic head at various 

control locations throughout the valley-fill aquifer over a 

32-year management horizon. The unit stress is chosen to be 

sufficiently high so that a numerically significant unit response 

is produced at all locations of interest by the end of the 32-

year period.

Computer Models 89
Figure 48. Sequence of steps involved in design and use of a constrained optimization model to solve a ground-water 

management problem.

90 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Define general water-management issues.

Meet with progessively larger groups of these entities.

Consider forming a technical advisory committee.

Define water-management items that can be controlled (decision variables).

Write objectives and constraints in commonly used words.

Write objectives and constraints as mathematical equations.

Identify the physically-based and political entities that make or significantly

 affect water-management decisions.

Define the water-management time frame (management horizon).

Formulate an optimization model to solve a specific problem.

Review formulation with water-management decision makers.

Review optimization results with decision makers.

Monitor key decision variables and constraints to determine ongoing

 success of the water-management plan.

Define and plan to collect additional hydrologic data needed to confirm

 critical water-management assumptions and conclusions.

Reformulate the optimization problem, if necessary.

Solve the constrained optimization model using selected software and,

 if necessary, a ground-water flow model.

Select constrained optimization software.

Determine method of calculating response of the ground-water flow system.

Identify and meet decision makers

Define the water-management problem

Solve the optimization problem

Develop water-management monitoring system

Implement water-management plan

Choose computer codes

Formulate the problem mathematically
Figures 49A−C each show the unit response at several 

observation wells to a simulated unit stress at one recharge 

basin. Figure 49D shows the unit response at one observation 

well (SBVMWD) to a simulated unit stress at several recharge 

basins. The curve labeled “Lytle” on figure 49D is the same 

curve labeled “SBVMWD” on figure 49A, and the curve 

labeled “Sweetwater” on figure 49D is the same curve labeled 

“SBVMWD” on figure 49B.

For a management horizon with a single stress period, 

such as a steady-state simulation, the response function is 

calculated by applying a unit stress for the entire period and 

observing the unit response in head at the end of the period. 

The unit stress can be applied at a single model cell or 

apportioned among a group of model cells. The unit response 

is observed at a single model cell and is the difference in 

simulated head with and without the unit stress. Therefore, to 

calculate a unit response, at least two model runs are required: 

one with no managed stresses and one for each managed stress 

that requires a unit response.

If the management horizon has multiple stress periods 

of identical length, such as the 32 1-year periods used in the 

optimization model of the San Bernardino area, use of unit 

response functions can take advantage of the linearity of the 

ground-water flow system. The unit response is calculated 

by simulating a unit value of stress for the first stress period 

and zero values for all subsequent stress periods. This input 

is essentially a unit pulse with the width of a single stress 

period. The response of head to this pulse is observed for all 

stress periods. The principle of superposition, which is the 

key assumption in use of response functions, allows the unit 

response function (pulse) to be shifted from one time period 

to another in order to simulate stresses that begin at any time 

within the management horizon, and superposition allows the 

individual responses to be summed at the end of each stress 

period as shown in figure 50 (Reilly and others, 1987). The 

two upper diagrams in figure 50 show response functions for 

a unit stress applied in year 1. The two lower diagrams show 

the response function for a unit stress applied in years 3 and 

5, which is simply the response function for year 1 shifted 

forward in time by 2 or 4 years.

The convention of positive and negative signs in the creation and use of response functions in ground-water optimization studies varies greatly and can cause significant problems 

in either formulation or interpretation of the optimization 

model. Pumpage in some studies is positive and in other studies negative. Increasing head in some studies is positive and in 

other studies negative. The sign convention used in this study 

is that recharge is positive, which causes a positive change 

in head and a positive response function; pumpage is negative, which causes a negative change in head and a negative 

response function.

The first step in creating the response-function part of 

the optimization model is to simulate the response of the 

aquifer to initial and boundary conditions and to all unmanaged stresses. This procedure involves eliminating all decision 

variables from the ground-water flow model or setting them 

at prescribed values. The simulation model then is used to 

calculate hydraulic head (hIbc

o, to) at each control (observation) 

location of interest (o) at the end of each stress period (to) over 

the entire management horizon. Subtracting the initial head at 

the beginning of the simulation (hInitial

o

) from initial and boundary condition head (hIbc

o, to) yields the initial and boundary 

condition response (rIbc

o, to); that is,

 rIbc

o, to = hIbco, to – hInitialo

 . (17)

This change in head represents the net effect of everything in the model, except the decision variables. In some 

formulations, an estimated or average value for some managed stresses is included as part of the unmanaged simulation 

in order to minimize the effect of hydraulic nonlinearities. 

In this case, the rIbc

o, to term also includes the effect of these 

background values, and the optimization model is used to 

define deviations from the background values. This technique 

is described in Danskin and Freckleton (1992) and Greenwald 

(1993).

The next step is to create a unit response function (ro, 

to, s, ta) for each managed stress. The basic idea is to use a 

unit pulse of recharge or discharge to cause changes in head 

throughout the area of interest and over the time frame of 

interest. This cause (unit pulse) and effect (change in head) 

is the response function. The technique typically involves 

application of a unit stress for a single decision variable (s) 

in the first stress period of the simulation (ta = 1). All other 

recharge, discharge, and boundary conditions are the same as 

those used during simulation of the initial and boundary condition response. The head (ho, to, s, ta) resulting from the unit stress 

is observed at all locations of interest (o) at the end of the first 

and all subsequent stress periods (to = 1, 2, 3 ...). Subtracting 

this head from the initial and boundary condition head yields 

the unit response function (ro, to, s, ta) for that decision variable, 

at all locations of interest and at all times of interest. That is, 

 ro, to, s, ta = hIbc

o, to – ho, to, s, ta . (18)

This procedure is repeated for each recharge or discharge component of the simulation model that is to be a managed part of 

the optimization model.

Once created, the unit response can be used to represent 

a unit stress applied during any single stress period throughout the management horizon. The response in head is simply 

shifted uniformly in time along with the applied unit stress. 

This procedure is illustrated in the lower graphs of figure 50. 

The capability of using a unit response for different time periods results from the linearity of the ground-water flow model 

and is a characteristic of superposition. The more nonlinear 

the flow model is, the more care is needed in creation and use 

of unit response functions. To minimize the effect of nonlinearities it may be necessary to create response functions for 

specific time periods and to use a different value of the unit 

stress.

Computer Models 91
Figure 49. Representative response of simulated hydraulic head to recharge in the San Bernardino area, California. Recharge 

simulated at A, Lytle Creek basin; B, Sweetwater basin; and C, Santa Ana River (upper) basin. Responses observed at selected 

observation wells at increasing distance from the recharge basin. Graph D shows responses at San Bernardino Valley Municipal 

Water District (SBVMWD). All responses are for the upper model layer and result from 10,000 acre-feet of recharge in the first 

year. Ground-water model area shown in dark gray.

92 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake Arrowhead

Silverwood

Lake

Cajon

Cable Cr

Cr

River

River

Plunge

Zanja The

Warm

Santa

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Seven Oaks Dam

Cr

15

215

10

215

15

A C

6

0

B

5

1

2

3

4

D

2

1

0

YEARS

RESPONSE, IN FEET

YEARS

San Bernardino Mountains

EXPLANATION

Redlands

Crafton Hills

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

Badlands

Shandin

Hills

Perris Hill

Artificial-recharge basin

Observation well and identifier

Fault or ground-water

barrier – May be concealed

or approximately located

Former marshland

Gabriel

Mts

San

San Bernardino Mountains

Redlands

San Bernardino

YUCAIPA BASIN

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Lytle Creek

basin

Sweetwater

basin

Santa Ana

River basin

Waterman

basin

Cone

Camp

(7Q4)

Newmark 4

(16E4)

Cone

Camp

(7Q4)

Highland Highland

0 6 KILOMETERS

0 6 MILES

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'

0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35

16

12

4

8

0

16

12

4

8

0

RESPONSE, IN FEET

SBVMWD

Newmark 4

Heap

Heap

(3Q1)

Tri-City

(9E2)

SBVMWD

(22D7)

WSB 13

(6H1)

WSB 1

(23P4)

W. Cram

(2J1)

SBVMWD

West San Bernardino 1 (WSB1)

West San Bernardino 13 (WSB13)

Observation well:

SBVMWD

W. Cram

Tri-City

Waterman

Lytle

Sweetwater

Santa Ana River

Observation well: Recharge basin:

Observation well:
In many cases, the value of the unit stress can be chosen 

to be the same magnitude as the value of the decision variable 

determined later by the optimization model. The unit stress, 

however, needs to be sufficiently large that the accuracy of 

the unit response is essentially unaffected by convergence and 

roundoff errors that occur during solution of the flow model. 

Also, the unit stress needs to be sufficiently large that an accurate response is generated in all locations of interest, as soon 

as is needed. If the unit stress is too small, the response will 

not reach all areas of the model or will not reach them soon 

enough to be numerically significant. If these conditions are 

met, then the unit response can be included as a reliable part of 

the optimization model. Finally, use of round numbers for the 

unit stress (1 ft3/s, 100 acre-ft/yr) tends to minimize errors in 

formulating the optimization model.

The development of response functions allows total 

drawdown (d) to be calculated from unit responses, values 

of decision variables, and the initial and boundary condition 

response. For example,

 do, to = (rIbc

o, to) + [SUM s=1, 

 ndv [SUM ta=1, ntp (ro, to, s, ta) (qs, ta)]] , (18)

where

d is total drawdown from managed and unmanaged stresses and from initial and boundary conditions, in ft;

r

Ibc is the response of simulated hydraulic head from initial 

and boundary conditions and from all unmanaged 

stresses, in ft;

r is the unit response of simulated hydraulic head, in ft 

per ft3/s; and

q is a managed stress, represented in the ground-water 

flow model by recharge or discharge for a model cell 

or group of model cells, in ft3/s; 

and indices

Figure 50. Superposition of response functions. Note different scale of graphs. Location of recharge (Santa Ana River upper 

basin) and water-level response (Cone Camp and SBVMWD) shown in figure 49.

Computer Models 93

0

0

2

4

6

8

10

12

14

16

5 10 15 20 25 0 5 10 15 20 25

0

0

2

4

6

8

10

12

14

16

5 10

TIME, IN YEARS TIME, IN YEARS

15 20 25

0

10

0

20

30

40

10

0

20

30

40

0.5

RECHARGE, IN THOUSANDS OF ACRE-FEET PER YEAR

10

0

20

30

40

10

0

20

30

40

RECHARGE, IN THOUSANDS OF ACRE-FEET PER YEAR

CHANGE IN HYDRAULIC HEAD FOR UPPER MODEL LAYER, IN FEETCHANGE IN HYDRAULIC HEAD FOR UPPER MODEL LAYER, IN FEET 1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 5 10 15 20 25

Total response Total response

Response function

Recharge in Santa Ana River upper basin

Recharge in Santa Ana River upper basin

Near recharge area

(4,000 feet from recharge, at Cone Camp)

In former marshland

(48,000 feet from recharge, at SBVMWD)

year 3

year 1

Response for unit

stress applied in:

year 5

year 3

year 1

Response for unit

stress applied in:

year 5

Response function
o is an index indicating the location where simulated 

hydraulic head is observed, represented in the 

ground-water flow model by a single model cell;

to is an index indicating the time period when the response is observed, calculated in the ground-water 

flow model at the end of a stress period;

s is an index indicating a specific managed stress;

ndv is the number of decision variables (managed stresses) 

having response functions;

ta is an index indicating the time period when the managed stress is applied, represented in the groundwater flow model by a stress period; and

ntp is the number of time periods simulated in the management horizon.

This relation is sometimes expressed in compact matrix notation as, 

 D = RIbc + R Q , (19)

where

D is a matrix of total drawdown at all control locations, at 

all time periods, in ft;

RIbc is a matrix of responses, at all control locations, at all 

time periods, resulting from initial and boundary conditions and from all unmanaged stresses, in ft;

R is a matrix of unit responses, at all control locations, at 

all time periods, from all managed stresses, applied at 

all time periods, in ft per ft3/s; and

Q is a matrix of all managed stresses, applied at all time 

periods, in ft3/s.

In some formulations, it is advantageous to calculate simulated 

hydraulic head for use in the optimization model. Using results 

from equation 18, 

 hMan

o, to = hInitialo, to + do, to (20)

where

hMan is managed hydraulic head, in ft;

hInitial is initial hydraulic head, in ft; and

d is total drawdown, in ft, caused by managed and 

unmanaged stresses and by initial and boundary 

conditions;

or in matrix notation,

 HMan = HInitial + RIbc + R Q (21)

where

HMan is a matrix of managed hydraulic heads, in ft; and

HInitial is a matrix of initial hydraulic heads, in ft.

Because response functions are an encapsulated form of 

the ground-water flow model, they can be instructive by themselves prior to being used to develop the optimization model. 

This additional benefit was demonstrated during the present 

study of the San Bernardino area. Many of the key hydraulic 

principles of managing recharge were identified when the 

response functions were developed for each of the artificialrecharge basins. Unit responses were calculated using a 1-year 

pulse of 10,000 acre-ft/yr during the first year, and zero flux in 

subsequent years. This relatively large unit stress was needed 

to create a sufficiently large response in heads throughout the 

simulated area as shown in figures 49 and 50. The large unit 

stress does create a spike in simulated heads near the artificialrecharge basin, but fails to create much change in head in the 

vicinity of the former marshland. 

Of particular interest is that although the recharge occurs 

only in the first year, the maximum change in simulated 

head does not necessarily occur in the first year. In fact, the 

response to recharge from the artificial-recharge basin adjacent 

to the Santa Ana River is not fully felt in the vicinity of the 

former marshland (SBVMWD, fig. 49C) for more than 30 

years. This time lag results from the shape of the Bunker Hill 

and Lytle Creek basins, from the large area of high storage (specific yield), and from the great distance between the 

artificial-recharge basin and the control location. The time lag 

also illustrates the difficulty in intuitively answering complex 

water-management questions involving many decision variables and control locations.

An equally important effect shown in figure 49D is how 

recharge in different artificial-recharge basins creates substantially different short-term effects on simulated heads in the 

vicinity of the former marshland. For example, the effect of 

recharge in the Waterman basin peaks in year seven. In contrast, the effect from recharge in the Santa Ana River basin has 

not peaked even after 30 years. Despite short-term differences, 

the longterm effect of recharge is similar for all basins. These 

results suggest that different recharge basins are ideally suited 

for managing either short-term or longterm ground-water levels in the former marshland. Response of simulated heads near 

the site of recharge is similar for all basins, probably because 

of similar aquifer characteristics near each basin. Analysis of 

the unit response functions such as those shown in figure 49

demonstrates the benefit that can be gained from setting up the 

optimization model, even before an optimal solution is found.

94 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
The major limitation in using response functions in 

linear or quadratic programming is that the response must be 

linear with respect to the applied stress. This in turn requires 

that the ground-water flow model must be linear. Over the 

past two decades, however, ground-water flow models have 

become increasingly nonlinear. As computational capabilities have increased, additional nonlinearities have been added. 

Optional packages, such as those listed in table 14, frequently 

are included with the standard computer code so that the 

aquifer system can be simulated more accurately. Some of 

these options include: (1) use of piecewise-linear recharge and 

discharge relations (streams, evapotranspiration), (2) recalculation of transmissivity and storage coefficients based on 

simulated hydraulic heads, and (3) dewatering and rewetting 

of model cells (McDonald and Harbaugh, 1988).

Methods have been developed to approximate typical nonlinearities such as those induced by stream recharge 

(Danskin and Gorelick, 1985), time-varying transmissivity 

(Danskin and Gorelick, 1985; Willis and Finney, 1985), and 

evapotranspiration (Danskin and Freckleton, 1992; Greenwald, 1993). These methods, however, can require significant computational capabilities and time, and some methods 

require use of another optimization technique (mixed-integer 

programming). For highly nonlinear ground-water problems, 

such as solute transport, nonlinear optimization techniques are 

required. Fortunately, many common ground-water management problems can be analyzed, at least initially, through the 

use of linear programming.

Design and development of the ground-water flow model 

for the San Bernardino area required achieving a balance 

between meeting the requirement of linearity and providing 

an accurate simulation of the valley-fill aquifer. Despite the 

restrictions of linear programming, it was necessary to include 

three nonlinearities in the ground-water flow model—streamflow routing, evapotranspiration, and underflow across the 

San Jacinto fault near the Santa Ana River. To determine how 

much these model nonlinearities alter the optimal solution, 

results of the optimization model were re-simulated with the 

full ground-water flow model and compared. A small disparity is to be expected because of the nonlinearities. A small 

additional disparity is caused by numerical approximations in 

the ground-water flow model; this difference is generally less 

than the number of decision variables times the closure criteria 

of the flow model solution and can be controlled sufficiently 

well by reducing the closure criteria. This technique was used 

by Yeh (1990) to critique optimization results from a similar, 

mildly nonlinear ground-water flow model, and the technique 

is included as an option in the optimization computer code by 

Greenwald (1993).

For water-management problems investigated as part of 

this present study, the head difference caused by hydraulic 

nonlinearities was acceptably small, and the linear-programming solutions were sufficiently accurate. The presence of a 

large disparity between the solutions, however, could occur 

for other optimization problems in the San Bernardino area 

and would indicate the need for another approach, such as the 

iterative techniques used by Danskin and Freckleton (1992) or 

Greenwald (1993). 

Mathematical Form of Objectives and 

Constraints

Water-management objectives and constraints are 

expressed in the constrained optimization model as mathematical equations. The objective function (equation) defines a specific objective that is to be maximized or minimized subject 

to a set of constraint equations. To answer a slightly different 

water-management question, a slightly different objective 

function can be combined with the same or nearly the same set 

of constraint equations. Commonly, reformulation of the optimization model to answer a related water-management question requires only that a specific constraint equation be used 

as the objective function, and the former objective function be 

included as a constraint. This capability of slight, but powerful 

modifications makes optimization techniques in general and 

this model in particular, an efficient way to investigate related 

water-management questions. A slightly different formulation 

of the optimization model not only provides additional insight 

about overall water management, but also can be used to represent the specific viewpoint of a different water-management 

entity. The following objectives and constraints summarize the 

major water-management issues in the San Bernardino area as 

of 1998. These issues are described in detail in a subsequent 

section of this report entitled “Water-Management Issues.”

Formulation of the objective function and constraints for 

the optimization model uses the same discretization of time 

as the ground-water flow model, which is used to calculate 

response functions. The shortest time period representing uniform stress in the flow model is a calendar year; therefore, the 

optimization model also uses calendar years. Use of a shorter 

time period for the optimization model is possible, but not recommended unless the ground-water flow model is revised and 

recalibrated using the shorter time period. The management 

horizon for the optimization model is defined as any number 

of sequential stress periods, or in this case calendar years. For 

the water-management scenarios described later in this report, 

a horizon of 32 years was used. The following formulation 

of objectives and constraints is sufficiently general so that a 

different management horizon could be used with only minor 

modifications to the objectives and constraints.

Computer Models 95
Objective Function

The objective function (equation) includes decision 

variables representing recharge of imported water, groundwater pumpage, and the cost of each of these. Other recharge 

and discharge components of the ground-water flow model are 

included in the optimization model as part of the right-hand 

side (RHS). Although these ground-water fluxes are not managed explicitly, they are an implicit part of the optimization 

model. Use of the RHS to account for unmanaged (background) stresses is described on page 91 of this report and in 

greater detail by Danskin and Freckleton (1992) and Gorelick 

and others (1993).

Imported water can be distributed via the Foothill pipeline to several artificial-recharge basins in the San Bernardino 

area (fig. 11). If a water-management goal is to limit use of 

this resource, then the objective function is to

 Minimize Z = sum k=1, ny [sum iar=1, 

 nar (QArtRech

iar, k)] , (22a)

where

iar is the index for a specific artificial-recharge 

basin;

k is the index for a specific year;

nar is the total number of artificial-recharge basins; 

ny is the total number of time periods (years) in the 

water-management period; and

QArtRech

iar, k is the quantity of imported water distributed to 

artificial-recharge basin iar, during time period 

k, in acre-ft.

Distributing imported water to an additional, proposed artificial-recharge basin can be analyzed by including the proposed 

basin in equation 22a.

The actual quantity of water recharging the valley-fill 

aquifer is slightly less than the quantity of water distributed to 

the artificial-recharge basin. During the calibration period of 

the ground-water flow model (1945–98), the recharge rate of 

imported water was assumed to be 90 percent. The remaining 

10 percent of the water was assumed to be lost to evapotranspiration. If the water-management goal is to maximize the 

quantity of imported water that is recharged to the valley-fill 

aquifer, then a coefficient reflecting the efficiency of recharge 

for each basin could be included in equation 22a. For example,

 Maximize Z = sum k=1, ny [sum iar=1, 

 nar (rriar, k QArtRech

iar, k)], (22b)

where

rriar, k is the recharge rate for artificial-recharge basin iar 

during time period k, expressed as a decimal fraction.

If minimizing the cost of supplying imported water for 

recharge is the primary water-management goal, then the 

objective function becomes

 Minimize Z = sum k=1, ny [sum iar=1, 

 nar (CImpWater

iar,k QArtRechiar, k)] , (22c)

where

CImpWater

iar, k is the cost of imported water distributed to basin 

iar, during time period k, in dollars per acrefoot.

The value of CImpWater

iar, k is determined by agreement with the 

State Water Project that supplies the imported water (California Department of Water Resources, 1995b). This cost, however, can vary depending on whether water was banked with 

the State Water Project and the source and timing of electricity 

used to import the water. For example, peak use of electricity 

can be two to three times more expensive than off-peak use. 

In 1998, the minimum value of CImpWater was about $100 per 

acre-ft to convey water from San Francisco Bay to the afterbay 

of the Devil Canyon powerplant. A small additional cost is 

needed to pump this water to different artificial-recharge 

basins within the San Bernardino area; therefore, CImpWater is 

slightly different for each basin. Equation 22c does not assure 

that imported water is distributed to the artificial-recharge 

basins with the highest recharge rates. Achieving this additional water-management goal will depend on the specific set 

of constraints involving the valley-fill aquifer.

As of 1998, several new production wells were under 

construction in the San Bernardino area. In addition, several wells have been proposed to provide additional water 

for municipal use, to restrict the transport of ground-water 

contaminants, or to lower ground-water levels near the former 

marshland. The effect of these wells can be included in the 

optimization model either individually or as defined sets of 

wells. The following formulation minimizes the total quantity 

of ground-water pumpage over the management horizon. The 

formulation considers individual wells, each having a fixed 

ratio of extraction from the upper and lower layers of the 

ground-water flow model. Specifically,

 Minimize Z = sum k=1, ny [sum iw=1, 

 nw (QPump

iw, k)] , (23)

where

iw is the index for a specific well;

k is the index for a specific time period;

nw is the total number of wells; and

QPump

iw, k is the quantity of pumpage from well iw during 

time period k, in acre-ft.

96 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Both existing and proposed wells can be included in equation 

23 as long as the extraction ratio from the two model layers 

is known or can be defined. The extraction ratio for all wells 

with pumpage during 1945–98 was defined during calibration 

of the ground-water flow model.

If it is important to analyze the effect of different ratios of 

extraction from the two model layers, then the extraction from 

a single well could be separated into two discharge quantities. 

Each discharge would be simulated in the respective layer of 

the ground-water flow model, and the two discharge quantities 

would be linked in the optimization model with a mass-balance constraint, as illustrated in equation 13c on p. 85. This 

more detailed formulation allows the effect of different perforated intervals for the well to be critiqued with the optimization model. 

If the water-management goal is to minimize the cost of 

pumpage, then the objective becomes a quadratic equation, 

such as described on p. 86 of this report. For a single time 

period, the equation is

 Minimize Z = ce eiw QPump

iw LTotaliw , (24a)

where

ce is the cost of electricity, in dollars per foot of lift per 

acre-foot;

eiw is the efficiency of well iw, expressed as a decimal 

fraction;

LTotal

iw is total lift at well iw, in ft; and

QPump

iw is the quantity of pumpage from well iw, in acre-ft.

Expanding total lift into separately calculated components 

yields

Minimize Z = ce eiw QPump

iw (LInitialiw + LIbciw + LManiw) (24b)

where

LIbc

iw is lift at well iw resulting from initial and boundary 

conditions and from unmanaged stresses, in ft;

LInitial

iw is initial lift at well iw, in ft; and

LMan

iw is total lift at well iw resulting from all managed 

stresses, in ft.

For a single stress period, equation 24b becomes

Minimize Z = sum iw=1, nw [ce eiw (QPump

iw)[LInitialiw+ 

 LIbc

iw + sum s=1, ns (QPumpiw riw, s)] , (24c)

where

ns is the total number of stresses; and

r

iw, s is the response of hydraulic head at location iw 

resulting from pumpage at location s, in ft. 

For multiple stress periods, the formulation becomes more 

cumbersome because pumpage in one time period can create 

additional lift in a later time period, as is indicated by the 

response functions (fig. 50). Therefore, equation 24c becomes

Minimize Z = sum k=1, ny [sum iw=1, nw [ce eiw, k 

 (QPump

iw, k)[LInitialiw + LIbciw, k + sum s=1, ns [sum ta=1, 

 ny (QPump

iw, k riw, k, s, ta )]] , (24d)

for ta <= k, 

where

r

iw, k, s, ta is the response of hydraulic head at location 

iw during time period k resulting from pumpage at location s 

during time period ta, in ft.

Although commonly used for water-management evaluations, equations 24d is a significant simplification of the actual 

operation of a production well and, therefore, needs to be used 

with caution. Well efficiency varies with discharge; response 

of lift to pumpage is slightly nonlinear; and pump capacities 

and bowl settings typically apply for a limited range of lift. If a 

change in lift requires either moving the pump or resizing the 

bowls, then a significant cost is incurred that is not included in 

equation 24d.

Many water-management goals involve both recharge and 

pumpage. These goals can involve maintaining an adequate 

quantity of ground water stored in the valley-fill aquifer or 

simply minimizing the magnitude of any change in present 

water-management operations. If the optimization model does 

not include both recharge and pumpage in the objective function, then it is possible that an optimal solution that minimizes 

recharge (eq. 22a) would require an unnecessarily high pumpage, or vice versa. To correct this possible limitation, the total 

quantity of recharge and pumpage can be minimized by

 Minimize Z = sum k=1, ny [sum iar=1, 

 nar (QArtRech

iar, k) + sum i=1, nw (QPumpiw, k)] , (25a)

which results from combining equations 22a and 23. 

If the objective is to minimize the total cost of recharge 

and pumpage, then the objective becomes

Minimize Z = sum k=1, ny [sum iar=1, nar [CImpWater

iar, k

QArtRech

iar, k] + sum iw=1, nw [ce

 eiw, k QPump

iw, k (LInitialiw + LIbciw, k + 

sum s=1, ns [sum ta=1, ny (QPump

iw, k riw, k, s, ta )])] , (25b)

for ta <= k, which results from combining equations 22c and 

24d. The method for calculating pumping cost for a well is 

described on p. 86 and in equations 15a–c.

Computer Models 97
Constraints

Water Supply and Water Distribution

The mathematically optimal value of the decision variables is constrained by various equations representing watersupply and water-distribution constraints. These constraints 

assure that adequate water is supplied through the present 

distribution system and that the quantities determined by the 

optimization model are physically possible.

For example, artificial recharge in each basin must be 

less than or equal to the maximum recharge capacity of that 

basin, and the sum of artificial recharge in all basins must be 

less than or equal to the total quantity of water that is available 

from the State Water Project. During all years and even more 

so during droughts, the maximum quantity of imported water 

is less than 100 percent of the entitlement value of 102,600 

acre-ft/yr (table 5). Expressed as a decimal fraction, the 

percentage of entitlement (PImpWater

k

) ranges from 0.10 to 0.60, 

depending on the particular year (k). These two water-supply 

constraints, applied for each time period k, are,

rriar, k QArtRech

iar, k ≤ maximum recharge capacity for each 

basin iar (26a)

and

sum iar=1, nar [QArtRech

iar, k] ≤ (PImpWaterk

) (102,600 acre-ft/

yr). (26b)

Water supply to each artificial-recharge basin also must be less 

than the capacity of the conveyance structures connecting the 

California Aqueduct to the basin. Specifically, for each time 

period k,

QArtRech

iar, k ≤ maximum turnout capacity for basin iar 

 (26c)

and

sum iar=1, nar [QArtRech

iar, k] ≤ maximum capacity of the 

Foothill pipeline. (26d)

Similarly, maximum pumpage from each individual site 

is restricted by well, pump, and aquifer characteristics, and 

total pumpage from all sites is restricted by a maximum value 

derived from legal adjudication or from an evaluation by local 

water managers based on distribution capabilities or on anticipated demand. These constraints are expressed for each time 

period (k) as

QPump

iw, k ≤ maximum historical or estimated production at 

each site iw, (27a)

and

sum iw=1, nw (QPump

iw, k)] ≤ maximum annual pumpage in 

the area. (27b)

Or to restrict cumulative production over a period of years,

sum k=1, ny [sum iw=1, nw (QPump

iw, k)] ≤ maximum 

cumulative pumpage in the area. (27c)

Ground-Water Level

Management of recharge and pumpage in the San Bernardino area is constrained by requirements on ground-water 

levels. In the vicinity of the former marshland, ground-water 

levels need to be sufficiently low to prevent possible liquefaction and sufficiently high to prevent additional land subsidence. In the alluvial fan areas, ground-water levels need to be 

maintained sufficiently high to assure a continuous supply of 

ground water to nearby wells.

These water-management constraints are represented in 

the optimization model in the following general way for each 

observation water-level control location (o) at each time period 

(k),

HInitial

o, k + [sum iar=1, nar [sum ta=1, ny (ro, k, iar, ta QArtRech

iar, ta)] + [sum iw=1, nw [sum ta=1, ny (ro, k, iw, ta QPumpiw, ta)]] ≤

HLimitUp

o, k (28a)

or

HInitial

o, k + [sum iar=1, nar [sum ta =1, ny (ro, k, iar, ta QArtRech

iar, ta)] + [sum iw=1, nw [sum ta=1, ny (ro, k, iw,ta QPumpiw, ta)]] ≥

HLimitLo

o, k (28b)

for ta <= k, where

HLimitUp

o, k and HLimitLo

o, k

are the upper and lower limits, respectively, of hydraulic head at location o 

during time period k.

Because the response function calculates the induced drawdown from managed stresses, it is sometimes more convenient 

to represent the ground-water-level constraint as a drawdown 

constraint. For example,

sum iar=1, nar [sum ta=1, ny (ro, k, iar, ta QArtRech

iar, ta)] + 

sum iw=1, nw [sum ta=1, ny (ro, k, iw, ta QPump

iw, ta)] 

 ≤ DLimitUp

o, k (29a)

or

sum iar=1, nar [sum ta =1, ny (ro, k, iar, ta QArtRech

iar, ta)] + 

sum iw=1, nw [sum ta =1, ny (ro, k, iw, ta QPump

iw, ta)] 

 ≥ DLimitLo

o, k (29b)

for ta <= k, where

DLimitUp

o, k DLimitLoo, k are the upper and lower limits, 

respectively, of drawdown at location o during time period k.

98 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
The total number of constraint equations increases rapidly 

with the dimensions of iar, iw, o, and k. For example, a 

problem with 5 recharge sites, 15 well sites, 50 observation 

locations, and 32 time periods can require more than 5,000 

constraint equations. Although optimization techniques are 

designed to address large problems, an optimization model 

with more than several thousand constraint equations can be 

cumbersome to work with, and the results can be time-consuming to interpret. Computational time typically is not a 

major concern in solving the optimization model itself, but 

computational time may become a major impediment if a 

ground-water flow model simulation is needed to calculate 

response functions for each of many decision variables, such 

as iar and iw. 

Ground-Water Quality

Ground-water-quality issues can be included in the 

optimization model through the use of hydraulic gradients 

computed by the ground-water flow model. The technique, 

as described by Lefkoff and Gorelick (1986), involves adding 

a hydraulic-gradient constraint in the optimization model to 

control movement of a selected water-quality constituent at 

an identified location in the aquifer. The flow model, through 

response functions, is used to calculate the change in gradient 

caused by the decision variables. The basic idea is to define 

a hydraulic gradient across the edge of a contaminated area, 

then to constrain this gradient so that the contamination does 

not spread further through the basin. The role of the optimization model is to control the spread of the contamination while 

simultaneously considering other water-management issues in 

the basin.

Formulation of the hydraulic-gradient constraint involves 

selecting a control point inside and outside the contaminated 

area. Typically, points are chosen for convenience at the center 

of cells in the ground-water flow model. Hydraulic head at 

each control point is calculated as the sum of the head resulting from unmanaged conditions and the drawdown resulting 

from managed stresses. Using the method of response functions described above for each managed stress (qs

),

 ho, k = hIbc

o, k + ro, k qs, k , (30)

for each control point. The hydraulic-gradient constraint can 

be written for each gradient pair p during time period k as,

 (hGradIn

p, k - hGradOutp, k) / dGradp ≤ GTargetp, k , (31)

where

hGradIn

p, k is total hydraulic head at the control point inside 

the contaminated area, in ft;

hGradOut

p, k is total hydraulic head at the control point outside 

the contaminated area, in ft;

dGrad

p is the distance between the inside and outside 

control points, in ft; and

GTarget

p, k is the target gradient, in ft per ft.

The target gradient is chosen to restrict the advective flow of 

ground water along the path defined by dGrad

p

. Typically, the 

gradient is chosen to be zero in order to prevent flow away 

from the contaminated area. A slightly negative gradient may 

be used to induce ground-water flow toward the contaminated 

area. A reduced positive gradient can be used to reduce the 

rate of transport of ground water away from the contaminated 

area.

By incorporating information about the effective porosity 

and hydraulic conductivity between the two control points, the 

hydraulic-gradient constraint can be reformulated as a velocity 

constraint. For example,

(Kp / pe

p

) (hGradIn

p, k - hGradOutp, k) / dGradp ≤ VTargetp, k , (32)

where

Kp is the horizontal hydraulic conductivity along length 

dGrad

p

 for gradient pair p, in feet per second (ft/s);

pe

p is the effective porosity along length dGradp, k for 

gradient pair p, dimensionless; and

VTarget

p, k is the target velocity for gradient pair p during time 

period k, in f/s.

A negative target velocity implies ground-water flow toward 

the contaminated area. Additional maximum and minimum 

constraints involving hGradIn and hGradOut may be necessary to 

restrict the optimal solution to realistic values of head in the 

vicinity of the hydraulic-gradient or velocity constraints. For 

example, head (h) at any point can be constrained by

 h ≤ ATop (33a)

and

 h ≥ ABot (33b)

where

ATop is altitude of the land surface, in ft; and

ABot is altitude of the bottom of the aquifer, in ft.

Equation 33a assures that inadvertent flooding of the land 

surface does not occur, and equation 33b assures that the 

aquifer is not dewatered. Similar constraints can be used to 

assure that managed drawdown along the contaminated boundary is physically reasonable and that saturated thickness does 

not change significantly so that the approximation of hydraulic 

linearity used to develop the response functions remains valid.

Computer Models 99
Although the use of hydraulic-gradient and velocity 

constraints is a powerful and useful approach, it has important 

limitations. The ground-water flow model does not simulate 

the actual transport of water-quality constituents (solutes), 

nor was the model calibrated using solute data. Rather, the 

flow model simulates advective Darcian flow in a two-layer, 

quasi-three-dimensional approximation of the valley-fill 

aquifer (eqs. 8 and 9). Neither dispersion, nor retardation of a 

solute is accounted for. Porosity, an aquifer characteristic that 

is required to compute the rate of movement of a solute, is not 

part of the flow model. Additionally, the vertical complexity 

of the 1,000-foot-thick valley-fill aquifer is highly simplified 

by considering only two layers. Nevertheless, the flow model 

may simulate the directional movement of a conservative 

solute, such as chloride, reasonably well because advective 

transport typically dominates dispersion in a regional, coarsegrained aquifer with steep hydraulic gradients like that found 

in San Bernardino. These limitations are inherent in all uses 

of a ground-water flow model to approximate solute transport, 

including the use of particle-tracking programs such as MODPATH (Pollock, 1994).

Economic

Depending on the formulation of the optimization model, 

economic considerations can be included either as a part of 

the objective function or as part of the constraints. If the 

objective is simply to minimize total recharge and pumpage 

(eq. 25a), then the cost of managed recharge and pumpage can 

be included as a constraint. For example,

sum k=1, ny [sum iar=1, nar (QArtRech

iar, k CImpWaterk

) + 

sum iw=1, nw (QPump

iw, k CPumpiw, k)] ≤ target cost. (34)

The target cost can be defined by historical operations or from 

planned future operations. Economic constraints can involve 

both the combined cost of operation, such as in equation 34, 

and the individual cost of operating a single well or artificialrecharge basin. For example, the cost of pumping well 1 during time period 3 can be constrained by

QPump

1, 3 CPump1, 3 ≤ maximum allowable cost for well 1 in 

year 3. (35)

Several pressure zones are used within the San Bernardino area to distribute pumped ground water (Camp 

Dresser and McKee, 1991). The zones operate at the following 

pressures, expressed as head: City of San Bernardino lower 

zone (1,250 ft), City of San Bernardino middle zone (1,316 ft), 

Baseline feeder (1,370 ft), City of San Bernardino upper zone 

(1,415 ft), City of San Bernardino Sycamore zone (1,580 ft), 

and Santa Ana Valley pipeline (1,850 ft). In order for ground 

water to be used within the valley, except locally for agriculture or domestic purposes, the water must be lifted to the 

pressure of the particular distribution line. In some water-management scenarios, this additional lift (LZone) will add substantially to the cost of pumpage. To incorporate this additional 

lift in the optimization model, LZone needs to be added to the 

initial lift LInitital in equation 15b to account for pumped ground 

water being delivered to the point of distribution. In this way, 

the additional pumping cost is incorporated in CPump

iw, k and can 

be included either in an objective function (eq. 24b) or in a 

constraint (eq. 34).

Fixed costs of operation, such as installation of additional 

wells, sometimes are included in an optimization model, but 

this procedure requires the use of integer programming, a 

technique that can significantly increase computational time 

(Schrage, 1991). Therefore, fixed pumpage and recharge costs 

were considered heuristically outside the optimization model 

for the San Bernardino area. For example, additional 16- to 

20-inch production wells commonly cost at least $500,000 

each for drilling, pump, motor, and site preparation (Camp 

Dresser and McKee, 1991). Additional 48-inch-diameter pipelines to distribute water for municipal use cost approximately 

$1.3 million per mile (Camp Dresser and McKee, 1991). 

These costs can be used to balance the locations of wells with 

the costs of pumpage, and to compare different configurations 

of wells.

Bounds

Setting limits (bounds) for each decision variable can 

be an efficient way of constraining an optimal solution. For 

example, both the MINOS and GAMS software packages use 

an implicit non-negativity bound for each decision variable 

in order to reduce the computational time needed to solve a 

linear-programming problem. Other limits, including an upper 

bound, can be specified for each variable, for example

 BLow ≤ decision variable ≤ BUp (36)

where BLow and BUp are lower and upper limits, respectively. 

This is an efficient way to define the physical limits of a 

decision variable. For example in the optimization model of 

the San Bernardino area, bounds can be used in lieu of some 

water-supply constraints. Additionally, use of bounds instead 

of constraints is recommended for large linear-programming 

problems with many constraints.

100 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Use and Limitations

The constrained optimization model of the San Bernardino area is a powerful tool for synthesizing complex 

water-management issues and for quantitatively comparing 

different methods of operation. However, analysis of a complex water-resource problem requires a systematic consideration of many different physical, political, and societal issues. 

Even when considering the physical issues, appropriate use of 

an optimization model is to provide additional information that 

will aid in making better, more informed decisions (Hillier and 

Lieberman, 1980, p. 3–5). Not all issues can be included in 

the model, nor should they be if the model is to be useful. And 

ultimately, the model, despite whatever degree of complexity 

is incorporated, is only a simplification of the real world.

Although optimization techniques can be powerful, the 

terminology can be misleading. True, an optimal solution 

probably is the most anticipated result from a linear-programming model, such as the one used in this study, and the optimal solution does define the best answer that can be achieved 

for a specific model formulation. But it is unlikely that the 

optimal solution is globally optimal for all water-management 

concerns that are present in a real system. There always will 

be additional concerns that could be included in a larger, more 

comprehensive optimization model. For nonlinear optimization, such as might be used to analyze a ground-water system with a time-varying approximation of transmissivity, an 

optimal solution is even more tenuous. For example, it is not 

possible to prove that the optimal solution from a nonlinear 

optimization model is globally optimal and not simply one of 

many different suboptimal solutions.

The key, therefore, is to define a sufficiently complex 

optimization model that includes the decision variables and 

constraints with the greatest hydrologic impact on a watermanagement issue. As in any modeling process, even initial 

formulation of the optimization model can be insightful. The 

formulation step requires choosing which components are 

most important. Objectives and constraints must be defined 

precisely and quantitatively—a process that commonly is 

more difficult and time-consuming than it first appears. Initial 

use of the optimization model can provide immediate insights 

by defining the feasibility space of potential solutions and by 

determining whether specific proposed operational plans are 

even feasible. 

In advanced use of the optimization model, various 

proposed water-management plans can be compared quantitatively. The most important decision variables can be identified, and equally important, the binding constraints can be 

identified. If necessary, key hydrologic characteristics can be 

verified with additional data collection prior to implementing 

a specific water-management plan. If the optimization process 

results in greater hydrologic insight for the water managers 

and an improved solution to a water-management problem 

(fig. 51), then the optimization model will have been useful.

Figure 51. Water-management solutions.

Computer Models 101

Best theoretical solution to objective

Near optimal strategies that satisfy

 water-management goals

Physically possible, but not desirable

Risky; perhaps physically impossible

Not physically possible

Optimal solution

Feasible

solutions

Water-Management Solutions

Infeasible

solutions
Although constrained optimization techniques can be 

exceptionally instructive, other traditional hydrologic investigations need to be combined with use of an optimization 

model. Concurrent collection of data, development and use of 

other mathematical models, and monitoring of the physical 

system all are needed to solve a typical water-management 

puzzle, as illustrated in figure 52. Information gained from 

each piece of the puzzle contributes in a different way to creating a more informed water-management decision.

The limitations that are specific to the optimization model 

of the San Bernardino area mostly are derived from limitations of the ground-water flow model that is used to calculate 

response functions. The true three-dimensional complexity 

of the aquifer system—which may be important in managing 

some water-quality issues—is not fully represented in the flow 

model, and thereby in the response functions used in the optimization model. Detailed data from multiple-depth monitoring 

wells (figs. 24 and 52) can be used to compensate for some of 

this simplification.

The slight nonlinearity of the ground-water flow model, 

which is caused by the piecewise linear and nonlinear 

approximation of some recharge and discharge components, 

may require adjustment to some results from the optimization model. Response functions that are calculated when 

simulated heads are near land surface will differ from those 

calculated when simulated heads are greater than 15 ft below 

land surface. Therefore, optimal pumpage calculated using the 

differents sets of response functions also will differ. In general, 

lowering simulated heads will require a greater pumpage if 

either evapotranspiration or gaining streams are simulated 

during the time period used to calculate the response functions. In this case, the additional pumpage can be as much as 

the quantity of evapotranspiration or gains in streamflow, as 

demonstrated by Danskin and Freckleton (1992). The potential 

adverse effects of these nonlinearitities can be determined by 

resimulation of the optimal values in the ground-water flow 

model. This resimulation is facilitated by an option in the 

MODMAN software, but is much more time-consuming when 

using GAMS software.

Limitations regarding costs include an assumption that 

a constant non-discounted value of dollars is sufficient to 

analyze pumping-cost alternatives. Because costs can be difficult to estimate and can change significantly during the time 

it takes water managers and the public to evaluate potential 

management plans, use of the optimization model may benefit 

from a comparison of quantities of water, rather than costs of 

water.

Figure 52. Water-management puzzle.

102 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Basinwide

Ground-Water

 Flow Model

Climate

Model Satellite

Data

Precipitation and

Surface-Water Gages

Smaller Scale

Models

Surface-Water

Model Monitoring Network of Wells

Constrained

Optimization Model

Drilling Program

Water-Quality Analyses

Luck
An important final caveat, similar to one regarding 

predictive use of the ground-water flow model, is that optimal 

values of recharge and discharge that are determined by the 

optimization model need to be reasonably close to calibrated 

values in the ground-water flow model. Recharge or discharge 

values that are significantly different from those used during 

calibration may prompt hydrologic conditions that are not well 

simulated by the flow model, for example dewatering of a 

hydrogeologic unit, compaction of the aquifer, or flooding of 

the land surface.

Evaluation of Selected WaterManagement Alternatives

Future water management in the San Bernardino area 

of southern California was evaluated with the aid of groundwater flow and constrained optimization models described 

in this report. Using the models, seven water-management 

scenarios were developed to quantify and to better understand the important characteristics of water management in 

the San Bernardino area. The scenarios are not intended to 

be a specific plan to adopt and follow. Actual management is 

too complex to be adequately represented in a single simulation. Rather, the scenarios were designed with the goal of 

demonstrating important hydrogeologic features in the area, 

such as recharge of imported water along the base of the 

San Bernardino Mountains or pumpage near the San Jacinto 

fault. Improved understanding of these features will permit a 

comprehensive water-management plan to be developed by the 

local water managers.

A management horizon of 32 years was chosen to 

investigate the longterm effects of major water-management 

issues affecting the San Bernardino area. Selection of the 

horizon was based primarily on two criteria. First, at least two 

decades are needed for the effects of recharge and discharge 

in different parts of the Bunker Hill and Lytle Creek basins to 

be communicated to all other parts of each basin. As shown 

in figure 49, the simulated response of ground-water levels in 

the former marshland to artificial recharge near the base of the 

mountains can take more than 25 years to be fully felt. 

Second, the management horizon needs to capture 

the historical variability of surface-water runoff in the San 

Bernardino area. An analysis of annual discharge data for the 

Santa Ana River identified a recent 16-year climatic cycle 

(1983–98) that has nearly the same statistical characteristics 

as three historical periods (1913–98, 1928–98, and 1945–98) 

(fig. 53). Average and below-average runoff for the 16–year 

cycle are nearly identical to the longer periods. Above-average 

runoff for the 16-year cycle, however, tends to be even greater 

than for the other periods. The prevalence of recent, high-runoff years, also illustrated in figure 14, is not well understood, 

but may be either a normal climatic cycle that is not within the 

historical record, or a symptom of climatic change. Creating 

the most credible future scenario of runoff favored using the 

16-year cycle because it is the most recent data and because it 

may be indicative of recent changes in climate.

Figure 53. Cumulative probability of annual runoff in the Santa Ana River, San Bernardino area, 

California, for selected time periods, 1913–98. Calendar-year data for USGS gaging station 11051501.

Evaluation of Selected Water-Management Alternatives 103

0

50

100

150

200

250

300

350

400

450

500

0 0.2 0.4 0.6 0.8 1.0

1913-98

1928-98

1945-98

1983-98

CUMULATIVE PROBABILITY

ANNUAL RUNOFF IN THE SANTA ANA RIVER,

PERCENT OF LONG-TERM AVERAGE

Years
To satisfy the criteria for a multi-decadal management 

horizon, two 16–year cycles were combined to extend the 

calibration period (1945–98) a total of 32 years into the future, 

to the year 2030. In order to prevent a statistical shift in runoff 

at the end of the calibration period, a cumulative departurefrom-mean runoff curve was used to create a nearly seamless 

transition from the calibration period to the assumed future 

conditions. This method ensured no water was unintentionally 

added or subtracted from the simulation. Use of the cumulative runoff curve favored beginning the climatic cycle (1983–

98) in 1999, then repeating it in 2015. The longest period of 

record for the Santa Ana River (1913–98) was used for the 

analysis of cumulative runoff, despite having a few months of 

missing data. If a shorter period, either 1928–98 or 1945–98, 

were used, then the match would have favored beginning the 

climatic cycle in 1998. Choosing one match point or the other 

did not appear to have a significant effect on the simulated 

results.

The shortest time period considered in the management 

scenarios is a single year—the shortest period of uniform 

recharge or discharge in the ground-water flow model. For 

some hydrologic processes, such as storm flow, this is a 

relatively long time. A single year also is too long to capture 

the seasonal effects of evapotranspiration or pumpage. But 

for most water-management questions in the San Bernardino 

area, a time frame ranging from 1 to 32 years provides an 

adequate ability both to simulate the hydrologic processes and 

to observe the effects of management decisions.

In summary, each water-management scenario simulated 

conditions in the San Bernardino area from 1945 to 2030. 

The model calibration period (1945–98) was included in each 

scenario to facilitate comparisons to historical conditions. This 

design also facilitates updating the ground-water flow model 

as new data becomes available and then resimulating a specific 

scenario. Future conditions (1999–2030) were based primarily on historical recharge and discharge that occurred during 

a representative climatic period 1983–98. Additional recharge 

or discharge was added as necesary to investigate a particular water-management issue. Scenarios 1 through 4 required 

use of only the ground-water flow model; scenarios 5 and 6 

required use of both the ground-water flow and constrained 

optimization models.

Water-Management Issues

Water managers in the San Bernardino area face a variety 

of issues involving water supply and water quality. Solving water-supply issues often requires use of both surface 

water (fig. 11) and ground water (fig. 31), and in recent years, 

management of one typically has involved management of 

the other. With the large number of water-quality issues in the 

area (fig. 36), virtually all water-management decisions about 

water supply also involve questions and decisions about water 

quality.

As in many urbanizing areas, actual water management in 

the San Bernardino area encompasses an incredibly large number of surface-water, ground-water, and water-quality issues—

far too many to evaluate in this study or to include in this 

report. Nevertheless, a few issues stand out from the others 

as having much greater than average hydrologic importance. 

Typically, these issues are areally extensive, create effects that 

last for years, and have large costs associated with them. This 

study attempted to integrate analysis of these primary issues, 

which are summarized below and are identified in photographs 

(fig. 54) and spatially (fig. 55).

Along the base of the San Bernardino and San Gabriel 

Mountains, ground-water levels rise and fall dramatically 

with changes in recharge (fig. 43). During droughts, falling 

ground-water levels reduce the yield of wells that supply water 

for domestic, municipal, and agricultural use. In some cases, 

ground-water levels may drop below the intake bowls of a production well, requiring an expensive lowering of the pump or 

discontinued use of the well. Many of the water-management 

efforts in the San Bernardino area over the past 100 years have 

been to ensure a reliable source of water to users in areas near 

the base of the mountains. These efforts began with diversion 

of streams and later were expanded to include the construction 

of artificial-recharge basins designed to conserve surface water 

by recharging the valley-fill aquifer. More recently, water 

was imported into the San Bernardino area, and the Foothill 

pipeline (fig. 11) was constructed to transfer both native and 

imported water along the base of the mountains. The Seven 

Oaks Dam, designed originally as a flood-control facility, has 

been modified to include a conservation pool so that more 

native surface water can be distributed in the Foothill pipeline to water-treatment plants or to artificial-recharge basins. 

These modifications to the original surface-water system have 

increased the capability of managing water in the area, but at 

the same time, they have created numerous questions about 

how to manage the surface-water resources most efficiently.

104 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 54. Photographs of major water-management issues in the San Bernardino area, California, 1998.

Evaluation of Selected Water-Management Alternatives 105

B

A

C D

Low ground-water levels near the base of the San Bernardino

Mountains, September 2004.

High ground-water levels in the former

marshland. View shows groundwater upwelling through the buckled concrete basement floor of the San Bernardino Valley

Municipal Water District, June 1985. 

Shandin Hills Perris Hill

Ground-water contamination in the Newmark area. View looking south from the San Bernardino Mountains, January 2005.

Possible liquifaction in the former marshland, September 2005. View is of the

same area as in figure10.

Approximate area of Newmark plume
Figure 55. Major water-management issues in the San Bernardino area, California, 1998.

106 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

FAULT

SAN

ANDREAS

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Creek

River

River

Cr

Plunge

Zanja The

Warm

Santa

Santa

Ana

Ana

City Cr

 Cr

Mill Cr

Lytle

Cr

San Timoteo

Cr

Hot ground water 

Imported water

California Aqueduct

Santa Fe 

USEPA-Muscoy

Contamination

Contamination

Historical land subsidence

Pumpage limitations

Pumpage limitations

Possible trigger of liquefaction

San Jacinto Fault

USEPA-Newmark

San Andreas Fault

Possible trigger of liquefaction

Contamination

Norton AFB 

Additional

local water

Seven Oaks

Dam

Redlands

Contamination

Contamination

EXPLANATION

Redlands

Crafton Hills

0 6 KILOMETERS

0 6 MILES

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

Redlands

San Bernardino

Badlands

Shandin

Hills Perris Hill

San Bernardino Mountains

Gabriel

Mts

San

15

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Basin boundary – Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray

Fault or ground-water barrier – May be concealed or approximately located. San Andreas and

San Jacinto Faults are likely to produce a major

earthquake causing liquefaction

Former marshland – Area of recurring high

ground water and potential liquefaction

Geothermal areas – Ground water may be usable for 

heating or too warm for public supply

Poor ground-water quality – Contamination includes

volatile organic solvents, which restricts use for public 

supply. Areas mapped in 1997 include USEPA (United 

States Environmental Protection Agency) superfund sites 

and Norton Air Force Base IRP (Investigation and 

Restoration Program) site

Historical land subsidence – Area of historical 

land subsidence caused by ground-water pumpage. 

During 1944-56, subsidence rate averaged more 

than 0.025 feet per year

Artificial-recharge basin – Available for additional 

ground-water recharge of local or imported surface 

water. By controlling runoff, Seven Oaks Dam

effectively increases the supply of local water

Pipeline – Imported water obtained from northern 

California can be used for either direct delivery or 

ground-water recharge. Entitlement for importation

exceeds 100,000 acre-feet per year

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'
In contrast to the area near the base of the mountains, 

ground-water levels near the former marshland remain nearly 

at land surface, even during droughts. The depth to ground 

water in this area is affected only minimally by short-term 

changes in recharge near the mountains; ground-water levels 

are affected most by nearby pumping and by the longterm 

quantity of recharge. The high ground-water levels, present during most of the last 100 years, temporarily dropped 

from about 1950 to 1975, a period of extensive ground-water 

pumpage and lower-than-average recharge. During this period, 

the town of San Bernardino expanded and built on the former 

marshland. Beginning in about 1980, ground-water levels rose 

to within a few ft of land surface, and the increase in hydrostatic pressure damaged basements, foundations, and concrete 

flood-control channels. Perhaps more importantly, the high 

ground-water levels indicate that the fine-grained deposits 

near land surface are saturated and, therefore, are susceptible 

to liquefaction during an intense earthquake. The enormously 

expensive and potentially deadly threat of liquefaction is of 

particular concern in the San Bernardino area because of the 

proximity of two major active faults—the San Jacinto and San 

Andreas—that border either side of the area (fig. 55).

The substantial increase in pumpage in the vicinity of 

the former marshland beginning about 1945 not only lowered 

ground-water levels, but also caused land subsidence of as 

much as one foot between about 1950 and 1970. Recent watermanagement efforts have focused on increasing pumpage from 

the former marshland in order to lower ground-water levels 

and thereby reduce the possible adverse effects of liquefaction. 

Additional pumpage from this area of abundant wells also may 

be needed to provide additional water to meet future municipal 

demand. Although some additional pumpage in the vicinity 

of the former marshland may be helpful or necessary, groundwater levels need to be maintained above historic minimum 

levels to prevent additional compaction of fine-grained 

materials in the valley-fill aquifer, and the accompanying land 

subsidence.

Many ground-water-quality issues are present in the San 

Bernardino area, including contamination by volatile organic 

compounds, such as TCE and PCE; high concentrations of 

nitrate and DBCP, a pesticide; high concentrations of minor 

inorganic constituents, such as fluoride; elevated temperature 

of ground water near geothermal areas; and an increase in 

dissolved-solids concentration resulting from the importation 

and reuse of water. Knowledge about the areal and vertical 

distribution of these water-quality problems varies, as does 

understanding of the physical processes affecting these problems. Some ground-water-quality problems, such as the TCE 

contamination near Newmark (fig. 55), have been identified 

spatially by extensive drilling and sampling. Other problems, 

such as TCE contamination in the Redlands area, are not characterized as well either horizontally or vertically. Some physical processes, such as the movement of fluoride in ground 

water, are well understood; others, such as the transport 

and fate of nitrogen compounds, are the subject of ongoing 

research. These uncertainties—both in describing the physical 

extent of ground-water-quality problems and in understanding 

the physical processes governing the transport and fate of the 

contaminants—limit the ability of water managers to make 

informed decisions.

All water-management issues have an economic component. For complex issues, economics by itself may not 

determine the eventual answer, but it does aid in discarding 

some alternatives and favoring others. Possible changes in 

water management involve capital costs, such as installing 

additional pipelines or wells, and operational costs, such as 

pumping water a greater distance to the land surface or across 

the land surface to other areas of use. The electrical cost of 

moving water typically is a sizeable percentage of the total 

operational cost and can vary significantly depending on when 

and where the electricity is obtained. The operational cost of 

supplying water, which in 1998 varied from about $100 to 

$400 per acre-ft, and the capital cost of acquiring new water 

supplies, which exceeded $1,000 per acre-ft, commonly are 

used to evaluate the economic viability of any possible change 

in water management.

One of the most difficult water-management issues 

involves the long-term operation of the valley-fill aquifer for 

water supply. In defining this operation, an immediate quandary appears: how to maintain both a full and an empty basin. 

A full basin during a period of abundant runoff is an expensive 

lost opportunity for recharge; an empty basin during a drought 

is a dangerous economic and political liability. An important 

part of water management in the San Bernardino area involves 

defining an acceptable balance between these two alternatives.

Description of Water-Management Alternatives

Water managers in the San Bernardino area generally 

are aware of the most important water-management issues 

confronting them. This knowledge has been gained from 

years of living and working in the area and from the many 

studies commissioned by the several water districts and city 

water departments to study possible solutions to individual 

water problems. During the past three decades, comprehensive 

water-management studies have been done, though only a few 

recommended solutions have been implemented. Part of the 

reason appears to have been a lack of technical understanding 

about key water-management issues, such as the transport of 

organic contaminants or the susceptibility of saturated sediment to liquefy. Part of the reason appears to have been a lack 

of agreement about who will pay for the solution. And, part of 

the reason may have been a lack of active involvement by all 

the major water-purveyors in any comprehensive water-management plan.

Evaluation of Selected Water-Management Alternatives 107
To help to address this last reason, the San Bernardino 

Valley Municipal Water District in 1987 formed an advisory commission composed of the major water purveyors in 

the area. At monthly meetings of the advisory commission, 

significant water issues and proposed water projects are presented and critiqued by the members. In this way, projects are 

brought forward in an open forum. A technical subcommittee 

of the commission also meets as needed to provide a more 

in-depth analysis of specific issues or projects. Membership 

and participation in the advisory commission is voluntary and 

typically includes more than 20 different public entities.

In 1990, a comprehensive water-management plan for 

the San Bernardino area was begun by the San Bernardino 

Valley Municipal Water District. The consulting firm of Camp, 

Dresser, and McKee was hired to oversee development of the 

plan; the advisory commission and, in particular, the technical 

subcommittee of the advisory commission provided an ongoing critique of the plan. The planning process extended over a 

6-year period and included a broad range of technical investigations (Camp, Dresser, and McKee, 1990; 1991; 1995a,b; 

1996). The present study—which includes a description of the 

hydrologic system, installation of monitoring wells, development of the ground-water flow and constrained optimization 

models, and evaluation of water-management alternatives—is 

a significant part of those technical investigations. The advisory commission and technical subcommittee continuously 

reviewed the planning procedures and the technical investigations, including this one, and provided suggestions that 

resulted in changes to both.

An important product of the planning process has been 

development and analysis of various water-management 

alternatives designed to help solve one or more of the major 

water-management issues affecting the San Bernardino area. 

These alternatives are described briefly below.

1. Continue the present water-management operations. This alternative may be perceived as the easiest path to 

pursue. It may be perceived that maintaining present operations will create the fewest new problems. 

2. Raise low ground-water levels near the base of 

the San Bernardino Mountains with additional recharge.

If ground-water levels near the base of the San Bernardino 

Mountains are unacceptably low, then raise them by recharging additional water from local sources or water imported via 

the State Aqueduct.

3. Recharge additional water so that the valley-fill 

aquifer does not become depleted. A recurring concern when 

ground-water levels decline is that the valley-fill aquifer may 

become depleted. Demand for water throughout the San Bernardino area is recognized as increasing, and there is concern 

that recharge may not be keeping up with increased pumpage.

4. Lower high ground-water levels near the former 

marshland with additional pumpage. If ground-water levels 

near the former marshland are too high, then pump additional 

ground water to lower the levels. This additional pumpage 

ideally might be located in the immediate area of the highground-water problem and would be pumped from either 

existing or new wells.

5. Extend the Baseline feeder pipeline to the east or 

south. This extension along with existing or new production wells along the pipeline would enable additional ground 

water to be pumped from the area of the former marshland. 

This additional ground-water production could be provided to 

urbanizing areas west of the Lytle Creek basin or it could be 

pumped into the State Aqueduct.

6. Create a water-transfer credit with the State Aqueduct system. If there is excess ground water near the former 

marshland, then one alternative would be to pump some of the 

excess ground water into the State Aqueduct in exchange for a 

future credit. The quality of the ground water pumped into the 

aqueduct and the willingness of the State to accept this water 

may be important concerns.

7. Pump excess ground water into the Santa Ana 

River. If there is excess ground water near the former marshland and no demand for the water, then simply pump it and 

discharge it into the Santa Ana River. This alternative would 

relinquish a valuable quantity of ground water, but might 

avoid expensive damages from liquefaction caused by a major 

earthquake.

8. Satisfy future increased demand for water by 

providing surface water. A major advantage of using surface 

water is that it comes into the San Bernardino area at a higher 

head than that required for distribution. The major disadvantage is that surface water must be treated prior to being distributed for municipal use. In most cases, pumped ground water is 

delivered directly from the production wells to the consumer 

with minimal treatment.

9. Satisfy future increased demand for water by 

providing ground water. Major advantages of using ground 

water are that it can be obtained throughout most of the San 

Bernardino area relatively inexpensively, and it generally does 

not need to be treated except for adding chlorine prior to being 

distributed for municipal use. Major disadvantages are that 

ground water has a lower head by the time it is pumped from 

wells and therefore may need to be boosted to a higher head 

for distribution.

10. Understand the possible effects of climate change 

on water availability. Discussions about possible climate 

change cause concern among both local residents and water 

purveyors. Neither they nor scientists yet understand what if 

any effects of climate change will need to be incorporated into 

future water-management plans.

11. Install and operate extraction wells along the 

leading edge of the Newmark contamination site to prevent 

contaminated ground water from moving further downgradient. These wells, referred to locally as the barrier wells, 

would presumably create a hydraulic barrier to prevent further 

ground-water movement. The number, placement, perforations, and pumping rate of the wells have been persistent 

technical questions.

108 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
12. Determine effective joint cleanup of the Newmark 

and Muscoy contamination sites. These two USEPA superfund sites are physically close to each other and are hydraulically connected via the ground-water system. Operational 

decisions about how to cleanup one site will affect the ability 

and cost of cleaning up the other site. 

13. Install and operate extraction-injection wells on 

Norton Air Force Base to cleanup localized ground-water 

contamination. As part of the closure of Norton Air Force 

Base, several areas and types of ground-water contamination 

were found. As of 1998, remediation plans included three new 

wells to extract contaminated ground water, a processing plant 

to remove the contamination, and seven new wells to re-inject 

the treated water.

14. Install a set of production wells near the Redlands 

contamination site to pump and treat contamination. This 

alternative attempts to restrict migration of contaminated 

ground water by controlling the hydraulic gradients near the 

assumed site of contamination. As of 1998, however, the areal 

and vertical extent of the contamination was not well defined.

15. Treat ground water from any production wells 

adversely affected by contamination from the Redlands 

site. This option recognizes the difficulty in restricting movement of the ground-water contamination and instead remedies 

any contamination when it adversely impacts a municipal 

supply well.

Simulated Scenarios

Selection and Design of Scenarios

The selection and design of water-management scenarios 

was made in consultation with numerous individuals living 

and working in the San Bernardino area. These individuals 

included staff from several of the local water districts and city 

water departments and staff from the consulting firm of Camp, 

Dresser, and McKee who were requested by the San Bernardino Valley Municipal Water District to develop an overall 

water-management plan for the area. A technical advisory 

committee, composed of these individuals, met many times 

over a 5-year period to identify critical water-management 

issues and how these issues might be analyzed objectively. 

The seven scenarios described in this report were designed to 

provide a quantitative analysis of these issues and sufficient 

hydrologic insight to allow water managers to understand 

the effects of their decisions. Each scenario, its purpose, and 

major results are summarized in table 19. Simulated recharge 

and discharge components for each scenario are listed in 

table 20.

Scenario 1: Average Recharge and Discharge, 

1999–2030

Scenario 1 uses the ground-water flow model to simulate the effects of average recharge and discharge for the 

next 32 years (1999–2030). Annual variations in recharge 

and discharge are not simulated so that the effects of average 

conditions, in particular on hydraulic heads, can be seen more 

readily as the valley-fill aquifer moves progressively toward 

equilibrium. In essence, scenarios 1 and 2 show the effects of 

not changing the 1998 water-management operations. Scenario 1 is the steady-state version of scenario 2, which is the 

standard transient simulation used as the baseline for 

scenarios 3–6.

Simulated recharge and discharge components used in 

scenario 1 are described in detail below. In summary, average 

values for 1983–98 were used for gaged runoff, recharge from 

ungaged runoff, recharge from local runoff, pumpage, and 

return flow. Head-dependent relations were used to simulate 

evapotranspiration, recharge from gaged runoff, and underflow across the San Jacinto fault near the Santa Ana River. 

Recharge of imported water was assumed to be zero. Annual 

declining values of underflow were estimated for San Timoteo 

Canyon and Sand Canyon. All other recharge, discharge, and 

parameter values in the ground-water flow model were the 

same as those used during calibration. As shown in table 20, 

all seven scenarios were designed with strong symmetry in 

recharge and discharge components. Therefore, much of the 

description below also applies to other scenarios.

Recharge from direct precipitation for scenario 1 is 

assumed to continue at the same constant value used for calibration of the ground-water flow model. This value was estimated for long-term conditions (1945–98) and was assumed 

to represent the average arrival of recharge at the water table. 

Any annual variations in recharge (fig. 18) were assumed to 

be damped by water percolating tens or hundreds of ft through 

the unsaturated zone. In this respect, the assumption of average recharge from direction precipitation for scenario 1 is consistent with the calibrated model and probably a good estimate 

of any future hydrologic conditions. 

One caveat, however, may be that the recent climatic 

cycle (1983–98) used for other recharge and discharge components in scenario 1 has a greater percentage of years with 

much greater than average runoff than the calibration period 

(1945–98) (fig. 53). These wetter conditions might cause some 

additional recharge from direct precipitation on the valley 

fill, although the amount is probably minor. Also, concurrent 

with the greater runoff are generally warmer winters, which 

increases evapotranspiration. Much of any increase in direct 

precipitation on the valley fill might be consumed by increased 

evapotranspiration.

Evaluation of Selected Water-Management Alternatives 109
Simulated gaged surface-water runoff for scenario 1 is 

calculated as the average for 1983–98. As shown in figure 53, 

this recent 16–year climatic cycle mimics many of the important statistical characteristics of runoff that occurred during 

longer, historical periods. Average runoff used for scenario 

1 captures these historical characteristics in a general way. 

One difference, however, for the recent period is the relatively 

greater abundance of runoff years with 100 to 300 percent of 

long-term average runoff.

As a result, the average gaged runoff for 1983–98 

(165,683 acre-ft/yr) is approximately 110 percent of the 

average for the base period 1928–98, and 113 percent of the 

average for the calibration period 1945–98. These differences 

mean that scenario 1 results in an above-average amount of 

gaged runoff. The differences, however, do not infer that scenario 1 uses an equivalent above-average recharge from gaged 

runoff. Simulated recharge from gaged runoff is a nonlinear 

head-dependent relation, heavily weighted toward ensuring 

that proportionately more recharge occurs during unusually 

wet years. This is accomplished in the ground-water flow 

model by having significantly greater streambed conductance 

in unusually wet years to mimic natural conditions (table 16). 

In scenario 1, however, recharge from gaged runoff in scenario 

1 was simulated with the lower stream conductance indicative 

of average runoff. Therefore, recharge from gaged runoff for 

scenario 1 is somewhat less than what would be indicated by 

comparing runoff for different time periods.

As for the calibration period, simulated recharge from 

ungaged runoff in scenario 1 is calculated using an average 

recharge value scaled by gaged runoff in the Santa Ana River. 

As described above, average gaged runoff in the river for 

1983–98 is slightly greater than for longer historical periods. 

Unlike recharge from gaged runoff, this higher percentage 

does translate directly into more recharge than for longterm 

conditions. The over-riding decision in designing scenario 1, 

however, was to be consistent with scenario 2 and the 1983–98 

period, even if it resulted in slightly more recharge from 

ungaged runoff. The effect of this decision, however, is fairly 

minor (about 2,000 acre-ft/yr).

Recharge from local runoff was calculated for scenario 1 

in the same way as recharge from ungaged runoff. For 1983–

98, the average value of recharge from local runoff is 5,900 

acre-ft/yr. This value was used as a constant value in scenario 

1 and tends to represent slightly wetter conditions than the 

longterm average. But the difference is not great, probably 

about 600 acre-ft/yr, so the total effect on the ground-water 

system is likely to be minor.

In scenario 1, no water is imported for recharge unlike 

during 1983–98 when a total of about 22,000 acre-ft of water 

was imported for this use (table 5). At a recharge rate of 

90 percent, this quantity equates to about 20,000 acre-ft of 

recharge to the ground-water system, primarily near the base 

of the San Bernardino Mountains (fig. 11). Despite the historical recharge during 1983–98, design of scenario 1 favored setting imported recharge to zero in order to observe the effects 

of using only native water. 

Also, since the mid-1980’s, the management philosophy of the San Bernardino Valley Municipal Water District 

and other water purveyors has been to minimize imported 

water for recharge in order to conserve economic resources 

and to limit increasing the already high ground-water levels 

in the former marshland. This philsophy was accentuated in 

1986 when a lawsuit was filed by the city of San Bernardino 

against the San Bernardino Valley Water Conservation District 

alledging that the District’s excessive purposeful recharge 

was responsible for the high ground-water levels and related 

damage to public infrastructure (refer p. 29). Settlement of 

this lawsuit involved payment of $3 million to the city of San 

Bernardino, and became a disincentive for any public entity 

purposefully recharging imported water or requesting that 

imported water be recharged.

Underflow for scenario 1 is set at the constant values 

used during calibration, at decreasing annual values calculated 

from regression equations 3 and 4 (fig. 27), or at an amount 

calculated by a head-dependent relation (eq. 10; fig. 28). These 

conditions assume that ground-water levels continue to decline 

in the Yucaipa basin (fig. 26) and that this decline continues to 

decrease underflow into the Bunker Hill basin (fig. 27). Any 

changes in ground-water levels in the Rialto-Colton basin are 

not likely to significantly affect underflow from the Bunker 

Hill basin. Therefore, despite the complexity of estimating or 

calculating underflow at several locations, it seems likely that 

the underflow assumed for scenario 1 will remain valid for a 

variety of future hydrologic conditions within the San Bernardino area.

Pumpage and return flow used for scenario 1 are the 

average of the values for 1983–98. Deciding on how to best 

simulate pumpage for 1999–2030 was probably the most difficult decision in designing scenarios 1 and 2. During the 16-

year period, many changes in the use of wells occurred: new 

wells were installed, a few wells were deepened, and some 

wells were taken out of production to ameliorate water-quality problems. Using the pumpage from the mid-1980’s for the 

early 2000’s means that some pumpage is overtly wrong. 

The strength of using the historical data verbatim, however, is that it represents a logically paired set with the local 

surface-water runoff. The historical locations and quantities 

of pumpage were decided by many local purveyors based on 

local runoff and on antecedent conditions of precipitation, 

runoff, and pumpage. Attempting to create a purely synthetic 

pumpage dataset for scenarios 1 and 2 appeared to add too 

much unquantified uncertainty, which would make the model 

results difficult to interpret. Also, the primary goal of scenario 

1 was to continue present water-management operations; 

therefore, using historical data directly seemed the most prudent choice. Subsequent investigators may wish to revisit this 

decision and carefully estimate future pumpage for each existing and planned well in the San Bernardino area. With many 

water purveyors and various future plans, developing annual 

estimates of future pumpage correlated to local runoff is not 

likely to be a precise or trivial exercise.

110 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Results from scenario 1 are shown in figure 56. The most 

obvious result is that simulated hydraulic heads in most areas 

of the model tend to flatten out relatively quickly and stay at 

about the level they were in 1998. Heads near Devil Canyon 

and in parts of the Lytle Creek basin, however, continue to 

decline through 2030. The decline near Devil Canyon, and in 

the nearby Newmark and Sweetwater areas, may result from 

having zero recharge of imported water. The decline also 

may result from increased pumpage related to ground-water 

contamination and cleanup. This increase in pumpage would 

depress the simulated head even further below historically 

high levels, which were sustained for a time (1972–85) by 

recharge of imported water (table 5). Assumptions of average 

recharge and pumpage probably are not reliable in this area of 

the model; therefore, simulated results need to be used with 

caution. 

The rationale for the decline in head in the Lytle Creek 

basin (WSB 1, fig. 56) is less obvious, but may be related 

simply to less recharge from Lytle Creek. As described above, 

average recharge of gaged runoff as simulated in scenario 1 

does not account fully for the extra recharge that occurs during years of above-average runoff. The historical record for 

well WSB 1 suggests that this type of recharge is critically 

important for the Lytle Creek basin. Imported water used for 

recharge in the Lytle Creek gravel pit was minimal during 

1983–98 (table 5) and is unlikely to explain the observed 

decline in simulated head.

Near the area of the former marshland, simulated head 

for the upper model layer, which approximates the water table, 

is tens of ft below land surface. This result suggests that the 

simulated quantity of pumpage along with head-dependent 

relations (evapotranspiration, underflow, and streams) is sufficient to decrease high ground-water levels—in a steady-state 

simulation. This result is instructive, in that it suggests the 

ground-water budget for scenario 1 is nearly balanced, but 

it greatly oversimplifies the true dynamics of the system, as 

illustrated below with results from scenario 2.

Scenario 2: Annual Variations in Recharge and 

Discharge, 1999–2030

Scenario 2 uses the ground-water flow model to simulate continuing the 1998 water-management operations with 

annual variations in recharge and discharge. Scenario 2 is 

essentially the transient version of scenario 1, and the baseline 

for scenarios 3–6. The recent 16-year climatic cycle 1983–98 

is used as the basis for the annual variations in recharge and 

discharge. Two of the 16-year cycles are combined to form the 

32-year evaluation period, 1999–2030. Results of the simulation are shown in figure 57.

The simulated recharge and discharge components for 

scenario 2 are summarized in table 20 and to a great extent are 

described above for scenario 1. The components that are the 

same for both scenarios 1 and 2 include: recharge from direct 

precipitation, recharge from imported water (zero), underflow for the constant flux areas (Badlands, Redlands Heights, 

Reservoir Canyon, and San Jacinto fault near barrier J), and 

underflow from the declining flux areas (San Timoteo Canyon 

and San Canyon). Two head-dependent relations (evapotranspiration and underflow across the San Jacinto fault near 

the Santa Ana River) also are the same though the simulated 

discharge will be different because the simulated heads will be 

different.

Differences between scenarios 1 and 2 include recharge 

from ungaged runoff, recharge from local runoff, pumpage, 

and return flow. Simulating each of these components used 

the annual values from 1983–98 verbatim. Because of this 

approach and because the components are simulated as specified fluxes, the average values for scenario 1 and the timevarying values for scenario 2 are comparable.

The major difference between scenarios 1 and 2 is 

recharge from gaged runoff. For scenario 2, simulating 

recharge from gaged runoff includes both annual runoff for 

1983–98 and greater streambed conductance during unusually wet years. Use in the ground-water flow model of a 

head-dependent stream-aquifer relation for gaged runoff and 

different annual values of streambed conductance make a 

priori comparisons between average recharge for scenario 1 

and time-varying recharge for scenario 2 qualitative at best. 

Scenario 1 approximates a typical “safe yield” analysis that 

uses average values, and, therefore, is susceptible to errors of 

interpretation caused by unusually wet years. For this reason, 

rigorous water-level and water-budget analysis should use 

results from the ground-water flow model simulating timevarying recharge such as done in scenario 2.

Comparing simulated results from scenario 2 (fig. 57) 

with those from scenario 1 (fig. 56), however, can be qualitatively instructive; a similar overall trend is present in most 

respective hydrographs. Identifying this trend, which appears 

to be approximately flat or slightly downward with time, was 

a primary goal in designing scenario 1. Vertical hydraulic 

gradients also are similar for both scenarios. These similarities 

confirm that that scenario 1, although simplified in particular 

with respect to recharge from gaged runoff, is an instructive 

version of scenario 2. The inset map for scenario 1 shows the 

complexity of simulated response throughout the valley-fill 

aquifer despite using average recharge and discharge. The 

inset map for scenario 2 may be more representative because 

of the symmetry of conditions preceeding 1998 and 2030. 

Evaluation of Selected Water-Management Alternatives 111
Figure 56. Results from water-management scenario 1 in the San Bernardino area, California, 1999–2030.

112 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

YEAR YEAR YEAR

40 50 60 70 80 90 00 10 20 30 40 50

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900

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60

ALTITUDE, IN FEET ABOVE SEA LEVEL

70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30

Santa

Ana

River

Seven Oaks 

Dam

1940-99 2000-30 1940-99 2000-30 1940-99 2000-30

0 6 KILOMETERS

0 6 MILES

EXPLANATION

Graphs Map

Redlands Crafton Hills

San Bernardino

Badlands

Gabriel

Basin

boundary

San Bernardino Mountains

Shandin

Hills

Mts

San

Difference in simulated hydraulic heads between 1998 

and 2030-Values in feet for the upper layer of the 

ground-water flow model. Rise indicates heads for 

scenario 1 in year 2030 are higher than heads in year 

1998.

10-30

> 30

Rise Decline

10-30

0-10

0-10 > 30

Scenario 1

Calibration

period

1945-98

1999-2030

1940

Measured ground-water level

Land surface

Simulated hydraulic head-For each

layer of the ground-water flow model

Upper layer

Lower layer

Devil

Canyon 2

1N/4W-7F1

USGS

2N/5W-33J4

WSB 13-Raynor 4

1S/4W-6H1

Heap

1S/4W-3Q1

Thorn 10

1S/4W-22B3

Redlands 32

1S/3W-21H1

Tri-City

1S/3W-9E2

W. Cram

1S/3W-2J1

Happe Mutual

Well Co.

1S/2W-29M1

Bryn Mawr Water Co.

1S/3W-31A3

WSB 1

1N/5W-23P4

Newmark 4

1N/4W-16E4

Meacham

1N/4W-35L1
Figure 57. Results from water-management scenario 2 in the San Bernardino area, California, 1999–2030.

Evaluation of Selected Water-Management Alternatives 113

Seven Oaks 

Dam

Santa

Ana

River

Devil Canyon 2

1N/4W-7F1

USGS

2N/5W-33J4

WSB 13-Raynor 4

1S/4W-6H1

Heap

1S/4W-3Q1

Thorn 10

1S/4W-22B3

Redlands 32

1S/3W-21H1

Tri-City

1S/3W-9E2

W. Cram

1S/3W-2J1

Happe Mutual

Well Co.

1S/2W-29M1

Bryn Mawr Water Co.

1S/3W-31A3

WSB 1

1N/5W-23P4

Newmark 4

1N/4W-16E4

Meacham

1N/4W-35L1

40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30

1,300

1,200

1,100

800

900

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900

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900

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900

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ALTITUDE, IN FEET ABOVE SEA LEVEL

YEAR YEAR YEAR

1940-99 2000-30 1940-99 2000-30 1940-99 2000-30

Measured ground-water level

Land surface

Simulated hydraulic head-For each

layer of the ground-water flow model

Upper layer

Lower layer

EXPLANATION

Difference in simulated hydraulic heads

between 1998 and 2030-Values in feet

for the upper layer of the ground-water flow

model. Decline indicates heads for scenario 2

in year 2030 are lower than heads in year

1998.

Graphs Map

0-10 10-30 30-50 > 50

0 6 KILOMETERS

0 6 MILES

Scenario 2

Calibration

period

1945-98

1999-2030

1940

Redlands Crafton Hills

San Bernardino

Badlands

Gabriel

Basin

boundary

San Bernardino Mountains

Shandin

Hills

Mts

Decline
In general, simulated results from both scenarios 1 and 

2 illustrate that the valley-fill aquifer is in balance without recharge of imported water. The slight decline in heads 

observed during the 32-year period probably is too minor to 

be indicative of a longterm change; rather the decline likely is 

within the range of uncertainty of the recharge and discharge 

values chosen for scenarios 1 and 2. An isolated exception is 

the decline in simulated head observed near the mountain front 

north of Shandin Hills. An important caveat to the conclusion 

that the valley-fill aquifer is in balance is that recharge chosen 

for scenarios 1 and 2 represents recent runoff, which has been 

slightly greater than longterm historical conditions, and therefore may not be indicative of future conditions.

 One of the characteristic results from scenario 2 is the 

repeating, sinusoidal pattern of simulated heads in each of 

the hydrographs (fig. 57). This pattern is a natural result of 

the climatic cycle used for scenario 2, but the fluctuations are 

enhanced by human actions. During years with below-average 

runoff, pumpage increases to make up for the lack of surface 

water. During years with above-average runoff, the reverse 

occurs. As a result, stress on the ground-water system is 

amplified during both wet and dry years.

The vertical range of this wet-dry cycle demonstrates the 

normal, active range of heads that can be expected to occur in 

the valley-fill aquifer. Significant annual and decadal fluctuations in ground-water levels are part of the historical record 

and, based on the results from scenario 2, similar fluctuations are likely to recur independent of any changes in water 

management. These fluctuations, both in the unconfined and 

confined hydrogeologic units, typically are 100 ft or more. 

Historically, many water purveyors have lowered or raised 

pump bowls to follow fluctuating ground-water levels. This 

retooling of production wells has been both a frustration and 

a cost to some water purveyors and seems likely to continue 

based on the fluctuations observed in figure 57.

An implicit part of future fluctuations in ground-water 

levels are future fluctuations in ground-water storage. In this 

respect, the results from scenario 1 are misleading. Achieving 

constant ground-water levels or no change in ground-water 

storage, probably is not possible. Rather, just as during the 

calibration period (fig. 45), significant changes in storage will 

occur. The magnitude of these changes likely will be similar to 

that observed during 1983–98; annual fluctuations of as much 

as 200,000 acre-ft and a cumulative change of as much as 

500,000 acre-ft, or more, can be expected. These fluctuations 

create opportunities to capture native runoff, but also may 

cause concern when ground-water levels are dropping, and the 

basin appears empty, unlikely to refill. Fluctuating groundwater levels and ground-water storage are an inherent part of 

the present operations in the valley-fill aquifer. The dynamic 

ground-water flow simulated in scenario 2, coupled with the 

public response to varying hydrologic conditions from 1984 to 

1998, prompted the quote at the beginning of this report,

“And it never failed that during the dry years the 

people forgot about the rich years, and during the 

wet years they lost all memory of the dry years. It 

was always that way.” John Steinbeck

This dynamic, observed by Steinbeck in the Salinas Valley of 

California, also typifies the hydrology of the San Bernardino 

area.

In several areas of the model, the maximum head reached 

during each cycle of increased recharge and decreased 

pumpage is similar to the maximum heads simulated during 

the historical period 1945–98. In the former marshland, the 

maximum head during scenario 2 is nearly at land surface, 

indicating a potential future concern about flooding of the 

land surface and possible liquefaction during an earthquake. 

The minimum heads reached during scenario 2 are generally 

from 50 to 100 ft above the minimum historical heads, which 

occurred about 1965. Based on these results, it does not seem 

likely that additional land subsidence will be induced with 

(1998) water-management practices even if gross pumpage 

continues to be augmented by the discretionary increase of 

10,000 acre-ft/yr exported to the city of Riverside (San Bernardino Valley Municipal Water District, 1981b, 1985).

Scenario 3: Increased Recharge Made Possible 

by Seven Oaks Dam, 1999–2030

Scenario 3 uses the ground-water flow model to simulate 

additional recharge made possible by construction of Seven 

Oaks Dam on the Santa Ana River. Because the primary 

purpose of this massive new dam is flood control, longterm 

retention of water behind the dam is minimized. During winter 

and spring, runoff is captured, then released fairly rapidly so 

that the dam has available capacity to prevent any future flooding that might occur. This operational policy tends to limit 

purposeful ground-water recharge that could be increased by 

presence of the new dam. 

To better satisfy local water purveyors who want Seven 

Oaks Dam not only to control floods, but also to retain water 

for later ground-water recharge, the Army Corps of Engineers 

added a conservation pool behind the dam. Although the pool 

eventually would fill with sediment, the pool would have an 

initial capacity of 16,000 acre-ft when the dam opened in the 

year 2000, decreasing to 7,000 acre-ft in the year 2050. The 

extra water available for ground-water recharge as a result 

of the conservation pool was estimated to be 4,116 acre-ft in 

2000 decreasing to 2,140 acre-ft in 2050. 

114 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Formulation of scenario 3 used scenario 2 as a baseline 

for all recharge and discharge components (table 20). To this 

baseline was added annual recharge as specified flux in one 

or more of the artificial-recharge basins (fig. 11). A total of 

eight different combinations of quantity, location, and temporal distribution of recharge were simulated as part of scenario 

3. These test cases used annual recharge ranging from about 

2,000 acre-ft to about 24,000 acre-ft. This extra recharge most 

commonly was put into the upper Santa Ana River basin or 

into the upper and lower Santa Ana River basins. For one test 

case, all seven artificial-recharge basins were used with the 

average annual recharge that occurred from imported water 

during 1972–98 (table 5; fig. 11).

In all eight test cases, the net quantity of recharge was 

much less than expected, generally averaging about 3,000 

acre-ft/yr or less. In some ways, this result should have been 

expected. Any increase in ground-water recharge, particularly 

over a period of years, will increase ground-water levels, 

which in turn will increase discharge that is dependent on 

ground-water levels: evapotranspiration, underflow across the 

San Jacinto fault near the Santa Ana River, and ground-water 

discharge to streams. To account for this interdependence, the 

change in ground-water storage compared to scenario 2 was 

used as a measure of the effect of increased recharge.

For example, the test case that used the estimate of 4,116 

acre-ft of available recharge in 2000 declining to 2,932 acre-ft 

in 2030 resulted in an average net increase in ground-water 

storage of 1,163 acre-ft/yr. This increase equates to about 

37,000 acre-ft of water contributed to the valley-fill aquifer 

during 1999–2030. Results of this simulation are shown in 

figure 58. The primary area of influence from this additional 

recharge to the valley-fill aquifer is near the upper and lower 

Santa Ana River basins, which were used for the recharge. The 

broader influence extends over the eastern half of the Bunker 

Hill basin, minimally changing the pattern of heads resulting 

from scenario 2 (fig. 57). Because this additional recharge is 

minimal compared to other recharge and discharge, the hydrographs for scenario 3 are similar to those for scenario 2.

What then is the value of the conservation pool? Viewed 

from one perspective, adding 37,000 acre-ft of water over a 

period of 32 years is nearly inconsequential in an area that 

averages nearly 150,000 acre-ft/yr of gaged runoff (table 1), 

and more than 180,000 acre-ft/yr of gross pumpage (fig. 25). 

However, viewed from another perspective, importing 37,000 

acre-ft of water would cost a minimum of $1.5 million just for 

electrical costs to lift it over the San Bernardino Mountains, 

and could cost as much as $37 million if it were from a new 

source of water (refer p. 107 this report).

One of the quandries of water management in the San 

Bernarino area is how to recharge water and capture it for use 

before it leaves the basin, or rather before it prompts, via a 

rise in ground-water levels, other water to leave the basin 

(figs. 49 and 50). Some previous water-management efforts 

have addressed this issue by using a “put and take” system 

where additional recharge is extracted a short distance away 

before it can significantly affect the rest of the aquifer. This 

technique can be successful, but it requires that an additional 

source of water be contemporaneous with an additional 

demand for water. Often extra water occurs when local 

demand can be satisfied in other ways—from precipitation, 

surface water, or other pumpage. 

One water-management idea that has been suggested is 

to export the pumped water for a credit to be used later when 

demand exceeds available local supplies. This idea is attractive 

because it stores the water as credit or cash, which may avoid 

the “user fee” associated with losing much of the additional 

recharge to increased discharge from the valley-fill aquifer. 

The presence of the State Aqueduct passing through the San 

Bernardino area in conjuction with large-capacity pipelines 

within the area (fig. 11) makes this a viable water-management 

option that would not be possible in many semiarid groundwater basins.

Analysis of the eight test cases for scenario 3 also 

illustrates the inherent difficulty of recharging available water 

during a period of abundant runoff. Ironically, the availability 

of surplus imported water often coincides with wetter-thanaverage local hydrologic conditions and decreased available 

storage capacity in the aquifer system. Stream channels and 

artificial-recharge basins are saturated, recharge tends to be 

rejected, and more ground-water is prompted to flow out of 

the basin either via streams or as underflow. A high-capacity, 

well-connected recharge, extraction, and distribution system 

might be required to overcome these hydraulic characteristics 

of the valley-fill aquifer and retain extra runoff for later use, as 

a paper credit.

In summary, water managers probably cannot escape 

two basic, controlling hydraulic characteristics of the San 

Bernardino area: (1) extra water becomes available during 

relatively infrequent periods of abundant runoff and (2) extra 

recharge prompts extra discharge from the valley-fill aquifer.

Scenario 4: Increased Pumpage Using Existing 

Wells, 1999–2030

Scenario 4 uses the ground-water flow model to simulate 

increased pumpage to lower ground-water levels in the former 

marshland and to meet increased future demand for municipal water. High ground-water levels in the former marshland 

have caused a variety of problems, including buckled foundations, damaged flood-control structures, and severed utility 

lines. Most of this damage occurred in the early 1980’s when 

ground-water levels rose to near land surface as a result of 

increased recharge of the valley-fill aquifer (fig. 59). The 

increase in hydrostatic pressure also creates the potential 

for liquefaction of near-surface earth materials as a result of 

ground-shaking during a severe earthquake.

Evaluation of Selected Water-Management Alternatives 115
Figure 58. Results from water-management scenario 3 in the San Bernardino area, California, 1999–2030.

116 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30

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1,200

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900

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900

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900

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1,700

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800

900

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700

800

900

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800

900

1,000

ALTITUDE, IN FEET ABOVE SEA LEVEL

YEAR YEAR YEAR

1940-99 2000-30 1940-99 2000-30 1940-99 2000-30

Devil Canyon 2

1N/4W-7F1

USGS

2N/5W-33J4

WSB 13-Raynor 4

1S/4W-6H1

Heap

1S/4W-3Q1

Thorn 10

1S/4W-22B3

Redlands 32

1S/3W-21H1

Tri-City

1S/3W-9E2

Happe Mutual

Well Co.

1S/2W-29M1

Bryn Mawr Water Co.

1S/3W-31A3

WSB 1

1N/5W-23P4

Newmark 4

1N/4W-16E4

Meacham

1N/4W-35L1

Simulated hydraulic head-For each

layer of the ground-water flow model

0 6 KILOMETERS

0 6 MILES

Graphs Map

W. Cram

1S/3W-2J1

EXPLANATION

Seven Oaks Dam

Redlands Crafton Hills

San Bernardino

Badlands

Gabriel

Basin

boundary

San Bernardino Mountains

Shandin

Hills

Mts

San

Santa

Ana

River

Difference in simulated hydraulic heads between 1998 

and 2030-Values in feet for the upper layer of the 

ground-water flow model. Rise indicates heads for 

scenario 3 in year 2030 are higher than heads in year 

1998.

Measured ground-water level

Land surface

Upper layer

Lower layer

Rise Decline

 0-10 30-50

10-30

1-10

< 50

Scenario 3

Calibration

period

1945-98

1999-2030

1940
Figure 59. Results from water-management scenario 4 in the San Bernardino area, California, 1999–2030. In each hydrograph, 

simulated hydraulic heads for the upper model layer during 1999–2030 are shown by four lines from top to bottom for 

scenarios 4a–d, respectively; results for scenario 4b are depicted by the darkest line and are presented on the inset map.

Evaluation of Selected Water-Management Alternatives 117

40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10 20 30

1,300

1,200

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900

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900

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900

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900

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900

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900

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ALTITUDE, IN FEET ABOVE SEA LEVEL

YEAR YEAR YEAR

1940-99 2000-30 1940-99 2000-30 1940-99 2000-30

Seven Oaks Dam

River

Devil Canyon 2

1N/4W-7F1

USGS

2N/5W-33J4

WSB 13-Raynor 4

1S/4W-6H1

Heap

1S/4W-3Q1

Thorn 10

1S/4W-22B3

Redlands 32

1S/3W-21H1

Tri-City

1S/3W-9E2

W. Cram

1S/3W-2J1

Happe Mutual

Well Co.

1S/2W-29M1

Bryn Mawr Water Co.

1S/3W-31A3

WSB 1

1N/5W-23P4

Newmark 4

1N/4W-16E4

Meacham

1N/4W-35L1

0 6 KILOMETERS

0 6 MILES

EXPLANATION

Graphs Map

Redlands Crafton Hills

Santa

Ana

San Bernardino

Badlands

Gabriel

Basin

boundary

San Bernardino Mountains

Shandin

Hills

Mts

San

 10-30

30-50 80-120

50-80

0-10

<120

Difference in simulated hydraulic heads between 1998 

and 2030 -Values in feet for the upper layer of the 

ground-water flow model. Decline indicates heads for 

scenario 4b in year 2030 are lower than heads in year 

Decline

Scenario 4

Scenario

4a

4b

4c

4d

Calibration

period

1945-98

1999-2030

1940

Simulated hydraulic head-For each

layer of the ground-water flow model

Measured ground-water level

Land surface

Upper layer

Lower layer
Controlling high ground-water levels has been a topic of 

conversation in the San Bernardino area for at least 20 years 

and an important part of previous water-management studies 

(Hardt and Hutchinson, 1980; Hardt and Freckleton, 1987; 

Danskin and Freckleton, 1992; Camp Dresser and McKee, 

1995a, 1995b). Part of the water-management challenge of 

lowering ground-water levels is technical: where to place 

wells; how much to pump them. These questions are addressed 

by scenario 4. Another part of the challenge is political: 

local concerns such as, “Don’t dry up the basin; don’t pump 

out inexpensive native water, then have to recharge expensive imported water.” These concerns, commonly voiced 

in meetings of the advisory commission formed by the San 

Bernardino Valley Municipal Water District, are the more 

difficult, and largely need to be addressed in the local political 

sphere.

Scenario 4 also shows some of the effects of providing 

additional ground water for municipal uses. Previous investigations by the California Department of Water Resources 

(1970, table 7) and by Camp Dresser and McKee (1995a, 

fig. 1–5) determined that demand for water in the San Bernardino area is likely to increase significantly by the year 

2020. Much of this increase is caused by progressive urbanization of agricultural area, which has been occurring since 

before 1949 (fig. 8). Although a significant quantity of water is 

used on the remaining agricultural land and will become available as the agricultural land is converted to urban use, both 

studies conclude that the total demand for water in the San 

Bernardino area will increase, perhaps by as much as 50,000 

acre-ft/yr.

 A study by Camp, Dresser, and McKee (1991) evaluated 

two alternatives in meeting this future demand: (1) delivering additional surface water via water-treatment plants, and 

(2) delivering additional ground water provided by increased 

production from existing wells and, if necessary, from new 

wells. Results of the study showed that meeting demand with 

additional ground-water pumpage is less expensive, even if 

additional recharge of relatively expensive imported water is 

necessary to prevent a longterm depletion of ground water. 

Scenario 4 uses the ground-water flow model to test the effects 

of a range of increased pumpage using existing wells. No 

recharge of imported water is included in scenario 4 in order 

to identify the effects of only using native water.

Formulation of scenario 4 used scenario 2 as a baseline 

for all recharge and discharge components (table 20). To this 

baseline was added excess pumping capacity at existing wells, 

and any induced return flow from that excess. To calculate 

excess pumping capacity, the most recent 5-year period 

(1994–98) was used. The rationale for selecting this period 

is twofold: (1) nearly all wells that were pumped sometime 

during the period probably were still operational in 1999, 

and (2) high-quality historical data are available to calculate 

recent average and maximum pumpage for each well. Excess 

pumping capacity was calculated for each well as the difference between the maximum and average annual pumpage for 

1994–98. Return flow was calculated for each well using the 

same percentages used to calculate other return flow in the 

model.

In order to simulate the effect of excess pumping capacity on controlling high ground-water levels, the distance of 

each well with excess capacity was calculated from the location where ground water (and surface water) flows out of the 

Bunker Hill basin. This location was defined as the mid-point 

of the section where ground water flows across the San Jacinto 

fault near the Santa Ana River (fig. 60A). Pumpage near 

ground-water outflow from the basin will produce the greatest 

capture of ground-water discharge and will be most effective 

at decreasing high ground-water levels. 

Cumulative values of excess pumping capacity (gross 

excess pumpage, net excess pumpage, and excess return 

flow) compared to distance from the basin outflow are shown 

in figure 60B. Both gross and net excess pumpage increase 

almost linearly to a distance of about 40,000 ft indicating the 

relatively predictable areal distribution of excess capacity. The 

near-zero value of excess return flow for distances less than 

about 18,000 ft from basin outflow results from the prevalence 

of wells used solely for export to the city of Riverside; these 

wells have no return flow. The areal distribution of excess 

pumping capacity with limited return flow suggests that using 

existing wells may be an efficient way to control ground-water 

levels in the area of the former marshland.

Scenario 4 was designed to test these observations. 

Excess pumping capacities were divided into four groups 

based on distance of the individual well from basin outflow: 

scenario 4a (all wells within 10,000 ft of basin outflow); 

scenario 4b (all wells within 20,000 ft); scenario 4c (all wells 

within 30, 000 ft), and scenario 4d (all wells with excess 

pumping capacity in the entire valley-fill aquifer). The areas 

and relative quantities of excess pumping are indicated on 

figures 60A and 60B, respectively.

Results for the four test cases in scenario 4 are shown on 

each hydrograph in figure 59. Scenario 4b with a distance of 

20,000-ft is shown on the inset map and highlighted on the 

hydrographs because this distance includes most of the former 

marshland and the area with recently high ground-water levels. 

For three of the four test cases, the change in ground-water 

levels is dramatic. Only for scenario 4a, the 10,000-ft distance, 

do heads remain relatively similar to the baseline condition, 

scenario 2. The modest downward slope of heads for scenario 

2 (fig. 57) and more so for scenario 4a indicates that the valley-fill aquifer is on the cusp of change. Ground-water storage 

is sensitive to an increase in net pumpage of as little as 14,000 

acre-ft/yr, the net excess pumpage simulated in scenario 4a.

118 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 60. Excess pumping capacity in the San Bernardino area, California, 1994–98. Graph A shows that each component of excess 

capacity (gross and net pumpage and return flow) increases from basin outflow, defined as the midpoint of ground-water underflow 

across the San Jacinto fault (figs. 22 and 39). Map B shows four areas which are defined by distance from basin outflow and are 

used to formulate scenarios 4a–d.

Evaluation of Selected Water-Management Alternatives 119

Former marshland

Artificial-recharge basin

Basin boundary-Bunker Hill

 and Lytle Creek ground-water

 basins shaded in darker gray

Area included in scenario 4

Fault or ground-water barrier

-May be concealed or 

 approximately located

0 6 KILOMETERS

0 6 MILES

15

215

10

215

15

A

100

90

80

70

60

50

40

30

20

10

20 40 60 80 0 0

Bunker Hill and Lytle

 Creek Basins

Basin outflow

10 - 20

0 - 10

(0 - 10 ft area)

(0 - 20 ft area)

(0 - 30 ft area)

(0 - >30 ft area)

20 - 30

>30

4a

4b

4c

4d

Distance from basin outflow-In

 thousands of feet

EXPLANATION

Gross excess pumpage

Net excess pumpage

Excess return flow equals

gross excess pumpage

minus net excess pumpage

DISTANCE FROM BASIN OUTFLOW, IN THOUSANDS OF FEET

CUMULATIVE PUMPAGE OR RETURN FLOW,

IN THOUSANDS OF ACRE-FEET PER YEAR

B
For scenario 4b, with a net pumpage of about 35,000 

acre-ft/yr, the decline in simulated heads is precipitious 

throughout nearly the entire valley-fill aquifer. Only beneath 

the upper reaches of the Santa Ana River, Mill Creek, Lytle 

Creek, and Cajon Creek do heads remain unchanged from 

conditions prior to 1999 (fig. 59). Large annual fluctuations 

continue even in these areas, but the deflections are similar 

to those that occurred during the 1980’s and 1990’s. Beneath 

the fomer marshlands, the simulated decline in head appears 

likely to remedy any concern about high ground-water levels. 

A caveat to this simulated result, however, is that the finegrained hydrogeologic unit UCM (fig. 24) may create perched 

water-table conditions, even as head in the underlying coarsegrained hydrogeologic unit UWB declines. The presence of 

this condition can be identified and monitored through the use 

of multiple-depth piezometers (figs. 24 and 35).

The maximum simulated decline for scenario 4b also 

warrants caution relative to renewed land subsidence caused 

by compaction of the aquifer system. In many parts of the 

valley-fill aquifer, the simulated head for scenario 4b declines 

below the minimum ground-water level reached in about 1965. 

Land subsidence resulting from withdrawal of ground water is 

a complex process that begins slowly and once initiated may 

be difficult and time-consuming to stop or reverse. Monitoring 

equipment including multiple-depth piezometers and extensometers, and remote-sensing data including interferometric 

synthetic aperture radar (InSAR) can be useful to detect, map, 

and analyze aquifer-system compaction (Galloway and others, 

1998).

An additional caveat about declining ground-water levels 

is that scenario 4d may not be a physically realistic simulation. The head decline far exceeds any that occurred during 

the calibration period. In fact, it is likely that the actual decline 

would be greater as the aquifer is dewatered and transmissivity 

and storage values are reduced from those used in the groundwater flow model.

Part of the rationale for scenario 4 was to evaluate the 

capability of the valley-fill aquifer to satisfy an increasing 

demand for municipal water. Based on the results shown in 

figure 59, extra net pumpage of more about 14,000 acre-ft/yr 

cannot be sustained without additional recharge of either 

native or imported water. Clearly, the extra net pumpage in 

scenario 4b (35,000 acre-ft/yr) cannot be sustained without 

additional recharge. This result infers that if a sizeable percentage of future municipal demand, estimated to be as much 

as 50,000 acre-ft/yr, is to be met using ground water, then 

some additional recharge is needed if ground-water levels are 

to be maintained above historical minimums. 

Scenario 5: Optimal Hydraulic Containment of 

Contaminated Ground Water in the Newmark 

Area

Scenario 5 uses the ground-water flow and constrained 

optimization models to determine the minimum pumpage necessary to prevent further movement of contaminated ground 

water away from the Newmark area, designated by the U.S. 

Environmental Protection Agency as a superfund site (fig. 61). 

The water-management plan designed to accomplish this goal 

consists of installing several production wells along the leading edge of the contaminated ground water. The idea is that 

pumping from these wells will induce all contaminated ground 

water to flow toward the wells, in effect creating a hydraulic 

barrier preventing further contamination of the valley-fill 

aquifer. Water extracted from the wells then will be treated and 

distributed for municipal use. The purpose of this scenario is 

to determine whether this plan is likely to succeed, and if so, 

how the wells can be operated optimally.

The water-management plan was developed by the U.S. 

Environmental Protection Agency in order to mitigate the 

ground-water contamination related to the Newmark site. The 

plan was designed by URS Corporation (1993) from field data 

and from use of a site-specific ground-water flow model (URS 

Corporation, 1991a,b). The location of the planned wells, 

referred to locally as the Newmark barrier wells, is along 

the south edge of the contaminated area as defined in 1998. 

The plan includes actual sites and design criteria for the five 

planned barrier wells shown in figure 61. Because no contamination was found in the upper hydrogeologic units near the 

south edge of the contamination, each barrier well is designed 

to extract ground water only from the middle and lower hydrogeologic units. These units correspond to the lower layer of 

the ground-water flow model described in this report. The stratigraphy, hydrogeologic units, and model layers in the vicinity 

of the Newmark contamination site are shown on section A–A ́

(figs. 23, 24, and 37). An additional four potential sites, each 

having a single well, were included in the optimization model 

in order to identify possible operational improvements from 

having additional barrier wells (fig. 61).

The optimization model is formulated to minimize total 

pumpage from the nine barrier wells subject to control of 

the simulated head gradient along the edge of the Newmark 

contamination site. Each well is assumed to have a maximum 

extraction rate of 3.5 ft3/s, a rate typical of other production 

wells in the area. None of the wells has any recharge capability. No ground water is extracted from wells located within 

the contaminated area. All other recharge and discharge is 

assumed to be unmanaged—simulated by the ground-water 

flow and optimization models, but not controlled. 

120 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 61. Results from water-management scenario 5 in the San Bernardino area, California, 1999–2030. Scenario 5a uses the 5 

planned wells; scenario 5b uses the 5 planned and 4 proposed wells. Scenario 5a uses all hydraulic-gradient constraints; scenario 5b 

uses only the 9 hydraulic-gradient constraints along the southern boundary.

Evaluation of Selected Water-Management Alternatives 121

Former marshland

Fault or ground-water

barrier-May be concealed

or approximately located

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood Lake

Cajon

Cable Cr

Creek

River

River

Cr

Plunge

Warm

Santa

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Area of contaminated

ground water-Newmark

Superfund site

15

215

10

215

15

20' 15' 10'

Bunker Hill and Lytle

Creek basins

EXPLANATION

Redlands Redlands

Crafton Hills

0 6 KILOMETERS

0 6 MILES

1 MILE

0 1 KILOMETER

0

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino San Bernardino

Badlands

Shandin

Hills

See detail of this

area below Perris Hill

Artificial-recharge basin

"Infeasible" indicates

no mathematical

solution exists

Top of bar indicates

maximum capacity;

shaded part of bar

indicates used capacity; Barrier wells Hydraulic-gradient

constraint-Arrow

indicates direction of

required ground-water

flow

Planned

Proposed

Configuation of barrier wells around areas

of contaminated ground water

Areas outside Bunker

Hill and Lytle Creek basins

Shandin

Hills

SCENARIO

0

30

40

50

20

10

5a 5b

TOTAL PUMPAGE,

IN THOUSANDS OF

ACRE-FEET PER YEAR

Total pumpage for

barrier wells

31.5

17.5Infeasible

17.0

San Bernardino Mountains

Gabriel

Mts

San

Boundary of Santa Ana

River drainage basin

YUCAIPA BASIN

The Zanja

Seven Oaks Dam

34

15'

34

10'

34

05'

117 25' 117 05'
Gradients are constrained for about one half of the site as 

shown in figure 61. Ground-water flow through the northern 

half of the site is assumed to be restricted sufficiently by the 

San Bernardino Mountains and Shandin Hills, which represent 

impermeable bedrock boundaries. The optimization model 

requires that the simulated head gradient along the edge of 

the site slopes in toward the contaminated ground water. Only 

gradients in the lower model layer are included as constraints 

because only this layer is believed to be contaminated. The 

precise mathematical formulation of the optimization model 

minimizes total pumpage from the barrier wells (eq. 23) subject to annual constraints on hydraulic gradients (eq. 31) and 

bounds on pumpage (eq. 36). 

As with the other water-management scenarios, a 32-year 

simulation period (1999–2030) was used for scenario 5. To 

simulate likely future hydrologic conditions, the values of 

recharge and pumpage used in scenario 2 also were used in 

scenario 5. The only difference from conditions described for 

scenario 2 is that during 1999–2030, no pumpage is permitted for any production well within the contaminated area and 

pumpage from each barrier well is assumed to range from zero 

to its maximum value.

Scenario 5 has a total of 288 decision variables (9 well 

sites times 32 time periods) and 1,472 constraints (46 gradient locations times 32 time periods). Each decision variable 

also has an upper and lower bound, which adds another 576 

constraints (288 decision variables times two bounds). A total 

of ten MODFLOW simulations were required for scenario 5 

(nine decision variables plus one unmanaged condition) to create the necessary response functions (figs. 49 and 50). 

Results from scenario 5 are shown in figure 61. The most 

important result is that the maximum pumping rate of 3.5 ft3/s 

for each of the five planned barrier wells is insufficient to 

satisfy the specified gradient constraints (scenario 5a, fig. 61). 

Gradients along the east and west sides of the contaminated 

area cannot be controlled with the five wells, nor can gradients 

at the far east and far west edge of the southern boundary. 

Only by using all nine wells can the gradient along the entire 

southern edge be reversed, toward the contamination (scenario 

5b, fig. 61).

Figure 62. Minimum annual pumpage needed to control hydraulic head gradients along the southern edge of 

contamination in the Newmark area, San Bernardino, California, 1999–2030. The westernmost well reaches the 

maximum annual pumpage of 3.5 cubic feet per second during four years.

122 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Barrier wells

Planned

West East

Proposed

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5 Maximum pumpage

4.0

1990 2000 2010 2020 2030 2040

YEAR

PUMPAGE, IN CUBIC FEET PER SECOND

1

1 2 3 4 5 6 7 8 9

2

3

4

5

6

7

8

9

Maximum annual pumpage at

 barrier wells

Relative location of barrier wells

EXPLANATION

Well 1

Well 9 Well 2
The minimum total pumpage from the nine wells is about 

435,000 acre-ft for the 32-year period, or about 2.1 ft3/s per 

well. Minimum annual pumpage for each well is shown in 

figure 62. The fluctuations in minimum pumpage mirror fluctuations in recharge: during years of high runoff, pumpage is 

low; during years of low runoff, pumpage is high. This pattern 

is the opposite of what was expected. The increase in head to 

the north as a result of recharge is not as much a determinant 

of optimal pumpage as the decrease in head to the south as a 

result of less recharge and greater pumpage from other wells 

during years of low runoff (figs. 25 and 31). 

Minimum pumpage at most wells is nearly the same, 

fluctuating from about 1.5 ft3/s to about 2.5 ft3/s. In contrast, 

minimum pumpage at the westernmost well fluctuates from 

about 2.5 ft3/s to the maximum capacity of 3.5 ft3/s, and 

exceeds about 2.7 ft3/s for most of the time. Pumpage at this 

well is a binding constraint, meaning the optimal solution 

is most sensitive to head gradients near the well. Installing 

an additional production well further to the west likely will 

improve control of the southern boundary and likely will 

reduce the total pumpage required from all nine wells. 

 Further use of the optimization model determined that 

total pumpage from the five planned wells would need to 

exceed 1,480,000 acre-ft for the 32-year period, or about 12.8 

ft3/s per well, in order to satisfy all gradient constraints along 

the southern edge of the contaminated area. This solution 

is physically unrealistic for a line of production wells in the 

Bunker Hill basin. Such high rates would result in excessive 

in-well drawdown and could induce additional land subsidence. Although this is an unrealistic solution, it illustrates the 

magnitude of the water-management problem. Ground water 

flowing east and then south around Shandin Hills tends to 

diverge, partially bypassing the line of barrier wells 

(fig. 61). Wells to the east and west of the contaminated area 

(fig. 31) tend to pull the contamination in those directions. 

Both the high transmissivity of the valley-fill aquifer and the 

fluctuating recharge and pumpage make the problem hydraulically difficult, as illustrated by these optimization results.

Neither solution presented in figure 61 can adequately 

control head gradients along the east and west sides of the 

contaminated area using either five or nine wells. To better 

undertand this result, 38 test cases were developed using the 

basic formulation of the optimization model for scenario 5. 

Different combinations of head gradients and pumpage capacity were used to identify a range of optimal solutions, or more 

precisely a suite of infeasible solutions. Most test cases were 

infeasible, indicating that control of the contamination boundary in all locations for all years is an elusive goal. If hydraulic 

control of the plume is possible in the real world, it will not be 

easy using only the nine wells shown on figure 61. 

A more common design of hydraulic control of groundwater contamination is to install wells to pump from within 

the contaminated area. Because of the difficulty identified by 

scenario 5 to hydraulically control contamination in the Newmark area, modifying design of the cleanup strategy to include 

extraction wells within the contaminated area may produce 

more effective hydraulic control of the contamination. Alternatively, installation of monitoring wells along the boundaries, 

particularly at the southwestern edge of the contamination, 

will help determine if contaminated ground water does evade 

the five barrier wells.

Part of testing scenario 5 was evaluating the difference 

between results from the linear constrained optimization 

model and the slightly non-linear ground-water flow model. 

Optimal pumpage from scenario 5b was simulated with the 

ground-water flow model. The resulting head gradients from 

the flow model were compared to head-gradient constraints 

from the optimization model. Any difference between the 

models is caused by a combination of numerical roundoff in 

both models and hydraulic non-linearities in the flow model. 

Although the absolute value of the heads was slightly different, the head gradients were virtually the same in both models. 

This similarity suggests that the hydraulic non-linearities 

(head-dependent stream recharge, evapotranspiration, and 

underflow) in the ground-water flow model are sufficiently 

distant from the barrier wells that any difference is muted by 

the relatively high transmissivity of the valley-fill aquifer. 

Use of the optimization model in scenario 5 illustrates 

how defining the feasible and infeasible regions (fig. 46) can 

be useful in gaining a better understanding of a water-management problem. Infeasible solutions typically highlight a critical hydrogeologic aspect of a water-management problem—an 

aspect that may or may not have been recognized from the 

outset as a controlling feature. In the case of scenario 5, this 

critical hydrogeologic aspect is the difficulty of controlling a 

dynamic boundary in a highly permeable aquifer. 

Scenario 6: Optimal Pumpage Using New Wells 

to Control Ground-Water Levels in the Former 

Marshland

Scenario 6 uses the ground-water flow and constrained 

optimization models to identify the minimum pumpage necessary to control ground-water levels in the former marshland 

of the San Bernardino area. The additional pumpage comes 

from new production wells that could be installed along three 

proposed extensions of the Baseline feeder pipeline (fig. 63). 

The water-management objective for scenario 6 is not only 

to prevent the adverse effects of high ground-water levels, 

such as the historical damage caused by elevated hydrostatic 

pressure and the potential damage that could be caused by 

liquefaction during a large earthquake, but also to prevent the 

adverse effects of low ground-water levels, such as the possible reoccurrence of land subsidence. 

Evaluation of Selected Water-Management Alternatives 123
Figure 63. Design of water-management scenario 6 in the San Bernardino area, California, 1999–2030.

124 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

LT AU F

AN S

S EA RD AN

Waterman

Canyon

Creek

Devil

Canyon

Creek

Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood

Lake

n jo a C

r C le ba C

keer C

ver Ri

re iv R

Cr

ge lun P

arm W

ta an S

ta naS

na A

anA

r

Cr C

City

lli M r C

le t yL

Cr

eo ot imT an S

Cr

The Zanja

Seven Oaks Dam

15

215

10

215

15

Major exsisting pipeline

20' 15' 10'

EXPLANATION

lls Hi

on ft ra C

0 6 KILOMETERS

0 6 MILES

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

sdn la daB

Shandin

Hills

Perris Hill

l ier baG

ts M

naS

CR

Proposed well site

l ier baG

ts M

naS

ns ai nt ou

o M in rd na er B an S

l ier baG

ts M

naS

Proposed pipeline

Arc showing 20,000-foot distance from

basin outflow

34

15'

34

10'

34

05'

117 25' 117 05'

Norton Air Force

Base

Basin boundary-Bunker Hill and Lytle Creek Hydraulic-head constraint site

ground-water basins shaded in darker gray comprise

the San Bernardino area, as defined in this report

Former marshland

Fault or ground-water barrier-May be concealed or approximately located

Artificial-recharge basin
The area of the Bunker Hill and Lytle Creek basins that 

has generated the greatest concern about extreme groundwater levels is near the former marshland. Since 1945, 

hydrostatic pressure in this area has been sufficiently high at 

times (late 1940’s, early 1980’s) to cause damage to public 

infrastructure, and sufficiently low at other times (mid 1960’s) 

to cause land subsidence of more than 1 foot (figs. 43

and 55). Control of ground-water levels throughout this area 

is achieved in scenario 6 by a uniform grid of hydraulic-head 

constraint sites shown in figure 63. Each site represents an 

upper and lower cell in the ground-water flow model, which is 

used to calculate the effect of pumpage on simulated hydraulic 

head. The effects of initial and boundary conditions and of all 

unmanaged stresses also are calculated by the flow model. The 

unmanaged stresses in scenario 6 are the same as those used in 

scenario 2. As in scenarios 1–5, the same 32-year management 

period, 1999–2030, is used.

For each of the 32 years, simulated head in the upper 

model layer at each of the constraint sites is required to be at 

least 30 ft below land surface, the depth necessary to prevent 

liquefaction and to avoid damage to subsurface structures from 

elevated hydrostatic pressure. Because elevated head in the 

lower model layer does not by itself cause hydrostatic damage, 

it is not restricted. To prevent additional land subsidence, head 

in both the upper and lower model layers at the constraint sites 

is required to be above the respective minimum simulated head 

during 1945–98, the calibration period for the ground-water 

flow model. These minimum heads are assumed to represent 

the pre-consolidation heads that probably were reset as a result 

of the significant decline of ground-water levels between 1945 

and 1970.

As part of the overall water-management plan developed 

by Camp, Dresser, and McKee (1995a), three possible extensions of the Baseline feeder pipeline were identified. The first, 

referred to as the “9th Street feeder east,” continues east on 

9th Street to Sterling Avenue. The second, referred to as the 

“South end feeder,” continues south from the first extension, 

down Arrowhead Avenue past the San Jacinto fault. The third, 

referred to as the “Central feeder,” bisects the South end feeder 

at Orange Show Road. A generalized pattern of possible 

production wells was designed to accompany each extension 

(fig. 63). A total of 29 possible new well sites were chosen, 

each to be about 2,460 ft apart, a distance equivalent to three 

model cells and three times the distance between barrier wells 

described in scenario 5. The goal in choosing the well sites 

was to provide a large number of high-capacity wells that 

would provide an abundant pumping capacity and the necessary well interference needed to control ground-water levels 

over a large area. The new well sites were located adjacent to 

the major pipelines in order to limit the cost of installing any 

additional pipe needed to convey water from the new wells 

to the major pipelines. New well sites also were restricted to 

the general area of the former marshland, defined as within a 

distance of 20,000 ft from basin outflow. The same approximation was used as part of scenario 4 (fig. 60).

All water extracted from the 29 well sites was assumed to 

be pumped directly into the respective pipelines, or if necessary, treated or blended prior to being added to flow in one of 

the pipelines. The eventual use of the pumped water was not 

defined; however, the additional pumpage was assumed not 

to replace any existing pumpage in the Bunker Hill or Lytle 

Creek basin, nor to contribute any return flow to any part of 

these basins. Because the objective of the dewatering sites is 

to control shallow ground-water levels, each well was assumed 

to be perforated only opposite hydrogeologic units UCM and 

UWB, which are represented as the upper layer of the groundwater flow model (fig. 37). The maximum pumping rate at 

each site is assumed to be 2.2 ft3/s, a sustainable pumping rate 

commonly achieved by nearby existing wells.

The mathematical formulation of the optimization model 

for scenario 6 minimizes the sum of total pumpage from the 

dewatering wells (eq. 23), subject to constraints on groundwater levels (eqs. 28a, b) and bounds on pumpage (eq. 36). 

This basic initial formulation was chosen for analysis in order 

to investigate the hydraulic characteristics controlling the 

solution to scenario 6. A more complex formulation could 

have minimized cost of additional pumpage, subject to the 

same constraints and bounds. Although cost is a commonly 

used objective in operations research, it can disguise important 

hydrologic characteristics of the problem and assigning costs 

can be highly controversial. If analysis of scenario 6 were to 

be expanded to include cost, important considerations would 

be both the fixed cost of installing the wells, likely to be about 

$1 million each, and the variable cost of pumping each well. 

Quadratic and integer programming techniques can be used to 

solve this type of optimization problem (Hillier and Lieberman, 1980, p. 714–755). 

Ground-water levels were constrained within the general area of the former marshland, using the same 20,000-ft 

distance from basin outflow used to locate the possible new 

well sites (fig. 63). Ground-water-level control sites were set 

at every fifth model cell within the 20,000-ft distance. This 

spacing was chosen to balance the need to ensure simulated 

ground-water levels were controlled within the former marshland, with the desire to reduce the total number of constaints 

in the optimization model. Although computationally more 

time-consuming, every model cell in the former marshland, or 

in the entire model domain, could have been used. 

Scenario 6 has a total of 928 decision variables (29 well 

sites times 32 time periods) and 5,568 constraints (58 groundwater-level control sites times 3 ground-water levels times 

32 time periods). Each decision variable also has an upper 

and lower bound, which adds another 1,856 constraints (928 

decision variables times two bounds).To obtain the response 

information for scenario 6, thirty simulations of the groundwater flow model were required: one for each managed well 

and one for the unmanaged condition. 

Evaluation of Selected Water-Management Alternatives 125
Figure 64. Infeasible head constraints for scenario 6. A, infeasibilities caused by unmanaged stresses. B, infeasibilities caused 

by attempting to decrease ground-water level to 30 feet below land surface, and C, temporal distribution of infeasibilities in B.

126 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

LT AU F

AN S

S EA RD AN

Waterman

Canyon

Creek

Devil

Canyon

Creek

Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood

Lake

n jo a C

r C le ba C

keer C

ver Ri

re iv R

Cr

ge lun P

arm W

ta an S

ta naS

na A

anA

r

Cr C

City

lli M r C

le t yL

Cr

eo ot imT an S

Cr

The Zanja

Seven Oaks Dam

15

215

10

215

15

20' 15' 10'

lls Hi

on ft ra C

0 6 KILOMETERS

0 6 MILES

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

sdn la daB

Shandin

Hills

Perris Hill

l ier baG

ts M

naS

CR

l ier baG

ts M

naS

ns ai nt ou

o M in rd na er B an S

l ier baG

ts M

naS

34

15'

34

10'

34

05'

117 25' 117 05'

Norton Air Force

Base

Scenario 6: Heads too low.

Three existing infeasibilities are

caused by unmanaged stresses.

EXPLANATION

Feasible constraint

Infeasible constraint

Hydraulic-head constraint site

A

Basin boundary-Bunker Hill and Lytle Creek 

ground-water basins shaded in darker gray comprise

the San Bernardino area, as defined in this report

Former marshland

Fault or ground-water barrier-May be concealed or approximately located

Artificial-recharge basin
Figure 64.—Continued.

Evaluation of Selected Water-Management Alternatives 127

LT AU F

AN S

S EA RD AN

Waterman

Canyon

Creek

Devil

Canyon

Creek

Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake

Arrowhead

Silverwood

Lake

n jo a C

r C le ba C

keer C

ver Ri

re iv R

Cr

ge lun P

arm W

ta an S

ta naS

na A

anA

r

Cr C

City

lli M r C

le t yL

Cr

eo ot imT an S

Cr

The Zanja

Seven Oaks Dam

15

215

10

215

15

0

50

100

150

200

250

300

350

2000 2010 2020 2030

CALENDAR YEAR

0

2

4

6

8

10

12

14

16

18

NUMBER OF INFEASIBLE

HEAD CONSTRAINTS

PERCENT ANNUAL RUNOFF

IN THE SANTA ANA RIVER

Percent runoff

Infeasible

constraints

20' 15' 10'

lls Hi

on ft ra C

0 6 KILOMETERS

0 6 MILES

Base digitized from U.S. Geological

Survey 1:100,000 San Bernardino, 1982

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

San Bernardino

sdn la daB

Shandin

Hills

Perris Hill

l ier baG

ts M

naS

CR

l ier baG

ts M

naS

ns ai nt ou

o M in rd na er B an S

l ier baG

ts M

naS

34

15'

34

10'

34

05'

117 25' 117 05'

Norton Air Force

Base

Scenario 6: Heads too high.

117 infeasibilities at 18 locations are

caused by attempting to decrease

ground-water level to 30 feet below

land surface. 

B

C Temporal distribution of 117 infeasibilities, spatially shown in B.
Although formulating scenario 6 was relatively simple, 

finding a feasible solution was not. Tens of model runs using 

MINOS identified hundreds of infeasibilities, and in the end 

no feasible, much less optimal solution was found. Most 

knowledge acquired from scenario 6 came from successive 

attempts to remove infeasiblities and progressively learning 

more about the hydraulic or hydrologic reason for the persistently infeasible solution. 

Results from scenario 6 indicate numerous hydrologically 

important findings. First, in the area of Lytle Creek, recent 

new pumpage appears to have lowered simulated heads below 

any simulated value during 1945–98. This result suggests that 

additional pumpage without sufficient additional recharge will 

result in ground-water levels below the constraint to prevent 

land subsidence (fig. 64A). Whether actual land subsidence 

will occur is unknown, but these infeasible head constraints 

are in the same area as historical land subsidence (fig. 55).

Second, the area where ground-water levels remain too 

high coincides remarkably well with the former marshland 

(fig. 64B). As noted by previous researchers, ground water 

accumulates, especially in wet years, in the vicinity of Warm 

Creek. This hydrologic process was referred to as “rising 

ground water” by Hardt and Hutchinson (1980), who identified the impending problems of high ground-water based on 

predictive simulations with a previous ground-water flow 

model. Actual damages caused by high ground-water levels 

began occurring in about 1979 and continued until a sequence 

of years with less runoff and less imported water resulted in 

falling ground-water levels from about 1984 to 1992. The 

location of these infeasible head constaints is the same location of high ground-water levels that caused infrastructure 

problems, prompting the lawsuit in 1986.

Third, fluctuating recharge and pumpage during 1999–

2030 make control of ground-water levels challenging. These 

fluctuations are essentially the background response from 

scenario 2. Ground-water levels in many years are adequately 

controlled with zero additional pumpage or with the capacity 

and configuration of wells in scenario 6. In some wet years, 

however, too much recharge arrives and the 29 proposed wells 

cannot overcome this rise in ground-water levels. The number 

of infeasible head constraints per year compared to the percent 

runoff for the Santa Ana River is shown in figure 64C. In general, years with more runoff have more infeasibilities. A subtle 

aspect of this result is that prior pumpage in drier years is not 

sufficient to adequately reduce the rising ground-water levels 

in wet years. Water managers will not know future conditions, 

but the optimization model has knowledge of impending wet 

years, and still cannot solve the problem.

Figure 65. Minimum and maximum pumpage for scenario 6 for the San Bernardino area, California. 

The apparent decrease in optimal minimum pumpage is caused by omitting infeasible head 

constraints from the optimization model. The actual minimum pumpage required to lower high groundwater levels, as indicated by the dashed line, is likely to be somewhat greater than that predicted by 

the optimization model. The maximum pumpage that can be obtained without having ground-water 

levels fall too low is approximately 20,000 acre-feet per year.

128 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

0

5,000

10,000

15,000

20,000

25,000

0 5 10 15 20 25 30 35 40

PUMPAGE, IN ACRE-FEET PER YEAR

Optimal maximum pumpage

Optimal minimum pumpage 

with infeasibilities

Estimated minimum 

pumpage, without

infeasibilities

HYDRAULIC-HEAD CONSTRAINT, IN FEET BELOW LAND SURFACE

Feasible

region

Infeasible region

Data point from optimization model
To obtain additional information from scenario 6, all 

infeasible head constraints were eliminated from the optimization model. Without the four infeasible (too low) head 

constraints at three locations (fig. 64A) and the 115 infeasible 

(too high) head constraints at 18 locations (fig. 64B), optimal 

solutions were obtained for several test cases. The minimum 

pumpage required to maintain head in the upper model layer 

at least 0, 10, 20, or 30 ft below land surface is shown in 

figure 65. In each test case, all constraints relating to land 

subsidence were satisfied, except the four that were deleted 

(fig. 64A). The unusual shape of the curve of minimum pumpage likely results from the progressive omission of infeasible 

constraints. A more likely linear shape might result if all 

infeasible (too high) constraints were kept in the optimization 

model and adequate areally distributed pumpage capacity were 

simulated. If this linear relation is valid, the minimum value of 

pumpage needed to lower simulated heads in the upper model 

layer to 30 ft below land surface is about 18,000 acre-ft/yr.

Testing also identified the maximum pumpage that 

could be obtained from the 29 wells without violating head 

constraints designed to prevent additional land subsidence. 

Optimization results suggest that an average of about 20,000 

acre-ft/yr of additional pumpage could be obtained from the 

San Bernardino area during the 32-year management period 

used for scenario 6 (fig. 64C).

In summary, however, pumpage quantity and spacing 

in scenario 6 is insufficient to solve the slowly evolving high 

ground-water problem—despite having more than 70,000 

acre-ft of installed capacity at 29 separate well sites along the 

three proposed extensions of the Baseline feeder. This result 

from the optimization model suggests that careful monitoring of ground-water levels is needed to identify any longterm 

trends. As soon as an upward trend is identified, additional 

pumpage needs to be used to control the rising ground water 

because as found during 1978–84, high ground-water levels 

in the San Bernardino area cannot be lowered significantly in 

a couple of months or couple of years. The inability of the 29 

wells proposed for scenario 6 to solve the rising ground-water 

problem over a 32-year period highlights the need to use a 

more areally extensive network of dewatering wells, such as 

illustrated by results from scenario 4.

Discussion

These seven water-management scenarios illustrate some 

of the more important characteristics of the hydrologic system 

in the San Bernardino area. Runoff from the adjacent San 

Bernardino and San Gabriel Mountains provides abundant 

recharge in an otherwise semiarid region. This recharge, in 

addition to ground-water pumpage that comprises essentially 

all ground-water discharge, causes significant, continuous 

fluctuations in ground-water levels and ground-water storage, 

as illustrated by scenarios 2, 3, and 4. The large areal size and 

high specific yield of the valley-fill aquifer create long-term 

trends in ground-water levels and storage that last for decades, 

as illustrated by scenarios 1 and 2. Both the short-term, detectable fluctuations and the longterm, less detectable trends make 

water-management decisions more difficult than they would be 

in a smaller, less hydraulically dynamic ground-water basin. 

For example, the installed pumpage capacity necessary to 

control ground-water levels needs to be larger than if the aquifer storage and fluctuations in aquifer storage were less. Perceiving long-term trends is made more difficult by the widely 

varying conditions that occur over a period of a few years. 

Because of this difficulty in perceiving trends from measured 

data, simulations using the ground-water flow model can be 

both instructive and important to illustrate the wide-ranging 

and long-term implications of water-management decisions.

Scenarios 1 and 2 clearly indicate that ground-water 

levels in most of the San Bernardino area will remain similar to levels experienced during 1983–98 if similar climatic 

conditions occur and 1998 water-management operations 

are continued. This conclusion is tempered by results from 

scenario 4, which illustrate that different assumptions about 

pumpage can result in a progressive decline in ground-water 

levels. Even during this decline, however, annual fluctuations 

in ground-water levels may pose a threat of additional damage 

from elevated hydrostatic pressure or from liquefaction during 

an intense earthquake. 

Evaluation of Selected Water-Management Alternatives 129
Results from scenarios 2, 3, and 4 suggest that additional 

pumpage is needed to control ground-water levels, but that 

the magnitude of the pumpage needs to be evaluated annually. Scenario 4 indicates that the capacity of existing wells is 

sufficient to accomplish this control; however, this physical 

capacity was not used during 1978-84 when rising groundwater levels caused extensive damage to foundations, basements, and flood-control channels. New pipelines, such as the 

three proposed extensions to the Baseline feeder, may aid in 

conveying additional pumpage to a place of beneficial use, 

but scenario 6 indicates that areally distributed pumpage is 

needed, not just extra pumpage from wells located along the 

new pipelines. A related finding from scenario 5 indicates that 

the high transmissivity of the valley-fill aquifer makes forceful 

control of ground-water levels or gradients difficult to achieve 

using only a few sites. A broader-scale solution probably is 

necessary, though it may be logistically and politically more 

difficult.

For the past 50 years, native recharge to the valley-fill 

aquifer has been sufficient, sometimes even excessive. If 

urbanization of the San Bernardino area continues and local 

demand for water increases as projected, then availability 

and use of imported water becomes critical. As indicated by 

scenario 4, the valley-fill aquifer cannot supply more than 

about an additional 10,000 acre-ft of ground water unless the 

recharge rate of native runoff is increased or water imported 

from outside the San Bernardino area is artificially recharged 

to the valley-fill aquifer. The great distance from the artificialrecharge basins to the production wells and the high specific 

yield of the valley-fill aquifer create a long response time from 

the largest basins on the Santa Ana River and Mill Creek to 

the area of most production wells. This hydraulic characteristic can be an aid in effective management of both native and 

imported water. Whenever inexpensive water becomes available, in effect, it can be stored in the valley-fill aquifer while 

in transit to the area of the production wells.

The primary caveat in this approach is that sufficient production eventually needs to extract the recharged water or high 

ground-water levels will result. As indicated from scenario 

4, the quantity, timing, and location of the extraction need to 

be determined carefully so that ground-water levels do not 

decline and cause land subsidence. The much shorter response 

time from other artificial-recharge basins, such as the Waterman basin, suggests that use of these basins may be helpful 

in making short-term adjustments to declining ground-water 

levels in the area of the production wells.

Attempts to control migration of the Newmark contamination present multiple challenges as indicated by results from 

scenario 5. These challenges relate to the hydraulics of the 

simulated ground-water flow system and are compounded by 

dispersion of the contaminates and a more complex threedimensional aquifer structure than that simulated with the 

ground-water flow model. The hydraulic challenges illustrated 

in this study include the high transmissivity of the valley-fill 

aquifer that makes creating and maintaining a hydraulic barrier 

difficult during fluctuating conditions of runoff, recharge, and 

pumpage. Also, the proximity of the Newmark barrier wells 

to other areas of major pumpage and to the former marshland 

can create a conflict in achieving both hydraulic control of 

the Newmark contamination and hydraulic control of groundwater levels that are either too high or too low. Resolution of 

this conflict may require some modification to the strategy that 

uses only barrier wells to control migration of the Newmark 

contamination.

Developing additional scenarios utilizing one or both of 

the ground-water flow and optimization models likely will 

result in additional insights about the valley-fill aquifer and 

about the interaction among the several conflicting water-management issues. Development of a scenario, however, often is 

not a quick and easy exercise despite its apparent simplicity. 

Consistency needs to be achieved among the many recharge 

and discharge components, between historical data and future 

projections, and between water-management concepts and 

numerical representation of those concepts. The payoff for the 

substantial effort in developing a well thought out, numerically 

robust scenario is hydrologic insight that would be difficult to 

gain in any other way.

Development and use of ground-water flow models is 

now common throughout the world and is an important part 

of gaining hydrologic insight, but numerical convergence of 

large, complex flow models, such as this model of the San 

Bernardino area, is an ongoing concern (Kuniansky and Danskin, 2003). A lack of convergence can occur in solving any of 

the tens of thousands of timesteps needed to prepare response 

simulations for an optimization model. These numerical 

errors, in turn, can cause uncertain results in the optimization 

model and may require re-formulation of the water-management scenario.

Computational time and accuracy required to solve 

a scenario combining ground-water flow and constrained 

optimization models mostly is determined by the flow model. 

For example, in scenario 6, calculating the 29 response functions required about 15 hours; solving the optimization model 

required about 1 minute. This disparity of time is typical of 

ground-water management problems and illustrates the need to 

have an efficient flow model. Total computational time for scenarios similar to those in this report will be determined by the 

number of decision variables requiring a response function, by 

the number of management time periods, and by the complexity and required numerical accuracy of the flow model.

An optimization model like a good ground-water flow 

model, needs to be as simple as possible. This goal of parsimony was central in designing scenarios 5 and 6. As observed 

by H.M. Wagner (1975, p. 6), the relatively simple process 

of designing an optimization model can result in a model that 

is too complex to critique or interpret. At the other end of 

the spectrum, having too few decision variables can produce 

an optimization model with too few degrees of freedom and 

essentially no feasibility space (fig. 46). Design of an effective 

optimization model is as much art as science, achieving a balance between these potential problems.

130 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Instructive management scenarios can be formulated by 

using just the ground-water flow model as in scenarios 1–4, 

or by using the combined flow and optimization models as 

in scenarios 5 and 6. An important difference exists between 

these two approaches. Results from a flow-model scenario 

such as in scenario 4 commonly are observed and interpreted 

with the goal of identifying general trends. In contrast, results 

from an optimzation model require 100 percent adherence 

to specific requirements. In scenario 6, each of the 7,424 

constraints must be satisfied, not just most, or nearly all. This 

provides an important advantage in use of a optimization 

model compared to a ground-water flow model to inspect the 

results of a potential water-management alternative. But it also 

requires a conformance that may not be as easy to achieve 

hydraulically, as it is to say in words during formulation of the 

scenario. 

The experience of developing and applying constrained 

optimization techniques in the San Bernardino area often 

went something like this: posing what seems to be a realistic 

optimization problem based on discussions with knowledgable 

water managers; finding the problem is infeasible; redesigning the problem to loosen some overly optimistic constraints; 

finding the problem remains infeasible for another hydraulic 

reason; loosening or removing additional constraints; possibly 

continuing these last steps several more times; finding an optimal solution; then progressively tightening some constraints to 

achieve an instructive, but tightly constrained optimal solution. The eventual benefit of this sequence is much more than 

a mathematically optimal answer to the problem. Rather, the 

larger benefit is a dramatically improved understanding of the 

aquifer system.

Suggestions for Future Work

Several decades of continuing investigations in the San 

Bernardino area have resulted in a large quantity of data and 

a much improved understanding of the surface-water and 

ground-water systems. This understanding has enabled a quantitative analysis of the area using both ground-water flow and 

constrained optimization models. But, as shown in figure 66, 

applied scientific investigations typically do not follow a linear 

path from data, to concepts, to models. Rather, they tend to 

follow an iterative path of learning that involves collection of 

data, refinement of concepts, and testing of the new data and 

concepts with improved mathematical models. The models, in 

turn, prompt new questions about the data and concepts and 

can be used to define which additional data are most important 

to refine concepts or to improve predictive capability of the 

model.

This pattern of iterative investigation applies to water 

management in the San Bernardino area. The present analysis 

evolved from use of an initial ground-water flow model that 

identified critical data deficiencies, to collection of new data, 

to refinement of hydrologic concepts, to evaluation of data and 

concepts with improved simulation and optimization models. 

Future work in the San Bernardino area likely will focus first 

on improved data collection to validate, extend, or discard 

existing hydrogeologic concepts. Subsequent studies likely 

will use modified ground-water flow, solute-transport, and 

optimization models to test the new data and concepts and to 

refine present conclusions about water management. Suggestions for this future work are listed below by general topic and 

are shown by general location in figure 67.

Figure 66. General process of scientific inquiry.

Suggestions for Future Work 131

11

11

14

21

14

21

Data 21

Models

Concepts
Figure 67. Water-management sites in the San Bernardino area, California, 1998.

132 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives

Waterman

Canyon

Creek

Devil

Canyon

Creek Waterman

Canyon

Creek

Devil

Canyon

Creek

Lake Arrowhead

Silverwood

Lake

Cable Cr

Creek

River

River

Plunge

Santa

Ana

Ana

Cr Cr

City

Mill Cr

Lytle

Cr

San Timoteo

Cr

Cajon

Zanja

The

Seven Oaks Dam

15

215

10

215

15

D

B

C

A

I

J

K L

H

G

F

E

Gabriel

Mts

c

f

g

e

b

d

a

San Bernardino Mountains

Continuous gaging station

11051501 Santa Ana River near Mentone

Plunge Creek near East Highlands

East Twin Creek near

Arrowhead Springs

Devil Canyon Creek near

San Bernardino

11058500

11063680

11062001

11060400

Lone Pine Creek near Keenbrook

Lytle Creek near Fontana

Cajon Creek below Lone Pine

Creek, near Keenbrook

11063510

11055501

11063500

A

H

G

E

F 11055801 City Creek near Highland

D

C

J

B

I 11065000 Lytle Creek at Colton

Warm Creek near San Bernardino

K

L

Santa Ana River at E Street

San Timoteo Creek near Loma

Linda

11059300

11057500

EXPLANATION

Crafton Hills

R 4 W R 4 W R 3 W R 3 W R 2 W

T

1

S

T

1

S

T

1

N

T

1

N

T

2

N

R 6 W R 5 W R 5 W

T

2

S

Badlands

Shandin

Hills

Perris Hill

San Bernardino Mountains

Gabriel

Mts

Priority area for installation

of additional multiple-depth

wells

YUCAIPA BASIN

Shaded relief base from U.S. Geological Survey 

digital elevation data, 1:24,000-scale

Warm Cr

Santa

Redlands

San Bernardino Highland

Basin boundary-Bunker Hill 

and Lytle Creek ground-water 

basins shaded in darker gray

d 1S/4W-22D2, 4-7 SBVMWD backyard

a

c

b

e 1S/4W-22J1-4 Commerce Center

f 1S/3W-15K1-5 Riverview

g 1S/2W-7Q1-6 Cone Camp

1S/4W-2D6-8 Sierra High School

Encanto Park

Meadowbrook Park

1S/4W-4E3-6

1S/4W-10B2-4

Multiple-depth cluster well site

Fault or ground-water

barrier-May be concealed

or approximately located

Artificial-recharge basin

Former marshland

Boundary of Santa Ana

River drainage basin

0 6 KILOMETERS

0 6 MILES

20' 15' 10'

34

15'

34

10'

34

05'

117 25' 117 05'
Data

1. Measurements of surface-water discharge.—Continued monitoring of surface-water discharge, at least for the 

Santa Ana River, will provide data needed to use the several 

predictive temporal relations based on flow in the Santa Ana 

River that are presented in this report. Continued discharge 

measurements also will facilitate a critique and an update of 

the ground-water flow model.

2. Multiple-depth monitoring wells.—Additional 

multiple-depth monitoring wells will help identify aquifer 

materials, measure vertical differences in hydraulic head, and 

quantify vertical changes in ground-water quality. The areas of 

greatest need are from where the Santa Ana River crosses the 

San Jacinto fault: (1) past Redlands toward the Yucaipa basin 

and (2) past Shandin Hills toward the upper reaches of Cajon 

Creek (fig. 67). Based on a similarly stated need in an earlier 

draft of this report, three multiple-depth monitoring wells 

(sites e, f, and g on fig. 67) were installed and have provided 

valuable new information.

3. Ground-water-level measurements.—Continuous 

ground-water-level measurements at multiple-depth monitoring well sites (fig. 67) provide valuable data to critique 

hydrogeologic concepts and vertical accuracy of the groundwater flow model. Semi-annual ground-water-level measurements from existing wells throughout the San Bernardino area 

provide an effective way to critique horizontal accuracy of the 

ground-water flow model.

4. Water-quality sampling.—Sampling a broad spectrum 

of ground-water constituents, including trace elements and 

naturally occurring isotopes (hydrogen, oxygen, and carbon), 

from production wells and multiple-depth monitoring wells 

will help identify the age, occurrence, and movement of 

ground water within the three-dimensional, valley-fill aquifer. 

Water-quality data from deeper sediment will facilitate identifying and interpretating interactions between the valley-fill 

aquifer and the surrounding bedrock. Selected samples of 

surface-water quality will be important to verify concepts of 

surface-water/ground-water interaction.

5. Flowmeter logs.—Flowmeter logs collected from as 

many production wells as possible will help define the relative quantity of water that enters each well from different 

hydrogeologic units and how the wells connect and transmit 

ground water between permeable zones within the aquifer 

system. These data will improve the definition and mapping of 

hydrogeologic units and will allow for a more accurate vertical distribution of pumpage in the ground-water flow model. 

Flowmeter logs commonly use an impeller or spinner tool to 

measure flow inside the well casing. Other techniques, including dye-injection or heat pulse, may be preferrable depending 

on access to the well and rate of flow inside the well.

6. Land-surface deformation.—Measurements of landsurface deformation will aid in identifying patterns of groundwater recharge and discharge, location and extent of poorly 

permeable faults, and distribution of fine-grained deposits. 

Monitoring could use permanently installed, continuously 

recording extensometers in combination with intermittantly 

available satellite range data processed using Interferometric 

Synthetic Aperature Radar (InSAR) techniques.

7. Geographic database.—Organizing the three-dimensional geometry of the valley-fill aquifer in a powerful spatial 

database, such as a geographic information system (GIS), will 

facilitate updates and revisions to the conceptual and numerical models. In particular, including the top and bottom of the 

hydrogeologic units at individuals wells in a spatial database 

will aid in developing structural contours of the units.

Concepts

8. Depositional history.—The depositional history of 

sediment constituting the valley-fill aquifer is known only 

cursorily. Additional information will be helpful to improve 

hydrogeologic understanding, in particular the location and 

age of depositional facies.

9. Hydrogeologic units.—Extending the hydrogeologic 

units and layering of the valley-fill aquifer, as presented in 

figure 24, to other areas of the Bunker Hill and Lytle Creek 

basins will help identify any inconsistencies in the present 

hydrogeologic concepts of the aquifer system. This mapping 

requires understanding the deposition history of the valley-fill 

aquifer.

10. Upper confining member.—An improved understanding of the upper confining member (UCM, fig. 24) in routine 

recharge water, in creating perched conditions, and in moving 

water to or from deeper pumped zones is critically important. 

Entwined with understanding the UCM is understanding the 

role of open well casings and gravel-packed wells in the vertical movement of ground water.

11. Pumpage return flow.—Use of a constant return flow 

percentage applied to pumpage from 1945 to 1998, as done 

in this report, has a strong effect on ground-water flow and 

budget. Changes in use of wells and changes in land use suggest a more complex spatial and temporal calculation may be 

warranted.

12. Ground-water flow from bedrock.—Defining the 

importance of a significantly deeper ground-water flow system 

through the basement complex (fig. 24), as indicated by the 

presence of geothermal water in several wells (fig. 55), will 

aid in evaluating the conceptual flow model, which presently 

includes only the valley-fill aquifer.

Suggestions for Future Work 133
Models

13. Representing hydrogeologic units. —Updating the 

ground-water flow model with altitudes of individual hydrogeologic units, thereby enabling the use of convertible unconfined-confined storage coefficients and time-varying transmissivity, will create a more realistic flow model.

14. Underflow.—Underflow out of the ground-water flow 

model across the San Jacinto fault near Barrier J (fig. 39) is not 

well understood, but is an important part of accurately simulating ground-water flow in the Lytle Creek basin. Resolving 

discrepancies with underflow used in the ground-water flow 

model of the Rialto–Colton basin will improve reliability of 

both models.

15. Land deformation.—A land-deformation (subsidence) 

package, added to the ground-water flow model, would permit 

better simulation of aquifer storage properties and periods of 

significant change in ground-water levels. Historical subsidence of the land surface indicates that some ground-water 

pumpage was derived from permanent aquifer compaction; 

this decrease in aquifer storage is not simulated presently in 

the ground-water flow model.

16. Vertically distributed pumpage.—Automatically 

proportioning pumpage to different model layers based on 

changing head during a simulation will significantly improve 

the ability of the ground-water flow model to simulate land 

subsidence and advective transport of solutes. Presently, 

pumpage is proportioned by hand using a constant temporal 

distribution.

17. Geologic framework model.—A geologic framework model rigorously combines information about geologic 

formations, sedimentary deposits, faults, and hydrogeologic 

units. Such a model can be used to critique three-dimensional 

concepts of geologic structure, depositional history, and movement of ground water. A geologic framework model of the 

Bunker Hill and Lytle Creek basins would help provide the 

three-dimensional knowledge necessary to improve vertical 

resolution of the ground-water flow model or to develop a 

solute-transport model. 

Management

18. Use of models.—Continued use of the ground-water 

flow and constrained optimization models described in this 

report can be a useful part of advancing water management 

of the San Bernardino area. The models are well suited to critique ideas and evaluate specific plans. The ground-water flow 

model was designed to facilitate updates as new data become 

available.

19. Management-monitoring sites.—Installation and use 

of monitoring sites for surface water and ground water can aid 

in determining the effectiveness of a water-management plan 

that has been implemented.

20. Real-time data.—Public access to real-time data facilitates timely water-management decisions and helps diffuse 

potential conflicts about what the actual hydrologic conditions 

are. An example of publically accessible real-time data is the 

website for this study [http://ca.water.usgs.gov/sanbern].

21. Public meetings.—Public meetings involving the 

many water purveyors in the San Bernardino area have been 

an effective method of hearing new ideas, dispelling rumors, 

critiquing ongoing technical work, and educating decision 

makers. Continued use of the meetings will be important as 

the ground-water flow and constrained optimization models 

are used to evaluate additional water-management alternatives.

22. Monitoring possible land subsidence.—Monitoring 

possible land subsidence would be an important part of any 

water-management plan that significantly increases groundwater pumpage.

23. Redlands contamination.—Mapping the character and 

extent of the Redlands contamination (fig. 36) in three dimensions will aid in understanding historical movement and in 

critiquing management alternatives.

24. Understanding nitrate contamination.—The fate and 

transport of nitrogen species is not well understood in the San 

Bernardino area, despite the significant adverse impacts of 

high nitrate levels on ground-water quality. Improved, validated conceptual models are critically important before either 

reliable simulation models or effective water-management 

plans can be developed.

134 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Summary and Conclusions

The San Bernardino area of southern California has 

several important water-management issues that are confronting local water managers. These issues include the threat of 

liquefaction of saturated fine-grained deposits near the land 

surface in the event of a major earthquake, the possible reoccurrence of land subsidence that can result from excessive 

ground-water pumpage, a decrease in available water—both 

locally and statewide—because of possible changes in climate, 

and the ongoing closure of municipal-supply wells that are 

contaminated by organic solvents, pesticides, or nitrate. The 

issues, which have evolved over the past century (fig. 68), 

continue to become more intertwined; solving one requires an 

understanding of each of the others. The purpose of this report 

is to provide water managers in the San Bernardino area with 

improved hydrologic information and computer models to aid 

them in understanding and solving these issues.

The hydrologic information provided in this report 

includes analysis of the surface-water and ground-water 

systems in the San Bernardino area, with an emphasis on 

the valley-fill aquifer in the Bunker Hill and the Lytle Creek 

basins, for calendar years 1945–98. The computer models 

include a three-dimensional ground-water flow model of the 

valley-fill aquifer and a contrained optimization model that 

integrates information from the flow model with surfacewater and economic data. The flow model was used to assure 

consistency among the hydrogeologic concepts and to provide 

quantitative information that cannot be obtained in other ways. 

The optimization model uses linear-programming techniques 

to determine the optimal quantities of recharge and pumpage, 

subject to constraints on ground-water levels throughout the 

basin, hydraulic gradients near contaminated areas, and costs 

of imported water and ground-water pumpage. The mathematically optimal solutions derived from the optimization model 

can be used with the other hydrologic information to guide 

water-management decisions.

Major conclusions from the study are summarized below 

by topic.

Ground-Water Recharge

1. Most recharge to the valley-fill aquifer occurs from 

recharge of gaged runoff. During 1945–98, recharge from 

gaged runoff averaged about 116,000 acre-ft/yr. 

2. Recharge from ungaged runoff is about 10 percent of 

recharge from gaged runoff. During 1945–98, recharge from 

ungaged runoff averaged about 16,000 acre-ft/yr.

3. Recharge of imported water is a relatively minor 

component of total recharge to the valley-fill aquifer. After 

the California State project water became available in 1972, 

recharge of imported water averaged about 6,000 acre-ft/yr 

for 1972–98. For the longer period 1945–98, recharge from 

imported water averaged about 3,000 acre-ft/yr.

4. Return flow from pumpage is a significant source of 

recharge to the upper layer of the valley-fill aquifer, nearly 

twice the quantity of recharge from ungaged runoff. During 

1945–98, return flow averaged about 26,000 acre-ft/yr. 

5. Recharge from underflow and recharge of local runoff 

are relatively minor components of total recharge, each averaging about 5,000 acre-ft/yr during 1945–98.

6. Recharge from direct precipitation is a minor component of total recharge, averaging less than about 1,000 acreft/yr during 1945–98.

7. Much of the recharge to the valley-fill aquifer occurs 

during years with unusually large runoff, which occur about 

once every 5 to 10 years.

8. Keeping the highly permeable stream channels and 

the off-channel artificial-recharge basins, despite continuing 

urbanization, is necessary to maintain historical quantities of 

recharge from native runoff.

9. Additional recharge to the valley-fill aquifer prompts 

additional discharge from the aquifer, making the gain in aquifer storage less than the amount of the recharge.

Ground-Water Discharge

10. Ground-water pumpage is by far the largest component of total ground-water discharge, averaging about 88 percent of total discharge. During 1945–98, gross ground-water 

pumpage averaged about 175,000 acre-ft/yr.

11. Ground-water discharge components other than 

pumpage are fairly minor. During 1945–98, underflow averaged about 13,000 acre-ft/yr, evapotranspiration averaged 

about 7,000 acre-ft/yr, and rising ground water averaged about 

5,000 acre-ft/yr. 

12. Additional ground-water pumpage from areas near 

the San Jacinto fault is necessary during the next 10 to 20 

years to prevent high ground-water conditions similar to those 

that occurred in 1945 and 1980. Much of this extraction can be 

from the upper water-bearing unit (UWB).

13. Additional ground-water pumpage also is needed 

from the upper confining member (UCM), generally less than 

100 ft thick, in order to control flooding of the land surface 

and possible liquefaction.

Summary and Conclusions 135
14. If additional ground-water pumpage exceeds about 

10,000 acre-ft/yr for several years, then some additional 

recharge needs to be considered.

Ground-Water Storage

15. Annual fluctuations in ground-water storage commonly range from 50,000 acre-ft to 100,000 acre-ft/yr as a 

result of normal fluctuations in natural runoff and historical 

pumpage.

16. Cumulative change in ground-water storage commonly exceeds 500,000 acre-ft during a 10-year period. This 

magnitude of change probably can be accommodated without 

causing either additional land subsidence or an increased risk 

from liquefaction.

17. Maximum cumulative change in storage during 

1945–98 was about 900,000 acre-ft, indicating the maximum 

storage in the valley-fill aquifer is at least this value.

18. Projected increases in demand for municipal water 

will tend to cause larger fluctuations in ground-water storage 

either because ground-water pumpage is increased or because 

less surface water is available for recharge.

19. Future fluctuations in ground-water storage, however, 

will be dampened somewhat by construction of Seven Oaks 

Dam on the Santa Ana River. Flood flows will be captured and 

an average of about 3,000 acre-ft/yr of runoff will be available 

for artificial recharge. 

High Ground-Water Levels

20. High ground-water levels in the former marshland 

can be caused by high runoff conditions, by the return of high 

ground-water levels in underlying hydrogeologic units, or by 

artificial recharge of an unusually large quantity of native or 

imported water, particularly in the East-Twin Creek area.

21. Ground-water levels in the upper water-bearing unit 

(UWB) can be expected to rise during wetter periods to levels 

similar to those observed in about 1945 and 1980, if basin 

management follows present (1998) practices. 

22. Under conditions of recent recharge and pumpage 

(1983-98), high ground-water levels can be expected to recur 

about once every 16 years and to persist for at least 3 to 4 

years.

23. If high ground-water levels in the former marshland 

return, yield of the valley-fill aquifer will decrease. Historically, this decrease has been by as much as 50,000 acre-ft/yr.

24. Control of shallow ground-water levels in the former 

marshland requires areally distributed pumpage. Control cannot be achieved during periods of abundant recharge by a few, 

large-capacity wells.

Liquefaction

25. High ground-water levels in both the upper confining 

member (UCM) and the upper water bearing unit (UWB) need 

to be controlled in order to reduce the threat of liquefaction 

during a strong earthquake.

26. Keeping shallow ground water in the former marshland at least 30 ft below land surface is needed to reduce the 

threat of liquefaction during a strong earthquake. Because of 

the abundant and highly variable recharge to the valley-fill 

aquifer, this goal is physically difficult to achieve.

Land Subsidence

27. Land subsidence, which occurred during 1945–65, 

can be expected to reoccur if ground-water levels decline significantly below historic levels in the upper water-bearing unit 

(UWB) or in deeper hydrogeologic units.

28. Additional ground-water pumpage either from new 

locations in the Bunker Hill or Lytle Creek basins or from 

lower hydrogeologic units needs to be monitored to prevent 

reoccurrence of land subsidence. 

29. Monitoring of possible land subsidence can be 

achieved by installing extensometers in key areas or by analysis of satellite data (InSAR).

Water Quality

30. Using only five barrier wells to stop migration of contaminates at the U.S. EPA Newmark Superfund site is unlikely 

to be successful. Additional wells along the barrier, or pumpage from inside the contaminated area may be needed.

31. Controlling migration of contaminates at the U.S. 

EPA Newmark Superfund site occassionally conflicts with 

maintaining ground-water levels in the vicinity of the former 

marshland. Analyzing both objectives in a joint simulationoptimization model helps to identify the conflicts and better 

understand possible hydraulic solutions.

Basin Yield

32. If high ground-water levels return, the recharge rate 

of native runoff can be expected to decline from 60 percent of 

total inflow to about 40 percent of total inflow.

136 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Figure 68. Bunker Hill dike in the San Bernardino area, California, circa 1904 and 2004.

Summary and Conclusions 137

B

circa 1904 (Mendenhall, 1905, WSP 142, plate XI)

A

circa 2004 (W.R. Danskin, USGS)
33. If high ground-water levels return, discharge of 

ground water into Warm Creek will reoccur, effectively 

decreasing basin yield.

Meeting Future Demand for Water

34. Meeting future demand for water will require a considerable increase in both ground-water pumpage and artificial 

recharge of imported water.

35. Use of excess pumpage capacity or creation of a new 

set of areally distributed wells throughout the former marshland would help meet future demand for water, as well as help 

control high ground-water levels.

Models

36. The ground-water flow model, calibrated with annual 

data for 1945–98, can be used to evaluate a range of watermanagement alternatives, involving annual changes in any 

recharge or discharge component. 

37. The ground-water flow model is well suited to provide boundary conditions for smaller-scale models developed 

to address more localized questions.

38. The constrained optimization model can be used 

in concert with the ground-water flow model to determine 

feasible, perhaps optimal ways of managing water resources in 

the San Bernardino area.

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Additional Tables

Additional Tables 147
Station no. Station name 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954

 Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined 

discharge

65,390 50,290 33,460 32,000 34,040 26,480 24,170 56,950 27,150 43,000

11054001 Mill Creek near Yucaipa, combined discharge 134,909 26,468 17,060 11,000 12,230 11,330 9,030 26,090 13,150 18,52011055501 Plunge Creek near East Highlands, combined 

discharge

18,067 16,013 13,725 13,526 13,803 12,775 12,461 8,580 1,820 5,900

11055801 City Creek near Highland, combined discharge 9,300 6,940 3,310 2,500 4,060 2,710 2,650 11,300 2,300 7,26011057000 San Timoteo Creek near Redlands 980 491 74 85 40 67 67 1,950 30 86911058500 East Twin Creek near Arrowhead Springs 4,400 2,740 1,690 1,250 2,060 1,630 1,310 5,410 1,400 3,90011058600 Waterman Canyon Creek near Arrowhead 

Springs

2,690 1,740 1,140 705 1,260 998 596 2,830 691 1,670

11062001 Lytle Creek near Fontana, combined discharge 31,300 33,540 25,880 13,930 11,760 10,050 8,540 38,180 13,660 18,50011063510 Cajon Creek below Lone Pine Creek, near 

Keenbrook

27,486 29,295 25,199 23,645 23,880 32,535 31,819 310,600 32,809 34,743

11063680 Devil Canyon Creek near San Bernardino 867 772 161 53 206 104 60 1,190 9 773

Total inflow 165,389 138,289 91,699 68,694 73,339 58,679 50,703 163,080 63,019 105,135

 Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge 62,630 57,250 47,280 42,800 37,150 31,440 27,020 35,220 24,540 24,92011060400 Warm Creek near San Bernardino

—

—

—

—

—

—

—

—

—

—

11059300 Santa Ana River at E Street 14,740 414,503 521,149 2,010 2,150 1,680 3,870 14,580 1,380 454,96311066050 Santa Ana River at Colton

—

—

—

—

—

—

—

—

—

—

11065000 Lytle Creek at Colton

—

—

—

—

—

—

—

—

—

—

Total outflow 77,370 71,753 68,429 44,810 39,300 33,120 30,890 49,800 25,920 79,883Inflow minus outflow 88,019 66,536 23,270 23,884 34,039 25,559 19,813 113,280 37,099 25,252

Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98.[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

See footnotes at end of table.

148 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Station no. Station name 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964

Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined discharge 27,620 26,820 25,640 68,810 26,560 24,690 15,790 33,470 17,410 17,63011054001 Mill Creek near Yucaipa, combined discharge 12,890 9,180 11,560 44,020 13,330 10,990 7,240 15,030 9,820 10,03011055501 Plunge Creek near East Highlands, combined 

discharge

2,010 2,880 3,770 11,870 1,910 1,650 882 4,380 1,240 1,410

11055801 City Creek near Highland, combined discharge 2,570 2,860 6,290 19,930 3,340 2,500 1,600 5,030 1,980 1,72011057000 San Timoteo Creek near Redlands 106 194 68 1,270 54 35 216 321 47 4611058500 East Twin Creek near Arrowhead Springs 1,750 1,580 2,140 5,910 1,160 1,030 612 1,710 795 64111058600 Waterman Canyon Creek near Arrowhead Springs 809 873 1,280 3,260 576 406 192 959 393 32511062001 Lytle Creek near Fontana, combined discharge 13,780 12,710 13,500 56,320 17,030 10,650 8,020 19,380 12,040 8,95011063510 Cajon Creek below Lone Pine Creek, near Keenbrook 32,587 32,168 34,160 310,100 33,714 32,241 32,032 38,783 32,021 31,553

11063680 Devil Canyon Creek near San Bernardino 590 235 390 3,690 280 90 5 475 12 21

Total inflow 64,712 59,500 68,798 225,180 67,954 54,282 36,589 89,538 45,758 42,326

Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge 19,830 19,830 19,350 25,230 16,060 14,090 14,560 — — —

11060400 Warm Creek near San Bernardino — — — — — — — — — —11059300 Santa Ana River at E Street 611,859 613,598 613,562 627,160 612,858 614,021 715,804 — — —

11066050 Santa Ana River at Colton — — — — — — — 16,560 15,780 15,10011065000 Lytle Creek at Colton — — — () () () () () () ()

Total outflow 31,689 33,428 32,912 52,390 28,918 28,111 30,364 16,560 15,780 15,100Inflow minus outflow 33,023 26,072 35,886 172,790 39,036 26,171 6,225 72,978 29,978 27,226

Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

See footnotes at end of table.

Additional Tables 149
Station no. Station name 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974

Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined discharge 41,170 65,170 61,220 29,730 216,400 37,870 31,390 23,410 56,500 37,43011054001 Mill Creek near Yucaipa, combined discharge 21,830 36,110 32,480 19,950 147,100 20,580 13,570 11,940 23,720 17,28011055501 Plunge Creek near East Highlands, combined 

discharge

7,040 8,900 9,180 2,080 32,690 3,350 3,040 1,750 7,920 3,740

11055801 City Creek near Highland, combined discharge 7,580 10,780 13,070 3,070 57,150 4,810 4,340 1,930 7,020 3,40011057000 San Timoteo Creek near Redlands 1,890 3,100 726 1285 17,938 1619 1353 126 11,383 34211058500 East Twin Creek near Arrowhead Springs 3,160 4,440 4,450 1,320 15,060 2,040 1,940 924 3,050 1,63011058600 Waterman Canyon Creek near Arrowhead Springs 1,570 2,040 2,770 809 9,290 1,360 813 716 1,740 1,10011062001 Lytle Creek near Fontana, combined discharge 33,900 42,240 45,570 17,590 145,200 21,540 16,980 13,660 29,360 22,89011063510 Cajon Creek below Lone Pine Creek, near Keenbrook 316,680 36,547 38,683 33,454 332,340 38,350 85,140 4,210 8,090 6,40011063680 Devil Canyon Creek near San Bernardino 1,330 1,390 2,810 857 10,880 2,140 1,380 465 2,040 1,930

Total inflow 136,150 180,717 180,959 79,145 674,048 102,659 78,946 59,031 140,823 96,142

Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge

—

—

—

—

—

—

—

—

—

—

11060400 Warm Creek near San Bernardino () 858 479 146 3,950 844 944 10593 1014,268 103,61711059300 Santa Ana River at E Street

— 949,742 14,060 11,910 246,700 17,340 15,230 12,020 30,900 25,490

11066050 Santa Ana River at Colton 55,340

—

—

—

—

—

—

—

—

—

11065000 Lytle Creek at Colton () 6,870 2,240 477 47,690 1,820 1,220 176 5,900 1,050

Total outflow 55,340 57,470 16,779 12,533 298,340 20,004 17,394 12,789 51,068 30,157Inflow minus outflow 80,810 123,247 164,180 66,612 375,708 82,655 61,552 46,242 89,755 65,985

Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

See footnotes at end of table.

150 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.

[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

Station no. Station name 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984

Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined discharge 31,460 30,800 22,940 110,200 102,600 219,600 33,530 61,590 163,100 38,71011054001 Mill Creek near Yucaipa, combined discharge 13,930 15,490 13,580 124,900 39,440 87,290 19,750 28,420 69,490 20,57011055501 Plunge Creek near East Highlands, combined discharge 2,870 2,860 2,710 20,600 8,560 24,750 2,510 6,920 18,800 2,88011055801 City Creek near Highland, combined discharge 2,860 2,600 2,420 28,130 10,190 39,780 3,180 7,500 21,700 4,13011057000 San Timoteo Creek near Redlands 291 450 425 4,100 13,273 18,070 1441 11,591 15,753 165311058500 East Twin Creek near Arrowhead Springs 1,470 1,300 808 9,430 3,730 15,950 3,430 4,600 13,280 2,84011058600 Waterman Canyon Creek near Arrowhead Springs 918 725 511 5,480 2,570 10,240 1,530 2,227 7,540 1,56011062001 Lytle Creek near Fontana, combined discharge 15,650 15,640 14,910 129,900 51,700 119,600 17,230 139,268 1106,569 23,30011063510 Cajon Creek below Lone Pine Creek, near Keenbrook 3,490 4,890 83,221 371,930 311,200 333,870 37,170 37,590 834,322 7,34011063680 Devil Canyon Creek near San Bernardino 112,820 114,069 111,690 1111,430 113,400 1114,542 278 113,203 119,220 112,895

Total inflow 75,759 78,824 63,215 516,100 236,663 573,692 89,049 162,909 449,774 104,878

 Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge — — — — — — — — — —

11060400 Warm Creek near San Bernardino 1,330 1,760 1,630 51,820 3,100 19,460 7,940 13,920 24,640 19,55011059300 Santa Ana River at E Street 19,410 24,000 24,550 153,000 55,630 320,300 27,150 61,260 248,770 44,04011066050 Santa Ana River at Colton — — — — — — — — — —

11065000 Lytle Creek at Colton 130 1,060 635 37,360 2,750 29,990 1,200 3,010 1213,100 133,117

Total outflow 20,870 26,820 26,815 242,180 61,480 369,750 36,290 78,190 286,510 66,707Inflow minus outflow 54,889 52,004 36,400 273,920 175,183 203,942 52,759 84,719 163,264 38,171

See footnotes at end of table.

Additional Tables 151
Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.

[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

Station no. Station name 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined discharge 30,570 43,100 24,020 21,220 17,680 12,770 26,450 39,390 170,100 35,74011054001 Mill Creek near Yucaipa, combined discharge 16,990 122,449 111,783 110,218 18,239 15,494 113,142 120,375 193,442 118,33511055501 Plunge Creek near East Highlands, combined discharge 2,580 4,990 2,080 1,960 2,030 1,770 3,450 4,260 24,460 2,67011055801 City Creek near Highland, combined discharge 3,340 5,740 2,410 2,414 2,320 1,460 4,410 6,050 32,470 3,28011057000 San Timoteo Creek near Redlands 1319 1833 151 1

0 1

0 1

0 1150 1681 16,040 1531

11058500 East Twin Creek near Arrowhead Springs 1,940 3,610 1,250 1,300 1,170 1,640 7,680 2,530 16,750 2,06011058600 Waterman Canyon Creek near Arrowhead Springs 11,050 12,071 1629 1659 1580 1867 14,557 11,411 110,099 11,12411062001 Lytle Creek near Fontana, combined discharge 16,190 26,850 13,780 15,690 11,480 8,210 16,810 45,210 123,000 16,62011063510 Cajon Creek below Lone Pine Creek, near Keenbrook 5,970 7,250 4,520 4,710 2,820 2,470 4,200 10,150 26,260 7,24011063680 Devil Canyon Creek near San Bernardino 112,360 112,962 111,994 111,713 111,690 111,200 112,180 112,538 1110,374 1,770

Total inflow 81,309 119,855 62,517 59,884 48,009 35,881 83,029 132,595 512,995 89,370

 Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge

—

—

—

—

—

—

—

—

—

—

11060400 Warm Creek near San Bernardino 19,150 18,590 14,500 11,530 9,340 6,780 5,350 5,860 5,690 2,61011059300 Santa Ana River at E Street 41,280 56,410 34,700 32,830 30,030 30,290 49,310 55,540 206,900 35,83011066050 Santa Ana River at Colton

—

—

—

—

—

—

—

—

—

—

11065000 Lytle Creek at Colton 1,390 4,660 1,730 1,910 1,020 1,550 4,160 8,900 18,640 841

Total outflow 61,820 79,660 50,930 46,270 40,390 38,620 58,820 70,300 231,230 39,281Inflow minus outflow 19,489 40,195 11,587 13,614 7,619 –2,739 24,209 62,295 281,765 50,089

See footnotes at end of table.

152 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.

[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

Station no. Station name 1995 1996 1997 1998 Average

Surface-water inflow to the San Bernardino area

11051501 Santa Ana River near Mentone, combined discharge 124,400 46,500 35,860 116,500 52,52811054001 Mill Creek near Yucaipa, combined discharge 167,896 124,350 118,402 163,480 27,70211055501 Plunge Creek near East Highlands, combined discharge 15,210 3,650 5,610 16,430 6,35111055801 City Creek near Highland, combined discharge 20,100 5,750 7,490 19,360 8,37711057000 San Timoteo Creek near Redlands 14,166 1972 1536 13,842 1,23811058500 East Twin Creek near Arrowhead Springs 9,480 3,540 4,270 9,990 3,80011058600 Waterman Canyon Creek near Arrowhead Springs 15,657 12,028 12,474 15,969 2,18711062001 Lytle Creek near Fontana, combined discharge 64,930 24,440 18,750 59,640 32,63011063510 Cajon Creek below Lone Pine Creek, near Keenbrook 16,440 7,250 4,820 12,860 9,13411063680 Devil Canyon Creek near San Bernardino 6,720 2,510 3,030 5,530 2,506

Total inflow 334,999 120,990 101,242 313,601 146,452

 Surface-water outflow from the San Bernardino area

11065801 Warm Creek near Colton, combined discharge — — — — —11060400 Warm Creek near San Bernardino 6,820 3,920 3,430 10,910 —11059300 Santa Ana River at E Street 153,400 28,580 18,580 110,000 —11066050 Santa Ana River at Colton — — — — —11065000 Lytle Creek at Colton 7,940 3,820 1,290 8,230 —

Total outflow 168,160 36,320 23,300 129,140 67,931Inflow minus outflow 166,839 84,670 77,942 184,461 78,522

See footnotes at end of table.

Additional Tables 153
Table 1. Annual discharge for gaged streams in the San Bernardino area, California, 1945–98—Continued.

[See fig. 2 for definition of the San Bernardino area; values in acre-feet per calendar year are accurate to no more than three significant figures; greater precision is shown for computation purposes only; measured data from the U.S. Geological Survey (J.A. Huff, U.S. Geological Survey, unpub. data, 2000); —, no data; (), data available but are included in another measurement; average values for 1945–98]

1Estimated from regression relations shown in figure 13A-E.2Estimated from the sum of the measured value for Cajon Creek (station no. 11063000) and the estimated value for Lone Pine Creek (station no. 11063500) determined from regression relation 

 shown in figure 13

F.

3Estimated from the sum of the measured values for Cajon Creek (station no. 11063000) and Lone Pine Creek (station no. 11063500).4Estimated from regression relation shown in figure 13I.5Estimated from regression relation shown in figure 13J.6Estimated from the sum of measured values for Santa Ana River near San Bernardino (station no. 11056200), San Timoteo Creek near Loma Linda (station no. 11057500), and wastewater discha

 ge to the Santa Ana River and Warm Creek.

7Estimated from the sum of measured values for Santa Ana River near San Bernardino (station no. 11056200), San Timoteo Creek near Loma Linda (station no. 11057500), Warm Creek Floodway 

 at San Bernardino (station no. 11059000), and wastewater discharge into the Santa Ana River and Warm Creek.

8Estimated from the sum of the measured value for Lone Pine Creek (station no. 11063500) and the estimated value for Cajon Creek (station no. 11063000) determined from regression relation

 shown in figure 13

G.

9Estimated from the sum of measured values for Santa Ana River near San Bernardino (station no. 11056200), Warm Creek Floodway at San Bernardino (station no. 11059000), and wastewater 

 discharge into the Santa Ana River and Warm Creek, and from the estimated value for San Timoteo Creek near Loma Linda (station no. 11057500) determined from regression relation shown in figure 7

K.

10Estimated from total outflow determined from regression relation shown in figure 13

H minus the sum of Santa Ana River at E Street (station no. 11059300) and Lytle Creek at Colton 

 (station no. 11065000).

11Combined discharge (upstream diversion by City of San Bernardino begun in 1975 and ceased in 1993).12Estimated from 11 months of daily values.13Estimated from regression relation shown in figure 13

L.

154 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Ungaged 

area

no.

(fig.17)

Ungaged area Acreage (acres)

Average 

annual 

precipitation

 (inches per year)

Potential ungaged 

runoff 

(acre-feet per year)

Estimated runoff 

rate 

(percent)

Estimated average 

ungaged 

runoff

 (acre-feet per year)

1 West of Lytle Creek 1,134 25.00 2,363 25 5912 Lytle Creek to Cajon Creek 5,085 124.44 10,355 25 2,5893 Cajon Creek to Devil Canyon Creek 7,625 24.54 15,594 25 3,8984 Devil Canyon Creek to Waterman Creek 2,497 20.99 4,367 25 1,0925 East Twin Creek to City Creek 5,582 20.87 9,709 25 2,4276 City Creek to Plunge Creek 2,575 19.51 4,186 25 1,0477 Plunge Creek to Santa Ana River 2,195 19.02 3,479 25 8708 Santa Ana River to Mill Creek 2,550 18.70 3,973 25 9939 Mill Creek to Crafton Hills 2,195 19.72 3,608 25 90210 Crafton Hills and adjacent older alluvium 5,295 15.14 6,681 20 1,33611 Badlands 1,593 15.00 1,992 20 39812 Bedrock outcrops within the valley fill 1,281 118.90 2,018 25 504

 Total 39,609 120.70 68,324 24.4 16,647

1Calculated for multiple areas.

Table 3. Average annual runoff from ungaged areas bordering the Bunker Hill and Lytle Creek basins in the San Bernardino area, California, 1928–98. [Values for calendar years; ungaged areas adapted from Webb and Hanson (1972, plate 26); estimated average ungaged runoff for calendar years 1945–98 is 0.946 times the values listed below]

Additional Tables 155
Calendar 

year

Precipitation 

at San

 Bernardino, 

in inches 

per year

Precipitation component

Percent of precipitation Acre-feet of water

Direct 

recharge

Local 

runoff

Evapotranspiration Recharge from local runoff Direct recharge Local runoff Evapo- transpiration Recharge from local runoff Total

1945 18.61 0 15 80 5 0 19,155 102,161 6,385 127,702 1946 17.90 0 15 80 5 0 18,424 98,264 6,141 122,830 1947 5.95 0 15 80 5 0 6,124 32,663 2,041 40,829 1948 13.24 0 15 80 5 0 13,628 72,682 4,543 90,853 1949 14.84 0 15 80 5 0 15,275 81,466 5,092 101,832 1950 9.00 0 15 80 5 0 9,264 49,406 3,088 61,758 1951 17.03 0 15 80 5 0 17,529 93,488 5,843 116,860 1952 21.69 0 15 80 5 0 22,326 119,069 7,442 148,837 1953 7.37 0 15 80 5 0 7,586 40,458 2,529 50,573 1954 19.35 0 15 80 5 0 19,917 106,224 6,639 132,780 1955 12.23 0 15 80 5 0 12,588 67,138 4,196 83,922 1956 11.21 0 15 80 5 0 11,538 61,538 3,846 76,923 1957 20.45 0 15 80 5 0 21,049 112,262 7,016 140,328 1958 20.83 0 15 80 5 0 21,440 114,348 7,147 142,935 1959 9.70 0 15 80 5 0 9,984 53,249 3,328 66,561 1960 12.69 0 15 80 5 0 13,062 69,663 4,354 87,079 1961 6.54 0 15 80 5 0 6,732 35,902 2,244 44,877 1962 10.53 0 15 80 5 0 10,839 57,805 3,613 72,257 1963 17.35 0 15 80 5 0 17,858 95,245 5,953 119,056 1964 9.88 0 15 80 5 0 10,169 54,237 3,390 67,797 1965 21.71 0 15 80 5 0 22,346 119,179 7,449 148,974 1966 14.76 0 15 80 5 0 15,192 81,026 5,064 101,283 1967 17.13 0 15 80 5 0 17,632 94,037 5,877 117,546 1968 7.50 0 15 80 5 0 7,720 41,172 2,573 51,465 1969 31.96 5 15 75 5 10,965 32,896 164,482 10,965 219,310 1970 14.54 0 15 80 5 0 14,966 79,819 4,989 99,773 1971 13.46 0 15 80 5 0 13,854 73,890 4,618 92,363 1972 6.85 0 15 80 5 0 7,051 37,604 2,350 47,005 1973 14.50 0 15 80 5 0 14,925 79,599 4,975 99,499 1974 15.06 0 15 80 5 0 15,501 82,673 5,167 103,342 

Table 4. Precipitation components for the San Bernardino area, California, 1945–98.[Precipitation at San Bernardino County Flood Control District station 47723 (fig. 6); precipitation components calculated for the Bunker Hill and Lytle Creek basins; average for calendar years 1945–98]

156 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar 

year

Precipitation 

at San

 Bernardino, 

in inches 

per year

Precipitation component

Percent of precipitation Acre-feet of water

Direct 

recharge

Local 

runoff

Evapotranspiration Recharge from local runoff Direct recharge Local runoff Evapo- transpiration Recharge from local runoff Total

1975 11.93 0 15 80 5 0 12,280 65,491 4,093 81,864 1976 15.07 0 15 80 5 0 15,512 82,728 5,171 103,410 1977 14.91 0 15 80 5 0 15,347 81,850 5,116 102,312 1978 30.83 5 15 75 5 10,578 31,733 158,667 10,578 211,555 1979 16.46 0 15 80 5 0 16,942 90,359 5,647 112,949 1980 26.57 5 15 75 5 9,116 27,349 136,743 9,116 182,323 1981 11.51 0 15 80 5 0 11,847 63,185 3,949 78,982 1982 22.92 0 15 80 5 0 23,592 125,822 7,864 157,277 1983 34.37 5 15 75 5 11,792 35,377 176,885 11,792 235,847 1984 8.93 0 15 80 5 0 9,192 49,022 3,064 61,278 1985 10.90 0 15 80 5 0 11,219 59,837 3,740 74,796 1986 15.52 0 15 80 5 0 15,975 85,199 5,325 106,498 1987 13.03 0 15 80 5 0 13,412 71,529 4,471 89,412 1988 12.18 0 15 80 5 0 12,537 66,863 4,179 83,579 1989 7.23 0 15 80 5 0 7,442 39,690 2,481 49,612 1990 8.19 0 15 80 5 0 8,430 44,960 2,810 56,200 1991 17.84 0 15 80 5 0 18,363 97,934 6,121 122,418 1992 20.10 0 15 80 5 0 20,689 110,341 6,896 137,926 1993 26.29 5 15 75 5 9,020 27,060 135,301 9,020 180,402 1994 13.87 0 15 80 5 0 14,276 76,141 4,759 95,176 1995 21.64 0 15 80 5 0 22,274 118,795 7,425 148,494 1996 18.70 0 15 80 5 0 19,248 102,656 6,416 128,319 1997 17.36 0 15 80 5 0 17,869 95,299 5,956 119,124 1998 29.00 5 15 75 5 9,950 29,850 149,249 9,950 198,998 

 Average 15.91 1 15 79 5 1,137 16,377 86,209 5,459 109,183 

Table 4. Precipitation components for the San Bernardino area, California, 1945–98—Continued.[Precipitation at San Bernardino County Flood Control District station 47723 (fig. 6); precipitation components calculated for the Bunker Hill and Lytle Creek basins; average for calendar years 1945–98]

Additional Tables 157
Site no. 

(fig. 11) Delivery point 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982

Deliveries inside the Bunker Hill and Lytle Creek basins

 Artificial recharge

1 Lytle Creek gravel pit 0 0 0 0 0 0 0 0 0 0 2,9122 Sweetwater to Devil Canyon 98 5,316 3,242 4,606 3,075 7,352 7,243 4,000 3,969 6,177 2,8993 Badger 22 3,991 3,204 2,684 2,166 3,134 624 294 294 895 1864 Waterman 1,155 22,918 9,747 6,821 7,045 3,637 181 48 48 7 05 Patton 0 0 0 0 1 0 12 0 0 0 06 City Creek 0 0 0 0 8 2 67 0 0 0 07 Santa Ana 0 0 0 0 260 10,438 5,103 126 126 8,494 3,171

 Subtotal 1,275 32,225 16,193 14,111 12,555 24,563 13,230 4,468 4,437 15,573 9,168

 Agricultural use

North Fork 0 0 0 0 0 0 20 35 35 682 66Bear Valley canal 0 0 0 0 0 0 0 0 0 0 0Greenspot pump station 0 0 0 0 0 0 0 0 0 0 0Edwards pump line na na na na na na na na na na naSeven Oaks Dam construction na na na na na na na na na na na Subtotal 0 0 0 0 0 0 20 35 35 682 66

 Municipal use

East Valley Water District 0 0 0 0 0 0 0 0 0 0 0 Subtotal 0 0 0 0 0 0 0 0 0 0 0

Deliveries outside the Bunker Hill and Lytle Creek basins

Linden ponds 0 0 0 0 0 0 0 0 0 0 3,514Havasu Water Company na na na na na na na na na na na Subtotal 0 0 0 0 0 0 0 0 0 0 3,514

Total imported 1,275 32,225 16,193 14,111 12,555 24,563 13,250 4,503 4,472 16,255 12,748Maximum entitlement 1,677 48,000 50,000 52,500 55,000 57,500 60,000 62,500 62,500 68,500 71,500

Table 5. Distribution, quantity, and use of water imported into the San Bernardino area, California, 1972–98.[Values, in acre-feet per calendar year, obtained from the San Bernardino Valley Municipal Water District (written commun., 2000), the local agency entitled to import water via the California State Water Project. Maximum annual entitlement is defined by state contract (Santa Ana Watershed Protection Agency, 1980, table 1, p. 33). No water was imported prior to 1972. na, not applicable]

158 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Site no. 

(fig. 11) Delivery point 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992

Deliveries inside the Bunker Hill and Lytle Creek basins

 Artificial recharge

1 Lytle Creek gravel pit 1,424 215 0 0 85 0 0 0 0 02 Sweetwater to Devil Canyon 54 169 1,161 0 0 0 3,840 6,834 982 1283 Badger 0 0 0 0 0 0 0 10 0 04 Waterman 0 0 0 0 0 0 0 0 0 05 Patton 0 0 0 0 0 0 0 0 0 06 City Creek 0 0 0 0 0 0 0 0 0 07 Santa Ana 0 0 0 0 0 0 545 0 82 0

 Subtotal 1,478 384 1,161 0 85 0 4,385 6,844 1,064 128

 Agricultural use

North Fork 0 573 1,417 282 2,406 2,509 2,136 2,488 922 0Bear Valley canal 0 618 1,947 626 3,022 4,367 7,861 7,848 3,428 2,538Greenspot pump station 0 0 0 0 551 27 68 0 25 5Edwards pump line na na na na 131 460 579 443 390 0Seven Oaks Dam construction na na na na na na na na na na Subtotal 0 1,191 3,364 908 6,110 7,363 10,644 10,779 4,765 2,543

 Municipal use

East Valley Water District 98 222 395 558 364 0 871 687 353 0 Subtotal 98 222 395 558 364 0 871 687 353 0

Deliveries outside the Bunker Hill and Lytle Creek basins

Linden ponds 4,736 3,471 3,879 5,345 3,030 4,601 4,522 65 435 1,559Havasu Water Company na na na na 78 58 63 52 55 52 Subtotal 4,736 3,471 3,879 5,345 3,108 4,659 4,585 117 490 1,611

Total imported 6,312 5,268 8,799 6,811 9,667 12,022 20,485 18,427 6,672 4,282Maximum entitlement 74,500 78,000 81,500 85,000 89,000 93,000 97,000 102,600 102,600 102,600

Table 5. Distribution, quantity, and use of water imported into the San Bernardino area, California, 1972–98—Continued.[Values, in acre-feet per calendar year, obtained from the San Bernardino Valley Municipal Water District (written commun., 2000), the local agency entitled to import water via the California State Water Project. Maximum annual entitlement is defined by state contract (Santa Ana Watershed Protection Agency, 1980, table 1, p. 33). No water was imported prior to 1972. na, not applicable]

Additional Tables 159
Site no. 

(fig. 11) Delivery point 1993 1994 1995 1996 1997 1998 Average 1972–98 Average 1945–98

Deliveries inside the Bunker Hill and Lytle Creek basins

 Artificial recharge

1 Lytle Creek gravel pit 0 0 0 2 0 0 172 862 Sweetwater to Devil Canyon 2,370 2,674 0 96 0 4 2,455 1,2283 Badger 0 0 0 0 0 0 648 3244 Waterman 0 0 0 0 0 0 1,911 9565 Patton 0 0 0 0 0 0 0 06 City Creek 0 0 0 0 0 0 77 397 Santa Ana 0 1,223 0 0 0 163 1,027 513

 Subtotal 2,370 3,897 0 98 0 167 6,291 3,146

 Agricultural use

North Fork 16 53 0 130 1,113 0 551 276Bear Valley canal 515 5,080 601 4,541 7,013 589 1,874 937Greenspot pump station 17 0 24 0 0 12 27 14Edwards pump line 0 18 0 174 423 0 97 48Seven Oaks Dam construction na na 49 547 627 638 69 34 Subtotal 548 5,151 674 5,392 9,176 1,239 2,618 1,309

 Municipal use

East Valley Water District 0 10 0 690 2,934 380 280 140 Subtotal 0 10 0 690 2,934 380 280 140

Deliveries outside the Bunker Hill and Lytle Creek basins

Linden ponds 1,502 261 0 78 0 0 1,370 685Havasu Water Company 0 0 0 0 0 0 13 7 Subtotal 1,502 261 0 78 0 0 1,384 692

Total imported 4,420 9,319 674 6,258 12,110 1,786 10,573 5,286Maximum entitlement 102,600 102,600 102,600 102,600 102,600 102,600 78,188 39,094

Table 5. Distribution, quantity, and use of water imported into the San Bernardino area, California, 1972–98—Continued.[Values, in acre-feet per calendar year, obtained from the San Bernardino Valley Municipal Water District (written commun., 2000), the local agency entitled to import water via the California State Water Project. Maximum annual entitlement is defined by state contract (Santa Ana Watershed Protection Agency, 1980, table 1, p. 33). No water was imported prior to 1972. na, not applicable]

160 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Site no. 

(fig. 20) Name of facility Type of treatment Disposal of effluent Period of operation

Range of 

discharge

(acre-feet per year)

1 City of San Bernardino, plant 1 Sewage treatment plant Direct discharge into Warm Creek 1928–1972 5,000–10,0002 City of San Bernardino, plant 2 Sewage treatment plant Direct discharge into Santa Ana River,

irrigation

1959–present 5,000–50,000

3 City of Redlands Sewage treatment plant Percolation ponds 1930s–present 1,500–10,7004 Mountainview Power Company, previously 

Southern California Edison Company, San Bernardino plant

Cooling tower disposal Direct discharge into Santa Ana River, 

export

1957–present 100–1500+

5 Santa Fe Railway Industrial treatment plant Evaporation ponds and city sewer system Prior to 1962–1994 300–7006 Loma Linda Sanitation District Sewage treatment plant Direct discharge into Santa Ana River 1945–1967 200–4007 Patton State Hospital Sewage discharge Irrigation (?) and city sewer system Prior to 1959–present 200–4008 Culligan, Inc. Industrial brine disposal Percolation and evaporation ponds 1942–1986 100–3009 Universal Rundle Co. Industrial treatment plant Percolation ponds 1946–unknown 10–15010 Lockheed Propulsion Sewage treatment plant Percolation ponds 1955–1976 50–10011 Norton Air Force base, now San 

Bernardino Airport Authority

Industrial treatment plant Percolation ponds, discharge to Santa Ana 

River, and city sewer system

1954–1995 86

12 Campus Crusade for Christ Sewage treatment plant Irrigation, percolation ponds 1938–present 30–5013 Glen Helen Rehabilitation Center Sewage treatment plant Percolation ponds 1959–present 10–20

Table 6. Major wastewater treatment facilities in the San Bernardino area, California.[Modified and updated from Hill (1979, table 2) and J.C. Hanson (Consulting Civil Engineer, unpub. data, 1984); present is 1998; +, greater than; (?), uncertain]

Additional Tables 161
Calendar year City of San Bernardino Southern California Edison, 

San Bernardino plantsc

Loma Linda 

Sanitation 

District

Total

Plant 1w Plant 2si

1945 6,999 nio nio e,p126 e,p7,1251946 6,828 nio nio e169 e6,9971947 7,063 nio nio e175 e7,2381948 7,062 nio nio e180 e7,2421949 7,925 nio nio e186 e8,1111950 8,116 nio nio e192 e8,3081951 8,506 nio nio e197 e8,7031952 9,325 nio nio e203 e9,5281953 7,865 nio nio e209 e8,0741954 8,715 nio nio e214 e8,9291955 9,914 nio nio e220 e10,1341956 9,512 nio nio e226 e9,7381957 9,792 nio e232 e231 e10,2551958 10,013 nio e310 e237 e10,5601959 8,845 1,736 271 e242 e11,0941960 7,641 4,462 227 e249 e12,5791961 7,718 6,071 315 e238 e14,3421962 6,239 7,054 242 265 13,8001963 5,577 7,438 253 233 13,5011964 6,278 7,624 227 328 14,4571965 6,761 8,212 203 p295 p15,4711966 6,994 8,316 163 nio 15,4731967 6,968 9,053 232 nio 16,2531968 6,700 9,214 342 nio 16,2561969 5,318 9,124 324 nio 14,7661970 4,377 9,865 473 nio 14,7151971 5,705 8,925 600 nio 15,2301972 6,784 9,963 623 nio 17,3701973 nio 17,640 515 nio 18,6601974 nio 17,070 1,004 nio 18,0741975 nio 16,820 1,099 nio 17,919

Table 7. Annual wastewater discharge to the Santa Ana River and Warm Creek in the San Bernardino area, California, 1945–98.[Refer table 6 for names and descriptions and figure 20 for locations of wastewater facilities. Data from Hill (1979); J.C. Hanson (Consulting Civil Engineer, unpub. data, 1984); S.H. Fuller (San Bernardino Valley Municipal Water District, unpub. data, 1999); H.E. Wade (Southern California Edison, unpub. data, 1993); Western−San Bernardino Watermaster (2000); and U.S. Geological Survey (surface-water station 11059100). Values in acre-feet;w all discharge to Warm Creek; si most discharge to the Santa Ana River and some to irrigation; sc discharge to Santa Ana River, Gage Canal, or Riverside Water Company Canal; e estimated; p partial record; nio, not in operation; RIX discharge to Rapid Infiltration/Extraction facility begun April 1996; average for 1945–98, excluding RIX discharge]

162 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar year City of San Bernardino Southern California Edison, 

San Bernardino plantsc

Loma Linda 

Sanitation 

District

Total

Plant 1w Plant 2si

1976 nio 17,530 1,137 nio 18,6671977 nio 17,720 1,338 nio 19,0581978 nio 18,690 1,350 nio 20,0401979 nio 19,350 1,057 nio 20,4071980 nio 20,670 1,463 nio 22,1231981 nio 21,120 1,518 nio 22,6381982 nio 24,493 843 nio 25,3361983 nio 23,170 464 nio 23,6341984 nio 21,759 183 nio 21,9421985 nio 23,814 122 nio 23,9361986 nio 25,442 365 nio 25,8071987 nio 27,154 127 nio 27,2811988 nio 27,290 49 nio 27,3391989 nio 28,300 38 nio 28,3381990 nio 27,770 57 nio 27,8271991 nio 26,980 35 nio 27,0151992 nio 25,510 38 nio 25,5511993 nio 24,660 5 nio 24,6651994 nio 24,790 14 nio 24,8041995 nio 26,260 30 nio 26,2901996 nio 0

[RIX31,084]

22 nio 31,106

1997 nio 0

[RIX44,326]

73 nio 44,399

1998 nio 0

[RIX48,709]

14 nio 48,723

Average 7,484 15,776 394 220 15,873

Table 7. Annual wastewater discharge to the Santa Ana River and Warm Creek in the San Bernardino area, California, 1945–98—Continued.[Refer table 6 for names and descriptions and figure 20 for locations of wastewater facilities. Data from Hill (1979); J.C. Hanson (Consulting Civil Engineer, unpub. data, 1984); S.H. Fuller (San Bernardino Valley Municipal Water District, unpub. data, 1999); H.E. Wade (Southern California Edison, unpub. data, 1993); Western−San Bernardino Watermaster (2000); and U.S. Geological Survey (surface-water station 11059100). Values in acre-feet;w all discharge to Warm Creek; si most discharge to the Santa Ana River and some to irrigation; sc discharge to Santa Ana River, Gage Canal, or Riverside Water Company Canal; e estimated; p partial record; nio, not in operation; RIX discharge to Rapid Infiltration/Extraction facility begun April 1996; average for 1945–98, excluding RIX discharge]

Additional Tables 163
Calendar year

Inflow Outflow

Net San Timoteo 

Canyon

Sand 

Canyon

Reservoir 

Canyon

Redlands 

Heights Badlands Total Near Barrier J Near Santa Ana River Total

1945 4,605 1,165 450 300 280 6,800 10,038 12,054 22,092

-15,292

1946 4,536 1,158 450 300 280 6,724 10,439 11,544 21,983

-15,259

1947 4,468 1,150 450 300 280 6,648 8,935 10,976 19,911

-13,263

1948 4,402 1,143 450 300 280 6,574 5,342 10,768 16,110

-9,536

1949 4,336 1,135 450 300 280 6,501 4,360 10,776 15,136

-8,635

1950 4,271 1,128 450 300 280 6,429 3,449 9,419 12,868

-6,439

1951 4,208 1,120 450 300 280 6,358 2,505 7,215 9,720

-3,362

1952 4,145 1,113 450 300 280 6,287 11,190 7,046 18,236

-11,949

1953 4,083 1,105 450 300 280 6,218 5,229 6,204 11,433

-5,215

1954 4,022 1,098 450 300 280 6,150 6,988 6,212 13,200

-7,050

1955 3,963 1,090 450 300 280 6,083 5,280 5,450 10,730

-4,647

1956 3,904 1,083 450 300 280 6,016 4,811 4,610 9,421

-3,405

1957 3,846 1,075 450 300 280 5,951 5,161 3,864 9,025

-3,074

1958 3,788 1,068 450 300 280 5,886 13,445 3,929 17,374

-11,488

1959 3,732 1,060 450 300 280 5,822 6,508 3,465 9,973

-4,151

1960 3,677 1,053 450 300 280 5,759 3,785 3,091 6,876

-1,117

1961 3,622 1,045 450 300 280 5,697 2,140 2,474 4,614 1,0831962 3,569 1,038 450 300 280 5,636 7,258 2,091 9,349

-3,713

1963 3,516 1,030 450 300 280 5,576 4,497 1,647 6,144

-568

1964 3,464 1,023 450 300 280 5,516 2,777 1,410 4,187 1,3291965 3,412 1,015 450 300 280 5,457 10,501 1,249 11,750

-6,293

1966 3,362 1,008 450 300 280 5,399 11,777 1,047 12,824

-7,425

1967 3,312 1,000 450 300 280 5,342 12,217 988 13,205

-7,863

1968 3,263 993 450 300 280 5,286 6,695 871 7,566

-2,280

Table 9. Annual underflow for the San Bernardino area, California, 1945–98.All values in acre-feet; −, outflow; net equals total inflow minus total outflow]

164 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar year

Inflow Outflow

Net San Timoteo 

Canyon

Sand 

Canyon

Reservoir 

Canyon

Redlands 

Heights Badlands Total Near Barrier J Near Santa Ana River Total

1969 3,215 985 450 300 280 5,230 18,938 886 19,824 -14,5941970 3,167 978 450 300 280 5,175 7,870 1,018 8,888 -3,7131971 3,121 970 450 300 280 5,121 6,491 1,207 7,698 -2,5771972 3,075 963 450 300 280 5,067 5,229 1,330 6,559 -1,4921973 3,029 955 450 300 280 5,014 9,667 1,500 11,167 -6,1531974 2,985 948 450 300 280 4,962 8,223 1,717 9,940 -4,9781975 2,941 940 450 300 280 4,911 6,018 1,764 7,782 -2,8711976 2,897 933 450 300 280 4,860 6,014 1,752 7,766 -2,9061977 2,855 925 450 300 280 4,810 5,737 1,729 7,466 -2,6561978 2,813 918 450 300 280 4,760 18,292 1,862 20,154 -15,3941979 2,771 910 450 300 280 4,711 12,949 2,524 15,473 -10,7621980 2,731 903 450 300 280 4,663 17,813 3,796 21,609 -16,9461981 2,691 895 450 300 280 4,616 6,576 5,160 11,736 -7,1201982 2,651 888 450 300 280 4,569 11,353 6,509 17,862 -13,2931983 2,612 880 450 300 280 4,522 17,144 7,626 24,770 -20,2481984 2,574 873 450 300 280 4,476 8,326 8,060 16,386 -11,9101985 2,536 865 450 300 280 4,431 6,214 7,995 14,209 -9,7781986 2,499 858 450 300 280 4,387 9,149 7,070 16,219 -11,8321987 2,462 850 450 300 280 4,342 5,280 6,159 11,439 -7,0971988 2,426 843 450 300 280 4,299 6,033 5,189 11,222 -6,9231989 2,391 835 450 300 280 4,256 4,220 4,164 8,384 -4,1281990 2,356 828 450 300 280 4,213 2,276 3,804 6,080 -1,867

Table 9. Annual underflow for the San Bernardino area, California, 1945-98—Continued.All values in acre-feet; −, outflow; net equals total inflow minus total outflow]

Additional Tables 165
Calendar year

Inflow Outflow

Net San Timoteo 

Canyon

Sand 

Canyon

Reservoir 

Canyon

Redlands 

Heights Badlands Total Near Barrier J Near Santa Ana River Total

1991 2,322 820 450 300 280 4,172 6,432 2,712 9,144

-4,972

1992 2,288 813 450 300 280 4,130 12,171 2,112 14,283

-10,153

1993 2,254 805 450 300 280 4,089 17,976 2,057 20,033

-15,944

1994 2,221 798 450 300 280 4,049 6,366 1,882 8,248

-4,199

1995 2,189 790 450 300 280 4,009 14,270 1,727 15,997

-11,988

1996 2,157 783 450 300 280 3,970 8,603 1,871 10,474

-6,504

1997 2,126 775 450 300 280 3,931 7,066 1,750 8,816

-4,885

1998 2,095 768 450 300 280 3,892 15,117 2,343 17,460

-13,568

Average 3,184 966 450 300 280 5,181 8,391 4,216 12,608

-7,427

Table 9. Annual underflow for the San Bernardino area, California, 1945-98

—Continued.

All values in acre-feet; −, outflow; net equals total inflow minus total outflow]

166 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar 

year

Plantiff Non-plaintiff

Total 

pumpage

Gross pumpage per 

model layer Return flow Total net pumpage Filed Filed Non-filed

Pumpage Source Pumpage Source Pumpage Source Upper Lower

1945 39,112 E1 70,943 E2 12,824 E3 122,879 70,296 52,583 20,083 102,796 1946 43,771 E1 81,807 E2 12,824 E3 138,402 79,300 59,102 22,557 115,845 1947 44,735 P-NV 86,486 NP-NV 12,824 E3 144,045 84,334 59,711 21,020 123,025 1948 51,540 P-NV 95,182 NP-NV 12,824 E3 159,546 93,776 65,770 24,675 134,871 1949 44,539 P-NV 92,227 NP-NV 12,824 E3 149,590 84,638 64,952 24,407 125,183 1950 52,523 P-NV 100,210 NP-NV 12,824 E3 165,557 96,822 68,735 27,020 138,538 1951 54,793 P-NV 103,356 NP-NV 12,824 E3 170,973 95,928 75,045 29,335 141,638 1952 43,444 P-NV 78,117 NP-NV 12,824 E3 134,385 74,642 59,743 23,636 110,749 1953 64,668 P-NV 106,949 NP-NV 12,824 E3 184,441 104,667 79,774 30,418 154,023 1954 51,827 P-NV 97,890 NP-NV 12,824 E3 162,541 88,907 73,634 28,310 134,231 1955 65,395 P-NV 105,637 NP-NV 12,824 E3 183,856 98,574 85,282 30,588 153,268 1956 70,771 P-NV 119,610 NP-NV 12,824 E3 203,205 108,812 94,393 34,745 168,460 1957 57,628 P-NV 100,878 NP-NV 12,824 E3 171,330 91,159 80,171 30,044 141,286 1958 60,571 P-NV 95,588 NP-NV 12,824 E3 168,983 87,413 81,570 28,398 140,585 1959 70,353 P-V 120,459 NP-V 12,824 NP-NFV 203,636 111,087 92,549 33,220 170,416 1960 64,865 P-V 116,019 NP-V 11,899 NP-NFV 192,783 105,163 87,620 32,518 160,265 1961 70,944 P-V 130,419 NP-V 13,680 NP-NFV 215,043 116,489 98,554 36,992 178,051 1962 65,102 P-V 109,181 NP-V 13,121 NP-NFV 187,404 100,304 87,100 32,301 155,103 1963 60,983 P-V 103,718 NP-V 12,599 NP-NFV 177,300 93,725 83,575 30,653 146,647 1964 65,892 P-NV 113,630 NP-NV 12,001 E4 191,523 99,967 91,557 33,287 158,237 1965 54,941 P-NV 104,133 NP-NV 11,404 E4 170,478 86,890 83,588 30,896 139,582 1966 57,337 P-NV 104,152 NP-NV 10,806 E4 172,295 84,886 87,410 29,838 142,457 1967 53,652 P-NV 91,970 NP-NV 10,209 E4 155,831 75,559 80,272 26,722 129,108 1968 63,210 P-NV 104,459 NP-NV 9,611 E4 177,280 87,453 89,828 29,034 148,246 1969 48,943 P-NV 89,131 NP-NV 9,014 E4 147,088 73,227 73,861 25,156 121,931 

Table 10. Annual ground-water pumpage in the San Bernardino area, California, 1945–98.[Values in acre-feet; na, not applicable; source, refer bottom of table for description of source of annual pumpage values]

Additional Tables 167
Calendar 

year

Plantiff Non-plaintiff

Total 

pumpage

Gross pumpage per 

model layer Return flow Total net pumpage Filed Filed Non-filed

Pumpage Source Pumpage Source Pumpage Source Upper Lower

1970 55,900 P-V 111,146 NP-V 8,416 NP-NFV 175,462 86,958 88,504 30,614 144,848 1971 61,015 P-V 115,077 NP-V 6,169 NP-NFV 182,261 93,158 89,103 31,212 151,049 1972 53,992 P-V 117,650 NP-V 6,735 NP-NFV 178,377 88,231 90,146 31,031 147,346 1973 49,752 P-V 101,447 NP-V 5,690 NP-NFV 156,889 75,886 81,003 26,803 130,086 1974 52,226 P-V 100,264 NP-V 5,531 NP-NFV 158,021 73,678 84,343 26,923 131,098 1975 56,800 P-V 97,365 NP-V 4,511 NP-NFV 158,676 77,326 81,350 24,652 134,024 1976 61,532 P-V 93,049 NP-V 4,047 NP-NFV 158,628 81,221 77,407 23,300 135,328 1977 58,889 P-V 96,783 NP-V 4,864 NP-NFV 160,536 82,405 78,131 25,085 135,452 1978 49,172 P-V 87,754 NP-V 3,928 NP-NFV 140,854 68,827 72,027 21,953 118,901 1979 59,759 P-V 91,385 NP-V 3,825 NP-NFV 154,969 77,305 77,664 22,997 131,972 1980 56,773 P-V 94,244 NP-V 4,797 NP-NFV 155,814 80,864 74,950 24,009 131,805 1981 58,996 P-V 112,431 NP-V 4,431 NP-NFV 175,858 89,976 85,882 27,214 148,644 1982 56,158 P-V 93,659 NP-V 4,128 NP-NFV 153,945 77,894 76,051 22,679 131,266 1983 49,629 P-V 84,122 NP-V 3,785 NP-NFV 137,536 64,394 73,142 20,844 116,692 1984 68,830 P-V 113,030 NP-V 4,574 NP-NFV 186,434 93,308 93,126 26,872 159,562 1985 71,770 P-V 119,117 NP-V 4,325 NP-NFV 195,212 91,107 104,105 27,942 167,270 1986 70,341 P-V 115,718 NP-V 4,487 NP-NFV 190,546 92,164 98,382 27,969 162,577 1987 66,869 P-V 124,000 NP-V 4,176 NP-NFV 195,045 94,955 100,090 28,642 166,403 1988 74,432 P-V 131,297 NP-V 4,685 NP-NFV 210,414 102,932 107,482 31,558 178,856 1989 60,919 P-V 132,986 NP-V 4,929 NP-NFV 198,834 94,964 103,870 32,277 166,557 1990 55,675 P-V 134,355 NP-V 4,573 NP-NFV 194,603 89,501 105,102 32,085 162,518 1991 60,379 P-V 124,138 NP-V 4,352 NP-NFV 188,869 82,593 106,276 30,348 158,521 1992 58,423 P-V 121,767 NP-V 4,223 NP-NFV 184,413 82,366 102,047 30,232 154,181 1993 60,796 P-V 122,509 NP-V 4,022 NP-NFV 187,327 88,308 99,019 29,373 157,954 1994 69,889 P-V 129,185 NP-V 4,167 NP-NFV 203,241 95,490 107,751 29,951 173,290 

Table 10. Annual ground-water pumpage in the San Bernardino area, California, 1945

–98

—Continued.

[Values in acre-feet; na, not applicable; source, refer bottom of table for description of source of annual pumpage values]

168 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar 

year

Plantiff Non-plaintiff

Total 

pumpage

Gross pumpage per 

model layer Return flow Total net pumpage Filed Filed Non-filed

Pumpage Source Pumpage Source Pumpage Source Upper Lower

1995 63,495 P-V 126,213 NP-V 4,155 NP-NFV 193,863 90,731 103,132 28,900 164,963 1996 72,790 P-V 138,295 NP-V 3,614 NP-NFV 214,699 102,389 112,310 32,001 182,698 1997 69,547 P-V 137,510 NP-V 3,475 NP-NFV 210,532 97,324 113,208 31,624 178,908 1998 62,084 P-NV 116,988 NP-NV 3,475 E5 182,547 85,455 97,092 26,390 156,157 

Average 59,044 na 107,512 na 8,163 na 174,719 88,810 85,909 28,173 146,546 

DESCRIPTION OF SOURCE OF PUMPAGE DATAWestern−San Bernardino Watermaster known pumpageP-NV Plaintiff, filed, non-verifiedP-V Plaintiff, filed, verifiedNP-NV Non-plaintiff, filed, non-verifiedNP-V Non-plaintiff, filed, verifiedNP-NFV Non-plaintiff, non-filed, verifiedEstimated pumpageE1 Average plaintiff, non-verified pumpage for 6-year period (1947−52), scaled to percent runoff in the Santa Ana River.E2 Average non-plaintiff, non-verified pumpage for 6-year period (1947−52), scaled to percent runoff in the Santa Ana River.E3 Non-plaintiff, non-filed, verified values for 1959.E4 Average non-plaintiff, non-filed, verified pumpage for 4-year period (1962−63, 1970−71), scaled to declining linear trend from 1963 to 1970.E5 Non-plaintiff, non-filed, verified values for 1997.

Table 10. Annual ground-water pumpage in the San Bernardino area, California, 1945–98—Continued.[Values in acre-feet; na, not applicable; source, refer bottom of table for description of source of annual pumpage values]

Additional Tables 169
Item Past ground-water flow model (Hardt and Hutchinson, 1980) Present ground-water flow model (this study)

Major benefits First three-dimensional simulation of ground-water flow in the 

San Bernardino area.

Simulation of individual recharge and discharge components; revised pumpage 

and boundary conditions; improved simulation of faults; longer simulation period.

Major limitations Most recharge and discharge components lumped into a single array; fixed areal distribution of recharge; time invariant underflow; non-filed pumpage missing. Time invariant transmissivity; idealized aquifer geometry; lack of ground-water quality data to confirm model results.

General characteristics

Areal extent Most of the valley-fill aquifer within the Bunker Hill and Lytle 

Creek basins.

All of the valley-fill aquifer within the Bunker Hill and Lytle Creek basins.

Computer code Finite-element code (Durbin, 1978). Modular finite-difference code (McDonald and Harbaugh, 1988).Size and number of model 

cells

296 variably-sized triangles per layer, each triangle with an average area of about 0.60 square miles. 5,337 identical squares per layer, 250 meters on a side, each square with an area of about 0.025 square miles

Number of layers Two transmissive layers separated by a confining layer. Two transmissive layers separated by a confining layer.Simulated period Calendar years 1945–72. Calendar years 1945–98.Length of uniform stress 1 year. 1 year.

Aquifer parameters

Transmissivity Variable per cell; time invariant. Variable per cell; time invariant; values interpolated from model values used by 

Hardt and Hutchinson (1980).

Storage Variable per cell. Variable per cell in the upper model layer using values interpolated from Eckis 

(1934); constant (0.0001) for cells in the lower model layer.

Confining layer Vertical leakage through a confining layer; restriction to vertical 

flow occurs only in the middle part of the basin, designated as the confining area (fig. 28C).

 Same methology (fig. 40D)

Faults Reduced value of transmissivity in model cells coincident with 

faults.

Simulated with the horizontal-flow barrier package between model cells (Hsieh 

and Freckleton, 1993).

Recharge and discharge

Recharge from precipitation None. CSF; small amount based on the areal distribution 

of average precipitation.

Table 12. Comparison between past and present ground-water flow models of the San Bernardino area, California.[ASF, annual specified flux; CSF, constant specified flux; HDF, head-dependent flux]

170 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Item Past ground-water flow model (Hardt and Hutchinson, 1980) Present ground-water flow model (this study)

Recharge from gaged runoff ASF; single recharge array scaled, with some variations, to annual 

discharge in the Santa Ana River.

HDF; simulates interaction between surface and ground water (Prudic, 1989).

Recharge from ungaged 

runoff

ASF; added to recharge array. ASF; linearly related to discharge in the Santa Ana River.

Recharge from local runoff None. ASF; uses the areal distribution of average precipitation.Artificial recharge from 

imported water

ASF; added to recharge array. ASF.

Underflow CSF; added to recharge array. ASF; HDF used for underflow beneath the Santa Ana River.Evapotranspiration HDF; includes rising ground water. HDF; simulates evapotranspiration only.Pumpage ASF; measured and estimated values using non-verified data from 

the local watermaster; omits non-filed pumpage.

ASF; measured and estimated values using verified and non-verified data from 

the local watermaster; includes non-filed pumpage.

Return flow ASF; subtracted from pumpage. ASF; simulated separately.

Table 12. Comparison between past and present ground-water flow models of the San Bernardino area, California—Continued.[ASF, annual specified flux; CSF, constant specified flux; HDF, head-dependent flux]

Additional Tables 171
Calendar 

year

Recharge Discharge

Change in 

storage

(s)

Residual

(c)

Precipitation

(e)

Gaged 

runoff

(s)

Ungaged 

runoff

(e)

Local 

runoff

(e)

Imported 

water

(e)

Underflow

(e)

Pumpage 

return 

flow

(e)

Total

sum

Gross 

pumpage

(e)

Evapotranspiration

(s)

Rising 

ground 

water

(s)

Underflow

(e)

Total

sum

1945 1,137 120,127 20,139 6,387 0 6,800 19,967 174,558 122,106 23,231 15,152 14,054 174,544 1 131946 1,137 120,025 15,460 6,140 0 6,724 22,423 171,910 137,510 20,641 13,021 13,544 184,716 (12,799)

-6

1947 1,137 94,687 10,291 2,042 0 6,648 20,851 135,656 142,900 15,024 10,271 12,976 181,171 (45,508)

-7

1948 1,137 70,673 9,846 4,543 0 6,574 24,537 117,310 158,502 10,666 6,842 12,768 188,778 (71,465)

-4

1949 1,137 75,292 10,526 5,095 0 6,501 24,257 122,808 148,518 9,284 5,831 12,776 176,409 (53,267)

-335

1950 1,137 60,561 8,175 3,088 0 6,429 26,894 106,285 164,585 6,140 3,397 11,419 185,540 (79,247)

-8

1951 1,137 52,582 7,495 5,844 0 6,358 29,187 102,603 169,932 4,518 2,252 9,215 185,918 (83,324) 91952 1,137 158,743 17,707 7,442 0 6,287 23,461 214,777 133,607 6,602 3,461 9,046 152,717 62,058 11953 1,137 64,246 8,320 2,529 0 6,218 30,280 112,731 183,872 3,295 1,240 8,204 196,611 (83,880)

-1

1954 1,137 106,321 13,303 6,639 0 6,150 28,205 161,755 162,058 3,201 1,189 8,212 174,660 (12,905) 11955 1,137 65,643 8,460 4,197 0 6,083 30,464 115,984 183,343 2,265 936 7,450 193,994 (78,021) 121956 1,137 60,343 8,320 3,847 0 6,016 34,580 114,243 202,488 1,917 840 6,610 211,855 (97,605)

-7

1957 1,137 69,672 7,966 7,016 0 5,951 29,949 121,691 170,952 1,902 860 5,864 179,579 (57,886)

-2

1958 1,137 231,624 21,300 7,146 0 5,886 28,267 295,360 168,519 8,155 6,452 5,929 189,055 106,310 

-5

1959 1,137 68,874 8,175 3,329 0 5,822 33,037 120,374 203,029 3,000 923 5,465 212,417 (92,036)

-8

1960 1,137 55,112 7,633 4,355 0 5,759 32,358 106,355 191,980 2,233 837 5,091 200,141 (93,773)

-14

1961 1,137 37,310 4,811 2,244 0 5,697 36,776 87,976 214,041 1,588 706 4,474 220,809 (132,835) 11962 1,137 90,394 10,291 3,613 0 5,636 32,103 143,175 186,380 1,669 864 4,091 193,003 (49,828)

-0

1963 1,137 46,471 5,348 5,952 0 5,576 30,463 94,947 176,386 1,371 724 3,647 182,128 (87,169)

-12

1964 1,137 42,963 5,467 3,390 0 5,516 33,085 91,559 190,534 1,168 633 3,410 195,745 (104,187) 01965 1,137 134,743 12,653 7,451 0 5,457 30,752 192,194 169,664 1,499 905 3,249 175,318 16,858 181966 1,137 171,347 20,139 5,063 0 5,399 29,685 232,771 171,620 2,017 1,215 3,047 177,900 54,866 51967 1,137 186,326 18,871 5,880 0 5,342 26,564 244,120 155,196 5,831 5,381 2,988 169,396 74,715 91968 1,137 80,113 9,173 2,574 0 5,286 28,865 127,148 176,712 2,862 969 2,871 183,414 (56,268) 21969 1,137 400,198 66,748 10,965 0 5,230 25,013 509,291 146,606 11,308 15,129 2,886 175,928 333,359 4

Table 15. Simulated ground-water budget for the valley-fill aquifer in the San Bernardino area, California, 1945−98. [All values in acre-feet. Method of calculation and source of recharge and discharge are listed in headings; (negative) change in storage indicates loss of water from the aquifer. Area, shown in figure 22, includes the Bunker Hill and Lytle Creek ground-water basins; (e), estimated; (s), simulated; (c), calculated]

172 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Calendar 

year

Recharge Discharge

Change in 

storage

(s)

Residual

(c)

Precipitation

(e)

Gaged 

runoff

(s)

Ungaged 

runoff

(e)

Local 

runoff

(e)

Imported 

water

(e)

Underflow

(e)

Pumpage 

return 

flow

(e)

Total

sum

Gross 

pumpage

(e)

Evapotranspiration

(s)

Rising 

ground 

water

(s)

Underflow

(e)

Total

sum

1970 1,137 104,569 11,583 4,991 0 5,175 30,438 157,893 174,878 4,672 1,906 3,018 184,474 (26,551) -301971 1,137 80,164 9,605 4,619 0 5,121 30,985 131,631 181,503 3,069 1,224 3,207 189,004 (57,374) 21972 1,137 59,995 7,170 2,351 1,208 5,067 30,831 107,759 177,714 2,346 948 3,330 184,338 (76,586) 71973 1,137 142,164 17,518 4,978 30,419 5,014 26,683 227,914 156,494 3,118 1,355 3,500 164,468 63,459 -131974 1,137 97,351 11,448 5,166 15,222 4,962 26,765 162,052 157,498 2,735 1,199 3,717 165,149 (3,112) 151975 1,137 76,841 9,605 4,094 13,275 4,911 24,468 134,331 158,061 2,426 1,079 3,764 165,330 (30,995) -41976 1,137 79,867 9,480 5,171 11,794 4,860 23,170 135,480 158,200 2,292 1,047 3,752 165,292 (29,805) -61977 1,137 64,689 7,170 5,117 22,653 4,810 24,966 130,543 160,145 2,395 1,472 3,729 167,741 (37,203) 61978 1,137 367,931 33,981 10,580 12,279 4,760 21,903 452,571 140,691 12,045 11,305 3,862 167,902 284,680 -111979 1,137 230,248 31,633 5,646 4,230 4,711 22,865 300,471 154,528 15,946 13,773 4,524 188,772 111,704 -41980 1,137 233,890 67,711 9,116 4,191 4,663 23,862 344,571 155,325 23,703 28,253 5,796 213,076 131,487 81981 1,137 94,289 10,291 3,950 14,321 4,616 27,097 155,700 175,469 10,543 6,951 7,160 200,123 (44,425) 31982 1,137 135,714 18,943 7,864 8,544 4,569 22,551 199,322 153,520 11,545 5,886 8,509 179,460 19,859 31983 1,137 204,569 50,283 11,796 1,404 4,522 20,723 294,436 137,137 26,578 29,462 9,626 202,803 91,615 181984 1,137 108,536 11,986 3,065 361 4,476 26,742 156,303 186,002 11,559 5,534 10,060 213,155 (56,849) -31985 1,137 83,675 9,480 3,740 1,108 4,431 27,813 131,385 194,783 6,701 2,369 9,995 213,848 (82,363) -1001986 1,137 121,958 13,303 5,328 0 4,387 27,836 173,950 190,105 6,097 2,107 9,070 207,379 (33,421) -81987 1,137 63,520 7,495 4,471 81 4,342 28,515 109,562 194,627 3,570 1,006 8,159 207,362 (97,804) 41988 1,137 60,606 6,474 4,180 0 4,299 31,437 108,133 210,010 2,588 720 7,189 220,507 (112,357) -171989 1,137 48,661 5,467 2,481 4,138 4,256 32,155 98,295 198,429 1,972 655 6,164 207,220 (108,920) -4

Table 15. SImulated ground-water budget for the valley-fill aquifer in the San Bernardino area, California, 1945−98—Continued. [All values in acre-feet. Method of calculation and source of recharge and discharge are listed in headings; (negative) change in storage indicates loss of water from the aquifer. Area, shown in figure 22, includes the Bunker Hill and Lytle Creek ground-water basins; (e), estimated; (s), simulated; (c), calculated]

Additional Tables 173
Calendar 

year

Recharge Discharge

Change in 

storage

(s)

Residual

(c)

Precipitation

(e)

Gaged 

runoff

(s)

Ungaged 

runoff

(e)

Local 

runoff

(e)

Imported 

water

(e)

Underflow

(e)

Pumpage 

return 

flow

(e)

Total

sum

Gross 

pumpage

(e)

Evapotranspiration

(s)

Rising 

ground 

water

(s)

Underflow

(e)

Total

sum

1990 1,137 36,506 3,977 2,810 6,497 4,213 32,083 87,224 194,598 1,235 620 5,804 202,257 (115,036) 31991 1,137 83,704 8,175 6,123 1,014 4,172 30,346 134,671 188,864 1,594 679 4,712 195,849 (61,189) 111992 1,137 120,025 12,181 6,899 117 4,130 30,230 174,720 184,409 1,607 605 4,112 190,733 (16,002)

-12

1993 1,137 379,934 52,482 9,022 2,254 4,089 29,371 478,290 187,323 11,708 9,920 4,057 213,007 265,269 141994 1,137 90,814 11,042 4,758 3,633 4,049 29,949 145,381 203,236 4,324 1,442 3,882 212,884 (67,501)

-2

1995 1,137 266,055 38,408 7,424 0 4,009 28,898 345,931 193,858 14,767 10,534 3,727 222,885 123,039 71996 1,137 123,131 14,265 6,418 93 3,970 31,999 181,013 214,695 5,939 2,153 3,871 226,658 (45,635)

-10

1997 1,137 102,672 11,042 5,956 0 3,931 31,622 156,360 210,527 4,334 1,419 3,750 220,031 (63,669)

-1

1998 1,137 239,066 35,918 9,951 151 3,892 26,388 316,504 182,543 16,485 12,105 4,343 215,475 101,028 11945

−98 

Maximum

1,137 400,198 67,711 11,796 30,419 6,800 36,776 509,291 214,695 26,578 29,462 14,054 226,658 333,359 18

1945

−98 

Average

1,137 121,584 16,199 5,460 2,944 5,181 28,050 180,555 174,189 6,839 4,773 6,216 192,017 (11,454)

-8

1983

−98

Average

1,137 133,340 18,249 5,901 1,303 4,198 29,132 193,260 191,947 7,566 5,083 6,158 210,753 (17,487)

-6

1945

−98 

Minimum

1,137 36,506 3,977 2,042 0 3,892 19,967 87,224 122,106 1,168 605 2,871 152,717 (132,835)

-335

Table 15. SImulated ground-water budget for the valley-fill aquifer in the San Bernardino area, California, 1945−98

—Continued. 

[All values in acre-feet. Method of calculation and source of recharge and discharge are listed in headings; (negative) change in storage indicates loss of water from the aquifer. Area, shown in figure 22, includes the Bunker Hill and Lytle Creek ground-water basins; (e), estimated; (s), simulated; (c), calculated]

174 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Scenario Purpose Description Result

Scenario 1—Average 

recharge and pumpage, 1999–2030.

Show the general trend of future 

surface-water flows and ground-water levels if present (1998) water-management operations are continued.

This scenario is the constant version of scenario 2. Runoff, 

recharge, and pumpage equal the average of annual values for the period 1983–98. No water is imported from Northern California.

In nearly all areas, ground-water levels flatten 

within a couple of years, indicating that the aquifer is highly transmissive and that recharge and discharge are approximately in balance (fig. 56). During the 32-year period, ground-water levels tend to rise in the former marshland and decline in the outlying areas.

Scenario 2—Annual 

variations in recharge and pumpage, 1999–2030.

Show the range of effects of 

continuing present (1998) water-management operations, assuming recent (1983–98) annual variations in recharge and pumpage.

This scenario is the base case for scenarios 1, 3, 4, and 6. 

Runoff, recharge, and pumpage equal annual values for the period 1983–98, repeated twice. No water is imported from Northern California.

In most areas, ground-water levels rise and fall 

within an acceptable range that prevents damage from elevated hydrostatic presssure, liquefaction, or land subsidence (fig. 57). High ground-waterlevel conditions, however, occur in the former marshland during wetter periods.

Scenario 3—Increase artificial recharge, 1999–2030. Show the effects of increasing artificial recharge of either 

imported water or local runoff made available for recharge by construction of Seven Oaks Dam.

Uses values of runoff, recharge, and pumpage from scenario 

2, plus additional artifical recharge ranging from 3,500 to 25,000 acre-feet per year in the Santa Ana River recharge basins.

Ground-water levels show little change compared 

to scenario 2 in most areas (figs. 57−58). Much of the additional recharge is discharged to the streams or increaes underflow out of the aquifer, decreasing the effect of the extra recharge.

Scenario 4—Increase 

ground-water pumpage, 1999–2030.

Show the effects of increasing 

ground-water pumpage using recent (1994–98) excess well capacity.

Uses values of runoff, recharge, and pumpage from scenario 

2. Extra pumpage is added equal to the difference between maximum and average pumpage for each well during 1994–98. No water is imported from Northern California. Four test cases (a−d) (fig. 60) are evaluated, each using wells located progessively further from the basin outflow.

In most areas, ground-water levels fall significantly 

if net pumpage exceeds about 15,000 acre-feet per year, which can be achieved using wells within 10,000 feet of basin outflow (fig. 59). Net pumpage of more than about 35,000 acrefeet per year, which can be obtained within the former marshland, causes precipitious declines likely to prompt additional land subsidence.

Scenario 5—Optimal 

hydraulic containment of contaminated ground water in the Newmark area.

Determine the minimum pumpage needed to prevent further 

migration of trichloroethylene (TCE) and perchloroethylene (PCE) contamination associated with the Newmark U.S. Environmental Protection Agency Superfund site.

Uses values of runoff, recharge, and pumpage from scenario 

2 except all pumpage within the plume is set to zero. Identifies the minimum pumpage needed to prevent further migration of the contamination by determining optimal pumpage at five planned and four hypothetical barrier well sites located along the leading (south) edge of the contamination (fig. 61). Constraints on hydraulic gradients around the edge of the plume are used to assure that the plume does not spread laterally or bypass the nine barrier wells.

Maximum pumpage from the five planned wells 

appears to be insufficient to prevent further migration of the contamination (figs. 61−62). If all nine well sites are used, the leading edge of the contamination can be contained. No realistic quantity of pumpage from the nine barrier well sites will restrict lateral, east-west migration of the contamination.

Table 19. Description of water-management scenarios simulated by the ground-water flow and constrained optimization models for the San Bernardino area, California.

Additional Tables 175
Scenario Purpose Description Result

Scenario 6—Optimal 

management of groundwater levels in the former marshland.

Determine the minimum total 

pumpage from hypothetical well sites along proposed extensions of the Baseline feeder pipeline in order to maintain safe ground-water levels within the vicinity of the former marshland.

Uses values of runoff, recharge, and pumpage from scenario 

2. Pumpage is determined at 29 possible well sites along three proposed extensions of the Baseline feeder pipeline (fig. 63). Ground-water levels are constrained at 58 locations within the former marshland to be no higher than 30 feet below land surface and no lower than the minimum simulated value during 1945–98.

Results indicate that the problem is infeasible 

with the assumed distribution of wells, even if the constraint is changed to 10 feet below land surface (figs. 64–65). About 20,000 acre-feet of additional pumpage is needed to satisfy the constraints at most locations during most years. Nearly all infeasiblities are caused by groundwater levels being too high during the occassional wet years.

Table 19. Description of water-management scenarios simulated by the ground-water flow and constrained optimization models for the San Bernardino area, California—Continued.

176 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives
Recharge or 

discharge 

component

Calibration

Scenario

1 2 3 4 5 6

Recharge from direct 

precipitation

Small contant value (table 4) Calibration Calibration Calibration Calibration Calibration Calibration

Recharge from gaged 

runoff

Measured annual discharge for 

gaged streams used in a streamflow-routing model linked to the ground-water flow model (table 1)

Average runoff 

values from scenario 2

Annual runoff 

values for 1983–98, repeated twice

Same runoff 

values as scenario 2

Same runoff 

values as scenario 2

Same runoff 

values as scenario 2

Same runoff 

values as scenario 2

Recharge from ungaged 

runoff

Estimates based on drainage area, 

precipitation, and runoff percentage, then scaled by percent annual runoff in the Santa Ana River (tables 2 and 3)

Average values from 

scenario 2

Annual values 

for 1983–98, repeated twice

Scenario 2 Scenario 2 Scenario 2 Scenario 2

Recharge from local 

runoff

Estimates based on annual precipitation (table 4) Average values from scenario 2 Annual values for 1983–98, 

repeated twice

Scenario 2 Scenario 2 Scenario 2 Scenario 2

Recharge from imported 

water

Estimated from measured annual 

values of imported water (table 5)

Zero Zero Zero Zero Zero Zero

Underflow from the 

Badlands, Redlands Heights, and Reservoir Canyon

Small constant values (table 9; 

figure 59)

Calibration Calibration Calibration Calibration Calibration Calibration

Underflow from San 

Timoteo Canyon

Estimated from regression equation (3) (table 9, figs. 26-27) Estimated from re- gression equation 

(3) (fig. 53)

Scenario 1 Scenario 1 Scenario 1 Scenario 1 Scenario 1

Underflow from Sand 

Canyon

Estimated from regression equation (4) (table 9, figs. 26-27) Estimated from re- gression equation 

(4) fig.27)

Scenario 1 Scenario 1 Scenario 1 Scenario 1 Scenario 1

Underflow across the 

San Jacinto fault near Barrier J

Constant value (table 9) Calibration Calibration Calibration Calibration Calibration Calibration

Table 20. Recharge and discharge components for scenarios 1–6 for the San Bernardino area, California, 1999–2030.[See table 19 for definition of scenarios. All values vary annually, unless noted as constant. Calibration is calibration of the ground-water flow model. Included, additional recharge or discharge component noted as included in selected scenarios; —, not included]

Additional Tables 177
Recharge or 

discharge 

component

Calibration

Scenario

1 2 3 4 5 6

Underflow across the San 

Jacinto fault near the Santa Ana River

Head-dependent discharge calculated from measured head in the 

Heap well (table 9, fig.28)

Head-dependent discharge calculated 

from simulated head in the model cell for the Heap well, equation 5 (fig. 28)

Same headdependent 

relation used in scenario 1

Same headdependent 

relation used in scenario 1

Same headdependent 

relation used in scenario 1

Same headdependent 

relation used in scenario 1

Same headdependent 

relation used in scenario 1

Pumpage Reported and estimated annual 

values (table 10)

Average values from 

scenario 2

Annual values 

for 1983–98, repeated twice

Scenario 2 Scenario 2 Scenario 2 Scenario 2

Return flow Estimated annual values based on 

constant percentage of pumpage per well

Average values from 

scenario 2

Annual values 

for 1983–98, repeated twice

Scenario 2 Scenario 2 Scenario 2 Scenario 2

Evapotranspiration Head-dependent value calculated from estimated maximum 

evapotranspiration

Same head-dependent relation used 

in calibration

Same headdependent 

relation used in calibration

Same headdependent 

relation used in calibration

Same headdependent 

relation used in calibration

Same headdependent 

relation used in calibration

Same headdependent 

relation used in calibration

Recharge of additional 

native water

Not included in

 calbration

—

— Included

—

—

—

Recharge of additional native or imported water ditto

—

—

—

—

—

—

Additional pumpage using 

excess well capacity ditto

—

—

— Included

—

—

Additional pumpage using 

barrier wells near the leading edge of Newmark plume ditto

—

—

—

— Included

—

Additional pumpage using 

possible wells along extensions of the Baseline feeder pipeline

 ditto

—

—

—

—

— Included

Table 20. Recharge and discharge components for scenarios 1–6 for the San Bernardino area, California, 1999–2030

—Continued.

[See table 19 for definition of scenarios. All values vary annually, unless noted as constant. Calibration is calibration of the ground-water flow model. Included, additional recharge or discharge component noted as included in selected scenarios; 

—, not included]

178 Hydrology, Description of Computer Models, and Evaluation of Selected Water-Management Alternatives