Documentation of the Santa Clara Valley 

Regional Ground-Water/Surface-Water 

Flow Model, Santa Clara County, California

By R.T. Hanson, Zhen Li, and C.C. Faunt

In cooperation with the

Santa Clara Valley Water District

Scientific Investigations Report 2004-5231

U.S. Department of the Interior

U.S. Geological Survey
U.S. Geological Survey, Reston, Virginia: 2004

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225-0286

U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

Charles G. Groat, Director

For more information about the USGS and its products:

Telephone: 1-888-ASK-USGS

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

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

endorsement by the U.S. Government.

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

reproduce any copyrighted materials contained within this report.

Suggested citation:

Hanson, R.T., Li, Zhen, and Faunt, C.C., 2004, Documentation of the Santa Clara Valley regional ground-water/surfacewater flow model, Santa Clara County, California: U.S. Geological Survey Scientific Investigations Report 2004–5231, 

75 p.
iii

Contents

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

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

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

Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

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

Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Land and Water Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Conceptual Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Geohydrologic Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Simulation of Ground-Water Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Model Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Previous Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Spatial Discretization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Temporal Discretization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Model Boundaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Hydraulic Properties. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Transmission Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Storage Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Flow Barriers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Simulated Inflows and Outflows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Valley-Floor Recharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Artificial Recharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Evapotranspiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Streamflow Routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Subsidence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Pumpage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Coastal Flow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Initial Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Model Revisions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Model Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Transient-State Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Model Sensitivity and Uncertainty. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

References Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
iv

Figures

Figure 1. Map showing Santa Clara Valley model area and model grid and 

selected water-level and compaction comparison sites, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Figure 2. Map showing geologic outcrops, major structural features, and depth 

to bedrock estimated from gravity for the Santa Clara Valley, 

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Figure 3. Graph showing cumulative departure for precipitation at San Jose and

Los Gatos, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Figure 4. Generalized section showing the extent of model layers of the previous

regional model (CH2M Hill, 1991) and the revised model. . . . . . . . . . . . . . . . . . . . . . . 10

Figure 5. Map showing the ground-water flow model grid and selected inflows and 

outflows for the Santa Clara Valley model, Santa Clara Valley, 

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 6. Maps showing the ground-water flow model grid, and multiplier arrays 

for selected hydraulic properties for the Santa Clara Valley model,

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 7. Maps showing the ground-water flow model grid and estimated mean 

monthly precipitation for the period 1952-99 for the Santa Clara Valley 

model, Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Figure 8. Map showing the streamflow-routing network for the Santa Clara Valley

model and selected inflow and comparison gaging stations, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Figure 9. Maps showing the ground-water flow model grid, skeletal elastic and

inelastic storage multipliers, and critical heads for all model layers

of the Santa Clara Valley model, Santa Clara Valley, California. . . . . . . . . . . . . . . . . 34

Figure 10. Map showing distributions of simulated pumped and nonpumped 

multi-aquifer wells, and single-aquifer wells for the Santa Clara

Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Figure 11. Graph showing distributions of simulated pumped, nonpumped, and

destroyed wells for selected monitoring wells, Santa Clara Valley, 

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Figure 12. Hydrographs showing measured and simulated water-level for 

selected long-term monitoring wells, Santa Clara Valley, California . . . . . . . . . . . . 46

Figure 13. Hydrographs showing measured and simulated streamflow for selected 

downstream gaging stations, Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . 52

Figure 14. Graph showing measured and simulated aquifer-system subsidence 

for selected extensometer wells, Santa Clara Valley, California . . . . . . . . . . . . . . . . 54

Figure 15. Graph showing measured and simulated water-level error for selected 

monitoring wells for all measurements and for each comparison

well, Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Figure 16. Graphs showing the distribution of measured and simulated wellbore

flow and estimated percentage of artificial recharge for

Williams No. 3 and 12th St. No. 10 water-supply wells, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Figure 17. Maps showing the hand-contoured measured and simulated groundwater levels, April and September, 1995, and March and September 

1997, for the Santa Clara Valley model, Santa Clara Valley, California . . . . . . . . . . . 60

Figure 18. Maps showing the hand-contoured measured subsidence, 1939–80, and

simulated ground compaction, 1983–99, for the Santa Clara Valley model, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Figure 19. Maps showing the InSAR-estimated seasonal compression 

and simulated deformation, January to September 1997, for the 

Santa Clara Valley model, Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . 65
v

Figure 20. Graphs showing percentages of components of the hydrologic 

budget for the previous model for the period 1970–89 and the revised 

model for the period 1970–99, Santa Clara Valley, California, and 

inflow and outflow components through time for the period 1970–99, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Animations

Animation 1. Map showing simulated water levels, 1970–99, for the Santa Clara 

Valley model, Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Animation 2. Map showing simulated wellbore flow for model layers 3 and 5, 1970–99,

for the Santa Clara Valley model, Santa Clara Valley, California . . . . . . . . . . . . . . . . 56

Animation 3. Map showing simulated streamflow gains and losses and groundwater recharge from precipitation for model layers 1 and 3, 1970–99, 

for the Santa Clara Valley model, Santa Clara Valley, California. . . . . . . . . . . . . . . . 56

Animation 4. Map showing simulated water levels, stream inflow, and artificial

recharge for model layers 1 and 3, 1970–99, for the Santa Clara Valley

model, Santa Clara Valley, California. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

Animation 5. Map showing simulated subsidence for all model layers and 

water-level change for layer 3, 1983–99, for the Santa Clara Valley model, 

Santa Clara Valley, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
vi

Tables

Table 1. Summary of calibrated base multiplier values for hydraulic properties 

of the Santa Clara Valley model, California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Table 2. Summary of horizontal flow barriers used in the Santa Clara Valley

ground-water flow model, California. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
vii

Conversion Factors, Vertical Datum, and 

Abbreviations

CONVERSION FACTORS

Temperature in degrees Celsius (oC) may be converted to degrees Fahrenheit (oF) as follows:

oF=1.8 oC+32.

VERTICAL DATUM

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. 

ABBREVIATIONS

CCOC Coyote Creek Outdoor Classroom (site)

cm centimeter

ET evapotranspiration

ft bls feet below land surface

g/cm3 grams per cubic centimeter

GHB general-head boundary

HFB Horizontal Flow Barrier (package)

HK horizontal hydraulic conductivity

IBS Interbed Storage (package)

InSAR interferometric synthetic aperture radar

K hydraulic conductivity

km/s kilometers per second

km-g/s-cm3 kilometers-grams per second-centimeter cubed

LPF Layer-Property Flow (package)

m meter

Multiply By To obtain

acre 0.4047 hectometer

acre-foot (acre-ft) 0.001233 cubic hectometer

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

foot (ft) 0.3048 meter

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

square foot per day (ft2/d) 0.09290 square meter per day

inch (in.) 25.4 millimeter

mile (mi) 1.609 kilometer

square mile (mi2) 2.590 square kilometer

pound 0.4545 kilogram
viii

MF2K MODFLOW-2000

MNW Multi-Node Well (package)

PDO Pacific Decadal Oscillation

RMS root-mean-square

SCVM Santa Clara Valley model

STPK Santana Park (site)

STR Streamflow Routing (package)

VK vertical hydraulic conductivity

Organizations

CDWR California Department of Water Resources

SCVWD Santa Clara Valley Water District

USGS U.S. Geological Survey
ix

Well-Numbering System

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

system for the subdivision of public lands. Identification consists of the township 

number, north or south; the range number, east or west; and the section number. Each 

section is divided into sixteen 40-acre tracts lettered consecutively (except I and O), 

beginning with “A” in the northeast corner of the section and progressing in a sinusoidal 

manner to “R” in the southeast corner. Within the 40-acre tract, wells are sequentially 

numbered in the order they are inventoried. The final letter refers to the base line and 

meridian. In California, there are three base lines and meridians; Humboldt (H), Mount 

Diablo (M), and San Bernardino (S). All wells in the study area are referenced to the 

Mount Diablo base line and meridian (M). Well numbers consist of 16 characters and 

follow the format 007S001E016C008M. In this report, well numbers are abbreviated 

and written 7S/1E-16C8. Wells in the same township and range are referred to only by 

their section designation, 16C8. The following diagram shows how the number for well 

7S/1E-16C8 is derived.

IMPORT figure saved as PDF into text/anchored f rame below.

D C B A

E F G H

M L K J

N P Q R

6 5 4 3 2

7 8 9 10 11 12

18 17 15 14 13

19 20 21 22 23 24

30 29 28 26 25

31 32 33 34 35 36

27

R2E R3E

T6S

T5S

T4S

R1E

RANGE

TOWNSHIP

R2W R1W

T7S

T8S

R1E

Well-numbering diagram (Note: maps in this report use abbreviated well numbers such as "16C8") Mount Diablo Meridian

SECTION 16

T7S

7S/1E-16C8

1

16
x
Documentation of the Santa Clara Valley 

Regional Ground-Water/Surface-Water Flow Model, 

Santa Clara County, California

By R.T. Hanson, Zhen Li, and C.C. Faunt 

Abstract

The Santa Clara Valley is a long, narrow trough extending 

about 35 miles southeast from the southern end of San 

Francisco Bay where the regional alluvial-aquifer system has 

been a major source of water. Intensive agricultural and urban 

development throughout the 20th century and related groundwater development resulted in ground-water-level declines of 

more than 200 feet and land subsidence of as much as 12.7 feet 

between the early 1900s and the mid-1960s. Since the 1960s, 

Santa Clara Valley Water District has imported surface water 

to meet growing demands and reduce dependence on groundwater supplies. This importation of water has resulted in a 

sustained recovery of the ground-water flow system. To help 

support effective management of the ground-water resources, a 

regional ground-water/surface-water flow model was 

developed. This model simulates the flow of ground water and 

surface water, changes in ground-water storage, and related 

effects such as land subsidence.

A numerical ground-water/surface-water flow model of 

the Santa Clara Valley subbasin of the Santa Clara Valley was 

developed as part of a cooperative investigation with the Santa 

Clara Valley Water District. The model better defines the 

geohydrologic framework of the regional flow system and 

better delineates the supply and demand components that affect 

the inflows to and outflows from the regional ground-water 

flow system. Development of the model includes revisions to 

the previous ground-water flow model that upgraded the 

temporal and spatial discretization, added source-specific 

inflows and outflows, simulated additional flow features such 

as land subsidence and multi-aquifer wellbore flow, and 

extended the period of simulation through September 1999. 

The transient-state model was calibrated to historical surfacewater and ground-water data for the period 1970–99 and to 

historical subsidence for the period 1983–99.

The regional ground-water flow system consists of 

multiple aquifers that are grouped into upper- and loweraquifer systems. Ground-water inflow occurs as natural 

recharge in the form of streamflow infiltration and areal 

infiltration of precipitation along stream channels, artificial 

recharge from infiltration of imported water at recharge ponds 

and along selected stream channels, and leakage along selected 

transmission pipelines. Ground-water outflow occurs as 

evapotranspiration, stream base flow, discharge through 

pumpage from wells, and subsurface flow to the San Francisco 

Bay.

The geohydrologic framework of the regional groundwater flow system was represented as six model layers. The 

hydraulic properties were redefined on the basis of cell-based 

lithologic properties that were delineated in terms of aggregate 

thicknesses of coarse-grained, fine-grained, and mixed textural 

categories. The regional aquifer systems also are dissected by 

several laterally extensive faults that may form at least partial 

barriers to the lateral flow of ground water. The spatial extent 

of the ground-water flow model was extended and refined to 

cover the entire Santa Clara Valley, including the Evergreen 

subregion. The temporal discretization was refined and the 

period of simulation was extended to 1970–99. 

The model was upgraded to MODFLOW-2000 (MF2K) 

and was calibrated to fit historical ground-water levels, 

streamflow, and land subsidence for the period 1970–99. The 

revised model slightly overestimates measured water levels 

with an root-mean-square error of −7.34 feet. The streamflow 

generally shows a good match on gaged creeks and rivers for 

flows greater than 1.2 cubic feet per second. The revised model 

also fits the measured deformation at the borehole 

extensometer site located near San Jose within 16 to 27 percent 

and the extensometer site near Sunnyvale within 3 percent of 

the maximum measured seasonal deformation for the deepest 

extensometers.
2 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

The total ground-water inflow and outflow of about 

225,500 acre-feet per year (acre-ft/yr) for the period 1970–89 

and of about 205,300 acre-feet per year for the period 

1970–99 is comparable with that of the previous model, 

207,200 acre-ft/yr for the period 1970–89. Overall the 

simulated net change in storage increased by about 

189,500 acre-ft/yr for the entire period of simulation, which 

represents about one and a half years of the 1970–99 average 

pumping. The changes in ground-water flow and storage 

generally reflect the major climate cycles and the additional 

importation of water by Santa Clara Valley Water District, 

with the basin in recovery since the drought of the late 1980s 

and early 1990s. The average total recharge rate, from natural 

and artificial recharge and from streamflow infiltration for the 

revised model for the entire simulation period 1970–99, was 

about 157,100 acre-ft/yr, which represents about 59 percent of 

the inflow to the ground-water flow system. The average rate 

of artificial recharge of about 77,600 acre-ft/yr represents 

about 30 percent of the inflow to the ground-water flow 

system. The average pumpage for the entire 29.75-year 

simulation period is about 133,400 acre-ft/yr and represents 

about 69 percent of the outflow from the ground-water flow 

system. Most of the simulated recharge infiltrates and flows 

through the uppermost layers (i.e. model layers 1 and 3) of the 

aquifer system. Most of the water that flows to the deeper 

model layers is occurring through wellbores, with wellbore 

flow representing 19 percent of the total ground-water inflow 

between model layers.

Introduction

The Santa Clara Valley is a long narrow trough extending 

about 35 mi southeast from the southern end of San Francisco 

Bay (fig. 1). In the first half of the 20th century, the valley was 

intensively cultivated for fruit and truck crops. Subsequent 

development has included urbanization and industrialization, 

and the area is now commonly known as “Silicon Valley.” The 

area underwent extensive ground-water development from the 

early 1900s through the mid 1960s. This development caused 

ground-water-level declines of more than 200 ft and induced 

regional subsidence of as much as 12.7 ft from the early 1900s 

to the mid-1960s (Poland, 1971; Poland and Ireland, 1988). 

As with other coastal aquifer systems, the possibility exists for 

the combined effects of land subsidence and seawater intrusion 

with large water-level declines (Tolman and Poland, 1940; 

Iwamura, 1980). The San Francisco Water Department started 

delivering imported water to several north county cities in the 

early 1950s. In the 1960s the Santa Clara Valley Water District 

(SCVWD) began importing surface water into the valley to 

help meet growing demands for water and to reduce the area's 

dependence on ground water. Imported water is treated and 

delivered to ponds used to artificially recharge the aquifer 

system. The combination of reduced ground-water pumpage 

and artificial recharge has caused ground-water levels to 

recover to near their predevelopment levels and this, in turn, 

has arrested the land subsidence in the area. Currently, the 

water purveyors in the Santa Clara Valley, in conjunction with 

SCVWD, would like to meet the water demand in the basin, 

while limiting any potential for additional land subsidence. A 

detailed ground-water/surface-water model is needed to assess 

successful management strategies that will minimize land 

subsidence while maximizing a reliable water supply to meet 

growing demands from water users.

To protect the quantity and quality of the ground-water 

supplies and reduce the adverse effects of subsidence, the 

SCVWD already operates a comprehensive watermanagement program. The program includes artificial 

recharge, an in-lieu replacement program in which imported 

water is provided to pumpers to supplant ground-water use, 

and promotion of conservation techniques. 

In order to evaluate how these activities can be conducted 

most effectively, it is necessary to compile and collect data to 

describe the geohydrologic and geochemical framework of the 

Santa Clara Valley, develop appropriate modeling tools to help 

understand the ground-water system, and provide a tool for 

evaluating alternative management strategies.

Purpose and Scope

The purpose of this study was to acquire a better 

understanding of the hydrogeologic system in the Santa Clara 

Valley and to develop a tool to help analyze the changes in 

storage and the potential problems affecting water-resources 

management for this coastal aquifer system. The study 

included development of a ground-water/surface-water flow 

model that simulates the historical development for the period 

1970–99 and related tools to help analyze simulation results. 

The purpose of this report is to describe the components of the 

regional ground-water/surface-water flow model that was 

constructed by the U.S. Geological Survey (USGS) in 

cooperation with the Santa Clara Valley Water District.

Approach

The regional model of ground-water/surface-water flow 

that simulates the hydrologic system was developed to help 

SCVWD evaluate the natural and human-induced controls on 

the regional water resources (fig. 1). This study revises and 

updates the Santa Clara Valley Model (SCVM) from the 

previous ground-water flow model (CH2M Hill, 1991) by 

incorporating new knowledge gained from recent studies, new 

hydrologic data, and new simulation techniques. 
Introduction 3

6S

7S

8S

5S

3W 2W 1W 1E 2E

280

280

680

880

101

101

130

237

85

35

35

84

17

87

82

A

A'

San Jose

Los Gatos

7A3 10J1

5N1, 2

33M3

3K3

34F2

24H1

7R99

30C2 22E2

22E14

15E1

5P2 9Q1

6P1

2G2 6L1 1B1

33A2

4E2

Williams No. 3

28N1

24C7 21A1

24H8

15Q1

2J6

16C8

18L1

Wells—

Wellbore flow wells

USGS multi-well

monitoring site

Model hydrograph

comparison wells

Extensometers

Rivers and streams

Percolation ponds

Reservoirs

Extent of

confined

aquifer zone

Alluvial basin

boundary

Active model grid—

layer 3

Evergreen subregion

Township and

range grid

Santa

Clara

Co

San Mateo

Co

EXPLANATION

12th Street #10 STPK

CCOC

Model faults—

Precipitation

stations

Monte Vista

New Cascade

Silver Creek

Evergreen

Model profile

(see fig. 4)

San

Francisco

Bay

San

Jose

CRH

ERH

NE

NWC

NWW

SCR

SEC

Subgroups (see fig. 12)

A A'

Alameda

Co

Santa Cruz

Co

Coyote Hills

DIABLO RANGE

SANTA CRUZ MTS

Oak Hill

Edenvale Hills

Coyote

Narrows

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

Universal Transverse Mercator Projection, Zone 10

0246 8 10 MILES

0246 8 10 KILOMETERS

Area of

map

Ca lifornia

Pacific Ocean

N

Figure 1. Santa Clara Valley model area and model grid and selected water-level and compaction comparison sites, Santa Clara Valley, California.
4 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

The previous model represented a compilation of previous 

hydrologic studies of the basin (California Department of 

Water Resources, 1967; Johnson and Dreiss, 1989; Iwamura, 

1995) and databases (Majumdar and others, 1977; CH2M Hill, 

1992a; Jaimes, 1998). The revised SCVM modifies the 

previous model with improved simulation techniques, and 

includes information derived from additional and subsequent 

studies of the ground-water resources (Muir and Coplen, 1981; 

Wilson, 1993; Metzger, 2002) and the geohydrologic 

framework (Poland and Ireland, 1988; Koltermann and 

Gorelick, 1992; Leighton and others, 1994; Fio and Leighton, 

1995).

A major revision to the modeling technique was the 

separation and re-estimation of major inflow and outflow 

components, which were combined in the previous model. In 

addition, several new model packages explicitly account for 

subsidence, streamflow routing, faults as horizontal flow 

barriers, multi-aquifer well pumpage for separation of 

intraborehole flow from interlayer flow, and inflow and 

outflow with general-head boundaries at the coastal boundary 

along the San Francisco Bay. The previous regional model 

(CH2M Hill, 1991) simulated a six-layer regional aquifer 

system within the Santa Clara Valley subbasin of the Santa 

Clara Valley (herein simply referred to as the Santa Clara 

Valley) with an areal extent of about 23 mi long and 14 mi wide 

(fig. 1). The previous model simulated ground-water flow for 

the period 1970–89 with constant-head boundaries at the 

inflow and outflow locations; a composite net-recharge 

composed of artificial recharge, natural areal and streamflow 

infiltration, transmission-pipe losses, and potential 

evapotranspiration; and a fixed vertical distribution of groundwater pumpage that spanned up to four layers for multi-aquifer 

wells.

All hydraulic properties were transformed from zonebased estimates to lithologic cell-based estimates. The groundwater model used for simulation was upgraded from 

MODFLOW-88 (McDonald and Harbaugh, 1988) to MF2K 

(Harbaugh and McDonald, 1996; Harbaugh and others, 

2000b). The revised model simulates artificial recharge plus 

transmission-line losses, natural areal recharge, streamflow 

routing and infiltration, and evapotranspiration separately. In 

addition, the constant-head boundaries were replaced with 

general-head boundaries at the Bay, and the simulation of 

subsidence, faults as horizontal-flow boundaries, and multiaquifer well pumpage were added to the model. Finally, 

seasonal stress periods were reduced to monthly periods and 

the simulation period was extended to 1999. The spatial 

discretization was revised to a uniform grid of 1,000-ft2 cells, 

and the areal extent of the model was expanded to include the 

Evergreen subarea in the southeastern part of Santa Clara 

Valley. These features allow the exploration of conjunctive-use 

and related ground-water development/replenishment 

strategies that affect the management of the water resources by 

SCVWD and better facilitate the evaluation of water-resources 

with respect to subsidence, recharge, and sustainability. 

Description of Study Area

The Santa Clara Valley is a 240-mi2 coastal watershed 

that borders the southern San Francisco Bay and principally 

drains parts of Santa Clara and San Mateo Counties (fig. 1). 

Most of the basin is characterized by gently sloping topography 

of coalescing alluvial fans that combine to form the valley floor 

and coastal tidal lowlands. 

The onshore ground-water basin is bounded by the Santa 

Cruz Mountains on the west, the Diablo Range and the Coyote 

Hills to the northeast, and small hills such as Oak Hill, and the 

Edenvale Hills to the southeast near Coyote Narrows (fig. 1). 

Mountain peaks in the Santa Cruz Mountains on the west 

exceed 2,600 ft in altitude, and peaks in the Diablo Range on 

the east exceed 4,200 ft. The sloping offshore plain and 

underlying aquifers extend beneath the Bay. However, the 

location of the northwest boundary and the extent of the 

ground-water basin offshore beneath the Bay and its 

connection with adjacent areas such as the Niles Cone or 

Fremont ground-water areas remains uncertain. In general, 

ground-water flow in the Santa Clara Valley can be 

characterized as a convergent regional flow system within a 

basin bounded by mountains and hills on three sides. Recharge 

to the ground-water flow system starts along the mountain 

fronts and flows toward the center of the basin and toward the 

southern San Francisco Bay. Much of the predevelopment flow 

paths has been modified by pumping centers characterized by 

groups of wells that have resulted in subregional cones of 

depression and related flow paths. Discharge from the groundwater flow system occurs as pumpage, underflow, base flow to 

streams, and evapotranspiration.
Introduction 5

The Santa Clara Valley is a regional ground-water basin 

that has been divided into two onshore subregions that 

represent the confined and unconfined parts of the aquifer 

systems (fig. 1). The basin contains extensive alluvial-aquifer 

systems that are bounded by faults and bedrock mountains 

(fig. 1). The area has undergone extensive ground-water 

development in the shallow upper aquifers (locally referred to 

as the “upper aquifers”), which are composed of Recent, 

Holocene-age, and Pleistocene-age fluvial deposits and marine 

estuarine deposits (locally referred to as the “Bay Mud” and 

“Old Bay Mud”) (fig. 2). Extensive ground-water development 

also has occurred below these deposits in the Pleistocene and 

Pliocene-age fluvial deposits that are locally referred to as the 

“lower aquifers” (fig. 2). The alluvial deposits that form the 

regional aquifer systems are unconformably underlain by 

Pliocene-age deposits of the Santa Clara Formation, Tertiaryage sediments that include the Miocene-age parts of the 

Monterey Formation, and Tertiary-age serpentinites (fig. 2). 

These underlying deposits form the relatively impermeable 

base of the regional aquifer systems. The alluvial aquifer 

systems are composed of a complex sequence of layers of 

fluvial sand and gravel and fluvial fine-grained silt and clay 

(California Department of Water Resources, 1967; Wagner 

and others, 1990; Wentworth, 1993, 1997; Wentworth and 

others, 1998; Knudsen and others, 2000). 

The surface-water system in the Santa Clara Valley 

includes the natural streamflow network, seven reservoirs, and 

a system of aqueducts, pipelines, and storm drains. The major 

streams discharge directly to the San Francisco Bay through 

the tidal lowlands along the southern end of San Francisco 

Bay. Other creeks, such as San Francisquito Creek that forms 

the northwestern boundary of the Santa Clara Valley Water 

District, drain directly into the San Francisco Bay. The 

reservoirs discharge directly into several of the major 

tributaries and creeks. The aqueducts and pipelines are used to 

transport imported water directly to treatment plants where the 

water is treated and then delivered to artificial-recharge 

facilities. The storm-drain channels drain additional runoff 

from the valley floor to the San Francisco Bay.

Climate

The climate of the basin is mediterranean and 89 percent 

of the rainfall occurs between November and April, which is 

typical of the California coastal areas. Average annual 

precipitation is about 14.5 in. at the City of San Jose

(1883–2002), about 23 in. near Los Gatos (1964–2001) in the 

intermediate altitudes of the Santa Clara Valley, and more than 

50 in. in the surrounding mountains (fig. 3). The average daily 

mean temperature ranges from 27.9οC (82.2οF) in San Jose 

during the middle of summer to below freezing in the 

bordering mountains during the winter. 

The climate is seasonally variable and has been variable 

throughout the period of record in the past century. The 

cumulative departure rainfall at San Jose, during the past 

century indicates a persistent set of multi-year wet and dry 

periods—some that are relatively long (10 to 21 years) and 

some periods that are shorter (2 to 9 years) (fig. 3). These wet 

and dry periods also are related to major droughts and floods 

(California History Center, 1981). Although wet years may 

occur in dry periods and dry years in wet periods, the historical 

climate (fig. 3) generally can be categorized into six climate 

cycles that represent 13 wet and dry periods that were 

determined from the cumulative departure of annual 

precipitation at San Jose as:

Land and Water Use

Prior to the 1900s, most land in the Santa Clara Valley 

was used for grazing cattle and dry-land farming. In the early 

1900s, agriculture was the chief economic activity. As in most 

coastal basins in California, urbanization since the late 1940s 

resulted in the transfer of agricultural lands to residential and 

commercial uses. Since 1915 the population of the valley has 

grown from less than 100,000 to more than 1.7 million in 2000, 

with a 12.4 percent increase between 1990 and 2000 in Santa 

Clara County (U.S. Census Bureau, 2003). Water use has 

changed from predominantly agricultural prior to the 1960s to 

almost completely urban and industrial water use since the 

mid-1960s. About 12.7 ft of land subsidence and more than 

200 ft of ground-water-level decline occurred from groundwater development from the early 1900s to the mid-1960s. To 

mitigate the effects of ground-water depletion, surface water 

was imported for direct use starting in the 1950s and for 

artificial recharge in the mid-1960s. Owing to the proximity to 

the San Francisco metropolitan area and the continued growth 

of the technology industries, growth may continue with an 

expanding urban and industrial economy. An excellent 

summary of the early development of water resources in Santa 

Clara County is given by the California History Center (1981). 

Cycle Wet Dry

1 — 1874–87

2 1888–96 1897–1903

3 1904–16 1917–36

3 1937–44 1945–65

4 1966–75 1976–77

5 1978–83 1984–91

6 1992–98 1999–2002
6 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Qh

Qp

Qp

Qp

sp

sp

Qhbm

QT

QT

Ts

Ts

Ts

Ts

KJf

KJf

KJs KJf

SAN ANDREAS

BERROCAL

MONTE

VISTA

CALAVERAS

SILVER CREEK

NEW CASCADE

HAYWARD

Geology from C. Wentworth,

U.S. Geological Survey,

written commun., 2003

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

Tertiary—Consolidated/unconsolidated sedimentary deposits

Pliocene-Quaternary-age sedimentary deposits (Santa Clara

Formation and equivalents)

Tertiary-age sedimentary deposits (includes some volcanics

and the Monterey Formation)

QT

Ts

Mesozoic—Consolidated rock

Franciscan assemblage

Great Valley sequence

Serpentinite and associated

Coast Range ophiolite complex

KJf

KJs

sp

Faults—Dashed where inferred

Quaternary—Unconsolidated sedimentary deposits

Late-Pleistocene-age deposits

Holocene-age deposits

Holocene-age Bay Muds

Qp

Qh

Qhbm

Alluvial basin boundary

Streams

San

Francisco

Bay

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

Universal Transverse Mercator Projection, Zone 10

Figure 2. Geologic outcrops, major structural features, and depth to bedrock estimated from gravity for the Santa Clara Valley, California.
Introduction 7

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

W DRY WET D W D W D D W W D D W

Year

Annual precipitation cumulative departure, in inches

MODEL SIMULATION

PERIOD 1970–99

–60

–50

–40

–30

–20

–10

0

10

20

30

40

San Jose annual

cumulative departure

Los Gatos annual

cumulative departure

EXPLANATION

Figure 3. Cumulative departure for precipitation at San Jose and Los Gatos, California.
8 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Acknowledgments

This study could not have been accomplished without the 

assistance of personnel from the Santa Clara Valley Water 

District. In particular Mark Merritt, Vanessa Reymers, Roger 

Pierno, and Bezhad Ahmadi are especially acknowledged for 

assistance with compilation of data needed to assemble the 

ground-water/surface-water flow model. We thank USGS 

hydrologists Keith Halford for his major contributions to the 

multi-node well package, Steve Predmore for his contribution 

to ARC-GIS algorithms for creating the streamflow network 

for MODFLOW, and Peter Martin for his technical guidance. 

In addition, we acknowledge the valuable guidance of USGS 

geologists/geophysicists Carl Wentworth and Bob Jachens for 

their contribution to characterizing the basin stratigraphy and 

structure.

Conceptual Model

Regional ground-water flow within the multiple aquifers 

of the Santa Clara Valley is the result of natural and artificial 

inflows and outflows. Ground water flows from the edges of 

the elliptical basin along the mountain fronts, where a 

combination of natural and artificial recharge enters the 

aquifers, to the pumping centers in the central part of the basin 

and to the Bay as underflow.

Ground-water inflow occurs as recharge, subsurface flow 

along the northern coastal boundary of the southern San 

Francisco Bay, and water derived from aquifer and interbed 

storage. Ground-water recharge includes areally distributed 

infiltration of precipitation in excess of runoff and evaporation, 

streamflow infiltration, artificial recharge, and losses from 

water-transmission lines. Ground-water outflow occurs as 

evapotranspiration, stream base flow, discharge through 

pumpage from wells, and subsurface flow to the San Francisco 

Bay. 

Geohydrologic Framework

For the purposes of the regional flow model, the regional 

ground-water flow systems are subdivided into upper-aquifer 

and lower-aquifer systems. The upper-aquifer system is 

composed of the Shallow aquifer, which is coincident with 

Holocene-age deposits, and the mid to late Pleistocene-age 

deposits. The upper-aquifer system contains some water that 

recently (less than 50 years before present) entered the groundwater system as recharge and some water that has entered the 

system as much as 2,500 years before present (Hanson and 

others, 2002a). The lower aquifer system is composed of 

sediments of early Pleistocene or Pliocene age and contains 

water that entered the ground-water system more than 10,000 

years before present (Hanson and others, 2002a). The presence 

of the Santa Clara Formation in the alluvial deposits of the 

Santa Clara Valley remains uncertain. The Santa Clara 

Formation was not initially identified in many deeper wells 

(Tolman and Poland, 1940) and has not been encountered in the 

recently completed multi-well monitoring sites completed by 

the USGS in cooperation with SCVWD. Therefore, the depth 

of the alluvial aquifer system and the depth of the effective 

ground-water flow system remain uncertain in some parts of 

the valley. The further delineation of the sequence stratigraphy 

and related hydrostratigraphy is part of ongoing USGS studies 

(Jachens and others, 2001). The regional aquifer system is 

underlain and surrounded by the relatively impermeable 

bedrock.

The ground-water flow system also is affected by the 

presence of faults that may potentially act as hydrologic flow 

barriers and by lithofacies that may represent regions of 

enhanced or reduced permeability. The faults identified as part 

of this study include the Silver Creek and Evergreen Faults in 

the eastern part of the valley and the Monte Vista and New 

Cascade Faults in the western part of the valley. In addition to 

these features, coarse-grained facies subparallel to and beneath 

selected stream channels potentially provide enhanced 

permeability, and fine-grained facies beneath other selected 

stream channels reduce permeability.

Simulation of Ground-Water Flow

A numerical ground-water flow model of the two regional 

aquifer systems in the Santa Clara Valley was developed to 

simulate transient conditions for the historical period of 

January 1970–September 1999. Model simulations provide a 

means to determine hydrologic conditions and aquifer response 

to changes in inflow and outflow through time over several 

climate cycles. Simulations were made using the threedimensional finite-difference ground-water flow model, 

MODFLOW-2000 (MF2K) (Harbaugh and others, 2000a, b). 

Additional packages were used in conjunction with the groundwater flow model to simulate the routing of streamflow 

(Prudic, 1989), land subsidence (Leake and Prudic, 1991), 

faults as horizontal barriers to ground-water flow (Hsieh and 

Freckleton, 1993), multi-aquifer (multi-node) wells (Halford 

and Hanson, 2002), and estimation of hydrologic time-series 

for ground-water levels, streamflow, and deformation (Hanson 

and Leake, 1998).
Simulation of Ground-Water Flow 9

The revised Santa Clara Valley model (SCVM) was 

calibrated with transient simulation that spans 30 years

(1970–99), over a period of systematic hydrologic data 

collection including reported pumpage. The steady-state 

simulation was not included because initial heads were used 

from the previous model, which was calibrated to a mean 

initial condition that generally represents those in 1970 on the 

basis of measured 1970 water levels (CH2M Hill, 1992b). 

Calibration of the SCVM included matching ground-water 

levels, streamflow, aquifer-system deformation, and selected 

wellbore flow during 1970–99. The SCVM separates the 

supply components (recharge and intrawellbore flow to the 

aquifers) and demand components (pumpage, changes in 

storage, stream base flow, evapotranspiration, and potential 

outflow at the Bay). This model structure facilitates the 

analysis and assessment of water-resources management 

alternatives and related changes in storage. The model also 

facilitates the analysis of the effect that implementation of 

selected alternatives and geologic controls might have on 

recharge, coastal landward flow (seawater intrusion), land 

subsidence, ground-water movement, and overall resource 

management under climatically varying conditions that affect 

supply and demand.

Model Framework

The SCVM is an extension and refinement of the 

previously developed regional models and local onedimensional deformation models. The orientation, areal extent, 

spatial and temporal discretization, model boundaries, and 

zonation of hydraulic properties constitute the framework of 

the numerical ground-water flow model developed for this 

study. 

Previous Models

The first models of the Santa Clara Valley divided the 

system into three model layers: an uppermost unconfined, a 

middle confining, and a lower confined layer (California 

Department of Water Resources, 1975; Reichard and 

Bredehoeft, 1984). The previous regional model (CH2M Hill, 

1991) simulated a six-layer regional aquifer system that was 

similar in structure, with an upper unconfined layer, a middle 

confining layer and a lower confined system that is split into 

four layers; the lowest layer is below the depth of most 

historical ground-water pumping (figs. 1, 4). The previous 

model covered the entire Santa Clara Valley except for the 

Evergreen subregion and had variable grid spacing with the 

smallest cells of 1,000 by 1,000 ft located near San Jose 

(CH2M Hill, 1991). This previous regional model simulated 

ground-water flow using MODFLOW-88 (McDonald and 

Harbaugh, 1988) for the period 1970–89. 

The simulation of subsidence was previously investigated 

(Reichard and Bredehoeft, 1984; Poland and Ireland, 1988; 

Wilson, 1993) and was assessed by SCVWD at selected well 

sites throughout the basin by the use of separate onedimensional deformation models (Helm, 1975, 1977, 1978; 

Poland and Ireland, 1988) that used water-level time-series 

derived from the regional ground-water flow model to drive 

the simulation of one-dimensional deformation. This previous 

approach to the simulation of ground-water/surface-water flow 

and subsidence decoupled the processes and did not allow for 

the interchange of mass flow. Combining the simulations in 

one regional model couples ground water released from or 

taken into storage related to aquifer-system deformation (i.e. 

compression as elastic deformation and compaction as 

inelastic deformation) and ground-water flow. 

 Spatial Discretization

The model grid of the SCVM is identical to the previous 

models (CH2M Hill, 1991), covers the entire alluvial aquifer 

system of the Santa Clara Valley, including the Evergreen 

subregion, and extends offshore into the southern San 

Francisco Bay in the northwest corner of all layers (fig. 1). The 

orientation of N 27.8οW and extent of the model grid was 

retained from the previous model (CH2M Hill, 1991). The 

SCVM contains a uniform grid with a cell size of 1,000 by 

1,000 ft for a total of 106 rows and 172 columns (fig. 1). In a 

manner similar to that of the previous model (CH2M Hill, 

1991), the SCVM contains six layers (fig. 4), five for the 

upper-aquifer system and one for the lower-aquifer system. 

The six model layers differ in areal extent throughout the 

model domain and the largest areal extent is in model layer 3 

(fig. 4). The top of the upper layer was realigned with the land 

surface throughout the upper layer (layer 1) and portions of 

layer 3 where the upper two layers are inactive. The bottom of 

the uppermost layer and the tops of the other five layers are 

coincident with the layer boundaries estimated for the previous 

model, except for the Evergreen subregion. These model-layer 

boundaries were generally aligned with the predominant 

altitudes of screened intervals in the water-supply wells. The 

bottom of the lowest layer remains relatively uncertain, but it 

is generally coincident with the bottom of the PliocenePleistocene alluvial deposits throughout most of the model 

area. In some areas the bottom of the lowest layer is coincident 

with relatively impermeable bedrock.
10 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

? ?

New Cascade Fault

Silver Creek Fault Evergreen

Fault

Monte Vista Fault

Altitude, in feet above NAVD 88

600

400

200

NAVD

88

–200

–400

–600

–800

–1,000

0 20,000 40,000 60,000 80,000

Confined-zone boundary

Distance along cross section, in feet

Model layer 1

Model layer 2

Model layer 3

Model layer 4

Model layer 5

Model layer 6

Vertical Exaggeration = 30X

A

(SW)

A'

(NE)

Figure 4. Extent of model layers of the previous regional model (CH2M Hill, 1991) and the revised model.
Simulation of Ground-Water Flow 11

The upper part of the upper-aquifer system represented by 

model layer 1 is composed of the Shallow aquifer consisting of 

Holocene-age and late-Pleistocene-age deposits and has an 

areal extent of about 122 mi2. The second layer represents the 

group of fine-grained deposits that includes the “Bay Mud” and 

“Old-Bay Mud” and is coincident in areal extent with layer 1. 

The upper-aquifer system has its largest areal extent in model 

layer 3 (fig. 1) with an active flow region of about 323 mi2, of 

which about 30 percent is offshore. The lower parts of the 

upper-aquifer system are represented by model layers 4 and 5 

and have an active flow region of 258 mi2 and 240 mi2, 

respectively; about 30 per cent of layer 4 and 32 percent of 

layer 5 are offshore. The lower-aquifer system is represented 

by model layer 6, which has an active flow region of 213 mi2, 

36 percent of which is offshore.

Temporal Discretization

The previous model simulated the historical period using 

a 14-year calibration period, 1970–83, and a six-year 

“verification” period, 1984–89. Trial-and-error calibration was 

achieved through adjustments to inflows, outflows, and 

hydraulic properties to match selected ground-water-level 

hydrographs at selected wells (locations shown in fig. 1). The 

temporal discretization of the previous model was seasonal 

stress periods using variable time steps (CH2M Hill, 1991). 

Therefore, all specified inflows and outflows such as recharge 

and pumpage were held constant, using average values for 

periods of three months. In the SCVM the stress periods were 

reduced to monthly periods and weekly time steps. The 

monthly time periods are short enough to maintain some degree 

of separation in the variability present in ground-water 

pumpage, natural recharge, and artificial recharge, and are long 

enough to encompass the recession periods of most streamflow 

events.

Model Boundaries

The perimeter of the active flow region within the revised 

model represents the approximate limit of the ground-water 

flow system. The outer boundary is represented by a 

combination of no-flow, specified flow, and head-dependent 

boundaries (fig.5). The landward model cells along the outer 

boundary of all active cells in all model layers are represented 

as a no-flow boundary. No-flow boundaries occur where there 

is no flow of water between the active flow-region model cells 

and the adjacent areas. The bottom of the lower layer is also 

represented as a no-flow boundary and is coincident with older 

consolidated deposits of Tertiary age or bedrock comprising 

the Great Valley Sequence, the ophiolite sequence, or the 

Franciscan Formation of Mesozoic age (Stanley and others, 

2002). These no-flow boundaries represent the contact with 

non-water-bearing rocks. The runoff from the surrounding 

mountain fronts results in ungaged streamflow that forms 

recharge that enters along stream channels in the uppermost 

layer that is treated as specified inflows and is described later 

in this section. Evapotranspiration is treated as a sink and is a 

head-dependent boundary along all of the major stream 

channels (fig. 5) and is discussed later in this section of the 

report.

The offshore boundary in all layers is represented as a 

source-sink boundary that has been located at the northwestern 

edge of the model grid and represents coastal flow or underflow 

using water-bearing units that continue beneath San Francisco 

Bay (California Department of Water Resources, 1967). This 

boundary is represented in the model as a general-head 

boundary that simulates an inflow (source) of water from 

outside the model area or a discharge (sink) of water from the 

boundary model cells to outside the model area. The offshore 

boundary is described later in this report in the “Coastal Flow” 

section.

Hydraulic Properties

The intrinsic hydraulic properties for the aquifers used in 

the revised model include horizontal and vertical hydraulic 

conductivity and specific storage (fig. 6). Average values of 

hydraulic properties are assigned at the center of each cell. 

Estimates of hydraulic properties are based, in part, on cell-bycell estimates of fractions of thickness for beds predominantly 

composed of coarse-grained, fine-grained, or mixed deposits. 

The product of these fractions and a base value (table 1) result 

in cell-by-cell hydraulic property values. The fractional 

thicknesses are referred to as multiplier values (fig.6). All 

layers have different cell-by-cell multiplier values except 

layer 2 which had constant hydraulic properties (fig. 6). These 

cell-based estimates were derived from hundreds of indexed 

lithologies from drillers' and geologists' logs (Leighton and 

others, 1994, fig. 3). The lithologies were grouped in four 

major categories representing incompressible fine-grained, 

compressible fine-grained, mixed, and coarse-grained deposits. 

The thicknesses for each category were summed at each well 

and linearly interpolated to each cell within the equivalent 

depth intervals of the model layers as defined from the previous 

model. This approach is similar to that used in previous model 

studies that have used textural facies to distribute regional 

estimates of hydraulic properties (Zimmerman and others, 

1991; Hanson and others, 2002a). The relation of textural 

properties to sedimentary facies was previously demonstrated 

for the Santa Clara Valley by numerous researchers 

(Koltermann and Gorelick, 1992; Fio and Leighton, 1995; 

Johnson, 1995a, b; Johnson and Dreiss, 1999) and represents a 

reasonable basis for estimating spatially distributed hydraulic 

properties. 
12 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

South-Central Silver CreekSouth-Central Silver Creek

North EvergreenNorth Evergreen

New Cascade

Monte Vista

Monte Vista

New Cascade

North Silver CreekNorth Silver Creek

EXPLANATION

Water-supply transmission pipes (Model layers 1 & 3)

Campbell Distributary

Evergreen Pipeline

Mountain View Distributary

Parallel East Pipeline

Penetencia Delivery Main

Santa Clara Distributary

Santa Teresa Tunnel

Snell Pipeline

Sunnyvale Distributary

West Pipeline

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

Horizontal flow barrier

characteristics, in feet

per day (See table 2 for

model layer assignments)

0.01

0.1

0.0001

0.001

Recharge ponds

Model pond cell

Streams

Alluvial basin boundary

Extent of confined aquifer zone

General-head boundary cell (GHB)

North-Central Silver CreekNorth-Central Silver Creek

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and

digital data, 1:100,000, 1981–89; Universal Transverse Mercator Projection, Zone 10.

Shaded relief base from 1:250,000-scale Digital Elevation Model; simulated sun

illumination from northwest at 30 degrees above the horizon

Figure 5. Ground-water flow model grid and selected inflows and outflows for the Santa Clara Valley model, Santa Clara Valley, California.
Simulation of Ground-Water Flow 13

EXPLANATION

Elevation,

in feet above NAVD 88

Evapotranspiration rate, in feet per

day x 10-3

Streams

0.402 to 0.728

0.729 to 1.146

1.147 to 1.935

1.936 to 3.414

3.415 to 9.001

0.000 to 0.023

0.024 to 0.075

0.076 to 0.148

0.149 to 0.232

0.233 to 0.399

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

Extent of confined

aquifer zone

Alluvial basin

boundary

–6 to 95

96 to 259

260 to 465

466 to 728

729 to 1,040

1,041 to 1,385

1,386 to 1,739

1,740 to 2,136

2,137 to 2,618

2,619 to 3,517

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;

Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

(Model layers 1 & 3)

Figure 5. —Continued.
14 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California San Francisco Bay San Francisco Bay San Francisco Bay 0246 8 10 MILES 0246 8 10 KILOMETERS Streams Alluvial basin boundary Extent of confined aquifer zone Horizontal hydraulic conductivity multiplier 0.0040 to 0.0050 0.0051 to 0.0060 0.0061 to 0.0070 0.0071 to 0.0080 0.0081 to 0.0090 0.0091 to 0.1000 0.1001 to 0.2000 0.2001 to 0.3000 0.3001 to 0.4000 0.4001 to 0.5000 0.5001 to 0.6000 0.6001 to 0.7000 0.7001 to 0.8000 0.8001 to 0.9000 0.9001 to 1.0000 1.0001 to 2.0000

1234567891011 to 45

Vertical hydraulic

conductivity multiplier

EXPLANATION

Specific storage

multiplier

0.001 to 0.1000.101 to 0.2000.201 to 0.3000.301 to 0.4000.401 to 0.5000.501 to 0.6000.601 to 0.684

1

A

1 23

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

1

Figure 6. Ground-water flow model grid, and multiplier arrays for selected hydraulic properties for the Santa Clara Valley model, Santa Clara Valley, 

California.
Simulation of Ground-Water Flow 15

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin

boundary

Extent of confined

aquifer zone

Horizontal hydraulic

conductivity multiplier

Vertical hydraulic

conductivity multiplier

EXPLANATION

Specific storage

multiplier 1 23

0.0001 to 0.00100.0011 to 0.00200.0021 to 0.00300.0031 to 0.00400.0041 to 0.00500.0051 to 0.00600.0061 to 0.00700.0071 to 0.00800.0081 to 0.00900.0091 to 0.10000.1001 to 0.20000.2001 to 0.30000.3001 to 0.40000.4001 to 0.50000.5001 to 0.60000.6001 to 0.70000.7001 to 0.80000.8001 to 0.90000.9001 to 1.00001.0001 to 5.0000

0.001 to 0.0100.011 to 0.0200.021 to 0.0300.031 to 0.0400.041 to 0.0500.051 to 0.0600.061 to 0.0700.071 to 0.0800.081 to 0.0900.091 to 0.1001.0001 to 2.00002.0001 to 3.00003.0001 to 4.00004.0001 to 5.00005.0001 to 6.00006.0001 to 7.00007.0001 to 8.00008.0001 to 9.00009.0001 to 10.000010.0001 to 11.9054

1

Confined "Unconfined"

234567891011 to 4445 to 71

1

B

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

3

Figure 6. —Continued.
16 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California San Francisco Bay San Francisco Bay San Francisco Bay 0246 8 10 MILES 0246 8 10 KILOMETERS Alluvial basin boundary Extent of confined aquifer zone Horizontal hydraulic conductivity multiplier Vertical hydraulic conductivity multiplier EXPLANATION Specific storage multiplier 1 23 0.0001 to 0.0010 0.0011 to 0.0020 0.0021 to 0.0030 0.0031 to 0.0040 0.0041 to 0.0050 0.0051 to 0.0060 0.0061 to 0.0070 0.0071 to 0.0080 0.0081 to 0.0090 0.0091 to 0.1000 0.1001 to 0.2000 0.2001 to 0.3000 0.3001 to 0.4000 0.4001 to 0.5000 0.5001 to 0.6000 0.6001 to 0.7000 0.7001 to 0.8000 0.8001 to 0.9000 0.9001 to 1.0000 1.0001 to 5.0000 0.001 to 0.010 0.011 to 0.020 0.021 to 0.030 0.031 to 0.040 0.041 to 0.050 0.051 to 0.060 0.061 to 0.070 0.071 to 0.080 0.081 to 0.090 0.091 to 0.100 1.0001 to 2.0000 2.0001 to 3.0000 3.0001 to 4.0000 4.0001 to 5.0000 5.0001 to 6.0000 6.0001 to 7.0000 7.0001 to 8.0000 8.0001 to 9.0000 9.0001 to 10.0000 10.0001 to 11.9054

1

Confined "Unconfined"

234567891011 to 4445 to 71

1

B

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

3

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Horizontal hydraulic

conductivity multiplier

Vertical hydraulic

conductivity multiplier

EXPLANATION

Specific storage

multiplier 1 23

0.0011 to 0.00200.0021 to 0.00300.0031 to 0.00400.0041 to 0.00500.0051 to 0.00600.0061 to 0.00700.0071 to 0.00800.0081 to 0.00900.0091 to 0.10000.1001 to 0.20000.2001 to 0.30000.3001 to 0.40000.4001 to 0.50000.5001 to 0.60000.6001 to 0.70000.7001 to 0.80000.8001 to 0.90000.9001 to 1.0000

1234567891011 to 60

0.001 to 0.1000.101 to 0.2000.201 to 0.3000.301 to 0.4000.401 to 0.5000.501 to 0.6000.601 to 0.7000.701 to 0.8000.801 to 0.9000.901 to 1.000

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

C

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

4

Figure 6. —Continued.
Simulation of Ground-Water Flow 17

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Horizontal hydraulic

conductivity multiplier

Vertical hydraulic

conductivity multiplier

EXPLANATION

Specific storage

multiplier 1 23

0.0011 to 0.00200.0021 to 0.00300.0031 to 0.00400.0041 to 0.00500.0051 to 0.00600.0061 to 0.00700.0071 to 0.00800.0081 to 0.00900.0091 to 0.10000.1001 to 0.20000.2001 to 0.30000.3001 to 0.40000.4001 to 0.50000.5001 to 0.60000.6001 to 0.70000.7001 to 0.80000.8001 to 0.90000.9001 to 1.0000

1234567891011 to 60

0.001 to 0.1000.101 to 0.2000.201 to 0.3000.301 to 0.4000.401 to 0.5000.501 to 0.6000.601 to 0.7000.701 to 0.8000.801 to 0.9000.901 to 1.000

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

C

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

4

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Horizontal hydraulic

conductivity multiplier

Vertical hydraulic

conductivity multiplier

EXPLANATION

Specific storage

multiplier 1 23

0.0010 to 0.00200.0021 to 0.00300.0031 to 0.00400.0041 to 0.00500.0051 to 0.00600.0061 to 0.00700.0071 to 0.00800.0081 to 0.00900.0091 to 0.10000.1001 to 0.20000.2001 to 0.30000.3001 to 0.40000.4001 to 0.50000.5001 to 0.60000.6001 to 0.70000.7001 to 0.80000.8001 to 0.90000.9001 to 1.0000

1234567891011 to 44

45 to 74

0.001 to 0.1000.101 to 0.2000.201 to 0.3000.301 to 0.4000.401 to 0.5000.501 to 0.6000.601 to 0.7000.701 to 0.8000.801 to 0.9000.901 to 1.000

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

D

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

5

Figure 6. —Continued.
18 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California San Francisco Bay San Francisco Bay San Francisco Bay Horizontal hydraulic conductivity multiplier Vertical hydraulic conductivity multiplier EXPLANATION Specific storage multiplier 1 23 0.0010 to 0.0020 0.0021 to 0.0030 0.0031 to 0.0040 0.0041 to 0.0050 0.0051 to 0.0060 0.0061 to 0.0070 0.0071 to 0.0080 0.0081 to 0.0090 0.0091 to 0.1000 0.1001 to 0.2000 0.2001 to 0.3000 0.3001 to 0.4000 0.4001 to 0.5000 0.5001 to 0.6000 0.6001 to 0.7000 0.7001 to 0.8000 0.8001 to 0.9000 0.9001 to 1.0000

1 0.001 to 0.100

0.101 to 0.2000.201 to 0.3000.301 to 0.4000.401 to 0.5000.501 to 0.6000.601 to 0.7000.701 to 0.8000.801 to 0.9000.901 to 1.000

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

E

3

2

Streams

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

6

Figure 6. —Continued.
Simulation of Ground-Water Flow 19

Table 1. Summary of calibrated base multiplier values for hydraulic properties of the Santa Clara Valley model, California

[ft, foot; ft/d, foot per day]

1Top value represents Ssfv for compressible fine-grained deposits and bottom value represents Ssfv for incompressible fine-, mixed and coarse-grained deposits.

Model layer

Base multiplier values

(LPF Package of MF2K)

Product of base multiplier values and initial 

specific storage values

(IBS Package of MF2K)

Horizontal hydraulic 

conductivity,

in ft/d

(PHK)

Vertical hydraulic 

conductivity,

in ft/d 

(PVK)

Aquifer 

specific storage,

in ft-1

(PSsk)

Interbed (aquitard) Skeletal 

Elastic Specific Storage, 

in ft-1

(Ssfe)

Interbed (aquitard) Skeletal 

Inelastic Specific Storage1, 

in ft-1

(Ssfv)

1 900 3.0 × 10−6 0.007 1.2 × 10−6 2 ×10−4

2 ×10−5

2 5 1.0 × 10−7 2.0 × 10−5 1.2 × 10−6 2 ×10−4

2 ×10−5

3 380 5.0 × 10−3 2.0 × 10−5 6.0 × 10−7 1 ×10−4

1 ×10−5

4 120 8.5 × 10−3 5.0 × 10−7 6.0 × 10−7 1 ×10−4

1 ×10−5

5 160 1.7 × 10−2 5.0 × 10−7 1.2 × 10−6 2 ×10−4

2 ×10−5

6 .05 5.0 × 10−2 5.0 × 10−7 1.2 × 10−6 2 ×10−4

2 ×10−5
20 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

The representation of hydraulic properties using the 

Layer Property Flow package (LPF) of MF2K requires the 

separate specification of intrinsic hydraulic properties, such as 

hydraulic conductivity, specific storage or specific yield, and 

aquifer layer thickness for each model layer (Harbaugh and 

others, 2000b). MF2K estimates model-layer hydraulic 

properties as a product of intrinsic hydraulic property and 

model-layer thickness. The aggregate thickness of aquifers and 

aquitards collectively equals the model-layer thickness for any 

one cell. Therefore, the model hydraulic properties required 

the specification of the fraction of the model-layer thickness 

that represents the aquifer or aquitard thickness on a cell-bycell basis. These fractions represent the multiplier arrays that 

are shown for all layers (model layers 1, 3–6) shown in

figure 6 except for model layer 2 that was simulated with single 

hydraulic properties for all cells (table 1). The multiplier arrays 

were used to prorate the thickness of coarse-, mixed-, and finegrained lithofacies at each model cell with the base multiplier 

values listed in table 1. In contrast to the zone-based approach, 

the cell-based definition of spatially distributed hydraulic 

properties represents the gradationally changing lithologic 

properties. This approach allows a more realistic 

representation of the coarse- and fine-grained lithofacies that 

control the hydraulic properties and related flow of ground 

water throughout the alluvial aquifer system. This approach 

also helps to minimize the number of hydraulic parameters 

needed to represent the variations in hydraulic properties. The 

hydraulic parameters are then used to scale the cell-based 

lithofacies multiplier arrays that represent the fractions of the 

model-layer thickness for each hydraulic property. 

Transmission Properties

The revised model simulates confined-aquifer conditions 

for all model layers. MF2K calculates the transmissivity as the 

product of hydraulic conductivity and saturated thickness of 

the aquifers. Therefore, transmissivity values could be affected 

by changes in saturated thickness. Throughout much of the 

modeled area, most of the transmissivity is associated with the 

selected coarse-grained layers of the aquifers that remain 

saturated, and many parts of the aquifers are confined or show 

water-level changes that are a relatively small percentage of 

the saturated thickness, such as the area outside the confined 

region in the southwestern part of model layer 3. Because the 

effective saturated thickness is relatively constant over most of 

the model area, it was considered acceptable to use confined 

aquifers that have constant transmissivities for the entire 

period of simulation. 

The transmission properties were based on the estimation 

of hydraulic conductivity, as required for simulation of 

ground-water flow with MF2K (Harbaugh and others, 2000b). 

Multiplier arrays were used to represent the spatial variation of 

horizontal and vertical hydraulic conductivity (fig. 6). Four 

categories were created for the alluvial deposits on the basis of 

the indexed numerical lithology database (Leighton and others, 

1994): incompressible fine-grained (sc1), compressible finegrained (sc2), mixed coarse- and fine-grained (sc3) and coarsegrained (sc4) sediments. The incompressible fine-grained 

material (sc1) is assumed to be relatively impermeable, is a 

relatively small fraction of the total thickness of alluvial 

deposits, and therefore was not included in any estimates of 

hydraulic properties. For each model layer the multiplier 

arrays were constructed as a combination of textural 

components as:

 and

where 

On the basis of these multiplier arrays (fig. 6), the 

hydraulic properties of each model cell are defined as a set of 

empirical relations as follows:

and

where

i,j, and k are row, column, and layer index for each 

model cell

Li,j,k is the layer thickness (in ft) of that cell;

Lsc(2−4) i,j,k refers to the thickness of an individual 

category fine–f (2), mixed–m (3), or 

coarse–c (4) at that cell; and 

MLTci,j,k,

MLTmi,j,k, and 

MLTfi,j,k

are multiplier arrays for category 4, 3, and 2, 

and represent the proportional layer 

thickness of coarse-grained, mixed, and 

compressible fine-grained sediments, 

respectively. 

HKi,j,k is horizontal hydraulic conductivity,

VKi,j,k is vertical hydaulic conductivity, and

PHKk and

PVKk

are regional base multiplier values for horizontal 

and vertical hydraulic conductivity for all of 

model cells of model layer k. 

MLTcijk , , Lsc4i j, ,k Lijk , , = ⁄

MLTmijk , , Lsc3ijk , , = Lijk , , ⁄

MLTfijk , , Lsc2i j, ,k Lijk , , = ⁄

HKijk , , =

PHKk MLTcijk , , 0.75 MLTmijk , , × ( ) + × ( )

VKijk , , PVKk MLTfijk , , = ×
Simulation of Ground-Water Flow 21

Values of PHK and PVK specified for each model layer 

(table1) were initially based on values from the previous 

model, and have been adjusted further during the calibration of 

the revised Santa Clara Valley model. The assumed fraction of 

0.75 was empirically based upon the percentage of the mixed 

fraction that is typically coarse-grained material from the 

inspection of cores from recently drilled monitoring-well sites 

in the Santa Clara Valley. In addition, slug test values from 

recently completed multiple-well monitoring sites were used to 

confirm the possible range of hydraulic conductivities. These 

tests yielded values that ranged from 0.1 to 583 ft/d (Rhett 

Everett, U.S. Geological Survey, unpub. data, 2002), with the 

highest values for the shallower deposits.

Storage Properties

Aquifer storage properties that are simulated using the 

LPF package of MF2K were separated from the aquitard 

storage properties simulated using the IBS package in the 

revised model (fig. 6). The aquifer storage property includes 

the compressibility of water and the compressibility of the 

coarser grained aquifer material. The skeletal specific storage 

only includes the compressibility of the finer-grained matrix of 

the compressible interbeds. The finer-grained interbeds 

simulated with IBS in MF2K are collectively referred to as 

aquitards in this report. MF2K requires specification of aquifer 

specific storage for all active cells in every model layer. In a 

manner similar to that of the hydraulic conductivity estimates, 

the estimates of specific storage were based on the fractional 

aggregate thicknesses of the cell-by-cell textural facies (fig. 6):

where

PSsk is the common base multiplier value for specific 

storage for all model cells for model layer k, and MLTci,j,k is the 

fractional thickness of the coarse-grained deposits. 

The remainder of the aquifer-system storage from the other 

textural categories is accounted for through the simulation of 

subsidence using the IBS package (described later in the 

Subsidence Section).

Values of PSs specified for each model layer (table 1) were 

initially based on values from the previous model, and were 

adjusted further during the calibration. Although the previous 

model simulated the uppermost layers as unconfined aquifers 

using specific-yield values for the cell-by-cell storage 

properties, the previous model contained numerous dry cells 

that impaired the simulation of ground-water flow and 

terminated some inflows and outflows. As noted above, the 

changes in saturated thickness are small, thus the use of 

confined aquifers does not impart any significant error and 

keeps all active cells active during the entire simulation. For the 

uppermost layers (model layers 1 and 3) values of specific yield 

were implemented by increasing the MLT array values in the 

region outside the confined zone defined for the previous 

model (fig. 1). This resulted in storage coefficients that are 

equivalent to specific-yield values ranging from about 0.01 to 

0.125 as shown by the larger multiplier-array values outside of 

the confined region of model layer 3 (fig 6).

Flow Barriers

In the revised model, faults that represent potential 

barriers to ground-water flow were simulated using the 

Horizontal Flow Barrier package (HFB) (Hsieh and 

Freckleton, 1993). The initial distribution of mapped faults was 

based on the analysis provided by the California Department of 

Water Resources (California Department of Water Resources, 

1967). This fault distribution was the basis for subsequent 

published maps of faults for the southern San Francisco Bay 

region (Pampeyan, 1970, 1993; Jennings, 1985, 1994; Oliver, 

1990; Page, 1993). In particular, the faults were published 

again with assigned relative recencies of age for the State 

geologic map (Jennings, 1994), which was revised from the 

original distributions of fault recency (Pampeyan, 1979; 

Bartugno and others, 1991). However, the basis for the 

distribution of inferred faults and their distinction from 

potential facies boundaries remains uncertain and an element 

of ongoing research by the USGS (Wentworth and others, 

2003a, b). The final distribution of faults used for the groundwater flow model is greatly simplified and has been modified 

on the basis of a revised set of mapped faults (Wentworth and 

others, 2003a). The hydraulic characteristic of these fault 

segments was uniformly set for specific faults and groups of 

layers as determined during model calibration. Information 

regarding fault names, value of hydraulic characteristic, and 

the distribution among model layers is summarized in table 2. 

SS,i,j,k is aquifer specific storage,

PSsk is the common base multiplier value for 

specific storage for all model cells for 

model layer k, and

MLTci,j,k is the fractional thickness of the coarsegrained deposits.

SSijk ,,, PSsk MLTci,j k, = ×
22 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Table 2. Summary of horizontal flow barriers used in the Santa Clara Valley ground-water flow model, California

[ft/d, foot per day]

1Fault identification number from Geologic Digital Data Base (Jennings, 1994)

2Fault replaces original Cascade Fault location (Jennings, 1994)

3Fault location partly revised from original fault location.

Fault name Fault identification number1

Calibrated hydraulic 

characteristic, 

in ft/d

Model 

layers

North Silver Creek 3480 0.01 1−6

North-Central Silver Creek 3636 .01.001 1−2

3−6

South-Central Silver Creek 3751 .01.001 1−2

3−6

North Evergreen 3574 .01 1−6

New Cascade 23819 .0001 3−6

Monte Vista 33836 .0001 3−6

Fault gaps 3819 and 3636 .1 3−6
Simulation of Ground-Water Flow 23

The Silver Creek Fault is represented by three segments: 

North Silver Creek, North-Central Silver Creek, and SouthCentral Silver Creek (fig. 5A). The fault location was based 

either on the mapped trace (Jennings, 1994) at the ground 

surface or on the inferred location that is aligned with 

interferometric synthetic aperture radar (InSAR) images 

(Galloway and others, 2000). Additional seismic imaging 

across the fault (Catchings and others, 2000; Williams and 

others, 2002) and geophysical investigations (Williams and 

others, 2002; Jachens and others, 2002) confirms the location 

of the fault and the potential displacement of layering within 

the sedimentary deposits in the uppermost model layer. These 

fault segments were used in all model layers for all active 

model cells coincident with the fault trace. The North 

Evergreen Fault is a single north-northwest-trending segment 

that traverses the Evergreen Basin between the Silver Creek 

and Hayward Faults (Wentworth and others, 2003a) (fig. 5A).

The Cascade Fault was relocated from the original trace 

(California Department of Water Resources, 1967; Jennings, 

1994) (figs. 1, 5A). The relocation of the fault (herein referred 

to as the “New Cascade” fault) was based on the trace of 

surface damage from the Loma Prieta earthquake in 1989 (Bob 

Jachens, U.S. Geological Survey, unpub. data, 2002) and on 

the envelope delineating the northeastern side of photolineaments (Carl Wentworth, U.S. Geological Survey, unpub. 

data, 2002) in conjunction with other estimates of deformation 

and folding along the western edge of the valley (Hitchcock 

and Kelson, 1999; Hitchcock and others, 1994). In addition, 

different hydrologic response across the proposed fault trace 

was inferred from the water-level hydrographs of two wells 

located east (7S/1W-30C2) and west (7S/1W-30E3) of the 

revised fault-trace location (figs. 1, 5A). The revised location 

also was moved to the southwest of two wells and the Los 

Gatos recharge ponds that were used to improve model 

calibration of water-level changes (7S/1W-30C2, -34F2) along 

the western side of the basin. The revised fault trace is an 

extension of mapped faults that occur in the bedrock outcrops 

along the western side of the basin (Wentworth and others, 

2003a). The Monte Vista Fault also was relocated on the basis 

of recent geologic mapping (Wentworth and others, 2003a). 

The revised “New Cascade” Fault also contains gaps 

represented by larger fault conductances coincident with Los 

Gatos Creek, Stevens Creek, and Ross Creek on the west side 

of the valley (fig. 5A). Similarly, a gap in the Silver Creek Fault 

along the lower Silver Creek was required on the east side of 

the valley to simulate larger fault conductances (fig. 5A). 

Simulated Inflows and Outflows

The previous model had simplified and fixed some of the 

head-dependent inflows and outflows for each stress period 

that were estimated a priori outside of the model. Therefore 

some of the inflows such as streamflow infiltration and 

outflows such as evapotranspiration were not dependent on the 

simulated heads in the ground-water flow model. In addition, 

the model had fixed regional hydraulic gradients and related 

basin inflows and outflows, and constant-head boundaries at 

the Coyote Narrows and San Francisco Bay coastal boundary 

(fig. 1). The previous model also combined inflows and 

outflows and set the spatial distribution. For example, a 

composite net-recharge was used that was composed of the 

combined inflows from artificial recharge, natural areal and 

streamflow infiltration, and transmission-pipe losses minus the 

estimated outflow from potential evapotranspiration. 

Similarly, pumpage that spans up to four model layers for 

multi-aquifer wells had a fixed vertical distribution between 

model layers for each well for all stress periods.

The revised model simulates inflows and outflows 

separately and more dynamically. Therefore, natural valleyfloor recharge, artificial recharge plus leakage from watersupply transmission-line, streamflow routing, and 

evapotranspiration are explicitly simulated as separate flow 

components. In addition, the constant-head boundaries that 

provided a potentially infinite source of simulated inflow and 

outflow in the previous model (CH2M Hill, 1991) were 

replaced with general-head boundaries at the San Francisco 

Bay boundary. The constant-head boundary at Coyote 

Narrows was replaced with streamflow routing inflow along 

Coyote Creek. Subsidence is a new simulated source of water 

from recoverable and non-recoverable storage. Faults as 

horizontal-flow boundaries affect the flow of ground water 

both parallel and perpendicular to the regional hydraulic 

gradients. Pumpage from wells that are screened across 

multiple aquifers is now simulated using multi-node wells that 

dynamically distribute the vertical distribution of groundwater pumpage or intrawellbore flow from unpumped wells.

The revised model simulates inflows and outflow 

components needed to assess water-resource management 

issues. Recharge to the ground-water system is simulated as 

natural areal recharge from the deep percolation of rainfall in 

excess of evapotranspiration and runoff, deep percolation of 

artificial recharge and losses from transmission lines, and 

streamflow infiltration that occurs during the routing of 

streamflow through the numerous creeks that drain the 

surrounding mountains. Outflows are simulated as groundwater pumpage, as ground water discharged to creeks as base 

flow, evapotranspiration, and underflow at and leakage to the 

San Francisco Bay boundary.
24 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Valley-Floor Recharge

For the Santa Clara Valley model, natural areal recharge 

was simulated as infiltration from a percentage of rainfall 

using the recharge package in MODFLOW. To capture the 

spatial and temporal variation of natural precipitation in the 

basin, 12 monthly average precipitation estimates were 

transferred to the SCVM model grid from mean monthly 

precipitation maps (fig. 7) for the period 1950–99 (Joseph A. 

Hevesi and Alan L. Flint, U.S. Geological Survey, unpub. data, 

2000). These maps were estimated from historical 

precipitation records (1950–99) in this region, and spatially 

interpolated for each 90- by 90-meter pixel using a 

precipitation-elevation correlation model (Hevesi and others, 

2002). This approach to estimating precipitation and recharge 

has been applied to other regional models (Hanson and others, 

2002a; D'Agnese and others, 2002; Reichard and others, 

2003). To impose temporally varying rainfall characteristics 

on these precipitation-recharge matrices, a scaling ratio was 

calculated and applied to the matrices for each month 

simulated. The ratio is defined as the measured total monthly 

precipitation at the San Jose station divided by the average 

total precipitation for that month for the period 1950–99. 

The precipitation-recharge relation has been applied 

uniformly throughout the basin. However, the infiltration of 

excess rainfall as valley-floor recharge to the ground-water 

flow system could be quite complex and influenced by a 

number of factors, such as land use, vegetation, soil type, and 

thickness of the unsaturated zone. Although this approach may 

overestimate infiltration from excess rainfall at highly 

developed municipal and industrial areas, such as the urban 

corridor in the central part of Santa Clara Valley, on the basis 

of model calibration of simulated and measured water-level 

hydrographs, the resulting recharge estimate generally 

captures the spatial variation of natural recharge. Conversely, 

on the basis of model calibration of simulated and measured 

water-level hydrographs, the temporal variation of natural 

recharge based on a single percentage of precipitation as 

applied in the previous model seems inadequate owing to the 

lack of multi-year variation in the simulated water-level 

hydrographs, which must reflect wet and dry climatic periods 

observed in the measured water-level hydrographs. Therefore, 

the single linear relation was subdivided into wet- and drymonth relations, separately, in order to manifest the effect of 

climate cycle on the hydraulic system. The distinction between 

wet and dry months was based on the ratio of monthly 

precipitation at San Jose to the period-of-record average 

precipitation for the respective month at San Jose. The monthly 

recharge is assumed to be occurring in a wet month if this 

precipitation-scaling ratio is larger than 1; and the recharge is 

assumed to occur in a dry month if the ratio is less than or equal 

to 1. For the Santa Clara Valley model, a simple linear 

precipitation-recharge relation was adopted initially, with 

recharge estimated to be 7.5 and 15 percent of the mean 

monthly scaled precipitation for wet months for the dryer 

Pacific Decadal Oscillation (PDO) period of 1970–77 and the 

wetter PDO period of 1978–99, respectively. The valley-floor 

recharge during dry months of wet and dry PDO periods was 

held constant at 4.5 percent of the scaled mean monthly 

precipitation. These percentages are collectively comparable 

to the 10 percent used in the previous model. In addition the 

resulting distributions of monthly precipitation are aligned 

with increasing precipitation and increasing elevation along 

the valley margins (fig. 7).

The final equations used for the calibrated model used to 

calculate recharge for the SCVM are specified as follows.

 For the wet months for dry PDO periods:

For the wet months for wet PDO periods:

For all the dry months in wet and dry PDO periods:

where

RCHi,j,T is the recharge matrix of the M monthly 

stress period T for all cells in the I 

rows and J columns of the SCVM 

model grid;

PSJ,T(M) is the measured precipitation at the San 

Jose (SJ) precipitation gage for 

each M month of the year for all T 

stress periods over the simulation 

period 1970–99;

Avg_PSJ,1950–99 is the average measured precipitation at 

the San Jose (SJ) precipitation 

gage for the M month over the 

PDO periods 1950–99; and

Pmap I,J,M is the averaged monthly precipitation 

matrix for one of the 12 months 

(M) (fig. 7), depending on the 

month of stress period T. 

RCHijT , , 0.075 PSJ T M , ( ) Avg–PSJ,1950 99 – = × ( ) ⁄

PmapIJM , , ×

RCHijT , , 0.15 PSJ T M , ( ) Avg–PSJ,1950 99 – = × ( ) ⁄

PmapIJM , , ×

RCHijT , , 0.045 PSJ T M , ( ) Avg–PSJ,1950 99 – = × ( ) ⁄

PmapIJM , , ×
Simulation of Ground-Water Flow 25

XPLANATION

246 8 10 MILES

4 6 8 10 KILOMETERS

A

B

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

cipitation, in millimeters

January

February

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. Ground-water flow model grid and estimated mean monthly precipitation for the period 1952–99 for the Santa Clara Valley model, Santa Clara Valley, 

California.
26 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

XPLANATION

C

D

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

cipitation, in millimeters

March

April

0246 8 10 MILES

0246 8 10 KILOMETERS

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. —Continued.
Simulation of Ground-Water Flow 27

EXPLANATION

San

Francisco

Bay

San

Francisco

Bay

E

F

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

Precipitation, in millimeters

May

June

0246 8 10 MILES

0246 8 10 KILOMETERS

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. —Continued.
28 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

XPLANATION

G

H

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

cipitation, in millimeters

July

August

0246 8 10 MILES

0246 8 10 KILOMETERS

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. —Continued.
Simulation of Ground-Water Flow 29

XPLANATION

I

J

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

cipitation, in millimeters

September

October

0246 8 10 MILES

0246 8 10 KILOMETERS

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. —Continued.
30 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

XPLANATION

K

L

240.1 to 354.0

200.1 to 240.0

180.1 to 200.0

160.1 to 180.0

140.1 to 160.0

120.1 to 140.0

100.1 to 120.0

90.1 to 100.0

80.1 to 90.0

70.1 to 80.0

60.1 to 70.0

50.1 to 60.0

40.1 to 50.0

30.1 to 40.0

20.1 to 30.0

10.1 to 20.0

5.1 to 10.0

1.1 to 5.0

0.6 to 1.0

0.2 to 0.5

cipitation, in millimeters

November

December

0246 8 10 MILES

0246 8 10 KILOMETERS

Alluvial basin boundary

Extent of confined

aquifer zone

Precipitation stations—

See fig. 1 for name

Base from U.S. Geological Survey digital elevation

data, 1:250,000, 1987, and digital data, 1:100,000,

1981–89; Universal Transverse Mercator Projection,

Zone 10. Shaded relief base from 1:250,000-scale

Digital Elevation Model; simulated sun illumination

from northwest at 30 degrees above the horizon

Figure 7. —Continued.
Simulation of Ground-Water Flow 31

Artificial Recharge

Artificial recharge occurs from the deep percolation of 

imported water, specifically from leakage from transmission 

pipelines that carry the imported water to water-treatment 

plants and SCVWD recharge ponds. The deep percolation of 

imported water was simulated using wells as constant inflows 

in the uppermost model layers (layers 1 and 3) at 11 groups of 

percolation ponds that are operated by SCVWD (fig. 5A). 

Inflows were located at the percolation ponds and were 

subdivided between multiple model cells and multiple ponds 

on the basis of the area of individual ponds for each group of 

ponds. The inflows used in the model were the reported 

monthly infiltration volumes (Mark Merritt, Santa Clara 

Valley Water District, unpub. data, 2002). Additional artificial 

recharge that is applied to selected stream channels was 

applied as an additional inflow to the streamflow-routing 

system. Artificial recharge was applied to Stevens, Regnart, 

Calabasas, Rodeo, Saratoga, San Tomas, Los Gatos, Ross, and 

Thompson Creeks (fig. 8). Additional artificial recharge that is 

applied along stream channels was applied to adjacent ponds 

for Penetencia, Guadalupe, and Coyote Creeks.

Additional artificial recharge was assumed to occur as 

leakage from the transmission pipelines that convey treated 

water and include the Penetencia delivery main, Evergreen, 

Parallel east, Snell, Santa Clara distributary, Campbell 

distributary, Sunnyvale distributary, West, Mountain View 

distributary pipelines, and the Santa Teresa tunnel (fig. 5A). An 

assumed leakage rate of about 10 percent was used for these 

cells, with the overall delivery of Hetch Hetchy imported water 

uniformly distributed over all the pipeline cells. The seasonal 

imported water ranged from 22,075 acre-ft in the winter of 

1970 to as much as 85,900 acre-ft in the spring of 1994 

(Bezhad Ahmadi, Santa Clara Valley Water District, unpub. 

data, 2001). This component of recharge was adopted from the 

previous model (CH2M Hill, 1991), which had a similar 

distribution of model cells, pipeline segments, leakage rates of 

9.5 percent, and reported volumes of imported water (Bezhad 

Ahmadi, Santa Clara Valley Water District, unpub. data, 

2001). 

The previous model also contained additional artificial 

recharge as sewer leakage and irrigation return flow. The 

previous model applied the sewer leakage uniformly over the 

entire active model region. This small inflow of water of about 

5,600 acre-ft/yr was not retained in the revised model. 

Similarly, the small amount of agricultural irrigation return 

flow was not included in the revised model.

Evapotranspiration

Evapotranspiration (ET) that was embedded as part of the 

net recharge simulated by the previous model (CH2M Hill, 

1992a) is now simulated separately using the ET package 

(McDonald and Harbaugh, 1988) in the revised model. The 

areal distribution of ET was limited to the cells that represent 

the streams and creeks owing to the considerable urbanization 

of the valley. Therefore, the ET cells were coincident with the 

streamflow network (fig. 5B). An assumed width of 100 ft was 

used as a fraction of the area of the cells representing the 

typical channel and flood-plain width covered by 

phreatophytes. As in the previous model, the ET rate was set to 

0.011 ft/day to represent ET from willow trees that are the 

common broad-leaf vegetation along many of the stream 

channels. An assumed ET extinction depth of 5 ft below the top 

of the uppermost model layers (layers 1 and 3) was used at all 

model cells where ET was potentially active.

Streamflow Routing

The streamflow-routing network used for the SCVM 

consists of 69 rivers, creeks, canals, and diversions. The 

previous model used estimated streamflow infiltration that was 

calculated independently and a priori and then added to the netrecharge array. Therefore, this head-dependent approach to 

routing and infiltration of streamflow is a major improvement 

in the representation of one of the major sources of recharge in 

the Santa Clara Valley. The model network is composed of 

1,724 cells within 137 stream segments that are subdivided 

into segments at the points of confluence or diversion (fig. 8). 

There are four streamflow diversions that divert streamflow to 

the artificial-recharge ponds in the network (fig. 8). The 

network includes both natural and manmade channels that 

collectively drain the Santa Clara Valley toward South San 

Francisco Bay. These are monitored near the points of inflow 

into the alluvial basin and at selected downstream gages. The 

simulation of streamflow routing uses the streamflow routing 

(STR) package (Prudic, 1989). The routing of streamflow is 

based upon the specification of streamflow at user-specified 

cells within the most upstream inflow segments. Geometric 

and hydraulic properties specified for every cell are streambed 

elevation, stream-channel width, Manning coefficient, and 

streambed conductance. The stream cells were assigned on the 

basis of the intersection of the model grid with the stream 

network for all cells that have a stream length of more than 

150 ft within a cell. 
32 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

67

16

13

10

7

58

75

72

1A 1

83

70

18

20

51

73

50

55

59

58

53

49

47

57

56

23B

46

44

21

24

25

44

32A

32A

35

33

26A

74

30 27

29

11170500

11166900

11167000

11169000

11172000

11172100

11167500 11168000

11168500

11169500

11169580

11169600

11166500

11166575

11163000

11163200

11163500

11166000 11162950

11164000 11164500

11165500

11166578

11169616

11167700

11171500

11169000

11166900

24

70

EXPLANATION

USGS gaging station

with number

Reservoirs

Former USGS gaging station now

operated by SCVWD

Downstream comparison site—

(see fig. 13)

SCVWD diversion station

with number

SCVWD gaging station with number

Alluvial basin boundary

Boundary of model grid

layer 3

Streamflow network

(Various colors used to

highlight adjacent segments)

Model streamflow network

(Various colors used to

highlight adjacent segments)

0246 8 10 MILES

0246 8 10 KILOMETERS

San

Francisco

Bay

Extent of confined aquifer zone

49

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;

Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

Figure 8. Streamflow-routing network for the Santa Clara Valley model and selected inflow and comparison gaging stations, Santa Clara Valley, California.
Simulation of Ground-Water Flow 33

The vertical flow along stream cells can be downward or 

upward. Downward flow represents streamflow infiltration as 

recharge into the shallow aquifers of the ground-water flow 

system. Upward flow represents stream base flow as discharge 

from the shallow aquifer. The flow is calculated for each 

weekly time step of each monthly stress period. The flow is 

based on the streambed conductance and the hydraulic gradient 

between the stream and the uppermost active model cell. The 

hydraulic gradient is based on the difference between the 

simulated water levels (that is, head) in the stream that 

represents the stream stage and the ground-water level in the 

corresponding model cell divided by the distance between the 

model-cell center and the bottom of the streambed. The stage is 

internally calculated by the STR package.

The inflows are a combination of natural runoff, 

controlled releases from reservoirs and artificial-recharge 

facilities, gaged streamflow, and ungaged streamflow. The 

inflows are specified monthly and represent the combination of 

inflows that occur on each stream channel at the point of entry 

onto the ground-water flow model grid (fig. 8). Each inflow 

rate is the average of the total inflow for each month of the 

simulation period. The gaged inflows for eight creeks are based 

on streamflow-gaging station data from the USGS (Friebel and 

others, 2002) and from the SCVWD (Behzad Ahmadi, Santa 

Clara Valley Water District, unpub. data, 2000). Additional 

artificial recharge released to selected streams was specified 

from SCVWD data (Mark Merritt, Santa Clara Valley Water 

District, unpub. data, 2001). Ungaged streamflow for 

47 selected tributaries were estimated from runoff estimates by 

the USGS (Alan L. Flint, U.S. Geological Survey, unpub. data, 

2000) that were based on the methods described by Hevesi and 

others (2002). Outflows from the streamflow network occur as 

discharge to the southern San Francisco Bay and as streamflow 

infiltration to the upper-aquifer system. The streamflow 

diversions occur at Kirk Ditch and Page Ditch on Los Gatos 

Creek and Junipero Serra Channel and Permanente Diversion 

channel on Stevens Creek (fig. 8).

The geometric and hydraulic properties were assigned to 

each stream cell. The streambed elevations were specified on 

the basis of the lowest Digital Elevation Model elevation 

coincident with the trace of the stream channel. The elevation 

of the bottom of the streambed was assumed to be a constant 10 

ft below the top of the streambed for all stream cells.

The stage is computed by the STR package using the 

stream channel width, slope, and Manning roughness 

coefficient for various bed materials (eqn. 2, Prudic, 1989). The 

channel widths for each stream cell were derived from data 

obtained from SCVWD for the entire streamflow network 

(Mark Merritt, Santa Clara Valley Water District, unpub. data, 

2001). The slopes were calculated from the difference in 

stream-cell elevations and cell dimensions. The channel 

bottom materials and related Manning coefficients are 

specified as part of the STR package input for each stream cell 

and were based on SCVWD data (Mark Merritt, Santa Clara 

Valley Water District, unpub. data, 2001). The Manning 

coefficients ranged from 0.01 to 0.50 (Mark Merritt, Santa 

Clara Valley Water District, unpub. data, 2001) for rivers, 

creeks, and channels in the Santa Clara Valley.

The initial nonzero values of streambed conductances 

were based on previous modeling studies that have streamflowrouting networks with streambed conductances determined 

through model calibration (Hanson and others, 2002a; Stamos 

and others, 2001). Streambed conductances were categorized 

into five groups based on the specified stream-channel bottom 

material. Lined channels were specified with a conductance of 

zero. Channel bottoms described as rock, natural, or “no data” 

for channel segments with earth levees, gabion, trapezoidal, Uframe, or sack concrete channels initially were assigned a value 

of 8,640 ft2/d. Channel bottoms described as “rock” or “no 

data” for channel segments with “rock lined,” “natural 

unmodified,” or “modified flood plain” channels initially were 

assigned a value of 43,200 ft2/d. Channel bottoms described as 

“earth excavated” or “natural” initially were assigned a value 

of 86,400 ft2/d. Additional streamflow segments had streambed 

conductances set to zero on the basis of the detailed description 

of reaches available for recharge delineated by SCVWD 

(J. Aguilera, Santa Clara Valley Water District, unpub. data, 

2002). In addition, the streambed conductances for all of the 

flood control channels and lined stream channels were set to 

zero. The natural bed material throughout the lower parts of the 

streamflow network below an elevation of 21 ft above sea level 

were assigned a zero streambed conductance. This assumed 

elevation was based on the distribution of losing and gaining 

reaches determined for San Francisquito Creek (Metzger, 

2002) and the distribution of gaining and losing reaches 

provided by SCVWD (J. Aguilera, Santa Clara Valley Water 

District, unpub. data, 2002).

Subsidence

The simulation of land subsidence for the revised groundwater flow model (SCVM) included all six model layers. The 

simulation of subsidence uses the interbed storage (IBS) 

package (Leake and Prudic, 1991). The simulation of 

subsidence is based on the simulation of compression and 

compaction in all model layers. The IBS package requires 

specification for each model layer of elastic (Sfe) and inelastic 

(Sfv) storage coefficients, previous compaction, and critical 

head (HC) (fig. 9). Although the Santa Clara Valley is the site 

of well documented historical subsidence of as much as 12.7 ft 

near San Jose (Poland and Ireland, 1988), for the purposes of 

this study no historical subsidence prior to 1970 was added to 

the simulated compaction. 
34 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

L

ay

er

1

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Skeletal elastic specific

storage multiplier

Skeletal inelastic specific

storage multiplier

EXPLANATION

Critical head,

in feet 12 3

–99 to –70–69 to –40–39 to –10

–9 to 2021 to 5051 to 80

81 to 110

111 to 140141 to 149

0.0001 to 0.0010.0020.0030.0040.0050.006

0.001 to 0.050.06 to 0.100.11 to 0.200.21 to 0.300.31 to 0.40

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

A

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

Figure 9. Ground-water flow model grid, skeletal elastic and inelastic storage multipliers, and critical heads for all model layers of the Santa Clara Valley 

model, Santa Clara Valley, California.
Simulation of Ground-Water Flow 35

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Skeletal elastic specific

storage multiplier

Skeletal inelastic specific

storage multiplier

EXPLANATION

Critical head,

in feet 12 3

–99 to –70–69 to –40–39 to –10

–9 to 2021 to 5051 to 80

81 to 110

0.0001 to 0.0010.0020.0030.0040.005

0.001 to 0.050.06 to 0.100.11 to 0.200.21 to 0.300.31 to 0.40

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

B

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

2

Figure 9. —Continued.
36 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California San Francisco Bay San Francisco Bay San Francisco Bay Skeletal elastic specific storage multiplier Skeletal inelastic specific storage multiplier EXPLANATION Critical head, in feet 12 3 –400 to –370 –369 to –340 –339 to –310 –309 to –280 –279 to –250 –249 to –220 –219 to –190 –189 to –160 –159 to –130 –129 to –100 –99 to –70 –69 to –40 –39 to –10 –9 to 20 21 to 50 51 to 80 81 to 110 111 to 140 141 to 149 0.0001 to 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010 0.011 to 0.020 0.001 to 0.05 0.06 to 0.10 0.11 to 0.20 0.21 to 0.30 0.31 to 0.40 0.41 to 0.50 0.51 to 0.60 0.61 to 0.70 0.71 to 0.80 0246 8 10 MILES 0246 8 10 KILOMETERS Alluvial basin boundary Extent of confined aquifer zone

1

C

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digitaldata, 1:100,000, 1981–89; Universal Transverse Mercator Projection, Zone 10.

Shaded relief base from 1:250,000-scale Digital Elevation Model; simulated sunillumination from northwest at 30 degrees above the horizon

L

ay

er

3

Figure 9. —Continued.
Simulation of Ground-Water Flow 37

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Skeletal elastic specific

storage multiplier

Skeletal inelastic specific

storage multiplier

EXPLANATION

Critical head,

in feet 12 3

–400 to –370–369 to –340–339 to –310–309 to –280–279 to –250–249 to –220–219 to –190–189 to –160–159 to –130–129 to –100

–99 to –70–69 to –40–39 to –10

–9 to 2021 to 5051 to 80

81 to 110

0.0001 to 0.0010.0020.0030.0040.0050.0060.0070.0080.0090.0100.011 to 0.020

0.02 to 0.050.06 to 0.100.11 to 0.200.21 to 0.300.31 to 0.400.41 to 0.500.51 to 0.600.61 to 0.700.71 to 0.80

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

D

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

4

Figure 9. —Continued.
38 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California San Francisco Bay San Francisco Bay San Francisco Bay Skeletal elastic specific storage multiplier Skeletal inelastic specific storage multiplier EXPLANATION Critical head, in feet 12 3 –189 to –160 –159 to –130 –129 to –100 –99 to –70 –69 to –40 –39 to –10 –9 to 20 21 to 50 51 to 80 81 to 110 111 to 140 141 to 149 0.0001 to 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010 0.011 to 0.020 0.02 to 0.05 0.06 to 0.10 0.11 to 0.20 0.21 to 0.30 0.31 to 0.40 0.41 to 0.50 0.51 to 0.60 0.61 to 0.70 0246 8 10 MILES 0246 8 10 KILOMETERS Alluvial basin boundary Extent of confined aquifer zone

1

E

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

5

Figure 9. —Continued.
Simulation of Ground-Water Flow 39

San

Francisco

Bay

San

Francisco

Bay

San

Francisco

Bay

Skeletal elastic specific

storage multiplier

Skeletal inelastic specific

storage multiplier

EXPLANATION

Critical head,

in feet 12 3

–189 to –160–159 to –130–129 to –100

–99 to –70–69 to –40–39 to –10

–9 to 2021 to 5051 to 80

81 to 110

111 to 140141 to 149

0.0001 to 0.0010.0020.0030.0040.0050.0060.0070.0080.0090.0100.011 to 0.020

0.001 to 0.050.06 to 0.100.11 to 0.200.21 to 0.300.31 to 0.400.41 to 0.500.51 to 0.600.61 to 0.700.71 to 0.800.81 to 0.900.91 to 1.00

0246 8 10 MILES0246 8 10 KILOMETERS

Alluvial basin boundaryExtent of confined

aquifer zone

1

F

3

2

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

L

ay

er

6

Figure 9. —Continued.
40 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

The simulated deformation is based on the change in head 

over each time step. The amount of deformation is based on the 

product of the compressibility of the aquitard and confining 

units within the regional system and their aggregate thickness 

in each cell of each model layer. The computed deformation 

represents the ultimate compression or compaction for a 

change in head that is instantaneous. Thus, the heads in 

adjacent aquifers and aquitards are assumed to be in 

equilibrium for each time step which, therefore, does not 

simulate delayed compaction. Because many of the individual 

aquitards are relatively thin (less than 20 ft thick), this was 

considered an acceptable approximation. In addition, the 

compressibilities are assumed to be constant for the entire 

simulation and are not dependent on changes in effective 

stress. Elastic compression or expansion is computed if the 

ground-water level (that is, head) in any cell is above the 

respective critical head. Inelastic compaction is computed if 

the ground-water level (that is, head) in any cell is below the 

critical head. If the simulated water level falls below the 

critical head in any time step, the critical head is updated to 

equal the new lower simulated ground-water level.

The estimates of skeletal elastic storage coefficients (S′fe) 

were based on a combination of estimated values from 

consolidation tests, extensometers, and reported values 

(Ireland and others, 1984; Poland and Ireland, 1988; Hanson, 

1989). An initial value of S′sfe for fine-grained deposits of 

3 × 10−6 ft−1 was assumed from other reported values for 

alluvial deposits (Ireland and others, 1984; Hanson, 1989). 

New specific storage values were estimated from 

consolidation-test data from samples of cores acquired during 

the recently completed monitoring-well sites (fig. 1). The 

skeletal elastic specific storage (S′sfe) data from consolidation 

tests range from 2.7 × 10−6 ft−1 to 1.4 x 10−4 ft−1 and represent 

a geometric mean S′sfe of 1.2 × 10−5 ft−1. The graphical 

estimates of S′fe for data collected for the period 1983–2001 

are about 1.2 × 10−3 and 6.2 × 10−3 from the San Jose and 

Sunnyvale extensometers, respectively (location shown in 

fig. 1). These graphical estimates from extensometer data 

result in S′sfe values on the order of 1.5 × 10−6 ft−1 and 

1.5 × 10−5 ft−1 for San Jose and Sunnyvale, respectively, based 

on the aggregate thickness of fine-grained deposits. The S′fe

and S′sfe estimates for the San Jose extensometer are 

comparable to the previous estimates of S′sfe reported for the 

San Jose extensometer of 1.5 × 10−3 for S'fe and 

1.9 × 10−6 ft−1 for S′sfe (Poland and Ireland, 1988). Even 

though the geometric mean from consolidation tests is about 

four times greater than the value commonly estimated from 

reported values, they fall within the range of values derived 

from graphical estimates of local extensometer data. 

The estimates of inelastic storage (S′fv) also were based 

on a combination of estimated values from consolidation tests, 

extensometers, and reported values. New specific storage 

values were estimated from consolidation-test data from 

samples of cores acquired during the recently completed 

monitoring-well sites. The inelastic specific storage (S′sfv) 

values, which are consistent with the previously reported 

values, range from 6.0 × 10−5 ft−1 to 6.6 × 10−4 ft−1 and 

represent a geometric mean S'sfv of 1.5 × 10−4 ft−1. A graphical 

estimate of S′fv for data collected for the period 1985–89 from 

the San Jose and Sunnyvale extensometers was 0.01, and 

results in an S′sfv value of 2.1 × 10−5 ft−1. A reported value of 

S′Sfv for fine-grained deposits of 2 × 10−4 ft−1 was assumed 

from reported values for other alluvial deposits (Ireland and 

others, 1984; Hanson, 1989) and reported values range from 

1.5 × 10−4 ft−1 to 1.3 × 10−3 ft−1 for the Santa Clara Valley 

(Poland and Ireland, 1988). 

The fine-grained interbed elastic skeletal storage 

coefficient (S′fe) is denoted with the prime and was estimated 

on a cell-by-cell basis as the product of a single value of the 

aquifer skeletal specific storage (S′sfe), 3 × 10−6 ft−1, and the 

aggregate cell-by-cell thickness of the compressible finegrained deposits (Leighton and others, 1994) for each active 

cell in every model layer (fig. 9) as:

where

The composite inelastic skeletal storage coefficient (S'fv) 

was estimated as the sum of the products of the non-interbed 

inelastic skeletal specific storage coefficient (S′sfv1) of 

2.0 × 10−5 ft−1 with the thickness of coarse-grained sediments 

(sc4), the incompressible fine-grained sediments (sc1), and the 

mixed sediments (sc3), and the product of the inelastic specific 

storage coefficient (S′sfv2) of 2.0 × 10−4 ft−1 and the thickness 

of the compressible fine-grained sediments (sc2) (fig. 9) as:

where

S′fe,i,j,k is interbed elastic skeletal storage,

S′sfe is the common, base multiplier value of 

interbed elastic skeletal specific storage 

for all model cells for model layer k; and

Lsc2i,j,k refers to the thickness of fine-grained 

sediments (2) for each cell in each model 

layer k.

S′fe i j k , , , S′sfe Lsc2ijk , , = ×

S′fv i j k , , , =

S′sfv1 Lsc1i j ,, ,k Lsc3i j, ,k Lsc4i j, ,k ( ) × [ ] + +

S′sfv2 Lsc2i j, ,k + ( ) ×
Simulation of Ground-Water Flow 41

The application of aggregate thickness for estimation of 

interbed and confining-layer storage properties has been 

applied in similar alluvial aquifer systems (Hanson and others, 

2002a; Hanson and Benedict, 1994; Hanson and others, 1990) 

and has been shown to be related to depositional environments 

in alluvial aquifers (Anderson and Hanson, 1987; Johnson and 

Dreiss, 1989; Johnson, 1995a, b).

The critical head is defined as the past maximum waterlevel altitude that resulted in inelastic compaction and was 

determined during model calibration. The critical head was 

initially set equal to the initial head, with the assumptions that 

the initial heads were representative of January, 1970, 

conditions and that the fine-grained deposits were normally 

consolidated. This approach resulted in anomalous changes in 

storage and increased water levels during the first few years of 

the simulation. Critical heads were previously estimated as 

being 80 ft lower in 1967 than in 1978 on the basis of the 

artesian head recovery at the San Jose index well 

(7S/1E-7R1/6M1; Poland and Ireland, 1988); this estimate is 

consistent with other estimates of critical (preconsolidation) 

heads (Holzer, 1981). Thus the critical heads were then 

uniformly reset to 80 ft below the initial conditions. A large 

decrease in head in the peripheral parts of model layer 3 outside 

a region defined by more than 0.1 ft of historical subsidence 

continued creating large contributions to storage. To eliminate 

this artifact, the critical heads were decreased another 160 ft in 

the peripheral areas of model layer 3. In addition, for cells 

located within the historical cones of depression, the critical 

heads were reduced another 10 ft to allow for a small amount 

of inelastic compaction in the late 1980s near the San Jose 

index well after the dry period in the late 1970s. The resulting 

critical-head values were based on model calibration and may 

represent a lower bound of critical heads within the basin and 

within specific model layers (fig. 9). Critical heads may 

nevertheless be uncertain in some parts of the basin because 

water-level declines during the droughts of the simulation 

period may not have exceeded historical low water levels.

Pumpage

The pumpage for the USGS–SCVWD Santa Clara Valley 

Model (SCVM) simulates pumpage from water-supply, 

industrial, and irrigation wells throughout the valley. Many of 

these wells are screened across multiple aquifers. In addition to 

these multi-aquifer wells, there are hundreds of wells that are 

not used or are used intermittently and may transmit flow 

between aquifers screened in these wells (fig. 10). For this 

reason, the multi-node well (MNW) package was developed as 

part of this project to more accurately simulate the effects of 

thousands of multi-aquifer wells (Halford and Hanson, 2002; 

McDonald, 1986). The multi-aquifer well package (McDonald, 

1986) was initially developed for the original MODFLOW-88 

(McDonald and Harbaugh, 1988); the new multi-node well 

package is used with MF2K (Harbaugh and others, 2000b) for 

the SCVM. The ability to dynamically apportion wellbore flow 

and allow for wellbore flow in unpumped wells has a 

significant effect on the calibration of regional ground-water 

flow systems (Halford and Hanson, 2003a,b) and on the 

distribution of other head-dependent inflows and outflows such 

as subsidence and streamflow infiltration (Hanson and others, 

2003). 

The pumpage for the initial calibration and verification 

period (1970–89) was modified from the seasonal distribution 

of pumpage used in the original ground-water flow model of 

the Santa Clara Valley (CH2M Hill, 1991, 1992a,b). The 

revised pumpage reuses the original seasonal pumpage but it is 

specified on a monthly basis. This initial distribution of 

pumpage only specified wells that were actively pumped. This 

resulted in a monotonic decrease in the number of wells from 

1,466 to 647 (fig. 11). This distribution of wells through time 

does not account for the possibility of wells providing 

intrawellbore flow between aquifers under nonpumped 

conditions. The revised pumpage includes all unpumped wells 

that span more than one model layer to simulate the potential 

for intrawellbore flow. Few new wells have been constructed in 

the 1990s, and hundreds have been destroyed since the 1970s 

(Behzad Ahmadi, Santa Clara Valley Water District, unpub. 

data, 2000). The number of unpumped wells is additionally 

reduced by the wells that have been destroyed for each month 

of the simulation. 

S′fv,i,j,k is inelastic skeletal storage,

S′sfv1 is the base multiplier value of non-interbed 

inelastic skeletal specific storage for all 

model cells for model layer k; 

S′sfv2 is the base multiplier value of interbed 

inelastic skeletal specific storage for all 

model cells for model layer k; and

Lsc(1–4) i,j,k refers to the thickness of sediments for 

category 4, 3, 2, and 1 and represents the 

proportional layer thickness of coarsegrained (4), mixed (3), and compressible 

fine-grained sediments (2) and 

incompressible fine-grained sediments 

(1), for each cell in each model layer k.
42 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

6S

7S

8S

5S

3W 2W 1W 1E 2E

280

280

680

880

101

101

130

237

85

35

35

84

17

87

82

7A3

10J1

5N1, 2

33M3

3K3

34F2

24H1

7R99

30C2 22E2

22E14

15E1

5P2 9Q1

6P1

2G2

6L1

1B1

33A2

4E2

28N1

24C7 21A1

24H8

15Q1

2J6

16C8

18L1

Wells—

Wellbore flow wells

USGS multi-well

monitoring site

Model hydrograph

comparison wells

Extensometers

Rivers and streams

Percolation ponds Extent of confined

aquifer zone

Alluvial basin

boundary Active model grid—

layer 3

Township and

range grid

Santa

Clara

Co

San Mateo

Co

EXPLANATION

Model faults—

Monte Vista

Cascade

Silver Creek

Evergreen

San

Francisco

Bay

San

Jose

CRH

ERH

NE

NWC

NWW

SCR

SEC

Subgroups (see fig. 12)

Alameda

Co

Santa Cruz

Co

Coyote Hills

DIABLO RANGE

SANTA CRUZ MTS

Oak Hill

Edenvale Hills

Coyote

Narrows

Multi-node (multi-aquifer)

wells—Jan. 1970

Single-node (single-aquifer)

wells—Jan. 1970

Unpumped multi-node wells—

Dec. 1989

Reservoirs

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

Universal Transverse Mercator Projection, Zone 10

0246 8 10 MILES

0246 8 10 KILOMETERS

Evergreen subregion

Figure 10. Distributions of simulated pumped and nonpumped multi-aquifer wells, and single-aquifer wells for the Santa Clara Valley, California.
Simulation of Ground-Water Flow 43

1970 1975 1980 1985 1990

Revised model

total wells

Previous model

total wells

Nonpumped

multi-aquifer

wells

Destroyed

wells

Year

0

200

400

600

800

1,000

1,200

1,400

1,600

Number of well entries

Figure 11. Distributions of simulated pumped, nonpumped, and destroyed wells for selected monitoring wells, Santa Clara Valley, California.
44 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

The revised pumpage is composed of three types of wells: 

single-aquifer wells, multiple-aquifer pumped wells, and 

multiple-aquifer unpumped wells. The single-aquifer wells 

predominantly occur in the southern and central parts of the 

valley (fig. 10). The multiple-aquifer wells occur throughout 

the valley and can span two to four model layers (fig. 10). 

Similarly unpumped multiple-aquifer wells occur throughout 

the valley as shown for December1989 (fig. 10).

The application of the MNW package to simulate 

multiple-aquifer well pumpage required the specification of 

the location of the wells (model row and column), the layers 

spanned by the well screens, the well radius, and the skin factor 

(Halford and Hanson, 2002). For single-aquifer wells, the well 

is specified as a single entry for any stress period that has 

nonzero pumpage. For multiple-aquifer wells, the well is 

specified using multiple records that are grouped together and 

represent the set of model layers that the well screens span. The 

initial distribution of pumpage from the previous model for the 

period 1970–89 was specified for layer specific pumpage. 

However, the MNW package reestimates the distribution of 

pumpage from the set of model layers for each well and for 

each time step because this vertical distribution of pumpage is 

head dependent. The reported well radius was specified if 

known or was assumed to be 0.87 ft (i.e. 8 in.) if unknown. The 

skin factor represents the potential linear, wellbore frictionalentrance flow losses (Halford and Hanson, 2002, eqn. 3) and 

was initially estimated to be 5 for all wells in all layers in all 

stress periods. The discharge for unpumped multiple-aquifer 

wells was specified as zero for any stress periods that had no 

reported pumpage. Similar to pumped wells, the vertical 

distribution of wellbore flow in unpumped wells is head 

dependent and is reestimated by the MNW package for every 

unpumped well for all time steps.

The updated pumpage for the period 1990–99 was 

estimated on a monthly basis for each well by SCVWD (Roger 

Pierno, Santa Clara Valley Water District, unpub. data, 2002) 

and added to the previous pumpage used for the previous 

model simulation period, 1970–89. Over 90 percent of the 

pumpage represents pumpage by the major water purveyors. 

This pumpage was reported on a monthly basis. The remaining 

10 percent of predominantly domestic pumpage is reported on 

a biannual or annual basis. This pumpage was prorated on a 

monthly basis from the annual distribution of the monthly 

reported pumpage (Roger Pierno, Santa Clara Valley Water 

District, unpub. data, 2002). These pumpage data also include 

wells that are not pumped and have not been destroyed and 

therefore provide a conduit for flow. 

Coastal Flow

Flow along the coastal boundary and beneath southern 

San Francisco Bay is represented by general-head boundaries. 

In the revised model, water exchange between the aquifer and 

San Francisco Bay is simulated using the general-head 

boundary (GHB). Two types of GHBs were specified. The first 

type of GHB simulates potential submarine and estuary areal 

leakage, which represents the vertical flow coming across the 

bay mud from or to the aquifer just below it in the coastal and 

offshore regions of model layer 1 (fig. 5). The second GHB 

type simulates offshore ground-water underflow along the 

northwestern edge of the model grid. These underflow GHB 

boundaries were represented by a line of GHB cells along the 

offshore northwestern margin of model layers 2 through 6. The 

GHB line simulates the potential lateral inflows and outflows 

of the lower aquifers (model layers 2 to 6) from external 

sources such as adjacent Bay Area aquifers. For model layer 1, 

GHB is specified for cells northwest of the shoreline; for the 

rest of the model layers, GHB is specified only at the edge cells 

below the Bay. 

The boundary heads of the external source in GHBs are 

assumed to be approximately equal to the average hydrostatic 

head of the Bay and were set equal to sea level. They are 

uniform everywhere regardless of depth and surface location. 

The conductance of GHB is defined as the product of the 

hydraulic conductivity of the aquifer along the submarine 

boundary of the aquifer within the model GHB cells and the 

cross-sectional area perpendicular to the ground-water flow 

divided by the distance from the center of the GHB cells to the 

external point of reference.

For the first type of GHB boundary that represents areal 

vertical leakage in model layer 1, the area of the model cells is 

a constant value equal to the area of the model cells, and a 

value of 0.0027 ft/d was assigned to the vertical hydraulic 

conductivity, Kv. This Kv is the same as the vertical hydraulic 

conductivity of bay mud estimated by the CDWR (California 

Department of Water Resources, 1967). The thickness of the 

bay mud may vary areally and was assumed to be equivalent to 

half of the aggregate thickness of compressible fine-grained 

deposits of each areal-GHB cell in model layer 1. 

For the second GHB type where the line of GHB cells 

simulates underflow beneath the San Francisco Bay, the K of 

the conductance is equal to the horizontal hydraulic 

conductivity of the model cell where the line GHB is located. 

The distance to the boundary is a uniform half width of the 

boundary model cell of 500 ft. The area perpendicular to flow 

is the product of the cell-by-cell thickness of the layer and the 

constant model-cell width. The conductance of each boundary 

line-GHB cell was set to twice the transmissivity of that model 

cell. 
Simulation of Ground-Water Flow 45

Initial Conditions

Initial conditions are the distribution of water levels at 

every active cell within each of the six model layers. The initial 

water levels were those of the previous model (CH2M Hill, 

1991) and were derived from historical water levels; they 

represent average winter 1970 conditions. These water levels 

did not contain water-level differences between model layers 

that are inherently present in a regional ground-water flow 

system. However, minor adjustments to the initial water levels 

were required to compensate for numerous dry cells that were 

simulated in the previous model. Therefore, the initial heads 

may not represent steady-state conditions in some parts of the 

model and for parts of some layers.

Model Revisions

Calibration and model development began with the 

previous model (CH2M Hill, 1991). The transition from the 

previous model to the revised model was a sequence of 

revisions and related calibration steps. The first revisions from 

the previous model were the modifications to the temporal and 

spatial discretization, which helps to better separate the supply 

(inflow) and demand (outflow) components of the groundwater flow system. On the basis of the finer discretization, the 

new estimates of artificial and natural recharge, 

evapotranspiration, and coastal flow boundaries were then 

implemented. The model was then transformed from the 

MODFLOW-88 structure to the MODFLOW-96 structure. 

After the revised boundary conditions were implemented, the 

multi-node well package, the interbed storage package, and the 

horizontal flow barrier package were added to the revised 

model. 

The revised model was then transformed from 

MODFLOW-96 to MF2K. After intermediate calibration, the 

estimation of the hydraulic properties was transitioned from the 

zone-based estimates of the previous model to the lithological 

cell-based estimates of the revised model using the LPF 

package of MF2K. The Evergreen subregion, which was 

deactivated in the previous model, was then added back into the 

active flow region. Finally, the model was updated to include 

the additional inflows and outflows for the period January 1990 

through September 1999.

Model Calibration

Model calibration was an integral part of upgrading and 

updating the previous model. Calibration was achieved through 

trial-and-error adjustments to natural recharge and hydraulic 

properties in order to achieve a good fit within each subarea 

over the historical period of simulation. These adjustments 

were made as systematically as possible, starting with the 

boundary inflows, recharge, and streamflow and then hydraulic 

properties. The initial calibration was completed for the model 

upgraded with new inflows, outflows, and hydraulic properties 

during the original historical period of simulation, 1970–89. 

Then the model was updated to simulate an additional 9.75 

years (1990–99) of inflows and outflows. Additional 

calibration adjustments were made on the basis of model 

performance during this additional historical period of 

simulation. The addition of the remaining historical period, 

2000–03, was not made because selected measured inflows and 

outflows were not available at the time of completion of this 

study.

Transient-State Calibration

Transient-state calibration was based primarily on 

spatially distributed temporal comparisons. Calibration 

adjustments were related to the combined fitting of the groundwater levels (fig. 12), streamflow (fig. 13), and subsidence

(fig. 14) time series. In addition, comparisons of all groundwater levels were made relative to the previous model and for 

selected portions of the period of calibration (fig. 15). Maps of 

ground-water levels were used for limited comparisons for the 

updated period but were considered less reliable than timeseries data because the composite water-level measurements 

and hand contours represent averaged conditions in many areas 

where there are large vertical-head differences within some 

parts of the aquifer systems. An overall estimate of model fit 

was made using all of the temporal comparison ground-water 

level data and extensometer data for the transient simulation. 

The final distribution of ground-water levels through time 

shows the effects of the time-varying recharge and pumpage as 

well as the effects of the faults on ground-water flow 

(Animation 1. Map showing simulated water levels, 1970–99, 

for the Santa Clara Valley model, Santa Clara Valley, 

California.).
46 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

1975 1980 1985 1990 1995 2000 1970 1975 1980 1985 1990 1995 2000

1975 1980 1985 1990 1995 2000

Year

Measured

Simulated-LY3

6S/1E-15Q1

Measured

Simulated-LY3

7S/1E-6L1

Measured

Simulated-LY4

6S/1W-24H8

Group=NE

Water-level altitude, in feet above NAVD 88

1970

1970

NAVD

88

NAVD

88

NAVD

88

NAVD

88

NAVD

88

–125

–100

–75

–50

–25

25

50

75

100

–125

–100

–75

–50

–25

25

50

75

100

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000 1970 1975 1980 1985 1990 1995 2000

Year

Group=ERH

Measured

Simulated-LY4

7S/1E-2J6

Measured

Simulated-LY5

7S/1E-16C6

Water-level altitude, in feet above NAVD 88

–125

–100

–75

–50

–25

25

50

75

100

–125

–100

–75

–50

–25

25

50

75

100

(Screened interval=181–412 ft)

(Screened interval=280–310 ft)

(Screened interval not reported)

(Screened interval not reported)

(Screened interval=508–697 ft)

Figure 12. Measured and simulated water-level for selected long-term monitoring wells, Santa Clara Valley, California.
Simulation of Ground-Water Flow 47

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

Water-level altitude, in feet above NAVD 88

Year Year

Group=CRH

1970 1975 1980 1985 1990 1995 2000

–25

25

125

100

75

50

Measured

Simulated-LY3

7S/1E-7R99

Measured

Simulated-LY3

7S/1W-9Q1

Measured

Simulated-LY3

7S/1W-15E1

Note scale change

Measured

Measured–LY4

7S/1W-2G2

NAVD

88

NAVD

88

NAVD

88

NAVD

88

(Screened interval=490–772 ft)

(Screened interval=280–461 ft)

(Screened interval=660–814 ft)

(Screened interval=262–476 ft)

Figure 12. —Continued.
48 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–25

25

50

75

100

125

150

175

200

1970 1975 1980 1985 1990 1995 2000

–100

–75

–50

–25

25

50

75

100

125

150

Water-level altitude, in feet above NAVD 88

Year

Group=CRH cont.

Measured

Simulated-LY3

7S/1W-22E2

Measured

Simulated-LY3 East of fault

7S/1W-30C2

Measured

Simulated-LY3

7S/1W-22E14

Simulated-LY3 West of fault

Note scale change

Note scale change

Measured

Simulated-LY4

7S/1W-34F2

Water-level altitude, in feet above NAVD 88

Group=SEC

1970 1975 1980 1985 1990 1995 2000

100

125

175

150

200

Measured

Simulated-LY1

8S/2E-7A3

1970 1975 1980 1985 1990 1995 2000

75

100

125

150

175

200

Year

Measured

Simulated-LY3

8S/2E-18L1

NAVD

88

NAVD

88

NAVD

88

NAVD

88

(Screened interval=305–501 ft) (Screened interval=334–786 ft)

(Screened interval=254–428 ft) (Screened interval=370–828 ft)

(Screened interval not reported) (Screened interval not reported)

Figure 12. —Continued.
Simulation of Ground-Water Flow 49

1970 1975 1980 1985 1990 1995 2000 1975 1980 1985 1990 1995 2000

1970 1975 1980 1985 1990 1995 2000 1970 1975 1980 1985 1990 1995 2000

Water-level altitude, in feet above NAVD 88

Year Year

Measured

Simulated-LY3

6S/2W-21A1

Measured

Simulated-LY3

6S/2W-28N1

Measured

Simulated-LY3

6S/2W-24C7

Group=NWC

Measured

Simulated-LY3

6S/2W-33A2

–125

–100

–75

–50

–25

25

50

75

100

–125

–100

–75

–50

–25

25

50

75

100

1970

–125

–100

–75

–50

–25

25

50

75

100

–125

–100

–75

–50

–25

25

50

75

100

NAVD

88

NAVD

88

NAVD

88

NAVD

88

(Screened interval not reported) (Screened interval=807–850 ft)

(Screened interval=300–380 ft) (Screened interval=257–489 ft)

Figure 12. —Continued.
50 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

NAVD

88

NAVD

88

NAVD

88

NAVD

88

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

25

50

75

100

Water-level altitude, in feet above NAVD 88

Year Year

Group=NWW

Measured

Simulated-LY3

7S/1W-4E2

Measured

Simulated-LY3

7S/1W-6P1

Measured

Simulated-LY3

7S/2W-1B1

Measured

Simulated-LY3

7S/1W-5P2

(Screened interval=309–557 ft) (Screened interval=290–760 ft)

(Screened interval=274–682 ft) (Screened interval=225–615 ft)

Figure 12. —Continued.
Simulation of Ground-Water Flow 51

1970 1975 1980 1985 1990 1995 2000

–125

–100

–75

–50

–25

NAVD

88

25

50

75

100

Water–level altitude, in feet above NAVD 88

Year

Year

Group=SCR

Measured

Simulated-LY3

7S/1E-33M3

Measured

Simulated-LY3

7S/1W-24H1

Note scale change

Measured

Simulated-LY3

8S/1E–5N1/2

Measured

Simulated-LY3

8S/1W-3K9

Note scale change

Note scale change

Measured

Simulated-LY3

8S/1E-10J1, 2

Note scale change

1970 1975 1980 1985 1990 1995 2000

60

160

135

110

85

1970 1975 1980 1985 1990 1995 2000

75

175

150

125

100

1970 1975 1980 1985 1990 1995 2000

75

175

150

125

100

1970 1975 1980 1985 1990 1995 2000

75

100

125

150

175

200

225

250

(Screened interval not reported) (Screened interval not reported)

(Screened interval not reported) (Screened interval not reported)

(Screened interval not reported)

Figure 12. —Continued.
52 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1970 1975 1980 1985 1990 1995 2000

Flow rate, in cubic feet per day

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1970 1975 1980 1985 1990 1995 2000

Year Year

Coyote Creek at Edenville SCVWD-58 Saratoga Creek at Pruneridge Ave. SCVWD-25

Los Gatos Creek at Lark Blvd. SCVWD-59 Los Gatos Creek at Lincoln Ave. SCVWD-50

Measured

Simulated

Measured

Simulated

Measured

Simulated

Measured

Simulated

Figure 13. Measured and simulated streamflow for selected downstream gaging stations, Santa Clara Valley, California (Well locations shown on figure 1).
Simulation of Ground-Water Flow 53

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1970 1975 1980 1985 1990 1995 2000

Flow rate, in cubic feet per day

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1970 1975 1980 1985 1990 1995 2000

Year Year

Guadalupe River above Blossom Hill Rd. SCVWD-20 Alamitos Creek near New Almaden SCVWD-70

Guadalupe River at San Jose USGS-11169000 Guadalupe River above Almaden Expway SCVWD-73

Measured

Simulated

Measured

Simulated

Measured

Simulated

Measured

Simualted

Figure 13. —Continued.
54 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

–0.50

–0.40

–0.30

–0.20

–0.10

0.00

0.10

Subsidence, in feet

Measured (7S/1E-16C5)

Simulated subsidence

(Layers 1-6)

SAN JOSE EXTENSOMETER

SUNNYVALE EXTENSOMETERS

Depth = 908 feet

Measured (6S/2W-24C7)

Linear displacement transducer

Simulated subsidence

(Layers 1-6)

Measured (6S/2W-24C3)

Simulated subsidence

(Layers 1-4)

Measured (6S/2W-24C4)

Simulated subsidence

(Layers 1-3)

–0.20

–0.10

0.00

0.10

0.20

0.30

–0.30

–0.20

–0.10

0.00

0.10

0.20

–0.20

–0.10

0.00

0.10

0.20

0.30

Subsidence, in feet

Year

1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

Depth = 550 feet

Depth = 250 feet

Depth = 1,005 feet

Figure 14. Measured and simulated aquifer-system subsidence for selected extensometer wells, Santa Clara Valley, California.
Simulation of Ground-Water Flow 55

Revised Model(1990-99)

Revised Model(1975-99)

Revised Model(1970-99)

Previous Model(1970-89)

EXPLANATION

B

Root Mean Square error, in feet

Well Number

0

20

40

60

80

100

120

140

6S/1E-15Q1

6S/1W-24H8

7S/1E-6L1

7S/1W-6P1

7S/1W-4E2

7S/1W-5P2

7S/2W-1B1

7S/1E-16C6

7S/1E-2J6

6S/2W-21A1

6S/2W-24C7

6S/2W-28N1

6S/2W-33A2

7S/1W-2G27S/1W-9Q1

7S/1W-15E1

7S/1W-30C2

7S/1W-34F2

7S/1E-7R99

7S/1W-22E2

7S/1W-22E14

7S/1W-24H1

8S/1E-5N1

8S/1E-10J2

7S/1E-33M3

8S/2E-18L1

8S/2E-7A3

–150 –100 –50 NAVD 88 50 100 150 200

Measured water-level altitude, in feet

Simulated water-level altitude, in feet

–150

–100

–50

NAVD

88

50

100

150

200

A

1:1 Correlation line

Figure 15. Measured and simulated water-level error for selected monitoring wells (A) for all measurements and (B) for each comparison well, Santa Clara 

Valley, California.
56 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Calibration of transient-state conditions was dependent 

on recharge (streamflow, valley-floor recharge, and artificial 

recharge) to and discharge (pumpage, streamflow, and ET) 

from the aquifer system and on hydraulic conductivity, 

storage, vertical hydraulic conductivity between layers, fault 

hydraulic characteristic, and general-head boundary 

conductance. During calibration, inflows such as reported 

pumpage and reported artificial recharge were implemented at 

the reported values and were not adjusted. The implementation 

of the multi-node well package maintained the net pumpage 

but redistributed ground-water flow vertically between layers 

through intrawellbore flow (Animation 2. Map showing simulated 

wellbore flow for model layers 3 and 5, 1970–99, for the Santa Clara Valley 

model, Santa Clara Valley, California.). Model parameters related to 

smaller inflows and outflows such as ET and GHB also were 

not adjusted during model calibration. The transformation in 

layer 1 from constant heads in the previous model to generalhead cells also resulted in a smaller region of cells that are now 

restricted to the offshore region beyond the present coastline.

After replacement of the recharge, evapotranspiration, 

and coastal flow boundaries, the model was calibrated for 

goodness of fit for the 28 water-level hydrographs (fig. 12). 

These hydrographs were combined into seven groups on the 

basis of location, hydrologic setting, and related characteristics 

of the water-level fluctuations (figs. 1, 12). Model calibration 

began with a quantification of the model error and flow 

analysis from the previous model as a partial basis of 

comparison for the revised model.

After the new recharge boundary conditions were 

implemented, the recharge was adjusted. The mountain-front 

recharge in the previous model was replaced by estimates of 

runoff simulated using the STR package in the numerous small 

ungaged creeks that drain the surrounding mountains. The 

runoff derived from the precipitation-runoff model 

underestimated streamflow from smaller creeks such as Hale 

and Ross Creeks. To better match the streamflow from smaller 

creeks, the runoff estimated from the precipitation-runoff 

model was increased by a factor of 10 from the initial 

estimates. This resulted in inflows closer to measured inflows 

for smaller drainage areas. In addition, selected streambed 

conductances were reduced from initial estimates to improve 

the match of measured and simulated streamflow for the 

downstream gages on the major streams and tributaries. In 

particular, conductances were reduced from 86, 400 ft2/d to 

50,000 ft2/d and from 43,200 ft2/d to 25,000 ft2/d to improve 

conveyance to downstream streamflow gages used for 

comparisons of streamflow. In addition, selected downstream 

segments on Los Gatos, Stevens, Permanente, Saratoga, 

Coyote, Lower Silver, and Penetencia Creeks and on the 

Guadalupe River were reduced to 200 ft2/d to reduce the 

stream base flow that was draining the upper model layer and 

preventing the full recovery of ground-water levels. These 

downstream segments with reduced conductances were based 

on reaches with little increased or decreased flow delineated by 

SCVWD (J. Aguilera, Santa Clara Valley Water District, 

unpub. data, 2002). The final distribution of streamflow also is 

aligned with the distribution of inflow and outflow reaches and 

shows a complex distribution of gains and losses through time 

and space (Animation 3. Map showing simulated streamflow 

gains and losses and ground-water recharge from precipitation 

for model layers 1 and 3, 1970–99, for the Santa Clara Valley 

model, Santa Clara Valley, California.).

The revised model represented climatic variation in 

valley-floor recharge through the use of wet- and dry-month 

indices applied to monthly precipitation maps (Animation 3, 

Animation 4. Map showing simulated water levels, stream 

inflow, and artificial recharge for model layers 1 and 3, 

1970–99, for the Santa Clara Valley model, Santa Clara 

Valley, California.), and climatic variation in artificial 

recharge (Animation 4). This method is simpler than the 

approach used in the previous model where valley-floor 

recharge was estimated using a linear relation that applied 

about 10 percent of the square of precipitation from San Jose 

and Los Gatos as recharge within seven zones. 

The revised model uses percentages of valley-floor 

recharge that include wet- and dry-month recharge percentages 

of precipitation, which are aligned with the major climatic 

cycles of the Pacific Decadal Oscillation (PDO) (Mantua and 

Steven, 2002) which, in turn, control the frequency and 

magnitude of major winter frontal storms. The temporal 

categories were based, in part, on the cumulative departure 

curve of precipitation for San Jose. This required segregation 

of the recharge percentages into the period 1970–77, which 

represents a period with drier wet months, and the subsequent 

period 1978–99, which represented wetter wet months. Wet 

years were about 23 percent wetter in the positive-index PDO 

period (1978–99) than they were during the dryer negativeindex PDO period (1947–77). The percentage of recharge for 

the dry months in positive and negative PDO periods was 

about the same and was kept the same for both PDO periods. 

Although these percentages result in more recharge during the 

wetter periods, they are consistent with the surface recharge 

and runoff estimates made for the Santa Clara Valley (Joe 

Hevesi, U.S. Geological Survey, unpub. data, 2001) for the 

historical period segregated by climate periods. The use of 

these indices helped improve the temporal match of multi-year 

cycles present in all the types of hydrologic time series used for 

model calibration. The final percentages of recharge were 

7.5 percent for wet months and 4.5 percent for dry months for 

the period 1970–77 (drier PDO period), and 15 percent for wet 

months and 4.5 percent for dry months for the period 1978–99 

(wetter PDO period). 
Simulation of Ground-Water Flow 57

Hydraulic properties were changed in the revised model 

as part of the calibration process. The distribution of aquifer 

and aquitard storage properties was replaced, followed by the 

replacement of vertical hydraulic conductivity and finally by 

the replacement of horizontal hydraulic conductivity. The 

replacement and separation of aquifer and aquitard properties 

facilitated the seasonal and multi-year variations that control 

changes in ground-water storage and related changes in water 

levels. The multipliers for specific storage for layer 3 also were 

increased outside the confined region to represent unconfined 

storage properties within layer 3.

After replacement of the aquifer and aquitard storage 

properties, large errors in water levels persisted during the 

initial period of the transient simulation. These water-level 

errors were largely eliminated by changing the critical-head 

estimates. Initially critical heads were set equal to initial heads, 

which assumed a normally consolidated distribution of 

compacted sediments. These critical heads were required to 

represent an overconsolidated estimate where critical heads 

vary spatially and are tens to hundreds of feet below the 1970 

initial heads. The assumption of critical heads equal to initial 

heads resulted in initial rises in water levels related to water 

entering the ground-water flow system from inelastic 

compaction; this resulted in erroneous simulation of 

subsidence, contributions of water to ground-water flow, and 

initial water-level rises that dissipated after about 5 to 7 years 

of simulation. Some error still persists along the edge of the 

historical subsidence bowl where more recent ground-water 

pumpage is relatively larger than in decades prior to the 

simulation period (see fig. 18, later in report). This may 

indicate that critical heads remain uncertain in this region.

The base value for the skeletal elastic specific storage also 

was reduced by 80 percent for model layers 3 and 4 and 

decreased by 60 percent for model layers 1, 2, 5, and 6 in order 

to improve the match between measured and simulated 

compression and compaction at the extensometer sites for the 

period 1983–99. Even though smaller values were needed to fit 

the measured seasonal compression from extensometers, the 

consolidation tests from selected cores at depth suggest that the 

elastic compressibility was 2 to 3 times greater than the initial 

estimate used for all depths. However, the smaller estimates are 

for cores from the depth regions that have the greatest 

pumpage. Reduction of the base value for the inelastic storage 

of 80 percent for model layers 3 and 4 is consistent with the 

core-consolidation tests. The final distribution of subsidence 

parameters resulted in a simulation of subsidence for the period 

1983–99 that shows predominantly elastic deformation and 

recovery with some inelastic deformation along the 

southwestern edge of the confined region during the 1984–91 

drought (Animation 5. Map showing simulated subsidence for 

all model layers and water-level change for layer 3, 1983–99, 

for the Santa Clara Valley model, Santa Clara Valley, 

California.).

Another major adjustment that affected the fit to water 

levels in the central part of the valley (CRH region) was the 

westward relocation of the “new Cascade” Fault as a horizontal 

ground-water flow barrier (figs. 1, 5). This barrier is needed to 

reduce the overestimation of water levels in the central part of 

the valley. Final adjustments to the barrier included gaps in the 

fault along the major creeks to allow recharge into the southcentral part of the valley. A similar gap also was required along 

the Silver Creek Fault at its intersection with lower Silver 

Creek to facilitate the flow of streamflow infiltration into the 

south-central part of the valley. In addition to the gaps, 

channels with higher hydraulic conductivities were emplaced 

in layers 1 and 3 beneath the major stream channels that 

extended through the gaps in the fault along selected tributaries 

and also northward from Coyote Narrows beneath Coyote 

Creek. The range of the horizontal hydraulic conductivity (HK) 

array values also were expanded for layers 1 and 3 from one to 

four orders of magnitude. The revised range for layer 1 is now 

from 0.004 to 0.684 with the additional selected stream cells set 

to a value of 2 in the multiplier array for HK (fig. 6A). 

Similarly, the revised range for layer 3 is now 0.0001 to 0.875 

with the additional selected stream cells set to a value of 5 in 

the multiplier array for HK (fig. 6B).

Several additional adjustments were made after extending 

the simulation through the update period of 1990–99. The skin 

factor (that is, resistance to inflow) for wellbore flow entrance 

losses (Halford and Hanson, 2002, eqn. 3) was increased from 

5 to 15 during calibration in order to better fit the potential head 

differences indicated at nearby multiple-well monitoring sites 

such as the Coyote Creek Outdoor Classroom (CCOC) site 

(Hanson and others, 2002b) (fig. 1). The increased skin factor 

also resulted in a better match with the measured and simulated 

percentages of wellbore flow per model layer at selected 

wellbores (fig. 16). The base value for horizontal hydraulic 

conductivity in model layer 5 also was increased with the 

change in skin factor. This increased the amount of water that 

was pumped from layer 5, improved the match between 

measured and simulated head differences, and improved the 

distribution of estimated wellbore flow from model layers. The 

wellbore flow generally matches peak wellbore flows in 

selected water-supply wells measured under actual operating 

conditions using dye-tracing methods (Izbicki and others, 

1999) in the Santa Clara Valley (Hanson and others, 2003). The 

distribution of wellbore flow also is consistent with the relative 

depth distribution of artificial-recharge estimates from depthspecific monitoring-well samples and from depth-dependent 

water-supply well samples (fig. 16) (Hanson and others, 2003). 

The alignment of increased recharge in the upper model layers 

also is consistent with the relatively larger hydraulic 

conductivity and related wellbore outflow from pumpage. 

However, the distribution of wellbore flow is subject to 

considerable changes through time as wells are turned on and 

off. The transient nature of the wellbore flow distribution is 

indicated by the temporal distribution of wellbore flow for 

model layers 3 and 5 (Animation 2).
58 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Percent artificial recharge

Depth-dependent estimated percent artificial recharge (12th St. No.10)

Depth-specific estimated percent artificial recharge (CCOC)

0 10 20 30 40 50

0

100

200

300

400

500

600

700

800

900

0 20 40 60 80 100

Cumulative percent

measured flow

(12th St. No. 10)

Previous model percent flow

Model-layer measured percent flow

Revised model percent flow

Depth below land surface, in feet

B

Pump

intake

0 100

Percent cumulative wellbore flow

Depth below land surface, in feet

Model layer 3

Model layer 4

Model layer 5

Model layer 3

Model layer 4

Model layer 5

Pump

intake

0

100

200

300

400

500

600

700

800

900

1,000

Depth-specific estimated

percent artificial recharge (STPK)

Previous model

percent flow

Depth-dependent

estimated percent artificial

recharge (Williams No. 3)

Cumulative percent

measured flow

(Williams No. 3)

Cumulative percent

measured flow

(Williams No. 3)

Model-layer

measured

percent flow Revised model

percent flow

20 40 60 80

0 10 20 30 40 50

A

Figure 16. Distribution of measured and simulated wellbore flow and estimated percentage of artificial recharge for (A) Williams No. 3 and (B) 12th St. No. 10 

water-supply wells, Santa Clara Valley, California.
Simulation of Ground-Water Flow 59

The final model has an average root-mean-square (RMS) 

error for water levels from the 27 comparison wells of 27 ft for 

the 29.75-year simulation period 1970–99 for 5,703 waterlevel measurements and shows a generally good correlation 

between measured and simulated water levels (fig. 12). When 

the first 5 years of the simulation are excluded for the 

dissipation of initial-condition errors, the average RMS error is 

reduced to 22 ft for the period 1975–99. The average RMS 

error for the updated period is 23 ft. The previous model had 

an average RMS error of 36 ft for the period 1970–89. When 

subdivided into the seven groups of wells, the revised model 

has improved the fit to water levels in the ERH, CRH, and SCR 

groups relative to the previous model (figs. 1, 15) and is 

generally comparable in the other groups. When the 

observations also are interpolated in time (Harbaugh and 

others, 2000a), the average error for the calibrated revised 

model is −7.34 ft. The negative error for the revised model 

generally represents an underestimation of extreme waterlevel declines for some regions (fig. 15A). These water-level 

declines may reflect instantaneous pumping conditions that are 

not simulated exactly when using average monthly pumping 

rates. Overall, the revised model substantially reduces the 

model error for almost all comparison wells relative to the 

previous model (fig. 15B).

The simulated streamflow generally matches measured 

streamflow for flows above 100,000 ft3/d (greater than 

1.2 ft3/s) for the simulated streamflow along Guadalupe River 

at San Jose (USGS Gage 11169000), and above Blossom Hill 

Road (SCVWD Gage 20), above Almaden Expressway 

(SCVWD Gage 73), and its tributary Alamitos Creek near New 

Almaden (SCVWB Gage 70); and along Los Gatos Creek at 

Lark Boulevard (SCVWD Gage 59), and at Lincoln Avenue 

(SCVWD Gage 50), Coyote Creek at Edenville (SCVWD 

Gage 58), and Saratoga Creek at Pruneridge Avenue 

(SCVWD Gage 25) (fig. 13). In addition, the losing and 

gaining reaches are generally consistent with the observed 

reaches within the streamflow network (Joseph Aguilera, 

Santa Clara Valley Water District, unpub. data, 2002) 

(Animation 3).

The revised model also fits the range of measured 

compression and compaction at the two extensometer sites 

located near San Jose within 15 to 27 percent and near 

Sunnyvale within less than 3 percent of the range of measured 

seasonal deformation for the deepest extensometers, 

respectively (fig. 14). The RMS errors for simulated 

subsidence at the San Jose extensometers are 0.06 (16C5) and 

0.12 ft (16C11) for the period 1983–93. The RMS errors for the 

simulated subsidence at the Sunnyvale extensometers are

0.03 ft (24C3), 0.02 ft (24C4), and 0.04 ft (24C7) for the period 

1983–97. The simulated deformation is within 48 and 

53 percent of the range of deformation for the two shallower 

extensometers near Sunnyvale. Monthly stress-period data 

improved the temporal detail of simulated changes in aquifer 

storage, and was in phase with resulting observed seasonal 

compression. This suggests that the simulation of ultimate 

compression was adequate for the predominantly elastic 

compression observed in the historical period of simulation. 

Elastic rebound is overestimated at depth, which may suggest 

that there is some delayed response in elastic rebound from the 

water-level recovery in the deeper parts of the aquifer system 

(see 1,005-ft depth extensometer 24C7, fig. 14).

The spatial comparison of the revised model includes 

water-level maps and estimated subsidence from multiple-year 

and seasonal water-level changes derived from InSAR images 

(Galloway and others, 2000). The simulated ground-water 

levels are in general agreement with the hand-contoured waterlevel maps (Behzad Ahmadi, Santa Clara Valley Water 

District, unpub. data, 2000) for the spring and fall of 1995 and 

1997 (fig. 17). The hand-contoured maps were completed 

without the faults as potential ground-water flow barriers and 

include specific cones of depression around selected well 

fields. The simulated subsidence also shows a similar pattern 

of deformation with respect to the spatial distribution derived 

from the historical subsidence (fig. 18), from the seasonal and 

multi-year InSAR images (fig. 19), and the overall recovery of 

the basin (Animation 5). The general trend of recovery of the 

land surface since 1992 also is in agreement with the analysis 

of the complete set (115) of InSAR images that indicate both 

long-term uplift along with the recovery of ground-water 

levels and continuation of seasonal deformation and recovery 

(Schmidt, 2002). The simulated data from the model also show 

the multi-year elastic deformation related to the drought 

(1984–91) superimposed onto the seasonal deformation that is 

not present in the limited (post-1991) InSAR data.
60 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

0

20

20

10

40

20

40

80

60

50

50

60

80

4060

80

280

240

260

120 120

140

160

180

180 200

220

100 100

100 120

140

160

180

240

200

300

220

280

200

260

220

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

A

Simulated ground-water level (April 1995), in feet Alluvial basin boundary

Confined zone limit

Line of equal water level

(April 1995), in feet—

Contour interval 10 feet

from 0 to 200 feet;

20 feet above 200 feet.

Hachures indicate depression

21 to 30

31 to 40

41 to 50

51 to 60

61 to 70

71 to 80

81 to 90

91 to 100

101 to 110

111 to 120

121 to 130

131 to 140

141 to 150

151 to 160

161 to 170

171 to 180

181 to 190

191 to 200

201 - 210

211 - 220

221 - 230

231 - 240

241 - 250

0 to 10

11 to 20

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

Universal Transverse Mercator Projection, Zone 10

Figure 17. Hand-contoured measured and simulated ground-water levels, April and September, 1995, and March and September, 1997, for the Santa Clara 

Valley model, Santa Clara Valley, California.
Simulation of Ground-Water Flow 61

1

0

0

0

0

0

0

0 20

40

8 60

0

100

140

180

160

200

220

220

200

240 280 260

250

120

0

20

20

2040

60

20

10

40

60

60

80

80

80

100

120

140

160

180

200

220

130

60

20

40

40

40

20

60

80

80

100

120

140

160 180

200

240

280

300

400

350

40

20

0

80

40

–20

–20

–20

–20

–40

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

B

Alluvial basin boundary

Confined zone limit

Simulated ground-water level (September 1995), in feet

Line of equal water level

(September 1995), in feet—

Contour interval 10 feet

from 0 to 200 feet;

20 feet above 200 feet.

Hachures indicate depression

11 to 20

21 to 30

31 to 40

41 to 50

51 to 60

61 to 70

71 to 80

81 to 90

91 to 100

101 to 110

111 to 120

121 to 130

131 to 140

141 to 150

151 to 160

161 to 170

171 to 180

181 to 190

191 to 200

201 to 210

211 to 220

221 to 230

231 to 240

–18 to –10

1 to 10

–9 to 0

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

Universal Transverse Mercator Projection, Zone 10

Figure 17. —Continued.
62 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

0

20

20

40

10

40

60

80

80

100

60

60

80

100

120

140

120

120

100

160 180

200

240

280 320

360

400

420

140

180

200 220

160

160

20 180 0

220

260

240

280

290

260

40

60

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

C

Alluvial basin boundary

Confined zone limit

Simulated ground-water level (March 1997), in feet

Line of equal water level

(March 1997), in feet—

Contour interval 10 feet

from 0 to 200 feet;

20 feet above 200 feet.

Hachures indicate depression

21 to 30

31 to 40

41 to 50

51 to 60

61 to 70

71 to 80

81 to 90

91 to 100

101 to 110

111 to 120

121 to 130

131 to 140

141 to 150

151 to 160

161 to 170

171 to 180

181 to 190

191 to 200

201 - 210

211 - 220

221 - 230

231 - 240

241 - 250

0 to 10

11 to 20

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

Universal Transverse Mercator Projection, Zone 10

Figure 17. —Continued.
Simulation of Ground-Water Flow 63

0

10

10

0

20

20

20

40

20

40

40

80

80

20

40

60 80

80

60

20

2040

60

80

80

100

120

120

140

140

160

180

200

220

100

60

140

160

180

20022

26

0

0

280

150

240

20

40

60

80

120

100

140

160

180

200

240

280

320

360

400

440

440

420

0

0

0

–20

–20

–20

–20

–40–60

–80

–20

–20

–20

–40

–60

0

0

0

40

20

60

80

40

5 0

20

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

D

Alluvial basin boundary

Confined zone limit

Simulated ground-water level (September 1997), in feet

Line of equal water level

(September 1997), in feet—

Contour interval 10 feet

from 0 to 200 feet;

20 feet above 200 feet.

Hachures indicate depression

11 to 20

21 to 30

31 to 40

41 to 50

51 to 60

61 to 70

71 to 80

81 to 90

91 to 100

101 to 110

111 to 120

121 to 130

131 to 140

141 to 150

151 to 160

161 to 170

171 to 180

181 to 190

191 to 200

201 to 210

211 to 220

221 to 230

231 to 240

241 to 250

–18 to –10

1 to 10

–9 to 0

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

Universal Transverse Mercator Projection, Zone 10

Figure 17. —Continued.
64 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

0.1 0.5

0.5

0.5

1

1

1

2

2

3

3

4

5

6

6

7

8

8

7

5

4

0.1

0.1

PALO

EVGN

SRTG

SNVL

GUAD

STPK

MCGY

CCOC

WILO

7S/1E-16C4

6S/2W-24C3

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

Simulated land subsidence, in feet (Jan 83–Sep 99)—

Negative number indicates uplift

Monitoring wells

Extensometers

–0.62 to –0.30

–0.29 to –0.20

–0.19 to –0.10

–0.09 to 0.00

1.51 to 3.00

3.01 to 6.00

6.01 to 9.00

0.01 to 0.10

0.11 to 0.50

0.51 to 1.50

Line of measured subsidence

(1939–80), in feet—

(Poland and Ireland, 1988)

Creeks

Basin boundary

Extent of confined aquifer zone

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;

Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

Figure 18. Hand-contoured measured subsidence, 1939–80, and simulated ground compaction, 1983–99, for the Santa Clara Valley model, Santa Clara Valley, 

California.
Simulation of Ground-Water Flow 65

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

Creeks Evergreen

North-Central Silver Creek

South-Central Silver Creek

New Cascade

Monte Vista

Alluvial basin boundary

InSAR land-surface deformation

(Jan 97–Aug 97)—(Galloway and others,

2000)

Model defined faults

Extent of confined aquifer zone

Recharge ponds

A

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;

Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

One fringe, or one color cycle, represents

1.1 inches (28 millimeters) of vertical

displacement. Areas where the radar signals

were poorly correlated are transparent

Range displacement Increasing relative subsidence

Figure 19. (A) InSAR-estimated seasonal compression and (B) simulated deformation, January to September 1997, for the Santa Clara Valley model, Santa Clara 

Valley, California.
66 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

PALO

EVGN

SRTG

SNVL

GUAD

STPK

MCGY

CCOC

WILO

7S/1E-16C4

6S/2W-24C3

San

Francisco

Bay

0246 8 10 MILES

0246 8 10 KILOMETERS

EXPLANATION

B

Simulated total compaction, in inches (Jan 97–Aug 97)—

Negative number indicates uplift

Monitoring wells

Extensometers

–7.44 to –3.60

–3.59 to –2.40

–2.39 to –1.20

–1.19 to 0.00

0.01 to 1.20

1.21 to 6.00

6.01 to 18.00

Creeks

Alluvial basin boundary

Extent of confined aquifer zone

Base from U.S. Geological Survey digital elevation data, 1:250,000, 1987, and digital data, 1:100,000, 1981–89;

Universal Transverse Mercator Projection, Zone 10. Shaded relief base from 1:250,000-scale Digital Elevation

Model; simulated sun illumination from northwest at 30 degrees above the horizon

Figure 19. —Continued.
Model Sensitivity and Uncertainty 67

The ground-water inflow and outflow also was compared 

with that of the previous model (fig. 20A). The total average 

simulated flow from the previous model was about 

207,200 acre-ft/yr for the period 1970–99. The revised model 

now has a slightly increased flow of about 225,500 acre-ft/yr 

for the same period. The total inflow and outflow is about 

205,300 acre-ft/yr for the period 1970–99. The net change in 

ground-water storage for the entire historical simulation period 

is variable and aligned with the climate cycles (fig. 20B). 

Overall the simulated net change in storage increased by about 

189,500 acre-ft/yr for the entire period of simulation, which 

represents about one and a half years of the 1970–99 average 

pumping. The multi-node well package now replaces most of 

the interlayer flow of the previous model. This flow represents 

about 19 percent of the total ground-water inflow as interlayer 

flow between model layers and represents wellbore flow 

through multi-aquifer wells. The rates of recharge of about 

155,300 acre-ft/yr for the previous model and 

147,800 acre-ft/yr for the revised model are similar for the 

period 1970–89. The average total recharge rate from natural 

and artificial recharge and from streamflow infiltration for the 

revised model for the entire simulation period of 1970–99 was 

about 157,100 acre-ft/yr, which represents about 72 percent of 

the inflow to the ground-water flow system with respect to net 

pumpage (fig. 20A). The average rate of artificial recharge of 

about 77,600 acre-ft/yr represents about 36 percent of the 

inflow to the ground-water flow system and about half of the 

outflow as pumpage (fig. 20A). Similarly, rates of pumpage of 

about 146,900 acre-ft/yr for the previous model and 

147,000 acre-ft/yr for the revised model are comparable for the 

period 1970–89. The average pumpage rate is somewhat less 

for the entire 29.75-year simulation period, averaging about 

133,400 acre-ft/yr. The average pumpage represents about 

61 percent of the outflow from the ground-water flow system 

(fig. 20A).

The changes in ground-water flow generally reflect the 

major climate cycles and the additional importation of water by 

SCVWD (fig. 20B). The basin has been in recovery since the 

drought of the late 1980s and early 1990s as demonstrated by 

the trend towards negative change in storage (that is, water 

going out of ground-water flow and back into ground-water 

storage) (fig. 20B). While the imported water has slightly 

declined with some year-to-year variation on the order of 

25,000 to 50,000 acre-ft/yr, the water-level recovery and 

related increase in ground-water storage generally is driven by 

a substantial decrease in ground-water pumpage since 1989 

(fig. 20B). The water derived from interbed storage has 

alternated around zero (fig. 20B) and represents a small 

percentage of the total change in storage over the period of 

simulation (fig. 20A). The ET has been a small and relatively 

constant component of the budget (fig. 20A). The streamflow 

infiltration shows some climatic variability and has remained 

between 20,000 and 50,000 acre-ft/yr through the 29.75-year 

period (fig. 20B). The outflow at the San Francisco Bay (Net 

GHB) has shown a small but steady increase during the basin 

recovery (fig. 20B). This is consistent with most of the recharge 

infiltrating and flowing through the uppermost layers 

(i.e. model layers 1 and 3) of the aquifer system. Most of the 

water that flows to the deeper model layers is occurring through 

wellbores, with wellbore flow representing 19 percent of the 

total ground-water inflow between model layers.

Model Sensitivity and Uncertainty

The SCVM model was extremely sensitive to changes in 

inflows, outflows, and selected hydraulic properties. In 

particular, the model failed convergence when some of the 

model parameters were perturbed out of the range of the final 

set of specified values. This, in part, prevented the use of 

systematic parameter-estimation techniques to estimate 

selected model parameters and related sensitivities that are 

based on perturbation approaches. During trial-and-error 

calibration, the model was noted to be most sensitive to 

increases in vertical hydraulic conductivity, decreases in 

horizontal hydraulic conductivity, decreases in streambed 

conductance, increases in conductances of horizontal flow 

barriers, decreases in specific storage, and increases in 

hydraulic characteristics for horizontal flow barriers. The 

application of the MNW package affected streamflow 

infiltration and the vertical distribution of water derived from 

compression and compaction (Hanson and others, 2003). The 

skin factor in the MNW package affected the interlayer flow 

and related water-level difference between model layers. The 

refined monthly specification of inflows and outflows has 

created more separation of the supply and demand components 

of the ground-water and surface-water resources. Therefore, 

the revised model is more capable of addressing watermanagement issues at the annual and seasonal time scales as 

reflected in the simulated ground-water levels, streamflow, and 

deformation time seires. The improved temporal and spatial 

separation, as well as individual simulation of inflows and 

outflows, also will facilitate the application of optimization 

modeling analysis to help SCVWD address the feasible 

solutions to water-resource goals subject to subsidence, 

streamflow, water-quality, and related economic constraints. 
68 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

HYDROLOGIC BUDGET

Revised Model

(1970–1999)

Storage

Artificial recharge

Recharge

Stream leakage

Interbed storage

Storage

Evapotranspiration

General-head boundary

(San Francisco Bay)

Stream leakage

Interbed storage

Net multi-node wells

19%

6%

75%

23%

6%

71%

Previous Model

(1970-1989)

Storage

Constant head

Total recharge

Storage

Constant head

Wells

Inflow Outflow

Inflow Outflow

23%

36%

19%

17%

5%

26%

2%

4%

3%

4%

61%

A

Figure 20. (A) percentages of components of the hydrologic budget for the previous model for the period 1970–89 and the revised model for the period 

1970–99, Santa Clara Valley, California, and (B) inflow and outflow components through time for the period 1970–99, Santa Clara Valley, California.
Model Sensitivity and Uncertainty 69 1970 1975 1980 1985 1990 1995 2000 Year

r year e-feet per acn Flow, i

Net storageStreamflow infiltrationAreal recharge

Artificial rechargeNet pumpageNet General-head boundary

EvapotranspirationNet interbed storage

–100,000–125,000–150,000–175,000–200,000

–25,000–50,000–75,000

0

75,00050,00025,000

125,000100,000

EXPLANATION

B

DRY WET WET WET DRY DRY

Figure 20. —Continued.
70 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Several elements of the revised model remain uncertain 

and will require additional investigation to improve the 

accuracy of the simulation of the ground-water and surfacewater flow and simulation of regional subsidence. The 

increased accuracy will allow SCVWD to address more 

detailed management questions related to the operation of 

artificial-recharge facilities, minimization of subsidence, 

increase in ground-water pumpage, or reduction in pumping of 

ground water high in nitrate or other contaminants. The largest 

uncertainties are related to model layering, smaller inflows and 

outflows, and selected hydrologic features and properties.

The representation of sedimentary layering and 

distribution of facies within the related model layers needs to 

be improved before the model is suitable for simulating the 

flow and distribution of artificial recharge using solutetransport or particle-tracking simulations. The current modellayering remains, in part, uncertain on the basis of model layers 

that were derived from a combination of well-screen 

distributions and lithologic layering. The redefinition of the 

sequence of stratigraphic layering would refine the 

geologically controlled flow paths in the ground-water flow 

system, and is part of ongoing research by the USGS. 

Some of the smaller inflows and outflows remain 

uncertain and may affect the accuracy of the model locally. 

The model could be improved by including more detailed 

estimates of the extent of leakage from water transmission 

lines, the nature of inflow and outflow that could affect 

seawater intrusion along the San Francisco Bay, and the 

distribution of gaining and losing streamflow reaches that are 

related to natural runoff events or application of artificial 

recharge. Distributed valley-floor recharge could be estimated 

with more detail and could distinguish between a combination 

of natural recharge from precipitation and artificial recharge 

from urban anthropogenic effects such as leaky water 

distribution systems, urban irrigation and concentrated urban 

runoff, or leaky sewer pipes.

Hydrologic features that remain uncertain include the 

location of some fault segments, critical-head distributions, 

and selected hydraulic properties. The exact location of the 

New Cascade Fault remains uncertain and is the subject of 

continued investigations by the USGS and the SCVWD. The 

distribution of critical heads remains uncertain and will be 

potentially better defined through inclusion of estimates from 

consolidation tests of cores obtained from the completion of 

the new monitoring-well sites. The uncertainty in critical heads 

is greatest along the southwestern and western parts of the 

basin where the model overestimation of subsidence may be 

the result of overestimating initial critical heads for 1970

(fig. 18). Selected hydraulic properties that remain uncertain 

include horizontal hydraulic conductivities related to a 

potential coarse-grained stream-channel facies farther north 

along Coyote Creek towards the San Francisco Bay that may 

be in alignment with the InSAR deformation pattern. These 

extensions of the deformation that are apparent from the 

InSAR images may be related to coarse-grained facies of the 

ancestral drainage along Coyote Creek and Guadalupe River 

(Schmidt, 2002). Additional estimates of horizontal hydraulic 

conductivity could be obtained from slug tests at the new 

monitoring-well sites. Finally, the distribution of streambed 

conductances could be better defined through the application 

of seepage-run studies and more detailed classification of 

streambed sediments.

Summary and Conclusions

The Santa Clara Valley is a long, narrow trough extending 

about 35 mi southeast from the southern end of San Francisco 

Bay. Ground water from the regional alluvial-aquifer system is 

a major source of water in the Santa Clara Valley, which has 

been the site of intensive agricultural and urban development 

throughout the 20th century. The related ground-water 

development resulted in ground-water-level declines of more 

than 200 ft and has induced as much as 12.7 ft of land 

subsidence between the early 1900s and the mid-1960s. Since 

the 1960s, Santa Clara Valley Water District has imported 

surface water to meet growing demands and reduce 

dependence on ground-water supplies. The use of imported 

water and implementation of artificial recharge has resulted in 

the sustained recovery of the ground-water flow system 

throughout many parts of the Santa Clara Valley. Management 

of the ground-water resources is facilitated by the development 

of a regional ground-water/surface-water flow model that 

simulates the flow of ground water and surface water, changes 

in ground-water storage, and related effects such as potential 

land subsidence.

A revised numerical ground-water/surface-water flow 

model of the Santa Clara Valley was developed as part of a 

cooperative investigation with Santa Clara Valley Water 

District. The flow model was developed to better define the 

geohydrologic framework of the regional flow system and to 

better delineate the supply and demand components that affect 

the inflows to and outflows from the regional ground-water 

flow system. Development of the model included revisions to 

the previous ground-water flow model that upgraded the 

temporal and spatial discretization, added source-specific 

inflows and outflows, simulated additional flow features such 

as land subsidence and multi-aquifer wellbore flow, and 

extended the period of simulation through September 1999. 

The transient-state model was calibrated to historical surfacewater and ground-water flows for the period 1970–99 and to 

historical subsidence for the period 1983–99.
Summary and Conclusions 71

The regional ground-water flow system consists of 

multiple aquifers that compose upper- and lower-aquifer 

systems. The upper-aquifer system is further divided into a 

confined region that is roughly coincident with the combined 

extent of the bay muds and an unconfined region that occurs 

between the confining beds and the surrounding mountains. 

Ground-water inflow occurs as natural recharge in the form of 

areal infiltration of precipitation and streamflow infiltration 

along stream channels. Ground-water inflow also occurs as 

artificial recharge from infiltration of imported water at 

recharge ponds, and from leakage along selected transmission 

pipelines. Ground-water outflow occurs as evapotranspiration, 

stream base flow, discharge through pumpage from wells, and 

subsurface flow to the San Francisco Bay.

The geohydrologic framework of the regional groundwater flow system was subdivided into six model layers for the 

simulation of developed ground-water flow conditions. The 

upper-aquifer system is composed of Holocene and 

Pleistocene-age deposits. The lower-aquifer system is 

composed of early Pleistocene and Pliocene-age deposits. In 

addition to the hydrostratigraphic layering, the model is 

bounded below and along the mountain fronts by relatively 

impermeable bedrock. The regional aquifer systems are also 

dissected by several laterally extensive faults that may form at 

least partial barriers to the horizontal flow of ground water.

The spatial and temporal extent of the ground-water flow 

model was extended relative to previous models. While the 

layering and coverage over the San Francisco Bay region 

remain similar to components of the previous models, the 

model now covers the entire Santa Clara Valley, including the 

Evergreen subregion that was not previously simulated. The 

temporal discretization is now monthly, and the historical 

simulation was extended to the period 1970–99. The spatial 

discretization also was “regularized” to square cells 1,000 ft per 

side throughout the model grid.

The hydraulic properties were redefined on the basis of 

cell-based lithologic properties that were delineated on the 

basis of aggregate thicknesses of coarse-grained, fine-grained, 

and mixed textural categories. The textural categories were 

used to estimate the horizontal and vertical hydraulic 

conductivities, and aquifer storage properties. The estimation 

of aquitard and confining-layer storage properties also was 

based on the cell-based aggregated thickness of fine-grained 

deposits and was used to simulate elastic and inelastic land 

subsidence.

The simulated inflows and outflows for the Santa Clara 

Valley Model included monthly specified flows and headdependent flows. Specified inflows included valley-floor 

recharge as the areally distributed infiltration of a portion of 

monthly precipitation, artificial recharge from infiltration of 

imported water at infiltration ponds and along selected stream 

channels, and leakage from selected transmission pipelines. 

Specified streamflows were routed through all of the gaged and 

ungaged creeks and rivers, which results in head-dependent 

streamflow infiltration. Intrawellbore flow resulted in headdependent interlayer inflows and outflows through pumped and 

nonpumped wells. A small amount of head-dependent inflow 

also occurs along the coastal boundary with the San Francisco 

Bay and may represent underflow or leakage from the Bay. 

Head-dependent outflows were simulated as ground-water 

pumpage; evapotranspiration along the stream channels; 

stream base flow; and outflow along the coastal boundary with 

the San Francisco Bay, which may represent underflow or 

leakage to the Bay. 

The model was upgraded to MF2K and was calibrated to 

fit historical ground-water levels, streamflow, and land 

subsidence for the period 1970–99. The revised model slightly 

overestimates measured water levels with an average error of

−7.34 ft. The streamflow generally shows a good match on 

gaged creeks and rivers for flows greater than 1.2 ft3/s. The 

revised model also fits the measured compression and 

compaction at the two extensometer sites located near San Jose 

within 16 to 27 percent and near Sunnyvale within 3 percent of 

the maximum measured seasonal deformation for the deepest 

extensometers, respectively.

The slightly increased total ground-water inflow and 

outflow of about 225,500 acre-ft/yr is comparable with the 

previous model 207,200 acre-ft/yr for the period 1970–89 and 

is comparable to the simulated total inflow and outflow of 

about 205,300 acre-ft/yr for the period 1970–99. Overall the 

simulated net change in storage increased by about 

189,500 acre-ft/yr for the entire period of simulation, which 

represents about one and a half years of the 1970–99 average 

pumping. The changes in ground-water flow and storage 

generally reflect the major climate cycles and the additional 

importation of water by SCVWD, with the basin in recovery 

since the drought of the late 1980s and early 1990s. The rates 

of recharge of about 155,300 acre-ft/yr for the previous model 

and 147,800 acre-ft/yr for the revised model are similar for the 

period 1970–89. The average total recharge rate from natural 

and artificial recharge and from streamflow infiltration for the 

revised model for the entire simulation period of 1970–99 was 

about 157,100 acre-ft/yr, which represents about 59 percent of 

the inflow to the ground-water flow system. This rate of inflow 

is comparable to the average rate of artificial recharge of about 

77,600 acre-ft/yr, which also represents about 30 percent of the 

inflow to the ground-water flow system. Similarly, rates of 

pumpage of about 146,900 acre-ft/yr for the previous model 

and 147,000 acre-ft/yr for the revised model are comparable for 

the period 1970–89. The average pumpage rate is somewhat 

less for the entire 29.75-year simulation period, averaging 

about 133,400 acre-ft/yr. The average pumpage represents 

about 69 percent of the outflow from the ground-water flow 

system. Most of the simulated recharge infiltrates and flows 

through the uppermost layers (i.e. model layers 1 and 3) of the 

aquifer system. Most of the water that flows to the deeper 

model layers is occurring through wellbores, with wellbore 

flow representing 19 percent of the total ground-water inflow 

between model layers.
72 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

References Cited

Anderson, S.R., and Hanson, R.T., 1987, Relation of aquifer 

compaction to Cenozoic depositional environments in the 

Tucson basin, Arizona, in Abstracts with Programs: 

Geological Society of America Annual Meeting and 

Exposition, Phoenix, Arizona, October 1987, 573 p.

Bartugno, E.J., McJunkin, R.D., and Wagner, D.L., 1991, Map 

showing recency of faulting, San Francisco–San Jose 

quadrangle, 1:250,000: California Department of 

Conservation, Division of Mines and Geology, Regional 

Geologic Map Series, Map 5A, Sheet 5.

California Department of Water Resources, 1967, Evaluation 

of ground water resources, South Bay, appendix A— 

Geology: Bulletin 118-1, 153 p.

__________ 1975, Evaluation of groundwater resources, south 

San Francisco Bay, Volume III, northern Santa Clara 

County area: Bulletin No. 118-1[variously paged].

California History Center, 1981, Water in the Santa Clara 

Valley—a history: Seonaid McArthur, ed., California 

History Center, De Anza College, Local History Studies, v. 

27, 

155 p.

Catchings, R.D., and Goldman, M.R., Gandhok, G., Rymer, 

M.J., and Underwood, D.H., 2000, Seismic imaging 

evidence for faulting across the northwestern projection of 

the Silver Creek Fault, San Jose, California: U.S. Geological 

Survey Open-File Report 00-125, 29 p.

CH2M Hill, 1991, Santa Clara Valley groundwater model 

project, Hydrogeological interpretation and numerical flow 

model: Draft technical memorandum, prepared for City of 

San Jose and Santa Clara Valley Water District, 35 p.

__________ 1992a, Santa Clara Valley groundwater model 

project, GIS data base and utility program documentation: 

Prepared for City of San Jose and Santa Clara Valley Water 

District [variously paged].

__________ 1992b, Basinwide groundwater flow model: 

Draft technical memorandum, prepared for City of San Jose 

and Santa Clara Water District [variously paged].

D'Agnese, F.A., O'Brien, G.M., Faunt, C.C., Belcher, W.R., 

and San Juan, Carma, 2002, A Three-dimensional numerical 

model of predevelopment conditions in the Death Valley 

regional, ground-water flow system, Nevada and California: 

U.S. Geological Survey Water-Resources Investigations 

Report 02-4102, 114 p.

Fio, J.L., and Leighton, D.A., 1995, Geohydrologic 

framework, historical development of the ground-water 

system, and general hydrologic and water-quality conditions 

in 1990, South San Francisco Bay and Peninsula area, 

California: U.S. Geological Survey Open-File Report 

94-357, 46 p.

Friebel, M.F., Freeman, L.A., Smithson, J.R., Webster, M.D., 

Anderson, S.W., and Pope, G.L., 2002, Water resources 

data, California water year 2001: U.S. Geological Survey 

Water-Data Report CA-01-2, v. 2, 450 p.

Galloway, D.L., Jones, D.R., Ingebritsen, S.E., 2000, 

Measuring land subsidence from space: U.S. Geological 

Survey Fact Sheet 051-00, 4 p. 

Halford, K.J., and Hanson, R.T., 2002, User's guide for the 

drawdown-limited, multi-node well (MNW) package for the 

U.S. Geological Survey's modular three-dimensional finitedifference ground-water flow model, versions MODFLOW96 and MODFLOW-2000: U.S. Geological Survey OpenFile Report 02-293, 33 p.

Halford, K.J., and Hanson, R.T., 2003, Effects of simulating 

multi-node wells on model calibration, interpretation, and 

prediction results—Modflow and more 2003: 

Understanding through modeling—Conference 

Proceedings, International Ground Water Modeling Center, 

Golden, Colorado, September 16–19, 2003, p. 70–73.

Hanson, R.T., 1989, Aquifer-system compaction, Tucson 

basin and Avra Valley, Arizona: U.S. Geological Survey 

Water-Resources Investigations Report 88-4172, 69 p.

Hanson, R.T., Anderson, S.R., and Pool, D.R., 1990, 

Simulation of ground-water flow and potential subsidence, 

Avra Valley, Arizona: U.S. Geological Survey WaterResources Investigations Report 93-4196, 47 p.

Hanson, R.T., and Benedict, J.F., 1994, Simulation of groundwater flow and potential subsidence, upper Santa Cruz 

Basin, Arizona: U.S. Geological Survey Water-Resources 

Investigations Report 93-4196, 47 p.

Hanson, R.T., and Leake, S.A., 1998, Documentation for 

HYDMOD, A program for time-series data from the U.S. 

Geological Survey's modular three-dimensional finitedifference ground-water flow model: U.S. Geological 

Survey Water-Resources Investigations Report 98-564, 

57 p.

Hanson, R.T., Li, Zhen., and Faunt, C. C., 2003, Application 

of the multi-node well package to the simulation of regionalaquifer systems in the Santa Clara Valley, California—

MODFLOW and More 2003: Understanding through 

Modeling—Conference Proceedings, International Ground 

Water Modeling Center, Golden, Colorado, 

September 16–19, 2003, p. 74–78.

Hanson, R.T., Martin, P., and Koczot, K.M., 2002a, 

Simulation of ground-water/surface-water flow in the Santa 

Clara–Calleguas Basin, Ventura County, California: U.S. 

Geological Survey Water-Resources Investigations Report 

02- 4136, 214 p.

Hanson, R.T., Newhouse, M.W., Wentworth, C.M., Williams, 

C.F., Noce, T.E., and Bennett, M.J., 2002b, Santa Clara 

Valley Water District multi-aquifer monitoring-well site, 

Coyote Creek Outdoor Classroom, San Jose, California: 

U.S. Geological Survey Open-File Report 02-369, 4 p.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and Anderman, E.R., 

2000a, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model-user guide to observation, 

sensitivity, and parameter-estimation processes and three 

post-processing programs: U.S. Geological Survey OpenFile Report 00-184, 209 p.
References Cited 73

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000b, MODFLOW-2000, the U.S. Geological 

Survey modular ground-water model—user guide to 

modularization concepts and the ground-water flow process: 

U.S. Geological Survey Open-File Report 00-92, 121 p.

Harbaugh, A.W., and McDonald M.G., 1996, User's 

documentation for MODFLOW-96, an update to the U.S. 

Geological Survey modular finite-difference ground-water 

flow model: U.S. Geological Survey Open-File Report 

96-485, 56 p.

Helm, D.C., 1975, One-dimensional simulation of compaction 

near Pixley, California, 1. constant parameters: Water 

Resources Research, v. 11, no. 3, p. 465–478.

________ 1977, Estimating parameters of compacting finegrained interbeds within a confined aquifer system by a onedimensional simulation of field observations: International 

Association of Hydrological Sciences, International 

Symposium on Land Subsidence, 2d, Anaheim, California, 

December 1976, Publication 121, p.145–156.

__________1978, Field verification of a one-dimensional 

mathematical model for transient compaction and expansion 

of a confined aquifer system, in Verification of mathematical 

and physical models of hydraulic engineering: American 

Society of Civil Engineers, Proceedings of Specialty 

Conference, College Park, Maryland, p. 189–195.

Hevesi, J.A., Flint, A.L., and Flint, L.E., 2002, Preliminary 

estimates of spatially distributed net infiltration and recharge 

for the Death Valley region, Nevada–California: U.S. 

Geological Survey Water-Resources Investigations Report 

02-4010, 36 p.

Hitchcock, C.S., and Kelson, K.I., 1999, Growth of late 

Quaternary folds in southwest Santa Clara valley, San 

Francisco Bay area, California—Implications of triggered 

slip for seismic hazard and earthquake recurrence: Geology, 

v. 27, no. 5, p. 391–394.

Hitchcock, C.S., Kelson, K.I., and Thompson, S.C., 1994, 

Geomorphic investigations of deformation along the 

northeastern margin of the Santa Cruz Mountains: U.S. 

Geological Survey Open File Report 94-187, map scale 

1:24,000.

Holzer, T.L., 1981, Preconsolidation stress of aquifer systems 

in areas of induced land subsidence: Water Resources 

Research, v. 17, no. 3, p. 693–704.

Hsieh, P.A., and Freckleton, J.R., 1993, Documentation of a 

computer program to simulate horizontal-flow barriers using 

the U.S. Geological Survey's modular three-dimensional 

finite- difference ground-water flow model: U.S. Geological 

Survey Open-File Report 92-477, 32 p.

Ireland, R.L., Poland, J.F., and Riley, F.S., 1984, Land 

subsidence in the San Joaquin Valley, California, as of 1980: 

U.S. Geological Survey Professional Paper 437-I, 

93 p.

Iwamura, T.I., 1980, Saltwater intrusion in the Santa Clara 

County Baylands area, California: Santa Clara Valley Water 

District Report, 115 p.

__________ 1995, Hydrogeology of the Santa Clara and 

Coyote Valleys ground water basins, California, in

Sangines, E.S., Anderson, D.A., and Busing, A.V., eds., 

Recent geologic studies of the San Francisco Bay area: 

Pacific Section of the Society of Economic Paleontologists 

and Mineralogists, v. 76, p. 173–192.

Izbicki, J.A., Christensen, A.H., and Hanson, R.T., 1999, U.S. 

Geological Survey combined well-bore flow and depthdependent water sampler: U.S. Geological Survey Fact 

Sheet 196-99, 2 p. 

Jachens, R.C., Wentworth, C.M., Gautier, D.L., and Pack, S., 

2001, 3-D geologic maps and visualization—A new 

approach to the geology of the Santa Clara (Silicon) Valley, 

California: U.S. Geological Survey Open-File Report 

01-223, 10 p.

Jachens, R.C., Wentworth, C.M., Graymer, R.W., McLaughlin, 

R.J., and Chuang, F.C., 2002, A 40-km-long concealed basin 

suggests large offset on the Silver Creek fault, Santa Clara 

Valley, California: Geological Society of America Abstracts 

with Programs, v. 34, no. 5, p. A99.

Jaimes, Luis, C., 1998, Groundwater elevation monitoring 

network, Santa Clara Valley groundwater basin: Santa Clara 

Valley Water District 1998, 35 p.

Jennings, C.W., 1985, An explanatory text to accompany the 

1:750,000 scale fault and geologic maps of California: 

California Department of Conservation, Division of Mines 

and Geology, Bulletin 201, 197 p.

__________ 1994, Fault activity map of California and 

adjacent areas, with locations and ages of recent volcanic 

eruptions: California Department of Conservation, Division 

of Mines and Geology, Bulletin 201, 92 p.

Johnson, N.M., 1995a, Characterization of alluvial 

hydrostratigraphy with indicator semivariograms: Water 

Resources Research, v. 31, no. 12, p. 3217–3227.

_________ 1995b, Deterministic and stochastic approaches for 

evaluating multiple scales of Santa Clara Valley 

hydrostratigraphy, in Sangines, E.M., Anderson, D.W., and 

Buising, A.B., eds., 1995, Recent geologic studies in the San 

Francisco Bay area: Pacific Section of the Society of 

Economic Paleontologists and Mineralogists, v. 76, 

p. 193–208.

Johnson, N.M., and Dreiss, S.J., 1989, Hydrostratigraphic 

interpretation using indicator geostatistics: Water Resources 

Research, v. 25, no.12, p. 2501–2510.

Koltermann, C.E., and Gorelick, S.M., 1992, Paleoclimatic 

signature in terrestrial flood deposits: Science, v. 256, 

p. 1775–1781.

Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, C.M., 

Helley, E.J., Nicholson, R.S., Wright, H.M., and Brown, 

K.M., 2000, Preliminary maps of Quaternary deposits and 

liquefaction susceptibility, nine-county San Francisco Bay 

region, California— a digital database: U.S. Geological 

Survey Open File Report 00-444, version 1.
74 Documentation of the Santa Clara Valley Regional Ground-Water/Surface-Water Flow Model, Santa Clara County, California

Leake, S.A., and Prudic, D.E., 1991, Documentation of a 

computer program to simulate aquifer-system compaction 

using the modular finite-difference ground-water flow 

model: U.S. Geological Survey Techniques of WaterResources Investigations, book 6, chap. A2, 68 p.

Leighton, D.A., Fio, J.L., and Metzger, L.F., 1994, Database of 

well and areal data, South San Francisco Bay and Peninsula 

area, California: U.S. Geological Survey Water-Resources 

Investigations Report 94-4151, 47 p.

Majumdar, Hiren, Gomez, M.J., McGarry, T.L., and Haines, 

D.A., 1977, District groundwater recharge facilities: Santa 

Clara Valley Water District 1977, 110 p.

Mantua, N., and Steven H., 2002, The Pacific Decadal 

Oscillation: Journal of Oceanography, v. 58, no.1, p. 35–44.

McDonald, M. G., 1986, Development of a multi-aquifer well 

option for a modular groundwater flow model, in

Khanbilvardi, R.M., and Fillos, J., eds., Groundwater 

hydrology, contamination, and remediation: Washington, 

D.C., Scientific Publications, p. 383–398.

McDonald, M.G., and Harbaugh, A.W., 1988, A modular 

three-dimensional finite-difference ground-water flow 

model: Techniques of Water-Resources Investigations of 

the U.S. Geological Survey, book 6, chap. A1, 586 p.

Metzger, L.F., 2002, Streamflow gains and losses along San 

Francisquito Creek and characterization of surface-water 

and ground-water quality, southern San Mateo and northern 

Santa Clara Counties, California, 1996–97: U.S. Geological 

Survey Water-Resources Investigations Report 02-4078, 

49 p.

Muir, K.S., and Coplen, T.B., 1981, Tracing ground-water 

movement by using the stable isotopes of oxygen and 

hydrogen, upper Penitencia Creek alluvial fan, Santa Clara 

Valley, California: U.S. Geological Survey Water-Supply 

Paper 2075, 18 p.

Oliver, H.W., 1990, Preliminary ground-water-quality data 

and the extent of the ground-water basin from drill-hole, 

seismic, and gravity data in the Palo Alto 7.5' quadrangle, 

California: U.S. Geological Survey Open-File Report 90-74, 

maps at scale 1:24,000.

Page, B.E., 1993, Geologic map of the Stanford lands and 

vicinity: Stanford Geological Survey, Palo Alto, California, 

Stanford University.

Pampeyan, E.H., 1970, Geologic map of the Palo Alto 7-1/2-

minute quadrangle, San Mateo and Santa Clara Counties, 

California: U.S. Geological Survey Open-File Map, scale 

1:12,000.

__________ 1979, Preliminary map showing recency of 

faulting in coastal north-central California: U.S. Geological 

Survey Miscellaneous Field Studies Map MF-1070, scale 

1:250,000.

__________ 1993, Geologic map of the Palo Alto and part of 

the Redwood Point 7-1/2' quadrangles, San Mateo and Santa 

Clara Counties, California: U.S. Geological Survey 

Miscellaneous Investigation Series Map I-2371, scale 

1:24,000.

Poland, J.F., 1971, Land subsidence in the Santa Clara Valley, 

Alameda, San Mateo, and Santa Clara Counties, California: 

U.S. Geological Survey Open-File Report, Map Scale 

1:125,000 [This precedes the time when open files were 

assigned numbers. Also released within jacket labeled “San 

Francisco Bay Region Environment and Resources 

Planning Study Technical Report 2."]

Poland, J.F., and Ireland, R.L., 1988, Land subsidence in the 

Santa Clara Valley, California, as of 1982: U.S. Geological 

Survey Professional Paper 497-F, 61 p.

Prudic, D.E., 1989, Documentation of a computer program to 

simulate stream-aquifer relations using a modular, finitedifference, ground-water flow model: U.S. Geological 

Survey Open-File Report 88-729, 113 p.

Reichard, E.G., and Bredehoeft, J.D., 1984, An engineering 

economic analysis of a program for artificial groundwater 

recharge: Water Resources Bulletin, v. 20, no. 6, 

p. 929–939.

Reichard, E.G., Land, M., Crawford, S.W., Johnson, T., 

Everett, R.R., Kulshan, T.V., Ponti, D.J., Halford, K.J., 

Johnson, T.A., Paybins, K.S., and Nishikawa, T., 2003, 

Geohydrology, geochemistry, and ground-water simulationoptimization of the central and west coast basins, Los 

Angeles County, California: U.S. Geological Survey WaterResources Investigations Report 03-4065, 184 p.

Schmidt, D.A., 2002, The kinematics of faults in the San 

Francisco Bay area inferred from geodetic and seismic data: 

unpublished Ph.D. dissertation, University of California at 

Berkeley, 200 p.

Stamos, C. L., Martin, P., Nishikawa, T., and Cox, B.F., 2001, 

Simulation of ground-water flow in the Mojave River Basin, 

California: U.S. Geological Survey Water-Resources 

Investigations Report 01-4002, 129 p.

Stanley, R.G., Jachens, R.C., Lillis, P.G., McLaughlin, R.J., 

Kvenvolden, K.A., Hostettler, F.D., McDougall, K.A., and 

Magoon, L.B., 2002, Subsurface and petroleum geology of 

the southwestern Santa Clara Valley (“Silicon Valley”), 

California: U.S. Geological Survey Professional Paper 

1663, 55 p.

Tolman, C.F., and Poland J.F., 1940, Ground-water, salt-water 

infiltration, and ground-surface recession in Santa Clara 

Valley, Santa Clara County, California: Transactions of the 

American Geophysical Union Fall Conference, 1940, 

p. 23–35. 

U. S. Census Bureau, 2003, 

http://quickfacts.census.gov/qfd/states/06/06085.html, 

accessed July 8, 2003.

Wagner, D.L., Bortugno, K.J., and McJunkin, R.D., 1990, 

Geologic map of the San Francisco–San Jose quadrangle: 

California Department of Conservation, Division of Mines 

and Geology, Regional Geologic Map Series, Map No. 5A, 

5 sheets.

Wentworth C.M., 1993, General distribution of geologic 

materials in the San Francisco Bay region, California— a 

digital map database: U.S. Geological Survey Open File 

Report 93-693, 10 p. 
References Cited 75

__________ 1997, General distribution of geologic materials 

in the San Francisco Bay region, California—a digital map 

database: U.S. Geological Survey Open-File Report 97-744. 

Wentworth, C.M., Blake, M.C., Jr., McLaughlin, R.J., and 

Graymer, R.W., 1998, Preliminary geologic map of the San 

Jose 30 X 60-minute quadrangle, California— a digital 

database: U.S. Geological Survey Open-File Report 98-795.

Wentworth, C.M., Hanson, R.T., Jachens, R.C., Langenheim, 

V.E., McLaughlin, R.J., Phelps, Geoffrey, Simpson, R.W., 

Stanley, R.G., and Williams, R.A., 2003a, Varied evidence 

for a blind thrust beneath the southwestern Santa Clara 

(Silicon) Valley, California: Geological Society of America, 

National Conference Abstracts with Programs, November 

2–5, Seattle, Washington, p. 74.

Wentworth, C.M., Hanson, R.T., Newhouse, Mark, Jachens, 

R.C., Mankinen, E.A., Phelps, Geoffrey, Tinsley, J.C., 

Williams, C.F., Williams, R.A., Andersen, D.W., and 

Metzger, E.P., 2003b, Stratigraphy and hydrogeology of the 

Santa Clara Valley, San Francisco Bay region, California— 

a progress report: American Association of Petroleum 

Geologists, Pacific Section, Conference Program and 

Abstracts, May 19–24, Long Beach, California, p. 94.

Williams, R.A., Stephenson, W.J., Wentworth, C.M., Odum, 

J.K., Hanson, R.T., and Jachens, R.C., 2002, Definition of 

the Silver Creek Fault and Evergreen Basin sediments from 

seismic reflection data, San Jose, California: Transactions of 

the American Geophysical Union Fall Conference, 

December 2002, v. 83, no. 47.

Wilson, A.M., 1993, Evaluation of pumping strategies for 

managing land subsidence in the Santa Clara Valley, 

California: unpublished Master's thesis for Department of 

Applied Earth Sciences, Palo Alto, California, Stanford 

University, 90 p. 

Zimmerman, D.A., Hanson, R.T., and Davis, P.A., 1991, A 

comparison of parameter estimation and sensitivity analysis 

techniques and their impact on the uncertainty in ground 

water flow model predictions: U.S. Nuclear Regulatory 

Commission NUREG/CR-5522 (Sandia National 

Laboratories SAND90-0128) [variously paged].