U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the California State Water Resources Control Board

A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program

Status and Understanding of Groundwater Quality in the MaderaChowchilla Study Unit, 2008: California GAMA Priority Basin Project

Photo placement

Scientific Investigations Report 2012–5094
Front Cover Map: Groundwater basins categorized by sampling priority. Location of groundwater basin 

boundaries from California Department of Water Resources (CDWR, 2003).

Cover photographs:

Front cover: Well in Madera County, California (photograph taken by Mike Solt, U.S. Geological Survey.)

Back cover: View looking east from sampled well located northeast of Chowchilla, California (photograph 

taken by Jennifer Shelton, U.S. Geological Survey.) 

Sampling priority

Study area

Low-use basins

Priority basins

Areas that are outside CDWR-defined

 groundwater basins
Status and Understanding of Groundwater 

Quality in the Madera-Chowchilla Study 

Unit, 2008: California GAMA Priority 

Basin Project

By Jennifer L. Shelton, Miranda S. Fram, Kenneth Belitz, and Bryant C. Jurgens

A product of the California Groundwater Ambient Monitoring and Assessment 

(GAMA) Program

Prepared in cooperation with the California State Water Resources Control Board

Scientific Investigations Report 2012–5094

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2013

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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:

Shelton, J.L., Fram, M.S., Belitz, Kenneth, and Jurgens, B.C., 2013, Status and understanding of groundwater 

quality in the Madera-Chowchilla Study Unit, 2008—California GAMA Priority Basin Project: U.S. Geological Survey 

Scientific Investigations Report 2012–5094, 86 p.
iii

Contents

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

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

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

Hydrogeologic Setting ..................................................................................................................................5

Methods.........................................................................................................................................................12

Status Assessment.............................................................................................................................12

Relative-Concentrations and Water-Quality Benchmarks .................................................12

Datasets for Status Assessment.............................................................................................13

Grid Wells....................................................................................................................................13

Additional Data Used for Spatially Weighted Calculation .................................................13

Identification of Constituents for Additional Evaluation in the Status Assessment.......15

Calculation of Aquifer-Scale Proportions..............................................................................19

Statistical Analysis ....................................................................................................................20

Potential Explanatory Factors....................................................................................................................20

Land Use...............................................................................................................................................20

Depth, Position Relative to the Corcoran Clay, and Lateral Position ........................................21

Groundwater Age ...............................................................................................................................21

Geochemical Conditions....................................................................................................................25

Correlations Between Explanatory Variables ................................................................................27

Status and Understanding of Water Quality ...........................................................................................29

Inorganic Constituents.......................................................................................................................29

Nutrients......................................................................................................................................33

Factors Affecting Nitrate.................................................................................................33

Trace Elements...........................................................................................................................41

Factors Affecting Arsenic ...............................................................................................45

Factors Affecting Vanadium............................................................................................46

Radioactive Constituents..........................................................................................................46

Factors Affecting Uranium and Gross Alpha Particle Activity..................................47

Constituents with SMCL Benchmarks.............................................................................................49

Factors Affecting Total Dissolved Solids ......................................................................49

Factors Affecting Manganese........................................................................................53

Organic and Special-Interest Constituents....................................................................................53

Pesticides....................................................................................................................................53

Factors Affecting Herbicides..........................................................................................56

Fumigants....................................................................................................................................56

Factors Affecting Fumigants...........................................................................................62

Other Volatile Organic Compounds.........................................................................................62

Special-Interest Constituents..................................................................................................64

Factors Affecting Perchlorate ........................................................................................64
iv

Figures

Figure 1. Map showing locations of the Madera-Chowchilla California Groundwater

Ambient Monitoring and Assessment (GAMA) study unit and the California

hydrogeologic provinces .................................................................. 4

Figure 2. Map showing geographic features and locations of grid cells, grid and

understanding wells sampled during April–May 2008, and wells with data in

the California Department of Public Health database during February

2005–February 2008, Madera-Chowchilla study unit, California GAMA Priority

Basin Project................................................................................. 6

Figure 3. Hydrogeologic map of the Madera-Chowchilla study unit, California GAMA

Priority Basin Project........................................................................ 7

Figure 4. Conceptual diagram of regional lateral groundwater flow and vertical flow

influenced by agricultural practices and natural discharge zones for the

aquifer system of the Madera-Chowchilla study unit, California GAMA Priority

Basin Project................................................................................. 9

Figure 5. Ternary diagrams showing percentages of urban, agricultural, and natural

land uses for the study unit and the areas surrounding individual wells,

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project....... 10

Figure 6. Map showing land use of the Madera-Chowchilla study unit and locations of

grid and understanding wells sampled during April–May 2008, and wells with

data in the California Department of Public Health database during February

2005–February 2008, Madera-Chowchilla study unit, California GAMA Priority

Basin Project................................................................................. 11

Figure 7. Boxplots showing well depth, depth to top of perforations, and perforation

lengths for grid and understanding wells, Madera-Chowchilla study unit, 2008,

California GAMA Priority Basin Project................................................... 22

Figure 8. Distribution of wells plotted on visualization of normalized lateral positions

from eastern margin of valley and the distribution of wells across the range of

normalized lateral position values, Madera-Chowchilla study unit, 2008,

California GAMA Priority Basin Project................................................... 23

Figure 9. Boxplots showing relation of classified groundwater age to well depth and

depth to top of perforation, Madera-Chowchilla study unit, 2008, California

GAMA Priority Basin Project............................................................... 24

Figure 10. Bar chart showing groundwater age distributions in depth classes,

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project ...... 25

Figure 11. Cross sections showing relations of dissolved oxygen, pH, and fraction of

calcium+magnesium in total cations to lateral position and depth of perforated

interval of wells, Madera-Chowchilla study unit, 2008, California GAMA Priority

Basin Project................................................................................. 26

Summary .......................................................................................................................................................64

Acknowledgments.......................................................................................................................................66

References Cited..........................................................................................................................................66

Appendix A. Ancillary Datasets ................................................................................................................73

Appendix B. Comparison of CDPH and USGS-GAMA Data..................................................................81

Contents—Continued
v

Figures—Continued

Figure 12. Dot plot showing maximum relative-concentrations of constituents detected in

grid wells, by type of constituent, in the Madera-Chowchilla study unit, 2008,

California GAMA Priority Basin Project................................................... 31

Figure 13. Dot plots showing relative-concentrations of selected nutrients, trace

elements, radioactive constituents, and inorganic constituents with secondary

maximum contaminant levels detected in grid wells, Madera-Chowchilla study

unit, 2008, California GAMA Priority Basin Project .................................... 32

Figure 14. Map showing concentrations of nitrate, as nitrogen, in USGS-GAMA wells and

the most recent analysis during February 12, 2005–February 12, 2008, for CDPH

wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project...... 37

Figure 15. Scatterplots showing relation between concentrations of nitrate, arsenic,

vanadium, uranium activity, and total dissolved solids with depth to top of

perforations in wells, Madera-Chowchilla study unit, 2008, California GAMA

Priority Basin Project........................................................................ 40

Figure 16. Scatterplots showing relations of nitrate, as nitrogen concentration, and

dissolved oxygen concentration, and nitrate, as nitrogen concentration, and

total dissolved solids, Madera-Chowchilla study unit, 2008, California GAMA

Priority Basin Project........................................................................ 41

Figure 17. Map showing concentrations of arsenic in USGS-GAMA wells and the most

recent analysis during February 12, 2005– February 12, 2008, for CDPH wells,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 42

Figure 18. Map showing concentrations of vanadium in USGS-GAMA wells and the most

recent analysis during February 12, 2005–February 12, 2008, for CDPH wells,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 43

Figure 19. Map showing concentrations of barium in USGS-GAMA wells and the most

recent analysis during February 12, 2005– February 12, 2008, for CDPH wells,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 44

Figure 20. Scatterplot showing relations of dissolved oxygen and pH values to arsenic

concentration and distance from Chowchilla River, Madera-Chowchilla study

unit, 2008, California GAMA Priority Basin Project .................................... 46

Figure 21. Map showing aof uranium in USGS-GAMA wells and the most recent analysis

during February 12, 2005–February 12, 2008, for CDPH wells,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 48

Figure 22. Scatterplot showing relation of bicarbonate concentrations and uranium

activities, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin

Project ....................................................................................... 49

Figure 23. Map showing concentrations of total dissolved solids (TDS) in USGS-GAMA

wells and the most recent analysis during February 12, 2005–February 12, 2008,

for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin

Project ....................................................................................... 50

Figure 24. Piper diagram showing major-ion composition and total dissolved solids

concentrations for groundwater samples from grid and understanding wells,

2008, Madera-Chowchilla study unit, California GAMA Priority Basin Project ...... 52

Figure 25. Dot plots showing detection frequency and maximum relative-concentrations

for organic and special-interest constituents detected in grid wells, 2008,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 54
vi

Figure 26. Graph showing detection frequency and relative-concentrations of selected

organic and special-interest constituents in grid wells, 2008,

Madera-Chowchilla study unit, California GAMA Priority Basin Project ............ 55

Figure 27. Maps showing maximum relative-concentrations of selected constituents in

organic constituent classes and perchlorate in USGS-GAMA wells and the

most recent analysis during February 12, 2005–February 12, 2008, for CDPH

wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project:

herbicides, fumigants, trihalomethanes, solvents, and perchlorate .................. 57

Figure 28. Scatterplots showing relations of herbicide, fumigant, trihalomethane, solvent,

and perchlorate total concentrations with depth to top of perforations in wells,

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project ...... 63

Figures—Continued

Tables

Table 1. Summary of number of wells and constituents by sampling schedule and

analyte group, Madera-Chowchilla study unit, 2008, California GAMA Priority

Basin Project................................................................................. 14

Table 2. Comparison of number of constituents analyzed and median method detection

levels or laboratory reporting levels by type of constituent for data reported in

the California Department of Public Health database and for data collected by

the U.S. Geological Survey (USGS) for the Madera-Chowchilla study unit, 2008,

California GAMA Priority Basin Project................................................... 15

Table 3. Benchmark type and value for constituents selected for additional evaluation

in the status assessment of groundwater quality in the Madera-Chowchilla

study unit, 2008, California GAMA Priority Basin Project .............................. 16

Table 4. Constituents detected in samples collected, but not selected for additional

evaluation in the status assessment for the Madera-Chowchilla study unit,

2008, California GAMA Priority Basin Project .......................................... 17

Table 5. Constituents historically reported at high relative-concentrations in the

California Department of Public Health database for the Madera-Chowchilla

study unit, 2008, California GAMA Priority Basin Project .............................. 18
vii

Tables—Continued

Table 6A. Results of Wilcoxon rank-sum tests for differences in values of selected

potential explanatory factors between samples classified into groups by

position relative to the Corcoran Clay, groundwater age, or well depth,

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project ...... 28

Table 6B. Results of Spearman’s tests of correlations between selected potential

explanatory factors, Madera-Chowchilla study unit, 2008, California GAMA

Priority Basin Project........................................................................ 29

Table 7A. Number of inorganic constituents analyzed and detected, by benchmark type

and constituent type, Madera-Chowchilla study unit, 2008, California GAMA

Priority Basin Project........................................................................ 30

Table 7B. Number of organic and special-interest constituents analyzed and detected,

by health-based benchmark type and constituent type, Madera-Chowchilla

study unit, 2008, California GAMA Priority Basin Project .............................. 30

Table 8. Aquifer-scale proportions using grid-based and spatially weighted methods for

those constituents that met criteria for additional evaluation in the status

assessment, Madera-Chowchilla study unit, 2008, California GAMA Priority

Basin Project................................................................................. 34

Table 9A. Aquifer-scale proportions for inorganic constituent classes,

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project ...... 36

Table 9B. Aquifer-scale proportions for organic constituent classes, Madera-Chowchilla

study unit, 2008, California GAMA Priority Basin Project .............................. 36

Table 10A. Results of Wilcoxon rank-sum tests for differences in values of water-quality

constituents between samples classified into groups by position relative to the

Corcoran Clay, groundwater age, or well depth, Madera-Chowchilla study unit,

2008, California GAMA Priority Basin Project .......................................... 38

Table 10B. Results of Spearman’s tests of correlations between selected potential

explanatory factors and water-quality constituents, Madera-Chowchilla study

unit, 2008, California GAMA Priority Basin Project .................................... 39
viii

Conversion Factors, Datums, and Abbreviations and 

Acronyms

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Radioactivity

picocurie per liter (pCi/L) 0.037 becquerel per liter (Bq/L) 

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

°F=(1.8×°C)+32

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

°C=(°F-32)/1.8

Datums

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

(NAVD 88).

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

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

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 

25 °C).

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

or micrograms per liter (μg/L).
ix

Abbreviations and Acronyms

AB Assembly Bill (through the California State Assembly)

AL-US U.S. Environmental Protection Agency action level

BQ benchmark quotient

Fract-CaMg calcium plus magnesium in milliequivalents divided by the sum of calcium, 

magnesium, sodium, and potassium in milliequivalents

GAMA Groundwater Ambient Monitoring and Assessment Program

HAL-US U.S. Environmental Protection Agency lifetime health advisory level

HBSL health-based screening level

MADCHOW prefix for Madera-Chowchilla study unit grid well

MADCHOWFP prefix for Madera-Chowchilla study unit understanding well

MCL-US U.S. Environmental Protection Agency maximum contaminant level

NL-CA California Department of Public Health notification level

pmc percent modern carbon

redox oxidation-reduction

RC relative-concentration

RSD5-US U.S. Environmental Protection Agency risk-specific dose at risk factor of 10–5

SMCL secondary maximum contaminant level

SMCL-CA California Department of Public Health secondary maximum contaminant level

SMCL-US U.S. Environmental Protection Agency secondary maximum contaminant level

TEAP terminal electron acceptor processes

U.S. United States

Organizations

CDPH California Department of Public Health (was California Department of Health 

Services prior to July 1, 2007)

CDWR California Department of Water Resources

LLNL Lawrence Livermore National Laboratory

NAWQA National Water-Quality Assessment Program (USGS)

SWRCB State Water Resources Control Board (California)

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

Conversion Factors, Datums, and Abbreviations and 

Acronyms—Continued
x

Conversion Factors, Datums, and Abbreviations and 

Acronyms—Continued

Selected Chemical Names

14C carbon-14

DO dissolved oxygen

DBCP 1,2-dibromo-3-chloropropane

EDB 1,2-dibromoethane

D-D dichloropropane-dichloropropene mixture

He helium

3He helium-3

4He helium-4

NDMA N-nitrosodimethylamine

PCE tetrachloroethene

1,2,3-TCP 1,2,3-trichloropropane

TDS total dissolved solids

THM trihalomethane

3H tritium

VOC volatile organic compound

Units of Measure

cm3 STP g–1 centimeters at standard temperature and pressure per gram

L liter

mg/L milligrams per liter (parts per million)

μg/L micrograms per liter (parts per billion)

μS/cm microsiemens per centimeter

per mil parts per thousand

ppb parts per billion

TU tritium unit

> greater than

≥ greater than or equal to

< less than

≤ less than or equal to

– not detected

% percent
Status and Understanding of Groundwater Quality in the 

Madera-Chowchilla Study Unit, 2008: California GAMA 

Priority Basin Project

By Jennifer L. Shelton, Miranda S. Fram, Kenneth Belitz, and Bryant C. Jurgens

Abstract

Groundwater quality in the approximately 860-squaremile Madera and Chowchilla Subbasins (Madera-Chowchilla 

study unit) of the San Joaquin Valley Basin was investigated 

as part of the Priority Basin Project of the Groundwater 

Ambient Monitoring and Assessment (GAMA) Program. The 

study unit is located in California’s Central Valley region in 

parts of Madera, Merced, and Fresno Counties. The GAMA 

Priority Basin Project is being conducted by the California 

State Water Resources Control Board in collaboration with the 

U.S. Geological Survey (USGS) and the Lawrence Livermore 

National Laboratory. The Project was designed to provide 

statistically robust assessments of untreated groundwater 

quality within the primary aquifer systems in California. 

The primary aquifer system within each study unit is defined 

by the depth of the perforated or open intervals of the wells 

listed in the California Department of Public Health (CDPH) 

database of wells used for municipal and community drinkingwater supply. The quality of groundwater in shallower or 

deeper water-bearing zones may differ from that in the 

primary aquifer system; shallower groundwater may be more 

vulnerable to contamination from the surface.

The assessments for the Madera-Chowchilla study unit 

were based on water-quality and ancillary data collected 

by the USGS from 35 wells during April–May 2008 and 

water-quality data reported in the CDPH database. Two 

types of assessments were made: (1) status, assessment of 

the current quality of the groundwater resource, and (2) 

understanding, identification of natural factors and human 

activities affecting groundwater quality. The primary aquifer 

system is represented by the grid wells, of which 90 percent 

(%) had depths that ranged from about 200 to 800 feet (ft) 

below land surface and had depths to the top of perforations 

that ranged from about 140 to 400 ft below land surface.

Relative-concentrations (sample concentrations divided 

by benchmark concentrations) were used for evaluating 

groundwater quality for those constituents that have Federal 

or California regulatory or non-regulatory benchmarks for 

drinking-water quality. A relative-concentration (RC) greater 

than 1.0 indicates a concentration above a benchmark. RCs 

for organic constituents (volatile organic compounds and 

pesticides) and special-interest constituents (perchlorate) were 

classified as “high” (RC is greater than 1.0), “moderate” (RC 

is less than or equal to 1.0 and greater than 0.1), or “low” (RC 

is less than or equal to 0.1). For inorganic constituents (major 

and minor ions, trace elements, nutrients, and radioactive 

constituents), the boundary between low and moderate 

RCs was set at 0.5. The assessments characterize untreated 

groundwater quality, not the quality of treated drinking water 

delivered to consumers by water purveyors; drinking-water 

benchmarks, and thus relative-concentrations, are used 

to provide context for the concentrations of constituents 

measured in groundwater.

Aquifer-scale proportion was used in the status 

assessment as the primary metric for evaluating regional-scale 

groundwater quality. High aquifer-scale proportion is defined 

as the percentage of the area of the primary aquifer system 

with RCs greater than 1.0 for a particular constituent or class 

of constituents; moderate and low aquifer-scale proportions 

are defined as the percentages of the area of the primary 

aquifer system with moderate and low RCs, respectively. 

Percentages are based on an areal, rather than a volumetric 

basis. Two statistical approaches—grid-based, which used 

one value per grid cell, and spatially weighted, which used 

multiple values per grid cell—were used to calculate aquiferscale proportions for individual constituents and classes of 

constituents. The spatially weighted estimates of high aquiferscale proportions were within the 90% confidence intervals of 

the grid-based estimates for all constituents except iron. 
2 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

The status assessment showed that inorganic constituents 

had greater high and moderate aquifer-scale proportions in the 

Madera-Chowchilla study unit than did organic constituents. 

RCs for inorganic constituents with health-based benchmarks 

were high in 37% of the primary aquifer system, moderate in 

30%, and low in 33%. The inorganic constituents contributing 

most to the high aquifer-scale proportion were arsenic 

(13%), uranium (17%), gross alpha particle activity (20%), 

nitrate (6.7%), and vanadium (3.3%). RCs for inorganic 

constituents with non-health-based benchmarks were high 

in 6.7% of the primary aquifer system, and the constituent 

contributing most to the high aquifer-scale proportion was 

total dissolved solids (TDS). RCs for organic constituents 

with health-based benchmarks were high in 10% of the 

primary aquifer system, moderate in 3.3%, and low in 40%; 

organic constituents were not detected in 47% of the primary 

aquifer system. The fumigant 1,2-dibromo-3-chloropropane 

(DBCP) was the only organic constituent detected at high 

RCs. Seven organic constituents were detected in 10% or 

more of the primary aquifer system: DBCP; the fumigant 

additive 1,2,3-trichloropropane; the herbicides simazine, 

atrazine, and diuron; the trihalomethane chloroform; and the 

solvent tetrachloroethene (PCE). RCs for the special-interest 

constituent perchlorate were moderate in 20% of the primary 

aquifer system.

The second component of this study, the understanding 

assessment, identified the natural and human factors that 

may affect groundwater quality by evaluating statistical 

correlations between water-quality constituents and potential 

explanatory factors, such as land use, position relative to 

important geologic features, groundwater age, well depth, 

and geochemical conditions in the aquifer. Results of the 

statistical evaluations were used to explain the distribution of 

constituents in the study unit. Depth to the top of perforations 

in the well and groundwater age were the most important 

explanatory factors for many constituents. High and moderate 

RCs of nitrate, uranium, and TDS and the presence of 

herbicides, trihalomethanes, and solvents were all associated 

with depths to the top of perforations less than 235 ft and 

modern- and mixed-age groundwater. Positive correlations 

between uranium, bicarbonate, TDS, and the proportion 

of calcium and magnesium in the total cations suggest that 

downward movement of recharge from irrigation water 

contributed to the elevated concentrations of these constituents 

in the primary aquifer system. High and moderate RCs of 

arsenic were associated with depths to the top of perforations 

greater than 235 ft, mixed- and pre-modern-age groundwater, 

and location in sediments from the Chowchilla River alluvial 

fan, suggesting that increased residence time and appropriate 

aquifer materials were needed for arsenic to accumulate in 

the groundwater. High and moderate RCs of fumigants were 

associated with depths to the top of perforations of less than 

235 ft and location south of the city of Madera; low RCs of 

fumigants were detected in wells dispersed across the study 

unit with a range of depths to top of perforations.

Introduction 

Groundwater composes nearly half of the water used 

for public and domestic drinking-water supply in California 

(Kenny and others, 2009). To assess the quality of ambient 

groundwater in aquifers used for drinking-water supply 

and to establish a baseline groundwater quality monitoring 

program, the California State Water Resources Control Board 

(SWRCB), in collaboration with the U.S. Geological Survey 

(USGS) and Lawrence Livermore National Laboratory 

(LLNL), implemented the Groundwater Ambient Monitoring 

and Assessment (GAMA) Program (California State Water 

Resources Control Board, 2010, website at http://www.swrcb.

ca.gov/gama/). The statewide GAMA Program currently 

consists of four projects: (1) the GAMA Priority Basin Project, 

conducted by the USGS (website at http://ca.water.usgs.gov/

gama/); (2) the GAMA Domestic Well Project, conducted 

by the SWRCB; (3) the GAMA Special Studies, conducted 

by LLNL; and (4) the GeoTracker GAMA online database, 

conducted by the SWRCB. On a statewide basis, the GAMA 

Priority Basin Project focused primarily on the deeper portion 

of the groundwater resource, and the SWRCB Domestic Well 

Project generally focused on the shallower aquifer systems.

The SWRCB initiated the GAMA Program in 2000 

in response to a legislative mandate (State of California, 

1999, 2001a, Supplemental Report of the 1999 Budget Act 

1999–00 Fiscal Year). The GAMA Priority Basin Project was 

initiated in response to the Groundwater Quality Monitoring 

Act of 2001 to assess and monitor the quality of groundwater 

in California (State of California, 2001b, Sections 

10780– 10782.3 of the California Water Code, Assembly Bill 

599). The GAMA Priority Basin Project is a comprehensive 

assessment of statewide groundwater quality designed to 

help better understand and identify risks to groundwater 

resources and to increase the availability of information 

about groundwater quality to the public. For the GAMA 

Priority Basin Project, the USGS, in collaboration with the 

SWRCB, developed a monitoring plan to assess groundwater 

basins through direct sampling of groundwater and other 

statistically reliable sampling approaches (Belitz and others, 

2003; California State Water Resources Control Board, 2003). 

Additional partners in the GAMA Priority Basin Assessment 

include the California Department of Public Health (CDPH), 

California Department of Pesticide Regulation (CDPR), 

California Department of Water Resources (CDWR), and 

local water agencies and well owners (Kulongoski and Belitz, 

2004).
Introduction 3

The range of hydrologic, geologic, and climatic 

conditions that exists in California must be considered in a 

statewide assessment of groundwater quality. Belitz and others 

(2003) partitioned the State into 10 hydrogeologic provinces, 

each with distinctive hydrologic, geologic, and climatic 

characteristics (fig. 1). All of these hydrogeologic provinces 

include groundwater basins and subbasins designated by 

the CDWR (California Department of Water Resources, 

2003). Groundwater basins generally consist of relatively 

permeable, unconsolidated deposits of alluvial or volcanic 

origin. Eighty percent of California’s approximately 16,000 

active and standby drinking-water wells listed in the statewide 

database maintained by the CDPH (hereinafter referred to as 

CDPH wells) are located in CDWR-designated groundwater 

basins within these hydrogeologic provinces. Groundwater 

basins and subbasins were prioritized for sampling on 

the basis of the number of CDPH wells in the basin, with 

secondary consideration given to municipal groundwater 

use, agricultural pumping, the number of historically leaking 

underground fuel tanks, and registered pesticide applications 

(Belitz and others, 2003). Of the 472 basins and subbasins 

designated by the CDWR, 116 priority basins, representing 

approximately 95 percent (%) of the CDPH wells located 

in basins, were selected for the project. Some areas outside 

of the defined groundwater basins were also included to 

represent the approximately 20% of CDPH wells not located 

in groundwater basins. The 116 priority basins and additional 

areas outside of the defined groundwater basins were grouped 

into 35 study units.

The goal of the GAMA Priority Basin Project is to 

produce three types of water-quality assessments for each 

study unit—(1) Status: assessment of the current quality of 

the groundwater resource, (2) Understanding: identification of 

the natural and human factors affecting groundwater quality, 

and (3) Trends: detection of changes in groundwater quality 

(Kulongoski and Belitz, 2004). The assessments are intended 

to characterize the quality of groundwater within the primary 

aquifer system of the study unit, not the treated drinking water 

delivered to consumers by water purveyors. The primary 

aquifer systems for the study units are defined by the depths 

of the perforated or open intervals of the wells listed in the 

CDPH databases for the study units. The CDPH database 

lists wells used for municipal and community drinkingwater supplies and includes wells from systems classified as 

non-transient (such as cities, towns, and mobile-home parks) 

and transient (such as schools, campgrounds, and restaurants). 

Groundwater quality in the primary aquifer system may differ 

from water in shallower or deeper parts of the aquifer systems. 

In particular, shallower groundwater may be more vulnerable 

to contamination from the land surface.

Purpose and Scope

The purposes of this report are to provide (1) a study 

unit description: briefly describe the hydrogeologic setting of 

the Madera-Chowchilla study unit, (2) a status assessment: 

assessment of the status of the current (2008) quality of 

groundwater in the primary aquifer system in the MaderaChowchilla study unit, and (3) an understanding assessment: 

identification of the natural and human factors affecting 

groundwater quality, and an explanation of the relations 

between water quality and selected explanatory factors. 

In the Madera-Chowchilla study unit, the primary aquifer 

system corresponds to a depth interval of approximately 

140 to 800 feet (ft) below land surface. Water-quality data 

for samples collected by the USGS for the GAMA Program 

in the Madera-Chowchilla study unit and details of sample 

collection, analysis, and quality-assurance procedures 

are described by Shelton and others (2009). Untreated 

groundwater samples were collected between April and 

May 2008. Utilizing those same data, this report describes 

methods used in designing the sampling network, identifying 

CDPH data for use in the status assessment, estimating 

aquifer-scale proportions for constituents, analyzing ancillary 

datasets, and assessing the status and understanding of 

groundwater quality by statistical and graphical approaches.

The status assessment uses two methods for calculating 

the areal proportion of the primary aquifer system with 

groundwater of defined quality (aquifer-scale proportion). 

Both methods are based on equal-area grid cells covering 

the study unit: one uses one well to represent each cell, and 

the other uses multiple wells to represent each cell. The first 

method is based on water-quality data from 30 wells selected 

by the USGS for spatial coverage of one well per grid cell 

across the study unit (grid wells). Samples were collected in 

April and May 2008 by the USGS for the GAMA Program 

for analysis of anthropogenic organic constituents, naturally 

occurring inorganic constituents, and geochemical and agedating tracers (Shelton and others, 2009). The resulting set 

of water-quality data from the 30 grid wells was considered 

to be representative of the primary aquifer system in the 

Madera-Chowchilla study unit. The second method uses 

the water-quality data from the grid wells, water-quality 

data from 5 additional wells sampled by the USGS for the 

GAMA Program (understanding wells), and data reported for 

wells in the CDPH database during the most recent 3 years 

available at the time of the USGS sampling for the GAMA 

Program. GAMA status assessments are designed to provide a 

statistically robust characterization of groundwater quality in 

the primary aquifer systems at the study-unit scale (Belitz and 

others, 2003). The statistically robust design also allows study 

units to be compared and results to be synthesized at regional 

and statewide scales.
4 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project Introduction 3

sac11-0401_fig 01

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

North American Datum of 1983 (NAD 83)

Provinces from Belitz and others (2003)

Klamath

Mountains

Cascades and

Modoc Plateau

Transverse Ranges and

selected Peninsular Ranges

Southern Coast

Ranges

Sierra

Nevada

Northern

Coast

Ranges

Desert

Central

Valley

Basin and Range

San Diego

Drainages

OREGON

NEVADA

MEXICO

ARIZONA

0 200 MILES

0 200 KILOMETERS

40

42 124 122 120 118 116 114

38

36

34

PA C I F I C O C E A N

Bakersfield

Los Angeles

San Diego

Redding

Sacramento

San

Francisco

San Joaquin

Valley

Sacramento Valley

Madera-Chowchilla

GAMA

Study Unit

Figure 1. Locations of the Madera-Chowchilla California Groundwater Ambient Monitoring and Assessment 

(GAMA) study unit and the California hydrogeologic provinces.
Hydrogeologic Setting 5

To provide context, the water-quality data discussed 

in this report are compared to California and Federal 

drinking-water regulatory and non-regulatory benchmarks 

for treated drinking water. Groundwater quality is defined in 

terms of relative-concentrations (the ratio of the concentration 

of a constituent in groundwater to the concentration of the 

benchmark for that constituent). The assessments in this report 

characterize the quality of untreated groundwater resources 

in the primary aquifer system in the study unit, not the treated 

drinking water delivered to consumers by water purveyors. 

This study does not attempt to evaluate the quality of water 

delivered to consumers; after withdrawal from the ground, 

water typically is treated, disinfected, and (or) blended with 

other waters to maintain acceptable water quality. Regulatory 

benchmarks apply to treated water that is delivered to the 

consumer, not to untreated groundwater.

The understanding assessment is based on water-quality 

data from the 30 grid wells and the 5 understanding wells 

sampled by the USGS for the GAMA Program. The potential 

explanatory factors affecting water quality in the primary 

aquifer system evaluated are land use, well depth, depth to 

the top of perforation, depth relative to the position of the 

Corcoran Clay, lateral position within the groundwater flow 

system, indicators of groundwater age, and geochemical 

conditions. Connections between potential explanatory factors 

and water quality are evaluated using statistical tests for 

correlations and by analysis of graphical relations.

Hydrogeologic Setting 

The southern two-thirds of the Central Valley 

Hydrogeologic Province consists of the San Joaquin Valley 

(fig. 1). The Madera-Chowchilla study unit is composed of 

two subbasins of the CDWR San Joaquin Valley groundwater 

basin: Madera and Chowchilla (California Department of 

Water Resources, 2003). The study unit is bounded partially 

on the north by the Chowchilla River, approximately on the 

west and south by the San Joaquin River, and on the east by 

foothills of the Sierra Nevada (fig. 2).

Similar to most areas in the San Joaquin Valley 

of California, the Madera-Chowchilla study unit has a 

Mediterranean climate, with hot, dry summers and cool, moist 

winters. Average annual rainfall across the study unit ranges 

from 11 inches (in.) over most of the study unit to 15 in. in 

the eastern portions of the study unit along the foothills of the 

Sierra Nevada (Western Regional Climate Center, 2009).

The main surface-water features in the MaderaChowchilla study unit are the San Joaquin, Fresno, and 

Chowchilla Rivers, and the Friant–Kern, Madera, and 

Chowchilla canals (fig. 2). There are also approximately 

150 miles of irrigation pipelines, 300 miles of open-flow 

canal systems each supplying water to one or more farms, and 

numerous irrigation ditches (California Department of Water 

Resources, 1966; Madera Irrigation District, 2004). The San 

Joaquin, Fresno, and Chowchilla Rivers are dammed and have 

reservoirs in the Sierra Nevada foothills east of the study unit. 

The canals and pipelines deliver surface water from the major 

rivers and reservoirs to agricultural areas in the study unit.

The Madera-Chowchilla study unit is located on the 

eastern side of the San Joaquin Valley (fig. 1). The San 

Joaquin Valley is a structural trough 200 miles long and up 

to 70 miles wide, and is filled with up to 32,000 ft of marine 

and continental sediments that range in age from Jurassic 

to Holocene. The freshwater aquifer systems primarily are 

contained in the Late Tertiary and Quaternary continental 

deposits on the top of the pile (Page, 1986). These deposits 

increase in thickness from north to south and are up to 3,000 ft 

thick in the Madera-Chowchilla study unit. The continental 

deposits consist of alluvial fan and fluvial deposits with 

some interbedded lacustrine deposits. Most of the sediments 

were derived from the Sierra Nevada to the east, with lesser 

amounts of sediment derived from the Coast Ranges to the 

west. Three physiographic regions are defined in the Valley: 

the eastern alluvial fans, the western alluvial fans, and the 

basin in the center. Sediments consist of gravels, sands, silts, 

and clays, and generally are coarser at the proximal sides 

of the fans, closest to the Sierra Nevada and Coast Ranges, 

and become finer towards the center the basin (Gronberg 

and others, 1998). The most extensive lacustrine deposit, the 

Corcoran Clay Member of the Tulare Formation, underlies 

large parts of the western alluvial fans and basin, and the distal 

end of parts of the eastern alluvial fans at depths dipping from 

50 ft on the eastern edge of the Clay to 300 ft along the margin 

of the Coast Ranges. The Corcoran Clay divides the San 

Joaquin Valley freshwater aquifer systems into an unconfined 

to semi-confined upper system and a largely confined lower 

system. The Madera-Chowchilla study unit includes eastern 

alluvial fan and basin areas (fig. 3).
6 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 02

EXPLANATION

01

FP-01

Chowchilla subbasin

 Madera subbasin

Madera-Chowchilla study unit

County boundary

Streams, rivers and canals

Grid wells (n=30)

Understanding wells (n=5)

CDPH wells with water-quality data in 

 3-year period 2/12/05–2/12/08 (n=125)

Equal-area randomized-sampling grid cell

Note: prefix “MADCHOW” removed from well id numbers for clarity.

120°30'

37°15'

36°45'

37°

120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Mendota

Friant

Fresno

Madera

Chowchilla

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Millerton

Lake

Owens Creek wens Creek

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalO

D

utside Canal

elta Mendota Canal

Delta Mendota Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Madera

Lake

Hensley

Lake

H.V. Eastman

Lake

FP-03 FP-01

FP-04

07

17

15

19

06

04

21

FP-05

05

16

03

18

14

08

11

02

01

13

27

FP-02

09

25

20

29

22 23

28

26

24

30

12

10

Figure 2. Geographic features and locations of grid cells, grid and understanding wells sampled during April–May 2008, 

and wells with data in the California Department of Public Health database during February 2005–February 2008, 

Madera-Chowchilla study unit, California GAMA Priority Basin Project. 
Hydrogeologic Setting 7

sac11-0401_fig 03

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Study unit boundary

County boundary

Streams, rivers, and canals

Wells Position relative to

Corcoran Clay Grid Understanding

East

Above/across

Below

Unknown

Geologic units

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant–Kern CanalFriant–Kern Canal

Third Lift CanalThird Lift Canal

Delta Mendota CanalDelta Mendota Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Main CanalMain Canal

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

Millerton

Madera Lake

Lake

Hensley

Lake

H.V. Eastman

Lake

Figure 3. Madera-Chowchilla study unit, California GAMA Priority Basin Project.
8 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Sediments in the eastern San Joaquin Valley primarily 

were deposited by large rivers draining glaciated areas of the 

Sierra Nevada (Mokelumne, Stanislaus, Tuolumne, Merced, 

San Joaquin, Kings, and Kaweah Rivers), and primarily 

are composed of material derived from granitic rocks of 

the Sierra Nevada batholith. The Madera-Chowchilla area 

is an exception because the Fresno and Chowchilla Rivers 

primarily have lower elevation watersheds that do not 

include glaciated areas of the Sierra Nevada (Weissmann 

and others, 2005). This difference affects the composition 

and depositional patterns of sediment in the study unit. The 

watershed of the Chowchilla River consists of a mixture of 

Mesozoic and Paleozoic metasedimentary and metavolcanic 

rocks, mafic intrusive rocks, and granitic rocks of the Sierra 

Nevada Batholith (Jennings, 1977; Saucedo and others, 2000; 

Weissmann and others, 2005), which results in mineralogically 

different sediment than sediment from granitic source rocks 

alone. These mineralogical differences are reflected in the 

soils, which have been extensively mapped in the Eastern 

San Joaquin Valley (Marchand and Allwardt, 1981). Soils 

derived from these mixed sources have a higher proportion of 

weatherable dark minerals (iron-magnesium silicate minerals 

and oxide and sulfide accessory minerals) and a lower 

proportion of quartz, compared to soils formed on sediments 

derived from granitic sources alone (Huntington, 1971). These 

differences are important because they may affect groundwater 

chemistry. The differences in sediment source also affect the 

physical structure of the sedimentary deposits. The glaciated 

areas of the Sierra Nevada yield much larger volumes of 

sediment than do the unglaciated areas; thus, the depositional 

sequences in the alluvial fans of rivers with headwaters in the 

glaciated areas are much thicker than those in the alluvial fans 

of rivers, such as the Chowchilla and Fresno Rivers, whose 

headwaters are in the unglaciated foothills (Weissmann and 

others, 2005).

The conceptual model of groundwater flow within 

the Madera-Chowchilla study unit (figs. 4A,B) is based on 

previous investigations in the Eastern San Joaquin Valley 

by Burow and others (2004) and Phillips and others (2007). 

Regional lateral flow of groundwater on the eastern side of 

the San Joaquin Valley and within the study unit is towards 

the southwest along the dip of the water-bearing units, and 

groundwater flows generally towards the axial trough (fig. 4A). 

Irrigation return flows are the major source of groundwater 

recharge, and groundwater pumping is the major source of 

discharge (Mitten and others, 1970; California Department 

of Water Resources, 2004a,b; Faunt, 2009). Groundwater on 

a lateral flow path may be repeatedly extracted by pumping 

wells and reapplied at the surface multiple times before 

reaching the valley trough (Phillips and others, 2007). 

This recharge and discharge pattern results in a substantial 

component of downward vertical flow (fig. 4B; Burow and 

others, 2004; Phillips and others, 2007; Faunt, 2009). These 

vertical flow components enhance vertical movement of water 

from recharge areas to the perforated intervals of withdrawal 

wells within shallow to intermediate depths in the system. 

These processes may occur in both agricultural and urban 

land-use areas. Groundwater age is vertically stratified, with 

water less than 50 years old in the upper parts of the aquifer 

system and water that may be tens of thousands of years old 

at depth (Burow and others, 2008). In the western part of the 

study unit, the Corcoran Clay may restrict the interaction 

between underlying confined and overlying unconfined 

groundwater; however, well-bores open to the aquifer above 

and below the Clay permit water exchange across the units 

(Williamson and others, 1989). At the western end of the 

flow system, there is upward movement of groundwater 

towards the San Joaquin River. Groundwater flow was 

artesian in the western portion of the study unit (Mendenhall, 

1908; Mendenhall and others, 1916), but with increasing 

groundwater development, water levels have generally 

exhibited a long-term declining trend (Todd Engineers, 2002; 

California Department of Water Resources, 2004a,b). 

Land use in the study unit is approximately 69% 

agricultural, 28% natural, and 3% urban on the basis of 

classification of USGS National Land Cover Data (Nakagaki 

and others, 2007) (fig. 5A). The agricultural land-use areas 

are mostly vineyards and orchards. Agricultural land use is 

distributed over most of the study unit (fig. 6), and natural 

land use occurs primarily along the eastern margin and in the 

central part of the western portion of the study unit. Most of 

the natural areas in the western portion of the study unit are 

grasslands and wetlands used as wildlife preserves. Most of 

the study unit is in Madera County (fig. 2), one of the fastest 

growing counties in the State (U.S. Census Bureau, 2010). The 

largest urban areas within the Madera-Chowchilla study unit 

are the cities of Madera and Chowchilla. The population of the 

city of Madera in July 2009 was 56,692, an increase of 31% 

since 2000 (U.S. Census Bureau, 2010). The population of the 

city of Chowchilla was 19,254 in July 2009, an increase of 

73% since 2000. The city of Fresno is just to the south of the 

study unit.
Hydrogeologic Setting 9

sac11-0401_fig 04ab

Water table

MORE CONSOLIDATED Regional flow

FLOOD-PLAIN

DEPOSITS

AGRICULTURAL RECHARGE

Public-supply wells Irrigation wells

San Joaquin

River

NOT TO SCALE

Corcoran Clay confining unit

120°30’

37°30’

36°30’

37°

120° 119°30’

FLUVIALLY DEPOSITED

ALLUVIAL FAN DEPOSITS

Aquifer

EXPLANATION

Madera-Chowchilla study unit

Streams

Generalized direction of regional groundwater flow

from valley margins towards San Joaquin River

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units

A

B

50 10 MILES

50 10 KILOMETERS

Sierra Nevada

Coast Range

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Figure 4. (A) Regional lateral groundwater flow and (B) vertical flow influenced by agricultural 

practices and natural discharge zones for the aquifer system of the Madera-Chowchilla study unit, 

California GAMA Priority Basin Project (modified from Burow and others, 2004; Phillips and others, 

2007).
10 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 05ab

0

20

40

60

80

100

Percent urban

0

20

40

60

80

100

0

20

40

60

80

100

Percent natural

0

20

40

60

80

100

Percent agriculture

Percent urban

Percent natural

Percent agriculture

100 80 60 40 20 0 100 80 60 40 20 0

Study unit land use Wells

Grid

EXPLANATION

Understanding

Average in 500-meter buffer surrounding CDPH wells with 

water quality data in 3-year period 2/12/05–2/12/08

Average for whole study unit

Average in 500-meter buffers surrounding USGS grid wells

A. Whole study unit and study unit based on 500-meter buffers surrounding 

grid and CDPH wells.

B. Grid and understanding wells in study unit based on land use within a 

500-meter buffer surrounding each well.

Figure 5. Percentages of urban, agricultural, and natural land uses for (A) the study unit and (B) the areas surrounding 

individual wells, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.
Hydrogeologic Setting 11

sac11-0401_fig 06

Fresno River Millerton

Lake

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

0 4 8 16 MILES

0 8 16 4 KILOMETERS

Land use

Grid wells (n=30)

Understanding wells (n=5)

CDPH wells with water-quality data in 

 3-year period 2/12/05–2/12/08 (n=125)

Boundary of MaderaChowchilla study unit

County boundary

Streams, rivers, and canals

Urban

Agricultural

Natural

EXPLANATION

120°30' 120°

37°

Madera

Fresno

Chowchilla

Merced

Mendota

Friant

San Joaquin RiverSan Joaquin River

Oakhurst

")

")

")

Madera

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Panoche CreekPanoche Creek

Fresno River

Third Lift CanalThird Lift Canal

California Aqueduct California Aqueduct

Outside CanalOutside Canal

Main CanalMain Canal

Chowchilla River Chowchilla River

Chowchilla Canal Chowchilla Canal

Friant-KernFriant-Ke

Ca

rn

nal

Madera CanalMadera Canal

H.V. Eastman

Lake

Figure 6. Land use of the Madera-Chowchilla study unit and locations of grid and understanding wells 

sampled during April–May 2008, and wells with data in the California Department of Public Health database 

during February 2005–February 2008, Madera-Chowchilla study unit, California GAMA Priority Basin Project.
12 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Methods

The methods described here are those used for the status 

and understanding assessments. Methods used to collect and 

analyze groundwater samples and results for quality-control 

assessment for the constituents listed in table 1 are described 

by Shelton and others (2009). Methods used for compilation 

of data on potential explanatory factors are described in 

appendix A.

Status Assessment

The status assessment is designed to quantify 

groundwater quality in areal proportions of the primary 

aquifer system. This section describes the methods used 

for (1) defining groundwater quality, (2) assembling the 

datasets used for the assessment, (3) determining which 

constituents warrant additional assessment, and (4) calculating 

aquifer-scale proportions.

Groundwater quality was defined in terms of 

relative-concentration (RC), which compares the 

concentrations of constituents in groundwater to the 

concentrations of regulatory and non-regulatory benchmarks 

used to evaluate drinking-water quality. Constituents were 

selected for additional evaluation in the status assessment

on the basis of objective criteria by using these RCs. 

Groundwater-quality data collected by the USGS for the 

GAMA Priority Basin Project (USGS-GAMA) and data 

compiled from the CDPH database were used in the status 

assessment. Two statistical methods were used to calculate the 

areal proportions of the primary aquifer system occupied by 

groundwater with high, moderate, or low RCs for a constituent 

or constituent class (aquifer-scale proportions): (1) the “gridbased” method, which uses one value per grid cell to represent 

groundwater quality (Belitz and others, 2010), and (2) the 

“spatially weighted” method, which uses many values per 

grid cell.

The CDPH database contains historical records from 

more than 25,000 wells, necessitating targeted retrievals to 

effectively access water-quality data. For example, for the area 

representing the Madera-Chowchilla study unit, the historical 

CDPH database contains more than 60,000 records from 

154 wells. The CDPH data were used in two ways in the status 

assessment: (1) to help identify constituents for additional 

evaluation in the assessment, and (2) to provide the majority 

of the data used in the spatially weighted calculations of 

aquifer-scale proportions.

Relative-Concentrations and 

Water-Quality Benchmarks

Relative-concentrations were used to provide context 

for water-quality data by comparing measured concentrations 

of constituents in groundwater samples to water-quality 

benchmarks that are generally applied to finished drinking 

water:

Sampleconcentration Relative concentration (RC) Benchmark concentration =

An RC less than 1 (<1.0) indicates a sample 

concentration less than the benchmark, and an RC greater 

than 1 (>1.0) indicates a sample concentration greater than 

the benchmark. The use of RCs also permits comparison of 

constituents present at a wide range of concentrations on a 

single scale.

Toccalino and others (2004), Toccalino and Norman 

(2006), and Rowe and others (2007) previously used RC 

by converting concentration to Benchmark Quotient (BQ), 

which is the ratio of measured concentration to a water-quality 

benchmark. The BQ concept is used in this study; however, 

the ratio of measured concentration to a water-quality 

benchmark is called relative-concentration (RC) rather 

than a BQ because the benchmarks used may be different. 

BQs are calculated using U.S. Environmental Protection 

Agency (USEPA) maximum contaminant levels (MCL-US) 

or USGS-USEPA Health-Based Screening Levels (HBSLs). 

HBSLs are determined using USEPA methodologies for 

establishing drinking-water guidelines and the most recent 

USEPA peer-reviewed, publically available human-health 

toxicity information (Toccalino, 2007). RCs are calculated 

using benchmarks established by USEPA and CDPH (U.S. 

Environmental Protection Agency, 2008a,b; California 

Department of Public Health, 2008a,b). HBSLs were not used 

in this study because they are not recognized by California 

drinking-water regulatory agencies, and the GAMA Program 

was intended to specifically focus on groundwater quality in 

California.

The benchmarks used to calculate RCs for each 

constituent were selected in the following order of priority:

1. Regulatory, health-based CDPH and USEPA maximum 

contaminant levels (MCL-CA and MCL-US, respectively) 

and action levels (AL-US).

2. Non-regulatory CDPH and USEPA secondary maximum 

contaminant levels (SMCL-CA and SMCL-US, 

respectively). For constituents with recommended and 

upper SMCL-CA levels, the values for the upper levels 

were used. 

3. Non-regulatory, health-based CDPH notification levels 

(NL-CA), USEPA lifetime health advisory levels 

(HAL-US), and USEPA risk-specific doses. Risk-specific 

doses for risks of 1 in 105 (RSD5-US) were calculated 

by dividing the USEPA values for the concentration 

of a constituent in drinking water corresponding to an 

estimated excess lifetime cancer risk of 1 in 104 by 10.

Note that for constituents with multiple types of benchmarks, 

this hierarchy may not result in selection of the benchmark 

with the lowest concentration. Additional information on the 

types of benchmarks and the benchmarks for all constituents 

analyzed is provided by Shelton and others (2009). 
Methods 13

For ease of discussion, RCs of constituents were 

classified into low, moderate, and high categories:

Category Organic and specialinterest constituents

Inorganic

constituents

High RC > 1.0 RC > 1.0

Moderate 1.0 ≥ RC > 0.1 1.0 ≥ RC > 0.5

Low 0.1 ≥ RC 0.5 ≥ RC

The boundary between “moderate” and “low” RCs was 

set at 0.1 for organic and special-interest constituents for 

consistency with other studies and reporting requirements 

(U.S. Environmental Protection Agency, 1998; Toccalino, 

2007). For organic constituents, detection at concentrations 

greater than one-tenth of a health-based benchmark value 

(RC>0.1) commonly is used to identify constituents that 

may warrant additional monitoring to evaluate trends 

in their occurrences. Organic constituents generally are 

human-made, are—ideally—not present in groundwater, 

and are infrequently detected at RCs greater than 0.1. Of 

the three special-interest constituents, two are organic 

compounds [1,2,3-trichloropropane (1,2,3-TCP) and 

N-nitrosodimethylamine (NDMA)]. The third, perchlorate, is 

an inorganic compound and is in the special-interest group, 

rather than the inorganic constituent group, because at the 

inception of the GAMA Priority Basin Project, the State of 

California was assessing potential regulation of perchlorate 

concentrations in drinking water and therefore had a “special 

interest” in perchlorate occurrence. An MCL-CA was 

promulgated in October 2007. 

For inorganic constituents, the boundary between 

“moderate” and “low” RCs was set at 0.5. The primary reason 

for using a higher boundary value was to focus attention on the 

inorganic constituents of most immediate concern (Fram and 

Belitz, 2012). The naturally occurring inorganic constituents 

tend to be more prevalent than organic constituents in 

groundwater. While more complex classifications could be 

devised based upon the properties and sources of individual 

constituents, use of a single moderate/low boundary value 

for each of the two major groups of constituents provided a 

consistent objective criteria for distinguishing constituents 

occurring at moderate rather than low concentrations.

Datasets for Status Assessment

Two datasets were used in the status assessment: 

data from grid wells, and a combination of data from grid 

wells, understanding wells, and CDPH wells. This section 

describes how each dataset was constructed. Comparisons of 

USGS-GAMA and CDPH data are presented in appendix B.

Grid Wells

The grid-based calculations of aquifer-scale proportions 

used data from 30 wells sampled by the USGS for spatial 

coverage of one well per grid cell across the study unit 

(grid wells). Detailed descriptions of the methods used to 

identify wells for sampling are given in Shelton and others 

(2009). Briefly, the Madera-Chowchilla study unit area 

was subdivided into 30 equal-area grid cells of 30 square 

miles (mi2) (fig. 2), and in each cell, one well was randomly 

selected to represent the cell (Scott, 1990). Wells primarily 

were selected from the population of wells in the statewide 

database maintained by the CDPH (Shelton and others, 2009). 

Of the 30 grid wells, 19 were listed in the CDPH database; of 

the remaining 11 wells, 6 were irrigation wells, and 5 were 

domestic wells. The depths of the perforated or open intervals 

in the irrigation and domestic wells were similar to the depths 

of the screened intervals in CDPH wells in the study unit 

(appendix B). The wells were numbered in the order of sample 

collection with the prefix “MADCHOW” identifying the study 

unit (fig. 2; Shelton and others, 2009; appendix A).

Samples were collected by the USGS from the grid 

wells and were analyzed for 282 to 288 constituents 

(table 1). All wells were sampled for alkalinity, dissolved 

oxygen, pH, specific conductance, temperature, volatile 

organic compounds (VOCs), pesticides, perchlorate, 

low-level 1,2,3-TCP, nutrients, major and minor ions, trace 

elements, noble gases, tritium, stable isotopes of water, 

uranium isotopes, carbon isotopes, and gross alpha and beta 

particle activity. Samples for analysis of turbidity, NDMA, 

pharmaceuticals, and arsenic and iron species were collected 

from some wells. Of the constituents with water-quality 

benchmarks, only NDMA was not analyzed in samples from 

all wells. The collection, analysis, and quality assurance of 

the constituents listed in table 1 are described in Shelton and 

others (2009). Pharmaceutical compounds were not detected 

at concentrations greater than or equal to method detection 

limits in the Madera-Chowchilla study unit. Fram and Belitz 

(2011a) present all results for pharmaceutical compounds 

in groundwater samples collected during May 2004 through 

March 2010 for 28 GAMA Priority Basin Project study units.

Additional Data Used for Spatially 

Weighted Calculation 

The spatially weighted calculations of aquifer-scale 

proportions used USGS-GAMA data from the 30 grid and the 

5 understanding wells, and data from CDPH wells reported 

from the most recent 3 years available in the CDPH database 

at the time of the USGS sampling for the GAMA Program.
14 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table 1. Summary of number of wells and constituents by sampling schedule and analyte group, 

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[Sampling schedule: “Intermediate” and “slow” sampling schedules refer to the amount of time required for a field crew to complete all 

work at a well. Typically, two intermediate wells or one intermediate well and one slow well could be sampled in one day. Abbreviations:

GAMA, Groundwater Ambient Monitoring and Assessment Program; LRL, laboratory reporting level]

Sampling schedule

Intermediate Slow 

Wells Number of wells

Total number of wells 25 10

Number of grid wells sampled 25 5

Number of understanding wells sampled 0 5

Analyte groups Number of constituents

Inorganic constituents

Nutrients 5 5

Major and minor ions and trace elements 36 36

Uranium isotopes 1 1 1

Gross alpha and beta particle activity 2 2 2

Specific conductance and alkalinity 2 2

Organic and special-interest constituents3

Volatile organic compounds (VOCs) (includes fumigants) 85 85

Pesticides and degradates 4 79 79

Polar pesticides and degradates 5 55 55

Perchlorate and low-level 1,2,3-trichloropropane (1,2,3-TCP) 6 2 2

N-nitrosodimethylamine (NDMA) 0 1

Geochemical and age-dating tracers

Dissolved oxygen, pH, and temperature 3 3

Noble gases and tritium 7 7 7

Stable isotopes of water 2 2

Tritium 8 1 1

Carbon isotopes 2 2

Turbidity 0 1

Arsenic and iron species 0 4

Total number of constituents analyzed by sampling schedule 282 288

1

 Three uranium isotopes were measured: uranium-234, uranium-235, and uranium-238. Uranium isotope samples were not collected at 

five USGS-grid wells sampled on the intermediate schedule.

2

 Both 72-hour and 30-day counts were measured for alpha and beta particle activities.

3

 Twelve pharmaceutical compounds were analyzed in samples from slow wells. Because pharmaceuticals are not discussed in this 

report, they are not included in the count of constituents analyzed.

4

 Does not include two constituents in common with polar pesticides and degradates (carbofuran and metalaxyl).

5

 Does not include three constituents in common with pesticides and degradates (atrazine, deethylatrazine, and tebuthiuron).

6

 Includes one analyte, 1,2,3-TCP, in common with VOC analyses. The LRL for the low-level analysis is 0.0050 microgram per liter 

(μg/L) compared to 0.12 μg/L for the VOC analysis; therefore, the low-level analysis is counted as a separate analysis.

7

 Analyzed at Lawrence Livermore National Laboratory, Livermore, California.

8

 Analyzed at USGS Stable Isotope and Tritium Laboratory, Menlo Park, California.
Methods 15

Table 2. Comparison of number of constituents analyzed and median method detection levels or laboratory 

reporting levels by type of constituent for data reported in the California Department of Public Health 

database and for data collected by the U.S. Geological Survey (USGS) for the Madera-Chowchilla study unit, 

2008, California GAMA Priority Basin Project.

[Abbreviations: GAMA, Groundwater Ambient Monitoring and Assessment Program; CDPH, California Department 

of Public Health; MDL, method detection level; LRL, laboratory reporting level; μg/L, micrograms per liter; NDMA, 

N-nitrosodimethylamine]

Constituent type

CDPH USGS-GAMA

Median 

Number of units

constituents

Median 

MDL

Number of

constituents Median LRL

Volatile organic compounds 

(including fumigants)

65 0.50 85 0.06 μg/L

Pesticides and degradates, and 

polar pesticides and metabolites

43 1 134 0.020 μg/L

NDMA 1 5 1 0.0020 μg/L

Perchlorate 1 4 1 0.10 μg/L

In addition to the 30 grid wells, 5 understanding wells 

in the Madera-Chowchilla study unit were sampled by 

USGS-GAMA. The understanding wells were located along 

the northern margin of the study unit and were selected to help 

identify differences in water quality with depth in the primary 

aquifer system. The understanding wells were numbered in the 

order of collection with the prefix “MADCHOWFP” (fig. 2; 

Shelton and others, 2009; appendix A).

The CDPH database contained water-quality data for 

154 wells. Of these 154 wells, 125 had water-quality data 

for samples collected between February 12, 2005, and 

February 12, 2008 (fig. 2), the most recent 3-year interval 

of data available from the CDPH database at the time of 

USGS-GAMA sampling in the study unit. These 125 wells 

provided the bulk of the data for the spatially weighted 

calculations. For wells with multiple analyses for a constituent 

during the 3-year interval, the most recent analysis was used. 

For the 20 wells (19 grid wells and 1 understanding well) with 

CDPH and USGS data, only the USGS data were used.

Reporting limits for inorganic constituents in the CDPH 

database were at concentrations below RCs of 0.5 for all 

constituents except antimony and thallium. Constituent 

concentration data from USGS-GAMA analysis and the CDPH 

database therefore can be adequately classified as having high, 

moderate, or low RCs. For organic (VOCs and pesticides) 

and special-interest constituents (NDMA and perchlorate), 

however, reporting limits used by USGS-GAMA were 

significantly lower than those in the CDPH database (table 2), 

and CDPH reporting limits had concentrations greater than 

RCs of 0.5 for some constituents. In addition, USGS-GAMA 

analyzed many more constituents than are reported in the 

CDPH database (table 2); therefore, the spatially weighted 

calculations of aquifer-scale proportions may provide only 

minimum estimates of the proportion of moderate values for 

those constituents.

Identification of Constituents for Additional 

Evaluation in the Status Assessment

Up to 288 constituents were analyzed by USGS-GAMA 

in samples from wells in the Madera-Chowchilla as part of 

the status assessment (table 1); however, only a subset of 

these constituents was selected for additional evaluation in 

this report. Three criteria were used to select constituents for 

additional evaluation:

1. Constituents present at high or moderate RCs in the 

CDPH database within the 3-year interval (February 12, 

2005–February 12, 2008) prior to the USGS-GAMA 

sampling period,

2. Constituents present at high or moderate RCs in the 

grid wells or understanding wells used in the status 

assessment, or

3. Organic constituents having study-unit detection 

frequencies greater than or equal to 10% in the grid well 

dataset regardless of concentration.

These criteria identified 14 inorganic constituents and 

10 organic constituents and special-interest constituents 

for additional evaluation in the status assessment (table 3). 

An additional 30 inorganic constituents and 16 organic 

constituents and all 20 geochemical and age-dating tracers 

were detected in the wells sampled by the USGS in April and 

May 2008, but were not selected for additional evaluation in 

the status assessment because they either have no established 

benchmarks, or they were only detected at low RCs and, for 

organic constituents, had study unit detection frequencies 

less than 10% (table 4). The remaining 198 constituents that 

were analyzed but not detected by USGS-GAMA are listed in 

Shelton and others (2009).
16 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table 3. Benchmark type and value for constituents selected for additional evaluation in the status assessment of 

groundwater quality in the Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[Benchmark type: AL-US, USEPA action level; HAL-US, USEPA lifetime health advisory level; MCL-CA, CDPH maximum contaminant 

level; MCL-US, USEPA maximum contaminant level; NL-CA, CDPH notification level; RSD5-US, USEPA risk-specific dose at a risk factor 

of 10–5; SMCL-CA, CDPH secondary maximum contaminant level. Benchmark units: μg/L, micrograms per liter; mg/L, milligrams per liter; 

μS/cm at 25°C, microsiemens per centimeter at 25 degrees Celsius; pCi/L, picocuries per liter. Other abbreviations: GAMA, Groundwater 

Ambient Monitoring and Assessment Program; USEPA, U.S. Environmental Protection Agency; CDPH, California Department of Public 

Health. Constituent names: DBCP, 1,2-dibromo-3-chloropropane; EDB, 1,2-dibromoethane; NDMA, N-nitrosodimethylamine; PCE, 

tetrachloroethene; 1,2,3-TCP, 1,2,3-trichloropropane; TDS, total dissolved solids; THM, trihalomethane]

Constituent Typical use or source Benchmark

type

Benchmark 

value

Benchmark

units

Organic constituents with health-based benchmarks

Atrazine Herbicide MCL-CA 1 μg/L

Diuron Herbicide RSD5-US 20 μg/L

Simazine Herbicide MCL-US 4 μg/L

DBCP Fumigant MCL-US 0.2 μg/L

EDB Fumigant MCL-US 0.05 μg/L

1,2,3-TCP1 Fumigant HAL-US 40 μg/L

PCE Solvent MCL-US 5 μg/L

Chloroform2 Disinfection byproduct (THM) MCL-US 80 μg/L

Constituents of special interest

NDMA Rocket fuel, disinfection byproduct NL-CA 0.01 μg/L

Perchlorate Natural, rocket fuel, fireworks MCL-CA 6 μg/L

Inorganic constituents with health-based benchmarks 

Nutrients

Nitrate plus nitrite, as nitrogen Natural, fertilizer, sewage MCL-US 10 mg/L

Trace elements

Arsenic Naturally occurring MCL-US 10 μg/L

Barium Naturally occurring MCL-CA 1,000 μg/L

Lead Naturally occurring AL-US 15 μg/L

Strontium Naturally occurring HAL-US 4,000 μg/L

Uranium Naturally occurring MCL-US 30 μg/L

Vanadium Naturally occurring NL-CA 50 μg/L

Radioactive constituents

Gross alpha particle activity Naturally occurring MCL-US 15 pCi/L

Uranium activity Naturally occurring MCL-CA 20 pCi/L

Inorganic constituents with aesthetic or technical (SMCL) benchmarks

Chloride Naturally occurring SMCL-CA 500 mg/L

TDS Naturally occurring SMCL-CA 1,000 mg/L

Specific conductance Naturally occurring SMCL-CA 1,600 μS/cm at 25°C

Iron Naturally occurring SMCL-CA 300 μg/L

Manganese Naturally occurring SMCL-CA 50 μg/L

1

 HAL-US was eliminated as of October 2009. NL-CA for 1,2,3-TCP is 0.005 μg/L. This report uses the HAL-US instead of NL-CA as the 

benchmark for 1,2,3-TCP because the NL-CA is less than the lowest reporting limit available for 1,2,3-TCP.

2

 Chloroform is a trihalomethane (THM). The MCL-US benchmark is the sum of chloroform, bromoform, bromodichloromethane, and 

dibromochloromethane.
Methods 17

Table 4. Constituents detected in samples collected, but not selected for additional evaluation in the status 

assessment for the Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[Benchmark types: MCL-US, USEPA maximum contaminant level; MCL-CA, CDPH maximum contaminant level; AL-US, USEPA 

action level; HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level; SMCL-US, USEPA secondary maximum 

contaminant level; SMCL-CA, CDPH secondary maximum contaminant level. Other abbreviations: GAMA, Groundwater Ambient 

Monitoring and Assessment Program; USEPA, U.S. Environmental Protection Agency; CDPH, California Department of Public Health]

Constituent Typical use or source Benchmark type

Inorganic constituents with health-based benchmarks

Aluminum Naturally occurring MCL-CA

Ammonia (as nitrogen) Naturally occurring HAL-US

Antimony Naturally occurring MCL-US

Beryllium Naturally occurring MCL-US

Boron Naturally occurring NL-CA

Cadmium Naturally occurring MCL-US

Chromium Naturally occurring MCL-CA

Copper Naturally occurring AL-US

Fluoride Naturally occurring MCL-CA

Gross beta particle activity Naturally occurring MCL-CA

Molybdenum Naturally occurring HAL-US

Nickel Naturally occurring MCL-CA

Nitrite (as nitrogen) Naturally occurring MCL-US

Selenium Naturally occurring MCL-US

Inorganic constituents with aesthetic/technical-based benchmarks

Silver Naturally occurring SMCL-CA

Sulfate Naturally occurring SMCL-CA

Zinc Naturally occurring SMCL-CA

Inorganic constituents with no benchmarks

Alkalinity Naturally occurring None

Bromide Naturally occurring None

Calcium Naturally occurring None

Cobalt Naturally occurring None

Iodide Naturally occurring None

Lithium Naturally occurring None

Magnesium Naturally occurring None

Nitrogen, total Naturally occurring None

Orthophosphate, as phosphorus Naturally occurring None

Potassium Naturally occurring None

Silica Naturally occurring None

Sodium Naturally occurring None

Tungsten Naturally occurring None

Organic constituents with regulatory, health-based benchmarks

1,1-Dichloroethane (1,1-DCA) Solvent MCL-CA

1,2-Dichloropropane Fumigant MCL-US

Bromodichloromethane Disinfection byproduct (THM) MCL-US

Bromoform (Tribromomethane) Disinfection byproduct (THM) MCL-US

cis-1,2-Dichloroethene (cis-1,2-DCE) Solvent MCL-CA

Dibromochloromethane Disinfection byproduct (THM) MCL-US

Dinoseb (Dinitrobutyl phenol) Herbicide MCL-CA

Trichloroethene (TCE) Solvent MCL-US
18 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Constituent Typical use or source Benchmark type

Organic constituents with non-regulatory, health-based benchmarks

Bromacil Herbicide HAL-US

Hexazinone Herbicide HAL-US

Tebuthiuron Herbicide HAL-US

Organic constituents with no benchmarks

3,4-Dichloroaniline Herbicide degradate (diuron) None

Deethylatrazine (2-Chloro-4-isopropylamino-6-amino-striazine; DEA)Herbicide degradate (atrazine) None

Deisopropyl atrazine (2-Chloro-6-ethylamino-4-amino-striazine; DIA)Herbicide degradate (atrazine) None

Imazethapyr Herbicide None

Norflurazon Herbicide None

Geochemical and age-dating tracers

Tritium Naturally occurring MCL-CA

pH Naturally occurring SMCL-US

Dissolved oxygen, temperature Naturally occurring None

Turbidity Naturally occurring None

Carbon-14 and δ13C of dissolved carbonates Naturally occurring None

δ2H and δ18O stable isotopes of water Naturally occurring None

Five noble gases, tritium, and δ3He Naturally occurring None

Four arsenic and iron species Naturally occurring None

Table 4. Constituents detected in samples collected, but not selected for additional evaluation in the status assessment 

for the Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.—Continued

[Benchmark types: MCL-US, USEPA maximum contaminant level; MCL-CA, CDPH maximum contaminant level; AL-US, USEPA 

action level; HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level; SMCL-US, USEPA secondary maximum 

contaminant level; SMCL-CA, CDPH secondary maximum contaminant level. Other abbreviations: GAMA, Groundwater Ambient 

Monitoring and Assessment Program; USEPA, U.S. Environmental Protection Agency; CDPH, California Department of Public Health]

Table 5. Constituents historically reported at high relative-concentrations in the California Department of Public 

Health database for the Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[The historical period of CDPH well data is from January 6, 1984, to February 11, 2005. The 3-year period used in the status assessment 

is from February 12, 2005, to February 12, 2008. Relative-concentration equals measured concentration divided by benchmark value; 

relative‐concentration greater than 1 is defined as high. Benchmark types: AL-US, USEPA action level; MCL-US, USEPA maximum 

contaminant level; MCL-CA, CDPH maximum contaminant level. Benchmark units: μg/L, micrograms per liter; mg/L, milligrams per 

liter; pCi/L, picocuries per liter. Other abbreviations: CDPH, California Department of Public Health; GAMA, Groundwater Ambient 

Monitoring and Assessment Program; USEPA, U.S. Environmental Protection Agency]

Constituent Benchmark

 type

Benchmark 

value Units

Date of 

most recent 

high value 

Number of 

historically 

high wells

Number of 

wells with 

analysis

Cadmium MCL-US 5 μg/L 02-15-98 1 84

EDB 1,2 MCL-US 0.05 μg/L 12-11-07 1 101

Fluoride 1 MCL-CA 2 mg/L 01-24-06 3 93

Lead 1,2 AL-US 15 μg/L 06-27-06 6 91

Mercury MCL-US 2 μg/L 04-19-85 2 84

Radium 1 MCL-US 5 pCi/L 08-18-05 1 73

1

1,2- Dibromoethane (EDB), fluoride, lead, and radium were reported at high relative-concentrations between February 12, 2005, and 

February 12, 2008, but the high value was not the most recent value reported for the well.

2

 1,2-Dibromoethane (EDB) was detected at moderate relative-concentration in USGS-GAMA samples, and lead was reported at 

moderate relative-concentration in the CDPH database between February 12, 2005, and February 12, 2008, thus, both constituents met the 

criteria for additional evaluation in the status assessment and are listed in table 8.
Methods 19

The USGS conducted a review of the water-quality 

data (January 6, 1984, to February 12, 2008) in the CDPH 

database to identify constituents that have been reported 

at high RCs historically, but not currently. Constituents 

may be historically high, but not currently high, because 

of improvement of groundwater quality with time or 

abandonment of wells with high concentrations. Constituents 

with historically high RCs that do not otherwise meet the 

criteria for selection for additional evaluation in the status 

assessment are not considered representative of current 

potential groundwater-quality concerns in the study unit. Two 

constituents, cadmium and mercury, were reported at high 

RCs before the 3-year interval used for the status assessment

(table 5). Cadmium was detected at low concentrations 

in several samples, and mercury was not detected in any 

samples analyzed by USGS-GAMA. Four constituents, 

1,2-dibromoethane, fluoride, lead, and radium, were reported 

at high RCs during the 3-year interval, but the most recent 

sample used in the status assessment did not have high RCs 

(table 5).

Calculation of Aquifer-Scale Proportions

The status assessment is intended to characterize the 

current quality of groundwater resources within the primary 

aquifer system of the Madera-Chowchilla study unit. The 

primary aquifer system is defined by the depth intervals over 

which wells listed in the CDPH database are perforated. The 

use of the term “primary aquifer system” does not imply 

that there exists a discrete aquifer unit. In most groundwater 

basins, public supply wells typically are perforated at greater 

depths than are domestic wells (Burow and others, 2008). 

Thus, because domestic wells are not listed in the CDPH 

database, the primary aquifer system generally corresponds 

to the portion of the aquifer system tapped by public wells. 

However, to the extent that domestic wells in the study unit 

are perforated over the same depth intervals as the CDPH 

wells, the assessments presented in this report may also be 

applicable to the portions of the aquifer systems used for 

domestic drinking-water supplies (appendix B).

Two statistical approaches, grid-based and spatially 

weighted, were selected to evaluate the proportions of the 

primary aquifer system with high and moderate RCs of 

constituents (Belitz and others, 2010). For ease of discussion, 

these proportions are referred to as “high” and “moderate” 

aquifer-scale proportions. Calculations of aquifer-scale 

proportions were made for individual constituents meeting 

the criteria for additional evaluation in the status assessment, 

and for classes of constituents. Classes of constituents with 

health-based benchmarks included nutrients, trace elements, 

radioactive constituents, herbicides, fumigants, solvents, and 

THMs. Class of constituents with aesthetic-based benchmarks 

included salinity indicators and trace elements.

The grid-based calculation uses the grid-well dataset. 

For each constituent, the high aquifer-scale proportion was 

calculated by dividing the number of cells represented by a 

high value for that constituent by the total number of grid 

cells with data for that constituent. The moderate aquifer-scale 

proportion was calculated similarly. Confidence intervals for 

the high aquifer-scale proportions were computed using the 

Jeffreys interval for the binomial distribution (Brown and 

others, 2001; Belitz and others, 2010). For calculation of high 

aquifer-scale proportion for a class of constituents, cells were 

considered high if any of the constituents had a high value. 

Cells were considered moderate if any of the constituents had 

a moderate value, but none had a high value within the cell. 

The grid-based estimate is spatially unbiased; however, it may 

not detect constituents that are present at high RCs in small 

proportions of the primary aquifer system.

The spatially weighted calculation uses the dataset 

assembled from the CDPH wells and all of the USGS wells. 

For each constituent, the high aquifer-scale proportion was 

calculated by computing the proportion of “high” wells in 

each cell and then averaging the proportions for all the cells 

(Isaaks and Srivastava, 1989; Belitz and others, 2010). The 

moderate aquifer-scale proportion was calculated similarly. 

Confidence intervals for spatially weighted detection 

frequencies of high concentrations are not described in this 

report. For calculation of high aquifer-scale proportion for a 

class of constituents, wells were considered high if any of the 

constituents had a high value. Wells were considered moderate 

if any of the constituents had a moderate value, but none had a 

high value.

In addition, for each constituent, the raw detection 

frequencies of high and moderate values for individual 

constituents were calculated using same dataset as used for 

the spatially weighted calculations. Raw detection frequencies 

are not spatially unbiased, however, because the wells in the 

CDPH database are not uniformly distributed (fig. 2). For 

example, if a constituent were present at high concentrations 

in a small region of the aquifer that had a high density of 

wells, the raw detection frequency of high values would be 

greater than the high aquifer-scale proportion. Raw detection 

frequencies are provided for reference but were not used to 

assess aquifer-scale proportions.

The grid-based high aquifer-scale proportions were used 

to represent proportions in the primary aquifer system unless 

the spatially weighted proportions were significantly different 

from the grid-based values. Significantly different results were 

defined as follows:

• If the grid-based high aquifer-scale proportion was 

zero and the spatially weighted proportion was nonzero, then the spatially weighted result was used. This 

situation can arise when a constituent is present at 

high RCs in a small proportion of the primary aquifer 

system.

• If the grid-based high aquifer-scale proportion was 

non-zero and the spatially weighted proportion was 

outside the 90% confidence interval (based on the 

Jeffreys interval for the binomial distribution), then the 

spatially weighted proportion was used.
20 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

The grid-based moderate and low proportions were used in 

most cases because the reporting limits for many organic 

constituents and some inorganic constituents in CDPH were 

higher than the boundary between the moderate and low 

categories. However, if the grid-based moderate proportion 

was zero and the spatially weighted proportion non-zero, then 

the spatially weighed value was used as a minimum estimate 

for the moderate proportion.

A subset of the constituents examined in the status 

assessment, as well as selected classes of constituents, was 

examined in the understanding assessment:

• Constituents with high aquifer-scale proportions 

of greater than 2%. These constituents were 

selected to focus the understanding assessment on 

those constituents that have the greatest effect on 

groundwater quality. 

• Classes of organic constituents that included 

constituents detected in 10% or more of grid wells, 

regardless of concentration.

The understanding assessment was based on the 35 grid 

and understanding wells sampled by USGS-GAMA. CDPH 

wells were not used because data for many of the potential 

explanatory factors were not available. In particular, data 

for age-dating tracers, dissolved oxygen, well depth, and 

depth to the top of screened interval are not maintained in 

the CDPH database. For different potential explanatory 

factors, correlations were tested using either the set of 

grid plus understanding wells or grid wells only. Because 

the understanding wells were not randomly selected on a 

spatially distributed grid, understanding wells were excluded 

from analyses of relations of water quality to areally 

distributed variables (land use and lateral position) to avoid 

areal-clustering bias. Understanding wells, however, were 

included in analyses of relations between constituents and the 

vertically distributed explanatory variables depth, groundwater 

age, and oxidation-reduction characteristics to aid in the 

identification of relations.

Statistical Analysis

Nonparametric statistical methods were used to test the 

significance of correlations between water-quality variables 

and potential explanatory variables. Nonparametric statistics 

are robust techniques that are generally not affected by 

outliers and do not require that the data follow any particular 

distribution (Helsel and Hirsch, 2002). The significance level 

(p) used for hypothesis testing for this report was compared 

to a threshold value (α) of 5% (α=0.05) to evaluate whether 

the relation was statistically significant (p<α). Correlations 

were investigated using Spearman’s method to calculate the 

rank-order correlation coefficient (rho) between continuous 

variables. The values of rho can range from +1.0 (perfect 

positive correlation), through 0.0 (no correlation), to –1.0 

(perfect negative correlation). For potential explanatory factors 

that were classified into categories (groundwater age, well 

depth, and position relative to the Corcoran Clay), the values 

of water-quality parameters between the categories were 

compared using the Wilcoxon rank-sum test. The Wilcoxon 

rank-sum test is a median test statistic that compares two 

independent data groups (categories) to determine whether 

one group contains larger values than the other (Helsel and 

Hirsch, 2002). The null hypothesis for the Wilcoxon ranksum test is that there is no significant difference between the 

observations of the two independent data groups being tested. 

All statistical analyses were done using TIBCO Spotfire S+®

8.1 for Windows.

Potential Explanatory Factors

Brief descriptions of potential explanatory factors 

including land use, depth, position relative to the Corcoran 

Clay, lateral position, groundwater age, and geochemical 

conditions are given in this section. Correlations between 

explanatory factors that could affect apparent relations 

between explanatory factors and water quality also are 

described. The data sources and methodology used for 

assigning values for potential explanatory factors are 

described in appendix A.

Land Use

Land use based on all the land within the study unit 

boundaries was 69% agricultural, 28% natural, and 3% urban 

(fig. 5A). Compared to the land use in the entire study unit, the 

average land use around the CDPH wells (500-meter radius) 

was 26% more urban and 18% less agricultural. Average land 

use around the grid wells was 13% more urban and 8% less 

agricultural than land use in the entire study unit (fig. 5A). The 

difference between overall land use and land use around wells 

reflects that public-supply wells are often located in or near 

communities. The difference between the average land use 

around the CDPH wells and around the grid wells reflects the 

spatially distributed nature of the grid wells. The CDPH wells 

are biased towards urban land use because urbanized areas 

generally have a higher density of CDPH wells.

Land use surrounding two-thirds of the individual grid 

wells was greater than 50% agricultural (fig. 5B; table A1). 

Most of the remaining grid wells were surrounded by mixtures 

of urban and natural land use. Four of the five understanding 

wells had greater than 75% agricultural land use.
Potential Explanatory Factors 21

An additional subcategory of agricultural land use 

included in the analysis of fumigant concentrations was 

percentage of orchard/vineyard land use. Orchard/vineyard 

land use has previously been related to concentrations of 

fumigants and nitrate in parts of the eastern San Joaquin 

Valley (Domagalski, 1997; Burow and others, 1998a). In the 

Madera-Chowchilla study unit, orchard/vineyard land use 

occurred primarily in the south-central portion of the study 

unit. Land use around more than half of the individual grid 

wells and understanding wells was greater than 10% orchard/

vineyard (table A1).

Depth, Position Relative to the Corcoran Clay, 

and Lateral Position 

Grid wells had well depths ranging from 140 to 830 ft, 

with a median of 388 ft (fig. 7A; table A2). Depth to the top 

of the perforations ranged from 48 to 506 ft, with a median 

of 240 ft (fig. 7B). The perforation length ranged from 0 to 

410 ft, with a median of 160 ft (fig. 7C). Three grid wells 

had perforation lengths of 0 ft; these wells have solid casings 

and draw groundwater through the open bottom of the well. 

The understanding wells generally were shallower with 

shorter perforation lengths than the grid wells (figs. 7A,C). 

The median well depth, depth to the top of perforations, and 

perforation length were 254, 212, and 42 ft, respectively, for 

understanding wells (figs. 7A,B,C).

The depth to the top of the Corcoran Clay dips from 

about 68 to 80 ft below land surface near Chowchilla to about 

350 to 400 ft below land surface at the southwestern edge of 

the study unit (Mitten and others, 1970; Page, 1986). Most of 

the USGS-GAMA wells sampled (20 out of 35 wells) were 

located east of the extent of the Corcoran Clay. Of the 15 wells 

located where the Corcoran is present, 8 were perforated 

below it, 6 were perforated above or across it, and there 

was not enough well construction information for 1 well to 

determine the depth relative to the position of the Corcoran 

Clay (fig. 3; table A2).

The wells were relatively evenly distributed across the 

study unit between the Sierra Nevada foothills and the central 

axis of the San Joaquin Valley (figs. 8A,B). The central axis 

is defined by the reach of the San Joaquin River that flows 

from southeast to northwest. Lateral position is calculated as 

the ratio of the distance of the well from the central axis of 

the valley (the downgradient, or distal, end of the regional 

groundwater flow system) to the total distance from the 

central axis to the margin of the valley along the foothills (the 

upgradient, or proximal, end of the regional groundwater flow 

system). Lateral positions of grid wells range from 0.05 for the 

well located closest to the central axis to 1.00 for wells located 

closest to the foothills (table A1, figs. 8A,B). 

Groundwater Age 

Data for the age-dating tracers tritium, carbon-14, and 

helium-4 were used to classify groundwater age distributions 

(appendix A, tables A3 and A4). Groundwater with tritium 

activity greater than or equal to 0.2 tritium units (TU), 

terrigenic helium less than 10% of total helium, and carbon-14 

greater than 80 percent modern carbon (pmc) was classified 

as having a “modern” age distribution (recharged since 

approximately 1950). Groundwater with tritium activity less 

than 0.2 TU and carbon-14 less than 80 pmc was classified 

as having a “pre-modern” age distribution (recharged before 

approximately 1950). Groundwater with tritium activity 

greater than or equal to 0.2 TU, and either terrigenic helium 

greater than or equal to 10% of total helium or carbon-14 

less than 80 pmc was classified as having a “mixed” age 

distribution. Groundwater with a mixed age distribution 

is a mixture of waters with modern and pre-modern 

age distributions.

Of the 35 Madera-Chowchilla grid and understanding 

well samples, 9 were classified as having modern groundwater 

age distributions, 17 were classified as having mixed age 

distribution, and 9 were classified as having pre-modern age 

distributions (table A4). Wells yielding groundwater with 

pre-modern age distributions typically were deeper than wells 

yielding groundwater with modern age distributions and were 

significantly deeper than wells yielding groundwater with 

mixed age distributions (fig. 9A, table 6A). Wells yielding 

groundwater with modern age distributions had significantly 

shallower depths to top of perforations than wells yielding 

groundwater with pre-modern age distributions (p=0.001) 

(fig. 9B, table 6A).

Classified groundwater ages and data for well depths 

and depths to top of perforations and bottom of perforations 

within the perforated interval were used to create a 3-factor 

classification system for well depth (fig. 10). Well depth and 

perforation interval information was available to classify 

thirty-three of the thirty-five wells sampled by USGS-GAMA 

as either shallow, mixed, or deep.

The boundary depth was selected to maximize the 

segregation of groundwater samples with modern age 

distributions from those with pre-modern age distributions. 

A boundary depth of 280 ft resulted in classification of all 

wells with modern age distributions as shallow or mixed depth 

wells, and all wells with pre-modern age distributions as deep 

or mixed depth wells (fig. 10).
22 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 07abc

Grid Understanding Grid Understanding

Grid Understanding

Well type

Depth, in feet below land surface

200

0

400

600

800

n=28 n=5 n=27 n=5

p=0.046

A. Well depth B. Depth to top of perforation

Length of perforated interval, in feet

100

0

200

300

400

n=27 n=5

C. Length of perforated interval

Understanding<Grid

EXPLANATION

outlier

outlier

n Number of wells

90th percentile

75th percentile

25th percentile

10th percentile

Median

Note: white box indicates significant difference

(Understanding-well depth significantly more

shallow than grid-well depth)

Figure 7. (A) Well depth, (B) depth to top of perforations, and (C) perforation 

lengths for grid and understanding wells, Madera-Chowchilla study unit, 2008, 

California GAMA Priority Basin Project.
Potential Explanatory Factors 23

sac11-0401_fig 08ab

Normalized lateral position

0.00–0.19 0.20–0.39 0.40–0.59 0.60–0.79 0.80–1.00

6

4

2

0

8

10

Number of wells

Downgradient Upgradient

Grid well

Understanding well

A. Distribution of wells plotted on visualization of normalized lateral positions

 from eastern margin of valley.

Boundary of Madera-Chowchilla study unit

Equal-area randomized-sampling grid cell

Grid well

Understanding well

EXPLANATION

Normalized Lateral 

Position Ranges

0.00 – 0.19

0.20 – 0.39

0.40 – 0.59

0.60 – 0.79

0.80 – 1.00

0 8 16 MILES 4

0 8 16 KILOMETERS 4

120°30 ́ 120°

37°

East edge of

valley ( = 1.00 )

Valley trough

( = 0.00 )

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

B. Distribution of wells across the range of normalized lateral position values.

Figure 8. (A) Distribution of wells plotted on visualization 

of normalized lateral positions from eastern margin of 

valley and (B) the distribution of wells across the range of 

normalized lateral position values, Madera-Chowchilla study 

unit, 2008, California GAMA Priority Basin Project.
24 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 9. Relation of classified groundwater age to (A) well depth and (B) depth to top of 

perforation, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

sac11-0401_fig 09ab Well depth, in feet below land surface

0

200

400

600

800

Modern<Pre-modern

p=0.001

Depth to top of perforations, in feet below land surface

0

100

200

300

400

500

600

n=14 n=9

Modern Mixed Pre-modern

Groundwater age classification

n=9

A n=9 n=15 n=9

B EXPLANATION

outlier

outlier

90th percentile

75th percentile

25th percentile

10th percentile

Median

n Number of wells

Note: white box indicates significant

difference (significantly more shallow

to top of perforations than other wells)
Potential Explanatory Factors 25

Figure 10. Groundwater age distributions in depth classes, Madera-Chowchilla study unit, 2008, California GAMA Priority 

Basin Project.

sac11-0401_fig 10

Number of wells

0 1 2 3 4 5 6 7

Depth classification

Shallow

Entire perforated 

interval and well 

depth ≤ 280 feet

Mixed

Top of perforations

≤ 280 feet; Bottom of 

perforated interval 

> 280 feet

Unknown

Deep

Entire perforated interval 

> 280 feet

EXPLANATION

Modern

Mixed

Pre-modern

Groundwater age classification

Geochemical Conditions

The geochemical conditions investigated as potential 

explanatory factors in this report are oxidation-reduction 

characteristics, pH, and cation ratios. 

Groundwater in the Madera-Chowchilla study unit was 

primarily classified as oxic; 34 of the 35 wells (97%) had 

dissolved oxygen concentrations greater than 0.5 milligram 

per liter (mg/L) (table A5). The one well with anoxic 

conditions was located in the northwestern portion of the study 

unit and was entirely perforated below the Corcoran Clay 

(fig. 11A). All eight wells with lateral position less than 0.20 

(closest to the central axis of the valley) had oxic conditions.

The pH values ranged from 6.8 to 8.4 in the 35 grid 

and understanding wells in the Madera-Chowchilla study 

unit (table A5). The highest values of pH (greater than or 

equal to 8) occurred in groundwater from five wells located 

in the northwest corner of the study unit. These five wells 

all had perforated intervals entirely below the Corcoran 

Clay (fig. 11B). 

The proportions of the major cations, calcium, 

magnesium, sodium, and potassium, in groundwater from 

the study unit varied widely (table A5). The proportion is 

expressed as Fract-CaMg, the ratio of the sum of calcium plus 

magnesium to the total of the four cations in milliequivalents, 

with higher values indicating higher proportions of calcium 

plus magnesium in the cations. The highest values (0.69 to 

0.79) were found in groundwater from wells with depth to 

top of perforations less than 235 ft and mostly with lateral 

positions less than 0.25 (fig. 11C). The lowest values (0.16 to 

0.49) mostly were found in deeper wells, particularly wells 

perforated below the Corcoran Clay.
26 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 11. Relations of (A) dissolved oxygen, (B) pH, and (C) fraction of calcium+magnesium in total cations to 

lateral position and depth of perforated interval of wells, Madera-Chowchilla study unit, 2008, California GAMA 

Priority Basin Project.

sac11-0401_fig 11abc

A. Dissolved oxygen

B. pH

C. Fract-CaMg

200

0

400

600

800

200

0

400

600

800

200

0

400

600

800

0.0 0.2 0.4 0.6 0.8 1.0

Depth below land surface, in feet Depth below land surface, in feet Depth below land surface, in feet

Lateral position

EXPLANATION

DO ≤ 0.5 mg/L (anoxic)

0.5 < DO ≤ 2 mg/L

DO > 2 mg/L

 Dissolved oxygen

Top

Bottom

 Perforated interval

 Open bottom well with perforated 

 interval length of 0 feet

Top

Bottom

 Corcoran Clay

CaMg ≤ 0.50

0.50 < CaMg < 0.68

CaMg ≥ 0.68

 Fraction calcium + magnesium (CaMg)

pH < 8

pH ≥ 8 

 pH
Potential Explanatory Factors 27

Correlations Between Explanatory Variables

Apparent correlations between potential explanatory 

factors and water-quality constituents could result from 

correlations among potential explanatory factors; therefore, 

identification of statistically significant correlations between 

potential explanatory factors is important. The potential 

explanatory factors examined for this study unit are not 

extensively correlated with one another with the exception 

of the correlations between depth, groundwater age, position 

relative to the Corcoran Clay, and geochemical indicators 

(tables 6A,B).

There were relatively few significant correlations 

between land use and other potential explanatory factors. 

Agricultural land use had a significant negative correlation 

and natural land use a significant positive correlation with 

lateral position (table 6B). Natural land use is dominant in two 

areas of the study unit: along the edge of the Sierra Nevada 

foothills (eastern margin) and near the center of the western 

margin, close to the San Joaquin River. However, the natural 

land-use area near the River has little population and very 

few wells compared to the area along the foothills (fig. 6). 

Thus, for areas within the 500-meter (m) buffers around the 

grid wells, natural land use occurs nearly entirely in the area 

along the foothills (lateral position > 0.8). The significant 

association between agricultural land use and wells perforated 

above/across the Corcoran Clay (table 6A) is a consequence 

of the Clay only being present in the western side of the 

study unit and the relation between agricultural land use and 

lateral position.

The significant positive correlation between urban 

land use and well depth (table 6B) reflects the greater depth 

of wells serving larger populations. The wells sampled by 

USGS-GAMA can be divided into four types: CDPH wells 

serving populations greater than 4,000 people (n=8), CDPH 

wells serving populations less than 500 people (n=13), 

irrigation wells (n=7), and domestic wells (n=7). The median 

depth of CDPH wells serving large populations (670 ft) was 

significantly greater than the median depths of CDPH wells 

serving small populations (325 ft; p=0.002), irrigation wells 

(346 ft, p=0.008), or domestic wells (317 ft; p=0.014) (see 

appendix B). There were no significant differences between 

the depths of CDPH wells serving small populations, irrigation 

wells, and domestic wells. The primary aquifer system is 

defined by the intervals over which wells in the CDPH 

database are perforated; therefore, all of the wells sampled 

by USGS- GAMA are representative of the primary aquifer 

system. CDPH wells serving large populations are located in 

or near the Cities of Fresno, Madera, and Chowchilla, or are 

located at institutions with large resident populations, which 

all correspond to areas with the most urban land use and the 

greatest population densities in the study unit. In contrast, 

CDPH wells serving small populations mostly are at schools, 

parks, stores, and restaurants that are located away from the 

major cities.

There were many significant correlations between 

well depth, groundwater age, and geochemical indicators. 

Groundwater with pre-modern age distributions was 

significantly associated with deeper wells and with greater 

depths to the top of the perforated interval (table 6A, 

figs. 9A,B). Groundwater with pre-modern age distributions 

also was significantly associated with higher pH and 

with lower Fract-CaMg values and dissolved oxygen 

concentrations. As expected from the relation between well 

depth and groundwater age, deeper wells had significantly 

higher pH and lower Fract-CaMg values and dissolved 

oxygen concentrations.

The lack of correlation between lateral position and 

dissolved oxygen was unexpected. Studies in other areas of 

the eastern San Joaquin Valley have found strong gradients in 

dissolved oxygen concentration in groundwater, with anoxic 

conditions commonly found in the center of the Valley (low 

lateral position) (Davis and Hall, 1959; Bertoldi and others, 

1991; Burow and others, 1998a,b; Bennett and others, 2010; 

Landon and others, 2010). 
28 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project Table 6A. Results of Wilcoxon rank-sum tests for differences in values of selected potential explanatory factors between samples classified into groups by position relative to the Corcoran Clay, groundwater age, or well depth, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project. [Relation of median values in pairs of sample groups tested shown for Wilcoxon rank-sum tests in which the two populations were determined to be significantly different (two-sided test) on the basis of p-values (not shown) less than threshold value (α) of 0.05; ns, test indicates no significant difference between the pair of sample groups. Position relative to Corcoran Clay: Abv/Ac, bottom of perforations are above Corcoran Clay or well is perforated across the Corcoran Clay; East, well located east of Corcoran Clay extent in subsurface; Blw, topmost perforation is below the Corcoran Clay. Age classification: Mod, modern; Mix, mixed; Pre, pre-modern. Depth classification: Shal, entire perforated interval ≤  280 ft; Mixed, top of perforated interval ≤ 280 ft and bottom of perforated interval > 280 ft; Deep, entire perforated interval > 280 ft. See Appendix A for more information about factors listed. Other abbreviations: Ca, calcium; Mg, magnesium; Fract-CaMg, calcium plus magnesium in milliequivalents divided by sum of calcium, magnesium, sodium, and potassium in milliequivalents; ft, feet below land surface; sig. diff., significant differences; <, less than; >, greater than] Potential explanatory factor Position relative to Corcoran Clay Age classification Depth classification Abv/Ac vs Blw (sig. diff.) Abv/Ac vs East (sig. diff.) Blw vs East (sig. diff.) Mod vs Pre (sig. diff.) Mod vs Mix (sig. diff.) Mix vs Pre (sig. diff.) Shal vs Deep (sig. diff.) Shal vs Mix (sig. diff.) Deep vs Mix (sig. diff.) Grid wells Agricultural land use (percent) ns Abv/Ac > East ns ns ns ns ns ns ns Natural land use (percent) ns East > AbvAc ns ns ns ns ns ns ns Urban land use (percent) ns ns ns ns ns Pre > Mix ns ns ns Orchard/vineyard land use (percent) ns ns ns ns ns ns ns ns ns Lateral position ns East > Abv/Ac East>Blw ns ns ns ns ns ns Grid and understanding wells Well depth ns ns ns ns ns Pre > Mix Deep > Shal Mix > Shal Deep > Mix Depth to top of perforation Blw > Abv/Ac East > Abv/Ac ns Pre > Mod ns ns Deep > Shal ns Deep>Mix pH Blw > Abv/Ac ns ns Pre > Mod ns ns Deep > Shal ns ns DO Abv/A c> Blw Abv/Ac > East ns Mod > Pre Mod > Mix ns Shal > Deep Sha l> Mix ns Fract-CaMg Abv/Ac > Blw Abv/Ac > East ns Mod > Pre ns ns Shal > Deep Shal > Mix Mix > Deep
Status and Understanding of Water Quality 29

Table 6B. Results of Spearman’s tests of correlations between selected potential explanatory factors, Madera-Chowchilla study unit, 

2008, California GAMA Priority Basin Project.

[Abbreviations: ρ (rho), Spearman’s correlation statistic; ρ values are shown for tests in which the variables were determined to be significantly correlated on 

the basis of p values (significance level of the Spearman’s test) less than threshold value (α) of 0.05 (not shown); ns, Spearman’s test indicates no significant 

correlation between factors; black text, significant positive correlation; red text, significant negative correlation]

ρ

Percent 

natural 

land use

Percent 

urban 

land use

Lateral 

position

Well

depth

Depth to 

top of 

perforation

pH

Dissolved 

oxygen 

concentration

Fract-CaMg

Grid wells

Percent agricultural land use –0.82 –0.53 –0.66 ns ns ns ns ns

Percent natural land use ns 0.72 ns ns ns ns ns

Percent urban land use ns 0.40 ns ns ns ns

Lateral position ns ns ns ns ns

Grid and understanding wells

Well depth 0.63 ns ns –0.43

Depth to top of perforation 0.53 –0.36 –0.61

pH –0.44 –0.71

Dissolved oxygen concentration 0.60

Status and Understanding of 

Water Quality 

The status assessment was designed to identify the 

constituents or classes of constituents most likely to be waterquality concerns by virtue of their high concentrations or 

their prevalence. The assessment applies only to constituents 

having regulatory or non-regulatory health-based or aesthetic/

technical based benchmarks established by the USEPA or the 

CDPH (as of 2008). The spatially distributed, randomized 

approach to well selection and data analysis yields a view 

of groundwater quality in which all areas of the primary 

aquifer system are weighted equally; regions with a high 

density of groundwater use or with high density of potential 

contaminants were not preferentially sampled (Belitz and 

others, 2010).

The understanding assessment was designed to help 

answer the question of why specific constituents are, or are 

not, observed in groundwater in the area, and may improve our 

understanding of how human activities and natural processes 

affect groundwater quality in the study unit. The assessment 

addresses a subset of the constituents discussed in the status 

assessment, and is based on statistical correlations between 

water quality and a finite set of potential explanatory factors. 

The assessment is not designed to identify specific sources of 

constituents to specific wells.

The following discussion of the status and understanding

assessment results is divided into two parts—inorganic 

constituents and organic constituents—and each part has 

a tiered structure. Each part begins with a survey of how 

many constituents were detected at any concentration in 

USGS-GAMA samples compared to the number analyzed, 

and a graphical summary of the RCs of constituents detected 

in the grid wells. Aquifer-scale proportions are presented 

for the subset of constituents that met criteria for additional 

evaluation based on RC, or for organic constituents, 

prevalence. Understanding assessment results are presented 

for the subset of status assessment constituents that had 

statistically significant correlations to potential explanatory 

factors. For constituents that have understanding assessment

results, those results are presented immediately following the 

status assessment results for that constituent.

Inorganic Constituents

Inorganic constituents typically occur naturally in 

groundwater, although their concentrations may be influenced 

by human activities as well as by natural factors. Forty-four 

of the 46 inorganic constituents analyzed for by USGSGAMA were detected (table 7A). Of these 44 constituents, 

23 had regulatory or non-regulatory health-based benchmarks, 

8 had non-regulatory aesthetic/technical-based benchmarks, 

and 13 had no established benchmarks. Of the 31 inorganic 

constituents with benchmarks, 11 were identified for additional 

evaluation in the status assessment because they were detected 

at moderate or high RCs in the grid wells: nitrate, arsenic, 

barium, uranium, vanadium, gross alpha particle activity, 

uranium activity (sum of uranium-234, uranium-235, and 

uranium-238), manganese, chloride, total dissolved solids 

(TDS), and specific conductance (fig. 12). The majority of 

these 11 constituents were detected at moderate or high RCs in 

more than 15% of the grid wells (fig. 13).
30 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table 7A. Number of inorganic constituents analyzed and 

detected, by benchmark type and constituent type, MaderaChowchilla study unit, 2008, California GAMA Priority Basin 

Project.

[Health-based benchmarks (HBB) include USEPA maximum contaminant 

level, CDPH maximum contaminant level, USEPA lifetime health advisory 

levels, action levels, and CDPH notification levels. CDPH secondary 

maximum contaminant level benchmarks (SMCL) are non-regulatory 

aesthetic benchmarks. Abbreviations: USEPA, U.S. Environmental 

Protection Agency; CDPH, California Department of Public Health]

Benchmark type Number

analyzed

Number

detected

Nutrients

HBB 3 3

SMCL 0 0

No benchmark 2 2

Total: 5 5

Major and minor ions

HBB 1 1

SMCL 4 4

No benchmark 8 8

Total: 13 13

Trace elements

HBB 18 16

SMCL 4 4

No benchmark 3 3

Total: 25 23

Radioactive constituents

HBB 3 3

SMCL 0 0

No benchmark 0 0

Total: 3 3

Sum of inorganic constituents

HBB 25 23

SMCL 8 8

No benchmark 13 13

Total: 46 44

Table 7B. Number of organic and special-interest constituents 

analyzed and detected, by health-based benchmark type and 

constituent type, Madera-Chowchilla study unit, 2008, California 

GAMA Priority Basin Project.

[Regulatory health-based benchmarks (HBB) include USEPA maximum 

contaminant level and CDPH maximum contaminant level. Non-regulatory 

health-based benchmarks include USEPA lifetime health advisory levels, 

risk-specific dose level at 10–5, and CDPH notification level. Abbreviations:

USEPA, U.S. Environmental Protection Agency; CDPH, California 

Department of Public Health; VOC, volatile organic compound]

Benchmark type Number

analyzed

Number

detected

Organic constituents

Pesticides and pesticide degradates

Regulatory - HBB 14 3

Non-regulatory - HBB 29 4

No benchmark 91 5

Total: 134 12

Fumigants

Regulatory - HBB 4 3

Non-regulatory - HBB 4 1

No benchmark 2 0

Total: 10 4

Other VOCs

Regulatory - HBB 29 8

Non-regulatory - HBB 21 0

No benchmark 25 0

Total: 75 8

Constituents of special interest

Regulatory - HBB 1 1

Non-regulatory - HBB 1 1

No benchmark 0 0

Total: 2 2

Sum of organic and special-interest constituents

Regulatory - HBB 48 15

Non-regulatory - HBB 55 6

No benchmark 118 5

Total: 221 26
Status and Understanding of Water Quality 31

sac11-0401_fig 12

10

1

0.1

0.01

0.001

0.0001

0.00001

Maximum relative-concentration, dimensionless

DBCP

EDB

PCE

NDMA

Perchlorate

Atrazine cis-1,2-DCE

TCE

Chloroform

1,1-DCA

Bromodichloromethane

Bromoform

Dibromochloromethane

1,2,3-TCP

1,2-DCP

Simazine

Diuron

Dinoseb

Bromacil

Tebuthiuron

Hexazinone

Arsenic

Uranium

Vanadium

Barium

Molybdenum

Strontium

Selenium

Boron

Fluoride

Chromium

Lead

Nickel

Aluminum

Copper

Cadmium

Antimony

Beryllium

Nitrate-N

Ammonia-N

Nitrite-N

Chloride (upper)

Sulfate (upper)

Zinc

Manganese

Iron

TDS (upper)

SC Uranium activity

Gross beta

Gross alpha

Organic and special-interest constituents Inorganic constituents

Volatile organic

compounds

Fumigants

Pesticides

Special interest

Nutrients

Inorganic

Inorganic-SMCL

Radioactive

Moderate

Low

Moderate

High

PCE Constituents with analyses in >20 grid wells and wells are spatially representative–

Name and center of symbol is location of data unless indicated by following location line: 

Constituent with analyses in <20 grid wells and wells are not spatially representative–

Name and center of symbol is location of data unless indicated by following location line:

NDMA

cis-1,2-DCE, cis-1,2-dichloroethene; DBCP, 1,2-dibromo-3-chloropropane; EDB, 1,2-dibromoethane; 1,1-DCA, 1,1-dichloroethane; 1,2-DCP, 1,2-dichloropropane; 

N, as nitrogen; NDMA, N-nitrosodimethylamine; PCE, tetrachloroethene; TCE, trichloroethene; 1,2,3-TCP, 1,2,3-trichloropropane; SMCL, secondary maximum 

contaminant level; SC, specific conductance; TDS (upper), total dissolved solids; upper, upper water-quality benchmark where multiple benchmarks exist.

EXPLANATION

Abbreviations

Figure 12. Maximum relative-concentrations of constituents detected in grid wells, by type of constituent, in the 

Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.
32 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 13

Nutrients

Trace elements

Radioactive constituents

Inorganic constituents having SMCLs

Gross alpha

particle activity

Manganese

Vanadium

Uranium

Barium

Uranium

activity

Nitratenitrogen

Specific

conductance

Total dissolved

solids

0 1 2 3 4 8 10

Chloride

Arsenic

Relative-concentration, dimensionless

Low Moderate High

Low Moderate High

Low Moderate High

High

High

High

High

Low Moderate High

Figure 13. Relative-concentrations of selected nutrients, trace elements, radioactive 

constituents, and inorganic constituents with secondary maximum contaminant levels detected 

in grid wells, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 33

Although uranium was considered a radioactive 

constituent for the status assessment, uranium is shown as 

both a radioactive constituent and a trace element in figures 12

and 13 to demonstrate that similar results were obtained for 

comparison to the MCL-CA of 20 picocuries per liter (pCi/L) 

and the MCL-US of 30 micrograms per liter (μg/L). Similarly, 

TDS and specific conductance are both shown on figures 12

and 13 to demonstrate that similar results were obtained for 

these two measures of salinity.

Three additional constituents were selected for additional 

evaluation in the status assessment because they had moderate 

or high RCs in the datasets used for the spatially weighted 

calculations of aquifer-scale proportions: strontium, lead, and 

iron (table 8). Strontium was included because it was reported 

at a high RC in one of the understanding wells. Lead and iron 

were included because they were reported at moderate or high 

RCs in the CDPH database during the 3-year interval prior to 

USGS sampling.

Aquifer-scale proportions for the constituents selected for 

additional evaluation in the status assessment are summarized 

in table 8. Spatially weighted high aquifer-scale proportions 

fell within the 90% confidence intervals for their respective 

grid-based aquifer high proportions for all constituents 

except iron, providing evidence that the grid-based approach 

yields statistically equivalent results to the spatially weighted 

approach. Aquifer-scale proportions for classes of inorganic 

constituents are summarized in table 9A.

For any inorganic constituent having health-based 

benchmarks (nutrients, trace elements, and radioactive 

constituents), 37% of the primary aquifer system had high 

RCs of at least one constituent, 30% had moderate values, 

and 33% had low values (table 9A). High RCs of nutrients, 

trace elements, and radioactive constituents all contributed to 

the high aquifer-scale proportions for inorganic constituents. 

For any inorganic constituent having non-health-based 

benchmarks (SMCL constituents), 6.7% of the primary 

aquifer system had high RCs of at least one constituent 

(table 9A). High RCs of TDS accounted for most of the high 

aquifer-scale proportion.

Nutrients

Nitrate was the only nutrient detected at moderate or high 

RCs in the study unit (table 8). Nitrate was detected at high 

RCs in 6.7% of the primary aquifer system and at moderate 

RCs in 20% (table 9A; fig. 13). Wells with high and moderate 

RCs of nitrate were distributed across the study unit (fig. 14).

Factors Affecting Nitrate

Groundwater age, depth, and geochemical conditions 

were the most significant explanatory factors related to nitrate 

concentrations. Nitrate concentrations were significantly 

higher in wells with modern groundwater, compared to 

pre-modern groundwater (table 10A), and had significant 

negative correlations with well depths and depths to top of 

perforations (table 10B; fig. 15A). All of the wells with high or 

moderate RCs of nitrate had depth to top of perforations less 

than or equal to 240 ft below land surface (fig. 15A). Nitrate 

concentrations were significantly higher in wells perforated 

above/across the Corcoran Clay compared to wells perforated 

below the Clay or wells east of the Clay (table 10A), likely 

because all of the wells classified as above/across the 

Corcoran had depths to top of perforations less than 240 ft. 

Nitrate concentrations were not significantly associated with 

lateral position (table 10B).

Nitrate concentration had a significant positive 

correlation with dissolved oxygen concentration and TDS 

(figs. 16A,B), and a negative correlation with pH (table 10B). 

These correlations likely reflect the correlations between 

geochemical conditions and well depth—dissolved oxygen 

had a significant negative correlation and pH a significant 

positive correlation with depth to top of perforations 

(table 6B). Denitrification of nitrate to nitrogen gas and 

intermediate products has been identified in other areas 

of the eastern San Joaquin Valley (McMahon and others, 

2008; Landon and others, 2010). In these studies, however, 

denitrification was associated with reducing conditions—

conditions that are rare in the Madera-Chowchilla study unit 

(fig. 11A). Thus, the low RCs of nitrate found in deep wells 

with mixed and pre-modern, oxic groundwater (fig. 16A) and 

found in groundwater with low RCs of TDS (fig. 16B) likely 

reflect the initial nitrate concentrations in the groundwater 

recharge. Modern recharge appears to have a much wider 

range of nitrate concentrations.

The associations between higher nitrate concentrations, 

shallower wells, well-oxygenated conditions, higher TDS, and 

recent (modern) recharge are similar to those found in other 

studies of the eastern San Joaquin Valley (Burow and others, 

1998a,b; Dubrovsky and others, 1998). These other studies 

also reported significant positive correlations between nitrate 

concentrations and percentage of agricultural land use in the 

vicinity of wells. Evaluation of historical datasets for nitrate 

concentrations in shallow groundwater (<200 ft) in the eastern 

San Joaquin Valley indicated that nitrate concentrations 

increased significantly from the 1950s to the 1980s, which 

approximately correlates with the increase in the amount of 

nitrate fertilizer applied in the eastern San Joaquin Valley 

(Dubrovsky and others, 1998; Burow and others, 2007).

Nitrate concentrations were not correlated with 

percentage of agricultural land use and were inversely 

correlated with percentage of urban land use in the MaderaChowchilla study unit (table 10B). The inverse correlation 

to urban land use may be explained by the association 

between more urbanized areas with greater population 

densities and deeper wells (see appendix B). The lack of 

correlation between nitrate and agricultural land use may be 

explained by the relatively large number of deep wells with 

pre-modern groundwater sampled for this study (fig. 15A). 

Previous USGS studies in the eastern San Joaquin Valley have 

focused primarily on shallower parts of the aquifer system 

and therefore sampled a greater proportion of wells receiving 

modern recharge.
34 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project Table 8. Aquifer-scale proportions using grid-based and spatially weighted methods for those constituents that met criteria for additional evaluation in the status assessment, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project. [Grid-based aquifer-scale proportions are based on samples collected by the USGS from 30 grid wells during April–May 2008. Spatially weighted aquifer-scale proportions and raw detection frequencies are based on samples collected by the USGS from the 30 grid wells and 5 understanding wells during April–May 2008 and data reported in the California Department of Public Health database during February 12, 2005–February 12, 2008. Relative-concentration categories: high, concentrations greater than water-quality benchmark; moderate, concentrations greater than or equal to 0.1 of benchmark but less than benchmark for organic constituents (threshold for inorganic constituents is 0.5 of benchmark); low, concentrations less than 0.1 of benchmark for organic constituents (threshold for inorganic constituents is 0.5 of benchmark). Benchmark types and values listed in table 3. Other abbreviations: USGS, U.S. Geological Survey; VOC, volatile organic compound; DBCP, 1,2-dibromo-3-chloropropane; EDB, 1,2-dibromoethane; PCE, tetrachloroethene; 123-TCP, 1,2,3-trichloropropane; TDS, total dissolved solids; THM, trihalomethane; SMCL, secondary maximum contaminant level; NA, not applicable] Constituent Raw detection frequency1 Spatially weighted aquifer-scale proportion1 Grid-based aquifer-scale proportion 90 percent confidence interval for grid-based high proportion2 Number of wells Percent moderate Percent high Number of cells Moderate proportion (percent) High proportion (percent) Number of cells Moderate proportion (percent) High proportion (percent) Lower limit (percent) Upper limit (percent) Inorganic constituents with health-based benchmarks Nutrients Nitrate 131 15 5.3 30 24 9.7 30 20 6.7 1.9 17 Trace elements Arsenic 84 4.8 9.5 30 6.0 9.8 30 10 13 5.7 26 Barium 83 4.8 1.2 30 9.0 1.1 30 10 0 0 4.4 Lead 82 1.2 0 30 0.5 0 30 0 0 0 4.4 Strontium 35 0 2.9 30 0 1.7 30 0 0 0 4.4 Uranium 62 6.4 11 30 7.2 17 30 3.3 13 5.7 26 Vanadium 42 17 2.4 30 20 1.1 30 20 3.3 0.6 12 Radioactive constituents Gross alpha particle activity 3 97 3.1 10 30 4.5 23 30 3.3 20 10 34 Uranium activity 49 6.1 16 28 4.8 20 30 3.3 17 7.9 30 Inorganic constituents with aesthetic or technical (SMCL) benchmarks Salinity indicators Chloride 91 0 2.2 30 0 4.4 30 0 3.3 0.6 12 TDS 91 8 3.3 30 17 7.8 30 13 6.7 1.9 17 Specific conductance 102 13 2.9 30 12 7.8 30 10 6.7 1.9 17 Trace elements Iron 91 1.1 11 30 1.1 7.0 30 0 0 0 4.4 Manganese 91 5.5 5.5 30 4.6 5.9 30 3.3 3.3 0.6 12 Organic and special-interest constituents Herbicides Atrazine  4 94 0 0 30 0 0 30 0 0 0 4.4 Diuron  4 36 0 0 29 0 0 29 0 0 0 4.5 Simazine  4 94 0 0 30 0 0 30 0 0 0 4.4
Status and Understanding of Water Quality 35

Constituent

Raw detection frequency1 Spatially weighted aquifer-scale proportion1 Grid-based aquifer-scale proportion 90 percent confidence interval for grid-based high proportion2

Number 

of wells

Percent 

moderate

Percent 

high

Number of 

cells

Moderate 

proportion

(percent)

High 

proportion

(percent)

Number

of cells

Moderate 

proportion

(percent)

High 

proportion

(percent)

Lower

limit

(percent)

Upper

limit

(percent)

Organic and special-interest constituents—Continued

Fumigants

DBCP 4 90 1.1 3.3 30 0 3.9 30 0 10 3.7 22

EDB 90 1.1 0 30 1.1 0 30 3.3 0 0 4.4

1,2,3-TCP  4 81 0 0 30 0 0 30 0 0 0 4.4

Other VOCs (THMs and solvents)

Chloroform 4 81 0 0 30 0 0 30 0 0 0 4.4PCE  4 79 2.5 0 30 0.4 0 30 3.3 0 0 4.4

Constituents of special interest

NDMA5 10 10 0 5 NA NA 5 NA NA NA NAPerchlorate 4 72 8.3 0 30 16 0 30 20 0 0 4.4

1 Based on most recent CDPH analysis during February 12, 2005–February 12, 2008, combined with grid-based data.2 Based on the Jeffreys interval for the binomial distribution (Brown and others, 2001).3 Gross alpha particle activities were not adjusted for uranium activity. The MCL-US for gross alpha particle activity applies to adjusted gross alpha particle activity, which is equal to measured gross alpha 

particle activity minus uranium activity.

4 Organic constituent or constituent of special interest detected in at least 10 percent of grid wells.5 Aquifer-scale proportions were not calculated for NDMA because only 5 of 30 grid cells had data for NDMA.

Table 8. Aquifer-scale proportions using grid-based and spatially weighted methods for those constituents that met criteria for additional evaluation in the status assessment, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.—Continued[Grid-based aquifer-scale proportions are based on samples collected by the USGS from 30 grid wells during April–May 2008. Spatially weighted aquifer-scale proportions and raw detection frequencies are based on samples collected by the USGS from the 30 grid wells and 5 understanding wells during April–May 2008 and data reported in the California Department of Public Health database during February 12, 2005–February 12, 2008. Relative-concentration categories: high, concentrations greater than water-quality benchmark; moderate, concentrations greater than or equal to 0.1 of benchmark but less than benchmark for organic constituents (threshold for inorganic constituents is 0.5 of benchmark); low, concentrations less than 0.1 of benchmark for organic constituents (threshold for inorganic constituents is 0.5 of benchmark). Benchmark types and values listed in table 3. Other abbreviations: USGS, U.S. Geological Survey; VOC, volatile organic compound; DBCP, 1,2-dibromo-3-chloropropane; EDB, 

1,2-dibromoethane; PCE, tetrachloroethene; 123-TCP, 1,2,3-trichloropropane; TDS, total dissolved solids; THM, trihalomethane; SMCL, secondary maximum contaminant level; NA, not applicable]
36 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table 9A. Aquifer-scale proportions for inorganic constituent classes, Madera-Chowchilla study unit, 2008, California GAMA 

Priority Basin Project.

[Relative-concentration categories: high, concentration of at least one constituent in group greater than water-quality benchmark; moderate, concentration 

of at least one constituent in group greater than 0.5 of benchmark and no constituents in group with concentration greater than benchmark; low, 

concentrations of all constituents in group less than or equal to 0.5 of benchmark. Abbreviations: SMCL, secondary maximum contaminant level; TDS, 

total dissolved solids; SC, specific conductance]

Constituent class

Aquifer-scale proportions

Low relativeconcentrations

(percent)

Moderate relativeconcentrations

(percent)

High relativeconcentrations

(percent)

Inorganic constituents with health-based benchmarks

Nutrients 73 20 6.7

Trace elements 1 57 30 13

Uranium and radioactive constituents 1 77 3.3 20

Any inorganic constituent with a health-based benchmark 33 30 37

Inorganic constituents with aesthetic or technical (SMCL) benchmarks

Salinity indicators (TDS, SC, chloride) 80 13 6.7

Manganese 93 3.3 3.3

Any inorganic constituent with an SMCL benchmark 77 17 6.7

1

 Uranium is not included in the trace element class.

2

 Aquifer-scale proportions for the class uranium and radioactive constituents were calculated using unadjusted gross alpha particle activity.

Table 9B. Aquifer-scale proportions for organic constituent classes, Madera-Chowchilla study unit, 2008, California GAMA 

Priority Basin Project.

[Relative-concentration categories: high; concentration of at least one constituent in group greater than water-quality benchmark; moderate, 

concentration of at least one constituent in group greater than 0.1 of benchmark and no constituents in group with concentration greater than 

benchmark; low, concentrations of all constituents in group less than or equal to 0.1 of benchmark. Abbreviation: THM, trihalomethane]

Constituent class

Aquifer-scale proportions

Not detected

(percent)

Low relativeconcentrations

(percent)

Moderate relativeconcentrations

(percent)

High relativeconcentrations

(percent)

Organic constituents with regulatory and non-regulatory health-based benchmarks

Herbicides 77 23 0 0

Fumigants 66 24 10.2 10

Solvents 90 6.7 3.3 0

THMs 83 17 0 0

Any organic constituent 47 40 3.3 10

1

 Spatially weighted
Status and Understanding of Water Quality 37

sac11-0401_fig 14

EXPLANATION

Urban land use

 Agricultural land use

Natural land use

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Equal-area randomized-sampling 

 grid cell

Relativeconcentration 

(RC) category

Measured

concentration, 

in milligrams

per liter

USGS GAMA 

Nitrate as nitrogen

Low

Moderate

High

120°30'

37°15'

36°45

37°

120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Millerton

Lake

Owens Creek wens Creek

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Madera

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake

CDPH 

≤5 

>5 and ≤10 

>10

Mendota

Friant

Fresno

Madera

Chowchilla

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

Figure 14. Concentrations of nitrate, as nitrogen, in USGS-GAMA wells and the most recent analysis during February 12, 

2005–February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.
38 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project Table 10A. Results of Wilcoxon rank-sum tests for differences in values of water-quality constituents between samples classified into groups by position relative to the Corcoran Clay, groundwater age, or well depth, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project. [Relation of median values in pairs of sample groups tested shown for Wilcoxon rank-sum tests in which the two populations were determined to be significantly different (two-sided test) on the basis of p-values (not shown) less than threshold value (α) of 0.05; ns, test indicates no significant difference between the pair of sample groups. Position relative to Corcoran Clay: Abv/Ac, bottom of perforations above Corcoran Clay or well is perforated across the Corcoran Clay; East, well located east of Corcoran Clay extent in subsurface; Blw, topmost perforation is below the Corcoran Clay. Age classification: Mod, modern; Mix, mixed; Pre, pre-modern. Depth classification: Shal, entire perforated interval and well depth ≤ 280 ft, Mixed, top of perforations ≤ 280 ft; bottom of perforations and well depth > 280 ft, Deep, entire perforated interval and well depth > 280 ft. See Appendix A for more information about explanatory factor listed. Other abbreviations: TDS, total dissolved solids; THM, trihalomethane; ft, foot; sig. diff., significant differences; <, less than; >, greater than] Water-quality constituents Position relative to Corcoran Clay Age classification Depth classification Abv/Ac vs Blw (sig. diff.) Abv/Ac vs East (sig. diff.) Blw vs East (sig. diff.) Mod vs Pre (sig. diff.) Mod vs Mix (sig. diff.) Mix vs Pre (sig. diff.) Shal vs Deep (sig. diff.) Shal vs Mix (sig. diff.) Deep vs Mix (sig. diff.) Inorganic constituents with health-based benchmarks Nitrate Abv/Ac > Blw Abv/Ac > East ns Mod > Pre ns ns Sha l > Deep Shal > Mix ns Arsenic ns ns ns ns ns ns Deep > Shal ns Deep > Mix Vanadium ns ns ns ns ns ns ns ns ns Gross alpha particle activity Abv/Ac > Blw Abv/Ac > East ns Mod > Pre Mod > Mix ns ns ns Mix > Deep Uranium activity Abv/Ac > Blw Abv/Ac > East ns Mod > Pre Mod > Mix ns Shal > Deep ns ns Inorganic constituents with aesthetic or technical (SMCL) benchmarks Chloride Abv/Ac > Blw Abv/Ac > East Blw > East Mod > Pre ns ns ns ns ns TDS Abv/Ac > Blw Abv/Ac > East ns Mod > Pre ns ns Shal > Deep ns Mix > Deep Manganese ns ns ns Pre > Mod ns Pre>Mix ns ns ns Organic constituents and constituent of special interest Sum of herbicides ns ns ns Mod > Pre Mod > Mix ns Shal > Deep ns Mix > Deep Sum of fumigants ns ns ns ns ns ns ns ns ns Sum of THMs ns ns ns Mod > Pre ns ns ns ns ns Sum of solvents ns ns ns ns Mod > Mix ns ns ns ns Perchlorate ns ns ns ns ns ns Shal > Deep ns ns
Status and Understanding of Water Quality 39

Table 10B. Results of Spearman’s tests of correlations between selected potential explanatory factors and water-quality constituents, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.[Abbreviations: ρ (rho), Spearman’s correlation statistic; ρ values are shown for tests in which the variables were determined to be significantly correlated on the basis of p-values (significance level of the Spearman’s test) less than threshold value (α) of 0.05 (not shown); ns, Spearman’s test indicates no significant correlation between factors; black text, significant positive correlation; red text, significant negative correlation. FractCaMg, calcium plus magnesium in milliequivalents divided by sum of calcium, magnesium, sodium, and potassium in milliequivalents]

ρ

Grid wells Grid and understanding wells

Percent 

agricultural 

land use 

Percent 

natural 

land use 

Percent 

urban 

land use 

Lateral 

position 

Well 

depth 

Depth 

to top of 

perforation 

pH 

Dissolved 

oxygen 

concentration 

Fract-CaMg

Inorganic constituents with health-based benchmarksNitrate ns ns –0.41 ns –0.49 –0.48 –0.56 0.73 0.66

Arsenic ns ns ns ns ns ns 0.44 –0.36 ns

Vanadium ns ns ns ns ns ns ns ns ns

Gross alpha particle activity ns –0.40 ns –0.46 ns –0.60 ns 0.36 0.46

Uranium activity 0.38 ns ns ns ns –0.61 –0.45 0.47 0.63

Inorganic constituents with aesthetic or technical (SMCL) benchmarksChloride 0.59 –0.63 ns –0.69 ns ns ns 0.38 ns

Total dissolved solids ns ns ns ns –0.43 –0.51 –0.43 0.42 0.62

Manganese ns ns 0.54 ns ns 0.37 0.41 ns ns

Organic constituents and constituent of special interestSum of herbicides ns ns ns ns ns –0.46 –0.43 0.43 0.46

Sum of fumigants ns ns ns ns ns ns ns ns ns

Sum of trihalomethanes ns ns 0.52 ns ns ns ns ns ns

Sum of solvents ns ns 0.43 ns ns ns ns ns ns

Perchlorate ns ns ns ns –0.41 ns –0.38 0.62 0.45
40 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 15abcde

A B

D

E

C

1086420 12 10

0 20 40 60 80 100 120 0 10 20 30 40 50

0 5 15 20 25

100

0

200

300

400

500

600

100

0

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface

100

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface Depth to top of perforation, in feet below land surface

100

200

300

400

500

600

0

100

200

300

400

500

600

Depth to top of perforation, in feet below land surface

Depth to top of perforation, in feet below land surface

Uranium, in picocuries per liter

0 250 500 750 1,000 1,250 4,000 5,000

Total dissolved solids, in milligrams per liter

Vanadium, in micrograms per liter

Nitrate, as nitrogen, in milligrams per liter Arsenic, in micrograms per liter

Low Moderate High Low Moderate High

Low Moderate High

Low Moderate High

Low Moderate High

EXPLANATION

Modern Mixed Pre-modern

Groundwater age classification

East

Below

Above/across

Position relative to 

Corcoran Clay

Figure 15. Relation between concentrations of (A) nitrate, (B) arsenic, (C) vanadium, (D) uranium activity, 

and (E) total dissolved solids with depth to top of perforations in wells, Madera-Chowchilla study unit, 2008, 

California GAMA Priority Basin Project.
Status and Understanding of Water Quality 41

Figure 16. Relations of (A) nitrate, as nitrogen concentration, 

and dissolved oxygen concentration, and (B) nitrate, as nitrogen 

concentration, and total dissolved solids, Madera-Chowchilla 

study unit, 2008, California GAMA Priority Basin Project.

sac11-0401_fig 16abcde

A

B

40

30

12

10

8

6

4

2

0

40

30

12

10

8

6

4

2

0

0 2 4 6 8 10

Low

Moderate

Low

Moderate

Moderate

High

Moderate

High

Low

ModerateModerate

High

Nitrate, as nitrogen, in milligrams per liter Nitrate, as nitrogen, in milligrams per liter

Dissolved oxygen, in milligrams per liter

0 200 400 600 800 1,000 1,200 4,000 5,000

Total dissolved solids, in milligrams per liter

p<0.001

p<0.001

EXPLANATION

Modern Mixed Pre-modern

Groundwater age classification

Shallow (Entire perforated interval ≤ 280 feet)

Mixed (Top of perforated interval ≤ 280 feet; 

 Bottom of perforated interval > 280 feet) 

Deep (Entire perforated interval > 280 feet)

Unknown

Well depth 

classification

Trace Elements

The constituent class trace elements includes a variety 

of metallic and non-metallic constituents that typically are 

present in groundwater at concentrations less than 1 mg/L. 

Trace elements with health-based benchmarks had high 

RCs in 13% of the primary aquifer system, moderate RCs in 

30%, and low RCs in 57% (table 9A). Arsenic accounted for 

most of the high and moderate RCs of trace elements with 

health-based benchmarks (table 8; fig. 13).

Arsenic was detected at high RCs in 13% of the 

primary aquifer system and at moderate RCs in 10% 

(table 8, fig. 13). High and moderate RCs of arsenic 

primarily occurred in the northern part of the study unit 

(fig. 17). Vanadium was detected at high RCs in 3.3% of 

the primary aquifer system and at moderate RCs in 20% 

(table 8, fig. 13). The well with a high RC of vanadium was 

in the northwestern corner of the study unit, and wells with 

moderate RCs of vanadium were distributed throughout 

the study unit (fig. 18). Strontium was detected at high 

RCs in 1.7% of the primary aquifer system (spatially 

weighted), and at moderate RCs in 0%. The USGS-GAMA 

understanding well with a high RC of strontium was located 

in the northwestern corner of the study unit in the same 

sample as the high RC value of barium (fig. 19). Barium 

was detected at high RCs in 1.1% of the primary aquifer 

system (spatially weighted) and at moderate RCs in 10%. 

The high and moderate RCs of barium were predominantly 

located on the western side of the study unit (fig. 19). 

Uranium is discussed with radioactive constituents. 
42 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 17. Concentrations of arsenic in USGS-GAMA wells and the most recent analysis during February 12, 2005–

February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.

sac11-0401_fig 17

CDPH 

≤5 

>5 and ≤10 

>10

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units Arsenic

Relativeconcentration 

(RC) category

Measured

concentration, 

in micrograms

per liter

USGS GAMA 

Low

Moderate

High

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

H.V. Eastman

Lake
Status and Understanding of Water Quality 43

sac11-0401_fig18

CDPH 

≤25 

>25 and ≤50 

>50

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units Vanadium

Relativeconcentration 

(RC) category

Measured

concentration, 

in micrograms

per liter

USGS GAMA 

Low

Moderate

High

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake

Figure 18. Concentrations of vanadium in USGS-GAMA wells and the most recent analysis during February 12, 2005–

February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.
44 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 19. Concentrations of barium in USGS-GAMA wells and the most recent analysis during February 12, 2005–

February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.

sac11-0401_fig19

CDPH 

≤500 

>500 and ≤1,000 

>1,000

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units Barium

Relativeconcentration 

(RC) category

Measured

concentration, 

in micrograms

per liter

USGS GAMA 

Low

Moderate

High

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake
Status and Understanding of Water Quality 45

Factors Affecting Arsenic

Higher arsenic concentrations were significantly 

correlated with wells classified as deep wells (table 10A), 

but were not significantly correlated with either well depth 

or depth to top of perforations (table 10B; fig. 15B). Arsenic 

concentrations were positively correlated with pH and 

negatively correlated with dissolved oxygen (table 10B; 

fig. 20).

Previous investigations of arsenic in the San Joaquin 

Valley and literature reviews have attributed elevated arsenic 

concentrations in groundwater to two mechanisms (Welch 

and others, 2000, 2006; Belitz and others, 2003; Stollenwerk, 

2003; Izbicki and others, 2008; Jurgens and others, 2008; 

Landon and others, 2010). One is the release of arsenic from 

dissolution of iron or manganese oxyhydroxides under iron- or 

manganese-reducing conditions. The other is desorption from 

(or inhibition of sorption to) aquifer sediments under oxic 

conditions with increasing pH. In the Madera-Chowchilla 

study unit, evidence for the first mechanism includes 

association of high RCs of arsenic with manganese-reducing 

conditions. The only USGS-GAMA sample with dissolved 

oxygen less than 0.5 mg/L had manganese-reducing conditions 

(table A5) and had the highest arsenic concentrations 

measured in USGS-GAMA samples (fig. 20A). This well was 

located in the northwest corner of the study unit. Elsewhere in 

the San Joaquin Valley, groundwater with high and moderate 

RCs of arsenic commonly occurs in the axial trough of the 

Valley, resulting in significant correlation between arsenic and 

lateral position (Belitz and others, 2003; Bennett and others, 

2010; Landon and others, 2010). Arsenic was not significantly 

correlated with lateral position in the Madera-Chowchilla 

study unit because, unlike elsewhere in the San Joaquin Valley, 

the axial trough in the Madera-Chowchilla study unit is not 

dominated by anoxic oxidation-reduction conditions (fig. 11A).

Evidence for the second mechanism includes association 

of high and moderate RCs of arsenic with high pH in some 

wells (fig. 20B). Although the correlation between arsenic 

and pH was statistically significant (table 10B), there were 

many samples with pH values greater than 7.5 that had 

low RCs of arsenic. Of the six oxic samples with arsenic 

concentrations greater than 5 μg/L, only two have pH ≥ 8.0, 

and of the five samples with pH ≥ 8.0, only two have arsenic 

concentrations greater than 5 μg/L, suggesting pH-controlled 

sorption processes alone are not a sufficient explanation for 

the distribution of elevated arsenic concentrations in MaderaChowchilla study unit groundwater.

The spatial distribution of elevated arsenic suggests that 

the composition of aquifer sediments is also a controlling 

factor. In the Madera-Chowchilla study unit, six of the seven 

USGS-GAMA samples with arsenic concentrations greater 

than 5 μg/L were from sites within 5 miles of the Chowchilla 

River along the northern margin of the study unit at lateral 

positions ranging from 0.05 to 0.92 (figs. 8, 17). Wells 

with high RCs of arsenic and lateral positions ranging from 

0.1 to 0.8 also were close to the Chowchilla River in the 

Central Eastside study unit immediately to the north of the 

Madera-Chowchilla study unit (Landon and others, 2010).

Sediments in the Chowchilla River alluvial fan are 

lithologically different from those in the alluvial fans from 

some of the larger rivers (Kings, San Joaquin, Merced, 

Tuolumne, Stanislaus, and Mokelumne) that compose the 

rest of the aquifer matrix in the eastern San Joaquin Valley 

(Weissmann and others, 2005). The Chowchilla River 

watershed is confined to the lower elevations of the Sierra 

Nevada foothills in an area where metamorphic rocks 

are abundant (Saucedo and others, 2000). In contrast, the 

watersheds of the large rivers, such as the San Joaquin River, 

extend to higher elevations in the Sierra Nevada and are 

dominated by granitic rocks. The difference in lithology of 

the sediment source for the Chowchilla River compared to 

the sediment sources for the other rivers is reflected in the 

compositions of soils formed on top of the fans (Weissmann 

and others, 2005).

The arsenic is weathered from minerals in the sediments 

derived from the source rocks in the foothills of the Sierra 

Nevada. In the Sierra Nevada, sulfide minerals, such as pyrite, 

that are associated with metamorphic rocks in the foothills 

generally are more abundant and contain more arsenic than 

minerals associated with the granitic rocks (Izbicki and others, 

2008). Thus, the sediments of the Chowchilla River alluvial 

fan may contain more arsenic that those of the San Joaquin 

River alluvial fan. In oxic groundwater, the sulfide minerals 

may be oxidized, releasing their arsenic into the groundwater.

The association between higher arsenic concentrations 

and deep wells suggests that residence time was also an 

important factor. Among the wells located close to the 

Chowchilla River, high and moderate RCs of arsenic primarily 

occurred in wells classified as deep. Shallow wells had low 

RCs of arsenic. The deep wells with high and moderate RCs of 

arsenic had mixed or pre-modern groundwater ages (fig. 15B). 

Arsenic was not significantly associated with groundwater age 

(table 10A) because only the deep wells near the Chowchilla 

River had elevated arsenic concentrations.
46 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Factors Affecting Vanadium

Vanadium concentrations were not significantly 

correlated with any of the explanatory factors tested 

(tables 10A,B). Wright and Belitz (2010) investigated 

the regional distribution of vanadium in groundwater in 

California and reported that high vanadium concentrations 

were almost always associated with oxic and alkaline 

groundwater conditions. This correlation was not observed 

in groundwater samples from the Madera-Chowchilla study 

unit. The groundwater sample that contained a high RC of 

vanadium had a pH value of 8.4 and contained 0.7 mg/L of 

DO; however, pH values of the six groundwater samples with 

moderate RCs of vanadium ranged from 7.0 to 8.4. Vanadium 

was not correlated with well depth factors (fig. 15C), and 

was not correlated with groundwater age, although moderate 

and high RCs occurred only in groundwater with mixed or 

pre-modern ages.

Radioactive Constituents

The MCL-US (15 pCi/L) for gross alpha particle activity 

applies to adjusted gross alpha particle activity, which is equal 

to the measured gross alpha particle activity minus uranium 

activity (U.S. Environmental Protection Agency, 2000). Data 

collected by USGS-GAMA and data compiled in the CDPH 

database are reported as gross alpha particle activity without 

correction for uranium activity. Gross alpha particle activity 

is used as a screening tool to determine whether additional 

radioactive constituents must be analyzed (California 

Department of Public Health, 2012). For regulatory purposes, 

analysis of uranium is only required if gross alpha particle 

activity is greater than 15 pCi/L; therefore, the CDPH database 

contains more data for gross alpha particle activity than for 

uranium. As a result, it is not always possible to calculate 

adjusted gross alpha particle activity. For this reason, gross 

alpha particle activity data without correction for uranium 

sac11-0401_fig 20ab

A B

0

0 2 4

Dissolved oxygen, in milligrams per liter pH

6 8 10 6.5 7.0 7.5 8.0 8.5

5

10

15

20

25

Low

Moderate

High

Low

Moderate

High

Arsenic concentration, in micrograms per liter

EXPLANATION

<5 miles 5–25 miles

Distance from Chowchilla River

Shallow (Entire perforated interval ≤280 feet)

Mixed (Top of perforated interval ≤280 feet; Bottom of perforated interval >280 feet)

Deep (Entire perforated interval >280 feet)

Unknown

Well depth classification

Figure 20. Relations of (A) dissolved oxygen and (B) pH values to arsenic concentration and distance 

from Chowchilla River, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 47

are the primary data used in the status assessments made by 

USGS-GAMA for the Priority Basin Project. Examination of 

data from samples having USGS-GAMA data for uranium and 

gross alpha particle activity indicated that, in the absence of 

data for uranium, uncorrected gross alpha particle activity data 

likely provides a more accurate estimate of the aquifer-scale 

proportions for uranium and radioactive constituents as a 

class, than does adjusted gross alpha particle activity (Miranda 

Fram, USGS California Water Science Center, written 

commun., 2012).

USGS-GAMA reports data for gross alpha particle 

activity counted 72 hours and 30 days after sample collection. 

Gross alpha particle activity in a groundwater sample may 

change with time after sample collection due to radioactive 

decay and ingrowth (activity may increase or decrease 

depending on sample composition and holding time) (Arndt, 

2010). Data from the 72-hour counts are used in this report.

Most data for uranium in the CDPH database are reported 

as activities in units of pCi/L, and the majority of uranium 

data gathered by USGS-GAMA are reported as concentrations 

in units of micrograms per liter. The factor used to convert 

uranium mass concentration to uranium activity depends on 

the isotopic composition of the uranium (U.S. Environmental 

Protection Agency, 2000). This report uses a conversion factor 

of 0.79.

Radioactive constituents with health-based benchmarks 

were present at high RCs in 20% of the primary aquifer 

system, and at moderate and low RCs in 3.3% and 77%, 

respectively (table 9A). Gross alpha particle activity and 

uranium activity were the radioactive constituents detected at 

high or moderate RCs in the primary aquifer system (table 8).

Gross alpha particle activity was detected at high RCs 

in 20% of the primary aquifer system, and uranium activity 

was detected at high RCs in 17%; moderate RCs of both were 

present in 3.3% of the primary aquifer system (table 8). Of the 

six grid wells with high RCs of gross alpha particle activity, 

five had high RCs of uranium activity and one had moderate 

RC. A high RC for radium was reported in the CDPH database 

for one well during the 3-year period February 2005–February 

2008 (table 5), but the high value was not from the most recent 

sample; therefore, no high RC is reported using the spatially 

weighted approach (table 8).

Factors Affecting Uranium and Gross Alpha 

Particle Activity

Groundwater with high and moderate RCs of uranium 

activity was primarily from wells located in the western 

portion of the study unit (fig. 21). Uranium and gross alpha 

particle activity were closely correlated (Spearman’s test; 

p<0.001, rho=0.73), and the patterns of significant correlations 

with potential explanatory factors were similar for the two 

constituents (tables 10A,B). The following discussion is 

limited to factors affecting uranium.

Geochemical conditions, groundwater age, and depth 

were the most significant explanatory factors related to 

uranium activities. Uranium activities were significantly 

greater in modern groundwater than in pre-modern 

groundwater, and in wells classified as shallow or mixed 

than in wells classified as deep (table 10A). Uranium was 

significantly negatively correlated with depth to the top of 

perforation (table 10B; fig. 15D), and positively correlated 

with dissolved oxygen concentration (table 10B).

This significant association between higher uranium 

activities, modern-age groundwater, oxic conditions, and 

shallow depths in the Madera-Chowchilla study unit is the 

same as the pattern observed in the eastern San Joaquin Valley 

as a whole (Jurgens and others, 2009a). Jurgens and others 

(2009a) attributed the elevated uranium in shallow modern-age 

groundwater to enhanced desorption of uranium from soil 

and aquifer sediments by recharge of water used for irrigation 

that has high bicarbonate concentrations. The bicarbonate is 

derived from biological production of carbon dioxide in the 

soil zones of irrigated landscapes. The groundwater budget 

in the eastern San Joaquin Valley is dominated by irrigation 

recharge and pumping (fig. 4; Faunt, 2009), which results in 

transport of irrigation recharge to depths in the aquifer system 

tapped by public-supply wells.

In the Madera-Chowchilla study unit, uranium activity 

had a significant positive correlation with bicarbonate 

(rho=0.800, p<0.001) (fig. 22), which is consistent 

with desorption of uranium from aquifer sediments by 

complexation with dissolved bicarbonate. Uranium also had 

a significant positive correlation with calcium (rho=0.678, 

p<0.001) and with Fract-CaMg (table 10B), which may 

indicate that part of the increase in bicarbonate is caused by 

dissolution of soil and sedimentary calcite.

Although all of the high RCs and most of the moderate 

RCs of uranium occurred in wells located in the western part 

of the study unit, uranium was not significantly correlated 

with lateral position (table 10A). However, the statistical test 

was made using only the grid wells; uranium had a significant 

negative correlation with lateral position when the grid and 

understanding wells were considered (Spearman’s test; 

p=0.020, rho=–0.39).
48 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 21. Activities of uranium in USGS-GAMA wells and the most recent analysis during February 12, 2005–February 12, 2008, for 

CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.

sac11-0401_fig 21

CDPH 

≤10 

>10 and ≤20

>20

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units Uranium activity

Relativeconcentration 

(RC) category

Measured

activity, 

in picocuries

per liter

USGS GAMA 

Low

Moderate

High

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake

Fresno

Friant

Mendota

Chowchilla

Madera

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)
Status and Understanding of Water Quality 49

Figure 22. Relation of bicarbonate concentrations and uranium 

activities, Madera-Chowchilla study unit, 2008, California GAMA 

Priority Basin Project.

sac11-0401_fig 22

Low

Moderate

High

Uranium activity, in picocuries per liter

10

0

20

30

40

50

60

70

0 100 200 300 400 500 600 700

EXPLANATION

Modern Mixed Pre-modern

Groundwater age classification

Shallow (Entire perforated interval ≤ 280 feet)

Mixed (Top of perforated interval ≤ 280 feet; 

 Bottom of perforated interval > 280 feet) 

Deep (Entire perforated interval > 280 feet)

Unknown

Well depth 

classification

Bicarbonate concentration, in milligrams per liter

Constituents with SMCL Benchmarks

Constituents with SMCL benchmarks were present at 

high RCs in 6.7% of the primary aquifer system, at moderate 

RCs in 17%, and at low RCs in 77% (table 9A). The 

constituent most commonly responsible for the high RCs was 

TDS, which was present at high RCs in 6.7% of the primary 

aquifer system (table 8). Chloride and manganese were each 

present at high RCs in 3.3% of the primary aquifer system, 

and moderate RCs of manganese were observed in 3.3% of 

the primary aquifer system. Nearly all of the wells with high 

and moderate RCs of TDS were located in the western portion 

of the study unit (fig. 23). Two of the wells with high RCs of 

TDS also had high RCs of chloride, and one of these wells 

also had a high RC of manganese. These two wells were 

located in the northwestern corner of the study unit.

All detections of iron in grid and understanding wells 

had low RCs, thus the grid-based calculation yielded a high 

aquifer-scale proportion of 0%. However, iron was reported at 

high RCs in 13 wells in the CDPH database, and the resulting 

spatially weighted high aquifer-scale proportion, 7.0%, was 

outside of the 90% confidence interval for the grid‐based 

high aquifer-scale proportion (table 8). The 13 CDPH 

wells with high RCs of iron were distributed throughout 

the study unit, and of those 13, only 4 also had high RCs of 

manganese. Because iron reduction typically occurs at lower 

oxidation-reduction potentials than manganese reduction 

(Appelo and Postma, 2005; McMahon and Chapelle, 2008), 

one would not expect to find groundwater with elevated iron 

concentrations without elevated manganese concentrations. 

As discussed in appendix B, these results may be due to the 

sampling methods typically used for samples collected for 

analysis of trace elements. Anoxic conditions, including 

elevated iron and manganese concentrations, have been 

found historically in the southwestern portion of the study 

unit (Mitten and others, 1970). Two of the wells were also 

sampled by USGS-GAMA (MADCHOW-05, -09). Specific 

conductance in MADCHOW-05 was 149 microsiemens 

per centimeter at 25 degrees Celsius (μS/cm at 25 ̊C) 

in November 2007 (CDPH) and 272 μS/cm at 25 ̊C in 

April 2008 (USGS-GAMA), and for MADCHOW-09, specific 

conductance was 310 μS/cm at 25 ̊C in January 2006 and 

760 μS/cm at 25 ̊C in April 2008 (USGS-GAMA). These 

differences may indicate that water quality has changed 

over time and that high iron concentrations may not be 

representative of the current water-quality conditions.

Factors Affecting Total Dissolved Solids

Groundwater age, depth, and geochemical conditions 

were the most significant explanatory factors related to TDS 

concentrations. The pattern of correlations between TDS 

and potential explanatory factors was similar to the patterns 

shown by nitrate and uranium (tables 10A,B). Similar to 

nitrate and uranium concentrations, TDS concentrations were 

significantly higher in modern groundwater as compared to 

pre-modern groundwater, in wells with shallower depths to the 

top of perforations compared with wells perforated at deeper 

depths, and in wells classified as above/across the Corcoran 

Clay compared with other positions relative to the Clay 

(tables 10A,B; fig. 15E). TDS concentrations had significant 

positive correlations with uranium activities (rho=0.593, 

p<0.001) and nitrate concentrations (rho=0.566, p<0.001). 
50 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 23. Concentrations of total dissolved solids (TDS) in USGS-GAMA wells and the most recent analysis during February 12, 

2005–February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California GAMA Priority Basin Project.

sac11-0401_fig 23

CDPH 

≤500 

>500 and ≤1,000 

>1,000

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

Quaternary alluvial fan deposits

Quaternary basin deposits

Quaternary stream channel deposits

Tertiary semi-consolidated to consolidated sediments

Mesozoic and Paleozoic igneous and metamorphic rocks

Corcoran Clay extent in subsurface

Geologic units Total dissolved solids

Relativeconcentration 

(RC) category

Measured

concentration, 

in milligrams

per liter

USGS GAMA 

Low

Moderate

High

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)
Status and Understanding of Water Quality 51

Together, these correlations suggest that increases in TDS, 

nitrate, and uranium may be related to similar processes. The 

higher concentrations of TDS (and nitrate and uranium) in 

shallower groundwater imply greater loading of dissolved 

constituents from the surface to groundwater in recent 

decades. This greater loading may be the result of several 

factors, including increases in recharge and fluctuation of 

water levels, changes in soil and soil pore-water chemistry 

caused by historical changes in land use, use of fertilizers, 

soil amendments and other chemicals at the land surface, and 

increases in consumptive water use by vegetation. 

Previous studies of eastern San Joaquin Valley 

groundwater have found negative correlations between 

TDS and lateral position (Mendenhall and others, 1916; 

Bertoldi and others, 1991; Bennett and others, 2010; Landon 

and others, 2010). Groundwater in the eastern alluvial fans 

typically has lower TDS concentrations than groundwater 

in the basin area. TDS was not correlated with lateral 

position (grid wells only) in the Madera-Chowchilla study 

unit (table 10B); however, for both grid and understanding 

wells, TDS had a significant negative correlation with lateral 

position (rho= –0.35, p=0.040) because the understanding 

wells typically were shallower than the grid wells (fig. 7). 

For the 24 wells classified as shallow or mixed depth, TDS 

was significantly negatively correlated with lateral position 

(rho=–0.71, p<0.001). The increase in TDS towards the 

center of the Valley may reflect a variety of natural and 

anthropogenic processes which include historical groundwater 

discharge and evapotranspiration patterns, irrigation return 

and irrigation recycling, addition of salts from anthropogenic 

activities at or near the land surface, rock/water interaction 

along regional groundwater flow paths, and upwelling of 

more saline groundwater influenced by interactions with deep 

marine or lacustrine sediments near the valley trough.

Detailed analysis of the processes accounting for 

increases in TDS is beyond the scope of this report, although 

the relations between TDS concentrations and geochemical 

characteristics of the groundwater may provide some 

insight into the sources of salinity. Major ion groundwater 

chemistry is represented on a Piper diagram, which shows the 

proportions of the major cations (calcium, magnesium, and 

sodium plus potassium) and the major anions (bicarbonate, 

sulfate, and chloride) on a charge-equivalent basis (fig. 24; 

Piper, 1944; Hem, 1992). The majority of the MaderaChowchilla groundwater samples have calcium or calcium 

plus sodium as the primary cations and bicarbonate as the 

primary anion. Samples from four wells have sodium as 

the primary cation and bicarbonate as the primary anion, 

and samples from three wells have chloride or chloride 

plus bicarbonate as the primary anions. This distribution of 

geochemical types is similar to that observed in the Central 

Eastside study unit (Landon and others, 2010) and in the 

Northern San Joaquin Valley (Izbicki and others, 2006; 

Bennett and others, 2010). Geographically, groundwater in the 

eastern alluvial fans typically has calcium plus sodium as the 

primary cations and bicarbonate as the primary anion, whereas 

groundwater in the basin area has a variety of compositions, 

with calcium and/or sodium as the primary cations and 

bicarbonate and/or chloride as the primary anions (Bertoldi 

and others, 1991).

The distribution of groundwater samples shown on the 

lower left portion of the Piper diagram shows a distinction 

between groundwater chemistry in wells with lower TDS and 

wells with higher TDS. Wells with higher TDS (>500 mg/L) 

yield calcium-dominated bicarbonate water that typifies 

the shallow and mixed depth wells. Wells with lower TDS 

(<500 mg/L) yield sodium-potassium bicarbonate water that 

mainly typifies the deeper wells.

Although TDS concentrations had a significant positive 

correlation with dissolved oxygen and a significant negative 

correlation with pH (table 10B), the only well with anoxic 

groundwater (MADCHOW-12) also had a high RC of 

TDS (1,070 mg/L) and a pH of 8.0. MADCHOW-12 is 

located in the the northwest corner of the basin area of 

study unit and is perforated entirely below the Corcoran 

Clay (table A2; figs. 2, 3). The primary cation in the sample 

from MADCHOW-12 is sodium, and the primary anion is 

chloride (fig. 24). The chloride-to-iodide ratio in this sample 

is low compared to the other samples from the MaderaChowchilla study unit and is in the range of chloride-to-iodide 

ratios of groundwater affected by interactions with marine 

sediments (Izbicki and others, 2006). One sample from a 

well perforated entirely below the Corcoran Clay in the 

basin area of the Central Eastside GAMA study unit located 

immediately north of the Madera-Chowchilla GAMA study 

unit had a similar anion composition (Landon and others, 

2010). Landon and others (2010) concluded that this sample 

may represent upwelling of deeper saline waters from the 

marine sedimentary deposits beneath the continental deposits 

that compose the freshwater aquifer system as a result of 

upward hydraulic gradients at the distal end of the regional 

groundwater flow system.

With the exception of MADCHOW-12, all of the 

samples with high or moderate RCs of TDS were perforated 

above and (or) across the Corcoran Clay (fig. 15E) and were 

oxic. All samples with high or moderate RCs of TDS had 

mixed or modern groundwater ages (fig. 15E). TDS had a 

significant positive correlation with Fract-CaMg (table 10B). 

Groundwater samples with low RCs of TDS generally have 

cation compositions closer to the sodium plus potassium apex 

(lower Fract-CaMg) of a Piper diagram, and groundwater 

samples with moderate or high RCs of TDS lie furthest from 

the sodium plus potassium apex (higher Fract-CaMg) (fig. 24). 

One possible mechanism for this elevated TDS and FractCaMg in modern, shallow groundwater may be enhanced 

dissolution of calcite from soils by irrigation recharge, 

similar to the mechanism responsible for increased uranium 

concentrations in modern, shallow groundwater in the eastern 

San Joaquin Valley (Jurgens and others, 2009a).
52 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 24

Total dissolved solids (mg/L)

EXPLANATION

<500

 0 

 20 

 40 

 60 

 80 

 100 

Magnesium

Sulfate plus Chloride

 20 

 0 

 40 

 60 

 80 

Percent

 100 

Sulfate

Calcium plus Magnesium

Percent

 100 

 80 

 60 

 40 

 20 

 0 

 100 

 80 

 60 

 40 

 20 

 0 

Calcium Chloride, Fluoride, Nitrite plus Nitrate

 100 

 80 

 60 

 40 

 20 

 0 

 0 

 20 

 40 

 60 

 80 

 100 

 0 

 20 

 40 

 60 

 80 

 100 

 100 

 80 

 60 

 40 

 20 

 0 

 100 

 80 

 60 

 40 

 20 

 0 

Bicarbonate

 0 

 20 

 40 

 60 

 80 

 100 

Shallow (Entire perforated interval 280 feet)

Mixed (Top of perforated interval 280 feet; Bottom of perforated interval >280 feet)

Deep (Entire perforated interval >280 feet)

Unknown

Well depth classification

>1,000

(anoxic)

>1,000

(oxic)

<1,000

>500

Percent

Sodium plus Potassium

Figure 24. Major-ion composition and total dissolved solids concentrations for groundwater samples from grid and 

understanding wells, 2008, Madera-Chowchilla study unit, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 53

Factors Affecting Manganese

Manganese concentrations were significantly higher 

in pre-modern groundwater than in modern or mixed-age 

groundwaters, and manganese concentrations were positively 

correlated with urban land use, pH, and depth to the top of 

perforations (tables 10A, B). Manganese concentrations 

were not correlated with dissolved oxygen concentrations 

(table 10B) possibly because the only sample with a high RC 

for manganese (MADCHOW-12) was also the only sample 

with dissolved oxygen concentration less than 0.5 mg/L 

(table A5). All 10 samples with manganese concentrations 

greater than 3 μg/L were from wells located within 5 miles of 

the Chowchilla River, similar to the areal distribution of wells 

with moderate and high RCs of arsenic (fig. 17).

Organic and Special-Interest Constituents

For this report, the organic and special-interest 

constituents are organized by constituent class: pesticides, 

VOCs, and special interest. Volatile organic compounds 

(VOCs) are present in paints, solvents, fuels, fuel additives, 

refrigerants, fumigants, and disinfected water, and are 

characterized by their tendency to evaporate. VOCs typically 

persist longer in groundwater than in surface water because 

groundwater is isolated from the atmosphere. Pesticides 

include herbicides, insecticides, and fumigants, and are 

applied to crops, gardens, lawns, around buildings, and along 

roads to help control unwanted vegetation (weeds), insects, 

fungi, and other pests in agricultural, urban, and suburban 

settings. Fumigants can be classified as VOCs because of 

their tendency to evaporate, but also can be classified as 

pesticides because they are used to control pests. Fumigants 

are of interest in California because of their historical use 

on vineyards and orchards. The constituents of special 

interest group includes two chemically unrelated constituents 

(perchlorate and N-nitrosodimethylamine) that are of interest 

in California because they have recently been detected in 

groundwater because of advances in analytical methods.

USGS-GAMA included analysis of a large number of 

organic constituents, many of which are not subject to any 

regulation in drinking water, and used analytical methods with 

lower detection limits than required for regulatory sampling. 

In the Madera-Chowchilla study unit, however, the majority 

of organic constituents detected were already subject to 

drinking-water regulations. Of the 134 pesticides and pesticide 

degradates analyzed, 12 were detected in at least one well 

(table 7B). Seven of those 12 had regulatory or non-regulatory 

health-based benchmarks. Of the five pesticide constituents 

detected with no benchmarks, three were degradates of parent 

compounds with benchmarks (table 4). Of the 10 fumigants 

analyzed, 4 were detected in at least one well, and all 4 had 

health-based benchmarks. Of the 75 other VOCs analyzed, 

8 were detected in at least one of the wells, and all have 

regulatory health-based benchmarks. Of the two specialinterest constituents, both were detected, and both have healthbased benchmarks. Of the 118 organic and special-interest 

constituents with no health-based benchmarks analyzed in this 

study unit, 5 were detected in groundwater.

Figure 25 summarizes the study-unit detection 

frequencies and maximum RCs for organic and special-interest 

constituents detected in the Madera-Chowchilla study unit. 

The fumigant 1,2-dibromo-3-chloropropane (DBCP), the 

solvent tetrachloroethene (PCE), and perchlorate were selected 

for additional evaluation in the status assessment because they 

had maximum RCs greater than 0.1 and study-unit detection 

frequencies greater than or equal to 10%. The fumigant 

1,2-dibromoethane (EDB) was selected for additional 

evaluation because it had a maximum RC greater than 0.1. 

Atrazine, simazine, diuron, chloroform, and 1,2,3-TCP were 

selected because they had study-unit detection frequencies 

greater than or equal to 10% (figs. 25, 26; table 8). Eleven 

other organic constituents with health-based benchmarks were 

detected in grid wells at RCs less than 0.1 and had study-unit 

detection frequencies less than 10% (fig. 25; table 4). 

Aquifer-scale proportions for individual organic and 

special-interest constituents are listed in table 8, and results 

for organic constituent classes are listed in table 9B. For 

any organic constituent having health-based benchmarks 

(pesticides and VOCs), 10% of the primary aquifer system, 

on an areal basis, had high RCs of at least one constituent, 

3.3% had moderate values, 40% had detections of organic 

constituents at low values, and 47% had no detections of 

organic constituents (table 9B).

Pesticides

Herbicides were not detected at high or moderate RCs 

in the Madera-Chowchilla study unit (tables 8, 9B); the 

maximum RC detected was 0.039 (atrazine) (figs. 25, 26). 

Twenty-three percent of grid wells sampled (7 of 30) had 

at least one herbicide detected (Shelton and others, 2009). 

Simazine was detected in 20% of the grid wells, and diuron 

and atrazine were each detected in 10% of the grid wells 

(figs. 25, 26). All of the grid well samples containing diuron 

also contained 3,4-dichloroaniline, a degradation product, and 

all of the grid well samples containing atrazine also contained 

the degradation product deethylatrazine. Deisopropyl atrazine, 

another a degradation product of atrazine, was detected in 

the sample containing the highest concentrations of atrazine 

and deethylatrazine. The degradation products of atrazine and 

diuron were detected in more samples than were these two 

parent compounds (Shelton and others, 2009). Benchmarks 

have not been established for these degradation products; thus, 

they are not included in the status assessment. 
54 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig 25

Detection frequency, in percent

0 10 20 30 40 50 60 70 80

1E-005

0.0001

0.001

0.01

0.1

1

10

Maximum relative-concentration, dimensionless

DBCP

EDB

PCE

Perchlorate

TCE cis-1,2-

DCE Atrazine

Diuron

Dibromochloromethane

Dinoseb

Chloroform

Bromodichloromethane 1,2,3-TCP

Bromacil

Hexazinone

Tebuthiuron

1,1-DCA

1,2-DCP

Bromoform

Simazine

Moderate

Low

Moderate

High

EXPLANATION

PCE Constituents with analyses in >20 grid wells and wells are spatially representative–

Name and center of symbol is location of data unless indicated by following location line: 

cis-1,2-DCE, cis-1,2-dichloroethene; DBCP, 1,2-dibromo-3-chloropropane; EDB, 1,2-dibromoethane; 1,1-DCA, 1,1-dichloroethane; 1,2-DCP, 1,2-dichloropropane; 

PCE, tetrachloroethene; TCE, trichloroethene; 1,2,3-TCP, 1,2,3-trichloropropane.

Abbreviations

Figure 25. Detection frequency and maximum relative-concentrations for organic and 

special-interest constituents detected in grid wells, 2008, Madera-Chowchilla study unit, California 

GAMA Priority Basin Project.
Status and Understanding of Water Quality 55

Figure 26. Detection frequency and relative-concentrations of selected organic and special-interest 

constituents in grid wells, 2008, Madera-Chowchilla study unit, California GAMA Priority Basin Project.

sac11-0401_fig 26

Trihalomethanes and Solvents

Herbicides

Fumigants

Special interest

Chloroform

PCE

Atrazine

Simazine

Diuron

DBCP

EDB

1,2,3-TCP

Perchlorate

0 2010 40 60 80 100 0.0001 0.001 0.01 0.1 1 10

Study-unit detection frequency, Relative-concentration, dimensionless

in percent

Low Moderate High

Low Moderate High

Low Moderate High

Low Moderate High

EXPLANATION

PCE, tetrachloroethene; DBCP, 1,2-dibromo-3-chloropropane; EDB, 1,2-dibromoethane; 1,2,3-TCP, 

1,2,3-trichloropropane.

Abbreviations
56 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Detections of atrazine and deethylatrazine are the most 

common two-compound mixtures of pesticides detected in 

the groundwater sampled by the National Water-Quality 

Assessment (NAWQA) Program (Gilliom and others, 2006), 

and their co-occurrence may reflect the relatively high degree 

of persistence of atrazine in groundwater environments 

(Kolpin and others, 1998). Deethylatrazine, atrazine, and 

simazine were the most frequently detected pesticide 

compounds in groundwater in major aquifers across the United 

States (Gilliom and others, 2006). In California, simazine is 

most commonly used on orchards and vineyards and on rightsof-way for weed control. Diuron is most commonly used on 

rights-of-way, alfalfa for forage, and orchards and vineyards, 

and atrazine has historically been most commonly used on 

corn and rights-of-way (Kegley and others, 2008). 

Herbicides were detected at low RCs in 9 of the 35 

USGS-GAMA wells used in the understanding assessment

(fig. 27A). Herbicides were not detected in any of the 69 

CDPH wells for which data were reported for herbicides 

between February 12, 2005, and February 12, 2008 

(fig. 27A). All of the detections in USGS-GAMA samples had 

concentrations that were lower than the reporting limits used 

in the CDPH database.

Insecticides were not detected in USGS-GAMA samples 

(not including the fumigants DBCP and EDB). No insecticide 

detections were reported in the CDPH database (not including 

the fumigants DBCP and EDB).

Factors Affecting Herbicides

Rather than considering atrazine, simazine, and diuron 

separately in the understanding assessment, concentrations of 

all herbicides with benchmarks were summed and treated as a 

constituent class.

Depth and groundwater age were the most significant 

factors affecting organic constituents (table 10A; fig. 28A). 

Herbicide concentrations were significantly greater in modern 

groundwater than in pre-modern or mixed groundwater, and 

in wells classified as shallow or mixed than in wells classified 

as deep. All of the wells with detections of herbicides had 

modern or mixed-age groundwater. Herbicide concentrations 

had a significant negative correlation with depth to the top 

of perforations, and herbicides were not detected in wells 

with the depths to top of perforation deeper than 240 ft below 

land surface.

Herbicides were correlated positively with dissolved 

oxygen and Fract-CaMg and negatively with pH and depth 

to top of perforations (table 10B). The correlations between 

herbicides and the geochemical explanatory factors likely 

result from the correlations between the geochemical 

explanatory factors and depth to top of perforations and 

shallow wells (tables 6A,B). Herbicide concentrations were 

not significantly correlated with land use (table 10B). The lack 

of correlation may reflect that the most frequently detected 

herbicides have agricultural and non-agricultural applications, 

or the lack of correlation may reflect the dominance of 

agricultural land use in the study unit. Sixty-nine percent of 

the study unit has agricultural land use, and the areas of urban 

land use are small in area and surrounded by agricultural land 

use (figs. 5A, 6).

Fumigants

The proportion of the primary aquifer system with high 

RCs of fumigants was 10%. DBCP was the only fumigant 

(and the only organic constituent) present at high RCs, and 

all detections had high RCs, resulting in a high aquifer-scale 

proportion for DBCP of 10% (table 8; figs. 25, 26). One of 

the samples with a high RC of DBCP also had a moderate 

RC of another fumigant, EDB. The detection frequency of 

1,2,3-TCP in grid wells was 33%, and all detections had low 

RCs (figs. 25, 26). 

DBCP and EDB are soil fumigants that were used to 

control nematodes primarily in orchard and vineyards, but 

their usage was discontinued in 1977 and 1983, respectively 

(Domagalski, 1997; California State Water Resources Control 

Board, 2002; Kegley and others, 2008). 1,2,3-TCP was used 

in the manufacture of D-D (dichloropropane-dichloropropene 

mixture) (California Department of Public Health, 2009), a 

soil fumigant whose usage was discontinued in 1987 (Kegley 

and others, 2008). DBCP was the most frequently detected 

fumigant or pesticide detected in groundwater samples 

collected from the San Joaquin Valley during 1971–1988 

(Domagalski, 1997) and in groundwater samples statewide 

in samples analyzed through 1999 (Troiano and others, 

2001). Detection frequencies of DBCP in San Joaquin 

Valley groundwater have been higher than those reported in 

most other parts of the nation because of DBCP’s historical 

use on orchards and vineyards in California (Dubrovsky 

and others, 1998; Zogorski and others, 2006). Vineyards 

in the San Joaquin Valley commonly have been located on 

soils with relatively coarse textures, and DBCP generally 

was applied by injection into the soils; these factors likely 

contributed to transport of DBCP to groundwater (Burow and 

others, 1998; 2000). Nationally, DBCP contributed to most 

of the concentrations of VOCs above MCLs or health-based 

screening levels (Zogorski and others, 2006).

In addition to the three USGS-GAMA wells with 

high RCs of DBCP, high or moderate RCs of DBCP were 

reported in three other wells in the CDPH database between 

February 12, 2005, and February 12, 2008, and low RCs 

were reported in another six CDPH wells (one of which 

was MADCHOW-18). For four of these nine CDPH wells, 

the detection of DBCP was not in the most recent sample 

analyzed, so these detections are not shown on fig. 27B. All 

nine CDPH wells and two of the three USGS wells with 

detections of DBCP were located south of the city of Madera 

(fig. 27B). EDB was detected in one USGS well and one 

CDPH well, both of which also had detections of DBCP and 

were located south of Madera. For one CDPH well, results for 

240 analyses of DBCP and EDB were reported in the CDPH 

database between April 2005 and December 2007. 
Status and Understanding of Water Quality 57

Figure 27. Maximum relative-concentrations of selected constituents in organic constituent classes and perchlorate in USGS-GAMA 

wells and the most recent analysis during February 12, 2005–February 12, 2008, for CDPH wells, Madera-Chowchilla study unit, California 

GAMA Priority Basin Project: (A) herbicides, (B) fumigants, (C) trihalomethanes, (D) solvents, and (E) perchlorate.

sac11-0401_fig 27a

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

EXPLANATION 0 5 10 KILOMETERS

Not detected

Low

Not detected

Land use

Urban

Agricultural

Natural

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals USGS GAMA CDPH 

(data in 3-year period

2/12/2005–2/12/2008) 

(grid and 

understanding)

atrazine

bromacil

dinoseb

diuron

hexazinone

simazine

tebuthiron

1

70

7

20

400

4

500

0.007

0.02

0.04

0.04

0.008

0.006

0.016

0.5

not available

no data

no data

no data

1

no data

RC is the sample concentration divided by the benchmark concentration.

Not detected means reported as a nondetection at a concentration less

 than the reporting limit (RL).

Low RC is a sample concentration less than one-tenth the benchmark

 concentration (0.1>RC).

 

* Herbicides with

benchmarks detected

Benchmark

concentrations, in

micrograms per liter

USGS-GAMA RL

concentrations, in

micrograms per liter

CDPH RL

concentrations, in

micrograms per liter

1

See tables 3 and 4 for benchmark types. 

Herbicides

Maximum relative-concentration (RC) by well

RC category* Wells

1

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant Kern CanalFriant Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

A. Herbicides

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake
58 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 27.—Continued

sac11-0401_fig 27b

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Land use

Urban

Agricultural

Natural

Vineyard

Not detected

Low

Moderate

High

Fumigants

Maximum relative-concentration (RC) by well

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

RC category*

USGS GAMA CDPH 

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

1,2-dibromo-3-chloropropane (DBCP)

1,2,-dibromoethane (EDB)

1,2,3-trichloropropane (1,2,3-TCP)

1,2-dichloropropane (1,2-DCP)

0.2

0.05

40

5

0.030

0.02

0.0050

0.02

0.01–0.5

0.02–0.5

0.5

0.5

RC is the sample concentration divided by the benchmark concentration.

Not detected means reported as a nondetection at a concentration less

 than the reporting limit (RL).

Low RC is a sample concentration less than one-tenth the benchmark

 concentration (0.1>RC).

Moderate RC is a sample concentration between one-tenth the benchmark

 concentration and the benchmark (1≥RC>0.1).

High RC is a sample concentration greater than the benchmark

 concentration (RC>1).

 

* Fumigants with

benchmarks detected

Benchmark

concentrations, in

micrograms per liter

USGS-GAMA RL

concentrations, in

micrograms per liter

CDPH RL

concentrations, in

micrograms per liter

1

1

See tables 3 and 4 for benchmark types. 

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

B. Fumigants

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake
Status and Understanding of Water Quality 59

Figure 27.—Continued

sac11-0401_fig 27c

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

Land use

Urban

Agricultural

Natural

Not detected

Low

EXPLANATION

Trihalomethane (THM)

Maximum relative-concentration (RC) by well

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals RC category*

USGS GAMA CDPH 

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

chloroform

bromoform

bromodichloromethane

dibromochloromethane

80

80

80

80

0.02

0.08

0.04

0.12

0.5

0.5

0.5

0.5

RC is the sample concentration divided by the benchmark concentration.

Not detected means reported as a nondetection at a concentration less

 than the reporting limit (RL).

Low RC is a sample concentration less than one-tenth the benchmark

 concentration (0.1>RC).

 

* THMs with

benchmarks detected

Benchmark

concentrations, in

micrograms per liter

USGS-GAMA RL

concentrations, in

micrograms per liter

CDPH RL

concentrations, in

micrograms per liter

1

See tables 3 and 4 for benchmark types. The benchmark for THMs is for the sum of

 chloroform, bromoform, bromodichloromethane, and dibromochloromethane. 

1

C. Trihalomethanes (THMs)

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake
60 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure 27.—Continued

sac11-0401_fig 27d

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

EXPLANATION

Land use

Urban

Agricultural

Natural

Not detected

Low

Moderate

EXPLANATION

Solvents

Maximum relative-concentration (RC) by well

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

RC category*

USGS GAMA CDPH 

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

tetrachloroethene (PCE)

trichloroethene (TCE)

1,1-dichloroethane (1,1-DCA)

cis-1,2-dichloroethene

 (cis-1,2-DCE)

5

5

5

6

0.04

0.02

0.04

0.02

0.5

0.5

0.5

not available

RC is the sample concentration divided by the benchmark concentration.

Not detected means reported as a nondetection at a concentration less

 than the reporting limit (RL).

Low RC is a sample concentration less than one-tenth the benchmark

 concentration (0.1>RC).

Moderate RC is a sample concentration between one-tenth the

 benchmark concentration and the benchmark (1≥RC>0.1). 

 

* Solvents with

benchmarks detected

Benchmark

concentrations, in

micrograms per liter

USGS-GAMA RL

concentrations, in

micrograms per liter

CDPH RL

concentrations, in

micrograms per liter

1

See tables 3 and 4 for benchmark types. 

1

D. Solvents

Millerton

Madera Lake

Lake

Hensley

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake
Status and Understanding of Water Quality 61

sac11-0401_fig 27e

37°15'

36°45'

37°

120°30' 120°15' 120° 119°45'

0 5 10 MILES

0 5 10 KILOMETERS

Duck Slough Duck Slough

Chowchilla River Chowchilla River

Panoche CreekPanoche Creek

Fresno River

San Joaquin River San Joaquin River

Fresno SloughFresno Slough

Chowchilla Canal Chowchilla Canal

Friant-Kern CanalFriant-Kern Canal

Third Lift CanalThird Lift Canal

Main CanalMain Canal

Main

Lift

Outside CanalOutside Canal

California AqueductCalifornia Aqueduct

Madera CanalMadera Canal

Owens Creek wens Creek

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

FRESNO CO

MADERA CO

MERCED CO

MARIPOSA CO

Fresno

Friant

Mendota

Chowchilla

Madera

EXPLANATION

Land use

Urban

Agricultural

Natural

Not detected

Low

Moderate

EXPLANATION

Perchlorate

Maxumum relative-concentration (RC) by well

Madera-Chowchilla study unit

County boundary

Streams, rivers, and canals

RC category*

USGS GAMA CDPH 

(data in 3-year period

2/12/2005–2/12/2008) 

Wells

(grid and 

understanding)

perchlorate 6 0.10 4

RC is the sample concentration divided by the benchmark concentration.

Not detected means reported as a nondetection at a concentration less

 than the reporting limit (RL).

Low RC is a sample concentration less than one-tenth the benchmark

 concentration (0.1>RC).

Moderate RC is a sample concentration between one-tenth the

 benchmark concentration and the benchmark (1≥RC>0.1). 

 

* THMs with

benchmarks detected

Benchmark

concentrations, in

micrograms per liter

USGS-GAMA RL

concentrations, in

micrograms per liter

CDPH RL

concentrations, in

micrograms per liter

1

See table 3 for benchmark types. 

1

E. Perchlorate

Millerton

Lake

San Joaquin River San Joaquin River

Delta Mendota CanalDelta Mendota Canal

H.V. Eastman

Lake

Madera

Lake

Hensley

Lake

Figure 27.—Continued
62 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Of these 240 samples, 24% had detections of DBCP, and 

34% had detections of EDB; of the total 139 detections of the 

two fumigants, 62 had high RCs, and 72 had moderate RCs. 

Highest concentrations of DBCP and EDB were detected in 

samples collected at the beginning of the pumping season 

(approximately June each year), and concentrations decreased 

through the season (through approximately September 

each year).

The other fumigants detected by USGS-GAMA, 

1,2,3-TCP and 1,2-dichloropropane, were detected at low 

RCs. Wells with detections are distributed across the study 

unit (fig. 27B).

Factors Affecting Fumigants

Rather than consider DBCP and 1,2,3-TCP separately 

in the understanding assessment, concentrations of all 

fumigants were summed and treated as a constituent class. 

Fumigants were not significantly correlated with any potential 

explanatory factors (tables 10A,B). Considered independently, 

DBCP and 1,2,3-TCP also were not significantly correlated 

with any potential explanatory factors. Fumigants also were 

not significantly correlated with any of the other water‐quality 

constituents selected for additional evaluation in the status 

assessment. The absence of significant correlations was 

unexpected, given the results obtained in other studies. 

Landon and others (2010) reported a significant positive 

correlation between DBCP and percentage of orchard/vineyard 

land use. Their findings are consistent with historical use of 

DBCP on orchards and vineyards in the Central Eastside area 

of the San Joaquin Valley, which is just to the north of the 

Madera-Chowchilla study unit. DBCP also was significantly 

positively correlated with nitrate in the Central Eastside study 

unit. Burow and others (1999, 2007) investigated occurrence 

of DBCP in shallow groundwater (60 to 260 ft below land 

surface) southeast of Fresno. DBCP concentrations generally 

were highest in groundwater 100 to 230 ft below land surface, 

where groundwater recharge ages generally corresponded to 

the time period during which DBCP was used (1955 to 1977), 

and DBCP had significant positive correlation with nitrate 

(Burow and others, 1998a, 1998b, 1999, 2007).

The lack of significant relations between fumigant 

occurrence and land use, groundwater age, depth, or other 

water-quality constituents in the Madera-Chowchilla study 

unit may reflect historic usage patterns in the study unit and 

the depths of wells sampled for this study. DBCP was used 

between 1955 and 1977, but historic fumigant-use patterns 

are not well documented. Partial reporting indicates DBCP 

was used intermittently to treat nematode infestations that 

primarily occurred in older, well-established vineyards 

and orchards (Burow and others, 1999); therefore, the use 

pattern was likely geographically patchy within the study 

unit. The fumigant mixture D-D was first used in 1943 (Oki 

and Giambelluca, 1987); thus, 1,2,3-TCP may have been 

introduced into groundwater prior to 1950, which may account 

for the presence of 1,2,3-TCP and 1,2-DCP in pre-modern 

groundwater in wells with depth to top of perforations greater 

than 300 ft below land surface (fig. 28B).

Other Volatile Organic Compounds

Water used for drinking water and other household uses 

in domestic, municipal, and community systems commonly 

is disinfected with hypochlorite solutions (bleach). In 

addition to disinfecting the water, the hypochlorite reacts with 

organic matter to produce trihalomethanes (THMs) and other 

chlorinated and/or brominated disinfection byproducts. The 

study-unit detection frequency of the THM chloroform was 

17% (fig. 25). No high or moderate RCs of chloroform were 

detected by USGS-GAMA or reported in the CDPH database 

(table 8). The maximum RC detected was 0.001 (fig. 26). Most 

detections of THMs in USGS-GAMA samples or reported in 

the CDPH database were in wells located in or near the cities 

of Chowchilla, Madera, and Fresno (fig. 27C).

The sum of THMs was significantly associated with 

modern groundwater and positively correlated with urban 

land use (tables 10A,B). Nationally, THMs have also been 

strongly correlated with urban land use (Zogorski and 

others, 2006). Potential urban sources of THMs include 

recharge from landscape irrigation with disinfected water, 

leakage from water distribution systems, and industrial 

and commercial usage of chlorinated disinfectants and 

reagents (Ivahnenko and Barbash, 2004). In addition, shock 

chlorination is a recommended procedure for treatment of 

bacterial contamination and odor problems in domestic wells, 

and may result in a reservoir of chlorinated water in the well 

bore and surrounding aquifer material (Seiler, 2006). Small 

systems, such as schools, campgrounds, restaurants, and small 

community associations, may be likely to maintain their wells 

following guidelines for domestic wells.

Solvents are used for a variety of industrial, commercial, 

and domestic purposes (Zogorski and others, 2006). The 

only frequently detected solvent was PCE, with a study-unit 

detection frequency of 10% (figs. 25, 26). PCE was also the 

most frequently detected solvent in groundwater nationally 

(Zogorski and others, 2006). PCE was present at moderate 

RCs in 3.3% of the primary aquifer system (table 8). PCE 

is typically used for dry-cleaning of fabrics and degreasing 

metal parts and is an ingredient in a wide range of products, 

including paint removers, polishes, printing inks, lubricants, 

and adhesives (Doherty, 2000). Detections of solvents in 

USGS-GAMA samples were in wells located in or near the 

cities of Chowchilla and Madera (fig. 27D).
Status and Understanding of Water Quality 63

Figure 28. Relations of (A) herbicide, (B) fumigant, (C) trihalomethane, (D) solvent, and (E) perchlorate 

total concentrations with depth to top of perforations in wells, Madera-Chowchilla study unit, 2008, 

California GAMA Priority Basin Project.

sac11-0401_fig 28abcde

A

D

B

C

E

Depth to top of perforation, in feet below land surface 100

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface 100

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface 100

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface 100

0

200

300

400

500

600

Depth to top of perforation, in feet below land surface 100

0

200

300

400

500

600

0.00 0.05 0.10 0.15 0.20 0.25 0.30

0.0 0.1 0.2 0.3 0.4

0.0 0.5 1.0 1.5 2.0

0.5 2.5 3.0

Sum of herbicides, in micrograms per liter

Sum of solvents, in micrograms per liter

Perchlorate, in micrograms per liter

Sum of fumigants, in micrograms per liter

0.00 0.01 0.02 0.03 0.04 0.40 0.60 0.80

Sum of trihalomethanes (THMs), in micrograms per liter

0.000 0.025 0.050 0.075 0.100 1.0 1.4

EXPLANATION

Modern Mixed Pre-modern

Groundwater age classification

East

Below

Above/across

Position relative

to Corcoran Clay

USGS–GAMA grid and understanding wells (n=33)
64 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Total solvent concentration is the sum of the 

concentrations of all chlorinated solvents with benchmarks. 

Three solvents in addition to PCE were detected (table 4), 

and all detections were in samples that also had detections 

of PCE (Shelton and others, 2009). The sum of solvents 

was significantly associated with modern groundwater and 

positively correlated with urban land use (tables 10A,B).

Special-Interest Constituents

Perchlorate is an inorganic anion with natural and 

anthropogenic sources. It is formed naturally in the 

atmosphere and is present in precipitation (Dasgupta and 

others, 2005; Rajagopalan and others, 2009). Perchlorate salts 

are the primary ingredient in solid rocket fuel and are used 

in explosives, safety flares, and fireworks; thus, sites that 

manufacture, use, or dispose of these products are potential 

sources of perchlorate contamination to groundwater (U.S. 

Environmental Protection Agency, 2005). Perchlorate is also 

present as a contaminant in the Chilean nitrate fertilizer that 

was used extensively in California before industrial sources of 

nitrate fertilizers were plentiful (Dasgupta and others, 2006).

Perchlorate was detected at moderate RCs in 20% of 

the primary aquifer system (table 8) and at low RCs in 50%. 

No high RCs of perchlorate were detected. Detections of 

perchlorate were distributed across the study unit (fig. 27E). 

Because NDMA was analyzed in only 5 of the 30 grid 

wells, aquifer-scale proportions for NDMA were not 

calculated. However, the one detection of NDMA had an RC 

of 0.25 (moderate).

Factors Affecting Perchlorate

Higher perchlorate concentrations were significantly 

associated with wells classified as shallow, and perchlorate 

concentration had a significant negative correlation with well 

depth (tables 10A,B; fig. 28E). Perchlorate was negatively 

correlated with pH and positively correlated with dissolved 

oxygen and Fract-CaMg. The correlations between perchlorate 

and the geochemical indicators likely reflect the significant 

associations between high pH and deep wells and between 

high dissolved oxygen concentrations and Fract-CaMg values 

and shallow wells.

Fram and Belitz (2011b) investigated the occurrence 

patterns and concentrations of perchlorate under natural 

conditions in California. They determined the expected 

detection frequencies of perchlorate at concentrations 

greater than threshold concentrations (0.1 μg/L and 

0.5 μg/L) under natural conditions as a function of climate. 

Climate is represented by the aridity index, which is the 

ratio of average annual precipitation to average annual 

evapotranspiration (United Nations Educational, Scientific, 

and Cultural Organization, 1979). For the average aridity 

index in the Madera-Chowchilla study unit, the predicted 

detection frequencies under natural conditions are 63% 

for concentrations of perchlorate >0.1 μg/L and 12% for 

concentrations >0.5 μg/L. Perchlorate was detected at a 

concentration of 0.1 μg/L or higher in 21 of the 30 grid well 

samples (70%) and it was detected at a concentration of 

0.5 μg/L or higher in 7 grid well samples (23%) (Shelton 

and others, 2009). These observed detection frequencies are 

greater than the predicted detection frequencies of 63% and 

12%, respectively, suggesting that anthropogenic sources or 

processes have increased the concentrations of perchlorate 

over natural, background levels in the Madera-Chowchilla 

study unit. There are no sites of known groundwater 

contamination from aerospace, military, or industrial 

sources of perchlorate in the Madera-Chowchilla study unit 

(U.S. Environmental Protection Agency, 2005; California 

Department of Toxic Substances Control, 2007; California 

State Water Resources Control Board, 2007), and the historic 

use of Chilean nitrate fertilizer is insufficient to account for the 

excess perchlorate (Dasgupta and others, 2006; Rajagopalan 

and others, 2006). The inverse correlation between perchlorate 

and well depth, and the association between higher 

concentrations of perchlorate and higher concentrations 

of herbicides, nitrate, and uranium are consistent with the 

source of the excess perchlorate being remobilization of 

naturally deposited perchlorate salts in the unsaturated zone by 

irrigation recharge (Fram and Belitz, 2011b).

Summary 

Groundwater quality in the approximately 860-squaremile Madera and Chowchilla Subbasins (Madera-Chowchilla 

study unit) of the San Joaquin Valley Basin was investigated 

as part of the Priority Basin Project of the Groundwater 

Ambient Monitoring and Assessment (GAMA) Program. The 

study unit is located in California’s Central Valley region in 

parts of Madera, Merced, and Fresno Counties. The GAMA 

Priority Basin Project is being conducted by the California 

State Water Resources Control Board in collaboration with the 

U.S. Geological Survey (USGS) and the Lawrence Livermore 

National Laboratory. The Priority Basin Project was designed 

to provide statistically robust assessments of untreated 

groundwater quality within the primary aquifer systems in 

California. The primary aquifer system within each study unit 

is defined by the depth of the perforated or open intervals 

of the wells listed in the California Department of Public 

Health (CDPH) database of wells used for public drinkingwater supply. The quality of groundwater in shallower or 

deeper water-bearing zones may differ from that in the 

primary aquifer system; shallower groundwater may be more 

vulnerable to contamination from the land surface.
Summary 65

The assessments for the Madera-Chowchilla study unit 

were based on water-quality and ancillary data collected 

by the USGS from 35 wells during April–May 2008, and 

on water-quality data reported in the CDPH database for 

125 wells between February 2005 and February 2008. 

Two types of assessments were made: status, which is 

an assessment of the current quality of the groundwater 

resource; and understanding, which includes identification 

of natural factors and human activities that may be affecting 

groundwater quality.

Relative-concentrations (sample concentrations divided 

by benchmark concentrations) were used for evaluating 

groundwater quality for those constituents that have Federal 

and (or) California regulatory or non-regulatory benchmarks 

for drinking-water quality. A relative-concentration (RC) 

greater than (>) 1.0 indicates a concentration above a 

benchmark. RCs for organic constituents (volatile organic 

compounds and pesticides) and special-interest constituents 

(perchlorate) were classified as “high” (RC>1.0), “moderate” 

(1.0≥RC>0.1), or “low” (RC≤0.1). For inorganic 

constituents (major ions, trace elements, nutrients, and 

radioactive constituents), the boundary between low and 

moderate RCs was set at 0.5. The assessments characterize 

untreated groundwater quality, not the quality of treated 

drinking water delivered to consumers by water purveyors; 

drinking-water benchmarks and thus, RCs, are used to provide 

context for the concentrations of constituents measured in 

groundwater.

Aquifer-scale proportion was used in the status 

assessment as the primary metric for evaluating regional-scale 

groundwater quality. High aquifer-scale proportion is defined 

as the percentage of the area of the primary aquifer system 

with an RC greater than 1.0 for a particular constituent or class 

of constituents; moderate and low aquifer-scale proportions 

are defined as the percentages of the area of the primary 

aquifer system with moderate and low RCs, respectively. 

Percentages are based on an areal basis, rather than on a 

volumetric basis. Two statistical approaches—grid-based, 

which used one value per grid cell, and spatially weighted, 

which used multiple values per grid cell—were used to 

calculate aquifer-scale proportions for individual constituents 

and classes of constituents. The spatially weighted estimates 

of high aquifer-scale proportions were within the 90 percent 

(%) confidence intervals of the grid-based estimates for all 

constituents except iron.

The status assessment indicated that inorganic 

constituents had greater high and moderate aquifer-scale 

proportions in the Madera-Chowchilla study unit than did 

organic constituents. RCs for inorganic constituents with 

health-based benchmarks were high in 37% of the primary 

aquifer system, moderate in 30%, and low in 33%. The 

inorganic constituents contributing most to the high aquiferscale proportion were arsenic (13%), uranium (17%), gross 

alpha particle activity (20%), nitrate (6.7%), and vanadium 

(3.3%). RCs for inorganic constituents with secondary 

maximum contaminant levels (non-health-based benchmarks) 

were high in 6.7% of the primary aquifer system, moderate 

in 17%, and low in 77%. The constituent contributing most 

to the high aquifer-scale proportion was total dissolved 

solids (TDS) (6.7%). RCs for organic constituents with 

health-based benchmarks were high in 10% of the primary 

aquifer system, moderate in 3.3%, and low in 40%; organic 

constituents were not detected in 47% of the primary aquifer 

system. The fumigant 1,2-dibromo-3-chloropropane (DBCP) 

was the only organic constituent detected at high RCs. 

Seven organic constituents were detected in 10% or more 

of the primary aquifer system: DBCP; the fumigant additive 

1,2,3-trichloropropane (1,2,3-TCP); the herbicides simazine, 

atrazine, and diuron; the trihalomethane (THM) chloroform; 

and the solvent tetrachloroethene (PCE). RCs for the specialinterest constituent perchlorate were moderate in 20% of the 

primary aquifer system.

The second component of this study, the understanding 

assessment, identified the natural and human factors that 

may affect groundwater quality by evaluating statistical 

correlations between water-quality constituents and potential 

explanatory factors, such as land use, position relative to 

important geologic features, groundwater age, well depth, 

and geochemical conditions in the aquifer. Results of the 

statistical evaluations were used to explain the distribution of 

constituents in the study unit. Depth to the top of perforations 

in the well and groundwater age were the most important 

explanatory factors for many constituents. High and moderate 

RCs of nitrate, uranium, and TDS, and the presence of 

herbicides, trihalomethanes, and solvents were associated 

with depths to the top of perforations less than 235 ft and with 

modern- and mixed-age groundwater. Positive correlations 

between uranium, bicarbonate, TDS, and proportion of 

calcium and magnesium in the total cations suggest that 

downward movement of recharge from irrigation water 

contributed to the elevated concentrations of these constituents 

in the primary aquifer system. High and moderate RCs of 

arsenic were associated with depths to the top of perforations 

greater than 235 ft, mixed- and pre-modern-age groundwater, 

and location in sediments from the Chowchilla River alluvial 

fan, suggesting that increased residence time and appropriate 

aquifer materials were needed for arsenic to accumulate in 

the groundwater. High and moderate RCs of fumigants were 

associated with depths to the top of perforations of less than 

235 ft and location south of the city of Madera; low RCs of 

fumigants were detected in wells dispersed across the study 

unit with a range of depths to top of perforations. Land use 

generally was not a significant explanatory factor, likely 

because more than 50% of the area within 500 meters of twothirds of the grid wells was classified as agricultural.
66 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Acknowledgments

The authors thank the following cooperators for 

their support: the State Water Resources Control Board 

(SWRCB), California Department of Public Health, California 

Department of Water Resources, and Lawrence Livermore 

National Laboratory. We especially thank the cooperating 

well owners and water purveyors for their generosity in 

allowing the U.S. Geological Survey (USGS) to collect 

samples from their wells. Funding for this work was provided 

by State of California bonds authorized by Proposition 50 

and administered by the SWRCB. We also thank the USGSGAMA team for the many tasks required to complete this 

work.

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72 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

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Appendix A 73

Appendix A. Ancillary Datasets 

Land Use

Land use was classified using an “enhanced” version 

of the satellite-derived (30-m pixel resolution) nationwide 

USGS National Land Cover Dataset (Nakagaki and others, 

2007). This dataset has been used in previous national and 

regional studies relating land use to water quality (Gilliom and 

others, 2006; Zogorski and others, 2006). The data represent 

land use during approximately the early 1990s. The imagery 

is classified into 25 land-cover classifications (Nakagaki 

and Wolock, 2005). These 25 land-cover classifications 

were condensed into 3 principal land-use categories: urban, 

agricultural, and natural. One subcategory of agricultural land 

use is orchard/vineyard. Land-use statistics for the study unit, 

study areas, and for circles with a radius of 500 m around 

each well were calculated for classified datasets by using 

ArcGIS (Johnson and Belitz, 2009). A 500-m radius centered 

on the well has been shown to be effective at correlating 

urban land use with VOC occurrence for the purposes of 

statistical characterization (Johnson and Belitz, 2009). 

Land-use statistics for grid and understanding wells are listed 

in table A1.

Land-cover classes are based on features distinguishable 

in Level II remote sensing data (high-altitude aerial 

photography; Anderson and others, 1976). Urban land use 

includes high, moderate, and low intensity development 

and developed open space. Agricultural land use includes 

cultivated crops and land used for pasture or hay. Natural land 

use includes everything else. Open-range grazing is classified 

as natural land use, not agricultural land use.

Lateral Position

The lateral position of wells serves as a proxy for the 

horizontal position in the regional groundwater flow system. 

Regionally, groundwater primarily flows from the eastern 

margins of the valley deposits along the Sierra Mountain 

front towards the San Joaquin River. The groundwater flow 

system has vertical flow components as well as horizontal flow 

components that deviate from the general direction in response 

to withdrawals and recharge (Phillips and others, 2007). 

Nevertheless, because the predominant pattern of regional 

groundwater flow is from the valley margin towards the 

San Joaquin River, lateral position serves as an approximate 

indicator of relative position of a well within the regional 

flow system. The normalized lateral position of each well 

was calculated as the ratio of the distance from the well to 

the edge of the regional groundwater flow system to the total 

distance from the valley trough to the edge of the valley. The 

eastern edge of the valley was represented by the boundary 

of the valley fill deposits and was assigned a value of 1.00 

(fig. 8). The valley trough was represented by the southeastto-northwest flowing reach of the San Joaquin River and was 

assigned a value of 0.00. Both boundaries were represented as 

approximate line segments, and lateral position was calculated 

along lines perpendicular to both bounding lines. The 

normalized lateral position (hereinafter, lateral position) was 

calculated for all 30- by 30-m-wide cells in the San Joaquin 

Valley as part of a regional groundwater flow modeling study 

(Faunt, 2009). Lateral position values were assigned to all 

wells residing within those cells in ArcGIS (version 9.2) 

(table A1). Higher values of lateral position indicate locations 

in the upgradient or proximal portion of the flow system, 

and lower values of lateral position indicate locations in the 

downgradient or distal portion of the flow system.

Depth

Well construction data were primarily determined from 

driller’s logs (table A2). In some cases, well construction data 

were obtained from ancillary records of well owners.

Well construction information, land-surface elevation, 

and the elevations of the top and bottom of the Corcoran Clay 

(Page, 1986) were used to code wells as to the depth of the 

perforated interval relative to the depth and position of the 

Corcoran Clay (table A2), using ArcGIS information compiled 

for the Central Valley model (Faunt, 2009). Wells perforated 

above or across the clay were coded as “Above/Across”; 

wells perforated below the Corcoran Clay were coded as 

“Below.” Wells located east of the extent of the Corcoran 

Clay were coded as “East.” Well construction information was 

incomplete for one well, which was coded as “Unknown.”

Groundwater Age

Groundwater dating techniques provide a measure of 

the time since the groundwater was last in contact with the 

atmosphere. Techniques aimed at estimating groundwater 

residence times or ‘age’ include those based on tritium (3H) 

(for example, Tolstikhin and Kamensky, 1969), carbon-14 

(14C) activity (for example, Vogel and Ehhalt, 1963; Plummer 

and others, 1993), dissolved noble gases, particularly helium-4 

(4He) accumulation (for example, Davis and DeWiest, 1966; 

Andrews and Lee, 1979; Kulongoski and others, 2008), and 

tritium in combination with its decay product helium-3 (3He) 

(Poreda and others, 1988; Schlosser and others, 1989).

Tritium (3H) is a short-lived radioactive isotope 

of hydrogen with a half-life of 12.32 years (Lucas and 

Unterweger, 2000). Tritium is produced naturally in the 

atmosphere from the interaction of cosmogenic radiation with 

nitrogen (Craig and Lal, 1961), by above-ground nuclear 

weapons testing, and by the operation of nuclear reactors. 
74 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table A1. Land-use information and lateral positions for grid and understanding wells sampled in April and May 2008, 

Madera-Chowchilla study unit, California GAMA Priority Basin Project.

[USGS-GAMA well identification number: MADCHOW, Madera-Chowchilla study unit grid well; MADCHOWFP, Madera-Chowchilla study 

unit understanding wells. Other abbreviations: m, meter]

USGS-GAMA well 

identification number

Land-use information1

Normalized 

lateral position 

(dimensionless)

Agricultural 

land use within 

500 m of the well

(percent)

Natural 

land use within 

500 m of the well

(percent)

Urban 

land use within 

500 m of the well

(percent)

Orchard / Vineyard 

land use within 

500 m of the well

(percent)

Grid wells

MADCHOW-01 45 7 49 40 0.49

MADCHOW-02 9 50 41 6 0.60

MADCHOW-03 0 5 95 0 0.61

MADCHOW-04 12 7 80 0 0.79

MADCHOW-05 68 25 6 66 0.91

MADCHOW-06 12 88 0 11 1.00

MADCHOW-07 57 43 0 0 0.92

MADCHOW-08 99 0 1 2 0.73

MADCHOW-09 59 12 29 14 0.50

MADCHOW-10 0 8 92 0 0.60

MADCHOW-11 95 3 2 38 0.72

MADCHOW-12 64 0 36 0 0.22

MADCHOW-13 99 1 1 99 0.37

MADCHOW-14 97 2 1 97 0.47

MADCHOW-15 63 37 0 57 0.89

MADCHOW-16 0 51 49 0 0.72

MADCHOW-17 0 100 0 0 1.00

MADCHOW-18 84 3 14 71 0.59

MADCHOW-19 12 88 0 12 0.99

MADCHOW-20 100 0 0 0 0.11

MADCHOW-21 24 63 13 20 1.00

MADCHOW-22 96 0 3 5 0.17

MADCHOW-23 96 2 2 0 0.05

MADCHOW-24 100 0 0 0 0.28

MADCHOW-25 99 1 0 0 0.24

MADCHOW-26 100 0 0 6 0.09

MADCHOW-27 96 0 4 92 0.25

MADCHOW-28 100 0 0 32 0.28

MADCHOW-29 77 22 1 77 0.11

MADCHOW-30 97 3 0 23 0.17

Understanding wells

MADCHOWFP-01 95 0 4 14 0.18

MADCHOWFP-02 75 8 17 58 0.63

MADCHOWFP-03 100 0 0 0 0.04

MADCHOWFP-04 97 3 0 64 0.81

MADCHOWFP-05 47 53 0 0 0.88

1Percent agricultural plus percent natural plus percent urban land use add up to 100 percent. Orchard/vineyard land use is a subset of agricultural 

land use.
Appendix A 75

Table A2. Well construction characteristics and position relative to the Corcoran Clay for grid and understanding 

wells sampled in April and May 2008, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[USGS-GAMA well identification number: MADCHOW, Madera-Chowchilla study unit grid well; MADCHOWFP, MaderaChowchilla study unit understanding wells. Other abbreviations: na, not available; >, greater than]

USGS-GAMA well 

identification 

number

Construction information

(feet below land surface datum, except where noted) Position relative

Well to Corcoran Clay

depth

Top of 

perforations 

Bottom of 

perforations 

Length of perforated 

interval, in feet 

Grid wells

MADCHOW-01 592 210 588 378 East

MADCHOW-02 600 240 600 360 East

MADCHOW-03 540 240 520 280 East

MADCHOW-04 480 180 470 290 East

MADCHOW-05 350 290 350 60 East

MADCHOW-06 310 48 310 262 East

MADCHOW-07 >300 na na na East

MADCHOW-08 820 410 800 390 East

MADCHOW-09 234 234 234 0 Below

MADCHOW-10 830 506 830 324 Below

MADCHOW-11 780 385 770 385 East

MADCHOW-12 300 240 300 60 Below

MADCHOW-13 670 500 660 160 East

MADCHOW-14 388 388 388 0 East

MADCHOW-15 450 390 450 60 East

MADCHOW-16 740 330 740 410 East

MADCHOW-17 140 na na na East

MADCHOW-18 330 210 280 70 East

MADCHOW-19 200 140 200 60 East

MADCHOW-20 352 200 340 140 Above/Across

MADCHOW-21 320 240 320 80 East

MADCHOW-22 325 325 325 0 Below

MADCHOW-23 655 400 655 255 Below

MADCHOW-24 294 244 294 50 Below

MADCHOW-25 >200 na na na Unknown

MADCHOW-26 510 210 510 300 Above/Across

MADCHOW-27 480 240 480 240 East

MADCHOW-28 216 204 212 8 Above/Across

MADCHOW-29 340 160 324 164 Above/Across

MADCHOW-30 388 358 388 30 Below

Understanding wells

MADCHOWFP-01 254 212 254 42 Above/across

MADCHOWFP-02 377 242 377 135 Below

MADCHOWFP-03 198 163 198 35 Above/across

MADCHOWFP-04 200 184 196 12 East

MADCHOWFP-05 340 240 340 100 East
76 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Tritium enters the hydrologic cycle following oxidation 

to tritiated water. Natural background levels of tritium 

in precipitation are approximately 3 to 15 TU (Craig and 

Lal, 1961; Clark and Fritz, 1997). Above-ground nuclear 

explosions resulted in a large increase in tritium values in 

precipitation, beginning in about 1950 and peaking in 1963 

at values over 1,000 TU in the northern hemisphere (Michel, 

1989). Radioactive decay over a period of 60 years would 

decrease tritium values of 10 TU to 0.6 TU. 

Previous investigations have used a range of tritium 

values from 0.2 to 1.0 TU as thresholds for indicating presence 

of water that has exchanged with the atmosphere since about 

1950 (Michel, 1989; Plummer and others, 1993; Michel and 

Schroeder, 1994; Clark and Fritz, 1997; Manning and others, 

2005; Landon and others, 2010; Kulongoski and others, 2010). 

For samples collected for the Madera-Chowchilla study unit 

in 2008, tritium values greater than a threshold of 0.2 TU 

were defined as indicating presence of groundwater recharged 

since about 1950. By using a tritium value of 0.2 TU for the 

threshold in this study, the age classification scheme allows 

for samples with a slightly larger fraction of pre-modern 

groundwater to be classified as modern than if a higher 

threshold were used. A higher threshold for tritium would 

result in fewer samples classified as modern than classified as 

pre-modern, when carbon-14 would suggest that the samples 

were primarily modern.

Carbon-14 (14C) is a widely used chronometer based 

on the radiocarbon content of organic and inorganic carbon. 

Dissolved inorganic carbonate species typically are used 

for 14C dating of groundwater. Carbon-14 is formed in the 

atmosphere by the interaction of cosmic-ray neutrons with 

nitrogen, and to a lesser degree, with oxygen and carbon. 

Carbon-14 is incorporated into carbon dioxide and mixed 

throughout the atmosphere. The carbon dioxide dissolves 

in precipitation which eventually recharges the aquifer. 

Carbon-14 activity in groundwater, expressed as percent 

modern carbon (pmc), reflects exposure to the atmospheric 

14C source and is governed by the decay constant of 14C (with 

a half-life of 5,730 yrs). Carbon-14 can be used to estimate 

groundwater ages ranging from 1,000 to approximately 

30,000 years before present because of its half-life. Calculated 

14C ages in this study are referred to as “uncorrected” because 

they have not been adjusted to consider exchanges with 

sedimentary sources of carbon (Fontes and Garnier, 1979). 

The 14C age (residence time) is calculated on the basis of the 

decrease in 14C activity because of radioactive decay since 

groundwater recharge, relative to an assumed initial 14C 

concentration (Clark and Fritz, 1997). An average initial 14C 

activity of 99 percent modern carbon (pmc) is assumed for this 

study, with estimated errors on calculated groundwater ages 

up to ±20%. Groundwater with a 14C activity of >88 pmc is 

reported as having an age of <1,000 years; no attempt is made 

to refine 14C ages <1,000 years. Measured values of percent 

modern carbon can be >100 pmc because the definition of the 

14C activity in “modern” carbon does not include the excess 

14C produced in the atmosphere by above-ground nuclear 

weapons testing. For the Madera-Chowchilla study unit, 14C 

activity ≤80 pmc was defined as indicative of presence of 

groundwater recharged before about 1950. The threshold value 

of 80 pmc was selected because all groundwater samples with 

tritium ≤ 0.2 TU also had 14C ≤80 pmc.

Helium (He) is a naturally occurring inert gas initially 

included during accretion of the planet, and later produced 

by radioactive decay of lithium, uranium, and thorium in the 

Earth. Helium (3He plus 4He) concentrations in groundwater 

often exceed the expected solubility equilibrium values as 

a result of air-bubble entrainment, or subsurface production 

of both isotopes, and their subsequent release into the 

groundwater (for example, Morrison and Pine, 1955; Andrews 

and Lee, 1979; Torgersen, 1980; Torgersen and Clarke, 1985). 

There are four primary sources of He in groundwater:

total equil exair trit terr,

total

equil

 He He He He He

where

He is the total amount of helium in the

groundwater sample;

He is the helium derived from equilibration

with the atmosphere at the time of

r

= + ++

exair

trit

terr

echarge;

He is the helium derived from dissolved air

bubbles ("excess" air);

He is the helium produced by radioactive

decay of tritium in the sample; and

He is the helium produced by radioactive

decay of uranium and thorium in aquifer

material or emanating from deeper in the

Earth's crust or mantle.

Heequil, Heexair, and Heterr all consist of helium-3 (3He) and 

helium-4 (4He); however, Hetrit consists only of 3He.

Heequil is a function of temperature at the time of 

recharge. Recharge temperatures were calculated from 

dissolved neon, argon, krypton, and xenon using methods 

described in Aeschbach-Hertig and others (1999, 2000) to 

model the Heexair component. The best model for the Heexair

component for each groundwater sample was selected 

by comparing the sums of the weighted squared standard 

deviations between the modeled and measured noble-gas 

concentrations (χ2). The model with the lowest χ2 value (least 

amount of deviation between the modeled and measured 

concentrations) was selected. The χ2 was compared to the 

value of a chi-squared distribution with the appropriate 

number of degrees of freedom for the model and a significance 
Appendix A 77

level (α) of 0.01 (χ2α=0.01). Recharge temperatures were 

only calculated for groundwater samples for which χ2 was less 

than χ2α=0.01 (Aeschbach-Hertig and others, 2000).

The presence of large concentrations of Heterr may be 

indicative of long groundwater residence times. For the 

purpose of estimating groundwater residence times, the 

amount of Heterr is converted to the parameter %Heterr–c, the 

percent of Heterr in Hetotal corrected for excess air:

% 100. terr terr c

total exair

He He

He He −

−

= ×

(Hetrit is neglected in calculation of %Heterr-c because it 

typically is very small.) For the Madera-Chowchilla study 

units, values of %Heterr–c >10% were defined as indicative 

of the presence of pre-modern groundwater. The threshold 

of 10% was selected because many of the samples with 14C 

≤80 pmc also had %Heterr–c >10%.

The 3He/4He ratio of Heterr was determined by the linear 

regression of Heterr/Hetotal and δ3He [(δ3He = Rmeas/Ratm –1) × 

100 percent, where Rmeas/Ratm is the measured 3He/4He ratio in 

the sample divided by the 3He/4He ratio in the atmosphere] for 

groups of related groundwater samples with tritium <1 TU. 

Noble gas concentrations and measured 3He/4He ratios 

are reported in table A3, and tritium,14C ages, and %Heterr–c

are reported in table A4. Because of uncertainties in age 

distributions, particularly the uncertainties caused by mixing 

of waters of different ages in wells with long screened or open 

intervals and high withdrawal rates, the uncorrected 14C ages 

were not specifically used for quantifying the relation between 

age and water quality in this report. While more sophisticated 

lumped parameter models for analyzing age distributions that 

incorporate mixing are available (Cook and Böhlke, 2000), 

use of these alternative models to understand age mixtures was 

beyond the scope of this report.

Groundwater samples with tritium >0.2 TU, 14C 

>80 pmc, and %Heterr–c <10% were classified as “Modern”; 

samples with tritium >0.2 TU, and 14C ≤80 pmc or %Heterr–c

≥10% were classified as “Mixed”; and samples with tritium ≤ 

0.2 TU, and 14C ≤80 pmc or %Heterr–c >10% were classified 

as “Pre-modern.” Groundwater age classifications are reported 

in table A4. Classification into modern, mixed, and premodern categories was sufficient to provide an appropriate 

and useful characterization for the purposes of examining 

groundwater quality.

Geochemical Conditions

Geochemical conditions investigated as potential 

explanatory factors in this report include oxidation-reduction 

characteristics, pH, and cation ratios. Oxidation-reduction 

(redox) conditions influence the mobility of many organic 

and inorganic constituents (McMahon and Chapelle, 2008). 

Redox conditions along groundwater flow paths commonly 

proceed along a well-documented sequence of Terminal 

Electron Acceptor Processes (TEAP), in which a single TEAP 

typically dominates at a particular time and aquifer location 

(Chapelle and others, 1995; Chapelle, 2001). The predominant 

TEAPs are oxygen-reducing (oxic), nitrate-reducing, 

manganese-reducing, iron-reducing, sulfate-reducing, and 

methanogenic. The presence of redox-sensitive chemical 

species suggesting more than one TEAP may indicate mixing 

of waters from different redox zones upgradient of the well, 

that the well is perforated or screened across more than one 

redox zone, or spatial heterogeneity in microbial activity in 

the aquifer. Redox conditions were represented by dissolved 

oxygen concentration and by classified redox condition 

(table A5). Dissolved oxygen (DO) concentrations were 

measured at 34 of the 35 USGS-GAMA wells. Classifications 

of redox condition were made using the framework of 

McMahon and Chapelle (2008). An automated workbook 

program was used to assign the redox classification to each 

sample (Jurgens and others, 2009b). A key component to the 

accurate classification of redox conditions using the McMahon 

and Chapelle framework is availability of DO data, which 

was lacking in one well sampled in the Madera-Chowchilla 

study unit. Because the iron, manganese, and sulfate values 

were low in that well, the DO was estimated to be equal to 

or greater than 1.0; therefore, all 35 grid and understanding 

wells had enough information to make a determination of 

redox condition (table A5). Higher concentrations of iron, 

manganese, and sulfate constituents (greater than the threshold 

value used by the McMahon and Chapelle redox framework) 

are generally indicative of reducing conditions.

The primary cations in groundwater typically are 

calcium, magnesium, sodium, and potassium. For this study, 

the cation composition of groundwater was represented by the 

ratio of calcium+magnesium to the sum of all four cations, 

in units of milliequivalents per liter. This parameter is called 

Fract-CaMg, and is equivalent to the distance from the sodium 

plus potassium apex on the cation triangle portion of a Piper 

plot (Piper, 1944).
78 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table A3. Results for analyses of noble gases in samples collected for the Madera-Chowchilla study unit, California GAMA Priority 

Basin Project.

[The five-digit number in parentheses below the constituent name is the U.S. Geological Survey parameter code used to uniquely identify a specific constituent 

or property. USGS-GAMA well identification number: MADCHOW, Madera-Chowchilla study unit grid well; MADCHOWFP, Madera-Chowchilla study 

unit understanding well. Other abbreviations: cm3 STP-g-1 H2O, cubic centimeters at standard temperature and pressure per gram of water; na, not available]

GAMA

identification

number

Sample 

collection 

data

Dissolved 

gas 

analysis 

date

Helium-3/ 

Helium-4 

(atom ratio) 

(61040)

Helium-4 

(cm3

 STP-g-1

H2

O) 

(85561)

Neon 

(cm3

 STP-g-1

H2

O) 

(61046)

Argon 

(cm3

 STP-g-1

H2

O) 

(85563)

Krypton 

(cm3

 STP-g-1

H2

O) 

(85565)

Xenon 

(cm3 STP-g-1

H2

O) 

(85567)

× 10–7 × 10–7 × 10–7 × 10–4 × 10–8 × 10–9

Grid wells

MADCHOW-01 04-14-08 12-11-09 31.67 0.54 2.34 3.25 6.78 9.14

MADCHOW-02 04-15-08 01-19-09 11.17 0.64 2.50 3.19 6.66 9.11

MADCHOW-03 04-15-08 01-19-09 16.12 0.61 2.38 3.49 7.59 9.96

MADCHOW-04 04-16-08 01-20-09 15.29 0.55 1.93 3.17 7.28 10.03

MADCHOW-05 04-16-08 01-20-09 7.10 1.77 2.63 3.18 6.67 8.90

MADCHOW-06 04-17-08 01-20-09 4.72 5.83 4.89 4.39 8.08 9.42

MADCHOW-07 04-21-08 01-06-10 12.50 0.55 2.00 3.01 6.26 8.82

MADCHOW-08 04-22-08 01-20-09 6.48 8.66 2.00 2.98 6.59 9.12

MADCHOW-09 04-22-08 12-04-09 16.25 0.47 3.80 3.15 5.69 8.82

MADCHOW-10 04-24-08 01-20-09 7.91 1.63 2.11 3.29 7.23 9.97

MADCHOW-11 04-24-08 01-20-09 10.20 4.84 8.74 6.52 10.79 11.91

MADCHOW-12 04-28-08 na na na na na na na

MADCHOW-13 04-29-08 01-21-09 11.63 0.69 2.28 3.36 7.26 9.95

MADCHOW-14 04-30-08 01-21-09 12.48 0.65 2.32 3.44 7.38 10.09

MADCHOW-15 04-30-08 12-11-09 5.25 12.89 2.18 3.24 7.20 10.15

MADCHOW-16 05-01-08 01-21-09 8.06 1.64 1.94 3.01 6.56 9.23

MADCHOW-17 05-01-08 01-28-09 10.79 0.94 1.96 2.91 6.33 7.82

MADCHOW-18 05-06-08 na na na na na na na

MADCHOW-19 05-06-08 01-21-09 4.81 2.76 2.40 3.38 7.42 10.31

MADCHOW-20 05-07-08 01-06-10 13.49 0.64 2.50 3.42 6.95 9.68

MADCHOW-21 05-07-08 01-21-09 11.80 0.56 1.93 2.98 6.48 8.54

MADCHOW-22 05-08-08 01-21-09 7.43 2.12 2.84 3.40 7.31 10.13

MADCHOW-23 05-12-08 12-14-09 6.16 12.28 2.18 3.33 7.51 9.92

MADCHOW-24 05-13-08 01-21-09 9.82 1.50 2.15 3.20 7.10 9.53

MADCHOW-25 05-13-08 01-22-09 13.11 0.78 2.63 3.63 7.38 9.69

MADCHOW-26 05-14-08 01-22-09 9.02 1.75 3.14 3.64 7.48 9.95

MADCHOW-27 05-14-08 01-22-09 32.30 0.63 2.43 3.40 7.41 9.77

MADCHOW-28 05-19-08 01-06-09 19.26 0.66 2.88 3.70 7.55 9.52

MADCHOW-29 05-20-08 01-06-10 15.22 0.73 2.84 3.62 7.37 10.34

MADCHOW-30 05-21-08 01-06-10 7.04 6.22 1.90 2.86 6.22 8.75

Understanding wells

MADCHOWFP-01 04-23-08 12-17-09 18.57 0.55 2.34 3.37 7.05 9.79

MADCHOWFP-02 05-05-08 01-21-09 11.41 0.79 2.11 3.29 7.51 10.27

MADCHOWFP-03 05-15-08 01-06-09 14.25 0.91 2.86 3.63 7.39 9.74

MADCHOWFP-04 05-21-08 01-07-09 7.44 4.93 2.20 3.22 7.06 10.07

MADCHOWFP-05 05-22-08 01-06-10 8.57 0.76 2.13 2.95 6.17 8.78
Appendix A 79

Table A4. Summary of groundwater age data and classification into modern, mixed, and pre-modern age categories for samples 

collected for the Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[USGS-GAMA well identification number: MADCHOW, Madera-Chowchilla study unit grid well; MADCHOWFP, Madera-Chowchilla study unit 

understanding well. Other abbreviations: TU, tritium units; na, data not available; >, greater than; <, less than]

USGS-GAMA well 

identification

number

Tritium 

activity 

(TU)

Carbon-14 

(percent 

modern)

Uncorrected 

carbon-14 age 

(years)

Terrigenic 

helium 

(percent of 

total helium)

Age 

classification

Grid wells

MADCHOW-01 6.2 121 < 1,000 0 Modern

MADCHOW-02 0.18 79 1,790 0 Pre-modern

MADCHOW-03 1.0 81 1,610 2.5 Modern

MADCHOW-04 4.0 106 < 1,000 16 Mixed

MADCHOW-05 0.34 77 2,020 71 Mixed

MADCHOW-06 1.7 104 < 1,000 91 Mixed

MADCHOW-07 0.40 53 5,050 10 Mixed

MADCHOW-08 0.31 50 5,420 95 Mixed

MADCHOW-09 5.2 116 < 1,000 0 Modern

MADCHOW-10 0.09 65 3,420 71 Pre-modern

MADCHOW-11 0.03 45 6,250 85 Pre-modern

MADCHOW-12 0.25 7 21,310 na Mixed

MADCHOW-13 0.37 62 3,750 21 Mixed

MADCHOW-14 0.31 84 1,310 13 Mixed

MADCHOW-15 0.15 38 7,740 97 Pre-modern

MADCHOW-16 0.12 59 4,200 73 Pre-modern

MADCHOW-17 3.1 112 < 1,000 51 Mixed

MADCHOW-18 7.1 115 < 1,000 na Modern

MADCHOW-19 0.84 72 2,560 83 Mixed

MADCHOW-20 0.40 109 < 1,000 1.7 Modern

MADCHOW-21 0.03 69 2,860 15 Pre-modern

MADCHOW-22 0.15 17 14,330 76 Pre-modern

MADCHOW-23 -0.06 5 24,110 96 Pre-modern

MADCHOW-24 1.5 55 4,750 69 Mixed

MADCHOW-25 1.1 115 < 1,000 19 Mixed

MADCHOW-26 0.25 102 < 1,000 68 Mixed

MADCHOW-27 8.5 99 < 1,000 3.7 Modern

MADCHOW-28 6.8 115 < 1,000 0 Modern

MADCHOW-29 2.7 109 < 1,000 0 Modern

MADCHOW-30 0.34 22 12,010 93 Mixed

Understanding wells

MADCHOWFP-01 5.0 101 < 1,000 0 Modern

MADCHOWFP-02 0.25 87 1,000 38 Mixed

MADCHOWFP-03 2.7 106 < 1,000 27 Mixed

MADCHOWFP-04 2.4 98 < 1,000 91 Mixed

MADCHOWFP-05 0.15 11 17,490 34 Pre-modern
80 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Table A5. Geochemical indicators for grid and understanding wells sampled in April and 

May 2008, Madera-Chowchilla study unit, 2008, California GAMA Priority Basin Project.

[USGS-GAMA well identification number: MADCHOW, Madera-Chowchilla study unit grid well; 

MADCHOWFP, Madera-Chowchilla study unit understanding well; Redox information: redox, oxidationreduction; oxic, dissolved oxygen > 0.5; anoxic (Mn), dissolved oxygen < 0.5 and manganese (IV) reducing. 

Other abbreviations: mg/L, milligrams per liter; na, not analyzed; Ca, calcium; Mg, magnesium; Fract-CaMg, 

calcium plus magnesium in milliequivalents divided by sum of calcium, magnesium, sodium, and potassium in 

milliequivalents]

USGS-GAMA well 

identification

number

Dissolved 

oxygen 

concentration,

(mg/L)

pH, 

standard 

units

Redox 

classification Fract-CaMg

Grid wells

MADCHOW-01 5.1 6.8 Oxic 0.73

MADCHOW-02 6.5 7.3 Oxic 0.55

MADCHOW-03 3.3 7.2 Oxic 0.55

MADCHOW-04 1.4 7.3 Oxic 0.66

MADCHOW-05 na 7.0 Oxic 0.58

MADCHOW-06 5.7 7.8 Oxic 0.49

MADCHOW-07 4.5 7.3 Oxic 0.66

MADCHOW-08 1.7 7.5 Oxic 0.61

MADCHOW-09 7.7 7.1 Oxic 0.79

MADCHOW-10 4.5 7.7 Oxic 0.49

MADCHOW-11 7.5 7.5 Oxic 0.59

MADCHOW-12 0.3 8.0 Anoxic (Mn) 0.29

MADCHOW-13 4.5 7.7 Oxic 0.28

MADCHOW-14 6.1 7.7 Oxic 0.58

MADCHOW-15 1.4 7.1 Oxic 0.43

MADCHOW-16 4.2 7.4 Oxic 0.53

MADCHOW-17 5.7 7.2 Oxic 0.78

MADCHOW-18 7.2 6.8 Oxic 0.66

MADCHOW-19 4 7.0 Oxic 0.64

MADCHOW-20 7.1 7.1 Oxic 0.72

MADCHOW-21 6.7 7.0 Oxic 0.60

MADCHOW-22 1.2 8.0 Oxic 0.54

MADCHOW-23 0.7 8.4 Oxic 0.16

MADCHOW-24 5.7 8.0 Oxic 0.55

MADCHOW-25 5.7 7.0 Oxic 0.78

MADCHOW-26 6 7.0 Oxic 0.72

MADCHOW-27 1.6 7.6 Oxic 0.56

MADCHOW-28 7.5 6.9 Oxic 0.78

MADCHOW-29 7.2 7.2 Oxic 0.69

MADCHOW-30 3 8.4 Oxic 0.33

Understanding wells 1.00

MADCHOWFP-01 8.2 7.4 Oxic 0.74

MADCHOWFP-02 6 7.5 Oxic 0.61

MADCHOWFP-03 7.8 6.8 Oxic 0.76

MADCHOWFP-04 3.3 7.4 Oxic 0.58

MADCHOWFP-05 1.3 7.6 Oxic 0.65
Appendix B 81

Appendix B. Comparison of CDPH and USGS-GAMA Data

Well Depths

Of the 35 the wells sampled by USGS-GAMA, 21 were 

wells listed in the CDPH database. Of the remaining 

14 wells, 7 were irrigation wells, and 7 were domestic 

wells. The assessments presented in this report are intended 

to characterize groundwater quality in the primary aquifer 

system, which is defined by the depth intervals over which 

wells listed in the CDPH database are open or perforated; 

therefore, it was important to verify that the irrigation and 

domestic wells sampled were open or perforated in the 

same depth ranges as were wells in the CDPH database. 

Well construction information is not available in the CDPH 

database, so the verification was made using information for 

the sampled wells only.

The 21 CDPH wells sampled by USGS-GAMA were 

divided into two types for comparison with the irrigation and 

domestic wells. Eight were CDPH wells serving drinking 

water to more than 4,000 people. These wells included wells 

operated by the larger cities in the study unit (Chowchilla, 

Madera, and Fresno) and wells operated by institutions 

with large resident populations (prisons). Thirteen were 

CDPH wells serving drinking water to less than 500 people. 

These wells included wells operated by schools, parks, and 

small businesses.

The median depth of CDPH wells serving large 

populations (670 ft) was significantly greater than the median 

depths of CDPH wells serving small populations (325 ft; 

p=0.002), irrigation wells (346 ft; p=0.008), or domestic 

wells (317 ft; p=0.014) (fig. B1A). There were no significant 

differences in the median depths of CDPH wells serving 

small populations, irrigation wells, and domestic wells. 

Median depths to the top of perforations for the four types 

of wells were similar, with the only significant difference 

being between CDPH wells serving large populations 

(286 ft) and irrigation wells (200 ft) (p=0.019; fig. B1B ). 

The median length of perforation interval of CDPH wells 

serving large populations (342 ft) was significantly greater 

than the median length of perforation interval of CDPH 

wells serving small populations (60 ft; p=0.001), irrigation 

wells (146 ft; p=0.040), or domestic wells (40 ft; p=0.003) 

(fig. B1C). There were no significant differences in the median 

lengths of perforation intervals of CDPH wells serving small 

populations, irrigation wells, and domestic wells. These 

comparisons indicate that these irrigation and domestic 

wells were perforated over the same depth intervals as the 

CDPH wells serving small populations, thus, these irrigation 

and domestic wells can be considered representative of the 

primary aquifer system.

Hydrochemical Facies

Major ion data for grid wells were compared with major 

ion data from all wells in the CDPH database for this study 

unit to evaluate whether the grid wells were representative of 

the range of groundwater types used for public supply. The 

datasets were compared using Piper diagrams (Piper, 1944; 

Hem, 1992). Piper diagrams show the relative contribution 

of major cations and anions (on a charge equivalent basis) as 

a percentage of the total ion content of the water (fig. B2). 

All recent (February 12, 2005–February 12, 2008) CDPH 

data having cation/anion data and an acceptable cation/anion 

balance were retrieved and plotted on these Piper diagrams 

for comparison with data from the USGS-GAMA samples. 

Cation/anion balance was calculated as the absolute value 

of the difference between the total cations and total anions 

divided by the average of the total cations and total anions, 

expressed as a percentage, and acceptable cation-anion 

balance was defined as <10%.

Similar ranges of water types were evident from grid 

wells and recent CDPH data (fig. B2). The anion compositions 

of the majority of CDPH and grid wells were classified as 

bicarbonate-type waters (anion composition greater than 60% 

bicarbonate), and most of the remainder was classified as 

bicarbonate-chloride-type. A few samples had chloride-type 

anion compositions. The cation compositions of the majority 

of CDPH and grid wells were classified as mixed-type 

(magnesium-calcium-sodium/potassium) or calcium-sodium/

potassium-type. A few samples had sodium/potassium-type 

cation compositions. The similarity of the range of relative 

abundance of major cations and anions in grid wells to that 

of the set of all CDPH wells indicates that the grid wells 

represent the diversity of water types present within the 

Madera-Chowchilla study unit.

The two differences between water chemistry data for 

grid and understanding wells and recent 3-year data for CDPH 

wells are (1) a higher proportion of the grid wells are at either 

end of the cation trend (at lowest and highest proportion 

sodium/potassium), and (2) on the anion triangle, the grid 

wells have a higher proportion that have slightly elevated 

sulfate proportion. Some of the grid wells that cause these 

differences are located in areas where there are few CDPH 

wells, generally in the western portion of the study unit.
82 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

sac11-0401_fig B1abc

A 

C

B

Depth, in feet below land surface Depth to top of perforations, in feet below land surface

Depth to top of perforations, in feet below land surface

200

0

400

600

800

100

0

200

300

400

500

600

100

0

200

300

400

500

Public supply,

small

Public supply,

large

Domestic Irrigation

Use of well

Public supply,

small

Public supply,

large

Domestic Irrigation

Use of well Use of well

Public supply,

small

Public supply,

large

Domestic Irrigation

n=8 n=13 n=6 n=5

n=8 n=13 n=6 n=5 n=8 n=13 n=6 n=6

EXPLANATION

outlier

outlier

90th percentile

75th percentile

25th percentile

10th percentile

Median

n Number of wells

Note: white box indicates group is significantly

different from all other groups

Figure B1. Boxplots showing (A) well depth, (B) depth to top of perforations, and (C) perforation length for sampled grid 

and understanding wells, grouped by well type, Madera-Chowchilla study unit, California GAMA Priority Basin Project.
Appendix B 83

sac11-0401_fig B02

PERCENT

Calcium

100 

80 

60 

40 

20 

0 

0 

20 

40 

60 

80 

100 

Magnesium

0 

20 

40 

60 

80 

100 

Sodium plus potassium

Chloride, fluoride, nitrite plus nitrate

0 

20 

40 

60 

80 

100 

100 

80 

60 

40 

20 

0 

Bicarbonate

100 

80 

60 

40 

20 

0 

Sulfate

0 

20 

40 

60 

80 

100 

Sulfate plus chloride

0 

20 

40 

60 

80 

100 

Calcium plus magnesium

100 

80 

60 

40 

20 

0 

100 

80 

60 

40 

20 

0 

PERCENT

PERCENT

CDPH well (most recent analysis with charge imbalance 

 less than 10 percent)

understanding well

grid well

EXPLANATION

Figure B2. Piper diagram for grid and understanding wells and for wells in the California Department of Public Health 

database with data during February 12, 2005–February 12, 2008, Madera-Chowchilla study unit, California GAMA 

Priority Basin Project.
84 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

Figure B3. Graphs showing relative-concentration values for (A) total dissolved solids and specific conductance, 

(B) arsenic and nitrate, (C) gross alpha particle and uranium activity, and (D) iron and manganese in groundwater 

from wells sampled by USGS-GAMA for the Madera-Chowchilla study unit that have data reported in the CDPH 

database between February 12, 2005, and February 12, 2008, California GAMA Priority Basin Project.

sac11-0401_fig B3abcd

A B

Low

Moderate

Moderate

High

Low

Moderate

Moderate

High

Low

Moderate

Moderate

High

Low

Moderate

C D Low Moderate

Low

Moderate

Moderate

High

Moderate

High

Low

Moderate

Moderate

High

0.00 0.25 0.50 0.75 1.00 1.25 1.50

0.0 0.1 0.2 0.3 0.4 0.5 0.6

0.00 0.5 1.0 1.5 2.0 2.5

0.00

0.25

0.50

0.75

1.00

1.25

1.50

0.0

0.5

1.0

1.5

2.0

2.5

3.0

USGS-GAMA analysis relative-concentration, dimensionless USGS-GAMA analysis relative-concentration, dimensionless

USGS-GAMA analysis relative-concentration, dimensionless

CDPH analysis relative-concentration, dimensionless CDPH analysis relative-concentration, dimensionless

1:1 line

1:1 line

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.0

0.5

1.0

1.5

2.0

8

10

0.0 0.5 1.0 1.5 2.0 8 10

USGS-GAMA analysis relative-concentration, dimensionless

1:1 line

1:1 line

CDPH analysis relative-concentration, dimensionless CDPH analysis relative-concentration, dimensionless

EXPLANATION

(n=20) (n=12)

Nitrate Arsenic

USGS and CDPH detections

USGS detections, CDPH nondetections

USGS and CDPH nondetections

EXPLANATION

(n=1) (n=10)

Uranium Gross alpha particle

USGS and CDPH detections

USGS detections, CDPH nondetections

EXPLANATION

(n=15) (n=15)

Iron Manganese

USGS and CDPH detections

USGS detections, CDPH nondetections

USGS nondetections, CDPH detections

USGS and CDPH nondetections

EXPLANATION

Specific conductance (n=18)

Total dissolved solids (n=11)
Appendix B 85

Water-Quality Constituents

Data acquired by USGS-GAMA and data from the CDPH 

database were compared to assess the validity of merging 

data from these two sources to create the dataset of inorganic 

and radioactive constituents used in the spatially weighted 

calculations of aquifer-scale proportions. Comparisons were 

made using data for the 20 grid and understanding wells that 

had data in the CDPH database between February 12, 2005, 

and February 12, 2008.

Eighteen wells had USGS-GAMA and CDPH data for 

specific conductance, and 11 wells had data for TDS from 

both sources (fig. B3A). USGS-GAMA specific conductance 

and TDS values were significantly higher than the CDPH 

values (Wilcoxon ranked-pair test; p=0.012 and p=0.011). 

The RC categories (high, moderate, or low) assigned to the 

wells were the same, however, whether the USGS-GAMA 

or CDPH values were used. Thus, although the datasets were 

significantly different, this difference was not large enough to 

affect the outcome of the status assessment.

Twenty wells had USGS-GAMA and CDPH data for 

nitrate, and 12 wells had data for arsenic from both sources 

(fig. B3B). There were no significant differences between 

USGS-GAMA and CDPH values for nitrate or arsenic 

(Wilcoxon ranked-pair test; p=0.95 for nitrate; p=0.9 for the 

7 wells with arsenic detections in both USGS-GAMA and 

CDPH). The RC categories (high, moderate, or low) assigned 

to the wells were the same whether the USGS-GAMA or 

CDPH values were used.

Ten wells had USGS-GAMA and CDPH data for gross 

alpha particle activity, and 1 well had data for uranium 

activity from both sources (fig. B3C). For the five data pairs 

with detections in both datasets, USGS-GAMA values were 

higher than CDPH values, although the difference was not 

statistically significant because of the small number of pairs 

(Wilcoxon ranked-pair test; p=0.059). The RC categories 

(high, moderate, or low) assigned to the wells were the same 

whether the USGS-GAMA or CDPH values were used.

Fifteen wells had USGS-GAMA and CDPH data for 

iron and manganese (fig. B3D). Three wells had detections 

reported in the CDPH database, and the USGS-GAMA 

results for those wells were either detections below the CDPH 

reporting limit of 100 μg/L or nondetections (laboratory 

reporting limit of 8 μg/L). Although the difference between 

the two datasets was not statistically significant due to the 

smallness of the datasets, the difference did have significant 

effects on the status assessment results. Iron was the only 

constituent for which the RC categories assigned to the wells 

by using USGS-GAMA and CDPH data were different: two 

wells that have low RCs calculated by using USGS-GAMA 

data have high RCs calculated by using CDPH data. These two 

wells, MADCHOW-05 and -09, have low RCs for manganese 

in both datasets. Thirteen CDPH wells had high RCs of iron 

reported between February 12, 2005, and February 12, 2008, 

and 9 of those 13 had low RCs of manganese. Given that 

iron reduction typically occurs at lower oxidation-reduction 

potentials than manganese reduction (Appelo and Postma, 

2005; McMahon and Chapelle, 2008), one would not expect 

to detect elevated iron concentrations in groundwater that 

does not have elevated manganese concentrations. Between 

May 2004 and October 2010, USGS-GAMA collected samples 

from 87 wells statewide that had high RCs of iron; of these 87, 

only 3 had low RCs of manganese. The presence of high RCs 

of iron with low RCs of manganese in CDPH data but not in 

USGS data may be caused by differences in sample collection 

methods. USGS-GAMA trace element concentrations were 

measured in filtered groundwater samples (Shelton and others, 

2009). CDPH trace element concentrations may have been 

measured on filtered or unfiltered groundwater samples. 

Suspended particles in unfiltered samples may contain iron 

if they are derived from metal parts of wells. For this reason, 

the high RCs of iron with low RCs of manganese are not 

considered representative of the water quality in the aquifer.
86 Status and Understanding of Groundwater Quality in the Madera-Chowchilla Study Unit, 2008: California GAMA Priority Basin Project

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Shelton and others—Status and Understanding of Groundwater Quality in the Madera-Chochilla Study Unit, 2008:

California GAMA Priority Basin Project—SIR 2012–5094