U.S. GEOLOGICAL SURVEY

Water-Resources Investigations Report

Numerical Simulation of Ground-Water Flow and

Assessment of the Effects of Artificial Recharge

in the Rialto–Colton Basin, San Bernardino 

County, California

Prepared in cooperation with the

SAN BERNARDINO VALLEY MUNICIPAL WATER DISTRICT

00-4243

By Linda R. Woolfenden and Kathryn M. Koczot

Sacramento, California

2001

5020-75
U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

For additional information write to: Copies of this report can be purchased from:

U.S. Geological Survey

Information Services

Box 25286

Federal Center

Denver, CO 80225

The use of firm, trade, and brand names in this report is for identification purposes only and 

does not constitute endorsement by the U.S. Geological Survey.

District Chief

U.S. Geological Survey

Placer Hall, Suite 2012

6000 J Street

Sacramento, CA 95819-6129
Contents III

CONTENTS

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

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

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

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

Field and Analytical Methods...................................................................................................................................... 9

Acknowledgments ....................................................................................................................................................... 11

Geohydrology ........................................................................................................................................................................ 11

Stratigraphic Units....................................................................................................................................................... 11

Description of Aquifer System .................................................................................................................................... 11

Water-Bearing Units .......................................................................................................................................... 12

Horizontal-Flow Barriers................................................................................................................................... 12

Ground-Water Levels and Movement.......................................................................................................................... 18

Recharge ............................................................................................................................................................ 27

Discharge ........................................................................................................................................................... 28

Numerical Simulation of Ground-Water Flow ...................................................................................................................... 29

Conceptual Model........................................................................................................................................................ 29

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

Flow-Model Construction............................................................................................................................................ 32

Model Grid ........................................................................................................................................................ 32

Boundary Conditions......................................................................................................................................... 33

Recharge ............................................................................................................................................................ 35

Underflow................................................................................................................................................ 35

Surface Spreading of Imported Water ..................................................................................................... 40

Ungaged Runoff and Subsurface Inflow ................................................................................................. 40

Irrigation Return Flow ............................................................................................................................. 41

Areal Recharge of Rainfall ...................................................................................................................... 42

Seepage Loss from the Santa Ana River, Warm Creek, and the Diversion Canal................................... 42

Discharge ........................................................................................................................................................... 43

Pumpage .................................................................................................................................................. 44

Underflow................................................................................................................................................ 45

Evapotranspiration................................................................................................................................... 47

Flow Barriers ..................................................................................................................................................... 47

Aquifer Properties.............................................................................................................................................. 49

Hydraulic Conductivity ........................................................................................................................... 49

Aquifer Thickness.................................................................................................................................... 49

Vertical Conductance............................................................................................................................... 54

 Storage Coefficient and Specific Yield................................................................................................... 54

Model Calibration........................................................................................................................................................ 56

Initial Conditions ............................................................................................................................................... 59

Transient Simulation.......................................................................................................................................... 60

Calibration Results ............................................................................................................................................ 61

Simulated Water Budgets ............................................................................................................................................ 75

Sensitivity Analysis ..................................................................................................................................................... 80

Simulated Effects of Artificial-Recharge Alternatives on Ground-Water Levels and Movement......................................... 82

Continued Artificial Recharge at Linden Ponds.......................................................................................................... 83

Discontinued Artificial Recharge at Linden Ponds ..................................................................................................... 85

Artificial Recharge at Cactus Basin............................................................................................................................. 85

Discussion of Results of Transient and Predictive Simulations ............................................................................................ 91
IV Contents

Effects of Artificial Recharge and the Importance of the Unnamed Fault.................................................................. 91

Stream Losses from the Santa Ana River and Warm Creek........................................................................................ 92

Underflow from the Rialto–Colton Basin to the Chino and North Riverside Basins ................................................. 93

Underflow from the Lytle Basin to the Rialto–Colton Basin...................................................................................... 95

Underflow from the Bunker Hill Basin to the Rialto–Colton Basin........................................................................... 96

Use and Limitations of Ground-Water Flow and Particle-Tracking Models ........................................................................ 98

Summary and Conclusions.................................................................................................................................................... 100

References Cited ................................................................................................................................................................... 103

Appendix A ........................................................................................................................................................................... 105

FIGURES

1–4. Maps showing:

1. Location and geographic setting of the Rialto–Colton Basin, San Bernardino County, California................. 4

2. Location of cluster sites, selected production wells, and stream-gaging stations in the Rialto–Colton 

Basin, San Bernardino County, California ....................................................................................................... 5

3. Land use in the Rialto–Colton Basin, San Bernardino County, California, 1949 ............................................ 7

4. Land use in the Rialto–Colton Basin, San Bernardino County, California, 1993 ............................................ 8

5. Graph showing annual precipitation and cumulative departure from mean annual precipitation at San Bernardino,

California, 1871–1998 ............................................................................................................................................. 10

 6. Map showing location of cluster sites, selected production wells, and lines of geohydrologic section in the 

Rialto–Colton Basin, San Bernardino County, California ....................................................................................... 13

 7. Generalized geohydrologic sections A–A’ through F–F’ in the Rialto–Colton Basin, San Bernardino County,

California ................................................................................................................................................................. 14

 8. Map showing composite potentiometric contours and direction of ground-water movement, spring 1945, 

in the Rialto–Colton Basin, San Bernardino County, California............................................................................. 20

9. Map showing potentiometric contours and direction of ground-water movement in the middle water-bearing 

unit, and in the lower water-bearing unit, spring 1996, in the Rialto–Colton Basin, San Bernardino County, 

California ................................................................................................................................................................. 21

 10. Hydrograph showing water-level altitude in selected production wells, 1928–98, in the Rialto–Colton Basin, 

San Bernardino County, California.......................................................................................................................... 23

11. Hydrograph showing water-level altitude in selected observation wells along a flowpath through Linden Ponds

artificial-recharge site, and in other parts of the basin southwest of the unnamed fault, 1992–98, in the 

Rialto–Colton Basin, San Bernardino County, California ....................................................................................... 24

 12. Graph showing annual recharge of imported water in the Rialto–Colton Basin, San Bernardino County, 

California, 1982–96 ................................................................................................................................................. 27

13. Graph showing annual pumpage in the Rialto–Colton Basin, San Bernardino County, California, 1945–96 ........ 28

14. Map showing model grid and boundary conditions for layers 1–4 of the Rialto–Colton Basin ground-water 

flow model, San Bernardino County, California ..................................................................................................... 30

15. Graph showing relation between water-level altitude in wells 1S/4W-29H2 and 1S/4W-28L1 in the Rialto–Colton

Basin, San Bernardino County, California............................................................................................................... 35

16–23. Maps showing model grid of the Rialto–Colton Basin ground-water flow model and areal distribution of:

16. Pumpage, irrigation canal, and artificial-recharge cells for layers 1–4 ............................................................ 38

17. Recharge from rainfall infiltration cells for layers 1–3 .................................................................................... 42

18. Stream and evapotranspiration cells for layer 1 ............................................................................................... 43

19. Flow barriers for model layers 3 and 4............................................................................................................. 48

20. Hydraulic conductivity for layers 1–4.............................................................................................................. 50

21. Thickness for layers 1–4................................................................................................................................... 52

22. Vertical conductance between layers 1 and 2, 2 and 3, and 3 and 4................................................................. 55

23. Primary and secondary storage coefficients for layers 1–4.............................................................................. 57

24. Graph showing relation between simulated head and measured water-level altitude, 1945, in the Rialto–Colton 

Basin, San Bernardino County, California............................................................................................................... 62

25–30. Maps showing:

25. Distribution of residuals for the initial-conditions (1945) simulation in the Rialto–Colton Basin, 

San Bernardino County, California .................................................................................................................. 63
Contents V

26. Location of wells, and hydrographs showing simulated heads and measured water-level altitudes for 

selected production wells in the Rialto–Colton Basin, San Bernardino County, California............................ 64

 27. Location of wells, and hydrographs showing simulated heads and measured water-level altitudes for 

selected cluster wells in layers 1–4 in the Rialto–Colton Basin, San Bernardino County, California............. 66

28. Simulated potentiometric contours for layers 1–4, 1945, in the Rialto–Colton Basin, San Bernardino 

County, California ............................................................................................................................................ 69

29. Simulated potentiometric contours for layers 1 and 2, 1996, in the Rialto–Colton Basin, San Bernardino 

County, California ............................................................................................................................................ 73

30. Measured water-level altitudes and simulated potentiometric contours for layers 3 and 4, 1996, in the 

Rialto–Colton Basin, San Bernardino County, California................................................................................ 76

31. Diagram showing components of recharge in the Rialto–Colton Basin, San Bernardino County, California ........ 79

32. Diagram showing components of discharge in the Rialto–Colton Basin, San Bernardino County, California....... 79

33–37. Maps showing:

33. Location of wells, and hydrographs showing measured water-level altitudes and simulated hydraulic-head

response in layer 3 for recharge in Linden Ponds, using the 1982–96 recharge pattern and the discontinued

artificial-recharge pattern, in the Rialto–Colton Basin, San Bernardino County, California........................... 84

34. Simulated flow paths of imported water during 1982–2027, with continued recharge at Linden Ponds, 

using the 1982–96 recharge pattern in the Rialto–Colton Basin, San Bernardino County, California ........... 86

35. Simulated flow paths of imported water in layer 3 during 1982–93 and during 1982–2027, with 

discontinued recharge at Linden Ponds in the Rialto–Colton Basin, San Bernardino County, California ...... 87

36. Location of wells, and hydrographs showing measured water-level altitudes and simulated hydraulic-head

response in layer 3 for recharge in Cactus Basin, using the 1982–96 recharge pattern and the discontinued

artificial-recharge pattern, in the Rialto–Colton Basin, San Bernardino County, California........................... 89

37. Simulated flow paths of imported water during 2000–2027, with recharge in Cactus Basin using the 

1982–96 recharge pattern, in the Rialto–Colton Basin, San Bernardino County, California.......................... 90

38–42. Graphs showing:

38. Simulated gains and losses from the Santa Ana River and Warm Creek, 1945–96, in the Rialto–Colton 

Basin, San Bernardino County, California ....................................................................................................... 92

39. Net pumpage and simulated underflow from the Rialto–Colton Basin to the Chino and North Riverside 

Basins, 1945–96, San Bernardino County, California...................................................................................... 94

40. Simulated underflow from the Lytle Basin to the Rialto–Colton Basin, 1945–96, San Bernardino County,

California.......................................................................................................................................................... 95

41. Annual discharge in Lytle Creek, 1945–96, San Bernardino County, California ............................................ 96

42. Simulated underflow from the Bunker Hill Basin to the Rialto–Colton Basin, 1945–96, San Bernardino 

County, California ............................................................................................................................................ 97

TABLES

1. Estimated annual recharge in the Rialto–Colton Basin, San Bernardino County, California, for various periods

during 1935–96....................................................................................................................................................... 26

2. Measured and estimated water-level altitudes in wells 1S/4W-29H2 and 1S/4W-28L1, San Bernardino

County, California, 1945–96................................................................................................................................... 34

3. Underflow from the Lytle Basin to the Rialto–Colton Basin, San Bernardino County, California, 1945–96........ 36

4. Underflow from the Bunker Hill Basin to the Rialto–Colton Basin, San Bernardino County, California, 

1945–96 .................................................................................................................................................................. 37

5. Quantities of imported water artificially recharged at Linden Ponds, San Bernardino County, California 

1982–96 .................................................................................................................................................................. 40

6. Ungaged runoff from the San Gabriel Mountains and the Badlands, San Bernardino County, California, 

1945–96 .................................................................................................................................................................. 41

7. Seepage loss in the diversion canal, San Bernardino County, California, 1945–55............................................... 44

8. Annual total and net pumpage from the Rialto–Colton Basin, San Bernardino County, California, 1945–96...... 44

9. Percent of pumpage from each layer for production wells in the Rialto–Colton Basin, San Bernardino County,

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

10. Measured water-level altitude and simulated hydraulic head in selected wells for initial conditions (1945) 

in the Rialto–Colton Basin, San Bernardino County, California............................................................................ 61
VI Contents

11. Model-simulated initial conditions and transient water budgets for the Rialto–Colton Basin, San Bernardino 

County, California................................................................................................................................................... 78

12. Sensitivity of hydraulic head in the Rialto–Colton Basin model (1996), San Bernardino County, California, 

to changes in model input....................................................................................................................................... 80

13. Actual and projected quantities of artificial recharge in Linden Ponds and Cactus Basin, San Bernardino County,

California, 1997–2027 ............................................................................................................................................ 82

14. Average values of major sources of recharge and discharge in the Rialto–Colton Basin, San Bernardino 

County, California................................................................................................................................................... 93

CONVERSION FACTORS, VERTICAL DATUM, ABBREVIATIONS, AND

DEFINITIONS, AND WELL-NUMBERING SYSTEM

Conversion Factors

Sea level: In this report, "sea level" refers to the National Geodetic Vertical Datum of 1929 (NGVD 

of 1929)—a geodetic datum derived from a general adjustment of the first-order level nets of both 

the United States and Canada, formerly called Sea Level Datum of 1929.

Multiply By To obtain

Length

inch (in.) 2.54 centimeter

foot (ft) 0.3048 meter

mile (mi) 1.609 kilometer

Area

square mile (mi2) 259.0 hectare

square mile (mi2) 2.590 square kilometer 

Volume

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

acre-foot (acre-ft) 0.001233 cubic hectometer 

Flow rate

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

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

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

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

feet per year (ft/yr) 111.252 meters per year

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

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

 square foot per second (ft2/s) 0.0929 square meter per second

Hydraulic conductivity

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

Leakance

foot per day per foot [(ft/d)/ft] 1 meter per day per meter
Contents VII

Well

1S/5W-12L1

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

R4W R3W

T1S

T1N

T2N

R7W R6W R5W

T2S

T3S

R5W

T1S

MERIDAN

BASE LINE 12

Abbreviations and Definitions

ADAPS Automated Data Processing System

AML Arc Macro Language

ARC-INFO Geographic information system (GIS) software developed by Environmental Systems 

Research Institute, Inc. (ESRI), Redlands, California

DEM Digital evaluation model

GWSI Groound-Water Site Inventory System

HFB Package Horizontal-flow-barrier package, a computer program (Hsieh and Freckleton, 1993) 

that simulates low-permeability geologic features that impede the horizontal flow of 

ground water

MODFLOW Modular finite-difference ground-water flow model developed by the U.S. Geological 

Survey (McDonald and Harbaugh, 1988) that simulates steady and unsteady flow in a 

flow system consisting of confined and (or) unconfined layers

MODPATH A particle-tracking postprocessing package, consisting of two Fortran computer codes, 

developed by the U.S. Geological Survzey to compute three-dimensional flow paths and 

times of travel using output from MODFLOW simulations

SBVMWD San Bernardino Valley Municipal Water District

USGS U.S. Geological Survey

Water year The 12-month period that starts October 1 and ends September 30; it is designated by the 

calendar year in which it ends and which contains 9 of the 12 months

Well- and Spring-Numbering System

Wells and springs are identified and numbered by the State of California 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 letter "S" inserted before the sequence number indicates a spring. 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). Because all wells in the study areas of this report are referenced to 

the San Bernardino base line and meridian, the final letter “S” will be omitted. Well numbers consist of 15 

characters and follow the format 001S005W-12L001S. In this report, well numbers are abbreviated and written 

1S/5W-12L1. The following diagram of the well-numbering system shows how well number 1S/5W-12L1 is 

derived. 

Abstract 1

Numerical Simulation of Ground-Water Flow and Assessment 

of the Effects of Artificial Recharge in the Rialto–Colton 

Basin, San Bernardino County, California

By Linda R. Woolfenden and Kathryn M. Koczot

ABSTRACT

The Rialto–Colton Basin, in western San 

Bernardino County, California, was chosen for 

storage of imported water because of the good 

quality of native ground water, the known storage 

capacity for additional ground-water storage in the 

basin, and the availability of imported water. To 

supplement native ground-water resources and 

offset overdraft conditions in the basin during dry 

periods, artificial-recharge operations during wet 

periods in the Rialto–Colton Basin were begun in 

1982 to store surplus imported water. Local water 

purveyors recognized that determining the movement and ultimate disposition of the artificially 

recharged imported water would require a better 

understanding of the ground-water flow system.

In this study, a finite-difference model was 

used to simulate ground-water flow in the Rialto–

Colton Basin to gain a better understanding of the 

ground-water flow system and to evaluate the 

hydraulic effects of artificial recharge of imported 

water. The ground-water basin was simulated as 

four horizontal layers representing the riverchannel deposits and the upper, middle, and lower 

water-bearing units. Several flow barriers bordering and internal to the Rialto–Colton Basin influence the direction of ground-water flow. Ground 

water may flow relatively unrestricted in the shallow parts of the flow system; however, the faults 

generally become more restrictive at depth. A 

particle-tracking model was used to simulate 

advective transport of imported water within the 

ground-water flow system and to evaluate three 

artificial-recharge alternatives.

The ground-water flow model was calibrated to transient conditions for 1945–96. Initial 

conditions for the transient-state simulation were 

established by using 1945 recharge and discharge 

rates, and assuming no change in storage in the 

basin. Average hydrologic conditions for 1945–96 

were used for the predictive simulations 

(1997–2027). Ground-water-level measurements 

made during 1945 were used for comparison with 

the initial-conditions simulation to determine if 

there was a reasonable match, and thus reasonable 

starting heads, for the transient simulation. The 

comparison between simulated head and measured 

water levels indicates that, overall, the simulated 

heads match measured water levels well; the 

goodness-of-fit value is 0.99. The largest differences between simulated head and measured water 

level occurred between Barrier H and the Rialto–

Colton Fault. Simulated heads near the Santa Ana 

River and Warm Creek, and simulated heads 

northwest of Barrier J, generally are within 30 feet 

of measured water levels and five are within 

20 feet.

Model-simulated heads were compared 

with measured long-term changes in hydrographs 

of composite water levels in selected wells, and 

with measured short-term changes in hydrographs 

of water levels in multiple-depth observation wells 

installed for this project. Simulated hydraulic 

heads generally matched measured water levels in 

wells northwest of Barrier J (in the northwestern 
2 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

part of the basin) and in the central part of the basin 

during 1945–96. In addition, the model adequately 

simulated water levels in the southeastern part of 

the basin near the Santa Ana River and Warm 

Creek and east of an unnamed fault that 

subparallels the San Jacinto Fault. Simulated 

heads and measured water levels in the central part 

of the basin generally are within 10 feet until about 

1982–85 when differences become greater. In the 

northwestern part of the basin southeast of Barrier 

J, simulated heads were as much as 50 feet higher 

than measured water levels during 1945–82 but 

matched measured water levels well after 1982. In 

the compartment between Barrier H and the 

Rialto–Colton Fault, simulated heads match well 

during 1945–82 but are comparatively low during 

1982–96. Near the Santa Ana River and Warm 

Creek, simulated heads generally rose above measured water levels except during 1965–72 when 

simulated heads compared well with measured 

water levels.

Average annual total recharge calculated by 

the model during 1945–96 was about 

33,620 acre-feet and average total discharge was 

about 35,220 acre-feet. Underflow from the Bunker Hill and Lytle Basins accounted for about 

59 percent of total recharge. Seepage loss from the 

Santa Ana River and Warm Creek accounted for 

about 15 percent of total recharge. Underflow to 

the Chino and North Riverside Basins accounted 

for about 65 percent of total discharge. Model 

results for 1945–96 indicate that the quantity of 

water removed from storage was about 

7,350 acre-feet, and the quantity going into storage 

was about 5,960 acre-feet, resulting in a net average storage depletion of about 1,390 acre-ft/yr.

A sensitivity analysis was done to determine 

the model inputs that were most important in 

affecting model-generated hydraulic heads at the 

calibration wells. In layers 1, 2, and 3, hydraulic 

heads were most sensitive to an increase in total 

recharge. Hydraulic heads in layer 1 also are sensitive to an increase in the streambed conductance. 

Hydraulic heads in layers 2 and 3 also are sensitive 

to removal of all internal barrier conditions. In 

layer 4, hydraulic heads were most sensitive to the 

removal of all internal barriers and removal of the 

unnamed fault. Hydraulic heads were least sensitive in layer 1 to a reduction in the primary storage 

coefficient and the removal of Barrier H; in layer 

2, to an increase in the primary storage coefficient 

and the removal of Barrier H; in layer 3, to a 

decrease in the primary storage coefficient and an 

increase in the vertical conductance; and in layer 4 

to an increase in the primary storage coefficient 

and a decrease in the primary storage coefficient.

Predictive simulations were made for three 

artificial-recharge alternatives, including artificial 

recharge at Linden Ponds, discontinued artificial 

recharge, and artificial recharge at Cactus Basin. 

To extend the ground-water flow model beyond 

1996, average hydrologic conditions (natural 

recharge and discharge) for 1945–96 were used for 

the predictive simulation period, 1997–2027. 

Results of the predictive simulations indicate that 

artificial recharge at Linden Ponds causes water 

levels to rise northeast of the unnamed fault (which 

isolates the recharge ponds from the main waterproducing part of the basin) but has little influence 

on water levels southwest of the unnamed fault. 

The water-level response to artificial recharge at 

Cactus Basin indicates that wells northwest of 

Barrier J and northeast of the unnamed fault are 

sufficiently isolated by the faults to be affected. 

Water levels southeast of Barrier J and north of the 

Santa Ana River and Warm Creek rose as much as 

50 feet higher than discontinued recharge levels. 

Water levels near the Santa Ana River and Warm 

Creek were not affected with artificial recharge at 

either Linden Ponds or Cactus Basin, indicating 

that a longer period of recharge would be needed 

to raise water levels in this area.

 Results of the particle-tracking simulations 

indicate that the imported water would reach production wells only with artificial recharge at 

Cactus Basin, suggesting that artificial recharge at 

Cactus Basin may make the imported water more 

available to production wells than recharge at Linden Ponds. The imported-water particles move 

only about a mile farther with artificial recharge at 

Linden Ponds than with discontinued recharge in 

the basin, indicating that artificial recharge may be 

only slightly more effective than the absence artificial recharge in the movement of imported water.
Introduction 3

INTRODUCTION

The Rialto–Colton Basin, in western San 

Bernardino County, California, is experiencing continued population growth. Water purveyors rely on 

ground-water resources to meet local water-supply 

needs. To supplement native ground-water resources 

and offset overdraft conditions in the basin during dry 

periods, artificial-recharge operations during wet periods were begun in 1982 to store surplus imported water 

originating in the Sierra Nevada; these artificialrecharge operations ended in 1994. Local water purveyors recognized the need to determine the movement 

and ultimate disposition of the artificially recharged 

imported water within the Rialto–Colton Basin. It was 

recognized, also, that this could be accomplished by 

means of a ground-water flow model of the Rialto–

Colton Basin, which could aid in better understanding 

the ground-water flow system and in evaluating the 

hydraulic effects of artificial recharge of imported 

water.

Purpose and Scope

In 1991 the San Bernardino Valley Municipal 

Water District (SBVMWD) entered into a cooperative 

program with the U.S. Geological Survey (USGS) to 

study the ground-water flow system and water chemistry in the Rialto–Colton Basin. In the first phase of the 

program the geohydrology and water chemistry were 

described (Woolfenden and Kadhim, 1997). The objectives of the second phase, which are described in this 

report, were to (1) evaluate and quantify the hydrologic 

information presented in the first phase of the study, (2) 

determine the movement and ultimate disposition of 

artificially recharged imported water, and (3) simulate 

general long-term effects on water levels likely to occur 

as a result of using three artificial-recharge alternatives 

proposed by SBVMWD. The hydrologic analysis in the 

second phase included the development and calibration 

of a ground-water flow model, which was used to simulate hydraulic heads in the Rialto–Colton Basin aquifer system. A particle-tracking post processor for the 

finite-difference flow model was used to simulate the 

movement and ultimate disposition of the artificially 

recharged imported water within the Rialto–Colton 

Basin. The flow model and post processor can provide 

useful information for evaluating the effectiveness of 

various artificial-recharge alternatives.

Description of Study Area

The 30-mi2 Rialto–Colton Basin is a northwesttrending alluvial basin in the upper Santa Ana River 

drainage area (fig. 1). The basin is about 10 mi long and 

varies in width from about 3.5 mi in the northwestern 

part to about 1.5 mi in the southeastern part. It is 

bounded on the northeast by the San Jacinto Fault, and 

on the southwest by the Rialto–Colton Fault. The San 

Gabriel Mountains and the Badlands form the northwestern and southeastern boundaries, respectively. The 

Santa Ana River cuts across the southeastern part of the 

basin. Warm and Lytle Creeks join near the southeastern boundary of the basin and then flow to meet the 

Santa Ana River near the center of the southeastern part 

of the basin. A canal that diverts water from Warm 

Creek to North Riverside Basin during 1945–55 (Steve 

Mains, Western Municipal Water District, oral commun., 1998) intersects Warm Creek within the basin 

near the San Jacinto Fault and cuts across the southeastern part of the basin in a southerly direction (fig. 2). 

Several unnamed ephemeral streams drain the San 

Gabriel Mountains in the northwestern part of the 

basin.

Historically, irrigated and nonirrigated agriculture were the main land uses in the developed part of 

the Rialto–Colton Basin. Both agricultural and urban 

development in the upper Santa Ana River drainage 

area, including the Rialto–Colton Basin, increased 

sharply during the 1940’s. In 1949, agricultural development, primarily citrus groves and vineyards, covered 

about half of the basin, and native vegetation covered 

most of the rest (Marisue Meza, SBVMWD, written 

commun., 1996). Urban development occupied only a 

small part of the basin (fig. 3). In 1957, agriculture 

began to decline. At the same time, urban development 

began to increase rapidly (California Department of 

Water Resources, 1970). In 1993, the primary land 

uses, which covered about two-thirds of the basin, were 

residential, industrial, and commercial (Marisue Meza, 

SBVMWD, written commun., 1996) (fig. 4). About 

one-third of the basin still was undeveloped and covered with native vegetation (shown as “vacant” in 

fig. 4). 

The upper Santa Ana River drainage is characterized by a warm-summer and mild-winter semiarid climate. Rainfall occurs principally from December 

through April; in summer, occasional thundershowers 

occur in the adjacent mountains. Mean annual precipitation at San Bernardino for 1871–1998 was 16.45 in. 
4 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

3Q1

29H2

29H1

3Q1 Production well and number –

Used to calculate hydraulic gradient across

the Rialto-Colton Basin

Barrier J

Fault

Fault

Fault

Rialto-Colton

Cucamonga

Fault

San Jacinto

San Andreas

Barrier E

Cajon

Creek

River

River

Cr

Warm

Santa

Santa

Ana

Ana

Cr City

Lytle

Cr

San Timoteo

Cr

Linden Ponds

Waterman

Canyon Creek

Devil

Canyon

Creek

215

15

215

10

11725' 11715' 20'

34

10'

34

05'

Unconsolidated deposits – Shaded in

 Rialto-Colton Basin

EXPLANATION

San Bernardino Mountains

0 5 KILOMETERS

0 5 MILES

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

R 4 W R 3 W R 4 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

Rialto

Colton

Los Angeles

California

San

Francisco

MAP

AREA

San Bernardino

County

Badlands

Gabriel

San

Mts

RIALTO - COLTON

BASIN

LYTLE

BASIN

BASIN

CHINO

BASIN

BUNKER

HILL

Partly consolidated deposits

Consolidated rocks

Contact

Fault – Dashed where approximately

located, dotted where concealed

Cactus

Basin

Slover Mtn

NORTH

BASIN

RIVERSIDE

Barrier H

Unnamed

Lytle

Creek

Fault

Figure 1. Location and geographic setting of the Rialto–Colton Basin, San Bernardino County, California.
Introduction 5

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin 

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Badlands

Colton

Narrows

Midvalley

landfill

RIALTO-COLTON BASIN

Cluster well site and number – Site at which one or

more wells are completed at different depths

Other well – Includes small domestic wells and observation

wells

Production well and number

Stream-gaging station and number (Station 11062001 is 1 mile

upstream from location shown)

Continuous recording

11066050 Discontinued

11059300

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Area inset 11F1-4

10H2

8E1-4

7C1

21K1-4

22N1-6

27D2-4

28J2-3

26L1

35B1-4 34D1-4

29Q1-5

11F1-4

11062001

19A1

7P3

7P2

18D1

17G1

17K1

17K2

31A1

18A1

30L1

27D1

28J1

34B2 29R15

34M1 2C1

5A3

5A2 3A1 4D2

2G1

2K1

3J1 3N2 12A1

12A2

12L1

12N1

12N1

18B1,2 18G1

18F1

18M1

18K1 17M1

2E1

Figure 2. Location of cluster sites, selected production wells, and stream-gaging stations in the Rialto–Colton Basin, San Bernardino County, 

California.
6 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

215

215

Cluster well site and number – Site at which one or

more wells are completed at different depths

Other well – Includes small domestic wells and observation

wells

Production well and number

21K11

Stream-gaging station and number

(Station 11062001 is 1 mile upstream

from location shown)

Continuous recording

11066050 Discontinued

11059300

11720' 19' 18' 11717'

3403'

3402'

11F1-4

12N1

San

Timoteo

Creek

Colton

Narrows

20H1-5

21K11

22D2, 4-7

28H1

11060400

11065000

11065801

11059300

21K1

21Q1

21Q3

28G1

28K1

28D1

28A6 29H3

28K2

27M1 27L1

21N1

29H2

28L1

11066050 28C1

21P1

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

0

0

1 KILOMETER

1 MILE

17M1

SANTA

ANA

RIVER

Warm

Creek

Lytle Creek

West Channel

Diversion

Canal

BOX SPRINGS

MTS

BADLANDS

NORTH

RIVERSIDE

BASIN

27N1

21R1

21L1

Colton

Figure 2.—Continued.
Introduction 7

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

Midvalley

landfill

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Unconsolidated deposits 

(Quaternary)

Partly consolidated deposits

(Quaternary and Tertiary)

Basement complex

(Pre-Tertiary)

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Slover

Mtn

Badlands

Colton

Narrows

San Gabriel Mountains

Land Use 1949 – Rialto-Colton Basin

Non-irrigated crops, pasture, fruits, and nuts

Irrigated crops, pasture, fruits, and nuts

Irrigated and non-irrigated citrus

Urban residential, commerical, industrial, and vacant

Native vegetation

Irrigated vineyards

 Figure 3. Land use in the Rialto–Colton Basin, San Bernardino County, California, 1949 (from Meza, M., San Bernardino Valley Municipal 

Water District, written commun., 1996).
8 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

San

Bernardino

Colton

Rialto

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Slover

Mtn

Badlands

San Gabriel Mountains

EXPLANATION

Geologic contact

Unconsolidated deposits 

(Quaternary)

Partly consolidated deposits

(Quaternary and Tertiary)

Basement complex

(Pre-Tertiary)

Land Use 1993 – Rialto-Colton Basin

Urban or built-up

Irrigated cropland and improved pasture land

Other agriculture

Vacant

Orchard and vineyards

Non-irrigated cropland and improved pasture land

Midvalley

landfill

Colton

Narrows

 Figure 4. Land use in the Rialto–Colton Basin, San Bernardino County, California, 1993 (from Meza, M., San Bernardino Valley Municipal 

Water District, written commun., 1996).
Introduction 9

(fig. 5). Extremes in precipitation include 37.08 in. in 

1884 and 5.46 in. in 1881 (National Oceanic and Atmospheric Administration, 1871–1998). A plot of the 

cumulative departure from mean annual precipitation 

(fig. 5) shows wet, dry, and average periods between 

1871 and 1998. A positive slope indicates above-average rainfall and a negative slope, below-average rainfall. Major wet periods were 1883–89, 1935–46, and 

1977–83. Major dry periods were 

1889–1904, 1947–77, and 1984–90. The dry period 

during 1984–90 was, in part, a reflection of the statewide 6-year drought that occurred during 1987–92.

Field and Analytical Methods

To gain a better understanding of the groundwater system, 11 test holes were drilled in the Rialto–

Colton Basin during 1992–94. Eight holes were drilled 

to depths of 935 to 1,000 ft and three were drilled to 

depths of 358 to 478 ft. Geophysical logs were obtained 

for all test holes. Four to six wells were completed at 

different depths in each of the eight deeper test holes, 

and one to three wells were completed in each of the 

three shallower test holes (fig. 2). During 1992–94, 

water levels in the wells were measured periodically. 

Beginning in 1996, water levels in 33 wells have been 

measured by transducers and recorded by data loggers 

at 15-minute intervals. Manual measurements are made 

every 4 to 6 weeks when the equipment is serviced. 

Water levels measured by the transducers are stored in 

the USGS’s Automated Data Processing System 

(ADAPS) data base; manual measurements are stored 

in the Ground-Water Site Inventory System (GWSI) 

data base. Water-level, borehole geophysical, and lithologic data, and analyses of these data, are reported by 

Woolfenden and Kadhim (1997).

Water was sampled at least twice at all cluster 

wells (a cluster site contains multiple wells in a borehole that are referred to as “cluster wells”) installed for 

this project during 1992–94, and analyzed for major 

ions, selected trace elements, nutrients, and the stable 

isotopes of oxygen and hydrogen (oxygen-18 and deuterium). Selected samples also were analyzed for carbon 13/14 and tritium. During 1992–95, water from 

selected production wells (fig. 2), a spring in the San 

Gabriel Mountains, Lytle Creek, and the Santa Ana 

River was sampled and analyzed for major ions, 

selected trace elements, nutrients, oxygen-18, and deuterium. Samples from six of the production wells, Lytle 

Creek, and the Santa Ana River were analyzed for tritium. Water-chemistry data and data analyses for 

1992–94 are described by Woolfenden and Kadhim 

(1997). To complete the water-chemistry data set along 

a flow path described by Woolfenden and Kadhim 

(1997), water was sampled from cluster wells 

1S/4W-20H4, 1S/4W-20H5, and 1N/5W-21K1-4 for 

carbon 13/14, and from production well 1N/5W-17K1 

for tritium in 1997.

To simulate ground-water flow in the Rialto–

Colton Basin, a modular four-layer finite-difference 

ground-water flow model was constructed using the 

FORTRAN-based modular computer code MODFLOW developed by the USGS (McDonald and Harbaugh, 1988). In this code, a governing partial 

differential equation for ground-water flow is approximated by finite-difference equations that are solved 

over a network composed of rectangular blocks (or 

cells) representing the area modeled. Solutions to the 

differential equations or the difference equations are 

hydraulic heads in the various model blocks at specific 

times. Major options required for simulation and for 

solution in the numerical model are referred to as 

“packages” (McDonald and Harbaugh, 1988, p. 3–20) 

and, for this study, include the Basic (input and output 

procedures), Block-Centered Flow, Well, Recharge, 

Evapotranspiration, and General-Head-Boundary 

packages. The preconditioned conjugate gradient 

(PCG2) solver was used for the initial-conditions simulation, and the Strongly Implicit Procedure solver was 

used for the transient simulation. The convergence criterion used for both solvers was 0.001 ft. Additional 

packages (not included by McDonald and Harbaugh, 

1988) are the Horizontal-Flow Barrier Package (Hsieh 

and Freckleton, 1993), which is used to simulate faults 

that form boundaries between components of the flow 

system, and the streamflow-routing package (Prudic, 

1989), which is used to model the interaction of the 

Santa Ana River and Warm Creek with the groundwater flow system. The stream-routing package is not a 

true surface-water flow model but rather is an accounting program that tracks the flow in one or more streams 

that interact with the ground water (Prudic, 1989).

The computer model used in this study to simulate advective transport of imported water through the 

ground-water flow system is MODPATH (Pollock, 

1994). MODPATH employs a particle-tracking technique to compute pathlines based on the results of 

MODFLOW. A complete description of MODPATH’s 
10 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

10

15

20

25

30

35

40

PRECIPITATION, IN INCHES

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

YEAR

-50

-40

-30

-20

-10

10

20

30

40

CUMULATIVE DEPARTURE FROM MEAN ANNUAL PRECIPITATION

AVERAGE

PERIOD

DRY

PERIOD

AVERAGE

PERIOD

WET DRY WET WET WET DRY

PERIOD

0

5

0

AVERAGE

PERCIPITATION

16.45 INCHES

50

 Figure 5. Annual precipitation and cumulative departure from mean annual precipitation at San Bernardino, 

California, 1871–1998.
Geohydrology 11

theoretical development, solution techniques, and limitations is given by Pollock (1994).

Acknowledgments

Special acknowledgment is given to the staff at 

San Bernardino Valley Municipal Water 

District— especially Louis Fletcher, Bob Reiter, Randy 

Van Gelder, and Sam Fuller—for their continued support for this program. Also acknowledged are Steve 

Mains from Western Municipal Water Agency for providing updated pumpage data. Babs Makinde-Odusola 

from the city of Riverside; Anthony Araiza and Manju 

Book from West San Bernardino County Water District; and Gene McMeans from Riverside-Highland 

Water Company are acknowledged for providing 

water-level data.

GEOHYDROLOGY

The geohydrology of the Rialto–Colton Basin is 

discussed in detail by Dutcher and Garrett (1963) and 

Woolfenden and Kadhim (1997). The geohydrologic 

analysis presented in these reports is summarized here 

to provide the necessary background information for 

the reader to understand the construction of the numerical model discussed in the following sections. For a 

more complete description of the geohydrology of the 

Rialto–Colton Basin, the reader is referred to these 

reports.

Stratigraphic Units

Stratigraphic units in the Rialto–Colton Basin 

are divided into four general categories: unconsolidated Quaternary alluvial deposits (Holocene and 

Pleistocene); partly consolidated Quaternary to Tertiary continental deposits (early Pleistocene to late 

Pleistocene); consolidated Tertiary continental deposits 

[Pliocene (?)]; and pre-Tertiary basement complex 

(Dutcher and Garrett, 1963). The unconsolidated alluvial deposits are composed of dune sand, river-channel 

deposits, and younger and older alluvium. The partly 

consolidated continental deposits underlie the alluvial 

deposits as lenticular bodies and crop out in the Badlands where they form the southeastern boundary of the 

Rialto–Colton Basin. These deposits also crop out at 

the base of the San Gabriel Mountains, which form the 

northwestern boundary of the basin. The consolidated 

continental deposits underlie the partly consolidated or 

alluvial deposits. The basement complex underlies the 

alluvial and continental deposits, and crops out in the 

San Gabriel Mountains (Dutcher and Garrett, 1963). 

The consolidated continental deposits and basement 

complex are considered non-water bearing and, therefore, are not part of the ground-water system. 

Description of Aquifer System

Because the stratigraphic units do not form welldefined aquifers and confining beds, the ground-water 

system was divided into water-bearing units. The division of the ground-water system into water-bearing 

units is based predominantly on analysis of lithology 

from drill cuttings and borehole geophysical logs. 

Analysis of these data is discussed in detail by 

Woolfenden and Kadhim (1997). The water-bearing 

units include the river-channel deposits, and the upper, 

middle, and lower water-bearing units. These waterbearing units may include more than one stratigraphic 

unit. Lithologic logs indicate that subsurface materials 

are largely heterogeneous alluvium that consists of various thicknesses of interbedded gravel, sand, silt, and 

clay. The resistivity logs indicate that the resistivity 

generally decreases with increasing depth. The riverchannel deposits were penetrated at only one site 

(1S/4W-20H1-5) completed during Phase 1 of this 

study. Although the lithology of the river-channel 

deposits at this site is similar to that of the upper waterbearing units, the resistivity log abruptly shifts to the 

left (indicating less resistive materials) at the contact 

between the two units (Woolfenden and Kadhim, 1997, 

p. 17). The materials composing the upper waterbearing unit are more resistive (curve shifts to the right) 

than those of the middle water-bearing unit (interbedded sand and clay). The materials composing the lower 

water-bearing unit (interbedded fine sand, silt, and 

clay) are less resistive (curve shifts to the left) than 

those composing the middle water-bearing unit 

(Woolfenden and Kadhim, 1997). 

The water-bearing units are unconfined to partly 

confined and are in hydraulic connection with each 

other. Consolidated deposits underlying the lower 

water-bearing unit form the base of the ground-water 

system. The geohydrologic sections of Woolfenden and 

Kadhim (1997) were updated and modified on the basis 

of these data and model calibration (described in the 
12 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

“Transient Simulation” section) for this report. The 

changes include a decrease in the bottom altitude of 

layer 3 in the vicinity of Barrier J and extension of the 

unnamed fault. The lines of geohydrologic section are 

shown in figure 6, and the geohydrologic sections, 

including resistivity logs, are shown in figure 7.

Water-Bearing Units

The river-channel deposits (fig. 6) underlie the 

present channels of Warm Creek and the Santa Ana 

River in the southeastern part of the basin. The northwestern boundary of the river-channel deposits trends 

from east to west across the Rialto–Colton Basin north 

of cluster site 1S/4W-20H1-5. The southeastern boundary trends from east to west south of production well 

1S/4W-27M1 (fig. 7, sections A–A′ and B–B′). These 

deposits consist of coarse sand and gravel interbedded 

with lower permeability deposits of fine sand and clay. 

Thickness of the river-channel deposits ranges from a 

feather edge to about 200 ft (fig. 4, sections A–A′,

B–B′, and F–F′. 

The upper water-bearing unit is present throughout the Rialto–Colton Basin (fig. 7, all sections). This 

unit consists of alluvial-fan deposits that grade to older 

river-channel deposits near the Santa Ana River and 

Warm Creek. The upper water-bearing unit underlies 

the river-channel deposits near the Santa Ana River and 

Warm Creek, and it is the uppermost unit throughout 

the rest of the basin. The alluvial fan deposits consist of 

coarse sand and gravel, cobbles, and boulders. The 

older river-channel deposits generally are finer grained 

than are the alluvial fan deposits. The upper waterbearing unit ranges in thickness from a feather edge in 

the northwestern part of the basin (fig. 7, sections A–A′

and B–B′) to about 300 ft (fig. 7, all sections). The 

upper water-bearing unit was unsaturated in the northwestern part of the basin during 1945–96 and was saturated in the southeastern part from the vicinity of 

production wells 1S/4W-18G1, 1S/4W-18F1, and 

1S/4W-18B2 to the southeastern basin boundary during 

the same period (fig. 2). 

The middle water-bearing unit exists throughout 

the basin and consists primarily of coarse to medium 

sand and interbedded fine sand and clay. The clay beds 

are more extensive in the northwestern part of the basin 

near the Rialto–Colton Fault. The middle waterbearing unit ranges in thickness from about 240 to 

600 ft and is thickest in the northwestern part of the 

basin southeast of Barrier J (fig. 7, all sections). The 

middle water-bearing unit is the main source of water 

to wells in the Rialto–Colton Basin (Woolfenden and 

Kadhim, 1997).

The lower water-bearing unit exists throughout 

the basin southeast of Barrier J and consists mainly of 

interbedded sand and clay. The thickness of this unit 

ranges from about 100 ft in the southeastern part of the 

basin to about 400 ft in the other parts of the basin 

(fig. 7, all sections).

Horizontal-Flow Barriers

Barrier E, the San Jacinto Fault, the Rialto–

Colton Fault, Barrier J, Barrier H, and an unnamed 

fault that subparallels the San Jacinto Fault about 1 mi 

to the southwest act as partial barriers to ground-water 

flow. Ground water may flow relatively unrestricted in 

the shallow parts of the flow system; however, the 

faults generally become more restrictive at depth. Barrier E forms the northeastern boundary of the Rialto–

Colton Basin, separating it from the Lytle Basin 

(fig. 2). Ground water flows across the section of Barrier E between Barrier J and the San Gabriel Mountains 

north of Barrier J, and to the junction of Barrier E and 

the San Jacinto Fault south of Barrier J.

The San Jacinto Fault forms the northeastern 

boundary of the Rialto–Colton Basin south of its junction with Barrier E, separating it from the Bunker Hill 

Basin (fig. 2). Ground water flows from the Bunker Hill 

Basin across the San Jacinto Fault in the vicinity of 

Warm Creek and the Santa Ana River in the riverchannel deposits and upper water-bearing unit.

The Rialto–Colton Fault forms the southwestern 

boundary, separating the basin from the Chino and 

North Riverside Basins (fig. 2). Ground water flows 

across the Rialto–Colton Fault in the southeastern part 

of the basin in the river-channel deposits and in the 

upper and middle water-bearing units, as discussed in 

the “Boundary Conditions” section of this report.

Barriers J and H were described by Dutcher and 

Garrett (1963); the extension of the unnamed fault 

north of Barrier J was described by Geosciences 

Support Services, Inc. (1992) and is referred to as “Barrier P1”; and the unnamed fault south of Barrier J was 

first described by Woolfenden (1994) and an updated 

description is given by Woolfenden and Kadhim 

(1997). The location and the extent of Barrier H and the 

unnamed fault were modified during model calibration 

as described later in the “Model Calibration” section. 

The unnamed fault was connected to “Barrier P1” for 
Geohydrology 13

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West

Channel

Flood-control

basin

(Artificial-recharge site)

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Line of geohydrologic section – Sections shown in

figure 7

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Partly consolidated deposits

(Quaternary and Tertiary)

Basement complex

(Pre-Tertiary)

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

NORTH RIVERSIDE BASIN Mts

Badlands

Colton

Narrows

San Gabriel Mountains

RIALTO-COLTON BASIN

LYTLE BASIN

Geology modified

from Morton (1974)

Unconsolidated deposits –

Shaded in Rialto-Colton Basin 

(Quaternary)

Midvalley

landfill

River-channel deposits

Diversion

canal

3A2

2E1 2G1

10H2

18B1

18F1

18M1

30L1

34M1

34B2

18A1

17G1

17K2

21L4

27M1

18M1

A A'

Production well and number

21K1-4

27D2-4

29Q1-5

29P2 28J2,3

26L1

35B1-4 34D1-4

8E1-4

11F1-4

20H1-5

20H1-5

22D2,4-7

Well cluster site with number – Site at which one or more

wells are completed at different depths

22N1-6

A

B

B'

A'

E

E'

D

D'

C

C'

F

F'

Unnamed 

Fault

Barrier H

 Figure 6. Location of cluster sites, selected production wells, and lines of geohydrologic section in the Rialto–Colton Basin, San Bernardino 

County, California.
14 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

?

?

?

?

?

?

?

?

?

B1

B2

B3

B4

N1

N2

N3

N4

N5

K1

K2

K3

K4

L1

N6

200

Sea

level

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

3,000

FEET

Barrier J

1N/5W-17G1

1N/5W-17K2

1N/5W-21K1-4

Section

C-C'

Section

D-D'

1N/5W-26L1 (Projected) 

1N/5W-35B1-4

A

1N/5W-18A1

BEND IN

SECTION

BEND IN

SECTION

LINDEN PONDS

Highland Avenue

Riverside Avenue

 1N/5W-22N1-6

15

 Figure 7. Generalized geohydrologic sections A–A′ through F–F′ in the Rialto–Colton Basin, San Bernardino County, California.
Geohydrology 15

E4

E3

E2

H2

H3

H4

H5

H1

H5

E1

?

?

?

?

?

?

?

? Unnamed fault

?

200

Sea

level

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

3,000

FEET

Section

E-E'

A'

BEND IN

SECTION 1S/4W-8E1-4

1S/4W-20H1-5 BEND IN SECTION

1S/4W-21L4 (Projected)

1S/4W-27M1

Foothill Boulevard

Warm Creek

Santa Ana River

EXPLANATION

River-channel deposits

Upper water-bearing unit

Middle water-bearing unit

Lower water-bearing unit

Consolidated deposits

Fault – Dashed where acts as 

partial barrier to ground-water flow

? Geologic contact – Dashed

where approximately located; 

queried where uncertain

Basement complex

Spontaneous potential and 

electric logs

Increasing

resistivity

- SP +

Water table, spring 1996

Well casing

Cluster well number

Production well perforated interval

0

0

2 KILOMETERS

2 MILES

VERTICAL SCALE GREATLY EXAGGERATED

10

Figure 7.—Continued.
16 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

?

?

?

?

?

F4

F3

F2

F1

Q5

Q4

Q3

Q2

P2

Q1

200

Sea

level

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

FEET

B

Section

D-D'

BEND IN

SECTION

BEND IN

SECTION

Section

C-C'

BEND IN

SECTION

BEND IN

SECTION

BEND IN

SECTION

Barrier J

Cucamonga Fault

1S/5W-11F1-4

1N/5W-29Q1-5

1S/5W-2E1

1S/5W-3A2

1N/5W-30L1

Highland Avenue

1N/5W-34M1

Foothill Boulevard

Sierra Avenue

Riverside Avenue

1N/5W-29P2

15

Figure 7.—Continued.
Geohydrology 17

H1

H2

H3

H4

H5

H5

Sea

level

200

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

FEET

Section

E-E'

B'

BEND IN

SECTION

BEND IN

SECTION 1S/4W-20H1-5

1S/4W-18M1

EXPLANATION

River-channel deposits

Upper water-bearing unit

Middle water-bearing unit

Lower water-bearing unit

Consolidated deposits

Fault – Dashed where acts as 

partial barrier to ground-water flow

? Geologic contact – Dashed

where approximately located; 

queried where uncertain

Basement complex

Spontaneous potential and 

electric logs

Increasing

resistivity

- SP +

Water table, spring 1996

Well casing

Cluster well number

Production well perforated interval

0

0

2 KILOMETERS

2 MILES

VERTICAL SCALE GREATLY EXAGGERATED

Figure 7.—Continued.
18 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

?

?

F4

F3

F2

F1

Q5

Q2

Q1

Q3

Q4

N1

N2

N3

N4

N5

N6

D3

D4

D2

D3

D2

D4

J2

J3

D1

B4

B3

B2

B1

1,000

1,200

1,400

1,600

200

200

400

600

800

Sea

level

FEET

1,000

1,200

1,400

1,600

200

200

400

600

800

Sea

level

FEET

C D D' C' 1S/5W-10H2 BEND IN SECTION 1S/5W-11F1-4 Section B-B' 1S/5W-2G1 Foothill Boulevard Highland Avenue Riverside Avenue BEND IN SECTION BEND IN SECTION Section B-B' Section A-A' Highland Avenue Riverside Avenue 1N/5W-29Q1-5 Sierra Avenue Rialto-Colton Fault Barrier H Barrier E San Jacinto Fault Rialto-Colton Fault San Jacinto Fault 1N/5W-27D2-4 1N/5W-22N1-6 BEND IN SECTION 1N/5W-34D1-4 BEND IN SECTION 1N/5W-28J2,3 BEND IN SECTION Section A-A' 1N/5W-35B1-4 Unnamed Fault Unnamed Fault

this report. These faults and barriers impede groundwater movement; however, ground water may flow 

relatively unrestricted above these faults and barriers in 

unfaulted parts of the alluvium, and to varying degrees 

across the vertical planes of these faults and barriers 

throughout their lengths.

Ground-Water Levels and Movement

Composite potentiometric contours for spring 

1945 that were constructed by Dutcher and Garrett 

(1963) were modified for this report (fig. 8). Water 

levels were measured in production wells that were perforated in more than one water-bearing unit and, therefore, represent composite water levels. Potentiometric 

contour lines modified (redrawn at a different scale) 

from Dutcher and Garrett (1963) show that ground 

water moved southward on the north side of Barrier J. 

Figure 7.—Continued.
Geohydrology 19

?

SECTIONS

A-A' AND B-B'

E4

E3

E2

E1

D2

D7

D6

D5

D4

H1

H2

H3

H4

H5

1,000

1,200

200

200

400

600

800

Sea

level

1,000

1,200

200

200

400

600

800

Sea

level

FEET FEET

E E' F F' 1S/4W-20H1-5 Warm Creek 1S/4W-22D2, 4-7 1S/4W-18M1 1S/4W-18F1 1S/4W-8E1-4 1S/4W-18B1 Lytle Creek West Channel BEND IN SECTION BEND IN SECTION Unnamed Fault Rialto-Colton Fault Rialto-Colton Fault San Jacinto Fault San Jacinto Fault

10

SECTION

B-B'

SECTION

A-A'

The potentiometric contours show that ground water 

moved southeastward from Barrier J between the San 

Jacinto Fault and the Rialto–Colton Fault, and westward and southwestward from the San Jacinto Fault 

near the Santa Ana River and Warm Creek. Data for 

1945 were not available east of the unnamed fault, and 

contour lines were not drawn in that area.

Ground-water levels in the Rialto–Colton Basin 

during 1992–98 were determined from measurements 

of static water levels in 37 cluster wells at 11 sites. 

Water-level measurements made during Phase 1 of this 

study (1992–95) indicate that ground-water movement 

in the river-channel deposits and the upper waterbearing unit generally was from northeast to southwest 

in the southeastern part of the basin in 1993 

(Woolfenden and Kadhim, 1997). Ground water flows 

across the San Jacinto Fault from the Bunker Hill Basin 

to the Rialto–Colton Basin, and across the Rialto–

Colton Fault from the Rialto–Colton Basin to the Chino 

and North Riverside Basins (Woolfenden and Kadhim, 

1997).

Ground-water movement in the middle waterbearing unit in spring 1996 generally was from northwest to southeast (fig. 9A). The potentiometric contour 

lines south of Barrier J and west of the unnamed fault 

for this period are similar to those drawn by 

Woolfenden and Kadhim (1997) for spring 1994, indicating that the direction of ground-water movement did 

not change significantly between 1994 and 1996. 

Potentiometric contours east of the unnamed fault for 

Figure 7.—Continued.
20 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Partly consolidated deposits

(Quaternary and Tertiary)

Basement complex

(Pre-Tertiary)

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

NORTH RIVERSIDE BASIN Mts

Badlands

Colton

Narrows

San Gabriel Mountains

RIALTO-COLTON BASIN

LYTLE BASIN

Geology modified

from Morton (1974)

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

(Quaternary)

Mid-valley

landfill

River-channel deposits

Well – Number indicates water-level altitude, in feet above

sea level

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Contour interval

25 feet. Datum is sea level

1,025

1,900

1,850

1,650

1,300

1,250

1,225

1,200

1,175

1,150

1,125

1,100

1,075

1,050

1,025

1,000

975

950

925

1,275

1,700

1,750

1,325

1,275

1,203

1,188

1,062

1,048 1,043

994

944

935

930 942

947

936

955

942

932

936

938

943

1,000

1,057

1,083

1658

1809

947

 Figure 8. Composite potentiometric contours and direction of ground-water movement, spring 1945, in the Rialto–Colton Basin, San 

Bernardino County, California (modified from Dutcher and Garrett, 1963).
Geohydrology 21

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site) Linden

Ponds

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Barrier H

Fault

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

NORTH RIVERSIDE BASIN Mts

Badlands

Colton

Narrows

San Gabriel Mountains

RIALTO-COLTON BASIN

LYTLE BASIN

Geology modified

from Morton (1974)

Midvalley

landfill

Cluster well – Number indicates water-level altitude, in feet above

sea level

Direction of ground-water movement

A

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 25 feet. Datum is

sea level

1,000

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Partly consolidated deposits

(Quaternary and Tertiary)

Basement complex

(Pre-Tertiary)

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

(Quaternary)

River-channel deposits

1,050

1,100

1,000

1,150

1,050

1,200

1,250

1,000

950

950

900

11F4

1,010

35B4

1,134

26L1

1,148

21K3

1,269

34D4

1,034

8E4

920

20H3

901

20H3

901

29Q4

1,055

22N3

1,264

 Figure 9. Potentiometric contours and direction of ground-water movement in the middle water-bearing unit (A), and in the lower waterbearing unit (B), spring 1996, in the Rialto–Colton Basin, San Bernardino County, California.
22 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

66

30

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

215

15

10

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto

Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

San

Bernardino

Colton

Rialto

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

NORTH RIVERSIDE BASIN Mts

Badlands

Colton

Narrows

San Gabriel Mountains

RIALTO-COLTON BASIN

LYTLE BASIN

Geology modified

from Morton (1974)

Midvalley

landfill

B

1,050

1,100

1,000

1,150

1,050

1,200

1,250

1,000

950

950

900

11F2

1,018

35B2

1,124

21K2

1,283 22N2

1,264

34D2

1,034

8E2

924

20H2

897

29Q3

1,051

Figure 9.—Continued.
Geohydrology 23

1S/5W-3A1

Middle and lower water-bearing units

Middle water-bearing unit

Middle water-bearing unit

1S/5W-12L1

B

C

1N/5W-17K1 A

1920 1930 1940 1950 1960 1970 1980 1990 2000

1920

800

850

900

950

1,000

1,050

1,100

ALTITUDE OF WATER LEVEL, IN FEET ABOVE SEA LEVEL

800

750

850

900

950

1,000

1,050

850

900

950

1,000

1,050

1,100

1,150

1930 1940 1950 1960 1970 1980 1990 2000

1920 1930 1940 1950 1960 1970 1980 1990 2000

River-channel deposits, and upper,

middle, and lower water-bearing units

1S/4W-21N1 D

800

750

850

900

950

1,000

1,050

1920 1930 1940 1950 1960

YEAR

1970 1980 1990 2000

1996 indicate greater movement (steeper gradient) of 

water across the fault than in 1994. Ground-water 

levels declined as much as 24 ft northeast of the 

unnamed fault and rose as much as 8 ft in the northwestern part of the basin. Geosciences Support Services, Inc. (1992), showed that ground water moved 

from the fractured and weathered basement complex in 

the San Gabriel Mountains and southwestward across 

Barrier E from the Lytle Basin to the Rialto–Colton 

Basin north of Barrier J. Although Barrier J impedes 

ground-water flow in the northwestern part of the 

basin, ground water can flow over the top of the barrier 

in the unfaulted part of the alluvium or where the fault 

is a less restrictive barrier. Once across Barrier J, 

ground water in the middle water-bearing unit moves 

southeastward. The unnamed fault, which subparallels 

the San Jacinto Fault, acts as a partial barrier and 

constrains ground-water movement to a narrow 

corridor between the two faults.

Ground water in the lower water-bearing unit 

also moves from the northwest to the southeast 

(fig. 9B) along the long axis of the basin. The unnamed 

fault acts as a highly restrictive barrier to ground-water 

flow in this unit (Woolfenden and Kadhim, 1997).

Long-term (1928–98) water levels in four production wells (fig. 2) are shown in figure 10. Well 

1N/5W-17K1 (fig. 2) is located northwest of Barrier J 

in a recharge area (underflow from Lytle Basin); well 

1S/5W-3A1 (fig. 2) is in the central part of the basin 

and is a key well mentioned in a 1969 Superior Court 

judgement requiring that water levels be maintained at 

specified levels (S. Fuller, SBVMWD, oral commun., 

1992); well 1S/5W-12L1 is in the southwestern part of 

the basin and also is a key well; and well 1S/4W-21N1 

is in the south-central part of the basin near the Santa 

Ana River and Warm Creek (fig. 2). Wells 1N5W17K1 and 1S/5W-12L1 are perforated exclusively in 

the middle water-bearing unit; well 1S/5W-3A1 is perforated in the middle and lower water-bearing units; 

and well 1S/4W-21N1 is perforated in all water-bearing units (Woolfenden and Kadhim, 1997).

Ground-water levels declined almost continuously in wells 1S/5W-12L1, 1S/5W-3A1, and 

1S/4W-21N1 (fig. 10) during most of a dry period during 1947–77 (fig. 5). Water levels began to recover 

before the end of the dry period probably owing to 

above-average precipitation in 1969 (fig. 5) and a 

reduction in pumpage. Water levels in well 

1S/4W-21N1 responded quickly to changes in precipitation (figs. 5 and 10) because of the well’s proximity to 

Warm Creek and the Santa Ana River. Water levels in 

well 1N/5W-17K1 did not respond to pumpage and 

recharge stresses on the ground-water system in the 

same manner as did wells southeast of Barrier J (fig. 

 Figure 10. Water-level altitude in selected production wells, 

1928–98, in the Rialto–Colton Basin, San Bernardino County, 

California.
24 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Artificial

recharge

Artificial

recharge

Artificial

recharge

1,240

1,250

1,260

1,270

1,280

1,290

1,300

1,310

1,320

1,330

1,340

1,350

1N/5W-22N1-5

22N1

22N2

22N3

22N4

22N5

Artificial

recharge

1,110

1,120

1,130

1,140

1,150

1,160

1,170

1,180

1,190

1,200

1,210

1N/5W-35B1-4

35B1

35B2

35B3

35B4

Artificial

recharge

900

910

920

930

940

950

960

970

980

990

1,000

1,010

1S/4W-8E1-4

8E1

8E2

8E3

8E4

Artificial

recharge

870

880

890

900

910

920

930

940

950

960

970

980

1S/4W-20H1-5

20H1

20H2

20H3

20H4

20H5

Imported water

detected in well

22N5

Imported water

detected in this

well

1,200

1,210

1,220

1,230

1,240

1,250

1,260

1,270

1,280

1,290

1,300

1,310

1,120

1,130

1,140

1,150

1,160

1,170

1,180

1,190

1,200

ALTITUDE OF WATER LEVEL, IN FEET ABOVE SEA LEVEL

1,210

1,220

1,230

1N/5W-21K1-4

21K1

21K2

21K3

21K4

1N/5W-26L1

26L1

A

1992 1993 1994 1995 1996

YEAR

1997 1998 1999 1992 1993 1994 1995 1996

YEAR

1997 1998 1999

 Figure 11. Water-level altitude in selected observation wells along a flowpath through Linden Ponds artificial-recharge site (A), and in 

other parts of the basin southwest of the unnamed fault (B), 1992–98, in the Rialto–Colton Basin, San Bernardino County, California.
Geohydrology 25

Artificial

recharge

Artificial

recharge

1,080

1,090

1,100

1,110

1,120

1,130

1,140

1,150

1,160

1,170

1,180

1,190

1N/5W-28J2

28J2

Artificial

recharge

1,030

1,040

1,050

1,060

1,070

1,080

1,090

1,100

1,110

1,120

1,130

1,140

1N/5W-29Q1-4

29Q1

29Q2

29Q3

29Q4

Artificial

recharge

1,000

1,010

1,020

1,030

1,040

1,050

1,060

1,070

1,080

1,090

1,100

1,110

1N/5W-34D1-4

34D1

34D2

34D3

34D4

1992 1993 1994 1995 1996

YEAR

1997 1998 1999

1992 1993 1994 1995 1996

YEAR

1997 1998 1999

ALTITUDE OF WATER LEVEL, IN FEET ABOVE SEA LEVEL

960

970

980

990

1,000

1,010

1,020

1,030

1,040

1,050

1,060

1,070

1S/5W-11F1-4

11F1

11F2

11F3

11F4

Artificial

recharge

1,120

1,130

1,140

1,150

1,160

1,170

1,180

1,190

1,200

1,210

1,220

1,230

1N/5W-27D2

27D2

Imported water

detected in this

well

B

Figure 11.—Continued.
26 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

10), indicating that the ground-water systems northwest and southeast of Barrier J are not well connected.

Water levels for 1992–98 in observation wells 

installed for this study are shown in figure 11. During 

1992–95, water levels in all wells east of the unnamed 

fault (1N5W-21K1-4, 1N/5W-22N1-5, 1N/5W-26L1, 

and 1N/5W-35B1-4) (fig. 2) responded to artificial 

recharge at Linden Ponds and recharge from Lytle 

Creek. Because artificially recharged imported water 

was detected in only two of the wells east of the 

unnamed fault (1N/5W-22N5 and 1N/5W-26L1) 

(Woolfenden, 1994), the rise in water levels in the other 

21 wells monitored probably resulted from a pressure 

response to the recharge of imported water and surface 

runoff, indicating that the ground-water system in this 

part of the basin is partly confined (Woolfenden and 

Kadhim, 1997). During 1996–98, water levels in wells 

1N/5W-21K1-4 declined rapidly but remained above 

1992 levels (fig 11). During the same period, water levels in wells 1N/5W-22N1-5 declined rapidly, reaching 

water levels similar to those in 1992 prior to artificial 

recharge; and in 1N/5W-35B1-4, water levels declined 

less rapidly than in wells 1N/5W-22N1-5 to below preartificial-recharge levels (fig. 11). Water levels in wells 

1S/4W-8E1-4 declined slowly during 1996–97, and the 

rate of decline increased slightly in 1998 (fig. 11).

During 1992–95, with the exception of well 

1N/5W-27D2 in which imported water was detected, 

water levels in cluster wells west of the unnamed fault 

showed little change (wells 1N/5W-29Q1-4, 

1N/5W-34D1-4, and 1S/5W-11F2-4 in figure 11). 

Although water levels in wells 1S/4W-20H1-5 west of 

the unnamed fault rose slightly at various times after 

artificial recharge began in 1992, it could not be determined if these water-level responses resulted from the 

1992–93 artificial-recharge period, an increase in natural recharge, and (or) a decrease in pumping 

(Woolfenden and Kadhim, 1997). During 1996–98, 

water levels fluctuated in wells 1N/5W-29Q1-4, 

1N/5W-34D1-4, and 1S/5W-11F2-4; however, the 

overall trend was upward (fig. 11). The water level in 

well 1S/5W-11F1 does not respond significantly to 

stresses on the ground-water system because it is 

perforated in the consolidated deposits, which are not 

well-connected hydraulically to the overlying units at 

this site (Woolfenden and Kadhim, 1997, fig. 11). At 

cluster site 1S/4W-20H1-5, which is southwest of the 

unnamed fault, water levels in wells, although fluctuating, showed a declining trend during 1996–97 and a rising trend in 1998 (fig. 11).

Table 1. Estimated annual recharge in the Rialto–Colton Basin, San Bernardino County, California, for various periods during 1935–96

 [Recharge values are in acre-feet; —, no estimate or data]

Recharge source

1936–49

(Dutcher and 

Garrett, 1963)

1935–60 

water years 

(California 

Department of 

Water Resources, 

1970)

1945–86

(Hardt and 

Hutchinson, 1981)

1945–96

(W.R. Danskin, 

USGS, oral commun., 1997)

1980–87

(Geosciences 

Support 

Services, Inc., 

1994)

1978–94

(Geosciences 

Support 

Services, Inc., 

1994)

1945–96 

(Woolfenden and 

Kadhim, 1997)

Underflow from 

Bunker Hill basin to 

Rialto–Colton Basin

14,300–

23,700

3,900–16,900 15,000 868–12,087 — — —

Underflow from Lytle 

Basin to Rialto–

Colton Basin

 4,000 3,700–4,200 — 500 1,493–2,274 6,800 —

Ungaged runoff

San Gabriel Mountains —————— 300–8,000 

The Badlands — — — — — — 0–1,000

Subsurface inflow 

from the San Gabriel 

Mountains

— — — — — 1,200 —

Imported water — — — — — — 0–5,345

Areal recharge of 

rainfall

— — — — — 28–21,000 —

Irrigation return flow — — — — — — 2,600–7,500
Geohydrology 27

1981198219831984198519861987198819891990199119921993199419951996

RECHARGE, IN ACRE-FEET

AVERAGE ANNUAL 

RECHARGE

2,776 ACRE-FEET

6,000

5,000

4,000

3,000

2,000

1,000

0

Recharge

The primary sources of recharge to the Rialto–

Colton ground-water system are underflow from Bunker Hill Basin across the San Jacinto Fault in the southeastern part of the basin and underflow from Lytle 

Basin across Barrier E in the northwestern part; 

ungaged runoff in small streams that drain the San 

Gabriel Mountains and the Badlands, and subsurface 

inflow from the San Gabriel Mountains; artificial 

recharge from imported water; irrigation return flow; 

seepage loss from the Santa Ana River and its tributaries, and from the diversion canal; and areal recharge of 

rainfall.

Estimates of underflow from Bunker Hill Basin 

and Lytle Basin to the Rialto–Colton Basin have been 

made by previous investigators for various time periods. Estimation methods included the use of Darcy’s 

law (Dutcher and Garrett, 1963), calibration of a 

ground-water flow model (California Department of 

Water Resources, 1970; Hardt and Hutchinson, 1980), 

and log-linear regression of estimated flows with 

water-level altitudes in a well (1S/4W-3Q1) in the Bunker Hill Basin (W. R. Danskin, USGS, written commun., 1997). Estimates of annual underflow from the 

Bunker Hill Basin to the Rialto–Colton Basin are given 

in table 1.

Several estimates of underflow from the Lytle 

Basin to the Rialto–Colton Basin across Barrier E were 

made by previous investigators. Estimation methods 

included the use of Darcy’s law (Geosciences Support 

Services Inc., 1992, 1994, and Dutcher and Garrett, 

1963), and calibration of a ground-water flow model 

(California Department of Water Resources, 1970). 

Estimates of annual underflow are given in table 1.

Estimates of ungaged runoff from the San Gabriel Mountains and the Badlands and subsurface inflow 

from the San Gabriel Mountains also are given in table 

1. Estimated ungaged runoff in the San Gabriel Mountains for 1945–94 reported by Woolfenden and Kadhim 

(1997) ranged from about 300 acre-ft in 1994 to about 

8,000 acre-ft in 1969. Estimated ungaged runoff in the 

Badlands reported by Woolfenden and Kadhim (1997) 

ranged from about 1,000 acre-ft in 1993 to no runoff 

during 1988–90. Estimated ground-water inflow from 

the San Gabriel Mountains was estimated by Geosciences Support Services, Inc. (1994), to be about 

1,200 acre-ft during 1978–94. The quantity of groundwater inflow from the Badlands has not been estimated.

The quantity of water imported for artificial 

recharge varied between 1982, when artificial recharge 

began, and 1994 (fig. 12), after which it was discontinued. During 1990–91, the total quantity of imported 

water recharged was less than 500 acre-ft (fig. 12) 

owing to a statewide drought during 1986–92. Quantities of imported water recharged ranged from 

5,345 acre-ft in 1986 to 65 acre-ft in 1990 (fig. 12).

Irrigation return flow from pumped wells is the 

quantity of pumped water that is returned to the groundwater system. Water is returned to the ground-water 

system as a result of percolation of excess water (water 

left after evaporation and transpiration) from crop irrigation and excess water from domestic or municipal 

irrigation of lawns, parks, and golf courses. Hardt and 

Hutchinson (1980) estimated excess-water return flow 

in the San Bernardino area to be 30 percent of annual 

pumpage from all sources. On the basis of reported 

annual pumpage from 1947 to 1994, annual recharge 

from irrigation return flow was estimated by Woolfenden and Kadhim (1997) to have ranged from about 

2,600 to about 7,500 acre-ft (table 1). On the basis of 

the pumpage data used for this report (described in the 

“Pumpage” section), annual recharge from irrigation 

return ranged from about 1,400 to 

5,000 acre-ft.

Areal recharge from precipitation occurs when 

rainfall infiltrates the land surface and percolates past 

the root zone to the water table; it generally is a small 

fraction of the total precipitation. Estimates of rainfall 

potentially available for recharge reported by Geosciences Support Services, Inc. (1994), range from 28 

to 21,000 acre-ft/yr during 1978–94 (table 1). Areal 

recharge was applied to the entire basin for this report. 

 Figure 12. Annual recharge of imported water in the Rialto–

Colton Basin, San Bernardino County, California, 1982–96.
28 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

AVERAGE ANNUAL

PUMPAGE

11,076 ACRE-FEET

194519501955196019651970197519801985199019952000

PUMPAGE, IN ACRE-FEET

0

5,000

10,000

15,000

20,000

YEAR

The areal recharge from precipitation estimate 

(described in the “Areal Recharge of Rainfall” section) 

for the basin is about 870 acre-ft/yr.

Seepage loss from the Santa Ana River, Warm 

Creek, and the diversion canal near Warm Creek (fig. 2) 

were not estimated by previous investigators referenced for this report. Estimates of seepage loss were 

obtained through calibration of the ground-water flow 

model described in the “Numerical Simulation of 

Ground-Water Flow” section of this report. Estimates 

made for this report are described in the “Recharge” 

subsection (“Flow-Model Construction” section).

Discharge

The major components of ground-water discharge in the Rialto–Colton Basin include pumpage; 

underflow across the Rialto–Colton Fault to the Chino 

and North Riverside Basins; evapotranspiration by 

phreatophytes along Warm Creek and the Santa Ana 

River; and seepage to the Santa Ana River and Warm 

Creek during wet years when water levels in the upper 

water-bearing unit and river-channel deposits rise 

above the base of the streambed. A major component of 

ground-water discharge for the period 1945–96 has 

been pumpage. Annual pumpage ranged from 

16,675 acre-ft in 1992 to 4,638 in 1982. Average annual 

pumpage for the period 1945–96 was 11,076 acre-ft/yr 

(fig. 13). Recent (late 1980’s to 1996) average pumpage 

was higher, about 15,000 acre-ft, owing, in part, to 

drought conditions during 1987–92. Pumpage data 

were not available for 1945–46, but pumpage is 

assumed for the purposes of this report to be equal to 

the 1947 pumpage. Values plotted in figure 13 are verified pumpages from the Watermaster at Western 

Municipal Water District (written commun., 1998). 

Pumpage data for 1947–94 given by Woolfenden and 

Kadhim (1997) included unverified data and thus 

reflect somewhat different pumpage values. Also, the 

unverified data set included diversion values during 

1945–55 that were treated separately for this phase of 

the study. Diversion values ranged from 15 acre-ft in 

1955 to 14,000 acre-ft in 1947. Estimates of underflow 

were simulated with the ground-water flow model and 

are described in the “Simulated Water Budgets” section 

of this report. Evapotranspiration by phreatophytes was 

estimated to be about 600 acre-ft/yr for 1945–96 

(Woolfenden and Kadhim, 1997). Ground water discharges to the Santa Ana River and Warm Creek when 

water-level altitudes in the aquifer underlying them 

exceed the altitudes of their streambeds. Seepage from 

the ground-water system to the Santa Ana River and 

 Figure 13. Annual pumpage in the Rialto–Colton Basin, San Bernardino County, California, 1945–96. (Data provided by the Watermaster 

at Western Municipal Water District.)
Numerical Simulation of Ground-Water Flow 29

Warm Creek is computed as part of the ground-water 

flow model. The estimates are described in the 

“Simulated Water Budgets” section of the report. 

NUMERICAL SIMULATION OF GROUND-WATER 

FLOW

Conceptual Model

The conceptual model of the Rialto–Colton 

ground-water basin is based on known and estimated 

physical and hydrologic characteristics of the groundwater flow system, and the conceptual model, in turn, 

forms the basis for the ground-water flow model. The 

physical characteristics of the study area are the boundaries of the basin (described earlier), the initial 

hydraulic-head distribution (for the transient model), 

and the types, location, and quantities of recharge and 

discharge (system stresses). Hydrologic characteristics 

simulated for the basin include those that reflect the 

ability of the system to transmit water (hydraulic conductivity and thickness); to store and release water 

(storage coefficient and specific yield); to allow for vertical passage of water between model layers (vertical 

conductance); and to control the flow of water across 

fault boundaries (hydraulic characteristic and generalhead boundary conductance).

Assumptions

A numerical model is only an approximation of 

the natural system because not all the characteristics of 

the natural system are known and can be included in 

sufficient detail for an exact representation. Simplifying assumptions are required to make the problem manageable. Some of the more important simplifying 

assumptions made for this study include:

1. The aquifer system can be represented by four layers. Each model layer corresponds to the 

water-bearing units described earlier in the 

“Description of Aquifer System” section of this 

report. 

2. The middle water-bearing unit was simulated as a 

single layer. However, two layers may be a more 

accurate conceptual representation of this part of 

the ground-water flow system. In the northwestern half of the basin south of Barrier J, a sandy 

clay unit separates the middle water-bearing unit 

into an upper member and a lower member; data 

were not available to simulate the upper member 

as a separate unit.

3. Ground-water movement within a layer is horizontal, and movement between layers is vertical. This 

assumption is a consequence of the vertical discretization used in the model (McDonald and 

Harbaugh, 1988, chap. 2, p. 31). Although 

ground-water flow generally is neither fully horizontal nor fully vertical in the actual system, this 

assumption adequately represents the large-scale 

flow regime.

4. The water-bearing layers are horizontally isotropic. 

Isotropy refers to the property of a medium to 

exhibit no directional preference in a physical 

process, such as the conductance of flowing 

water. Isotropic characteristics are difficult to 

determine in natural ground-water flow systems 

owing to the complex nature of basin geometry 

and potential for boundary effects that can mask 

isotropy or emulate anisotropy. In 1996, there 

were no data to suggest that large-scale anisotropic exist in the Rialto–Colton ground-water basin.

5. The hydraulic connection between the major waterbearing units can be simulated by assigning a vertical conductance between layers. 

6. Changes in ground-water storage in the model layers 

occur instantaneously with changes in hydraulic 

head. In most natural ground-water flow systems, 

there is a delayed response to storage changes as 

the various materials that make up a ground-water 

basin release water at differing rates.

7. Recharge from ungaged runoff and subsurface 

inflow, underflow, and imported water occurs 

instantaneously. It is assumed that recharged 

water reaches the water table in the same year in 

spite of a large unsaturated zone in some areas 

(for example, in the vicinity of Linden Ponds). In 

reality, the water may take more than a year to 

reach the water table. This assumption does not 

significantly affect model-calculated heads for 

long-term simulations.

8. Faults internal to the flow system can be simulated 

adequately by horizontal-flow barriers (Hsieh and 

Freckleton, 1993) that impede the flow of ground 

water within the Rialto–Colton Basin. Faults in 

the Rialto–Colton Basin are steeply dipping or 

vertical and are known to affect water levels and 

movement. These conditions, and the assumption 
30 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

COLUMN

ROW ROW

EXPLANATION FOR

LAYERS 1 AND 2

Model boundary

Layer boundary

(double line)

Boundary type

Flux cell

General-head cell

No flow

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

A

B

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Geologic contact

Geologic units –

See figure 2 for

explanation

?

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

Barrier H

Unnamed Fault

 Figure 14. Model grid and boundary conditions for layers 1–4 of the Rialto–Colton Basin ground-water flow 

model, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 31

C

D

Model boundary

Layer boundary

(double line)

Boundary type

Flux cell

General-head cell

No flow, bottom

boundary cell

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION FOR

LAYERS 3 AND 4

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

COLUMN

ROW ROW

No flow

Linden Ponds

Cactus

Basin

?

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

? ?

? ?

?

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Geologic units –See figure

2 for explanation

Geologic contact

0

0

3 KILOMETERS

3 MILES

Mid-valley

landfill

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

? ?

? ?

?

0

0

3 KILOMETERS

3 MILES

Unnamed Fault

Barrier H

Barrier H

Unnamed Fault

Figure 14.—Continued.
32 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

of horizontal flow (assumption number 2), conform to the criteria described by Hsieh and 

Freckleton (1993) for modeling with horizontalflow barriers.

9. Underflow from the Lytle Basin to the Rialto–

Colton Basin can be estimated as a percentage of 

discharge in Lytle Creek and can be adjusted 

through model calibration. This assumption is 

based on the water-level response to discharge in 

Lytle Creek reported by Woolfenden and Kadhim 

(1997). Data show that water levels during 

1928–96 responded quickly to peak discharges in 

Lytle Creek. 

10. Underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin can be estimated using 

Darcy’s Law. This assumption states that the 

quantity of underflow from the Bunker Hill Basin 

can be calculated using the annual spring hydraulic gradients across the southeastern part of the 

Rialto–Colton Basin, the average hydraulic conductivities of layers 1 and 2, and an estimate of the 

boundary area across which the underflow occurs.

11. Irrigation-return flow is assumed to be constant at 

30 percent of pumpage for the entire simulation 

period (1945–96). Although agricultural irrigation decreased during 1945–96, it was assumed 

that the corresponding increase in domestic and 

municipal irrigation would justify use of the same 

return-flow factor. 

12. Although the consolidated deposits are not impermeable, the quantity of water contributed by them 

is considered to be negligible. 

Flow-Model Construction

The three-dimensional finite-difference model 

MODFLOW (McDonald and Harbaugh, 1988) was 

used to simulate flow in the Rialto–Colton Basin. In 

order to numerically simulate ground-water flow in the 

aquifer system with MODFLOW, it is necessary to (1) 

divide the aquifer system into a grid, (2) determine the 

boundary conditions, (3) estimate rates and distribution 

of recharge and discharge, (4) estimate the aquifer 

properties within the model area, and (5) discretize 

time of model simulation.

Model Grid

The aquifer system is divided into four horizontal layers of square cells all with side lengths (grid 

spacing) of about 820 ft (fig. 14). There are 90 rows and 

90 columns of cells. The total number of cells is 8,100, 

and 2,768 of these represent the ground-water flow system. The grid spacing was chosen for consistency with 

an existing ground-water flow model in the adjacent 

Bunker Hill Basin (W.R. Danskin, USGS, written commun., 1997). Four layers were chosen to represent the 

four water-bearing units as described previously, and, 

because all water-bearing units are tapped by production wells, to account for pumpage from each unit. 

Layer 1 represents the river-channel deposits near the 

Santa Ana River and Warm Creek. Layer 1 consists of 

96 active cells (fig. 14A). Layer 2 represents only the 

saturated part of the upper water-bearing unit in the 

southeastern part of the basin. The upper water-bearing 

unit in the northwestern part of the basin is unsaturated. 

Layer 2 consists of 296 active cells, and underlies layer 

1 but extends beyond layer 1 to the southeastern boundary and to about one-third the length of the basin northwestward (fig. 14B). Layer 3 (middle water-bearing 

unit) is areally extensive throughout the model and 

underlies layer 2 in the southeastern one-third of the 

basin. Layer 3 is the only water-bearing layer represented northwest of Barrier J (fig. 14C) because the 

chemistry of water from well 1N/5W-17K2 northwest 

of Barrier J is similar to that of the middle waterbearing unit in the rest of the basin, and different, for 

the most part, from that of the other water-bearing units 

(Woolfenden and Kadhim, 1997). Layer 3 consists of 

1,297 active cells (fig. 14C). Layer 4 (lower waterbearing unit) is the lowermost layer south of Barrier J; 

it underlies layer 3 and consists of 1,079 active cells 

(fig. 14D). All layers have variable thicknesses. Average values for the physical and hydraulic characteristics of the aquifer system within a cell area do not vary 

within the model cell. The model calculates the average 

hydraulic head within each active cell. Model cells outside the flow system are inactive and are not assigned 

parameter values.

Boundary Conditions

No-flow, general-head, and variable-flux boundary conditions are used to simulate the aquifer system’s 

interaction with the regional flow system. No-flow 

boundaries are used around and below the modeled 

area to represent contact with segments of faults that 
Numerical Simulation of Ground-Water Flow 33

act as barriers to ground-water movement between 

basins and contact with consolidated deposits and 

rocks (fig. 14). The segments of the San Jacinto Fault 

from its junction with Barrier E (fig. 2) to the northwestern boundary of layer 1 and from the southeastern 

boundary of layer 1 to the Badlands are no-flow boundaries in all layers (fig. 14). No-flow boundary conditions were assigned to the Rialto–Colton Fault from the 

projection of the southeastern boundary of layer 1 to 

the Badlands in layer 2; from the San Gabriel Mountains to the projection of the northwestern boundary of 

layer 2, and from the projection of the southeastern 

boundary of layer 1 to the Badlands in layer 3; and 

throughout its extent in layer 4. It was assumed that the 

fault is an effective barrier to ground-water movement 

within layers 2, 3, and 4 along these segments. The top 

surface of the consolidated deposits—which underlie 

the lower water-bearing unit (layer 4) southeast of Barrier J, and the middle water-bearing unit (layer 3) 

northwest of Barrier J—forms a no-flow boundary 

between the active ground-water flow system and the 

underlying deposits (fig. 14D). 

General-head boundaries in the river-channel 

deposits and in the upper and middle water-bearing 

units where the Rialto–Colton Fault is not a barrier or a 

partial barrier to ground-water movement 

(figs. 14A–C) are used to simulate mechanisms for 

underflow from the Rialto–Colton Basin to the Chino 

and North Riverside Basins. A general-head boundary 

simulates a source of water outside the model area that 

either supplies water to, or receives water from, the 

adjacent cells at a rate proportional to the hydraulichead differences between the source and the model cell 

(McDonald and Harbaugh, 1988, p. 11-1). 

At a general-head boundary, the rate at which 

water is exchanged between the model cell and the outside source or sink is given by 

where:

Q is the rate of flow into or out of the model cell 

(L3T-1),

C is the conductance between the external source

or sink and the model cell (L2T-1),

HB is the head assigned to the external source or

sink (L), and

h is the hydraulic head within the model cell (L).

Values of C (conductance) were initially calculated from

where:

K is the hydraulic conductivity between the

model cell and the boundary head (LT-1),

W is the cell width perpendicular to flow (L),

b is the cell thickness (aquifer thickness) 

perpendicular to flow (L), and

L is the distance between the model cell center

and the specified boundary head measured

parallel to flow (L).

The boundary heads (HB) in the river-channel 

deposits and in the upper and middle water-bearing 

units are set equal to the measured water-level altitude 

at wells 1S/4W-29H2 and 1S/4W-28L1 (river-channel 

deposits and upper water-bearing unit) (table 2). Missing water-level data for the period 1945–55 for well 

1S/4W-28L1 were estimated by the linear-regression 

equation

where: 

H1 is the measured water-level altitude for well

1S/4W-29H2, and

H2 is the measured water-level altitude for well

1S/4W-28L1.

The regression relation between 1S/4W-29H2 

and 1S/4W-28L1 is shown in figure 15. The R2

 value, 

which measures the goodness-of-fit of the data for the 

regression relation, is 0.95. An R2

 value of 1.0 would 

indicate that the data were perfectly correlated. Waterlevel data also were not available for well 1S/4W-28H2 

for 1978–81. Water levels for these years were estimated from water levels in nearby well 1S/4W-29H1 

(fig. 1).

Specified-flux boundaries are used to simulate 

underflow from the Lytle Basin to the Rialto–Colton 

Basin across Barrier E in the northeast, and from the 

Bunker Hill Basin to the Rialto–Colton Basin across 

the San Jacinto Fault in the southeast (fig. 14A–C). 

Underflow occurs across Barrier E in layer 3 (middle 

water-bearing unit) both northwest and southeast of 

Barrier J (fig. 14C). Underflow occurs across the San 

Jacinto Fault between the northwestern and southeastern boundaries of layer 1 in both layer 1 (river-channel 

deposits) and layer 2 (upper water-bearing unit) 

(figs. 14A,B). Specified-flux boundaries are simulated 

in the model as injection wells with positive discharges 

Q C HB h = ( ) – ,

C KWb L = ⁄ ,

H2 1.11 = ∗H1 – 102.06,
34 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

and are input using the well package (McDonald and 

Harbaugh, 1988, p. 8-1, 8-2). Specified-flux values 

representing underflow from the Lytle Basin to the 

Rialto–Colton Basin are given in table 3, and those representing underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin are given in table 4. Values for 

underflow from the Lytle Basin were obtained from 

calibration of the ground-water flow model. Values for 

underflow from Bunker Hill Basin were obtained from 

a calculation of Darcy’s Law. These procedures are 

described further in the “Underflow” subsection 

(“Flow-Model Construction” section) of this report.

 Recharge

Recharge to the Rialto–Colton Basin includes (1) 

underflow from the Lytle and Bunker Hill Basins, (2) 

surface spreading of imported water, (3) ungaged runoff and subsurface inflow, (4) irrigation return flow, (5) 

areal recharge of rainfall, and (6) seepage loss from the 

 Table 2. Measured and estimated water-level altitudes in wells 1S/4W-29H2 and 1S/4W-28L1, San Bernardino County, California, 1945–96

[Water-level altitudes are in feet above sea level; values for 1S/4W-28L1 in italics are estimated from regression; values for 1S/4W-29H2 in bold italics are 

estimated from water-level altitudes in nearby well 1S/4W-29H1]

Year 1S/4W-29H2 1S/4W-28L1 Year 1S/4W-29H2 1S/4W-28L1 Year 1S/4W-29H2 1S/4W-28L1

1945 926.6 928.69 1965 828.0 807.26 1985 913.8 915.26

1946 926.5 928.58 1966 841.0 825.26 1986 913.2 912.26

1947 925.7 927.69 1967 857.8 858.26 1987 906.7 904.26

1948 925.5 927.47 1968 858.8 861.26 1988 897.1 907.26

1949 924.8 926.69 1969 895.8 897.70 1989 892.5 902.26

1950 919.1 920.35 1970 903.2 907.26 1990 888.8 892.26

1951 893.4 891.76 1971 890.5 892.26 1991 888.5 886.31

1952 921.9 923.46 1972 876.2 861.26 1992 894.8 893.32

1953 895.2 893.76 1973 884.2 883.26 1993 900.5 907.26

1954 904.3 903.88 1974 879.6 881.26 1994 914.1 913.26

1955 895.8 894.43 1975 879.4 876.20 1995 917.6 918.26

1956 869.7 865.39 1976 874.9 871.19 1996 897.0 895.76

1957 871.3 870.26 1977 859.5 849.26

1958 892.2 873.26 1978 934.0 936.92

1959 857.1 858.26 1979 908.1 900.26

1960 849.6 846.26 1980 912.0 899.26

1961 829.2 830.26 1981 912.0 914.26

1962 841.3 835.26 1982 912.6 906.26

1963 831.0 822.34 1983 914.0 916.26

1964 831.1 813.26 1984 914.3 915.01
Numerical Simulation of Ground-Water Flow 35

x = Water-level altitude in well 1S/4W-29H2

y = Water-level altitude in well 1S/4W-28L1

ALTITUDE OF WATER LEVEL IN WELL 1S/4W-28L1, IN FEET

ALTITUDE OF WATER LEVEL IN WELL 1S/4W-29H2, IN FEET

800

820

840

860

880

900

920

800 820 840 860 880 900 920

R 2 = 0.949

y = 1.112x - 102.0

Santa Ana River, Warm Creek, and the diversion canal. 

Quantities of imported water artificially recharged in 

spreading basins are measured values and are used 

without modification in the flow model. Underflow, 

surface spreading of imported water, and ungaged runoff and subsurface inflow are simulated as wells with 

positive flux values, and are included in the MODFLOW well package construction described in detail in 

Appendix A. The diversion canal also is simulated as 

wells with a positive flux value, but the wells were not 

included in the well package construction described in 

Appendix A.

Underflow

Underflow from the Lytle Basin to the Rialto–

Colton Basin across Barrier E was assigned to layer 3 

in the ground-water flow model. Underflow from the 

Lytle Basin was distributed to 21 cells along the extent 

of Barrier E (fig. 14C). Through model calibration, it 

was determined that 50 percent of underflow occurred 

north of Barrier J, and 50 percent occurred southeast of 

the barrier. Initial values of underflow from the Lytle 

Basin to the Rialto–Colton Basin for both the initialconditions and transient simulations were estimated by 

multiplying the measured discharge in Lytle Creek by a 

given percentage. The simulated water levels were then 

compared with measured water levels in well 

1N/5W-17K1 north of Barrier J. Underflow values 

were adjusted during model calibration until simulated 

heads matched the measured water levels reasonably 

well. Discharge in Lytle Creek was multiplied by 35 

percent for most years. During years in which measured discharge was at least two standard deviations 

above the mean (1969, 1980, 1983, and 1993), Lytle 

Creek discharge was multiplied by 15 percent. The 

model-calibrated values of underflow between the 

Lytle Basin and the Rialto–Colton Basin are given in 

table 3. This method of estimating underflow was chosen because water levels northwest of Barrier J are 

influenced, in part, by recharge from Lytle Creek. 

 Figure 15. Relation between water-level altitude in wells 1S/4W-29H2 and 1S/4W-28L1 in the Rialto–Colton Basin, San Bernardino 

County, California.
36 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Water levels in well 1N/5W-17K1 increased rapidly 

during periods of high discharge in Lytle Creek, 

remained relatively constant during periods of average 

discharge, and declined sharply during periods of low 

or no discharge (Woolfenden and Kadhim, 1997). In 

addition, the major-ion chemistry (calcium, 

magnesium, sodium, potassium, chloride, sulfate, and 

bicarbonate concentrations) and oxygen-18 and deuterium signatures in water from well 1N/5W-17K1 are 

similar to those in Lytle Creek. Detectable levels of tritium also were found in water from this well, indicating 

that water in that well is relatively recent (less than 44 

years old) (Woolfenden and Kadhim, 1997). 

Underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin was assigned to layers 1 and 2 in 

the ground-water flow model on the basis of water 

chemistry from wells adjacent to the San Jacinto Fault 

and perforated at similar depths in the Rialto–Colton 

and Bunker Hill Basins. Water from wells perforated at 

depths corresponding to layers 1 and 2 on both sides of 

the fault had similar chemistry, and water in wells perforated at depths corresponding to layer 3 did not have 

similar chemistry (Woolfenden and Kadhim, 1997). 

Water-chemistry data for layer 4 were not available for 

the Bunker Hill Basin (Woolfenden and Kadhim, 

Table 3. Underflow from the Lytle Basin to the Rialto–Colton Basin, San Bernardino County, California, 1945–96

[Underflow values are in acre-ft]

Year Above Barrier J Below Barrier J Total Year Above Barrier J Below Barrier J Total

1945 5,478 5,478 10,956 1970 3,769 3,769 7,538

1946 5,870 5,870 11,740 1971 2,972 2,972 5,944

1947 4,529 4,529 9,058 1972 2,390 2,390 4,780

1948 2,438 2,438 4,876 1973 5,138 5,138 10,276

1949 2,058 2,058 4,116 1974 4,006 4,006 8,012

1950 1,759 1,759 3,518 1975 2,739 2,739 5,478

1951 1,495 1,495 2,990 1976 2,737 2,737 5,474

1952 6,682 6,682 13,364 1977 2,609 2,609 5,218

1953 2,391 2,391 4,782 1978 9,742 9,742 19,484

1954 3,238 3,238 6,476 1979 9,048 9,048 18,096

1955 2,412 2,412 4,824 1980 8,970 8,970 17,940

1956 2,224 2,224 4,448 1981 3,015 3,015 6,030

1957 2,363 2,363 4,726 1982 6,870 6,870 13,740

1958 9,856 9,856 19,712 1983 7,993 7,993 15,986

1959 2,980 2,980 5,960 1984 4,078 4,078 8,156

1960 1,864 1,864 3,728 1985 2,833 2,833 5,666

1961 1,404 1,404 2,808 1986 4,699 4,699 9,398

1962 3,392 3,392 6,784 1987 2,412 2,412 4,824

1963 2,107 2,107 4,214 1988 2,746 2,746 5,492

1964 1,566 1,566 3,132 1989 2,009 2,009 4,018

1965 5,932 5,932 11,864 1990 1,437 1,437 2,874

1966 7,392 7,392 14,784 1991 2,942 2,942 5,884

1967 7,975 7,975 15,950 1992 7,912 7,912 15,824

1968 3,078 3,078 6,156 1993 9,225 9,225 18,450

1969 10,890 10,890 21,780 1994 2,908 2,908 5,816

1995 11,363 11,363 22,726

1996 4,278 4,278 8,556
Numerical Simulation of Ground-Water Flow 37

1997). Thus, the water-chemistry data suggest that 

underflow occurs only in layers 1 and 2. 

Underflow was distributed to 18 cells, 9 in each 

layer (figs. 14A, B). The cells in both layers lie along 

the San Jacinto Fault between the northwestern and 

southeastern boundaries of layer 1 (river-channel 

deposits). Through model calibration, it was 

determined that 75 percent of underflow came from 

layer 1 and 25 percent from layer 2. The quantity of 

underflow for both the initial-conditions and transient 

simulations was based on calculation of Darcy’s Law,

where: 

Q is the volume rate of ground-water flow (L3/t),

a is the cross-sectional area of saturated waterbearing material through which flow occurs

(L2), and 

i is the hydraulic gradient (dimensionless). 

The value of hydraulic conductivity used in the 

calculation is an average of the conductivities for layers 

1 and 2. The hydraulic gradient was calculated from 

water levels in well 1S/4W-3Q1 in the Bunker Hill 

Basin and 1S/4W-29H2 in the North Riverside Basin 

(fig. 1). As mentioned previously in the “Boundary 

Q Kai = , Conditions section,” water levels for 1978–81 were 

Table 4. Underflow from the Bunker Hill Basin to the Rialto–Colton Basin, San Bernardino County, California, 1945–96

[Underflow values are in acre-feet

Year Underflow 

layer 1

Underflow 

layer 2 Total Year Underflow 

layer 1

Underflow 

layer 2 Total 

1945 10,934 2,734 13,668 1970 5,030 1,258 6,288

1946 10,578 2,644 13,222 1971 6,495 1,624 8,119

1947 10,413 2,603 13,016 1972 7,981 1,995 9,976

1948 10,429 2,607 13,036 1973 7,657 1,914 9,571

1949 10,343 2,586 12,929 1974 8,004 2,001 10,005

1950 10,288 2,572 12,860 1975 7,862 1,966 9,828

1951 11,889 2,972 14,861 1976 8,359 2,090 10,449

1952 9,429 2,357 11,786 1977 10,253 2,563 12,816

1953 11,116 2,779 13,895 1978 5,347 1,337 6,684

1954 10,060 2,515 12,575 1979 8,920 2,230 11,150

1955 10,509 2,627 13,136 1980 9,543 2,386 11,929

1956 12,213 3,053 15,266 1981 9,969 2,492 12,461

1957 11,148 2,787 13,935 1982 10,142 2,536 12,678

1958 9,665 2,416 12,081 1983 9,643 2,411 12,054

1959 12,008 3,002 15,010 1984 12,331 3,083 15,414

1960 12,426 3,106 15,532 1985 8,766 2,192 10,958

1961 13,198 3,300 16,498 1986 7,748 1,937 9,685

1962 10,860 2,715 13,575 1987 8,175 2,044 10,219

1963 11,183 2,796 13,979 1988 7,761 1,940 9,701

1964 10,500 2,625 13,125 1989 7,368 1,842 9,210

1965 10,316 2,579 12,895 1990 7,577 1,894 9,471

1966 8,581 2,145 10,726 1991 7,149 1,787 8,936

1967 7,137 1,784 8,921 1992 6,915 1,729 8,644

1968 7,571 1,893 9,464 1993 6,925 1,731 8,656

1969 5,245 1,311 6,556 1994 5,817 1,454 7,271

1995 5,872 1,468 7,340

1996 7,643 1,911 9,554
38 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Layer 1

Layer 2

EXPLANATION FOR

LAYER 1 AND 2

Model boundary

Layer boundary

(double line)

Pumpage cell

Irrigation canal cell

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

COLUMN

ROW ROW

? Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

0

0

3 KILOMETERS

3 MILES

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

Barrier H

Unnamed Fault

0

0

3 KILOMETERS

3 MILES

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

Barrier H

Unnamed Fault

 Figure 16. Model grid and areal distribution of pumpage, irrigation canal, and artificial-recharge cells for 
Numerical Simulation of Ground-Water Flow 39

Layer 3

Layer 4

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION FOR

LAYER 3 AND 4

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Model boundary

Layer boundary

(double line)

Pumpage cell

Artificial-recharge cell

COLUMN

ROW ROW

? Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Figure 16.—Continued.
40 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

estimated from water levels in nearby well 

1S/4W-29H1 (fig. 1). In 1984, water-level data were 

not available for 1S/4W-3Q1; consequently, underflow 

was estimated to be 35 percent of discharge in the 

Santa Ana River. Estimates of underflow from the Bunker Hill Basin are given in table 4.

Surface Spreading of Imported Water

Recharge from surface spreading of imported 

water at Linden Ponds was assigned to layer 3 in the 

ground-water flow model. This quantity was distributed equally between two cells (fig. 16) and was simulated using the well package (McDonald and 

Harbaugh, 1988, p. 8-1,8-2). Imported water recharged 

during 1982–96 is a known quantity (table 5) and 

therefore was not modified during model calibration. 

An estimate of the time it takes for the imported water 

to move vertically to the water table can be made using 

the vertical hydraulic conductivity, the porosity of 

layer 3, and the distance from land surface to the water 

table. The horizontal hydraulic conductivity used in the 

model is described in the “Hydraulic Conductivity” 

section of this report, and the vertical hydraulic conductivity is described in the “Vertical Conductance” 

section of this report. The vertical hydraulic conductivity is estimated to be about 0.1 times the horizontal 

hydraulic conductivity (Heath, 1983). The horizontal 

hydraulic conductivity at Linden Ponds is 

0.0005787 ft/s; hence the vertical hydraulic conductivity is 0.00005787 ft/s. The porosity for layer 3 (0.30) 

was estimated on the basis of stable-isotope data and is 

described in the “Simulated Effects of ArtificialRecharge Alternatives on Ground-Water Levels and 

Movement” section. The distance to the water table was 

about 300 ft in spring 1996 (fig. 7). Thus, the time it 

takes for the imported water to reach the water table is 

calculated by [330 ft/(0.30*0.00005787 ft/s)]/(86,400 

s/d), which equals about 220 days. This value was not 

used in the model explicitly; however, it is assumed that 

artificially recharged water reaches the water table in 

the same year in which recharge occurs. A clay lens 

about 360 ft below land surface impedes the farther vertical movement of the imported water (Woolfenden, 

1994; Woolfenden and Kadhim, 1997). 

 Ungaged Runoff and Subsurface Inflow

Ungaged runoff and subsurface inflow were simulated using the well package, and quantities of inflow 

were assigned to layer 3 at the base of the San Gabriel 

Mountains in the northwestern part of the model grid 

and to layer 2 at the base of the Badlands in the southeastern part of the model grid (fig. 14). The quantity of 

ungaged surface runoff is a function of the drainage 

areas for the small creeks and the mountain fronts. Estimates of ungaged runoff can be calculated by multiplying these drainage areas by a unit discharge value 

obtained from a gaged creek draining the same mountains (J.C. Bowers, USGS, oral commun., 1994). Discharge values from Lytle Creek and San Timoteo Creek 

were used to obtain the unit discharges for the San Gabriel Mountains and the Badlands, respectively. 

Ungaged runoff and subsurface inflow from the San 

Gabriel Mountains were distributed equally to 17 cells. 

Ungaged runoff and subsurface inflow from the Badlands were distributed equally to two cells (fig. 14B). 

Estimates made by Woolfenden and Kadhim (1997) for 

ungaged runoff were used in the model and are given in 

table 6. Subsurface inflow from the Gabriel Mountains 

was reported by Geosciences Support Services, Inc. 

(1994), to be 1,200 acre-ft/yr for the period 1978–93, 

and this value was used in the model. Subsurface inflow 

from the Badlands was assumed to be negligible and 

was not modeled. Quantities of ungaged runoff and 

subsurface inflow were not adjusted during model 

calibration. 

Table 5. Quantities of imported water artificially recharged at Linden 

Ponds, San Bernardino County, California 1982–96 

[Quantities are in acre-feet]

Year Artificial-recharge quantity

1982 3,220

1983 4,736

1984 3,471

1985 3,879

1986 5,345

1987 3,030

1988 4,601

1989 4,522

1990 65

1991 435

1992 1,559

1993 3,747

1994 261

1995 0

1996 0
Numerical Simulation of Ground-Water Flow 41

Irrigation Return Flow

Irrigation return flow is the quantity of total 

pumpage returned to the aquifer. Water is returned as a 

result of percolation from agricultural irrigation and 

from some domestic and municipal uses. Irrigation 

return flow in the Rialto–Colton Basin was estimated to 

be 30 percent of total pumpage for each well on the 

basis of the ground-water flow model for the Bunker 

Hill Basin (Hardt and Hutchinson, 1980; W.R. 

Danskin, USGS, oral commun., 1994). Irrigation return 

flow was accounted for in the model by reducing 

pumpage by 30 percent. This method of return-flow 

computation does not imitate the actual process. 

Ground water is pumped from the different waterbearing units (layers) within the basin, whereas return 

flow occurs only in the uppermost unit. However, in the 

Rialto–Colton Basin, the middle water-bearing unit 

(layer 3) is the uppermost saturated unit throughout 

nearly two-thirds of the basin and also is the main 

water-producing unit in the basin (Woolfenden and 

Kadhim, 1997). In a simplification of the actual process, the return flow factor of 30 percent is held constant throughout the model simulation period 

(1945–96). Land use gradually changed from agricultural to urban between 1949 and 1993 (figs. 3 and 4), 

and the assumption that irrigation return from watering 

lawns, golf courses, parks, and other such areas would 

be approximately the same percentage as that from irriTable 6. Ungaged runoff from the San Gabriel Mountains and the Badlands, San Bernardino County, California, 1945–96

[Recharge values are in acre-feet]

Year San Gabriel Mountains The Badlands Total Year San Gabriel Mountains The Badlands Total

1945 1,733 88 1,821 1971 940 32 972

1946 1,857 44 1,901 1972 756 2 758

1947 1,433 7 1,440 1973 1,626 125 1,751

1948 771 8 779 1974 1,267 31 1,298

1949 651 4 655

1975 866 26 892

1950 556 6 562 1976 866 41 907

1951 473 6 479 1977 825 38 863

1952 2,114 176 2,290 1978 7,192 370 7,562

1953 756 3 759 1979 2,862 295 3,157

1954 1,024 78 1,102

1980 6,622 728 7,350

1955 763 10 773 1981 954 40 994

1956 704 17 721 1982 2,174 143 2,317

1957 747 6 753 1983 5,900 519 6,419

1958 3,118 115 3,233 1984 1,290 59 1,349

1959 943 5 948

1985 896 29 925

1960 590 3 593 1986 1,487 75 1,562

1961 444 19 463 1987 763 5 768

1962 1,073 29 1,102 1988 869 0 869

1963 667 4 671 1989 636 0 636

1964 496 4 500

1990 455 0 455

1965 1,877 170 2,047 1991 931 14 945

1966 2,339 279 2,618 1992 2,451 61 2,512

1967 2,523 65 2,588 1993 6,251 985 7,236

1968 974 26 1,000 1994 266 78 344

1969 8,039 716 8,755 1995 2,872 641 3,513

1970 1,193 56 1,249 1996 1,353 92 1,445
42 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

COLUMN

ROW

 Recharge Layers 1, 2, 3

Layer 1

Layer 2

EXPLANATION

Model boundary

Layer boundary

(double line)

Recharge

Recharge from rainfall

infiltration cell

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Layer 3

Layer 2

? Fault – Dashed where

 approximately located;

 dotted where concealed;

 queried where doubtful

0

0

3 KILOMETERS

3 MILES

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

Barrier H

Unnamed Fault

gating orange groves (the main agricultural land use in 

1949) may be overstated. 

Areal Recharge of Rainfall

Direct infiltration of precipitation is simulated as 

areal recharge. Areal recharge was assigned to the 

uppermost active layer in the model (fig. 17) and was 

distributed equally to all recharge cells in the model 

grid. The rate of areal recharge assigned to each 

recharge cell was 1.38 × 10-9 ft/s (0.5 in/yr; a total of 

about 870 acre-ft/yr for the basin); this rate is based on 

a calibrated ground-water flow model for the adjacent 

Bunker Hill Basin (Hardt and Hutchinson, 1980). Areal 

recharge from rainfall was assumed constant with time.

Seepage Loss from the Santa Ana River, 

Warm Creek, and the Diversion Canal

Stream recharge was assigned to layer 1 in the 

model to cells along the Santa Ana River and Warm 

Creek (fig. 18), and was simulated using a model package that simulates interaction between the stream and 

the aquifer (Prudic, 1989, p. 1–11). Model input 

included stream discharge into the basin, stream width, 

altitudes of the top and bottom of the streambed, stream 

stage, and stream conductance. Discharge quantities 

used in the flow model are measured values and are 

given by Woolfenden and Kadhim (1997). Stream 

width was assumed to be the width of one cell (about 

820 ft). The top altitude of the streambed was assumed 

to be the land-surface altitude at the stream, and the 

bottom altitude was assumed to be 5 ft lower than the 

top altitude. The stream stage was assumed to be 5 ft 

higher than the top altitude of the streambed (landsurface altitude plus 5 ft). The stream conductance was 

 Figure 17. Model grid and areal distribution of recharge from rainfall infiltration cells for layers 1–3 of the 

Rialto–Colton Basin ground-water flow model, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 43

Layer 1

EXPLANATION

Model boundary

Layer boundary

(double line)

Evapotranspiration cell

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Stream cell

COLUMN

ROW

? Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

0

0

3 KILOMETERS

3 MILES

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

Barrier H

Unnamed Fault

assumed to be 0.1 ft2/s. These values correspond to 

those determined from a calibrated flow model for the 

adjacent Bunker Hill Basin (W.R. Danskin, USGS, oral 

commun., 1994) and were not modified during model 

calibration.

Water was diverted from Warm Creek into an 

irrigation canal (fig. 2) during 1945–55. The canal has 

an unlined channel, and seepage was simulated as a 

series of wells (fig. 16) with a positive flow rate. The 

percentage of seepage loss in the canal was assumed to 

be the same as the percentage of seepage loss in Warm 

Creek and the Santa Ana River. Quantities of seepage 

loss were determined by computing a ratio between the 

model-generated seepage loss in Warm Creek and the 

Santa Ana River, and total inflow from both sources. 

The ratio did not vary significantly during 1945–55, 

and the 1945 value was used for the entire period. The 

measured quantity of water diverted from Warm Creek 

is multiplied by the computed ratio (10 percent) to 

determine seepage loss. The quantity of seepage loss 

from the canal simulated in the ground-water flow 

model ranged from 1,978 acre-ft in 1948 to 3 acre-ft in 

1955 (table 7).

 Discharge

The primary components of ground-water discharge from the aquifer system are (1) pumpage, (2) 

underflow from the Rialto–Colton Basin to the Chino 

Basin, (3) evapotranspiration from bare soil and of 

phreatophytes along the Santa Ana River and Warm 

Creek, and (4) seepage loss from the aquifer to the 

Santa Ana River and Warm Creek. Seepage loss from 

the aquifer to the Santa Ana River and Warm Creek was 

simulated in the same manner as discussed in the 

“Recharge” subsection (“Flow-Model Construction” 

section) for seepage from the Santa Ana River and 

Warm Creek to the aquifer and is not discussed in this 

 Figure 18. Model and areal distribution of stream and evapotranspiration cells for layer 1 of the Rialto–Colton 

Basin ground-water flow model, San Bernardino County, California.
44 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

section. The values of stream discharge into the basin, 

stream width, top and bottom altitudes of the 

streambed, stream stage, and stream conductance are 

the same as those discussed in the previous section.

Pumpage

Ground-water pumpage is a major discharge in 

the Rialto–Colton Basin. A total of 47 wells were 

pumped at some time during the period 1945–96 

(fig. 16). Pumpage from individual wells in the 

Rialto–Colton Basin has been reported to and verified 

by the Santa Ana River Watermaster since 1947, and is 

managed by the Western Municipal Water District. 

Because land-use and hydrologic conditions during 

1945–46 were similar to those of 1947, pumpage for 

 Table 7. Seepage loss in the diversion canal, San Bernardino 

County, California, 1945–55

[Quantities are in acre-feet]

Year Seepage loss

1945 1,123

1946 1,260

1947 1,404

1948 1,978

1949 1,326

1950 1,116

1951 669

1952 230

1953 378

1954 132

1955 3

 Table 8. Annual total and net pumpage from the Rialto–Colton Basin, San Bernardino County, California, 1945–96

[Pumpage values are in acre-feet; net pumpage values equal total pumpage minus irrigaton return flow]

Year Total Pumpage Net Pumpage Year Total Pumpage Net Pumpage

1945 6,791 4,754 1970 11,469 8,028

1946 6,791 4,754 1971 11,293 7,905

1947 6,791 4,754 1972 10,319 7,223

1948 6,630 4,641 1973 7,763 5,434

1949 9,400 6,580 1974 8,817 6,172

1950 10,496 7,347 1975 11,002 7,701

1951 12,995 9,096 1976 11,470 8,029

1952 9,093 6,365 1977 8,688 6,082

1953 12,672 8,870 1978 7,571 5,300

1954 11,416 7,991 1979 7,103 4,972

1955 10,242 7,169 1980 5,595 3,916

1956 12,839 8,987 1981 6,237 4,366

1957 12,018 8,413 1982 6,402 4,481

1958 12,122 8,485 1983 4,638 3,247

1959 13,092 9,164 1984 8,892 6,224

1960 11,244 7,871 1985 10,051 7,036

1961 14,471 10,130 1986 9,932 6,952

1962 10,580 7,406 1987 13,085 9,160

1963 9,732 6,812 1988 14,076 9,853

1964 13,029 9,120 1989 15,526 10,868

1965 13,186 9,230 1990 17,551 12,286

1966 13,684 9,579 1991 14,244 9,971

1967 11,543 8,080 1992 16,675 11,672

1968 14,184 9,929 1993 14,892 10,424

1969 11,729 8,210 1994 14,227 9,959

1995 15,922 11,145

1996 15,758 11,031
Numerical Simulation of Ground-Water Flow 45

1945–46 was assumed to be the same as that of 1947. 

Reported and estimated annual (total and net) pumpage 

values are given in table 8. 

Net pumpage is used in the model and was not 

modified during calibration. Irrigation return flow is 

accounted for in the model by calculating net pumpage 

(the total pumpage minus the quantity of water that is 

returned to the system). As stated in the “Irrigation 

Return Flow” section of this report, the return-flow factor is 30 percent, and net pumpage values are, therefore, 70 percent of total pumpage values.

Pumpage is assigned to layers on the basis of the 

length of the perforated interval of a well within a given 

water-bearing unit and the hydraulic conductivity of 

that water-bearing unit. ARC/INFO AML (Arc Macro 

Language) programs were developed to compute net 

pumpage from total pumpage and to assign net pumpage to individual model layers (the water-bearing unit 

and designated layers described in the “Model Grid” 

section), and to create MODFLOW-readable well 

packages (see Appendix A). ARC/INFO is a geographic information system from Environmental 

Systems Research Institute, Inc. (ESRI), of Redlands, 

California. 

The AML programs assign pumpage vertically 

using top and bottom altitudes of perforated intervals, 

land-surface altitudes, top and bottom altitudes of 

model layers, and the hydraulic conductivity of the 

model layer to calculate the percentage of pumpage 

contributed by each layer. Percentages calculated by 

the ARC/INFO programs are given in table 9. The vertical pumpage distribution is computed by multiplying 

the net pumpage for a well by the percentages mentioned above. The method is described by

q(net)=q(n) * pcnt_ir / 100,

q(n) = QT * pcnt(n), and

pcnt(n)=

[L(n)*k(n)][L(1)*k(1)+L(2)*k(2)+...+L(n)*k(n)],

where:

q(n) is the total pumpage assigned to model 

layer n (ft3/s),

n is the model layer number,

pcnt_ir is the irrigation efficiency (the remainder 

is the return flow),

QT is the total pumpage of a given well (ft3/s),

pcnt(n) is the percentage of total pumpage assigned

to layer n,

L(n) is the length of perforated interval of a well

in model layer n (ft), and

k(n) is the hydraulic conductivity in model layer 

n (ft/s).

Total pumpage for reported years 1945–96 is 

computed as

QT = [Yr * -0.0013813 (ft3/s)/acre-ft]* (pcnt_qt / 100),

where:

Yr is the total pumpage of well (acre-ft) and

pcnt_qt is the percentage of pumpage to be used 

in the model run.

Total pumpage for the predictive simulation (1997–

2027) is computed as

QT = [Yr * -0.0013813 (ft3/s)/acre-ft] * (pcnt_qt / 100),

where the variables are as defined above. 

Where construction data are not available or the 

hydrologist has better knowledge of the contributing 

model layer, pumpage is assigned vertically in the following manner. If perforated-interval data are not available but well depth is known, pumpage is evenly 

distributed to each layer the well intersects. Where no 

well-construction data are available, the pumpage is 

assigned on the basis of construction data for nearby 

wells or on the basis of knowledge of the basin hydrogeology. These model-layer designations are entered 

into the ARC/INFO data base and remain unchanged 

during operation of the AML programs (see Appendix 

A). 

Underflow

Underflow from the Rialto–Colton Basin to the 

Chino and North Riverside Basins was assigned to layers 1, 2, and 3, with 7 cells in layer 1, and 21 cells each 

in layers 2 and 3 (figs. 14A–C). As mentioned previously, the effect of underflow is simulated using the 

general-head boundary package. Input to the package 

are head (described in the “Boundary Conditions” section) and conductance. Conductance values were determined during model calibration. For layer 1, the 

conductance values are 0.05 ft2/s. For layers 2 and 3, 

the conductance values are 0.04 ft2/s (fig. 14C). On the 

basis of water levels measured in the Rialto–Colton 

Basin (for example, in wells 1S/4W-20H3-5), waterlevel differences between layers 1, 2, and 3 typically 

are less than 10 ft.
46 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Table 9. Percent of pumpage from each layer for production wells in the Rialto–Colton Basin, San Bernardino County, California

[—, well not screened in layer]

State well

number 

Percent

layer 1 

Percent 

layer 2 

Percent

layer 3 

Percent

layer 4

1N/5W-7P2 — — 100 —

1N/5W-7P3 — — 100 —

1N/5W-18D1 — — 100 —

1N/5W-17G1 — — 100 —

1N/5W-17K1 — — 100 —

1N/5W-17K2 — — 100 —

1N/5W-30A1 — — 50 50

1N/5W-27D1 — — 88 12

1N/5W-28J1 — — 42 58

1N/5W-29R15 — — 50 50

1N/5W-34B1 — — 58 42

1N/5W-34M1 — — 60 40

1S/5W-2C1 — — 55 45

1S/5W-2E1 — — 51 49

1S/5W-2G1 — — 46 54

1S/5W-2K1 — — 71 29

1S/5W-3A1 — — 79 21

1S/5W-3J1 — — 89 11

1S/5W-3N2 — — 95 5

1S/5W-4D2 — — 100 —

1S/5W-5A2 — — 50 50

1S/5W-5A3 — — 84 16

1S/5W-12A1 — — 50 50

1S/5W-12A1 — — 50 50

1S/5W-12L1 — — 100 —

1S/5W-12N1 — — 99 1

1S/4W-7C1 — — 100 —

1S/4W-17M1 — 54 46 —

1S/4W-18B1 — 29 71 —

1S/4W-18F1 — 2 77 21

1S/4W-18G1 — — 96 4

1S/4W-18K1 — — — 100

1S/4W-21K1 — 38 50 12

1S/4W-21L1 41 46 13 —

1S/4W-21N1 54 20 21 5
Numerical Simulation of Ground-Water Flow 47

Evapotranspiration

Evapotranspiration is assigned to all cells in 

layer 1 (fig. 18). The land-surface altitude, evapotranspiration rate, and extinction depth are data needed for 

the evapotranspiration package in the model 

(McDonald and Harbaugh, 1988, p. 10-1–10-7). The 

land-surface altitude for layer 1 was estimated from a 

digital elevation model (DEM). The evapotranspiration 

rate used in the model is 1.39 X 10-13 ft3

/s and the 

extinction depth is 15 ft. The basis for these assigned 

values is their use in the calibrated ground-water flow 

model for the adjacent Bunker Hill Basin (W. R. 

Danskin, USGS, oral commun., 1994). 

Flow Barriers 

Barrier J, the unnamed fault, and Barrier H are 

modeled as horizontal-flow barriers using the HFB 

(horizontal-flow barrier) package (Hsieh and 

Freckleton, 1993). Conceptually, a horizontal-flow barrier is a thin, vertical low-permeability feature, such as 

a fault. In the model, the feature is simulated as a series 

of horizontal-flow barriers situated on the boundary 

between pairs of adjacent cells (each relevant cell 

boundary is a “barrier” in the HFB package). The 

barrier effect is determined by the “hydraulic characteristic,” which is defined to be the hydraulic conductivity 

divided by the barrier width (Hsieh and Freckleton, 

1993). The smaller the hydraulic characteristic, the 

more effective the barrier is to ground-water 

movement. 

The distribution of horizontal-flow barriers in 

the Rialto–Colton Basin and their hydraulic characteristics are shown in figure 19. Barrier J is modeled only 

in layer 3. Both the unnamed fault and Barrier H are 

modeled in layers 3 and 4. Hydraulic characteristics for 

all flow barriers were adjusted during both model calibrations. Barrier J has three segments of varying 

hydraulic characteristics. The hydraulic characteristic 

assigned to Barrier J east of the unnamed fault is 

smaller than that west of the fault to enable matching of 

simulated heads with measured water-level altitudes 

and to restrict the quantity of water flowing into the 

corridor between the unnamed fault and the San Jacinto 

Fault southeast of Barrier J. The hydraulic characteristic of the unnamed fault northwest of Barrier J is larger 

than that of the fault southeast of Barrier J, indicating 

that this segment of the unnamed fault is a less effective 

barrier than are the other segments. Southeast of Barrier J, the hydraulic characteristic of the northern half 

of the unnamed fault is lower than that of the southeastern half to better match simulated heads to measured 

water-level altitudes in the corridor between the 

unnamed fault and the San Jacinto Fault. The hydraulic 

characteristic of the unnamed fault in layer 4 is smaller 

than that for layer 3 for both the northern and southern 

segments. This is consistent with the results from analysis of stable-isotope data by Woolfenden and Kadhim 

(1997) that indicate greater mixing of water northeast 

1S/4W-21P1 100 — — —

1S/4W-21Q1 52 38 10 —

1S/4W-21Q3 — 85 15 —

1S/4W-27L1 — 44 56 —

1S/4W-27M1 — 24 68 9

1S/4W-28A6 32 68 — —

1S/4W-28C1 23 42 34 —

1S/4W-28D1 7 66 27 —

1S/4W-28G1 98 2 — —

1S/4W-28K1 68 24 8 —

1S/4W-28K2 93 7 — —

1S/4W-29H3 90 10 — —

State well

number 

Percent

layer 1 

Percent 

layer 2 

Percent

layer 3 

Percent

layer 4

Table 9. Percent of pumpage from each layer for production wells in the Rialto–Colton Basin, San Bernardino County, California—Continued
48 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Layer 3

Layer 4

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION FOR

LAYERS 3 AND 4

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Model boundary

Layer boundary

(double line)

COLUMN

ROW ROW

Flow barrier – Number

indicates the hydraulic

characteristic of the

fault segment, in feet

per second

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Line dividing fault 

segments

?

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

1.0 X 10

1.0 X 10

5.0 X 10-10

9.0 X 10-9

7.5 X 10-9

-7

1.0 X 10-12

2.5 X 10-10

-9

9.0 X 10 -10

1.0 X 10 -10

1.0 X 10 -12

 Figure 19. Model grid and areal distribution of flow barriers for model layers 3 and 4 of the Rialto–Colton 

Basin ground-water flow model, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 49

of the unnamed fault with water southwest of the 

unnamed fault in layer 3 than in layer 4. Barrier H has 

the smallest hydraulic characteristic of any fault within 

the basin.

Aquifer Properties

Aquifer properties used in the model include 

hydraulic conductivity, aquifer thickness, vertical 

leakance, storage coefficient, and specific yield. 

Hydraulic conductivity and top and bottom altitudes of 

each layer were used in this model so that transmissivity (hydraulic conductivity times saturated thickness) 

may be recalculated at each iteration as hydraulic heads 

change. Recalculating the transmissivity at each iteration, along with the potential for storage-term conversions, allows simulation of changes between confined 

and unconfined conditions. Confined conditions may 

be simulated when the hydraulic head rises above a 

confining unit, and aquifer thickness is used to calculate transmissivity. Conversely, unconfined conditions 

may be simulated when hydraulic heads decline below 

the bottom of the confining unit, and the saturated 

thickness (the difference between simulated watertable surface and bottom altitude of the water-bearing 

unit) is used to calculate transmissivity. In this model, 

layer 1 is always unconfined, and layers 2 and 3 are 

allowed to convert back and forth from confined to 

unconfined conditions and allowed to rewet cells that 

have gone dry in the previous iterations. Layer 4 is 

strictly confined.

Hydraulic Conductivity

Hydraulic conductivity refers to the watertransmitting characteristic of a material in quantitative 

terms (Heath, 1983). Hydraulic conductivity multiplied 

by the saturated thickness of the aquifer equals the 

transmissivity (the capacity of an aquifer to transmit 

water of the prevailing kinematic viscosity) (Heath, 

1983) and is used by MODFLOW in both the initialcondition and transient-state ground-water flow 

simulations. 

The distribution of hydraulic conductivity for 

layers 1–4 is shown in figure 20. A constant value of 

0.0015 ft/s (130 ft/d) was assigned to layer 1 (fig. 20A). 

This value is based on a description of river-channel 

deposits by Dutcher and Garrett (1963) and on 

hydraulic-conductivity values for geologic materials 

reported by Freeze and Cherry (1979). 

A constant hydraulic-conductivity value of 

0.0039 ft/s (337 ft/d) was assigned to layer 2 (fig. 20B). 

This value is based on hydraulic conductivities 

reported by Dutcher and Garrett (1963) for younger 

alluvium, which probably approximates the upper 

water-bearing unit, and hence, layer 2. 

Hydraulic-conductivity values for layer 3 varied 

throughout the basin (fig. 20C). Hydraulicconductivity values range from 0.0001547 ft/s (13 ft/d) 

southwest of the unnamed fault northwest of Barrier J 

to 0.0009259 ft/s (80 ft/d) southeast of Barrier J. The 

hydraulic-conductivity values southeast of Barrier J 

were reported by Geosciences Support Services, Inc. 

(1994), and are based on calculations using specific 

capacities, saturated thickness, and a constant (2,000, 

in this case) that accounts for the storage coefficient 

and transmissivity of the aquifer at the well, effective 

radius of the well, and duration of the specific-capacity 

test (Heath, 1983, p. 61) for selected wells in the 

Rialto–Colton Basin. The hydraulic-conductivity value 

northeast of the unnamed fault north of Barrier J 

(0.0001736 ft/s [15 ft/d]) is reported by Dutcher and 

Garrertt (1963). The value assigned to cells southwest 

of the unnamed fault was slightly lower 

(0.0001547 [13 ft/d]) to account for different aquifer 

materials farther west of Lytle Creek.

Hydraulic-conductivity values for layer 4 varied 

throughout the basin (fig. 20D). Hydraulicconductivity values range from 0.0001010 ft/s (9 ft/d) 

to 0.0002314 ft/s (20 ft/d). No information or data were 

available for the hydraulic conductivity of layer 4 

(lower water-bearing unit). The hydraulicconductivity values were estimated to be one-fourth 

those of layer 3, which are consistent with those for the 

finer grained (silty sand) material (Freeze and Cherry, 

1979) present in the lower water-bearing unit.

Aquifer Thickness

Aquifer thickness is the difference between the 

top and bottom altitudes of a water-bearing unit under 

confined conditions, and the water table and the bottom 

of the unit for unconfined conditions. Aquifer thickness 

is used to calculate transmissivity under confined conditions. The aquifer thickness distributions for layers 

1–4 during initial conditions are shown in figure 21. 

Thicknesses were determined from altitudes of the 

water table and top and bottom altitudes, as described 

above, along cross sections shown in figure 7, and values between the section lines were interpolated. The 
50 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Layer 1

Layer 2

EXPLANATION FOR

LAYERS 1 AND 2

Model boundary

Layer boundary

Conductivity –

In feet per second

0.0015 (layer 1)

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

0.0039 (layer 2)

COLUMN

ROW ROW

A

B

? Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

 Figure 20. Model grid and areal distribution of hydraulic conductivity for layers 1–4 of the Rialto–Colton 

Basin ground-water flow model, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 51

Layer 3

Layer 4

Model boundary

Layer boundary

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Conductivity –

In feet per second

0.0001736

0.0004050

0.0005787

0.0009259

0.0001547

Model boundary

Layer boundary

EXPLANATION

Conductivity –

In feet per second

0.0001013

0.0002315

0.0001447

COLUMN

ROW ROW

? Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

D

C

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Figure 20.—Continued.
52 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Layer 1

Layer 2

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

Model boundary

Layer boundary

EXPLANATION

0-50

50-99

100-149

150-199

200-249

Model boundary

Layer boundary

EXPLANATION

Thickness – In feet

Thickness – In feet

50-99

100-149

150-199

COLUMN

ROW ROW

Layer 1

Layer 2

A

B

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

?

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

 Figure 21. Model grid and areal distribution of thickness for layers 1–4 of the Rialto–Colton Basin ground-
Numerical Simulation of Ground-Water Flow 53

Layer 3

Layer 4

Model boundary

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION

Layer boundary

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Thickness - In feet

Thickness - In feet

100-199

200-299

300-399

400-499

500-599

Model boundary

Layer boundary

EXPLANATION

100-199

200-299

300-399

400-499

500-599

0-99

COLUMN

ROW ROW

?

C

D

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Figure 21.—Continued.
54 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

thickness of layer 1 ranges from 50 ft in the northeast 

to 200 ft in the southwest (fig. 21A). The thickness of 

layer 2 ranges from a feather edge to 250 ft. Layer 2 is 

thickest in the center of the layer and thins toward the 

northwest where the upper water-bearing unit becomes 

unsaturated. The thickness of layer 3 ranges from a 

feather edge to 600 ft. The thinnest part of layer 3 is 

north of Barrier J, and the thickest part of layer 3 is in 

the northwestern part of the layer south of Barrier J. 

Layer 3 generally thins from northwest to southeast. 

The thickness of layer 4 ranges from 100 to 600 ft and 

is greatest adjacent to the northeastern boundary.

Vertical Conductance

Vertical leakage between adjacent layers occurs 

whenever there is a difference in hydraulic head 

between layers. The rate at which leakage occurs is 

determined by the following equation:

Q = Kv * DELRj * DELCi(Hk - Hk+1),

B

where:

Q is the vertical leakage [L3/T],

Kv is the effective value of vertical hydraulic 

conductivity between the center of cell

i,j,k and cell i, j, k+1 [L/T],

DELRj is the cell width along row j [L],

DELCi is the cell width along column i [L],

B is the distance between the centers of

model layer k and k+1 [L]

Hk is the hydraulic head in cell i,j,k [l]

Hk+1 is the hydraulic head in cell i,j,k+1 [L]

cell i,j,k represents a model cell in row i, column j, 

and layer k [dimensionless], and

cell i,j,k+1 represents a model cell in row i, column j,

and layer k+1 [dimensionless].

The quantity of Kv/B in the above equation is 

referred to the “vertical leakance term” and is designated “Vcont” in this report. The ground-water flow 

model requires that the user specify the term Vcont as 

input data. Vcont is calculated using the following 

equation (McDonald and Harbaugh, 1988, p. 5–13):

1 Vconti,j,k+1/2 = ____________________, delvk/2 + delvk+1/2 --------- ---------- kzi,j,k kzi,j,k+1

where:

delvk is the thickness of model layer k,

delvk+1 is the thickness of model layer k+1,

kzi,j,k is the vertical hydraulic conductivity 

of the upper layer in cell i,j,k, and

kzi,j,k+1 is the vertical hydraulic conductivity 

of the lower layer in cell i,j,k+1.

The value of vertical hydraulic conductivity, kz, 

is typically one-tenth to one-hundredth of the horizontal hydraulic conductivity. In this model, the vertical 

hydraulic conductivity of layers 1, 2, and 3 is one-tenth 

of the horizontal conductivity, and the conductivity of 

layer 4 is one-hundredth of the horizontal conductivity. 

The calculated Vcont distributions between model layers 1 and 2, 2 and 3, and 3 and 4 are presented in figure 

22. 

 Storage Coefficient and Specific Yield

The storage coefficient is defined as the volume 

of water that an aquifer releases from or takes into storage per unit surface area of the aquifer per unit change 

in head and is dimensionless (Heath, 1983, p. 28). The 

value of the storage coefficient depends on whether the 

aquifer is confined or unconfined. The storage coefficient for most confined aquifers ranges from about 

0.00001 to 0.001. The storage coefficient for unconfined aquifers, which is virtually equal to the specific 

yield, usually ranges from about 0.1 to 0.3 (Heath, 

1983, p. 28-9). The primary storage coefficient is used 

to simulate confined conditions, and the secondary 

storage coefficient is used to simulate unconfined conditions in a layer that can convert from confined to 

unconfined. The storage-coefficient values were determined from model calibration as described in the 

“Transient Simulation” section. Layer 1 is simulated as 

always unconfined, and the value of the primary and 

secondary storage coefficient is 0.30 (fig. 23A).

Layer 2 is simulated as always unconfined where 

it is the uppermost layer, and the primary and secondary storage coefficient is 0.30 (fig. 23B). Where layer 2 

underlies layer 1, the storage-term conversion is 

allowed to occur. The primary storage coefficient is 

0.0001 and the secondary storage coefficient is 0.30 

(fig. 23B). 

The distribution of storage coefficients for layer 

3 is variable (fig. 23C). Layer 3 is the only layer active 

northwest of Barrier J. Unconfined conditions are 

assumed at all times in this area, and the primary and 
Numerical Simulation of Ground-Water Flow 55

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

Model boundary

Layer boundary

EXPLANATION

Model boundary

EXPLANATION

Layer boundary

2.00-2.99

3.00-3.99

4.00-4.99

5.00-5.99

2.00-2.99

1.00-1.99

3.00-3.99

4.00-4.99

Vertical conductance –

In seconds (all values

are X 10 )

-1

-7

Vertical conductance –

In seconds (all values

are X 10 )

-1

-6

ROW ROW

COLUMN

?

Layer 1

Layer 2

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Figure 22. Model grid and real distribution of vertical conductance between layers 1 and 2, 2 and 3, and 3 
56 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Model boundary

No vertical

conductance

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION

Layer boundary

69

65

60

55

50

45

40

35

30

25

20

15

10

7

< 1.00

2.00-2.99

1.00-1.99

Vertical conductance -

In seconds (all values

are X 10 )

-1

-8

COLUMN

ROW

?

Layer 3

Fault - Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

secondary storage coefficient is 0.25. Southeast of Barrier J, the primary and secondary storage coefficients 

varied according to degree of aquifer confinement. 

Immediately southeast of Barrier J and southwest of the 

unnamed fault, layer 3 is always confined and the primary and secondary storage coefficients are 0.0001 

(fig. 23C). Between this area and where layer 3 underlies layer 2, the primary storage coefficient is 0.0001 

and the secondary coefficient is 0.075 (fig. 23C). 

Where layer 3 underlies layer 2, the primary storage 

coefficient is 0.005 and the secondary coefficient is 

0.05. Secondary storage coefficients of 0.075 and 0.05 

indicate partially confined conditions owing to the 

existence of discontinuous clay lenses in these areas. 

Northeast of the unnamed fault, the primary storage 

coefficient is 0.0001 except near te junction of the 

unnamed frult and the San Jacinto Fault where it is 

0.005; the secondary storage coefficient is 0.15 in the 

northernmost part and 0.05 in the southernmost part 

(fig. 23C). 

The distribution of primary and secondary storage coefficient for layer 4 is shown in figure 23D. It is 

assumed that the head in layer 4 will never decline 

below the bottom altitude of layer 3, and these confined 

conditions prevail all the time. The primary and secondary storage coefficient for layer 4 is 0.0001.

Model Calibration

Ground-water conditions during the period 

1945–96 were used to calibrate the flow model to transient or time-dependent conditions. Ground-water conditions were adjusted until simulated water levels 

approximated measured water levels. Seepage data for 

the Santa Ana River and (or) Warm Creek were not 

available for calibration. A transient condition exists 

when aquifer recharge and discharge change with time, 

resulting in an increase or decrease in the quantity of 

water stored in the basin. Ground-water conditions in 

Figure 22.—Continued.
Numerical Simulation of Ground-Water Flow 57

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

Model boundary

Layer boundary

Primary storage coefficient

(Dimensionless)

Secondary storage coefficient

(Dimensionless)

EXPLANATION

Model boundary

Primary storage

coefficient

(Dimensionless)

EXPLANATION

Layer boundary

0.30

0.0001

0.30

0.30

0.30

ROW ROW

COLUMN

?

Layer 2

Layer 1

A

B

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

 Figure 23. Model grid and areal distribution of primary and secondary storage coefficients for layers 1–4 of 
58 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Layer 3, Primary Storage

Layer 3, Secondary Storage

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

69

65

60

55

50

45

40

35

30

25

20

15

10

7

69

65

60

55

50

45

40

35

30

25

20

15

10

7

Model boundary

Layer boundary

Secondary storage

coefficient

(Dimensionless)

EXPLANATION

Model boundary Primary storage

coefficient

(Dimensionless)

EXPLANATION

0.05

0.075

0.0001

0.15

0.25

0.005

0.0001

0.25

COLUMN

ROW ROW

C

C

Layer boundary

?

(part 1.)

(part 2.)

Mid-valley

landfill

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

? ?

? ?

?

0

0

3 KILOMETERS

3 MILES

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

Barrier H

Unnamed Fault

Fault – Dashed where

approximately located;

dotted where concealed;

queried where doubtful

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

Figure 23.—Continued.
Numerical Simulation of Ground-Water Flow 59

Model boundary

Layer boundary

6 10 15

69

65

60

55

50

45

40

35

30

25

20

15

10

7

20 25 30 35 40 45 50 55 60 65 70 75 80

6 20 10 15 25 30 35 40 45 50 55 60 65 70 75 80

EXPLANATION

69

65

60

55

50

45

40

35

30

25

20

15

10

7

0.0001

Primary and secondary

storage coefficient

(Dimensionless)

COLUMN

ROW

D

Layer 4

Mid-valley

landfill

Linden Ponds

Cactus

Basin

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ? ? ?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

Barrier H

Unnamed Fault

1945 were used to provide initial conditions for the 

transient simulation. This year was chosen for consistency with an existing ground-water flow model in the 

adjacent Bunker Hill Basin (W.R. Danskin, USGS, oral 

commun., 1994) and because conditions at that time 

approximated steady state, whereby net recharge to the 

system equaled net discharge from the system, water 

levels remained relatively constant, and aquifer storage 

did not change with time. 

Initial Conditions

A set of initial conditions is required input for 

transient calibration. Hydraulic heads generated by 

simulating initial conditions primarily are dependent 

on the recharge and discharge from the ground-water 

system, the hydraulic conductivity and layer 

thicknesses of the aquifer system, and vertical leakance 

between layers. The initial-conditions simulation consisted of trial-and-error modification of (1) the initial 

estimates of hydraulic conductivity, (2) the quantity 

and distribution of underflow from the Lytle Basin to 

the Rialto–Colton Basin, (3) the distribution of underflow from the Bunker Hill Basin to the Rialto–Colton 

Basin, (4) the conductance of the general-head boundary between the Rialto–Colton Basin and the Chino and 

North Riverside Basins, and (5) the horizontal-flowbarrier hydraulic characteristic assigned to duplicate 

measured basinwide hydraulic heads. Ground-water 

conditions for 1945 were used to simulate initial conditions in the Rialto–Colton Basin. Conditions during 

1945 approximated steady state, whereby net recharge 

to the system equaled net discharge from the system 

and, because hydraulic heads are constant in simulating 

initial conditions, the storage component of the system 

is not part of the initial-condition 

simulation.

Values for underflow from the Lytle Basin to the 

Rialto–Colton Basin were calculated to be equivalent 

to 35 percent of discharge in Lytle Creek in 1945 (discharge in Lytle Creek, 31,300 acre-ft; underflow about 

Figure 23.—Continued.
60 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

10,960 acre-ft). Fifty percent of this underflow (about 

5,480 acre-ft) occurs northwest of Barrier J, and fifty 

percent southeast of Barrier J. Underflow from the 

Bunker Hill Basin to the Rialto–Colton Basin for 1945 

was estimated to be about 13,660 acre-ft. Ungaged runoff and subsurface inflow for 1945 was estimated to be 

2,930 acre-ft from the San Gabriel Mountains and 

90 acre-ft from the Badlands. Seepage loss from the 

Santa Ana River and Warm Creek was computed by the 

flow model to be about 3,260 acre-ft. Streambedconductance estimates for the adjacent Bunker Hill 

ground-water flow model (0.1 ft2

/s) were used in this 

simulation. The quantity of irrigation return flow for 

1945 was estimated to be about 2,040 acre-ft 

(30 percent of total pumpage). Average annual recharge 

from precipitation was 860 acre-ft. The quantity of 

underflow from the Rialto–Colton Basin to the Chino 

and North Riverside Basins (about 24,710 acre-ft) was 

computed by the flow model. Water levels measured in 

wells 1S/4W-29H2 and 1S/4W-28L1 in 1945 were 

used as external heads in the general-head-boundary 

package, which simulates underflow between the 

Rialto–Colton Basin and the Chino and North Riverside Basins. Discharge from pumpage for 1945 was 

assumed to be the same as for 1947 (6,791 acre-ft) 

when collection of pumpage data began. Net pumpage 

used in the initial-conditions simulation was 

4,754 acre-ft (70 percent of total pumpage).

Transient Simulation

Ground-water conditions (stresses) during the 

period 1945–96 were used as input to calibrate the 

ground-water flow model to transient or timedependent conditions. Transient conditions in the 

Rialto–Colton Basin are the result of stresses on the 

system imposed by the major sources of recharge to 

and discharge from the Rialto–Colton Basin. Hydraulic 

heads resulting from the initial-conditions simulation 

were used as initial conditions for the transient simulation. The period 1945–96 was modeled as 52 one-year 

stress periods. Water levels in the transient period have 

declined and recovered in response to increases and 

decreases in pumpage and recharge during wet and dry 

periods (Woolfenden and Kadhim, 1997). 

Changes in hydraulic head are dependent on 

recharge and discharge, boundary conditions, and aquifer properties. For transient calibration, the quantity of 

recharge from rainfall, the irrigation-return-flow factor, 

the evapotranspiration rate, and the streambed conductance are the same as those in the initial-condition calibration and were not adjusted. Annual estimates of 

ungaged runoff, described previously in the “Ungaged 

Runoff and Subsurface Inflow” section, were used in 

the model without modification. Annual net pumpage 

data, described previously in the “Pumpage” section, 

are measured values and were not adjusted during transient calibration except in distribution to layers as 

noted earlier. Therefore, the calibration procedure for 

transient conditions consisted of modifying (1) initial 

estimates of storage coefficient, (2) hydraulic conductivity, (3) bottom altitude of layer 3, (4) hydraulic conductance of the general-head boundary representing the 

interface between the Rialto–Colton Basin and the 

Chino and North Riverside Basins, (5) the hydraulic 

characteristic of horizontal flow barriers, (6) the quantity and distribution of underflow from the Lytle Basin 

to the Rialto–Colton Basin, and (7) the layer distribution of underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin. These parameters were modified 

during the transient calibration until simulated hydraulic heads reasonably matched measured values. The 

vertical-leakance values were recalculated whenever 

the hydraulic-conductivity values and (or) bottom altitude of layer 3 were changed. Modifications to hydraulic conductivity, bottom altitude of layer 3, vertical 

leakance, hydraulic conductance of the general-head 

boundary, hydraulic characteristic of horizontal-flow 

barriers, and underflow during transient calibration 

were reentered into the initial-conditions model to 

ensure that simulated heads were not adversely 

affected, thus making model calibration for the Rialto–

Colton ground-water flow model an iterative process.

The final values of general-head boundary conductance used in the flow model were determined by 

calibration. The model-calibrated values of conductance are 0.05 ft2/s for layer 1 and 0.04 ft2

/s for layers 

2 and 3. 

Hydraulic conductivity in layers 1 and 2 was not 

adjusted during model calibration. Hydraulicconductivity distributions in layer 3 and, consequently, 

layer 4 (as described in the “Hydraulic Conductivity” 

section, layer 4 values were estimated to be one-fourth 

those for layer 3) were adjusted, but it was found that 

water levels were relatively insensitive to this parameter. Therefore, the original parameters described in the 

“Hydraulic Conductivity” section were used in subsequent modeling.
Numerical Simulation of Ground-Water Flow 61

Top and bottom altitudes for layers 1 and 2, bottom altitudes for layer 4, and top altitudes for layer 3 

were not adjusted significantly during model calibration. Bottom altitudes for layer 3 in the northwestern 

part of the basin southeast of Barrier J and in the vicinity of the Linden Ponds artificial-recharge site were 

decreased 50 to 400 ft to produce more realistic (consistent with historical data [Dutcher and Garrett, 

1963]) values and to eliminate the drying of cells in 

layer 3 in that area.

Primary and secondary storage-coefficient distributions for layers 1–4 are shown in figure 23. The 

original storage-coefficient values are based on those 

given by Heath (1983) for confined and unconfined 

aquifers. Decreasing the primary and secondary storage coefficients during transient model calibration 

resulted in greater short-term variation in water levels, 

and increasing the parameter resulted in less variation. 

Primary and secondary storage coefficients for all layers are a result of transient model calibration.

Calibration Results

Ground-water-level measurements made during 

1945 were used for comparison with the initialconditions simulation to determine if there was a reasonable match, and thus reasonable starting heads, for 

the transient simulation. Depth-dependent water-level 

data generally are not available for 1945; hence, composite water-level measurements made in production 

wells (usually perforated in more than one layer) were 

used for comparison during the calibration. Hydraulic 

heads calculated for layer 3 were compared with the 

available 1945 measured water levels. Layer 3 was 

chosen because it simulates the main water-producing 

unit (the middle water-bearing unit), and water levels 

measured in wells perforated in the different layers 

generally do not vary significantly (Woolfenden and 

Kadhim, 1997). Simulated heads and measured water 

levels are given in table 10. The relation between simulated head and measured water levels, shown in figure 

24, indicates that, overall, the simulated heads match 

measured water levels well; the goodness-of-fit value 

is 0.99. The largest differences between simulated head 

and measured water level (−55.6 ft for well 

1S/5W-5A2 and −40.5 ft for well 1S/5W-5A3) (fig. 25) 

occurred between Barrier H and the Rialto–Colton 

Fault. Simulated heads near the Santa Ana River and 

Warm Creek, and simulated heads northwest of Barrier 

J, generally are within 30 ft of measured water levels 

and five are within 20 ft (fig. 25). The maximum difference between simulated heads and measured water levels near the Santa Ana River and Warm Creek is 26.8 ft 

at well 1S/4W-21N1; the minimum difference is 7.7 ft 

at well 1S/4W-21R1. The maximum difference 

between simulated head and measured water level in 

the central part of the basin is 25.8 ft at well 

1S/4W-17M1 and the minimum is −1.9 ft at well 

1S/5W-12L1. Northwest of Barrier J, differences 

between simulated head and measured water level are 

26.2 ft at well 1N/5W-17K1 and 24.4 ft at well 

1N/5W-19A1.

For this report, simulated heads were compared 

with measured long-term changes in hydrographs of 

composite water levels in selected wells, and with measured short-term changes in hydrographs of water lev-

 Table 10. Measured water-level altitude and simulated hydraulic 

head in selected wells for initial conditions (1945) in the Rialto–

Colton Basin, San Bernardino County, California

[Water-level altitude and hydraulic head in feet above sea level]

State well 

number

Measured 

water-level 

altitude

Simulated 

hydraulic 

head

Residual

1N/5W-17K1 1,809.4 1,835.6 26.2

1N/5W-19A1 1,658.3 1,682.7 24.4

1N/5W-28J1 1,083.1 1,105.9 22.8

1S/5W-5A2 1,202.9 1,147.3 −55.6

1S/5W-5A3 1,187.8 1,147.3 −40.5

1S/5W-3A1 1,061.5 1,073.6 12.1

1S/5W-2C1 1,056.6 1,067.2 10.6

1S/5W-2K1 1,048.5 1,055.5 7.0

1S/5W-12L1 993.8 991.9 −1.9

1S/5W-12N1 999.9 992.4 −7.5

1S/4W-7C1 1,043.2 1,051.4 8.2

1S/4W-18E1 943.1 958.1 15.0

1S/4W-18B2 944.0 966.7 22.7

1S/4W-17M1 934.8 960.6 25.8

1S/4W-21N1 929.8 956.6 26.8

1S/4W-21L1 941.9 962.6 20.7

1S/4W-21P1 947.1 960.1 13.0

1S/4W-21Q1 942.0 958.3 16.3

1S/4W-21Q3 936.0 960.0 24.0

1S/4W-21R1 955.3 963.0 7.7

1S/4W-28H1 936.2 955.6 19.4

1S/4W-28K2 931.5 948.8 17.3

1S/4W-27N1 937.6 957.9 20.3
62 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SIMULATED HEAD, IN FEET ABOVE SEA LEVEL

800

800 1,000 1,200 1,400 1,600 1,800 2,000

1,000

1,200

1,400

1,600

1,800

2,000

MEASURED WATER-LEVEL ALTITUDE, IN FEET ABOVE SEA LEVEL

x = simulated head

y = measured water-level altitude

y = 0.994x - 16.09

R 2 = 0.992

els in multiple-depth observation wells (cluster wells) 

installed for this project. Model-simulated hydraulic 

heads were compared with measured long-term composite water levels at 20 production wells for 1945–96 

(fig. 26). The model generally simulated heads well 

northwest of Barrier J and during 1945–82 in the central part of the basin (for example, wells 1S/5W-2K1, 

1S/5W-12L1, and 1S/4W-18F1). 

Hydrographs for wells northwest of Barrier J 

(1N/5W-17K1 and 1N/5W-19A1) and in the central 

part of the basin during 1945–82 show the smallest difference between simulated heads and measured water 

levels (fig. 26). Simulated heads and measured water 

levels in the central part of the basin generally are 

within 10 ft until about 1982–85 when differences 

become greater (for example, wells 1S/5W-2K1 and 

1S/5W-12L1) (fig. 26). Prior to 1982, simulated heads 

generally were within the range of measured waterlevel fluctuation at wells 1S/5W-2K1, 1S/5W-3A1, and 

1S/5W-12L1. After 1982–85, simulated heads were as 

much as 50 ft below measured water levels at well 

1S/5W-2K1 and as much as 25 ft below measured 

water levels at well 1S/5W-12L1. Simulated heads generally were about 10 to 50 ft higher than measured 

water levels in well 1S/4W-18F1. 

In the northwestern part of the basin southeast of 

Barrier J, simulated heads in wells 1N/5W-34M1, 

1N/5W-27D1, and 1N/5W-34B1 were as much as 

50 feet higher than measured water levels during 

1945–82 but matched measured water levels well after 

1982. In the compartment between Barrier H and the 

Rialto–Colton Fault, simulated heads match well 

during 1945–82 but are comparatively low during 

1982–96. Near the Santa Ana River and Warm Creek, 

simulated heads generally rose above measured water 

levels during the periods—except during 1965–72 

 Figure 24. Relation between simulated head and measured water-level altitude, 1945, in the 

Rialto–Colton Basin, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 63

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

Unnamed Fault

Barrier H

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin 

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Other well – includes small domestic wells and observation

wells; number below line is residual

Production well – number above line is well number and 

number below line is residual

28H1

19.4

-7.5

12N1

17K1

28J1

2C1

5A3

5A2 3A1

2K1

12L1

12N1

18E1

17M1

21Q1

21Q3

28K2

21P1

21N1

19A1

18B2

27N1

22.8

-40.5

-55.6

 10.6

12.1

 7.0

 8.2

-7.5

-1.9

22.7

15.0

26.8

13.0

20.3

24.0

21L1

20.7

21R1

7.7

28H1

19.4

7C1

26.2

24.4

25.8

16.3

17.3

when simulated heads compared well with measured 

water levels (for example, 1S/4W-21N1and 

1S/4W-21Q3) (fig. 26). Simulated heads rose above 

measured water levels during the period 1945–65 when 

data were available in wells 1S/4W-21K1, 

1S/4W-21K2, 1S/4W-21Q3, and 1S/4W-28H1 

(fig. 26). The differences between simulated heads and 

measured water levels, particularly in the northwestern 

part of the basin, may be due, in part, to unknown fault 

geometry and geologic structure. 

Model-simulated heads were compared with 

recent measured depth-dependent water levels in 

29 wells for 1992–96 (fig. 27). The simulated heads 

and measured water levels for layers 1 and 2 are shown 

in the hydrographs for wells 1S/4W-20H5 and 

 Figure 25. Distribution of residuals for the initial-conditions (1945) simulation in the Rialto–Colton Basin, San Bernardino County, California.
64 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Avenue Highland

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

3407'

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

0

0

3 KILOMETERS

3 MILES

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

Other well – Includes small domestic wells and

observation wells

Production well and number

21K11

San Gabriel Mountains

NORTH RIVERSIDE BASIN

12L1

Simulated hydraulic head

Graphs

Measured water-level altitude

19A1

21K11

28H1

17K1

27D1

34B1 29R15

34M1

5A2 3A1 4D2

2K1

12L1

18F1

28K2 28K1

21N1

21P1

21Q1

21Q3

7C1

1N/5W-19A1 – Well identification

number

(17, 23) – Row, column number

Measured Modeled

1N/5W-34B1

(30,40)

(25,37)

1N/5W-27D1

1S/5W-4D2

(37,31)

Layer 3

1S/5W-2K1

(40,46)

1920 40 60

YEAR

80 2000 1920 40 60

YEAR

80 2000

1,700

2,000

1,900

1,800

1N/5W-17K1

(14,27)

Measured

Layer 3-4 1N/5W-34M1

(34,36)

1,150

1,050

950

850

1,250

1.150

1,050

950

1,300

1,200

1,100

1,000

1,800

1,700

1,600

1,500

1,150

1,050

950

850

1,150

1,050

950

850

1920 40 60

YEAR

80 2000

1920 40 60

YEAR

80 2000

1,100

1,000

900

800

1,100

1,000

900

800

1,150

1,050

950

850

1N/5W-5A2

(36,29)

1S/5W-3A1

(51,47) Layers 3-4

1S/5W-12L1

(47,52)

Layer 3

Layers 3-4

Layers 3-4

Layer 3

Layer 4

Layer 3

 Figure 26. Location of wells, and hydrographs showing simulated heads and measured water-level altitudes (in feet above sea level) for 

selected production wells in the Rialto–Colton Basin, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 65

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

3407'

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

San

Bernardino

Colton

Rialto

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

19A1

21K11

28H1

17K1

27D1

34B1 29R15

34M1

5A2 3A1 4D2

2K1

12L1

18F1

28K1 28K2

21N1

21P1

21Q1

21Q3

7C1

YEAR

1920 40 60 80 2000

YEAR

1920 40 60 80 2000

YEAR

1920 40 60 80 2000

YEAR

1920 40 60 80 2000

Measured

Modeled

1S/4W-7C1

(47,57)

Layer 3

1S/4W-21K11

(59,73)

1S/4W-21P1

(60,72)

Layers 1-3

1S/4W-21Q3

(47,57)

Layers 2-3

(66,72)

1S/4W-28K1 Layers 1-3

1S/4W-18F1

(52,58) Layers 3-4

1S/4W-21N1

(60,70) Layers 1-4

1S/4W-21Q1

(61,72)

Layers 1-3

1S/4W-28H1

(65,74)

1,100

1,000

900

800

1,100

1,000

900

800

1,100

1,000

900

800

1,150

1,050

950

850

1,150

1,050

950

850

1,050

950

850

750

1,200

1,100

1,000

900

1,150

1,050

950

850

1,150

1,050

950

850

1,150

1,050

950

850

Layers 1-2

1S/4W-28K2

(65,72)

Layers 1-2

Layers 2-4

1S/4W-20H4, respectively. Simulated heads generally 

are within 25 ft of measured water levels in both wells.

Simulated heads in layer 3 in the compartment 

between the unnamed fault and the San Jacinto Fault 

(wells 1N/5W-21K3, 1N/5W-22N3, and 1N/5W-35B4) 

generally were within 50 ft of measured water levels. 

Simulated heads in wells at the artificial-recharge 

ponds (1N/5W-22N3-5) and wells upgradient from the 

ponds (1N/5W-21K3) respond sooner to both artificial 

and natural recharge than do measured water levels (fig. 

27). This difference may be due to the time lag between 

when surface spreading of imported water occurs and 

when the imported water actually recharges the water 

table during initial wetting. Artificial recharge and 

Figure 26.—Continued.
66 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Cr

Linden Ponds

Cactus

Basin

Diversion

canal

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

?

?

?

34 07'

117 22'30" R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

0

0

3 KILOMETERS

3 MILES

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately

located; dotted where concealed;

queried where doubtful

Unconsolidated deposits – Shaded

in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological

Survey 1:100,000 San

Bernardino, 1982

Box

Springs

Mts

Badlands

RIALTO-COLTON BASIN

San Gabriel Mountains

Simulated hydraulic head

Graphs

Measured water-level altitude

?

11F1-4

8E1-4

21K1-4

22N1-6

26L1

35B1-4

34D1-4

29Q1-5

11F1-4

20H1-5

Cluster well site and number –

Site at which one or more wells

are completed at different depths

1N/5W-21K3

(20,34) – Row, column number

Well identification

number 1N/5W-21K4

(20,34)

YEAR

1990 92 94 96 98 2000

YEAR

1990 92 94 96 98 2000

YEAR

1990 92 94 96 98 2000

YEAR

1990 92 94 96 98 2000

YEAR

1990 92 94 96 98 2000

1N/5W-22N3

(22,37)

1N/5W-22N4

(22,37)

1,300

1,200

1N/5W-22N5

(22,37)

1,100

1,000

1,300

1,200

1N/5W-35B3

(30,47)

1N/5W-35B4

(30,47)

1N/5W-29Q4

(29,27)

(30,36)

1N/5W-34D3

1N/5W-34D4

(30,36)

(46,63)

1S/4W-8E4

900

800

1,100

1,000

1S/5W-11F3

(44,45)

Modeled Measured

1S/5W-11F4

(44,45)

1S/4W-20H4

(59,67)

1S/4W-20H3

(59,67)

1S/4W-20H5

(59,67)

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1,100

1,000

900

800

1,100

1,000

900

1,200

1,100

1,000

950

1,250

1,150

1,050

950

1,250

1,150

1,050

850

1,150

1,050

950

850

1,150

1,050

950

800

1,100

1,000

900

800

1,100

1,000

900

800

1,100

1,000

900

1990 92 94 96 98 2000 1990 92 94 96 98 2000

YEAR YEAR YEAR YEAR

1990 92 94 96 98 2000 1990 92 94 96 98 2000

A

Layer 3

Layer 3

Layer 3

Layer 3

Layer 3

Layer 3

Layer 3 Layer 2 Layer 1

Layer 3

Layer 3

Layer 3

Layer 3 Layer 3 Layer 3

Layer 3

 Figure 27. Location of wells, and hydrographs showing simulated heads and measured water-level altitudes (in feet above sea level) for 

selected cluster wells in layers 1–3 (A), and layer 4 (B), in the Rialto–Colton Basin, San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 67

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Cr

Linden Ponds

Cactus

Basin

Diversion

canal

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

?

?

?

34 07'

11722'30" R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

0

0

3 KILOMETERS

3 MILES

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately

located; dotted where concealed;

queried where doubtful

Unconsolidated deposits – Shaded

in Rialto-Colton Basin 

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological

Survey 1:100,000 San

Bernardino, 1982

Box

Springs

Mts

Badlands

RIALTO-COLTON BASIN

San Gabriel Mountains

Graphs ?

Simulated hydraulic head

Measured water-level altitude

11F1-4

8E1-4

21K1-4

22N1-6

26L1

35B1-4

34D1-4

29Q1-5

11F1-4

20H1-5

Cluster well site and number –

Site at which one or more wells

are completed at different depths

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1,100

1,400

1,300

1,200

1N/5W-21K1 – Well identification

number

(20,34) – Row, column number

Measured Modeled

1N/5W-21K2

(42,34)

YEAR

1990 92 94 96 98 2000

YEAR

1990 92 94 96 98 2000

1990 92 94 96 98 2000 1990 92 94 96 98 2000

YEAR YEAR YEAR YEAR

1990 92 94 96 98 2000 1990 92 94 96 98 2000

(22,37)

1N/5W-22N1 1N/5W-22N2

(22,36)

1,100

1,000

1,300

1,200

1N/5W-35B1

1N/5W-35B2

(30,47)

(30,47) B

YEAR

1990 92 94 96 98 2000

1S/4W-20H2

(59,67)

900

800

1,100

1,000

1S/4W-8E3

(46,63)

1S/4W-8E2

(46,63)

900

800

1,100

1,000

900

800

1,100

1,000

900

1,200

1,100

1,000

1S/5W-11F2

(44,45)

900

1,200

1,100

1,000

1N/5W-34D2

(30,36)

900

1,200

1,100

1,000

1N/5W-29Q2

(29,27)

900

1,200

1,100

1,000

1N/5W-29Q3

(29,27)

1,100

1,000

1,300

1,200

Layer 4

Layer 4

Layer 4

Layer 4 Layer 4

Layer 4

Layer 4

Layer 4

Layer 4

Layer 4 Layer 4 Layer 4

Layer 4

Figure 27.—Continued.
68 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

underflow from the Lytle Basin are simulated as wells 

with positive flow rates; these effects occur instantaneously in the model. Therefore, the lag time (about 6 

months) between the onset of the recharge event and 

the water-level response (fig. 11) is not accounted for in 

the model. Also, the water-level response to individual 

artificial-recharge events may not be simulated adequately with annual stress periods. In addition, the simulated water-level peaks after the 1992 recharge event 

occurred later than the measured water-level peaks in 

most wells in the compartment between the San Jacinto 

Fault and the unnamed fault, indicating that the spatial 

and temporal distribution of recharge is not well understood. Simulated heads were about 10 to 50 ft too low 

in the rest of the basin (wells 1N/5W-34D3-4, 1N/5W29Q3-4, and 1S/4W-11F3-4), implying insufficient 

recharge to layer 3 in the northwestern part of the basin 

west of the unnamed fault. Near Warm Creek, water 

levels were about 20 ft too high (well 1S/4W-20H3) 

(fig. 27), implying too much recharge to layer 3 in this 

area.

Differences between simulated head and measured water level in layer 4 in the compartment 

between the unnamed fault and the San Jacinto Fault 

varied with location (fig. 27). At the artificial-recharge 

ponds, simulated heads were lower than measured 

heads at wells 1N/5W-22N1,2 during 1992–94 but 

compared well during 1994–96. Upgradient from the 

recharge ponds, water-level differences generally were 

within 20 ft except during 1992–94 at wells 

1N/5W-21K1,2. Simulated heads downgradient from 

the recharge ponds were 25 to 50 ft higher than measured water levels (wells 1N/5W-35B1,2 and 

1S/4W-8E2). Simulated heads were about 15 to 50 ft 

lower than measured water levels in layer 4 in the rest 

of the basin (wells 1N/5W-29Q2,3, 1N/5W-34D2, and 

1S/5W-11F2) (fig. 27). 

Differences between simulated heads and measured water levels may be attributed to several factors. 

These differences indicate that (1) the distribution of 

recharge in layer 3 may not be adequately simulated; 

(2) there may be a source of recharge to layer 3 and (or) 

layer 4 that is not simulated; (3) there may exist aquifer 

heterogeneities that are not simulated in the model; (4) 

the hydraulic-conductivity values should be higher in 

the recharge areas; and (or) (5) the storage-coefficient 

values should be higher in the recharge areas. The only 

source of recharge to layer 4 that is simulated in the 

model is vertical movement of water from layer 3; 

hence, water levels in layer 4 are affected by recharge 

patterns in layer 3. Values of hydraulic conductivity 

and storage coefficient were not increased beyond 

those shown in figures 20 and 23, respectively, during 

model calibration because available data do not support 

the higher values.

The simulated potentiometric contours in the 

Rialto–Colton Basin are shown in figure 28 for initial 

conditions (1945). Contour lines for layer 1 (fig. 28A) 

show that ground water moves westward in this layer 

from the Bunker Hill Basin to the North Riverside 

Basin.

The simulated potentiometric contours for layer 

2 are shown in figure 28B. Ground water moves southwestward and southeastward across the unnamed fault 

and upward from layer 3 at the northeastern boundary 

of layer 2. Near the Santa Ana River and Warm Creek, 

ground water moves westward from the Bunker Hill 

Basin to the North Riverside Basin.

The simulated potentiometric contours for layer 

3 are shown in figure 28C. Ground water moves across 

Barrier E from the Lytle Basin in the northwestern part 

of the basin and then moves southward and southwestward north of Barrier J. South of Barrier J, ground 

water moves in a southeastward direction along the axis 

of the basin. In the southeastern part of the basin, 

ground water moves in a westward direction across the 

Rialto–Colton Fault to the North Riverside Basin. 

Water levels east of the unnamed fault were 25 to 

100 ft higher than those west of the fault.

The simulated potentiometric contours for layer 

4 are shown in figure 28D. Ground water southeast of 

Barrier J moves from northwest to southeast along the 

axis of the basin. Water levels east of the unnamed fault 

were about 50 to 100 ft higher than those west of the 

fault. The source of recharge to layer 4 in the model is 

downward movement of water from layer 3. Discharge 

from layer 4 is from pumpage or upward movement of 

ground water to layer 3 in the southeastern part of the 

basin.

Simulated 1996 potentiometric contours for layers 1 and 2 are shown in figure 29. In layer 1, ground 

water moves westward from the Bunker Hill Basin to 

the North Riverside Basin (fig. 29A). In layer 2, ground 

water moves southeastward from the unsaturated part 

of layer 2 (fig. 29B). In the vicinity of the Santa Ana 

River and Warm Creek, ground water moves westward 
Numerical Simulation of Ground-Water Flow 69

Barrier H

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Geology modified

from Morton (1974)

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 1

Model boundary

Layer boundary

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 10 feet (A, B) and

25 feet (C, D). Datum is sea level

950

Unnamed

A

Fault

960

970

950

 Figure 28. Simulated potentiometric contours for layers 1–4 (A–D), 1945, in the Rialto–Colton Basin, San Bernardino County, California.
70 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

Unnamed Fault

Barrier H

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 2

Model boundary

Layer boundary

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 10 feet (A, B) and

25 feet (C, D). Datum is sea level

950

San

Bernardino

Colton

Rialto

3407'

11722'30"

Geology modified

from Morton (1974)

B

1,020

990

980

970

960

960

950

950

Figure 28.—Continued.
Numerical Simulation of Ground-Water Flow 71

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden

Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier J

?

?

?

?

?

?

?

?

0

0

3 KILOMETERS

3 MILES

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 3

San

Bernardino

Colton

Rialto

3407'

11722'30"

Geology modified

from Morton (1974)

1,950

1,900

950

Model and layer boundary

Direction of ground-water movement

C

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 10 feet (A,B)

and 25 feet (C, D). Datum is sea level

950

1,850

1,000

1,025

1,050

1,175

1,200

1,650

1,700

1,750

1,150

1,100

1,075

950

Unnamed

Fault

1,800

975

1,075

1,100

1,125

1,125

1,150

1,175

1,200

1,225

1,300

Figure 28.—Continued.
72 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden

Ponds

Cactus

Basin

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 4

San

Bernardino

Colton

Rialto

3407'

11722'30"

Geology modified

from Morton (1974)

1,000

Model boundary

Layer boundary

Direction of ground-water movement

950

D

1,225

1,000

1,025

1,050

1,175

1,200

1,150

1,125

1,100

1,075

1,125

1,150

1,175

1,100

1,075

1,050

1,025

950

975

1,200

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 10 feet (A, B)

and 25 feet (C, D). Datum is sea level

Figure 

28.—Continued.
Numerical Simulation of Ground-Water Flow 73

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 1

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

940

920

930

Model boundary

Layer boundary

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 10 feet. Datum is sea level

920

Colton

Narrows

A

 Figure 29. Simulated potentiometric contours for layers 1 and 2 (A,B), 1996, in the Rialto–Colton Basin, San Bernardino County, California.
74 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 2

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

Model boundary

Layer boundary

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval variable. Datum is sea level

960

1,000

935

925

920

925

945

935

930

940

950

960

980

B

Figure 29.—Continued.
Numerical Simulation of Ground-Water Flow 75

from the Bunker Hill Basin to the North Riverside 

Basin. Ground-water levels in layers 1 and 2 in 1945 

were about 5 to 15 ft lower than those in 1996.

Simulated 1996 potentiometric contours for layers 3 and 4 are shown in figure 30. In layer 3, ground 

water moves generally southward northwest of Barrier 

J (fig. 30A). Ground water moves southeastward southeast of Barrier J. Water levels east of the unnamed fault 

were from 50 to 200 ft higher than those west of the 

fault. Water levels in 1945 ranged from about 25 to 

50 ft higher than those in 1996, except east of the 

unnamed fault where water levels were as much as 

25 ft higher in 1996 (fig. 30A). In layer 4, ground water 

moves southeastward southeast of Barrier J (fig. 30B). 

Water levels east of the unnamed fault were about 50 to 

200 ft higher than those southwest of the fault. Water 

levels in 1945 ranged from about 25 to 50 ft higher than 

those in 1996 except east of the unnamed fault 

(fig. 30B).

Simulated Water Budgets

A summary water budget of all simulated 

recharge and discharge components input into or calculated by the flow model for initial conditions (1945), 

average 1945–96 transient-state conditions, and 1996 

transient-state conditions is presented in table 11. 

Recall that for all simulations, ungaged runoff and subsurface inflow, irrigation return flow, areal recharge, 

artificial recharge, pumpage, and evapotranspiration 

are input to the model. Recall also that irrigation return 

flow is accounted for in the model by calculating net 

pumpage, which is the total pumpage minus the water 

that is returned to the system. As mentioned in the “Irrigation Return Flow” section of this report, the returnflow factor is 30 percent; therefore, the net-pumpage 

values are 70 percent of total-pumpage values. Underflow from the Lytle Basin to the Rialto–Colton Basin 

and from the Bunker Hill Basin to the Rialto–Colton 

Basin was determined from model calibration. The 

model simulates outflows from the general-head 

boundary, stream recharge and discharge, and flow to 

and from storage. 

Total recharge to the basin was about 

34,920 acre-ft in 1945 under initial conditions. Underflow from the Bunker Hill Basin accounted for about 

39 percent of the total recharge; and underflow from 

the Lytle Basin accounted for about 31 percent (fig. 

31). Seepage loss from the Santa Ana River and Warm 

Creek and mountain-front recharge each contributed 

9 percent of total recharge in 1945 (fig. 31). Average 

total recharge during 1945–96 was about 

33,620 acre-ft. Underflow from the Lytle and Bunker 

Hill Basins accounted for a lesser percentage of total 

recharge during 1945–96 (60 percent) than during 1945 

(70 percent) (fig. 31). The quantity of underflow from 

both the Bunker Hill and Lytle Basins (20,300 acre-ft) 

was about 18 percent less than the 1945 quantity 

(24,620 acre-ft). The quantities of underflow from the 

Bunker Hill and Lytle Basins during 1945–96 were 

about 17 and 19 percent less, respectively, than in 1945. 

During 1945–96, average total pumpage 

(11,080 acre-ft) also was greater than in 1945 

(6,791 acre-ft); this increased pumpage may have created steeper hydraulic gradients in layers 1 and 2 in the 

vicinity of the Santa Ana River and Warm Creek, 

inducing greater quantities of water to move from the 

Bunker Hill Basin to the Rialto–Colton Basin. Total 

recharge during 1996 was about 31,830 acre-ft. The 

quantity of underflow from both the Lytle Basin 

(8,560 acre-ft) and the Bunker Hill Basin 

(9,550 acre-ft) in 1996 was less than the long-term 

average, owing, in part, to less-than-average discharge 

in Lytle Creek, which contributes to underflow from 

the Lytle Basin, and a relatively shallow hydraulic gradient across the southeastern part of the basin. The discharge in Lytle Creek in 1996 was 24,400 acre-ft, 

which is 7,940 acre-ft less than the 1945–96 average 

(USGS ADAPS database). The hydraulic gradient 

between wells 1S/4W-3Q1 and 1S/4W-29H2 was 0.005 

during 1996, which was less than the 1945–96 average 

(0.006).

Model-calculated seepage loss from the Santa 

Ana River and Warm Creek was 3,260 acre-ft, about 9 

percent of total recharge for initial conditions in 1945 

(fig. 31). The average seepage loss for 1945–96 was 

4,860 acre-ft, about 15 percent of the average total 

recharge (fig. 31). The quantity of seepage loss in 1996 

was 5,490 acre-ft, accounting for 18 percent of total 

recharge to the Rialto–Colton Basin (fig. 31). The 

quantity of seepage loss from the Santa Ana River and 

Warm Creek varied significantly during 1945, 

1945–96, and 1996, indicating that relatively high 

ground-water levels caused more water to remain in the 

stream channel and leave the Rialto–Colton Basin as 

surface flow during 1945 than during the 1945–96 

average period and 1996.

Total discharge for 1945 initial conditions was 

about 34,940 acre-ft. Underflow from the Rialto–

Colton Basin to the Chino and North Riverside Basins 
76 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier J

?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

RIALTO- COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN Cluster well – Number indicates measured water-level altitude, in feet 

above sea level

Layer 3

A

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

1,925

1,900

1,850

1,000

1,000

1,050

1,050

1,200

1,250

1,300

1,600

1,650

1,700

1,750

1,125

1,100

1,100

Model and layer boundary (layer 3)

Direction of ground-water movement

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 25 feet. Datum is

sea level

950

925

950

1,150

1,800

11F4

35B4

26L1

21K3

34D4

8E4

20H3

20H3

901

29Q4

1,055

22N3

1,010

1,134

1,148

1,269

1,034

920

901

1,264

 Figure 30. Measured water-level altitudes and simulated potentiometric contours for layers 3 and 4 (A,B), 1996, in the Rialto–Colton Basin, 

San Bernardino County, California.
Numerical Simulation of Ground-Water Flow 77

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden

Ponds

Cactus

Basin

Lytle Creek

East Channel

Lytle Creek

West Channel

Flood-control

basin

Diversion

canal

22N2

1,264

215

15

66

30

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto

Fault

Barrier J

?

?

?

?

?

?

?

?

Unnamed

Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

Mid-valley

landfill

RIALTO- COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Layer 4

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

B

Potentiometric contour – Shows altitude at which waterlevel would have stood in tighly cased wells. Dashed where

approximately located. Contour interval 25 feet. Datum is

sea level

950

1,000

1,050

1,200

1,150

1,100

1,250

1,300

1,100

1,150

1,050

1,000

950

925

Model boundary

Layer boundary (layer 4)

Direction of ground-water movement

11F2

1,018

35B2

1,124

21K2

1,283

34D2

1,034

8E2

924

20H2

897

20H2

897

29Q3

1,051

Cluster well – Number indicates measured water-level altitude, in feet 

above sea level

Figure 30.—Continued.
78 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Table 11. Model-simulated initial conditions and transient water budgets for the Rialto–Colton Basin, San Bernardino County, California

[Budget values in acre-feet; —, no value;<<,much less than]

Initial conditions Transient

1945 1945–96 average 1996

Recharge

Underflow from Lytle Basin

 North of Barrier J................................................................................. 5,480 4,460 4,280

 South of Barrier J................................................................................. 5,480 4,460 4,280

Total.................................................................................................. 10,960 8,920 8,560

Underflow from Bunker Hill Basin

 Layer 1.................................................................................................. 10,930 9,100 7,640

 Layer 2.................................................................................................. 2,730 2,280 1,910

 Total................................................................................................. 13,660 11,380 9,550

Seepage loss from the Santa Ana River and Warm Creek.................... 3,260 4,860 5,490

Ungaged runoff and subsurface inflow

 San Gabriel Mountains ......................................................................... 2,930 2,950 2,550

 Badlands ............................................................................................... 90 120 90

Total.................................................................................................. 3,020 3,070 2,640

Irrigation return flow ............................................................................... 2,040 3,320 4,730

Imported water.......................................................................................... — 750 0

Seepage loss from diversion canal ........................................................... 1,120 190 —

Areal recharge ........................................................................................... 860 860 860

Underflow from Chino Basin...................................................................

Layer 1................................................................................................... 0 20 0

Layer 2................................................................................................... 0 130 0

Layer 3................................................................................................... 0 120 0

Total.................................................................................................. 0 270 0

Total recharge............................................................................................ 34,920 33,620 31,830

Water from storage ................................................................................... — 7,350 11,110

Discharge

Total pumpage ........................................................................................... 6,790 11,080 15,760

Underflow to Chino and North Riverside Basins

Layer 1................................................................................................... 4,100 4,670 4,880

Layer 2................................................................................................... 10,280 9,460 10,760

Layer 3................................................................................................... 10,300 9,570 10,800

Total.................................................................................................. 24,710 23,700 26,440

Seepage loss to the Santa Ana River and Warm Creek 3,440 440 0

Evapotranspiration................................................................................... <<1 <<1 <<1

Total discharge .......................................................................................... 34,940 35,220 42,200

Water to storage ........................................................................................ — 5,960 720

Recharge - Discharge ................................................................................ 

−20 2−1,600 −210,370

Storage depletion....................................................................................... 0 1,390 10,390

1

 The difference between recharge and discharge in this simulation should be 0. The observed differences are due to accumulation of small 

consistent errors in the model and rounding of numbers. 2

 The difference between recharge and discharge should be equal to the storage depletion. The observed differences are due to 

accumulation of small consistent errors in the model and rounding of numbers.
Numerical Simulation of Ground-Water Flow 79

39%

Ungaged

runoff

9%

Streams

9% Lytle

Basin

underflow

31%

3% Diversion

canal

Irrigation

return

flow

Irrigation

return

flow

3% 6%

Areal recharge

31%

Ungaged

runoff

6%

Streams

18%

Lytle

Basin

underflow

27%

3%

Areal recharge

Artificial

recharge

1945-96

1996

1945

Bunker Hill Basin underflow

Bunker Hill Basin underflow

Bunker Hill Basin underflow

34%

Ungaged

runoff

9%

Streams

15%

Lytle

Basin

underflow

Chino

Basin

underflow

26%

1%

2%

2% 10%

Irrigation

return

flow

15%

1%

Diversion

canal

Areal

recharge Underflow

71%

Pumpage

19%

Streams

10%

Underflow

68%

Pumpage

31%

Underflow

63%

Pumpage

37%

1945

1945-96

1996

Streams

1%

was the main component of discharge for 1945 initial 

conditions, accounting for 71 percent of the total discharge (fig. 32). Total pumpage accounted for 19 percent of total discharge, and seepage loss to the Santa 

Ana River and Warm Creek for 10 percent (fig. 32). 

Average total discharge for 1945–96 was about 

35,220 acre-ft. Underflow accounted for about 

68 percent of total discharge, and total pumpage 

accounted for about 31 percent (fig. 32). Seepage loss 

to the Santa Ana River and Warm Creek only 

accounted for 1 percent of discharge. Total pumpage in 

the Rialto–Colton Basin varied about the average during 

1949–71, and then increased during 1984–96 (fig. 13), 

owing, in part, to the drought in California during 1987–

92. Pumpage in 1996 (15,760 acre-ft) accounted for 37 

percent of total discharge, and underflow to the Chino 

and North Riverside Basins (26,440) accounted for 63 

percent (fig. 32). The increase in pumpage and decrease 

in underflow in 1996 probably is due to less-than-average rainfall.

During 1945–96, the average annual quantity of 

water removed from storage exceeded the average 

annual quantity that went into storage, resulting in an 

average storage depletion in the basin of 1,390 acre-ft. 

During 1996, about 11,110 acre-ft of recharge was 

removed from storage and about 720 acre-ft went into 

 Figure 31. Components of recharge in the Rialto–Colton 

Basin, San Bernardino County, California.

 Figure 32. Components of discharge in the Rialto–Colton Basin, 

San Bernardino County, California.
80 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

storage. During the 1987–92 drought, basin storage 

probably was depleted in some areas owing to 

decreased recharge and increased pumping during this 

period, allowing recharge during the subsequent years 

to refill in these areas of the basin, thus accounting for 

the quantity of water going into storage. Total discharge exceeded total recharge by about 10,370 acre-ft 

during 1996 owing to increased pumpage and 

decreased recharge from underflow from the Lytle and 

Bunker Hill Basins.

Sensitivity Analysis

The sensitivity of the Rialto–Colton model was 

determined for changes in total recharge (defined as the 

sum of underflow from the Lytle and Bunker Hill 

Basins, ungaged runoff, and areal recharge), net pumpage, irrigation return flow, hydraulic conductivity, vertical conductance, primary and secondary storage 

coefficients, general-head boundary conductance, 

horizontal-flow-barrier characteristic, artificial 

recharge, and streambed conductance. These model 

parameters (subsequently referred to as “inputs”) were 

varied individually while holding the remaining inputs 

Table 12. Sensitivity of hydraulic head in the Rialto–Colton Basin model (1996), San Bernardino County, California, to changes in model input

[Range of changes in feet, and range numbers are separated by slash (/); unsigned numbers in range of change are positive or zero and indicate increases or 

no change (zero) from values in the calibrated model, negative numbers indicate declines; rank (in parentheses) from most sensitive (1) to least (21); —, barrier either on or off]

1

Total recharge is the sum of underflow from Lytle and Bunker Hill Basins, ungaged runoff, and areal recharge.

Model input 

Factor of

change 

model

Range of change in hydraulic head and calibrated head, and rank

Layer 1 Layer 2 Layer 3 Layer 4

1

Total recharge 2.0 44/15 (1) 73/14 (1) 453/14 (1) 211/19 (3)

1Total recharge .75 −3/−7 (8) −3/−19 (7) −3/−74 (6) −4/−61 (6)

Irrigation return flow 2.0 4/2 (9) 10/2 (11) 42/1 (9) 39/2 (10)

Irrigation return flow .5 −1/−2 (12) −1/−5 (15) −.5/−21 (14) −1/−24 (13)

Hydraulic conductivity 1.25 .6/−4 (7) .6/−12 (9) 14/−52 (10) .4/−53 (7)

Hydraulic conductivity .75 6/−9 (4) 17/−1 (6) 76/−10 (4) 78/−.3 (4)

Vertical conductance .5 .9/−.2 (11) 4/−.6 (14) 8/−1 (19) 20/−10 (11)

Vertical conductance 2.0 .1/−.6 (13) .4/−3 (17) .6/−6 (21) 8/−14 (14)

Primary storage coefficient 2.0 .3/.1 (19) .8/.1 (20) 12/−3 (16) 3/.1 (20)

Primary storage coefficient .5 0/−.1 (20) 0/−.8 (19) 0/−8 (20) 0/−1 (21)

Secondary storage coefficient 2.0 .3/−.1 (18) 1/−3 (16) 4/−14 (15) 4/−13 (16)

Secondary storage coefficient .5 −.2/−.8 (15) −.1/−1 (18) 9/−3 (17) 1/−3 (19)

General-head boundary conductance .1 46/30 (3) 66/31 (4) −.6/65 (7) 61/24 (9)

General-head boundary conductance 10 −6/−13 (5) −6/−13 (13) 7/−20 (12) −3/−19 (17)

All faults are not barriers — −.4/−1 (16) 4/−47 (2) 0.6/−373 (2) 54/−167 (1)

No unnamed fault — −.2/−0.7 (17) 6/−45 (3) 71/−320 (3) 61/−160 (2)

No Barrier H — 0/0 (21) 0/0 (21) 9/−61 (5) 7/−59 (5)

Artificial recharge 2.0 2/0.6 (10) 15/0.6 (8) 50/−0.1 (8) 49/0.8 (8)

Artificial recharge .5 −.3/−1 (14) −0.3/−8 (12) 0.1/−26 (13) −0.4/−26 (12)

Streambed conductance .1 −4/−10 (6) −1/−10 (10) 0/−10 (18) −0.8/−9 (18)

Streambed conductance 10 32/11 (2) 31/3 (5) 28/−0.1 (11) 22/2 (15)
Numerical Simulation of Ground-Water Flow 81

at their calibrated values. In general, the amount of 

variation for a particular input was based on reasonable 

ranges of values that would be expected in the natural 

system. Vertical conductance was varied at 0.5 and 2.0 

times its calibrated values. General-head boundary 

conductance and streambed conductance were varied 

at 0.1 and 10 times their calibrated values. Total 

recharge and hydraulic conductivity were varied at 

0.75 and 2.0 times their calibrated values. Artificial 

recharge was varied at 0.5 and 2.0 times its measured 

value. Primary and secondary storage coefficients were 

varied at 0.5 and 2.0 times their calibrated values. 

Greater variation in the total recharge, in vertical conductance, in the hydraulic conductivity, and in the primary and secondary storage coefficients, caused 

instability in the model, and the solution failed to converge. Aquifer parameters were not varied for individual layers; the values were either increased or 

decreased in all layers for a given sensitivity run. 

Horizontal-flow-barrier hydraulic characteristics for 

all faults, the unnamed fault and Barrier H each were 

set to a value of 1×1030 to represent no-barrier conditions. The sensitivity of the model to changes in irrigation-return flow and net pumpage was determined by 

variation of the irrigation return flow. An increase in 

the 

irrigation-return-flow factor is equivalent to a decrease 

in net pumpage. The converse also is true. The 

irrigation-return-flow factor was varied at 2.0 and 0.5 

times its calibrated value (30 percent).

A sensitivity analysis was performed on an 

ongoing basis during the calibration process in order to 

determine the model areas, as well as inputs, that were 

most important in affecting model-generated hydraulic 

heads at the calibration wells. In addition, considerable 

calibration effort was placed on determining reasonable values for those items that were both the most sensitive and the least well known: underflow from the 

Lytle and Bunker Hill Basins, underflow to the Chino 

and North Riverside Basins, and hydraulic characteristics of faults. Results presented in table 12 are those 

from the final sensitivity analysis of the calibrated transient (1945–96) model. The maximum and minimum 

head given in table 12 are the maximum and minimum 

differences between the calibrated head and the head 

simulated from changes in model inputs.

The sensitivities of hydraulic head to changes in 

inputs are presented in table 12. Sensitivity is ranked 

from 1 to 21, whereby the lowest rank indicates the 

most sensitive (largest deviation from zero) input and 

the highest rank indicates the least sensitive (smallest 

deviation from zero) input. The hydraulic heads in layers 1 and 2 are most sensitive to an increase (2.0×) the 

total recharge (rank 1). The hydraulic heads in layer 1 

also are sensitive to an increase (10×) in the streambed 

conductance (rank 2), a decrease (0.1×) in the generalhead boundary conductance (rank 3), and a decrease 

(0.75×) in the hydraulic conductivity (rank 4). Hydraulic heads in layer 2 also are sensitive to the removal of 

all internal faults (no barrier effect) (rank 2), the 

removal of the unnamed fault (no barrier effect) (rank 

3), and a decrease (0.1×) in the general-head boundary 

conductance (rank 4). Hydraulic heads in layer 1 are 

least sensitive to a decrease (0.5×) in the primary storage coefficient (rank 20) and the removal of Barrier H 

(rank 21). Hydraulic heads in layer 2 are least sensitive 

to an increase (2.0×) in the primary storage coefficient 

(rank 20) and the removal of Barrier H (rank 21).

Hydraulic heads in layer 3 are most sensitive to 

an increase (2.0×) in total recharge (rank 1) and 

removal of all internal faults (no barrier effect) (rank 2). 

Hydraulic heads in layer 3 also are sensitive to removal 

of the unnamed fault (rank 3), and a decrease (0.75×) in 

the hydraulic conductivity (rank 4). Hydraulic heads in 

layer 4 are most sensitive to the removal of all internal 

faults (rank 1) and the removal of the unnamed fault 

(rank 2). Hydraulic heads in layer 4 also are sensitive to 

an increase (2.0×) in total recharge (rank 3), and a 

decrease (0.75×) in hydraulic conductivity (rank 4). 

Hydraulic heads in layer 3 are least sensitive to a 

decrease (0.5×) in the primary storage coefficient (rank 

20) and an increase (2.0×) in the vertical conductance 

(rank 21). Hydraulic heads in layer 4 are least sensitive 

to an increase (2.0×) in the primary storage coefficient 

(rank 20) and a decrease (0.5×) in the primary storage 

coefficient (rank 21).

The relative sensitivity of hydraulic heads in 

layer 3 to an increase (rank 2) or decrease (rank 6) in 

total recharge may, at least in part, explain why the 

model-generated heads just southeast of Barrier J generally are too high during 1955–82 (for example, 

1N/5W-27D1 and 1N/5W-34B1) and, in the central part 

of the basin, generally are too low during 1982–96 (for 

example, 1S/5W-2K1 and 1S/5W-5A2). The largest 

increase or decrease in heads occurred in the recharge 

area northwest of Barrier J. In addition, hydraulic heads 

near the Santa Ana River and Warm Creek are too high 
82 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

during most of the simulation period (except during 

1965–72). The relative sensitivity in hydraulic heads to 

the variation in total recharge (rank 1 for layers 1,2,and 

3, and rank 4 for layer 4 to an increase in total recharge, 

and rank 6 for layers 3 and 4, and rank 7 and 8, respectively, for layers 2 and 1 to a decrease in total recharge) 

may explain, in part, this temporal distribution of 

model-generated heads, thus indicating that the spatial 

and temporal distribution of recharge may not be completely accurate.

SIMULATED EFFECTS OF ARTIFICIAL-RECHARGE 

ALTERNATIVES ON GROUND-WATER LEVELS 

AND MOVEMENT

Predictive simulations for the Rialto–Colton 

Basin were run for three artificial-recharge alternatives: continued artificial recharge at Linden Ponds, 

discontinued artificial recharge, and artificial recharge 

at Cactus Basin. To extend the ground-water flow 

model beyond 1996, average hydrologic conditions 

(natural recharge and discharge) for 1945–96 were 

used for the predictive simulation period, 1997–2027. 

Because artificial-recharge operations were discontinued at Linden Ponds in 1995, artificial-recharge values 

for 1995–99 are zero. The predictive ground-water 

flow model for the Rialto–Colton Basin (1997–2027) 

was used to simulate the water-level response in 

selected wells to continued artificial recharge at Linden 

Ponds and artificial recharge at Cactus Basin. Projected 

artificial recharge begins in 1997, and the temporal pattern of artificial recharge used was repetition of the 

artificial-recharge quantities from 1982–96 recharge 

pattern twice during 2000–2027 (see 1982–

96 recharge pattern—“recharge pattern 1”, table 13), 

with zero recharge quantities from 1997 through 1999. 

The discontinued recharge pattern (“recharge pattern 

2”) consists of zero recharge for each year during 

2000–27 (table 13). As described in the “Recharge” 

section of this report, artificial recharge in Linden 

Ponds is simulated using the well package, and the 

recharge quantities are assigned equally to two cells, 

(21, 37) and (22, 37), in layer 3. Artificial recharge in 

Cactus Basin also is simulated using the same recharge 

rate and pattern as was used at Linden Ponds. The well 

package was used to simulate artificial recharge, and 

the recharge quantities are assigned equally to cells 

(34, 42) and (35, 42) in layer 3. Water-level responses 

in layer 3 (the main producing unit) are evaluated at 

selected cluster and production wells. For comparison, 

simulated heads using discontinued artificial recharge 

are shown on all hydrographs.

 Results from the predictive simulations were 

used in conjunction with the computer model MODPATH (Pollock, 1994) to simulate advective transport 

of nonreactive constituents in imported water within the 

Table 13. Actual and projected quantities of artificial recharge in 

Linden Ponds and Cactus Basin, San Bernardino County, California, 

1997–2027

[Recharge quantities are in acre-feet]

Year Recharge pattern 1 Recharge pattern 2

1997 0 0

1998 0 0

1999 0 0

2000 3,220 0

2001 4,736 0

2002 3,471 0

2003 3,879 0

2004 5,345 0

2005 3,030 0

2006 4,601 0

2007 4,522 0

2008 65 0

2009 435 0

2010 1,559 0

2011 3,747 0

2012 261 0

2013 0 0

2014 0 0

2015 0 0

2016 3,220 0

2017 4,736 0

2018 3,471 0

2019 3,879 0

2020 5,345 0

2021 3,030 0

2022 4,601 0

2023 4,522 0

2024 65 0

2025 435 0

2026 1,559 0

2027 3,747 0
Simulated Effects of Artificial-Recharge Alternatives on Ground-Water Levels and Movement 83

Rialto–Colton Basin. MODPATH, which computes 

pathlines and travel distances, was used to track the 

movement of the imported water in layer 3 using a 

particle-tracking technique and the results of the 

ground-water flow model simulations. Layer 3 was 

selected because the imported water is recharged to 

layer 3; it also represents the main water-producing 

unit in the basin. To assess the effect that artificial 

recharge of imported water has on ground-water flow 

directions and the distance traveled, particle tracking 

was simulated using the same two temporal artificialrecharge patterns mentioned previously at Linden 

Ponds and recharge pattern 1 at Cactus Basin. In addition, particle tracking was simulated assuming discontinued artificial recharge in the Rialto–Colton Basin 

(recharge pattern 2). Because average values for 

stresses were used for the predictive simulation, a netpumpage value was assigned to all wells. Therefore, a 

well that was inactivated or destroyed sometime during 

1945–96 may capture some of the imported water. 

The use of MODPATH in this analysis assumes, 

as is generally valid for high-permeability systems such 

as layer 3 in the Rialto–Colton Basin, that the influence 

of advection will be much more important than that of 

dispersion. The use of MODPATH also assumes that 

hydraulic heads and the magnitude and direction of the 

flow velocity at any point in the model are constant 

throughout the simulation; in reality, however, hydraulic heads and flow velocities are known to be increasing 

or decreasing in response to ground-water pumping 

and (or) artificial recharge. It also was assumed that the 

lithology within a cell is constant, and that particles are 

stopped when they enter cells where discharge to sinks 

is larger than 25 percent of the total flow to the cell. It 

must be emphasized that particle-tracking simulations 

provide only a general indication of relative rates and 

directions of solute movement. 

Aquifer porosity is a required input for MODPATH simulations. Because estimates of porosity in the 

unconsolidated deposits of layers 1, 2, and 4 are not 

available for the Rialto–Colton Basin, porosities used 

in MODPATH were based on ranges of values for materials published by Freeze and Cherry (1979, p. 37). A 

porosity of 40 percent was used for model layer 1 and 

is within the range of values for gravel (25 to 

40 percent) and sand (25 to 50 percent) with interbedded clay (40 to 70 percent), which are found in the 

river-channel deposits. The porosity assigned to layer 2 

is 35 percent, which is within the range for gravel and 

sand. A porosity of 45 percent, which probably is representative of the fine-grained material found in the 

lower water-bearing unit, was used for layer 4.

For layer 3, porosity was estimated using modelcalibration techniques. Historical stable-isotope and 

tritium data for 1993 indicate that the imported water 

had moved as far as well 1N/5W-26L1 (about 1.5 mi 

from Linden Ponds) since 1982 along the axis of the 

basin between the unnamed fault and the San Jacinto 

Fault (Woolfenden, 1994). Movement probably occurs 

preferentially in the coarse-grained deposits within the 

middle water-bearing unit. In the particle-tracking 

model, a porosity of 30 percent or less was needed to 

duplicate the 1993 conditions; a porosity of 30 percent 

resulted in a simulation of imported-water movement 

no farther than well 1N/5W-26L1. Smaller values of 

porosity resulted in greater distances of imported-water 

movement. To provide a conservative estimate of the 

distance traveled by the imported water, a porosity of 

30 percent was chosen for simulation of the artificialrecharge alternatives. A porosity value of 30 percent 

also is within the range for the sand and gravel found 

within the middle water-bearing unit (layer 3). 

Continued Artificial Recharge at Linden Ponds

In this alternative, the 1982–96 artificialrecharge pattern for Linden Ponds was repeated twice 

to simulate the period 1997–2027. The water-level 

response in selected wells to the repeated 1982–96 

recharge pattern (pattern 1, table 13) at Linden Ponds 

through 2027 is shown in figure 33. Model-simulated 

water levels in cluster wells northeast of the unnamed 

fault and southeast of Barrier J (1N/5W-21K3, 

1N/5W-22N5, 1N/5W-35B3), and in production well 

(1S/4W-7C1) southeast of Barrier J, fluctuated in 

response to the temporal variability in the recharge pattern and the quantity recharged. Simulated water levels 

in wells 1N/5W-21K3, 1N/5W-22N5, 1N/5W-35B3, 

and 1S/4W-7C1 rose to their maximum level about 8 

years after the onset of the first year of nonzero 

recharge. Water levels rose by as much as 75 ft in wells 

1N/5W-22N5 and 1N/5W-21K3, as much as 50 ft in 

well 1N/5W-35B3, and as much as 30 ft in well 

1S/4W-7C1. Because in the model simulation the 

imported water is injected directly into layer 3, and not 

placed on top, the simulated rise in water levels is a lateral pressure transfer that occurs as the injected water 

displaces the native ground water. 
84 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Cr

Linden Ponds

Cactus

Basin

Diversion

canal

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

?

?

?

3407'

11722'30" R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

0

0

3 KILOMETERS

3 MILES

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately

located; dotted where concealed;

queried where doubtful

Unconsolidated deposits – Shaded

in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological

Survey 1:100,000 San

Bernardino, 1982

Box

Springs

Mts

Badlands

RIALTO-COLTON BASIN

San Gabriel Mountains

Cluster well

Production well

Simulated hydraulic head

with artificial recharge

Graphs – Shaded area indicates

predictive simulation (1997-2027)

Measured water-level altitude

Simulated hydraulic head

with discontinued artificial 

recharge

?

Other well

Discontinued

artificial recharge

With artificial recharge

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199019952000200520102015202020252030

199019952000200520102015202020252030

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2030

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2,000

ALTITUDE, IN FEET ALTITUDE, IN FEET

YEAR YEAR YEAR YEAR

YEAR

1,700

1,800

1,900

1,100

800

900

1,000

1,100

800

900

1,000

1,100

800

900

1,000

1,100

800

900

1,000

1,050

750

850

950

1,100

800

900

1,000

1,200

900

1,000

1,100

1,300

1,000

1,100

1,200

1,250

950

1,050

1,150

1,400

1,100

1,200

1,300

1,400

1,100

1,200

1,300

17K1 21K3 22N5

35B3

34D3

8E4

7C1

21K11

12L1 18F1 20H3 21N1

11F4

2K1

3A1

5A2

1,300

1,000

1,100

1,200

1,200

900

1,000

1,100

1,200

900

1,000

1,100

1,150

850

950

1,050

Predictive

simulation

 Figure 33. Location of wells, and hydrographs showing measured water-level altitudes and simulated hydraulic-head response in layer 3 for

recharge in Linden Ponds, using the 1982–96 recharge pattern and the discontinued artificial-recharge pattern, in the Rialto–Colton Basin, 

San Bernardino County, California.
Simulated Effects of Artificial-Recharge Alternatives on Ground-Water Levels and Movement 85

Simulated water levels with artificial recharge at 

Linden Ponds approximated simulated water levels 

with discontinued recharge in well 1N/15W-17K1 

northwest of barrier J, indicating that well is sufficiently isolated by faults to respond to artificial 

recharge. Model-simulated water levels rose slightly 

during 1997–2027 in wells 1S/5W-5A2, 1S/5W-3A1, 

1S/5W-2K1, 1N/5W-34D3, 1S/5W-11F4, and 

1S/4W-18F1. The magnitude of the simulated waterlevel rises decreases from northwest to southeast as the 

distance from Linden Ponds increases. A slight 

response that mimics the pattern of artificial recharge 

can be seen in the simulated water levels in these wells 

and simulated water levels rose as much 10 ft after the 

onset of artificial recharge. Simulated water levels in 

wells near the Santa Ana River and Warm Creek 

(1S/4W-21N1, 1S/4W-20H3, and 1S/4W-21K11) do 

not respond to artificial recharge and approximates 

water levels with discontinued recharge in the basin.

For the MODPATH simulation of recharge pattern 1 at Linden Ponds, particles were placed in the center of the two model cells containing Linden Ponds (fig. 

16); the model then calculated the direction in which 

these particles (representing the imported water) 

moved and the distance traveled at the end of the predictive simulation. The flow direction of imported 

water recharged at Linden Ponds in 1982 using 

recharge pattern 1 is shown in figure 34. Also shown is 

the distance traveled (about 5 mi) by the end of the predictive simulation (2027) by the imported water 

recharged in 1982. The movement of the imported 

water is southeastward and is largely restricted to the 

narrow corridor between the unnamed fault and the San 

Jacinto Fault, and nearly reaches the southeastern segment of the unnamed fault. One flow line did cross the 

unnamed fault in the vicinity of well 1S/5W-2C1. None 

of the imported water particles recharged in 1982 

reached the outflow boundary between the Rialto–

Colton Basin and the Chino and North Riverside 

Basins and no particles were captured by wells. The 

average flow velocity of the imported water was about 

900 ft/yr.

Discontinued Artificial Recharge at Linden Ponds

Results of the particle-tracking simulation for 

artificial recharge in Linden Ponds during 1982–96 are 

shown in figure 35; particle tracking depicted in figure 

35A begins in 1982 and ends in 1993. The simulation 

shows (fig. 35A) that the imported water recharged in 

1982 remains in the narrow corridor between the 

unnamed fault and the San Jacinto Fault, and just 

reaches well 1N/5W-26L1, about 1.5 mi southeast of 

Linden Ponds. The average velocity of imported-water 

movement was about 600 ft/yr. Imported water did not 

cross the unnamed fault and reach well 1N/5W-27D2, 

which was reported to contain imported water in 1993 

(Woolfenden, 1994), because the model does not simulate the unfaulted part of the alluvium that allows the 

movement of imported water to that well.

Imported water was recharged in Linden Ponds 

during 1982–93. Results of the particle-tracking simulation for artificial recharge in Linden Ponds assuming 

discontinued recharge (recharge pattern 2) at Linden 

Ponds during 1997–2027 are shown in figure 35B. In 

figure 35B, particle tracking begins in 1982 and ends in 

2027. The movement of the imported water (fig. 35B) 

is southeastward along the axis of the basin and is primarily restricted to the narrow corridor between the 

unnamed fault and the San Jacinto Fault. No flow lines 

crossed the unnamed fault and no imported water was 

captured by wells. The imported water moved about 

4 mi southeast of Linden Ponds at an average velocity 

of 700 ft/yr. 

Artificial Recharge at Cactus Basin

Results of the simulations for Cactus Basin 

showing the water-level response to recharge pattern 1, 

with artificial recharge starting in 2000 and the simulation ending in 2027, are shown in figure 36. Modelsimulated water levels in well 1N/5W-17K1 northwest 

of Barrier J steadily rose during 1997–2027, but as in 

the previous case, only in response to natural recharge. 

Again, simulated water levels in well 1N/5W-17K1 

matched those of discontinued recharge. Simulated 

water levels in wells 1N/5W-21K3, 1N/5W-22N5, 

1N/5W-35B3, and 1S/4W-7C1 southeast of Barrier J 

and northeast of the unnamed fault declined slightly, 

then flattened to a constant level during most of the 

simulation using recharge pattern 1. Simulated water 

levels did not respond to the increases and decreases of 

the pattern of artificial recharge, indicating the influence of the isolating effect of Barrier J and the unnamed 

fault (fig. 36). Water levels in wells 

1S/5W-5A2, 1S/5W-3A1, 1S/5W-2K1, and 

1N/5W-34D3 responded to the variations in recharge 

pattern 1, rising by as much as 50 ft higher than with 
86 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Highland Avenue

66

30

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

Unnamed Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

3407'

11722'30"

R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Geology modified

from Morton (1974)

Flow path –

Origin of path

?

?

?

11F1-4

10H2 8E1-4

7C1

21K1-4

22N1-6

27D2-4

28J2-3

26L1

35B1-4

34D1-4

29Q1-5

19A1

7P3

7P2

18D1

17G1

17K1

17K2

31A1

18A1

30L1

27D1

28J1

34B2 29R15

34M1 2C1

5A3

5A2 3A1 4D2

2G1

2K1

3J1 3N2 12A1

12A2

12L1

12N1

18B1,2 18G1

18F1

18M1

18K1 17M1

2E1

12N1

11F1-4 Well cluster site with number – Site at which one or

more wells are completed at different depths

Other well – Includes small domestic wells and observation

wells

Production well and number

 Figure 34. Simulated flow paths of imported water during 1982–2027, with continued recharge at Linden Ponds, using the 1982–96 recharge 

pattern in the Rialto–Colton Basin, San Bernardino County, California.
Simulated Effects of Artificial-Recharge Alternatives on Ground-Water Levels and Movement 87

Flow path –

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Avenue Highland

66

30

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J ?

?

?

?

?

?

?

?

Unnamed Fault

Barrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

RIALTO-COLTON BASIN

San Gabriel Mountains

NORTH RIVERSIDE BASIN

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

A

11F1-4

10H2

8E1-4

7C1

21K1-4

22N1-6

27D2-4

28J2-3

26L1

35B1-4 34D1-4

29Q1-5

19A1

7P3

7P2

18D1

17G1

17K1

17K2

31A1

18A1

30L1

27D1

28J1

34B2 29R15

34M1 2C1

5A3

5A2 3A1 4D2

2G1

2K1

3J1 3N2 12A1

12A2

12L1

12N1

18B1,2 18G1

18F1

18M1

18K1 17M1

2E1

12N1

11F1-4 Well cluster site with number – Site at which one or

more wells are completed at different depths

Other well – Includes small domestic wells and observation

wells

Production well and number

Origin of path

 Figure 35. Simulated flow paths of imported water in layer 3 during 1982–93 (A) and during 1982–2027 (B), with discontinued recharge at 

Linden Ponds in the Rialto–Colton Basin, San Bernardino County, California.
88 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Figure 35.—Continued.
Simulated Effects of Artificial-Recharge Alternatives on Ground-Water Levels and Movement 89

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Cr

Linden Ponds

Cactus

Basin

Diversion

canal

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

?

?

?

3407'

11722'30" R 6 W R 5 W

R 5 W R 4 W

T 1 N

T 1 S

0

0

3 KILOMETERS

3 MILES

EXPLANATION

San Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately

located; dotted where concealed;

queried where doubtful

Unconsolidated deposits – Shaded

in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

CHINO BASIN

Base from U.S. Geological

Survey 1:100,000 San

Bernardino, 1982

Box

Springs

Mts

Badlands

RIALTO-COLTON BASIN

San Gabriel Mountains

Cluster well

Production well

Simulated hydraulic head

with artificial recharge

Graphs – Shaded area indicates

predictive simulation (1997-2027)

Measured water-level altitude

Simulated hydraulic head

with discontinued artificial 

recharge

?

Other well

Predictive

simulation

Discontinued artificial recharge

With artificial

recharge

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ALTITUDE, IN FEET ALTITUDE, IN FEET

YEAR YEAR YEAR YEAR

YEAR

1,700

1,800

1,900

1,100

800

900

1,000

1,100

800

900

1,000

1,100

800

900

1,000

1,100

800

900

1,000

1,050

750

850

950

1,100

800

900

1,000

1,200

900

1,000

1,100

1,300

1,000

1,100

1,200

1,250

950

1,050

1,150

1,400

1,100

1,200

1,300

1,400

1,100

1,200

1,300

17K1 21K3 22N5

35B3

34D3

8E4

7C1

21K11

12L1 18F1 20H3 21N1

11F4

2K1

3A1

5A2

1,300

1,000

1,100

1,200

1,200

900

1,000

1,100

1,200

900

1,000

1,100

1,150

850

950

1,050

 Figure 36. Location of wells, and hydrographs showing measured water-level altitudes and simulated hydraulic-head response in layer 3 for

recharge in Cactus Basin, using the 1982–96 recharge pattern and the discontinued artificial-recharge pattern, in the Rialto–Colton Basin, 

San Bernardino County, California.
90 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

SANTA

ANA

RIVER

Lytle

Creek

Wash

Warm

Creek

San

Timoteo

Creek

Linden Ponds

Cactus

Basin

Lytle Creek

East Channel

Flood-control

basin

Diversion

canal

(Artificial-recharge site)

215

15

10

Foothill Boulevard

Sierra Avenue

Riverside Avenue

Avenue Highland

66

30

?

Cucamonga

Fault

Fault

Rialto-Colton

San

Jacinto Fault

Barrier E

Barrier J

?

?

?

?

?

Unnamed

Fault

Ba

rrier H

0

0

3 KILOMETERS

3 MILES

T 1 N

T 1 S

EXPLANATION

San

Bernardino

Colton

Rialto

Geologic contact

Fault – Dashed where approximately located;

dotted where concealed; queried where doubtful

Unconsolidated deposits –

Shaded in Rialto-Colton Basin

River-channel deposits

Partly consolidated deposits

Basement complex

BUNKER HILL BASIN

LYTLE BASIN

CHINO BASIN

Base from U.S. Geological Survey

1:100,000 San Bernardino, 1982

Box

Springs

Mts

Badlands

Colton

Narrows

San Gabriel Mountains

NORTH RIVERSIDE BASIN

Flow path –

Origin of path

R 6 W R 5 W

R 5 W R 4 W

3407'

11722'30"

Geology modified

from Morton (1974)

?

?

?

11F1-4

10H2 8E1-4

7C1

21K1-4

22N1-6

27D2-4

28J2-3

26L1

35B1-4

34D1-4

29Q1-5

19A1

7P3

7P2

18D1

17G1

17K1

17K2

31A1

18A1

30L1

27D1

28J1

34B2 29R15

34M1 2C1

5A3

5A2 3A1 4D2

2G1

2K1

3J1 3N2 12A1

12A2

12L1

12N1

18B1,2 18G1

18F1

18M1

18K1 17M1

2E1

12N1

11F1-4 Well cluster site with number – Site at which one or

more wells are completed at different depths

Other well – Includes small domestic wells and observation

wells

Production well and number

 Figure 37. Simulated flow paths of imported water during 2000–2027, with recharge in Cactus Basin using the 1982–96 recharge pattern, in 

the Rialto–Colton Basin, San Bernardino County, California.
Discussion of Results of Transient and Predictive Simulations 91

discontinued recharge. Water levels peaked about 7 

years after the onset of the first nonzero artificialrecharge year in wells 1S/5W-2K1 and 1S/5W-3A1, 

and about 8 years after the onset in well 1S/4W-11F4. 

Water levels in wells 1S/5W-12L1 and 1S/4W-11F4 

show a lesser response to recharge pattern 1 in Cactus 

Basin, rising as much as 20 ft and 25 ft, respectively, 

higher than the levels with discontinued recharge. 

Water levels in well 1S/4W-8E4 remained unchanged 

during the simulation and were about 10 ft higher than 

water levels with discontinued recharge. Water levels in 

wells near the Santa Ana River and Warm Creek 

remained unchanged during 2000–2027 for both artificial recharge and with discontinued recharge patterns, 

indicating that neither recharge pattern 1 nor natural 

recharge affects water levels in those wells over the 

period of this simulation.

Simulated flow paths of imported water 

recharged in the Cactus Basin during 2000–2027 using 

recharge pattern 1 are shown in figure 37. Particles 

were assigned to the cell centers and tracking began in 

2000 when recharge was simulated to begin. The 

imported water is shown to move in a southeastward 

direction with some lateral movement near the recharge 

basin. Two wells, 1S/5W-2K1 and 

1S/5W-3A1, capture some of the water as indicated by 

the cessation of flow lines. There also is some movement of imported water upgradient from the recharge 

basin, owing to a mounding of a large quantity of water. 

The average flow velocity of the imported water for this 

recharge alternative is about 500 ft/yr.

DISCUSSION OF RESULTS OF TRANSIENT AND 

PREDICTIVE SIMULATIONS

Effects of Artificial Recharge and the Importance 

of the Unnamed Fault

Results of the predictive simulation indicate that 

artificial recharge in Linden Ponds has little influence 

on water levels southwest of the unnamed fault but 

causes water levels to rise significantly in the narrow 

corridor between the unnamed fault and the San Jacinto 

Fault. Hydrographs in figures 33 and 36 show that natural recharge under average conditions (1945–96) does 

not enhance water levels in wells in the corridor 

between the unnamed fault and the San Jacinto Fault. 

During the zero-recharge years between artificialrecharge events (2013–2015) at Linden Ponds, water 

levels in wells responding to artificial recharge 

declined to the same levels as in earlier zero-recharge 

years (1995–99), indicating that artificial recharge is 

the primary source of recharge to those wells during 

average conditions. Water levels in wells west of the 

unnamed fault did not respond significantly to artificial 

recharge in Linden Ponds but showed a steadily 

increasing trend during 1997–2027, indicating that natural recharge under average conditions influences 

water levels west of the unnamed fault. 

The flow lines from the particle-tracking simulation of discontinued recharge did not extend as far as 

those of artificial recharge in Linden Ponds. One flow 

line did cross the central segment of the unnamed fault 

during the simulation of continued recharge at Linden 

Ponds. In addition, inspection of figures 34 and 35B

shows that during the predictive simulation (1997–

2027), imported water recharged in 1982 moved about 

1.3 mi farther during continued artificial recharge than 

during discontinued recharge. This indicates that artificial recharge in Linden Ponds has a significant effect on 

the ground-water flow system within the corridor 

between the San Jacinto Fault and the unnamed fault 

when assuming the quantities of recharge used in the 

predictive simulations. Quantities of imported water 

artificially recharged in Linden Ponds would need to be 

increased to move the imported water southwest of the 

unnamed fault to where the production wells are 

located.

The unnamed fault creates a flow compartment 

between it and the San Jacinto Fault. The inability of 

the model to simulate the movement of imported water 

southwest of the unnamed fault is a major limitation in 

addressing the issue of imported-water movement. The 

particle-tracking simulation should not be used to track 

imported water recharged in Linden Ponds southwest 

of the unnamed fault, but it could be used to show flow 

paths and average flow velocities, qualitatively, in the 

preferred flow direction along the axis of the basin. 

Additional data are needed in order to simulate, with 

confidence, the upper zone of layer 3, in which the 

unnamed fault is a less restrictive barrier that allows the 

imported water to move southwestward across the fault 

and recharge shallow wells (for example, well 

1N/5W-27D2 where the imported water was detected 

in 1993). 
92 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

2,000

3,000

4,000

1,000

0

-1,000

-2,000

-3,000

-4,000

-5,000

-6,000

1940 1950 1960 1970

YEAR

1980 1990 2000

STREAM GAINS, IN ACRE-FEET STREAM LOSSES, IN ACRE-FEET

Stream Losses from the Santa Ana River and 

Warm Creek

Seepage from the Santa Ana River and Warm 

Creek is the third largest source of recharge in the 

basin. Simulated gains and losses from the Santa Ana 

River and Warm Creek during 1945–96 are shown in 

figure 38. During this period, gains to the Santa Ana 

River and (or) Warm Creek from the aquifer occurred 

during 1945–50, 1952, 1978, 1981–86, and 1995. 

Minor quantities (about 11 and 10 acre-ft) of ground 

water flowed into the Santa Ana River and (or) Warm 

Creek in 1980 and 1987, respectively. During 1948–96, 

the Santa Ana River and Warm Creek constantly lost 

water. The main reason for this constant stream loss is 

the decline in water levels during the prolonged dry 

period during 1948–77 and the 6-year drought during 

1987–92 in California (fig. 5). Water levels recovered 

sufficiently to intersect the bottom of the streambed 

during the 1978–86 wet period. Also, the maximum 

quantity of stream loss (about 5,500 acre-ft) for many 

years probably is the maximum value that can be calculated using a streambed conductance of 0.1 ft2

/s. 

The average values for the major sources of 

recharge to and discharge from the Rialto–Colton 

Basin are given in table 14. During the 1948–77 dry 

period, seepage loss from the Santa Ana River and 

Warm Creek (4,619 acre-ft) was slightly less than that 

 Figure 38. Simulated gains and losses from the Santa Ana River and Warm Creek, 1945–96, in the Rialto–Colton Basin, San Bernardino 

County, California.
Discussion of Results of Transient and Predictive Simulations 93

of the 1945–96 average (4,863). After the 1948–77 dry 

period, water levels in the vicinity of the Santa Ana 

River and Warm Creek recovered quickly. In 1978, 

about 380 acre-ft of ground water flowed into the Santa 

Ana River and (or) Warm Creek along some reaches. 

Ground water continued to flow into the river and (or) 

creek every year, except 1979, during 1978–86 wet 

period. The maximum gain (1,070 acre-ft) during this 

period occurred in 1984.

The average values in table 14 suggest that the 

lower water levels are primarily due to increases in 

pumpage and underflow to the Chino and North Riverside Basins, and a decrease in underflow from the Lytle 

Basin during the 1948–77 dry period and the 1987–92 

drought. A decrease in underflow from the Bunker Hill 

Basin also contributed to lower water levels during 

1987–92. Underflow to the Chino and North Riverside 

Basins was greater than the long-term average (1945–

96) during the 1948–77 dry period; it decreased to 

below the average during the 1978–86 wet period, and 

it then increased again during the 1987–92 drought. 

This is consistent with increased pumping in the Chino 

and North Riverside Basins, which creates a greater 

hydraulic gradient toward these basins, thus inducing 

greater quantities of outflow from the Rialto–Colton 

Basin. Discharge from pumping in the Rialto–Colton 

Basin also contributed to the general decline of water 

levels. Pumpage was slightly greater than the longterm average (11,078 acre-ft) during 1948–77, which 

was about 31 percent of outflow from the basin. Pumping decreased during the 1978–86 wet period, and then 

increased to about 1.37 times the long-term average 

during the 1987–96 drought. Underflow from the Lytle 

Basin was about 83 percent of the long-term average 

during 1948–77 and about 73 percent during 1987–92. 

During the 1978–86 wet period, underflow from the 

Lytle Basin was about 1.42 times that of the long-term 

average. Underflow from the Bunker Hill Basin slightly 

was slightly higher than the long-term average during 

1948–77. This is consistent with the increased pumping 

in the Rialto–Colton Basin that would create greater 

hydraulic gradients across the San Jacinto Fault. During 

the 1987–92 drought, underflow from Bunker Hill 

Basin was about 78 percent that of the long-term average. 

Underflow from the Rialto–Colton Basin to the 

Chino and North Riverside Basins

The long-term (1945–96) average underflow 

from the Rialto–Colton Basin to the Chino and North 

Riverside Basins is the main source of discharge from 

the Rialto–Colton Basin, constituting about 68 percent 

of total discharge (fig. 32). This is an indication that the 

Rialto–Colton Basin is not intensely developed (longterm pumpage is 31 percent of total discharge). Under 

extreme drought conditions and (or) as a result of population growth in the basin, pumpage increases slightly 

(37 percent of total discharge in 1996). The annual 

quantities of simulated underflow and net pumpage 

during 1945–96 are shown in figure 39. During most 

years of the 1945–96 simulation period, underflow 

quantities exceeded pumpage quantities by a considerable amount. Pumpage exceeded underflow in ten years 

during the simulation period, 1958, 1966, 1968–70, 

1978, and 1992–95. In 1992, underflow and pumpage 

were nearly equal. 1969, 1978, 1993, and 1994 were 

wet years. 1970 and 1995 were dryer years, and water 

levels remained high, thus maintaining shallower 

hydraulic gradients across the Rialto–Colton Fault. In 

1969 and 1970, pumpage exceeded underflow considerably (by about 10,160 and 8,100 acre-ft, respectively) and was only about 13 percent and 29 percent, 

Table 14. Average values of major sources of recharge and discharge in the Rialto–Colton Basin, San Bernardino County, California

[All values are in acre-feet]

Time 

period

 Recharge Discharge

Bunker Hill 

underflow

Lytle Basin 

underflow

Seepage 

loss

Ungaged 

runoff

Irrigation return 

flow

Underflow to 

Chino Basin Pumpage

1945–96 11,377 8,931 4,863 3,042 3,323 23,746 11,078

1948–77 11,990 7,457 4,619 2,598 3,372 24,956 11,241

1978–86 11,446 12,722 5,475 4,710 2,214 20,580 7,380

1987–92 9,363 6,486 5,500 2,226 4,558 26,007 15,193

1993–96 8,205 13,887 5,539 3,134 4,565 17,520 15,217
94 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

1940 1950 1960 1970

YEAR

1980 1990 2000

PUMPAGE OR UNDERFLOW, IN ACRE-FEET

Underflow

Pumpage

respectively, of pumpage. In 1978, there was zero 

underflow to the Chino and North Riverside Basins. 

During the 1987–92 statewide drought in California, 

pumpage in the Rialto–Colton Basin increased, but 

underflow still was significantly greater until 1991, 

indicating that pumping in the Chino and North Riverside Basins created hydraulic gradients large enough to 

induce a considerable quantity of underflow from the 

Rialto–Colton Basin.

During several years (1958, 1966, 1969, 1970, 

1972, 1978, and 1980), simulated underflow from the 

Chino Basin to the Rialto–Colton Basin occurred along 

the outflow boundary in some areas. Higher-thanaverage precipitation occurred during most of these 

years (1958, 1969, 1978, and 1980), which would produce high water levels. These high water levels could 

cause either a reversal of the hydraulic gradient toward 

the Rialto–Colton Basin, creating underflow into the 

basin from the Chino Basin, or conditions that would 

cause ground water to flow freely from one basin to the 

other (Sam Fuller, SBVMWD, oral commun., 2000). 

Quantities of underflow into the Rialto–Colton Basin 

ranged from 86 acre-ft in 1966 to 7,543 acre-ft in 1978 

(no ground-water outflow occurred during 1978). Precipitation during 1970 was below average; however, 

water levels probably remained relatively high, thus 

allowing the reversed hydraulic gradients or freely 

moving ground-water conditions to be maintained. Precipitation during 1972 was well below average, yet 498 

acre-ft of ground water flowed into the Rialto–

Colton Basin from the Chino Basin. This implies that 

either pumpage in the Rialto–Colton Basin near the 

Santa Ana River exceeded that in the Chino Basin in 

the same area, thus creating a reversal of gradient, or 

that the model does not simulate underflow as accurately during this year as during other years. 

 Figure 39. Net pumpage and simulated underflow from the Rialto–Colton Basin to the Chino and North Riverside Basins, 1945–96, San 

Bernardino County, California.
Discussion of Results of Transient and Predictive Simulations 95

0

5,000

10,000

15,000

20,000

25,000

1940 1960 1970 1950

YEAR

1980 1990 2000

UNDERFLOW FROM LYTLE BASIN, IN ACRE-FEET

Underflow from the Lytle Basin to the Rialto–

Colton Basin

The simulated quantity of underflow from the 

Lytle Basin to the Rialto–Colton Basin during 1945–96 

is shown in figure 40. With the exception of a few wet 

years, underflow values for the 30-year dry period during 1948–77 were comparatively small (less than the 

long-term average of about 8,931 acre-ft). In 1961, 

underflow from the Lytle Basin was only 31 percent of 

the long-term average. Average underflow during 

1948–77 period was about 7,457 acre-ft (table 14), 

16 percent lower than the long-term average. Average 

underflow during the 1978–86 wet period was 

12,722 acre-ft, significantly higher (42 percent) than 

the long-term average (table 14). During the 1987–92 

drought, the average underflow was about 

6,486 acre-ft, 73 percent of the long-term average. 

Underflow from the Lytle Basin to the Rialto–

Colton Basin is influenced by the quantity of discharge 

in Lytle Creek. Water levels in well 1N/5W-17K1 

respond rapidly to streamflow in Lytle Creek, and 

water sampled from this well was tritiated, indicating 

recent (less than 50 years old) recharge (Woolfenden 

and Kadhim, 1997). It should be mentioned, however, 

that the source of underflow may not be entirely from 

streamflow in Lytle Creek. The method of using Lytle 

Creek discharge values to obtain underflow values was 

simply a way to quantify a largely unknown value. 

Underflow values from the Lytle Basin to the Rialto–

Colton Basin used in the calibrated model of the Bunker Hill and Lytle Basins were held constant during 

1945–96 (W.R. Danskin, USGS, written commun, 

1999). This method was tried initially in the construction and calibration of the flow model for the Rialto–

Colton Basin, but it was quickly evident that underflow 

 Figure 40. Simulated underflow from the Lytle Basin to the Rialto–Colton Basin, 1945–96, San Bernardino County, California.
96 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

0

LYTLE CREEK DISCHARGE, IN ACRE-FEET

1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000

Mean + two standard deviations

32,377 acre-feet + 66,700 acre-feet

= 99,077 acre-feet

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

from Lytle Basin greatly influences the variability in 

basinwide water levels.

During model calibration, the quantity of underflow from Lytle Basin was adjusted until simulated 

water levels matched measured water levels in well 

1N/5W-17K1 by multiplying the discharge in Lytle 

Creek by 35 percent if discharge was less than two standard deviations above the mean annual discharge, and 

15 percent if discharge was greater than or equal to two 

standard deviations above the mean (fig. 41). Two standard deviations above the mean annual discharge is 

99,077 acre-ft. In each of the two categories of Lytle 

Creek discharge, an increase in discharge results in an 

increase in underflow. Five years (1969, 1978, 1980, 

1983, and 1993) of exceptionally high discharge occur 

in the 15 percent category (fig. 41). It is possible to 

obtain underflow values during these high-discharge 

years that are less than those during other years using 

this method. This result is supported by the calculation 

of underflow from the Bunker Hill Basin, which was 

made using hydraulic gradients. During exceptionally 

wet years such as 1969, 1978, 1980, 1983, and 1993, 

hydraulic gradients generally were shallower than during normal or dryer years, resulting in smaller quantities of underflow from the Bunker Hill Basin than 

during other years. 

The percent-of-discharge method is one way to 

base calculation of underflow on real data. It is not necessarily the best method of estimation. Installation of 

shallow wells in the Lytle Basin and northwestern 

Rialto–Colton Basin, and long-term water-level monitoring would provide needed data to validate this 

method or to calculate underflow using a more robust 

method.

Underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin

Underflow from the Bunker Hill Basin to the 

Rialto–Colton Basin is a significant source of recharge. 

The quantities of underflow initially used in model 

 Figure 41. Annual discharge in Lytle Creek, 1945–96, San Bernardino County, California.
Discussion of Results of Transient and Predictive Simulations 97

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

1940 1945 1950 1955 1960 1965 1970

YEAR

1975 1980 1985 1990 1995 2000

UNDERFLOW, IN ACRE-FEET

construction and calibration were based on a linearregression relation used in the Bunker Hill and Lytle 

model (W.R. Danskin, USGS, written commun., 1997). 

During model calibration, however, the quantities of 

underflow required adjustment in order to match simulated water levels with measured water levels. Shown in 

figure 42 are the underflow values used in the Rialto–

Colton model. 

As mentioned previously (see “Underflow” subsection [“Flow-Model Construction” section]), underflow from the Bunker Hill Basin was based on 

calculation of Darcy’s Law. These estimates did not 

follow the same wet- and dry-period trend as did that 

from the Lytle Basin. During the 1948–77 dry period 

and the 1978–86 wet period, underflow from the Bunker Hill Basin was not significantly different (greater 

by about 5 percent and 1 percent, respectively) from 

that of the long-term average. Pumping during the dry 

period also was not significantly different (about 2 percent greater) than the long-term average pumping. During the wet period, however, pumping was 

considerably greater (33 percent) from the long-term 

average. This indicates that overall decreases in pumping and rises in water-levels the Rialto–Colton Basin 

during the wet period matched those in the Bunker Hill 

Basin in order to maintain the overall hydraulic gradients equivalent to those during 1948–77 and, as a 

result, roughly equivalent values of underflow. During 

the 1987–92 drought, underflow was only about 82 percent of the long-term average. Pumping in the Rialto–

Colton Basin, however, was considerably greater 

(about 37 percent) than the long-term average. The 

additional pumping in the Rialto–Colton Basin did not 

induce greater underflow across the San Jacinto Fault, 

indicating that water levels in the Bunker Hill Basin 

had declined sufficiently to decrease the hydraulic gradient across the San Jacinto Fault to less than the longterm average and less than during the previous dry and 

wet periods. A shallow hydraulic gradient combined 

with a decline in water levels, and thus, less saturated 

thickness, results in quantity of underflow smaller than 

that during the previous dry and wet periods, and 

smaller than the long-term average. 

 Figure 42. Simulated underflow from the Bunker Hill Basin to the Rialto–Colton Basin, 1945–96, San Bernardino County, California.
98 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

USE AND LIMITATIONS OF GROUND-WATER 

FLOW AND PARTICLE-TRACKING MODELS

The ground-water flow model can best be used 

as a tool for comprehensively analyzing hydrologic 

processes in the Rialto–Colton Basin. The model incorporates all available data for the system and calculates 

quantitative estimates of flows and heads, including 

their spatial and temporal variations. The model was 

designed to answer general questions regarding basinwide ground-water flow directions, to refine the existing conceptual model, and to evaluate boundary 

conditions, water budgets, and the effects of artificial 

recharge on the ground-water flow system. 

The model also can be used as a guide for future 

data collection. For example, the inability of the model 

to simulate the flow of imported water across the 

unnamed fault during 1982–93 points to the need for 

collection of data in the upper part of layer 3, where the 

imported water probably occurs. Definition of the location and extent of the unnamed fault both laterally and 

vertically with surface geophysics, drilling of shallow 

wells, collection of water-chemistry data, and longterm water-level monitoring would lend confidence to 

a finer vertical discretization of layer 3 in the vicinity 

of the artificial-recharge ponds. Another example of 

using the model as a guide to direct future data collection is the need to collect seepage data along the Santa 

Ana River and Warm Creek. These data would provide 

additional calibration targets that would help further 

constrain the model; they also would help in assessing 

the estimated quantities of underflow from the Bunker 

Hill Basin to the Rialto–Colton Basin and modelcalculated quantities of underflow from the Rialto–

Colton Basin to the Chino and North Riverside Basins.

Although a ground-water model can be a useful 

tool for investigating aquifer response, it is a simplified 

approximation of the actual system based on average or 

estimated conditions, and the accuracy of its predictions are dependent on the accuracy of the input data. 

The flow model has been calibrated to observed longterm and short-term trends of hydraulic heads throughout the basin. Deviation of simulated hydraulic heads 

from measured water levels results from simplifications associated with the system conceptualization; 

errors in estimated aquifer characteristics and model 

parameters; errors of estimated or measured recharge, 

discharge, or historical water levels; and errors associated with the numerical-solution procedure. 

During the course of model calibration, adjustments to the conceptual model could be required in 

order to match water levels adequately. Generally, the 

numerical model can be a useful tool in understanding 

a ground-water flow system. However, data are not 

areally extensive enough to provide a completely accurate determination of physical features. In this study, 

flow barriers were reoriented and extended to better 

simulate elevated water levels in given areas. In addition, initial estimates of bottom altitudes of model layers were decreased by as much as 400 ft immediately 

southwest of Barrier J to represent altitudes based on 

historical data and to prevent the drying of model cells 

where the water levels were known not to have declined 

below a given water-bearing unit (model layer). 

Simplifications described in the flow model 

“Assumptions” section of this report can contribute to 

errors that might affect the model’s accuracy. Simplifications include representing the middle water-bearing 

unit as one layer. The middle water-bearing unit consists of two zones: an upper zone that can contain 

perched water (a saturated zone not connected to the 

main aquifer owing to its location overlying a lowpermeability layer) and a lower zone that is the main 

water-producing zone in the basin. Because few waterlevel data are available for the upper zone and the areal 

extent of the clay lens separating the zones is not well 

known, the upper zone was not simulated as a separate 

layer. The upper zone, however, is important because 

the imported water probably has moved, to date, only 

in this zone. Another simplification is that layer 3 is the 

only active layer occurring northwest of Barrier J. Few 

subsurface data exist northwest of Barrier J. The presence of layer 3 northwest of Barrier J is based on the 

chemistry of the water in well 1N/5W-17K1 

(Woolfenden and Kadhim, 1997), which is consistent 

with that of the water in wells perforated in the middle 

water-bearing unit southeast of Barrier J and southwest 

of the unnamed fault. 

The assumption of no-flow boundary conditions 

along most of the San Jacinto Fault and the Rialto–

Colton Fault also may contribute to errors. Ground 

water may flow in the unfaulted part of the alluvium 

from the Bunker Hill Basin to the Rialto–Colton Basin 

over the top of the San Jacinto Fault and from the 

Rialto–Colton Basin to the Chino Basin over the top of 

the Rialto–Colton Fault. Other simplifications include 

the simulation of clay lenses with a verticalconductance value instead of a separate layer; an 
Use and Limitations of Ground-Water Flow and Particle-Tracking Models 99

assumption of homogeneity of the layers where there 

may be heterogeneities within the basin that are currently (1999) unknown; and the assumption of an 

absence of faults southeast of Barrier J and west of the 

unnamed fault where faults may exist. The simplification of using a constant 30-percent irrigation-returnflow factor for the entire transient simulation period 

(1945–96) also could have a significant effect on model 

results. Future work should include a variable returnflow factor to account for changes in land use from 

agricultural (higher return flow) to urban (lower return 

flow).

The method for accounting for irrigation return 

flow assumes that irrigation return occurs immediately; 

whereas, in areas where there is a thick unsaturated 

zone (such as in the Rialto–Colton Basin), return flow 

may take years to reach the water table. This delay 

could have a significant effect on timing of actual 

water-level declines and recoveries.

There are limitations and errors specific to the 

use of horizontal-flow barriers in simulating faults 

internal to the Rialto–Colton Basin. These limitations 

and errors include uncertainty as to the degree of 

hydraulic connection between the fault-bounded compartments within the basin, the fact that the model does 

not account for storage effects in the horizontal-flow 

barriers, and the uncertainty of the estimated hydraulic 

characteristic assigned to each barrier. Errors in the 

number, location, and estimated hydraulic characteristics of the horizontal-flow barriers can affect both initial-conditions and transient simulations. Errors 

introduced by omission of the storage properties of the 

barriers will be manifested only during transient simulations.

Recharge, discharge, and water levels generally 

are considered to have been measured or estimated correctly. However, errors in these values can be a serious 

concern because they directly affect model values of 

aquifer characteristics and (or) model parameters. For 

example, inaccuracies in water-level measurements 

that are used in model calibration can directly affect the 

model value obtained through model calibration. The 

quantity of underflow from the Lytle Basin was determined by increasing or decreasing estimates until simulated head approximated measured water-level 

altitudes at well 1N/5W-17K1. If actual water-level 

measurements for well 1N/5W-17K1 were higher or 

lower than those used, different values of underflow 

would have been obtained. Thus, a greater certainty in 

the values of one input will generally translate into a 

lessening of the uncertainty in the values of the other.

The numerical model is based on the “groundwater flow” equation, which is an approximation used 

to characterize ground-water flow systems, and the 

equation describes the time-varying hydraulic-head 

configuration in three dimensions for ground water of 

constant density in a porous medium. The equation 

takes into account major influence factors and neglects 

others. Analytical solutions to the ground-water flow 

equation are valid through continuous space and time 

intervals, but solutions to the equations used in the 

numerical model (approximations to the ground-water 

flow equation) are valid only at discrete locations at 

specified times. The numerical model can calculate 

flow rates from the hydraulic-head information it generates, but they are not a direct solution result.

As the number of model-grid cells is increased 

and the length of model stress periods is reduced, 

results calculated by the numerical model will 

approach the exact solution to the ground-water flow 

equation. In general, the numerical model is an approximation, but experience has shown that it is a good one. 

Nonetheless, a certain amount of error is introduced by 

these approximations. Additional error is introduced by 

assuming that hydraulic conductivity and specific storage (or storage coefficient) are strictly functions of 

location and not of both location and time. Other errors 

result from truncation of numeric values or selection of 

convergence criterion or are associated with the particular numerical procedure used to solve the model equations. Usually, these errors are not serious.

Care should be used in interpreting model results 

where the model is poorly calibrated, such as near Barrier H and in the vicinity of well 1N/5W-27D1, or 

where available data are sparse, such as northwest of 

Barrier J. Poorly calibrated parts of the model reflect 

site-specific inaccuracies in conceptualization of the 

ground-water flow system owing to lack of information; significant errors can be introduced where few 

data are available. 

Limitations specific to the MODPATH simulations include those associated with discretization and 

those associated with uncertainty of parameters and 

boundary conditions. The degree of spatial discretization influences the level of detail at which hydrogeologic and system boundaries can be represented, the 

accuracy of velocity calculations, and the ability to 

accurately and unambiguously represent internal sinks 
100 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

(Pollock, 1994). The discretization of the Rialto–

Colton model represents the hydrogeologic and system 

boundaries with adequate accuracy. The constant grid 

spacing of the Rialto–Colton model introduces error in 

the velocity calculations near strong sources or sinks. 

Where the model grid contains a strong source or sink, 

such as near the recharge ponds or large production 

wells, finer discretization in the vicinity of the source 

or sink would produce more accurate calculations of 

velocity. The effect of spatial discretization on the representation of internal sinks is especially important for 

particle-tracking analyses because of the ambiguity 

associated with the movement of particles through 

weak sink cells. These cells contain sinks that do not 

discharge at a large enough rate to consume all of the 

water entering the cell (Pollock, 1994). Although it was 

assumed that some of the particles would pass through 

cells with weak sinks, there is no way to know whether 

a specific particle should discharge to the sink or pass 

through it. The uncertainty associated with this limitation, however, may not be large because of the lack of 

production wells in the direction of flow of imported 

water from the artificial-recharge ponds. 

The uncertainty in parameters and boundary 

conditions is the most important limitation in both the 

ground-water-flow and particle-tracking analyses. 

The use of estimated values of aquifer characteristics 

(such as hydraulic conductivity, storage coefficient, 

and vertical hydraulic conductivity) and model parameters (conductance of the general-head boundary 

between the Rialto–Colton Basin and the Chino and 

North Riverside Basins and the fault hydraulic characteristics) will introduce error into the model. These 

errors are difficult to quantify because both aquifer 

characteristics and model parameters were obtained, 

for the most part, through model calibration. The 

uncertainty of the location of the Rialto–Colton Fault 

boundary also will introduce error into the model. 

Uncertainty associated with aquifer characteristics may 

be relatively small because, overall, the model is not as 

sensitive to aquifer characteristics as it is to the model 

parameters. Uncertainty in the numerical representation of boundary conditions requires that interpreting 

model results near boundaries should be done with 

care. 

As mentioned previously in the “Simulated 

Effects of Artificial-Recharge Alternatives on GroundWater Levels and Movement” section, imported-water 

particles in the MODPATH simulations did not reach 

well 1N/5W-27D2 in 1993 (fig. 35A). However, 

imported water was presumed to be detected in that 

well in 1993 on the basis of stable-isotope data 

(oxygen-18 and deuterium) collected for Phase 1 of this 

study (Woolfenden, 1994). The current conceptualization of the ground-water flow system, which is based 

on available geohydrologic data, does not account for a 

mechanism that would allow significant quantities of 

water to move across the unnamed fault in layer 3, and 

thus be detectable at well 1N/5W-27D2. A clay lens 

separates the middle water-bearing unit (layer 3) into 

two zones near the Linden Ponds artificial-recharge 

site, and the imported water probably moves across the 

unnamed fault in the upper zone of this unit where the 

fault may be a less restrictive barrier. Hence, results of 

the ground-water flow model and the particle-tracking 

model, in this regard, demonstrate the applicability of 

collecting and analyzing additional data, such as those 

that can be obtained from drilling relatively shallow 

test-monitoring wells and performing aquifer tests 

(which were beyond the scope of this study). These 

data would refine the conceptual and mathematical 

models of the Rialto–Colton ground-water basin. 

Nonetheless, it is believed that, in general, the current 

models offer valuable insight into the gross behavior of 

the ground-water flow system and the movement of 

imported water.

SUMMARY AND CONCLUSIONS

The Rialto–Colton Basin trends northwestsoutheast; its width is about 3.5 mi in the northwest and 

about 1 mi in the southeast, and its length is about 

10 mi. The basin is bounded on the northeast by the San 

Jacinto Fault and on the southwest by the Rialto–

Colton Fault. The San Gabriel Mountains and the Badlands form the northwestern and southeastern boundaries, respectively. Consolidated deposits underlie the 

basin and form its lower boundary. Ground-water 

movement is from east to west in the river-channel 

deposits; from northwest to southeast and from east to 

west in the upper water-bearing unit; and along the axis 

of the basin from northwest to southeast in the middle 

and lower water-bearing units. Three internal 

barriers—Barrier J, Barrier H, and an unnamed 

fault—restrict ground-water movement to various 

degrees within the Rialto–Colton Basin. The location 

and extent of Barrier H and the unnamed fault were 

modified during model calibration.
Summary and Conclusions 101

The ground-water flow system in the Rialto–

Colton Basin consists of unconsolidated and partly 

consolidated deposits of gravel, sand, silt, and clay. The 

ground-water flow system is divided into four waterbearing units: the river-channel deposits, and the upper, 

middle, and lower water-bearing units. Thickness of 

the water-bearing units varies within the basin. Thickness of the middle water-bearing unit, which is the 

main water-producing unit in the basin, ranges from 

about 240 to 600 ft. 

Sources of recharge to the Rialto–Colton Basin 

are underflow from the Lytle and Bunker Hill Basins; 

seepage loss from the Santa Ana River, Warm Creek, 

and the diversion canal; surface spreading of imported 

water; ungaged runoff from the San Gabriel Mountains 

and the Badlands, and subsurface inflow; irrigation 

return flow; and areal recharge of rainfall. The components of discharge from the Rialto–Colton Basin are 

pumpage, underflow from the Rialto–Colton Basin to 

the Chino and North Riverside Basins, seepage loss 

from the aquifer to the Santa Ana River and Warm 

Creek, and evapotranspiration. 

A three-dimensional finite-difference model, 

MODFLOW, was used to simulate and evaluate 

ground-water flow in the Rialto–Colton Basin. The 

ground-water flow system was divided into four layers 

that represent the river-channel deposits, and the upper, 

middle, and lower water-bearing units. A particletracking model, MODPATH, was used to simulate 

advective transport of imported water within the flow 

system for three artificial-recharge alternatives.

The flow model was calibrated to transient conditions for 1945–96. A simulation was made to provide 

initial conditions for the transient-state simulation by 

using 1945 recharge and discharge rates, and assuming 

no change in storage. For the initial conditions, the 

model-simulated hydraulic heads generally matched 

measured water levels more closely in wells in the central and southeastern parts of the basin than in other 

parts of the basin. For transient conditions, the modelsimulated hydraulic heads generally matched water 

levels more closely in wells northwest of Barrier J, in 

the northwestern part of the basin just southeast of Barrier J during 1982–96, and in the central part of the 

basin during 1945–82. In addition, water levels were 

matched adequately east of the unnamed fault during 

the transient simulation. 

Total recharge in 1945 was about 34,920 acre-ft 

for the initial-conditions simulation. Combined underflow from the Bunker Hill and Lytle Basins accounted 

for about 70 percent of recharge to the basin in 1945 for 

the initial-conditions simulation. Seepage loss 

accounted for about 9 percent in 1945 for the initial 

conditions. Total discharge for 1945 initial conditions 

was 34,940 acre-ft. Underflow from the Rialto–Colton 

Basin to the Chino and North Riverside Basins 

accounted for about 71 percent of total discharge, and 

pumpage accounted for about 19 percent. 

Average total recharge for the 1945–96 transient 

simulation was 33,620 acre-ft. Average total discharge 

was 35,220 acre-ft, indicating that, for longer periods, 

overdraft conditions may exist but are not significant 

(about 5 percent of average total recharge). Underflow 

from the Bunker Hill and Lytle Basins accounted for 

about 60 percent of total recharge. Seepage loss from 

the Santa Ana River and Warm Creek accounted for 

about 15 percent of total recharge. During 1945–96, an 

average of 7,350 acre-ft of water was removed from 

storage and an average of 5,960 acre-ft of water went 

into storage. Underflow to the Chino and North Riverside Basins accounted for about 68 percent of total discharge. The net average storage depletion was about 

1,390 acre-ft/yr.

Total recharge for the 1996 transient simulation 

was 31,830 acre-ft and total discharge was 

42,200 acre-ft. The net average reduction in storage 

(net average recharge minus net average discharge) was 

10,370 acre-ft/yr. Underflow from the Lytle and Bunker Hill Basins accounted for about 58 percent of total 

recharge. Seepage loss from the Santa Ana River and 

Warm Creek accounted for about 18 percent of total 

recharge. Pumpage and underflow from the Rialto–

Colton Basin to the Chino and North Riverside Basins 

were higher than the 1945–96 averages. The quantity of 

water coming out of storage was 

11,110 acre-ft and the quantity of water going into storage was 720 acre-ft. Storage depletion was 

10,390 acre-ft.

A sensitivity analysis was done to determine the 

model inputs that were most important in affecting 

model-generated hydraulic heads at the calibration 

wells. In addition, considerable calibration effort was 

placed on determining reasonable values for those 

items that were both the most sensitive and least well 

known. In layers 1, 2 and 3, hydraulic heads were most 

sensitive to an increase in total recharge. Hydraulic 

heads in layer 1 also are sensitive to an increase in the 

streambed conductance. Hydraulic heads in layers 2 

and 3 also are sensitive to removal of all internal barrier 

conditions. In layer 4, hydraulic heads were most sen-
102 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

sitive to the removal of all internal barriers and removal 

of the unnamed fault. Hydraulic heads were least sensitive in layer 1 to a reduction in the primary storage 

coefficient and the removal of Barrier H; in layer 2, to 

an increase in the primary storage coefficient and the 

removal of Barrier H; in layer 3, to a decrease in the primary storage coefficient and an increase in the vertical 

conductance; and in layer 4 to an increase in the primary storage coefficient and a decrease in the primary 

storage coefficient.

The goal of artificial recharge in the Rialto–

Colton Basin is to store imported water during wet periods for use during dry periods. To achieve this goal, it 

is desirable for the imported water to be available to 

production wells within the basin. Predictive simulations were made for three artificial-recharge alternatives: continued artificial recharge at Linden Ponds, 

discontinued artificial recharge in the Rialto–Colton 

Basin, and artificial recharge at Cactus Basin. To 

extend the ground-water flow model beyond 1996, 

average hydrologic conditions (natural recharge and 

discharge) for 1945–96 were used for the predictive 

simulation period (1997–2027). Two recharge patterns 

were evaluated for the artificial-recharge alternatives: 

using the 1982–94 recharge quantities in Linden Ponds 

(pattern 1) and discontinuing recharge at Linden Ponds 

(zero recharge, pattern 2). Years of zero recharge were 

included between the 13-year periods of recharge for 

pattern 1. Particle-tracking simulations were made for 

all three artificial-recharge alternatives. For recharge at 

Linden Ponds, particle tracking began in 1982. For 

recharge at Cactus Basin, particle tracking began in 

2000.

For continued recharge at Linden Ponds using 

recharge pattern 1, lack of significant water-level 

response from artificial recharge in wells southwest of 

the unnamed fault and northwest of Barrier J indicate 

that recharging in Linden Ponds using recharge pattern 

1 is not an effective method of raising water levels in 

the area that has the most production wells in the basin. 

Water levels near Warm Creek and the Santa Ana River 

were not affected by artificial recharge at Linden 

Ponds.

Results of the particle-tracking simulation for 

artificial recharge at Linden Ponds starting in 1982 and 

ending in 2027 indicate that the water recharged in 

1982 remained in the narrow corridor between the 

unnamed fault and the San Jacinto Fault and moved 

southeastward from Linden Ponds a distance of about 5 

mi. The imported water moved at an average velocity of 

900 ft/yr. One flow line crossed the central part of the 

unnamed fault, indicating that in ensuing years, the 

imported water may reach one of the current (1996) 

main pumping areas.

Results of the particle-tracking simulation for 

discontinued recharge in the Rialto–Colton Basin 

under average hydrologic conditions for an extended 

period (1982–2027 in this case), indicate that natural 

recharge was sufficient to move some imported water 

recharged during 1982–94, a distance of about 4 mi. 

None of the flow lines crossed the unnamed fault. The 

average velocity of imported-water movement was 

700 ft/yr.

The water-level response to recharge pattern 1 

starting in 2000 and ending in 2027 at Cactus Basin 

indicates that wells northwest of Barrier J and northeast 

of the unnamed fault are sufficiently isolated by the 

faults to be affected. Water levels southeast of Barrier 

J and north of the Santa Ana River and Warm Creek 

rose as much as 50 ft higher than discontinued recharge 

levels. Water levels near the Santa Ana River and Warm 

Creek again were not affected, indicating that a longer 

period of recharge would be needed to raise water levels in this area.

Simulated flow paths of imported water 

recharged in Cactus Basin using recharge pattern 1 

beginning in 2000 and ending in 2027 showed that 

water moved southeastward, with an average velocity 

of about 500 ft/yr. Two production wells captured some 

of the water. 

Results of all the predictive simulations, which 

are based on the current conceptualization of the 

Rialto–Colton Basin ground-water system, indicate 

that artificial recharge at Cactus Basin may be more 

effective than recharge at Linden Ponds at raising water 

levels in a greater part of the basin and that the 

imported water can be captured by production wells 

using recharge pattern 1. One flow line generated by 

recharge in Linden Ponds in 1982 crossed the unnamed 

fault but did not reach a production well. Artificial 

recharge at Cactus Basin raises water levels more effectively southeast of the unnamed fault where production 

wells are located, and artificial recharge at Linden 

Ponds raises water levels more effectively northeast of 

the unnamed fault. 

The model is able to duplicate hydraulic heads 

fairly accurately northwest of Barrier J, just southeast 

of Barrier J in the northwest part of the basin during 
References Cited 103

1982–96, and in the central part of the basin during 

1945–82. Where the conceptualization of model layers 

is oversimplified, however, the accuracy of the model is 

less certain. As a predictive tool, the ground-water flow 

model can provide qualitative information about flow 

directions and water-level changes and can be used to 

test alternative conceptualizations of the ground-water 

flow system. Alternative artificial-recharge scenarios 

can be used to predict water-level trends and track 

water particles from the recharge source for various 

time periods. Different artificial-recharge locations can 

be tested throughout the basin. Other management 

issues, such as changes in pumping patterns and quantities, also can be tested. Both the ground-water-flow 

and particle-tracking models should be used for longterm trends over broad areas rather than focusing on 

site-specific simulations.

REFERENCES CITED

California Department of Water Resources, 1970, Meeting 

water demands in the Chino-Riverside area: Bulletin 

No. 104-3, 27 p.

Dutcher, L.C., and Garrett, A.A., 1963 [1964], Geologic and 

hydrologic features of the San Bernardino area, 

California—with special reference to underflow across 

the San Jacinto fault: U.S. Geological Survey WaterSupply Paper 1419, 114 p.

Freeze, R.A., and Cherry, J.A., 1979, Groundwater: Englewood Cliffs, N.J., Prentice-Hall, Inc., 604 p.

Geosciences Support Services, Inc., 1992, Wellsite evaluation of a portion of the Rialto–Colton Basin northwest 

of Barrier J: 12 p.

——— 1994, Opinions as to conditions in the Rialto–Colton 

ground water basin: 31 p.

Hardt, W.F., and Hutchinson, C.B., 1980, Development and 

use of a mathematical model of the San Bernardino valley ground-water basin, California: U.S. Geological 

Survey Open-File Report 80-516, 80 p.

Heath, R.C., 1983, Basic ground-water hydrology: U.S. 

Geological Survey Water-Supply Paper 2220, 84 p.

Hsieh, Paul, and Freckleton, J.R., 1993, Documentation of a 

computer program to simulate horizontal-flow barriers 

using the U.S. Geological Survey’s modular threedimensional finite-difference ground-water flow 

model: U.S. Geological Survey Open-File Report 92-

477, 32 p. 

McDonald, M.G., and Harbaugh, A.W., 1988, A modular 

three-dimensional finite-difference ground-water flow 

model: U.S. Geological Survey Techniques of WaterResources Investigations, book 6, chap. A1, 576 p.

Morton, D.M., 1974, Generalized geologic map of southwestern San Bernardino County, California: U.S. 

Geological Survey Special Report 113, B Series, Plate 

1B, 1:48:000.

National Oceanic and Atmospheric Administration, 1871–

1998, published monthly and annually (all data prior to 

1940 by U.S. Weather Bureau), Climatological data: 

National Oceanic and Atmospheric Administration, 

Climatological data, monthly publications, annual summaries, various paginations.

Pollock, D.W., 1994, User’s Guide for MODPATH/MODPATH-PLOT, version 3: a particle tracking postprocessing package for MODFLOW, the U.S. Geological Survey finite-difference ground-water flow model: 

U.S. Geological Survey Open-File Report 94-464, 

249 p.

Prudic, D.E., 1989, Documentation of a computer program 

to simulate stream-aquifer relations using a modularfinite-difference, ground-water flow model: U.S. 

Geological Survey Open-File Report 88-729, 113 p.

Woolfenden, L.R., 1994, Oxygen-18, deuterium, and tritium 

as tracers of imported water in the Rialto–Colton Basin, 

California in Effects of human-induced changes on 

hydrologic systems: American Water Resources Association, p. 923–932.

Woolfenden, L.R., and Kadhim, Dina, 1997, Geohydrology 

and water chemistry in the Rialto–Colton Basin, San 

Bernardino County, California: Water-Resources 

Investigations Report 97-4012, 101 p.
104 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

106 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

APPENDIX A
107 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

APPENDIX A

Two ARC/INFO AML (Arc Macro Language) programs, LOAD_DATA.AML and 

MK_WELLPKG.AML, are used to create MODFLOW-readable well-package files of initial, transient, 

or predictive conditions for the Rialto–Colton ground-water flow model. These programs, described in 

this appendix, make well-package management easier and data more accessible than with existing methods. 

The programs have been tested with ARC/INFO software version 7.2.1 (a geographic information system from Environmental Systems Research Institute, Inc., Redlands, California) on a SUN workstation with a Sun 5.7 operating system. ARC/INFO stores information about geographic features in an 

INFO data base. INFO is a tabular data base used by ARC/INFO to store and manipulate featureattribute tables and other related tables. For example, INFO allows INFO tables to be linked to one 

another to perform logical and arithmetic operations on rows and columns of data in the INFO tables.

The AML programs currently perform the following functions: 

1. LOAD_DATA.AML uses INFO to load (“import” command) ASCII flat files into INFO 

tables of pumpage, hydraulic conductivity, recharge, underflow, aquifer top and bottom altitudes, 

aquifer source of well water, well construction, and model row/column locations of wells. It 

computes predictive annual totals for recharge, underflow, and pumpage, and saves results in 

INFO tables. Data in these INFO tables are accessed via INFO by MK_WELLPKG.AML and 

used to create the well-package file.

2. MK_WELLPKG.AML uses INFO to make the MODFLOW well-package file. It computes 

net pumpage from total pumpage. The user has the option to vary (through menu selections) the 

quantity of predictive data in order to test the scenarios of interest. 

Both programs handle data for four or five model layers (the water-bearing unit and layer designations 

described in the “Model Grid” section) and thus meet the requirements of the Rialto–Colton study. An 

operational summary follows. For more detailed documentation, see the notes in the program code 

attached.
Appendix A 108

LOAD_DATA.AML 

LOAD_DATA.AML imports ASCII flat files into INFO tables and computes and saves predictive data. Settings may be entered into a menu (data.menu), which is displayed once the program is 

invoked. Each category of data is entered into its own INFO table. In the menu (fig. A1), the user may 

select the data set to import, the number of model layers the data describe (4 or 5), the reported period of 

record contained in the flat file, the location of the flat file, and the settings used to compute the predictive data. The user may “APPLY” the settings to continue or “DISMISS” to close the program and not 

update the information.

 Figure A1. Menu (data.menu) displayed after LOAD_DATA.AML is run.
109 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

The flat file must be formatted to be accepted by INFO. Examples of these formats are available 

at the menu “FORMAT HELP” button (fig. A1), which displays a window when selected 

(load_examples.popup). The correct format is comma-delimited, with no carriage-return symbols or 

extraneous commas. For characters (names), single quotes should be placed around data when a space is 

included. 

When data are imported into an INFO table, the old table of the same name is deleted and a new 

one is created. Therefore, it is necessary to import the entire data set, not just selected records, even if 

the operator is just updating records.

 LOAD_DATA.AML enters each line of data into INFO as a single record, and each column of 

the flat file is entered as an “item” (a column) of the INFO table. INFO-table items holding pumpage or 

recharge data are labeled with a “Y” and the year of the measurement (for example, “Y1945” ).

 Predictive data are computed for a range of years (set in the menu), and from an average of 

reported data (single year or range of years) specified in the menu (fig. A1),

where: avg = summation of data selected / number of years of data selected

 example: for predictive year Y2020, if averaging from a range of years,

 Y2020 = Y1996 - Y1945 / 52 

 or if using a single year, 

 Y2020 = Y1996 / 1.

The INFO-table items storing predictive data are calculated to equal this average. 
Appendix A 110

The INFO tables created for each data set are :

Button Description of data set INFO table____

Pumpage Total annual pumpage for 47 wells (acre-ft) total_pumpage

Ks Hydraulic conductivity of model layers (cells with wells) (ft/s) well_ks4 or well_ks5

Mtn Front Mountain-front-recharge, annual totals (ft3/s) rchg_mtn_ann

Art Rchg Artificial recharge, annual totals (ft3/s) art_rchg_ann

Lytle UF Underflow from Lytle basin, annual totals (ft3/s) uf_lytle_ann

BH UF Underflow from Bunker Hill basin, annual totals (ft3/s) 

uf_bh_ann

Layer Alt Model-layer altitudes of cells containing wells (ft) layer_alt4 or layer_alt5

*Well Perfs Altitudes of perforated intervals (ft) well_perfs4 or well_perfs5

Well RowCol Model grid row and column designations for the 47 wells well_rowcol

*May contain layer designations and percent of total pumpage assigned to a layer, as determined 

by the user. These settings remain unchanged during the operation of MK_WELLPKG. AML. 

The INFO table name includes “4” or “5” when data are specific to a model with that many layers (for 

example, “well_perfs4”) . 
111 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

If desired, the model-layer designation and percentage of total pumpage assigned to the layer may 

be entered into INFO and will remain unchanged during the operation of MK_WELLPKG.AML. This is 

done when construction information is missing, or when the hydrologist has better knowledge of the contributing model layer (see “Pumpage” section of the report for a discussion of the logic employed to set 

these designations). Selecting the “Well Perfs” button imports the information into an INFO table it creates. The format (displayed for “Well Perfs” at the “FORMAT HELP” button) is: 

PLEASE FORMAT FLAT FILES AS DESCRIBED BELOW:

 DATA CATEGORY BUTTON

---------------------------------------------------------------------------- 

---Well Perforations (feet) well_perfs

** To control the amount of pumpage assigned to a layer,

** Set model-layer designations (and percent contributions if water

** comes from more than one layer) in items ‘layer’ and ‘pcnt(n)’

** where: (pcnt(n) = maximum 5 decimal places)

** example: enter layer one = 1, layer two and three = 23, etc.

  pcnt(n) need only be set if more than one layer contributing ** ** 

INFO table: WELL_PERFS_4

 items: wellid lse top_ele bop_ele layer pcnt1 pcnt2 pcnt3 pcnt4

 format (nodata = -99):

 001N005W07P002E,2156.00,-99.00,-99.00,23,0,0.25,0.75,0

In the example above, 25 percent of total pumpage is assigned to layer 2 and 75 percent is assigned to 

layer 3. For more detailed documentation of LOAD_DATA.AML, see the program and menus attached.
Appendix A 112

MK_WELLPKG.AML

MK_WELLPKG.AML creates the MODFLOW-readable well-package file desired by the user. 

Options may be entered into a menu (wellpkg.menu), which is displayed once MK_WELLPKG.AML is 

run (fig. A2). The user may set the simulation type (initial, transient, or predictive conditions), simulation period, number of model layers, percentage of total pumpage not returned to the system as “irrigation return flow,” and the percentage of total pumpage used in predictive computations. The user may 

“APPLY” the settings to continue or “DISMISS” to close the program and not update the information.

 Figure A2. Menu displayed by MK_WELLPKG.AML.
113 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

This program uses four primary AML routines. The order of operation is: (1) the calc_perfs 

routine, which computes the length of the perforated interval within a model layer, (2) the calc_pcnt routine, which computes the weighted percentage of total pumpage contributed by a layer (if not specified 

in the well_perfs INFO table) from the lengths of perforated intervals (from calc_perfs routine) and the 

hydraulic conductivity of the layer at a given well, (3) the calc_qn routine, which distributes total pumpage vertically to model layers (in -ft3/s) using the percentages computed in calc_pcnt for both the 

reported and predictive period, and adjusts predictive pumpage according to menu settings (results are 

stored in an INFO table), and (4) the pump_out routine, which reads the total pumpage assigned to 

model layers (from calc_qn routine) and computes net pumpage (based on the menu setting, fig. A2), 

and, reading from the computations of net pumpage and INFO tables of underflow, mountain-front 

recharge, and artificial recharge, creates the MODFLOW well-package file. 

The INFO table holding the total pumpage assigned to model layers (created with calc_qn routine) is labeled to identify the file contents. For example, the name “QT_4_PRED80” indicates that total 

pumpage is assigned to a four-layer model and, for the predictive period (1997-2027), 80 percent of the 

pumpage estimated by LOAD_DATA.AML has been saved for output. Thus, well “A” (assuming a 

four- layer model and that all four layers are contributing), will show four records for each stress period 

-- one for each of the four model layers.

 MK_WELLPKG.AML reads the INFO table of total pumpage assigned to model layers (for 

example, “QT_4_PRED80” ) and computes net pumpage on the basis of the menu setting (fig. A2). For 

the Rialto–Colton model, net pumpage is 70 percent, (the remainder is assumed to be “irrigation-return 

flow,” see the “Irrigation-Return Flow” section of this report for a complete discussion). These values 

are unloaded directly into the MODFLOW well-package file.
Appendix A 114

 For the period of record specified in the menu (fig. A2), MK_WELLPKG.AML outputs net 

pumpage and recharge in order of ascending stress period and model-layer number. The resulting MODFLOW well-package file contains the header information required by MODFLOW, and in a fix-formatted single record: layer, row, column, measurement in cubic feet per second (- for net pumpage or + for 

recharge data), and a source comment. An example of the MK_WELLPKG.AML output follows: 

 287 40

89 Y1945

 1 60 70 -0.001034_Y1945 001S004W21N001E 01S04W21N01

 1 63 74 -0.060306_Y1945 001S004W28A006E 01S04W28A05

 1 64 74 -0.249211_Y1945 001S004W28G001E 01S04W28G01

 1 66 72 -0.446225_Y1945 001S004W28K001S 01S04W28K01

 1 55 72 1.344719_uf_bh_ann 550072

 1 56 73 1.344719_uf_bh_ann 560073

 1 57 73 1.344719_uf_bh_ann 570073

 1 61 76 1.344719_uf_bh_ann 610076

 1 62 77 1.344719_uf_bh_ann 620077

 1 63 77 1.344719_uf_bh_ann 630077

 2 50 59 -0.028987_Y1945 001S004W18B001E 01S04W18B01

 2 52 62 -0.065981_Y1945 001S004W17M001S 01S04W17M01

 2 60 70 -0.000391_Y1945 001S004W21N001E 01S04W21N01

 2 64 74 -0.005086_Y1945 001S004W28G001E 01S04W28G01

 2 66 72 -0.157958_Y1945 001S004W28K001S 01S04W28K01

The well-package file (example above) is named with the menu settings selected by the user. For 

example, the file “initial_4_n70.dat” holds initial-condition data for a four-layer model, wherein net 

pumpage is 70 percent of the total pumpage for a well. The file “predictive_5_p120_n70.dat” holds 

predictive simulation data for a five-layer model, wherein the predictive data are 120 percent of values 

computed by LOAD_DATA.AML, and the net pumpage (for the entire simulation period) is 70 percent 

of the total pumpage for the well. See the program and menus attached for specific documentation of 

MK_WELLPKG.AML.
115 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Coding for DATA.MENU: 

/*--------------------------------------------------------------------------

7 data.menu

/* field definitions

 Data set to load:

 %class1

 Number of Model Layers: %class2

 Reported Record (example, 1945 1996) Begin: %b_year End: %e_year

 Note: Flat file must contain data for each year. 

 Use zero for “nodata” in pumpage, conductivity, recharge, and underflow.

 Use -99 for “nodata” in altitude and perforation data. 

 Flat File to Load ( location and name: /full path/.../data/name ):

 %class3

 TO COMPUTE PREDICTIVE DATA:

 Predictive Period (example, 1997 2027) Begin: %b_year_p End: %e_year_p

 

 Reported Data Used in Predictive Calculations:

 Single Year (example, 1996 1996) or Range of Years (example, 1945 1996): 

 Begin: %b_year_av End: %e_year_av

 

 %apply %format_help %dismiss

%class1 CHOICE .info_t PAIRS INITIAL ‘total_pumpage’ ~

 ‘Pumpage’ ‘total_pumpage’ ‘Ks’ ‘well_ks’ ~

 ‘Mtn Front’ ‘rchg_mtn_ann’ ‘Art Rchg’ ‘art_rchg_ann’ ~

 ‘Lytle UF’ ‘uf_lytle_ann’ ‘BH UF’ ‘uf_bh_ann’ ‘Layer Alt’ ‘layer_alt’ ~

 ‘Well Perfs’ ‘well_perfs’ ‘Well RowCol’ ‘well_rowcol’ 

%class2 CHOICE .no_l SINGLE INITIAL ‘4’ ‘4’ ‘5’ 

%b_year INPUT .b_year 10 TYPEIN YES INITIAL 1945 SCROLL NO REQUIRED REAL

%e_year INPUT .e_year 10 TYPEIN YES INITIAL 1996 SCROLL NO REQUIRED REAL

%class3 INPUT .flat_f 75 TYPEIN YES REQUIRED CHARACTER

%b_year_p INPUT .b_year_p 10 TYPEIN YES INITIAL 1997 SCROLL NO REQUIRED REAL

%e_year_p INPUT .e_year_p 10 TYPEIN YES INITIAL 2027 SCROLL NO REQUIRED REAL

%b_year_av INPUT .b_year_av 10 TYPEIN YES INITIAL 1945 SCROLL NO REQUIRED REAL

%e_year_av INPUT .e_year_av 10 TYPEIN YES INITIAL 1996 SCROLL NO REQUIRED REAL

%apply BUTTON ‘Apply’ &return

%format_help BUTTON ‘Format Help’ &popup load_examples.popup 

%dismiss BUTTON CANCEL ‘Dismiss’ &s .exit_pgm = .true. ; &dv .info_t ~

 .no_l .b_year .e_year .flat_f .b_year_p .e_year_p .b_year_av ~

 .e_year_av ; &return

%FORMOPT SETVARIABLES RETURN

%FORMINIT &s .exit_pgm = .false.
Appendix A 116

Coding for LOAD_EXAMPLES.POPUP

PLEASE FORMAT FLAT FILES AS DESCRIBED BELOW:

 DATA CATEGORY BUTTON

---------------------------------------------------------------------------- 

---Total Pumpage (acre-feet) Pumpage

INFO table: total_pumpage

 items: wellid otherid1 otherid2 y1945...y1996

 format (nodata = 0): 001S005W12A001E,name1,name2,0,27,..,100

---Hydrologic Conductivity (ft3/s) Ks

INFO table: WELL_KS_4

 items: wellid k1 k2 k3 k4

 format (nodata = 0): 001S005W12A001E,0,0,0.0005787,0.0001447

INFO table: WELL_KS_5

 items: wellid k1 k2 k3 k4 k5

 format (nodata = 0): 001S005W12A001E,0,0,0,0.0005787,0.0001447

---Mountain Front Rchg (ft3/s) Mtn_Front

INFO table: RCHG_MTN_ANN 

 items: layer row column Y1945....Y2027

 format (nodata = 0): 1,1,1,0.237765,0.247835,....,0.247835

---Lytle Underflow (ft3/s) Lytle_UF

INFO table: UF_LYTLE_ANN

 items: layer row column Y1945....Y2027

 format (nodata = 0): 1,1,1,0.237765,0.247835,....,0.247835

---Bunker Hill Underflow (ft3/s) BH_UF

INFO table: UF_BH_ANN

 items: layer row column Y1945....Y2027

 format (nodata = 0): 1,1,1,0.237765,0.247835,....,0.247835

---Model Layer Altitudes (feet) layer_alt

INFO table: LAYER_ALT_4

 items: wellid top1 bot1 top2 bot2 top3 bot3 top4 bot4

 format (nodata = -99): 001N005W07P002E,-99,-99,1850,1720,-99,-99,-99,-99

 

INFO table: LAYER_ALT_5

 items: wellid top1 bot1 top2 bot2 top3 bot3 top4 bot4 top5 bot5

 format (nodata = -99): 

 001N005W07P002E,-99,-99,-99,-99,1850,1720,-99,-99,-99,-99

 

---Model row/column of well locations well_rowcol

INFO table: WELL_ROWCOL

 items: wellid row col

 format (all data required): 001S005W12A001E,43,55

 
117 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

---Well Perforations (feet) well_perfs

** To control the amount of pumpage assigned to a layer,

** Set model-layer designations (and percent contributions if water

** comes from more than one layer) in items ‘layer’ and ‘pcnt(n)’

** where: (pcnt(n) = maximum 5 decimal places)

** example: enter layer one = 1, layer two and three = 23, etc.

  pcnt(n) need only be set if more than one layer contributing ** ** 

INFO table: WELL_PERFS_4

 items: wellid lse top_ele bop_ele layer pcnt1 pcnt2 pcnt3 pcnt4

 format (nodata = -99):

 001N005W07P002E,2156.00,-99.00,-99.00,23,0,0.25,0.75,0

INFO table: WELL_PERFS_5

 items: wellid lse top_ele bop_ele layer pcnt1 pcnt2 pcnt3 pcnt4 pcnt5

 format (nodata = -99):

 001N005W07P002E,2156.00,-99.00,-99.00,34,0,0,0.25,0.25,0.5
Appendix A 118

Coding for LOAD_DATA.AML:

/*--------------------------------------------------------------------------

/*

/* Program: load_data.aml Written for Linda Woolfenden by KMKoczot

/* Version: 1.0

/* Language: AML 

/* Arc Version and Platform: 7.2.1 UNIX

/* Subsystem: Arc

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Purpose: To load Rialto–Colton GW Model data into INFO TABLES for

/* use in the program mk_wellpkg.aml. The data that may be loaded include 

/* total pumpage, conductivity, mountain-front recharge, artificial recharge,

/* underflow (Lytle and Bunker Hill areas), model-layer altitudes by 

/* row/column, well-perforation altitudes, and model grid-cell location 

/* for each well.

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Menu called: data.menu 

/*

/* Popup window (called in data.menu at ‘help’ button): load_examples.popup

/*

/* Popup window and menu called by: load_data.aml 

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Variables used by program (in order of operation):

/* set in data.menu:

/* Name: Type: Description:

/* .info_t character Data set to make into INFO Table.

/* .no_l integer Number of model layers in flat file data

/* (4 OR 5).

/* .b_year real number Beginning year of reported data in flat file.

/* .e_year real number Ending year of reported data in flat file. 

/* .flat_f character Location/name of flat file to load.

/* .b_year_p real number Beginning year, predictive period (format yyyy).

/* .e_year_p real number Ending year, predictive period (format yyyy).

/* .b_year_av real number Beginning year, reported data to compute 

/* predictive data from (format yyyy).

/* .e_year_av real number Ending year, reported data to compute 

/* predictive data from (format yyyy).

/* .exit_pgm character Closes program if conditions are ‘true’.

/*

/* set in load_data.aml:

/* .exit_pgm character Closes program if conditions are ‘true’.

/* tempcov character Temporary coverage created and killed to add

/* the INFO subdirectory.

/* .f character Name of INFO table to be created.

/* junk character Variable set to delete a file. 

/* .n integer Model-layer number used in an item name.

/* .date integer Year of reported data.

/* .date_p integer Year of predictive data.
119 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

/* Y character Name of item to hold predictive data.

/* .final character Name of INFO table successfully created. 

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Routines used in program (alphabetical order):

/* Name: Description:

/* art_rchg_ann_rtne Calls routine ‘recharge_rtne’ and sets INFO table 

/* name to ‘art_rchg_ann’.

/* bailout_rtne Closes program if problem is encountered.

/* check_settings Verifies required INFO tables exist, user has 

/* permission to work in the directory, and the

/* directory is an ARC/INFO workspace.

/* cleanup_rtne Closes the variables set by this program.

/* layer_alt_rtne Creates the INFO table for model-layer top and 

/* bottom altitudes (with data set for 

/* 4 or 5 model layers).

/* predict_years Computes predictive data and stores results

/* in INFO table items.

/* rchg_mtn_ann_rtne Calls routine ‘recharge_rtne’ and sets INFO table

/* name to ‘rchg_mtn_ann’.

/* recharge_rtne Creates the INFO table for a recharge data set.

/* total_pumpage_rtne Creates the INFO table for total_pumpage.

/* uf_lytle_ann_rtne Calls routine ‘recharge_rtne’ and sets INFO table

/* name to ‘uf_lytle_ann’.

/* uf_bh_ann_rtne Calls routine ‘recharge_rtne’ and sets INFO table

/* name to ‘uf_bh_ann’.

/* well_ks_rtne Creates the INFO table for conductivity 

/* (with data set for 4 or 5 model layers).

/* well_perfs_rtne Creates the INFO table for well construction

/* altitudes (land surface, top and bottom

/* of perforations) and percent of total pumpage

/* and model-layer number contributing water.

/* (with data set for 4 or 5 model layers).

/* well_rowcol_rtne Creates the INFO table holding model-layer

/* row column of well locations.

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* History:

/* Author/Site, Date, Version Event

/* -------------------------------------------------------------------------

/* kmkoczot 8/20/98 --- load_data.aml first cut written

/* uses data.menu. 

/* kmkoczot 12/10/98 --- load_data.aml revised to add

/* altitudes.

/* kmkoczot 3/3/99 --- load_data.aml revised to send

/* warning to screen if 

/* working file is missing.

/* kmkoczot 3/12/99 --- load_examples.popup written 

/* kmkoczot 8/99 1.0 load_data.aml revised to use new

/* data.menu, which includes

/* option to load pumpage.

/* Modified some routines

/* to reduce processing time.
Appendix A 120

/* Added total_pumpage_rtne

/* to create pumpage INFO

/* table. Added 

/* variable and routine

/* descriptions to header. 

/* Added comment lines to 

/* coding. (Final coding)

/*

/*--------------------------------------------------------------------------

/*

/* Disclaimer:

/* Although this program has been used by the U.S. Geological Survey, no

/* warranty, expressed or implied, is made by the USGS as to the accuracy

/* and functioning of the program and related program material nor shall the

/* fact of distribution constitute any such warranty, and no responsibility

/* is assumed by the USGS in connection herewith.

/*

/*--------------------------------------------------------------------------

&severity &error &routine bailout_rtne

&terminal 9999

&menu data.menu &form &STRIPE ‘LOAD DATA’ 

 &if %.exit_pgm% &then &return Exiting Program Load_data.aml

 &messages &off

/* Check to see if flat file (%.flat_f%) exists. 

 &call check_settings

/* Create INFO table.

 &call %.info_t%_rtne

/* List finished INFO table below.

 &type [quote FINISHED :> . NEW INFO TABLE CREATED. SEE BELOW: ]

 &type [quote ]

&messages &on

 dir info %.final%

&messages &off

/* Cleanup the directory.

 &call cleanup_rtne 

 

&messages &on

&return /* closes load_data.aml

/*----------------------ROUTINES--------------------------------------------

/*---------------------bailout_rtne

&routine bailout_rtne

 &severity &error &ignore

 &if [quote [translate [show program]]] = ‘TABLES’ &then QUIT
121 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 &s .exit_pgm = .true.

 &messages &on

 &type ‘An error has occurred in load_data.aml.’

 &if %.exit_pgm% &then &return Exiting Program load_data.aml

 &call cleanup_rtne 

&return /* closes bailout_rtne

/*---------------------check_settings

&routine check_settings

/* verify the user has write permission to the current workspace

 &if not [access [show workspace] -write] &then 

 &do

 &type;&type Warning!! User [upcase [username]] does not have write ~

 permissions

 &type to the current workspace. The program has been canceled.

 &return

 &end /* if-then-do

 

/* verify the current directory is an arc/info workspace

 &if not [exists [show workspace] -workspace] &then

 &do 

 &s tempcov = [scratchname -dir]

 create %tempcov% 

 kill %tempcov% all /* this creates the needed INFO subdirectory.

 &end /* if-then-do

 

/* Check to see flat file specified in data.menu exists.

 &if ^ [exists %.flat_f%] &then 

 &do 

 &type [quote Flat file not found in: %.flat_f% ]

 &type [quote Please check path and file name.]

 &s .exit_pgm = .true.

 &messages &on

 &if %.exit_pgm% &then &return Exiting Program load_data.aml

 &end /* if-then-do 

&return

/*---------------------total_pumpage_rtne

&routine total_pumpage_rtne /* Loads total_pumpage (AF) . 

/*--define name of INFO table to hold data. 

 &s .f = %.info_t%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info]

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%]

/*--define INFO table

TABLES

 define %.f%

 WELLID 15 15 C

 OTHERID1 15 15 C

 OTHERID2 15 15 C

 ~
Appendix A 122

 sel

 /* additems to hold reported total pumpage (acre-feet) of each well 

 &do .date = %.b_year% &to %.e_year% &by 1

 additem total_pumpage Y%.date% 6 6 I 

 &end /* do 

 

/*--load data from flat file. 

 sel %.f%

 add from %.flat_f% 

 commit

QUIT /*TABLES

 

/*--compute and add predictive data 

 /* additems to hold predictive data.

 &do .date_p = %.b_year_p% &to %.e_year_p% &by 1

 additem %.f% %.f% Y%.date_p% 6 6 I

 &end /* do 

 additem %.f% %.f% avg 10 10 n 2

 additem %.f% %.f% tot_range 15 15 n 2

 

 /* compute predictive data and load value to items added above.

 &call predict_years 

 

 &s .final = %.f%

&return /* closes total_pumpage_rtne

/*---------------------well_ks_rtne

&routine well_ks_rtne /* Load conductivities. 

/*--define name of INFO table to hold data. 

 &s .f = %.info_t%_%.no_l%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info]

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%] 

/*--define INFO table

TABLES

 define %.f%

 WELLID 15 15 C

 ~

 sel

 /* additems to hold conductivity (ft/sec) of each layer

 &do .n = 1 &to %.no_l% &by 1 

 additem %.f% k%.n% 11 11 N 7

 &end /* do

 

/*--load data from flat file. 

 sel %.f%

 add from %.flat_f% 

 commit

QUIT /*TABLES
123 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 &s .final = %.f%

&return /* closes well_ks_rtne

/***---------------------NOTE: recharge_rtne is used to load: 

/*** rchg_mtn_ann uf_lytle_ann uf_bh_ann

 /*---------------------for art_rchg_ann

 &routine art_rchg_ann_rtne

 &call recharge_rtne /* loads recharge data (ft3/s).

 &return /* closes rchg_mtn_ann_rtne

 /*---------------------for rchg_mtn_ann

 &routine rchg_mtn_ann_rtne

 &call recharge_rtne

 &return /* closes rchg_mtn_ann_rtne

 /*---------------------for uf_lytle_ann

 &routine uf_lytle_ann_rtne

 &call recharge_rtne

 &return /* closes uf_lytle_ann_rtne

 /*---------------------for uf_bh_ann

 &routine uf_bh_ann_rtne

 &call recharge_rtne

 &return /* closes uf_bh_ann_rtne

/*---------------------recharge_rtne

&routine recharge_rtne /* Load recharge and underflow (ft3/s).

/*--define name of INFO table to hold data.

 &s .f = %.info_t%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info]

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%] 

/*--define INFO table

TABLES

 define %.f%

 LAYER 4 10 I

 ROW 4 10 I 

 COL 4 10 I 

 ~

 /* Set years to load to INFO table.

 &do .date = %.b_year% &to %.e_year% &by 1

 /* additems to hold mountain-front recharge (ft3/s).

 additem %.f% Y%.date% 10 10 N 6

 &end /* do

/*--load data from flat file.

 sel %.f%

 add from %.flat_f%
Appendix A 124

 commit

 

/*--Create the common item, ‘CELL’. 

 redefine 

 5

 cell 8 8 i

 ~

 sel

QUIT /*TABLES

/*--compute and add predictive data 

 /* additems to hold predictive data.

 &do .date_p = %.b_year_p% &to %.e_year_p% &by 1

 additem %.f% %.f% Y%.date_p% 10 10 N 6

 &end /* do 

 additem %.f% %.f% avg 10 10 n 6

 additem %.f% %.f% tot_range 15 15 n 6

 

 /* compute predictive data and load value to items added above.

 &call predict_years 

 

 &s .final = %.f%

&return /* closes recharge_rtne

/*---------------------layer_alt_rtne

&routine layer_alt_rtne 

/* Loads top and bottom altitude for model with layers specified in menu. 

/*--define name of INFO table to hold data. 

 &s .f = %.info_t%_%.no_l%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info]

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%] 

/*-- define the new INFO table

TABLES

 define %.f%

 WELLID 15 15 C

 ~

 sel

 

 /* additems to hold top and bottom model layer altitudes

 /* for cells containing wells.

 /* example: item top1 = top of layer 1 altitude (feet)

 &do .n = 1 &to %.no_l% &by 1 

 additem %.f% top%.n% 8 8 N 1

 additem %.f% bot%.n% 8 8 N 1

 &end /* do

 

/*--load data from flat file.

 sel %.f%

 add from %.flat_f% 

 commit

 
125 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

QUIT /* TABLES

 &s .final = %.f%

&return /* closes layer_alt_rtne

/*---------------------well_perfs_rtne

&routine well_perfs_rtne /* Loads new perforation altitude data.

/* Note: This data set includes items LAYER and PCNT%no_l%, 

/* These may have been set by the hydrologist in the flat file.

/* Otherwise, they are computed by MK_WELLPKG.AML. 

/*--define name of INFO table to hold data. 

 &s .f = %.info_t%_%.no_l%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info] 

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%] 

/*-- define the new INFO table 

TABLES

 define %.f%

 WELLID 15 15 C 

 LSE 8 8 N 2 

 TOP_ELE 8 8 N 2 

 BOP_ELE 8 8 N 2

 LAYER 5 10 I

 ~

 sel

 

 /* additems to hold percent of total pumpage in layer n. 

 /* example: item PCNT1 = percent of total from layer 1.

 &do .n = 1 &to %.no_l% &by 1 

 additem %.f% PCNT%.n% 7 7 N 5

 &end /* do

 ~

/*--load data from flat file.

 sel %.f%

 add from %.flat_f%

 commit

QUIT /* TABLES

 &s .final = %.f%

&return /* closes well_perfs_rtne

/*---------------------well_rowcol_rtne

&routine well_rowcol_rtne /* Loads row/column modelgrid cell for each well. 

/*--define name of INFO table to hold data.

 &s .f = %.info_t%

 &if [exists %.f% -info] &then &s junk [delete %.f% -info] 

 &type [quote LOADING %.flat_f% (%.b_year%-%.e_year%)]

 &type [quote . TO INFO TABLE: %.f%]
Appendix A 126

/*-- define the new INFO table 

TABLES

 define %.f%

 WELLID 15 15 C

 ROW 4 4 I

 COL 4 4 I

 ~

/*--load data from flat file.

 sel %.f%

 add from %.flat_f% 

 commit

 

/*--Create the common item, ‘CELL’. 

 redefine 

 16

 cell 8 8 i

 ~

QUIT /* TABLES

 &s .final = %.f%

&return /* closes well_rowcol_rtne

/*---------------------predict_years

&routine predict_years 

/* calcs predictive years to the average of reported years

/* where: avg = average value of years selected in menu

/* avg = summation of data selected/ number of years

/*

/* example: for predictive year Y2020, if 

/* a range of years Y2020 = Y1996 - Y1945 / 52

/* or if a single year Y2020 = Y1996 / 1

TABLES

 sel %.f%

 /* compute average value from range of years specified in the menu.

 calc tot_range = 0 /* just in case it holds some other value.

 commit

&type [quote COMPUTING PREDICTIVE DATA FROM AVERAGE OF YEARS ~

 %.b_year_av%-%.e_year_av%]

 &do .date = %.b_year_av% &to %.e_year_av% &by 1

 calc tot_range = tot_range + Y%.date%

 commit 

 &end /* do

 &s denom = %.e_year_av% - %.b_year_av% + 1

 calc avg = tot_range / %denom% 

 commit

 /* calculate predicted years to equal the average value. 

 &do .date = %.b_year_p% &to %.e_year_p% &by 1

 &s Y = Y%.date% 

 calc %Y% = avg /* average computed above. 

 commit

 &end /* do
127 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

QUIT /* TABLES

&return

/*---------------------cleanup_rtne

&routine cleanup_rtne /* closes global variables set by this program.

 &dv .info_t .no_l .b_year .e_year .flat_f .b_year_p .e_year_p ~

 .b_year_av .e_year_av .exit_pgm .f .n .date .date_p .final

&return 

/*---------------------end of routines.
Appendix A 128

Coding for WELLPKG.MENU

7 wellpkg.menu

/* field definitions

 Output File:%class1

 Simulation Period (example, 1945 2027) Begin: %b_year End: %e_year 

 Number of Model Layers:%class2

 Net Pumpage, Percent of Total, Default = 70 (remainder is return flow):

 %class3

 

 Percent Total Pumpage, Default = 100 (adjusted for predictive runs):

 %class4 

 %apply %dismiss

%class1 CHOICE .QTYPE SINGLE INITIAL ‘initial’ ~

 ‘initial’ ‘transient’ ‘predictive’

%b_year INPUT .b_year 10 TYPEIN YES INITIAL 1945 SCROLL NO REQUIRED REAL

%e_year INPUT .e_year 10 TYPEIN YES SCROLL NO REQUIRED REAL

%class2 CHOICE .no_l SINGLE INITIAL ‘4’ ‘4’ ‘5’

%class3 INPUT .pcnt_ir 10 TYPEIN YES INITIAL 70 SCROLL NO REQUIRED ~

 RANGE 0 100 INTEGER

%class4 INPUT .pcnt_qt 10 TYPEIN YES INITIAL 100 SCROLL NO REQUIRED ~

 RANGE 0 10000 INTEGER

%apply BUTTON ‘Apply’ &return

%dismiss BUTTON CANCEL ‘Dismiss’ &s .exit_pgm = .true. ; &dv .QTYPE ~

 .b_year .e_year .no_l .pcnt_ir .pcnt_qt ; &return

%FORMOPT SETVARIABLES RETURN

%FORMINIT &s .exit_pgm = .false.
129 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

Coding for MK_WELLPKG.AML

/*--------------------------------------------------------------------------

/*

/* Program: mk_wellpkg.aml Written for Linda Woolfenden by KMKoczot.

/* Version: 1.0

/* Language: AML

/* Arc Version and Platform: 7.2.1 UNIX

/* Subsystem: Arc

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Purpose: Creates a MODFLOW-readable well-package file for initial, 

/* transient, or predictive conditions, to be used in the Rialto–Colton

/* MODFLOW model. Computes net pumpage from total pumpage. Vertically 

/* distributes net pumpage to model layers according to the location of 

/* perforated intervals and the conductivity of the model layer. Pumpage 

/* quantities can be specified for a model layer (in the well_perfs file 

/* loaded by LOAD_DATA.AML), overriding this feature. Pumpage values for 

/* predictive scenarios (1997-2027) may be adjusted by any percentage to 

/* evaluate the effects of future increases and (or) decreases in pumpage.

/* The percentage of total pumpage used in the predictive computations, 

/* the irrigation efficiency rate used in the net pumpage computations, the 

/* type of output (initial, transient or predictive), the number of model 

/* layers, and the simulation period, are set in the menu. Output includes

/* -Q (net pumpage) and +Q (mountain-front and artificial recharge, and 

/* underflow). 

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Menu called: wellpkg.menu 

/*

/* Menu called by: mk_wellpkg.aml

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* UNIX SYSTEM tools used in program:

/* vi editor used in “calc_perfs” routine.

/* paste command used in “calc_perfs” routine.

/*

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Variables used by program (in order of operation):

/* set in wellpkg.menu:

/* Name: Type: Description:

/* .QTYPE character Type of MODFLOW output file (initial,

/* (transient or predictive conditions). 

/* .b_year real number Beginning year of simulation period (format yyyy).

/* .e_year real number Ending year of simulation period (format yyyy). 

/* .no_l integer Number of model layers to output to MODFLOW 

/* file (four or five).

/* .pcnt_ir integer Net pumpage (percent of total pumpage). The 

/* remainder is assumed to be return flow.

/* .pcnt_qt integer Percent of total pumpage used in predictive

/* computations.
Appendix A 130

/* .exit_pgm character Closes program if conditions are ‘true’. 

/* 

/* set in mk_wellpkg.aml:

/* .exit_pgm character Closes program if conditions are ‘true’.

/* tempcov character Temporary coverage created and killed to add

/* the INFO subdirectory.

/* i_f character Lists of INFO tables verified in

/* check_settings routine.

/* junk character Variable set to delete a file.

/* f character Lists of INFO tables and flat files to delete

/* in clean-up routines. 

/* n integer Model-layer number used in an item name.

/* i character Lists of INFO-table items to drop from INFO

/* tables (in clean-up routines).

/* yr integer Year used in an item name (format yyyy).

/* unload_years character String of items holding net pumpage that are

/* unloaded to a temporary file.

/* .mfile character Name of MODFLOW file created by mk_wellpkg.aml.

/* X character Lists of INFO tables.

/* .IR integer Irrigation efficiency rate.

/* header character The first line unloaded to the MODFLOW file.

/* It contains ' 287 40' .

/* .date integer Year of simulation period.

/* Y character Name of item (a stress period) holding 

/* simulated data.

/* C1 integer Count of net pumpage from records in stress 

/* period %Y% that are in an active area and

/* layer of the MODFLOW model.

/* C%X% integer Count of records in stress period %Y% that 

/* are in an active area and layer of the

/* MODFLOW model. These records are counted

/* from the recharge INFO tables.

/* name character Name of an INFO-table holding recharge data.

/* C3 integer Summation of the totals found in C1 and C%X%

/* for stress period %Y%. 

/* headvar character The line unloaded to the MODFLOW file at the

/* beginning of each stress period. It

/* contains a total of records in the stress

/* period %C3% (read by MODFLOW), and a 

/* stress-period label %Y%.

/* 

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* Routines used in program (in order of operation):

/* Name: Description:

/* bailout_rtne Closes program if problem is encountered.

/* check_settings Verifies required INFO tables exist, user has 

/* permission to work in the directory, and the

/* directory is an ARC/INFO workspace.

/*

/* calc_perfs Makes INFO table: layer_perfs%.no_l%. See NOTES.

/* mk_layer_perfs4 Called by “calc_perfs” routine. 

/* Following seven assumptions for each well

/* (see notes in “calc_perfs” routine), sums the
131 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

/* length of the perforated interval per model 

/* layer into a single record (four-layer model

/* only).

/* mk_layer_perfs5 Called by “calc_perfs” routine. Sums the

/* length of the perforated interval per model 

/* layer into a single record 

/* (like mk_layer_perfs4 but for a five-layer 

/* model only).

/* redefine_4_rtne Called by “calc_perfs” routine. Redefines a new

/* model-layer number. Model-layer numbers are

/* assigned in the routine based on the location 

/* of perforated intervals, unless layers were 

/* already assigned in well_perfs_%.no_l% 

/* (four-layer model only).

/* redefine_5_rtne Called by “calc_perfs” routine. Redefines a new

/* model-layer number (like redefine_4_rtne but

/* for a five-layer model only).

/* clean_layer_perfs4 Called by “calc_perfs” routine. Deletes extra

/* items in layer_perfs%.no_l% (four-layer model

/* only).

/* clean_layer_perfs5 Called by “calc_perfs” routine. Deletes extra

/* items in layer_perfs%.no_l% (four-layer model

/* only).

/*

/* calc_pcnt Makes INFO table: layer_pcnts%.no_l%. See NOTES.

/* calc_denom4 Called by “calc_pcnt” routine. Computes the

/* denominator of the equation to find the

/* percentage of total pumpage coming from the

/* model layer perforated by a well. This is

/* computed from the perforated length and the 

/* conductivity of the model layer of that well

/* (four-layer model only).

/* calc_denom5 Called by “calc_pcnt” routine. Computes the

/* denominator of an equation as in “calc_denom4”

/* (five-layer model only).

/*

/* calc_qn Makes INFO table: QT_%.no_l%_pred%.pcnt_qt%.

/* See NOTES.

/*

/* pump_out Makes MODFLOW well-package file. See NOTES.

/* cleanup_pump_out Called by “pump_out” routine. Deletes extra

/* items in QT_%.no_l%_pred%.pcnt_qt% 

/* and the recharge INFO tables. 

/* 

/* cleanup_rtne Closes the variables and routines set by this 

/* program. 

/* 

/*::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

/*

/* NOTES:

/* Mk_wellpkg.aml must be run in the directory containing the

/* INFO tables it will read from. 

/*

/* Mk_wellpkg.aml permits the user to create MODFLOW-readable 
Appendix A 132

/* well-package files for the Rialto–Colton ground-water flow model. In the

/* menu, the user may select initial, transient, or predictive conditions,

/* set the simulation period, choose between four and five model layers, 

/* specify net pumpage (as a percent of total pumpage) to output, and 

/* specify the percentage of total pumpage to use for predictive data.

/* 

/* 

/* Mk_wellpkg.aml was created by catenating four amls together.

/* The amls became primary routines in this program and are called

/* (in order of processing): calc_perfs, calc_pcnt, calc_qn, and pump_out.

/*

/* “Calc_perfs” routine creates the INFO table layer_perfs%.no_l% from

/* INFO tables well_perfs_%.no_l% and layer_alt_%.no_l%. These INFO 

/* tables were created using load_data.aml. Unless already set in 

/* well_perfs_%.no_l%, this routine identifies the model layer(s) the

/* well is perforated in, and determines the length of perforated interval 

/* within model layer(s) for each well.

/*

/* where: n = model-layer number

/* L(n) = length of perforated interval in layer n (ft)

/* 

/* “Calc_pcnt” routine creates the INFO table layer_pcnts%.no_l% from 

/* layer_perfs%.no_l% (killed at end) and from well_ks_%.no_l%. Unless 

/* already set in well_perfs_%.no_l%, this routine calculates the 

/* percentage of the total perforated interval in each model layer

/* (weighted by conductivity of the model layer). It assigns model-layer 

/* numbers where not already assigned in well_perfs_%.no_l%.

/* 

/* where: k(n) = hydraulic conductivity of layer n (ft/sec)

/* pcnt(n) = L(n) * k(n) / L1*k1 + L2*k2 ... + L(n)*k(n)

/* pcnt(n) = percentage of total pumpage from layer n 

/* ( a representative fraction)

/* 

/* “Calc_qn” routine creates the INFO table 

/* QT_%.no_l%_pred%.pcnt_qt% from INFO tables layer_pcnts%.no_l% (killed 

/* at end) and total_pumpage. It calculates the vertical distribution of 

/* total pumpage (in -ft3/s) for both the reported and predictive period 

/* and adjusts (as specified in the menu) predictive pumpage (1997-2027) 

/* to simulate future increases and (or) decreases in pumpage. For each 

/* well, a single record is saved from each contributing layer and for all 

/* years modeled (1945-2027). 

/* 

/* where: q(n) = QT * pcnt(n) 

/* q(n) = total pumpage assigned to layer n (-ft3/s) 

/* n = is the model-layer number 

/* QT = total pumpage of well (-ft3/s) 

/* pcnt(n) = percentage of total pumpage assigned to model layer n 

/* 

/* Total pumpage for reported years 1945–96 is calculated as: 

/* QT = Yr * -.0013813 (ft3/s)/acre-ft 

/* 

/* Total pumpage for predictive years 1997-2027 is calculated as: 

/* QT = Yr * -.0013813 (ft3/s)/acre-ft * pcnt_qt / 100 
133 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

/* where: Yr = total pumpage of well (acre-ft)

/* pcnt_qt = percentage of total to be used in the MODFLOW modeling 

/* run. 

/*

/* “Pump_out” creates the MODFLOW-readable flat file (ft3/s). It

/* reads from QT_%.no_l%_pred%.pcnt_qt% and calculates net pumpage (-ft3/s)

/* for all years in the simulation period. These net pumpage values of 

/* vertically distributed data are unloaded along with data from INFO tables

/* containing +Q, including (+Q) art_rchg_ann, rchg_mtn_ann, uf_lytle_ann,

/* and uf_bh_ann. Data are unloaded in order of ascending stress period

/* and model-layer number.

/*

/* where: q(net) = q(n) * pcnt_ir / 100

/* 

/* pcnt_ir = irrigation efficiency (remainder is return flow). 

/*

/*

/* -------------------------------------------------------------------------

/* History:

/* Author/Site Date Version Event

/* -------------------------------------------------------------------------

/* kmkoczot 6/30/95 1.0 pump_out.aml written for 

/* Masters thesis. Unloads

/* pumpage and recharge into

/* MODFLOW readable format.

/* kmkoczot 8/19/96 2.0 pump_out.aml modified for Mojave

/* MODFLOW model.

/* kmkoczot 7/17/97 --- calc_perfs.aml first cut written

/* kmkoczot 7/18/97 --- calc_qn.aml first cut written

/* kmkoczot 8/24/97 3.0 pump_out.aml modified for Rialto-

/* Colton MODFLOW model. 

/* kmkoczot 2/8/98 1.0 calc_perfs.aml revision

/* kmkoczot 2/9/98 1.0 calc_pcnt.aml written

/* kmkoczot 2/11/98 1.0 calc_qn.aml revision 

/* kmkoczot 2/12/98 3.1 pump_out.aml revision

/* kmkoczot 5/4/98 --- four amls revised to create 

/* four-layer model output.

/* kmkoczot 5/6/98 --- four amls revised to create

/* five-layer model output.

/* kmkoczot 5/6/98 --- pumpall_4amls.aml catenated amls

/* above into this program

/* to make four-layer output.

/* kmkoczot 6/2/98 --- pumpall_4amls.aml revised to read

/* from files of years. Aml 

/* sections revised and added

/* as routines. **Output is 

/* for four layers.

/* kmkoczot 8/11/98 --- four amls creating five-layer 

/* output revised as routines.

/* kmkoczot 8/13/98 --- mk_wellpkg.aml revised above

/* “pumpall_4amls.aml”, to 

/* include five-layer routines. 

/* Renamed as this program.

/* (**four and five-layer output).
Appendix A 134

/* kmkoczot 8/19/98 --- mk_wellpkg.aml revised to allow

/* output of percentages of 

/* total pumpage (for use in

/* predictive modeling runs).

/* kmkoczot 8/21/98 --- mk_wellpkg.aml revised to use

/* out.menu.

/* kmkoczot 3/3/99 --- mk_wellpkg.aml revised to send

/* warning to screen if

/* working files are missing.

/* kmkoczot 3/23/99 --- mk_wellpkg.aml revised to use 

/* wellpkg.menu. 

/* kmkoczot 8/99 1.0 mk_wellpkg.aml revised to use new

/* wellpkg.menu which allows the 

/* simulation period to be 

/* entered. No no longer

/* reads from files of years.

/* Modified some routines to

/* reduce processing time.

/* Added variable and routine 

/* descriptions to header. Added

/* comment lines to coding.

/* (Final coding)

/*

/*--------------------------------------------------------------------------

/*

/* Disclaimer:

/* Although this program has been used by the U.S. Geological Survey, no

/* warranty, expressed or implied, is made by the USGS as to the accuracy

/* and functioning of the program and related program material nor shall the

/* fact of distribution constitute any such warranty, and no responsibility

/* is assumed by the USGS in connection herewith.

/*

/*==========================================================================

/*-- Begin mk_wellpkg.aml.

&severity &error &routine bailout_rtne

&terminal 9999

/* Call menu.

 &menu wellpkg.menu &form &stripe ‘MAKE WELL PACKAGE’ 

 &if %.exit_pgm% &then &return Exiting Program Mk_wellpkg.aml

 &messages &off &all

 /* Verify the INFO tables and flat files exist to make output.

 &call check_settings

/* Begin computing. 

&type [quote MAKING WELL-PACKAGE FOR %.qtype% CONDITIONS ~

WITH %.no_l% MODEL LAYERS.]

&type [quote FOR YEARS BEGIN: %.b_year% END: %.e_year%]

&type [quote USING %.pcnt_ir% PERCENT OF TOTAL PUMPAGE FOR NET CALCULATIONS]

&type [quote AND %.pcnt_qt% PERCENT OF TOTAL PUMPAGE FOR PREDICTIVE ~

CALCULATIONS.]

&type ‘ ‘

&type [quote CALCING LENGTH OF PERFORATED INTERVAL IN EACH LAYER...]

 &call calc_perfs
135 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

&type [quote CALCING PERCENT OF TOTAL PUMPAGE FROM EACH LAYER...] 

 &call calc_pcnt

&type [quote CALCING RATE OF NET PUMPAGE (-ft3/s) FROM EACH LAYER...]

 &call calc_qn

 &call pump_out

&type [quote . FINISHED :> .]

&type ~

 [quote YOUR NEW WELL-PACKAGE FILE IS: %.mfile%.dat .]

 &messages &on

&return /* closes mk_wellpkg.aml 

/*----------------------ROUTINES--------------------------------------------

/*---------------------bailout_rtne

&routine bailout_rtne

 &severity &error &ignore

 &if [quote [translate [show program]]] = ‘TABLES’ &then QUIT

 &s .exit_pgm = .true.

 &messages &on

 &type ‘An error has occurred in mk_wellpkg.aml.’

 &if %.exit_pgm% &then &return Exiting Program Mk_wellpkg.aml

 &call cleanup_rtne

&return /* closes bailout_rtne

/*---------------------check_settings

&routine check_settings

/* verify the user has write permission to the current workspace

 &if not [access [show workspace] -write] &then 

 &do

 &type;&type Warning!! User [upcase [username]] does not have write ~

 permissions

 &type to the current workspace. The program has been canceled.

 &return

 &end /* if-then-do

 

/* verify the current directory is an arc/info workspace

 &if not [exists [show workspace] -workspace] &then

 &do 

 &s tempcov = [scratchname -dir]

 create %tempcov% 

 kill %tempcov% all /* this leaves the needed INFO subdirectory.

 &end /* if-then-do

 

/* Verify the existence of INFO tables.

 &do i_f &list WELL_KS_%.no_l% art_rchg_ann rchg_mtn_ann ~ 

 uf_lytle_ann uf_bh_ann layer_alt_%.no_l% ~

 well_perfs_%.no_l% well_rowcol total_pumpage 

 &if ^ [exists %i_f% -info] &then 

 &do 

 &type [quote Missing INFO File: %i_f%]

 &type ‘Please create using Load_data.aml .’

 &s .exit_pgm = .true.

 &messages &on
Appendix A 136

 &if %.exit_pgm% &then &return Exiting Program Mk_wellpkg.aml

 &end /* if-then-do

 &end /* do-if-then

&return /* closes check_settings routine.

/*---------------------calc_perfs

&routine calc_perfs

/* For active cells only, find perf lengths and active layer n for 

/* each well, unless already specified in INFO table: well_perfs_%.no_l%.

/* Calculates length of well perf interval for layer n.

/* makes INFO table: layer_perfs%.no_l%

/* which is populated with perf lengths for each wellid.

/* Verify cleanup of directory.

 &do f &list work.csv f.wcsv layer_perfs%.no_l% temp2

 &if [exists %f% -info] &then &s junk [delete %f% -info]

 &end /* do-if-then

 &do f &list temp.dat fix loadok lp_wellids

 &if [exists %f%] &then &s junk [delete %f%]

 &end /* do-if-then

/*-- Begin length calculations.

TABLES

/* Note: layer_alt_%.no_l% contains model top(n) and bot(n) altitudes.

 &if ^ [iteminfo layer_alt_%.no_l% -info wellid -indexed] &then 

 indexitem layer_alt_%.no_l% wellid

 relate add r.1 layer_alt_%.no_l% info wellid wellid linear auto

/* Perf lengths are computed for layer n based on seven assumptions:

/* 1) layer n is not active at perfs.

/* 2) perfs are not in layer n.

/* 3) top_ele ge top(n) and bop_ele lt top(n) and bop_ele ge bot(n).

/* 4) top_ele le top(n) and bop_ele ge bot(n).

/* 5) top_ele le top(n) and top_ele gt bot(n) and bop_ele le bot(n).

/* 6) top_ele ge top(n) and bop_ele le bot(n).

/* 7) model layer was loaded (along with other data) into

/* well_perfs_%.no_l%. Therefore, record ignored.

 copy well_perfs_%.no_l% work.csv

 additem work.csv active 2 2 i

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 additem work.csv d3_%n% 9 9 n 2

 additem work.csv d4_%n% 9 9 n 2

 additem work.csv d5_%n% 9 9 n 2

 additem work.csv d6_%n% 9 9 n 2

 &end /* do

 sel work.csv 

/* Compute perf lengths in active layer n.

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 /* For assumption #7 above:
137 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 /* remove records with set layer/pcnt contribution.

 resel layer lt 1

 /* Find records in active layers. Flag working records.

 resel r.1//top%n% ne -99 and r.1//bot%n% ne -99

 calc active = 1 

 /* Compute for #3 assumption above.

 resel top_ele ge r.1//top%n% and bop_ele lt r.1//top%n% and ~

 bop_ele ge r.1//bot%n%

 /* and since anything above top%n% is not considered...

 calc d3_%n% = r.1//top%n% - bop_ele

 commit 

 /* Compute for #4 assumption above.

 resel active = 1

 resel top_ele le r.1//top%n% and bop_ele ge r.1//bot%n%

 calc d4_%n% = top_ele - bop_ele 

 commit

 /* Compute for #5 assumption above.

 resel active = 1

 resel top_ele le r.1//top%n% and top_ele gt r.1//bot%n% and ~

 bop_ele le r.1//bot%n%

 /* and since anything below bot%n% is not considered...

 calc d5_%n% = top_ele - r.1//bot%n%

 commit

 /* Compute for #6 assumption above.

 resel active = 1

 resel top_ele ge r.1//top%n% and bop_ele le r.1//bot%n%

 /* and since anything outside layer is not considered...

 calc d6_%n% = r.1//top%n% - r.1//bot%n%

 commit

 calc active = 0

 commit

 &end /* do

QUIT /*TABLES

&call mk_layer_perfs%.no_l%

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 additem layer_perfs%.no_l% d3_%n% 9 9 n 2

 additem layer_perfs%.no_l% d4_%n% 9 9 n 2

 additem layer_perfs%.no_l% d5_%n% 9 9 n 2

 additem layer_perfs%.no_l% d6_%n% 9 9 n 2

 &end /* do

 sel layer_perfs%.no_l%

 add from temp.dat

 commit

 sel

 &do n = [unquote 1 &to %.no_l% &by 1 ]
Appendix A 138

 additem layer_perfs%.no_l% L%n% 9 9 n 2 

 &end /* do

 sel layer_perfs%.no_l%

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 calc L%n% = d3_%n% + d4_%n% + d5_%n% + d6_%n%

 commit

 &end /* do

 sel

/*-- End length calculations.

/*-- Load new layer(s) for each well.

/* Prepare layer_perfs%.no_l% for new layer data.

 additem layer_perfs%.no_l% layer_temp 5 10 i # layer

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 additem layer_perfs%.no_l% layer%n% 1 1 i

 &end /* do

 sel layer_perfs%.no_l%

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 resel L%n% gt 0

 calc layer%n% = %n%

 commit

 &end /* do

 &call redefine_%.no_l%_rtne

 resel junk_layer gt 0 

 unload lp_wellids wellid

 unload fix junk_layer

 commit

 sel 

QUIT /*TABLES

/* Edit temporary file. 

 &data vi fix > /dev/null

 :g/0/s///g

 :wq

 &end /* data

 &sys paste -d’,’ lp_wellids fix > loadok

TABLES

 define temp2

 wellid 15 15 c

 layer 5 10 i

 ~

 add from loadok

 commit

 sort wellid

 commit

 relate add r.2 temp2 info wellid wellid ordered auto

 sel layer_perfs%.no_l%
139 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 resel wellid = r.2//wellid

 calc layer_temp = r.2//layer

 commit

 resel layer_temp gt 0

 calc layer = layer_temp

 commit

QUIT /*TABLES

/*-- End new layers. 

/* clean up directory

 &do f &list temp.dat fix loadok lp_wellids 

 &if [exists %f%] &then &s junk [delete %f%]

 &end /* do-if-then

 &do f &list temp2 work.csv f.wcsv

 &if [exists %f% -info] &then &s junk [delete %f% -info]

 &end /* do-if-then

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 dropitem layer_perfs%.no_l% layer_perfs%.no_l% layer%n%

 &end /* do 

&call clean_layer_perfs%.no_l%

&return /* closes calc_perfs

/*---------------------mk_layer_perfs4

&routine mk_layer_perfs4

 frequency work.csv f.wcsv

 wellid

 layer

 PCNT1 

 PCNT2 

 PCNT3 

 PCNT4 

 end

 d3_1

 d4_1 

 d5_1

 d6_1

 d3_2

 d4_2

 d5_2

 d6_2

 d3_3

 d4_3

 d5_3

 d6_3

 d3_4

 d4_4

 d5_4

 d6_4

 end

TABLES

 sel f.wcsv
Appendix A 140

 unload temp.dat wellid layer PCNT1 PCNT2 PCNT3 PCNT4 ~

 d3_1 d4_1 d5_1 d6_1 d3_2 d4_2 d5_2 d6_2 d3_3 d4_3 d5_3 d6_3 ~

 d3_4 d4_4 d5_4 d6_4 

 sel

 define layer_perfs%.no_l%

 wellid 15 15 c

 layer 5 10 i

 PCNT1 7 9 N 5

 PCNT2 7 9 N 5

 PCNT3 7 9 N 5

 PCNT4 7 9 N 5

 ~

 sel

&return /* closes mk_layer_perfs4

/*---------------------mk_layer_perfs5

&routine mk_layer_perfs5

 frequency work.csv f.wcsv

 wellid

 layer

 PCNT1 

 PCNT2 

 PCNT3 

 PCNT4 

 PCNT5

 end

 d3_1

 d4_1 

 d5_1

 d6_1

 d3_2

 d4_2

 d5_2

 d6_2

 d3_3

 d4_3

 d5_3

 d6_3

 d3_4

 d4_4

 d5_4

 d6_4

 d3_5

 d4_5

 d5_5

 d6_5

 end

TABLES

 sel f.wcsv

 unload temp.dat wellid layer PCNT1 PCNT2 PCNT3 PCNT4 PCNT5 ~

 d3_1 d4_1 d5_1 d6_1 d3_2 d4_2 d5_2 d6_2 d3_3 d4_3 d5_3 d6_3 ~

 d3_4 d4_4 d5_4 d6_4 d3_5 d4_5 d5_5 d6_5 
141 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 sel

 define layer_perfs%.no_l%

 wellid 15 15 c

 layer 5 10 i

 PCNT1 7 9 N 5

 PCNT2 7 9 N 5

 PCNT3 7 9 N 5

 PCNT4 7 9 N 5

 PCNT5 7 9 N 5

 ~

 sel

&return /* closes mk_layer_perfs5

/*---------------------redefine_4_rtne

&routine redefine_4_rtne

redefine 

 234 

 junk_layer 4 4 I

~

&return /* closes redefine_4_rtne

/*---------------------redefine_5_rtne

&routine redefine_5_rtne

redefine 

 286 

 junk_layer 5 5 I

~

&return /* closes redefine_5_rtne

/*---------------------clean_layer_perfs4

&routine clean_layer_perfs4

 &do i &list D3_1 D4_1 D5_1 D6_1 D3_2 D4_2 D5_2 D6_2 D3_3 D4_3 D5_3 D6_3 ~

 D3_4 D4_4 D5_4 D6_4

 dropitem layer_perfs%.no_l% layer_perfs%.no_l% %i%

 &end /* do 

&return /* closes clean_layer_perfs4

/*---------------------clean_layer_perfs5

&routine clean_layer_perfs5

 &do i &list D3_1 D4_1 D5_1 D6_1 D3_2 D4_2 D5_2 D6_2 D3_3 D4_3 D5_3 D6_3 ~

 D3_4 D4_4 D5_4 D6_4 D3_5 D4_5 D5_5 D6_5 

 dropitem layer_perfs%.no_l% layer_perfs%.no_l% %i%

 &end /* do

&return /* closes clean_layer_perfs5

/*---------------------calc_pcnt

&routine calc_pcnt

/* calcs percent of total pumpage from layer n
Appendix A 142

/* makes INFO table: layer_pcnts%.no_l%

/* kills INFO table: layer_perfs%.no_l%

/* where: k(n) = hydraulic conductivity of layer n (ft/sec)

/* pcnt(n) = L(n) * k(n) / L1*k1 + L2*k2 ... + L(n)*k(n)

/* pcnt(n) = percentage of total pumpage from layer n 

/* (representative fraction)

/*-- Verify cleanup of directory.

&if [exists layer_pcnts%.no_l% -info] &then &s junk ~

 [delete layer_pcnts%.no_l% -info]

TABLES

/*-- Begin percent calcs based on perf. interval length and K(n).

 &if ^ [iteminfo well_Ks_%.no_l% -info wellid -indexed] &then 

 indexitem well_Ks_%.no_l% wellid

 relate add r.1 well_Ks_%.no_l% info wellid wellid linear auto

 /* Set up file to receive new percent value for each layer.

 copy layer_perfs%.no_l% layer_pcnts%.no_l%

 /* Items L(n) and k(n) come from other files and are related by wellid.

 additem layer_pcnts%.no_l% denom 11 11 N 7

 sel layer_pcnts%.no_l% 

 /* Calculate pcnt%n% for each layer.

 &call calc_denom%.no_l%

 resel layer_temp gt 0

 resel denom ne 0 /* verify the denominator is not equal to zero.

 &do n = [unquote 1 &to %.no_l% &by 1 ] 

 calc pcnt%n% = L%n% * r.1//k%n% / denom

 &end /* if-then-do

 commit

 /* Calc pcnt(n) for wells perfed in one layer.

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 resel layer_temp lt 1

 resel layer = %n% 

 calc pcnt%n% = 1

 commit

 &end /* do

 kill layer_perfs%.no_l%

QUIT /*TABLES

/*-- End percent calcs based on perf. interval length and K(n).

/* clean up directory

dropitem layer_pcnts%.no_l% layer_pcnts%.no_l% denom 

&return /* closes calc_pcnt

/*---------------------calc_denom4
143 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

&routine calc_denom4

/* calc pcnt(n) 

calc denom = L1 * r.1//k1 + L2 * r.1//k2 + L3 * r.1//k3 + L4 * r.1//k4

&return /* closes calc_denom4

/*---------------------calc_denom5

&routine calc_denom5

/* calc pcnt(n) 

calc denom = L1 * r.1//k1 + L2 * r.1//k2 + L3 * r.1//k3 + L4 * r.1//k4 ~

 + L5 * r.1//k5

&return /* closes calc_denom5

/*---------------------calc_qn

&routine calc_qn

/* Calculates total pumpage (-ft3/s) from each layer for each well.

/* where: q(n) = QT * pcnt(n)

/* q(n) = total pumpage assigned to layer n (-ft3/s)

/* QT = total pumpage of well (-ft3/s)

/* makes INFO table: QT_%.no_l%_pred%.pcnt_qt%

/* kills INFO table: layer_pcnts%.no_l%

/* Verify directory cleanup.

 &do f &list QT_%.no_l%_pred%.pcnt_qt% pumpage_temp

 &if [exists %f% -info] &then &s junk [delete %f% -info]

 &end /* do-if-then

 &if [exists load_this] &then &s junk [delete load_this]

copyinfo total_pumpage pumpage_temp

TABLES

 &if ^ [iteminfo layer_pcnts%.no_l% -info wellid -indexed] &then 

 indexitem layer_pcnts%.no_l% wellid

 relate add r.1 layer_pcnts%.no_l% info wellid wellid linear auto

 

 &if ^ [iteminfo well_rowcol -info wellid -indexed] &then 

 indexitem well_rowcol wellid 

 relate add r.2 well_rowcol info wellid wellid linear auto

/*-- Calcs one layer at a time (all years). Dumps to flat file: load_this.

/*-- Data in “load_this” are added to INFO table: QT_%.no_l%_pred%.pcnt_qt%.

 /* Set up pumpage_temp for calculations. 

 &do yr = 1945 &to 2027 &by 1 

 additem pumpage_temp Y%yr%qn 10 10 n 6 Y%yr%

 &end /* do

 additem pumpage_temp QT 10 10 N 6

 

 /* Add and update row column cell (=rowcol) items with current data.

 additem pumpage_temp layer 5 10 I # otherid2

 additem pumpage_temp row 4 10 I # layer

 additem pumpage_temp col 4 10 I # row

 additem pumpage_temp cell 8 8 I # col

 sel pumpage_temp
Appendix A 144

 resel wellid = r.2//wellid

 calc cell = r.2//cell

 calc row = r.2//row

 calc col = r.2//col

 sel

 

/*-- Begin calcs of net pumpage (qn) by well for layer n. 

 sel pumpage_temp

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 calc layer = %n%

 

 /* For the Reported Period:

 /* Converts total pumpage in acre-ft to -ft3/s (MODFLOW discharge). 

 &do yr = 1945 &to 1996 &by 1

 calc qt = ( Y%yr% * -.0013813 )

 /* Calculate vertical total pumpage 

 calc Y%yr%qn = qt * r.1//pcnt%n% 

 calc qt = 0

 &end /* do

 

 /* For the Predictive Period:

 /* Converts total pumpage in acre-ft to -ft3/s (MODFLOW discharge) 

 /* and adjusts total pumpage to the percentage set in the menu

 /* to test the predictive scenario of interest.

 &do yr = 1997 &to 2027 &by 1 

 calc qt = ( Y%yr% * -.0013813 ) * ( %.pcnt_qt% / 100 )

 /* Calculate vertical net pumpage 

 calc Y%yr%qn = qt * r.1//pcnt%n% 

 calc qt = 0

 &end /* do

 /* unload predictive data. 

 &s unload_years = Y1945qn

 &do n = 1946 &to 2027 &by 1

 &s unload_years = %unload_years% Y%n%qn

 &end /* do

 unload load_this WELLID otherid1 otherid2 layer row col cell ~

 %unload_years%

 commit

 

 /* set items back to zero. 

 calc qt = 0

 calc layer = 0

 commit

 &end /* do 

/*-- End calcs of q(n) for each layer.

 /* Set up file to receive computed data.

 define QT_%.no_l%_pred%.pcnt_qt%

 WELLID 15 15 C

 OTHERID1 15 15 C 

 OTHERID2 15 15 C

 LAYER 5 10 I 
145 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 ROW 4 10 I

 COL 4 10 I

 CELL 8 8 I 

 ~ 

 sel

 &do yr = 1945 &to 2027 &by 1

 additem QT_%.no_l%_pred%.pcnt_qt% Y%yr% 10 10 n 6

 &end /* do

 /* Load data into new INFO table.

 sel QT_%.no_l%_pred%.pcnt_qt%

 add from load_this

 commit

 sel

QUIT /*TABLES

/* Clean up directory.

 &do f &list pumpage_temp layer_pcnts%.no_l%

 &if [exists %f% -info] &then &s junk [delete %f% -info]

 &end /* do-if-then

 &if [exists load_this] &then &s junk [delete load_this]

&return /* closes calc_qn

/*---------------------pump_out

&routine pump_out

/* This unloads INFO table data to the well-package flat file 

/* in MODFLOW format, for initial, transient, or predictive 

/* time series. 

/* format =: layer(10f) row(10f) col(10f) Qn(10f) comment_lines

/* Variables below set in wellpkg.menu.

/* for initial-conditions .mfile = initial 

/* for transient .mfile = transient

/* for predictive .mfile = predictive 

/* Irrigation efficiency .pcnt_ir = .70 (example) 

/* reading from INFO tables:

/* QT_%.no_l%_pred%.pcnt_qt% -- annual -Q in ft3/s by layer

/* uf_lytle_ann -- annual +Q in ft3/s by layer

/* uf_bh_ann -- annual +Q in ft3/s by layer

/* rchg_mtn_ann -- annual +Q in ft3/s by layer

/* art_rchg_ann -- annual +Q in ft3/s by layer

&call cleanup_pump_out /* in case program bombed before.

TABLES

/*--Set MODFLOW file name. 

 &if %.qtype% cn ‘predict’ &then 

 &s .mfile = %.qtype%_%.no_l%_p%.pcnt_qt%_n%.pcnt_ir% 

 &else &do 

 &s .mfile = %.qtype%_%.no_l%_n%.pcnt_ir%
Appendix A 146

 &end /* if-then-else-do

 &if [exists %.mfile%.dat] &then &s junk [delete %.mfile%.dat]

 &type [quote UNLOADING -Q AND +Q TO MODFLOW FILE %.mfile%.dat.]

 

/*-- Prepare INFO tables for calculations.

 /* Add temporary items to INFO tables.

 &do X &list QT_%.no_l%_pred%.pcnt_qt% uf_lytle_ann uf_bh_ann ~

 rchg_mtn_ann art_rchg_ann

 additem %X% temp1 15 15 c

 additem %X% space 1 1 c

 &end /* do

 /* Add another temporary item to QT_%.no_l%_pred%.pcnt_qt%.

 additem QT_%.no_l%_pred%.pcnt_qt% pumpage_a 10 10 n 6

/*-- Calculate irrigation efficiency rate. 

 &s .IR = [unquote %.pcnt_ir% / 100 ] 

 

/*-- Output stress period net pumpage.

 /* Set header line

 &s header = ‘ 287 40’ 

 /* Unload header to MODFLOW format.

 sel QT_%.no_l%_pred%.pcnt_qt%

 resel $recno = 1

 unload %.mfile%.dat [quote %header%] columnar junk1

 commit

 /* Set years of data to unload to well-package flat file.

 &do .date = %.b_year% &to %.e_year% &by 1 /* simulation period.

 &s Y = Y%.date% 

 /* Calculate -Q net, taking out return flow.

 sel QT_%.no_l%_pred%.pcnt_qt%

 calc pumpage_a = %Y% * %.IR% 

 commit

 sel

 /* Count number of records by stress period that are in an active 

 /* cell and -Q lt 0. 

 sel QT_%.no_l%_pred%.pcnt_qt%

 move [quote [unquote ‘_’]%Y%] to temp1

 sort cell wellid

 resel %Y% lt 0 and cell gt 0 and layer gt 0

 show number select

 &s C1 = [show number select]

 commit

 &do X &list uf_lytle_ann uf_bh_ann rchg_mtn_ann art_rchg_ann

 /* Count no. of recs = active cell and +Q lt 0 per stress period.

 sel %X%

 &s name = %X%

 move [quote _%name%] to temp1

 resel %Y% gt 0
147 Numerical Simulation of Ground-Water Flow and Assessment of the Effects of Artificial Recharge in the Rialto–Colton Basin, San Bernardino County

 show number select

 &s C%X% = [show number select]

 &end /* do

 &s C3 = %C1% + %Cuf_lytle_ann% + %Cuf_bh_ann% + %Crchg_mtn_ann% ~

 + %Cart_rchg_ann%

 &if %C3% < 10 &then ~

 &s headvar = [quote %C3% %Y%]

 &else &if %C3% < 100 &then ~

 &s headvar = [quote %C3% %Y%]

 &else &if %C3% < 1000 &then ~ 

 &s headvar = [quote %C3% %Y%]

 &else ~

 &s headvar = [quote %C3% %Y%]

 commit

 /* Unload header and record count to MODFLOW format.

 sel QT_%.no_l%_pred%.pcnt_qt%

 commit

 resel $recno = 1

 unload %.mfile%.dat [quote %headvar%] columnar junk1

 commit

 /* Unload data to MODFLOW format.

 &do n = [unquote 1 &to %.no_l% &by 1 ]

 sel QT_%.no_l%_pred%.pcnt_qt%

 resel %Y% lt 0 and cell gt 0 and layer = %n% 

 unload %.mfile%.dat layer row col pumpage_a temp1 space wellid ~

 space otherid1 columnar junk1

 commit

 &do X &list uf_lytle_ann uf_bh_ann rchg_mtn_ann art_rchg_ann

 sel %X% 

 resel %Y% gt 0 and cell gt 0 and layer = %n% 

 unload %.mfile%.dat layer row col [quote %Y%] temp1 space ~

 cell columnar junk1 

 commit

 &end /* do

 &end /* do

 &end /* do 

/* Close the file with years to calculate data for.

&type [close -all]

QUIT /*TABLES

/* clean up directory

&call cleanup_pump_out

&return /* closes pump_out

/*---------------------cleanup_pump_out

&routine cleanup_pump_out

 &if [exists junk1 -file] &then &s junk [delete junk1 -file]
Appendix A 148

 &do X &list QT_%.no_l%_pred%.pcnt_qt% uf_lytle_ann uf_bh_ann ~

 rchg_mtn_ann art_rchg_ann

 dropitem %X% %X%

 temp1 

 space

 end

 &end /* do

dropitem QT_%.no_l%_pred%.pcnt_qt% QT_%.no_l%_pred%.pcnt_qt% pumpage_a

&return /* closes cleanup 

/*---------------------cleanup_rtne

&routine cleanup_rtne 

/* close all global variables set by this program.

 &dv .QTYPE .b_year .e_year .no_l .pcnt_ir .pcnt_qt .exit_pgm ~

 .mfile .IR .date 

 /* close routines set by this program.

 &if ^ [null [show relates]] &then &do

 relate drop;r.1;;

 relate drop;r.2;;

 &end /* if-then-do

 

 &return /* closes cleanup_rtne 

 

/*---------------------end of routines.