U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2014–5174

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 Sierra Nevada 

Regional Study Unit, 2008: California GAMA Priority Basin Project

Photo placement
Front Cover Map: Groundwater basins categorized by sampling priority. Location of groundwater basin 

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

Sampling priority

Study area

Low-use basins

Priority basins

Areas that are outside CDWR-defined

 groundwater basins

Cover photographs: 

Front cover: Wellhouse and holding tank near Angels Camp, California. (Photograph taken by Barbara J. 

Dawson, U.S. Geological Survey.)

Back cover: View near Tuolumne Meadows in Yosemite National Park, California. (Photograph taken by 

George L. Bennett, U.S. Geological Survey.)
Status and Understanding of Groundwater 

Quality in the Sierra Nevada Regional 

Study Unit, 2008: California GAMA Priority 

Basin Project

By Miranda S. Fram and Kenneth Belitz

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 2014–5174

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

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Suggested citation:

Fram, M.S., and Belitz, Kenneth, 2014, Status and understanding of groundwater quality in the Sierra Nevada 

Regional study unit, 2008—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations 

Report 2014–5174, 118 p., http://dx.doi.org/10.3133/20145174.

ISBN 978-1-4113-3867-8

ISSN 2328-0328 (online)

ISSN 2328-031X (print)
iii

Contents

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

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

Hydrogeologic Setting of the SNR Study Unit...........................................................................................7

Geology...................................................................................................................................................7

Hydrology and Climate.........................................................................................................................7

Land Use...............................................................................................................................................11

Methods.........................................................................................................................................................11

Status Assessment.............................................................................................................................11

Groundwater Quality Defined as Relative-Concentrations ................................................12

Data Used for Status Assessment ..........................................................................................13

Data for Grid-Based Calculations of Aquifer-Scale Proportions..............................13

Additional Data Used for Spatially Weighted Calculations of 

Aquifer-Scale Proportions .................................................................................14

Selection of Constituents for Evaluation................................................................................14

Calculation of Aquifer-Scale Proportions..............................................................................21

Understanding Assessment..............................................................................................................24

Tests of Correlations Among Potential Explanatory Factors and Between 

Potential Explanatory Factors and Water Quality...................................................24

Comparison of Aquifer-Scale Proportions Among Primary Aquifer Systems .................25

Characteristics of the Primary Aquifer System .............................................................................25

Geology........................................................................................................................................25

Land Use......................................................................................................................................25

Climate and Hydrology..............................................................................................................30

Depth and Groundwater Age...................................................................................................30

Geochemical Conditions...........................................................................................................32

Status and Understanding of Groundwater Quality...............................................................................33

Inorganic Constituents.......................................................................................................................33

Trace Elements...........................................................................................................................43

Arsenic................................................................................................................................43

Boron ................................................................................................................................56

Fluoride...............................................................................................................................57

Other Trace Elements.......................................................................................................57

Nutrients......................................................................................................................................57

Uranium and Radioactive Constituents..................................................................................58

Uranium ..............................................................................................................................58

Gross Alpha Particle Activity..........................................................................................58

Radon-222...........................................................................................................................58

Constituents with SMCL Benchmarks....................................................................................59

Manganese and Iron........................................................................................................59

Organic and Special-Interest Constituents....................................................................................60

Herbicides...................................................................................................................................60

Solvents.......................................................................................................................................64

Gasoline Oxygenates ................................................................................................................64

Trihalomethanes.........................................................................................................................66

Perchlorate .................................................................................................................................72
iv

Contents—Continued

Summary........................................................................................................................................................74

Acknowledgments.......................................................................................................................................75

References ...................................................................................................................................................75

Appendix A. Lithologic-Grid Wells.........................................................................................................83

Appendix B. Attribution of Ancillary Data ............................................................................................89

Appendix C. Effect of Data Gaps on Aquifer-Scale Proportions for Inorganic Constituents.....104

Appendix D. Radioactivity.....................................................................................................................108

Appendix E. Comparison of Major-Ion Data ......................................................................................109

Appendix F. Additional Water-Quality Data........................................................................................115

Figures

1. Maps showing location of the California hydrogeologic provinces and the 

Sierra Nevada Regional study unit, California Groundwater Ambient 

Monitoring and Assessment Priority Basin Project and selected 

major geologic features in California ........................................................................................3

2. Map showing county, national park, and California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project, 

Sierra Nevada Regional study unit boundaries.......................................................................6

3. Maps showing simplified geology, elevation and major hydrologic features, and 

land use for the Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project................................................8

4. Map showing locations of public-supply wells from the California Department 

of Public Health database, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................23

5. Bar chart showing area assigned to the four aquifer lithologies in the study unit 

as a whole, and the areas represented by wells sampled by the U.S. Geological 

Survey having data for 24 or more inorganic constituents with health-based 

benchmarks, by wells in the California Department of Public Health database 

having data for 10 or more inorganic constituents with health-based benchmarks, 

and by any well having data for 10 or more inorganic constituents with 

health-based benchmarks, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................26

6. Ternary diagrams showing percentage of urban, agricultural, and natural land use 

in the Sierra Nevada Regional study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment Priority Basin Project in the aquifer lithologic units, 

and the areas surrounding each USGS-GAMA well ............................................................27

7. Bar chart showing numbers of sites sampled by the U.S. Geological Survey 

in each aquifer lithologic class and depth class, Sierra Nevada Regional 

study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment Priority Basin Project..........................................................................................31

8. Bar charts showing relation between depth classification and groundwater age 

classification for the Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................32
v

Figures—Continued

9. Graph showing maximum relative-concentrations of constituents detected 

in lithologic-grid wells by constituent class for the Sierra Nevada Regional 

study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment Priority Basin Project..........................................................................................34

10. Graphs showing relative-concentrations of selected trace elements with 

regulatory and non-regulatory health-based benchmarks, nutrients and 

radioactive constituents with regulatory health-based benchmarks, and 

salinity indicators and trace elements with non-regulatory secondary 

maximum contaminant level benchmarks, in USGS-grid wells, Sierra 

Nevada Regional study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment Priority Basin Project..............................................................35

11. Graphs showing aquifer-scale proportions for arsenic, boron, fluoride, and 

uranium and for nitrate, total dissolved solids, manganese, and organic 

constituents in the aggregated, granitic, metamorphic, sedimentary, and volcanic 

primary aquifer systems, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................44

12. Maps showing concentrations of arsenic, boron, fluoride, nitrate, uranium, and 

manganese for wells sampled by USGS-GAMA for the Sierra Nevada Regional 

study unit in 2008, the Tahoe-Martis study unit in 2007, and the Central Sierra 

and Southern Sierra study units in 2006 and all wells in the California Department 

of Public Health database with data during the period May 2006 through 

October 2008, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................46

13. Graph showing area-weighted detection frequency and maximum 

relative-concentration of organic and special-interest constituents 

detected by the U.S. Geological Survey in samples collected for the 

Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................61

14. Graphs showing area-weighted detection frequencies and 

relative-concentrations of selected organic and special-interest 

constituents, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................62

15. Maps showing maximum relative-concentrations of herbicides, solvents, the 

gasoline oxygenate methyl tert-butyl ether, the trihalomethane chloroform, and 

perchlorate for USGS-GAMA wells, and all wells in the California Department of 

Public Health database with data during the period May 2006 through 

October 2008, Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................67

16. Graph showing predicted probability of detecting perchlorate at concentrations 

above three threshold concentrations in groundwater under natural conditions 

at four aridity indices to observed detection frequencies of perchlorate at 

concentrations above the four threshold concentrations and average aridity 

indices for sets of 21 or 20 groundwater samples, Sierra Nevada Regional 

study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment Priority Basin Project..........................................................................................73
Tables

1. Relative-concentration categories used for assessing groundwater quality 

in the Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................12

2. Summary of numbers of wells used in the calculations of aquifer-scale 

proportions for the Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................14

3. Summary of constituent groups and number of wells sampled by the U.S. 

Geological Survey for the Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................15

4A. Benchmark type and value and reporting levels for constituents detected at 

moderate or high relative-concentrations and organic constituents detected 

with more than 10 percent detection frequency in at least one primary aquifer 

system, Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................16

4B. Benchmark type and value and reporting levels for constituents detected only 

at low relative-concentrations and constituents that were detected and did 

not have benchmarks, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................18

5. Constituents reported at concentrations greater than benchmarks in the 

California Department of Public Health database prior to May 2006 but not 

during the time period used for the status assessment (May 2006 through 

October 2008), Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................20

6A. Results from multi-stage Kruskal-Wallis tests for differences in median values of 

selected potential explanatory factors among samples classified into groups by 

aquifer lithology class, oxidation-reduction class, depth class, or groundwater age 

class, Sierra Nevada Regional study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment Priority Basin Project..............................................................28

6B. Results from Spearman’s rho tests for correlations between selected potential 

explanatory factors, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................29

6C. Results of contingency table tests for association between selected potential 

explanatory factors, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................30

7A. Aquifer-scale proportions for inorganic constituents for the granitic, 

metamorphic, sedimentary, and volcanic primary aquifer systems, 

Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................38

7B. Aquifer-scale proportions for inorganic constituents for the aggregated primary 

aquifer system, Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................40
Tables—Continued

8A. Summary of aquifer-scale proportions in the granitic, metamorphic, sedimentary, 

volcanic, and aggregated primary aquifer systems for inorganic constituent classes 

with health-based benchmarks, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................41

8B. Summary of aquifer-scale proportions in the granitic, metamorphic, 

sedimentary, volcanic, and aggregated primary aquifer systems for 

inorganic constituent classes with secondary maximum contaminent 

level benchmarks, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment Priority Basin Project.....................42

9. Results of contingency table tests for differences in aquifer-scale proportions 

of selected inorganic constituents and constituent classes between granitic, 

metamorphic, sedimentary, and volcanic primary aquifer systems, Sierra 

Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment Priority Basin Project ..................................................................................42

10A. Results of multi-stage Kruskal-Wallis tests for differences in median values 

of selected potential explanatory factors and water-quality constituents 

between samples classified into groups by aquifer lithologic class, 

oxidation-reduction class, site type class, or groundwater age class, 

Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................52

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

explanatory factors and selected water-quality constituents, Sierra Nevada 

Regional study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment Priority Basin Project..........................................................................................54

11. Results of Spearman’s rho tests for correlations between selected water-quality 

constituents, Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................56

12. Aquifer-scale proportions of organic and special-interest constituents for the 

granitic, metamorphic, sedimentary, volcanic, and aggregated primary aquifer 

systems, Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment Priority Basin Project..............................................63

13. Summary of aquifer-scale proportions for organic constituent classes for the 

granitic, metamorphic, sedimentary, volcanic, and aggregated primary aquifer 

systems, Sierra Nevada Regional study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment Priority Basin Project..............................................................65

14. Results of contingency table tests for differences in aquifer-scale proportions 

of selected organic constituents and constituent classes between granitic, 

metamorphic, sedimentary, and volcanic primary aquifer systems, Sierra Nevada 

Regional study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment Priority Basin Project..........................................................................................66
viii

Conversion Factors, Datums, and Abbreviations and 

Acronyms

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

acre 4,047 square meter (m2

)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2

)

acre 0.004047 square kilometer (km2

)

square foot (ft2

) 0.09290 square meter (m2)

square mile (mi2

) 2.590 square kilometer (km2) 

Flow rate

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

Radioactivity

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

picocurie per liter (pCi/L) 0.313 tritium units (TU)

SI to Inch/Pound

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

Area

square kilometer (km2

) 0.3861 square mile (mi2)

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

°F=(1.8×°C)+32

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

Conversion Factors, Datums, and Abbreviations and 

Acronyms—Continued

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 the distance above the vertical datum.

Selected Terms and Symbols

α significance level

> greater than

≥ greater than or equal to

< less than

≤ less than or equal to

Abbreviations and Acronyms

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

BQ benchmark quotient

ft bls feet below land surface

G granitic aquifer lithology

GAMA California Groundwater Ambient Monitoring and Assessment Program

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

HBSL health-based screening level

LUFT leaking (or formerly leaking) underground fuel tank

M metamorphic aquifer lithology

Ma mega annum, million years ago

MCL-CA California Department of Public Health maximum contaminant level 

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

NAWQA National Water-Quality Assessment Program (USGS

NL-CA California Department of Public Health notification level 

p p-value (probability)

pmC percent modern carbon

RC relative-concentration

RSD5-US U.S. Environmental Protection Agency risk-specific dose at a risk factor of 

10–5

S sedimentary aquifer lithology
x

Conversion Factors, Datums, and Abbreviations and 

Acronyms—Continued 

Abbreviations and Acronyms—Continued Abbreviations and Acronyms

SNR Sierra Nevada Regional study unit

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 process

TT-US U.S. Environmental Protection Agency treatment technique

TU tritium unit

V volcanic aquifer lithology

Organizations

CDPH California Department of Public Health (Department of Health Services prior 

to July 1, 2007)

CDWR California Department of Water Resources

LLNL Lawrence Livermore National Laboratory

SWRCB State Water Resources Control Board (California)

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

Selected Chemical Names

14C carbon-14

δ13C ratio of carbon-13 to carbon-12 in the sample relative to the ratio of 

carbon-13 to carbon-12 in the PeeDee belemnite standard, in units of per mil

DO dissolved oxygen

MTBE methyl tert-butyl ether

NDMA N-nitrosodimethylamine

PCE tetrachloroethene (perchloroethene)

1,2-DCA 1,2-dichloroethane

TDS total dissolved solids

THM trihalomethane

VOC volatile organic compound
Status and Understanding of Groundwater Quality in 

the Sierra Nevada Regional Study Unit, 2008: California 

GAMA Priority Basin Project

By Miranda S. Fram and Kenneth Belitz

Abstract

Groundwater quality in the Sierra Nevada Regional 

(SNR) study unit was investigated as part of the California 

State Water Resources Control Board’s Groundwater Ambient 

Monitoring and Assessment Program Priority Basin Project. 

The study was designed to provide statistically unbiased 

assessments of the quality of untreated groundwater within 

the primary aquifer system of the Sierra Nevada. The primary 

aquifer system for the SNR study unit was delineated by the 

depth intervals over which wells in the State of California’s 

database of public drinking-water supply wells are open or 

screened. Two types of assessments were made: (1) a status 

assessment that described the current quality of the groundwater resource, and (2) an evaluation of relations between 

groundwater quality and potential explanatory factors that 

represent characteristics of the primary aquifer system. The 

assessments characterize untreated groundwater quality, rather 

than the quality of treated drinking water delivered to consumers by water distributors.

The status assessment was based on water-quality data 

collected by the U.S. Geological Survey from 83 wells in the 

SNR study unit in 2008 and from 117 wells in 3 small study 

units within the SNR study unit in 2006–07 and on waterquality data compiled in the State’s database for 1,066 wells 

sampled in 2006–08. To provide some context for the results, 

water-quality data were converted to relative-concentrations 

(RCs), which are the sample concentrations divided by 

the concentrations of Federal or California regulatory and 

non-regulatory benchmarks for drinking-water quality. RCs 

for inorganic constituents (major ions, trace elements, nutrients, and radioactive constituents) were classified as “high” 

(RC > 1.0, indicating that concentration is above the benchmark), “moderate” (1.0 ≥ RC > 0.5), or “low” (RC ≤ 0.5). 

For organic constituents (volatile organic compounds and 

pesticides) and special-interest constituents (perchlorate and 

N-nitrosodimethylamine [NDMA]), the boundary between 

moderate and low RCs was set at 0.1. All benchmarks used 

for organic constituents were health-based, whereas healthbased and aesthetic-based benchmarks were used for inorganic 

constituents.

The primary metric used for quantifying regional-scale 

groundwater quality was “aquifer-scale proportion.” Aquiferscale proportions were calculated as the areal percentages 

of the primary aquifer system having high, moderate, and 

low RCs for a given constituent or class of constituents. The 

SNR study unit area was classified into four aquifer lithologic 

types—granitic rocks, metamorphic rocks, sedimentary 

deposits, and volcanic rocks—and aquifer-scale proportions 

were calculated on an area-weighted basis for each of the 

four aquifer lithologies and for the study unit as a whole 

(aggregated system).

The results of the status assessment indicated that 

inorganic constituents were present at high and moderate 

RCs in greater proportions in the SNR study unit aggregated 

primary aquifer system than were organic constituents and 

that there were significant differences (p < 0.05) between the 

four aquifer lithologies. One or more inorganic constituents 

with health-based benchmarks were present at high RCs in 

16 percent of the aggregated primary aquifer system and at 

moderate RCs in 21 percent. Arsenic (9.7 percent), uranium 

(2.9 percent), boron (2.0 percent), fluoride (1.8 percent), and 

nitrate (1.4 percent) were the constituents most commonly 

present at high RCs.

For inorganic constituents with aesthetic-based benchmarks, 18 percent of the aggregated primary aquifer system 

had high RCs of one or more constituent, and 6.8 percent had 

moderate RCs. Iron (15.8 percent), manganese (15.1 percent), 

and total dissolved solids (1.3 percent) were the constituents 

most commonly present at high RCs.

Organic constituents were not detected in 72 percent of 

the primary aquifer system. One or more organic constituents 

had high RCs in 0.1 percent of the primary aquifer system, 

moderate RCs in 3.0 percent, and low RCs in 25 percent. 

Proportions of the four lithologic primary aquifer systems with 

high or moderate concentrations of organic constituents were 

not significantly different. Three organic constituents had areaweighted detection frequencies greater than 10 percent in the 

primary aquifer system as a whole or at least one of the four 

lithologic primary aquifer systems: the gasoline oxygenate 

methyl tert-butyl ether, the trihalomethane chloroform, 

and the herbicide simazine. The special-interest constituent 
2 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

perchlorate was detected at high RCs in 0.01 percent of the 

primary aquifer system and at moderate RCs in 1.0 percent, 

and detection frequencies could be accounted for by the 

distribution of perchlorate under natural conditions.

Statistical tests were used to evaluate relations between 

constituent concentrations and potential explanatory factors 

descriptive of land use, geography, depth, geochemical 

conditions, and groundwater age. Higher concentrations of 

trace elements, radioactive constituents, and constituents 

with aesthetic-based benchmarks generally were associated 

with anoxic conditions, higher pH, and location within a 

particular compositional band in the Sierra Nevada batholith corresponding to the southwestern part of the study unit. 

High concentrations of organic constituents generally were 

associated with greater proportions of urban land use. No 

significant relations were observed between the concentrations 

of organic constituents and measures of well depth or 

groundwater age, perhaps because of the high proportions of 

springs and modern groundwater in the dataset.

Introduction

Groundwater composes approximately 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 (website at 

http://www.waterboards.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 groundwater information system, operated 

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

Basin Project primarily focused on the deep portion of the 

groundwater resource, and the SWRCB Domestic Well Project 

generally focused on the shallow aquifer systems.

The SWRCB initiated the GAMA Program in 2000 in 

response to a legislative mandate (State of California, 1999, 

2001a). 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) and 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 Project include the California 

Department of Public Health (CDPH), California Department 

of Pesticide Regulation, California Department of Water 

Resources (CDWR), and local water agencies and well owners 

(Kulongoski and Belitz, 2004).

The ranges of hydrologic, geologic, and climatic conditions that exist in California were considered in this 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. 1A). These hydrogeologic provinces 

include groundwater basins defined by the CDWR (California 

Department of Water Resources, 2003). Groundwater basins 

in California generally consist of relatively permeable, 

unconsolidated deposits of alluvial origin. Eighty percent of 

the approximately 16,000 active and standby public drinkingwater supply wells listed in the State’s database (hereinafter 

referred to as CDPH wells) are located in CDWR-defined 

groundwater basins. The CDPH Drinking Water Program was 

transferred to the SWRCB Division of Drinking Water on 

July 1, 2014, however the label “CDPH” is retained in this 

report for consistency with other GAMA Priority Basin Project publications and because the CDPH had jurisdiction over 

public-supply wells at the time that samples were collected for 

this study.

Groundwater basins 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 the number of 1-square-mile (mi2

) sections 

having registered pesticide applications (Belitz and others, 

2003). Of the 472 basins defined by the CDWR, 116 contained 

approximately 95 percent of the CDPH wells located in basins. 

These 116 basins were defined as “priority basins,” and the 

remaining 356 basins were defined as “low-use” basins. All of 

the priority basins, selected low-use basins, and selected areas 

outside of groundwater basins were grouped into 35 GAMA 

Priority Basin Project study units. The 35 study units together 

represent approximately 95 percent of all CDPH wells. Of the 

10 hydrogeologic provinces, the Sierra Nevada province contains the largest number of CDPH wells outside of the CDWRdefined groundwater basins. About 97 percent of the total area 

and approximately 85 percent of the CDPH wells in the province are outside of the CDWR-defined groundwater basins. The 

entire Sierra Nevada hydrogeologic province was defined as 

the Sierra Nevada Regional (SNR) study unit (fig. 1A).

The GAMA Priority Basin Project was designed 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 explanation of the relations between water quality 
Introduction 3

Basin and Range

Central

Valley

Klamath

Mountains

Desert

Cascades and

Modoc Plateau

Transverse Ranges and

selected Peninsular Ranges

Southern Coast

Ranges

Sierra Nevada Regional

 (SNR) study unit

Northern

Coast

Ranges

San Diego

Drainages

Bakersfield

San

Francisco

Sacramento

OREGON

NEVADA

MEXICO

ARIZONA

Redding

Los Angeles

San Diego

Pacific Ocean

0 200 MILES

0 200 KILOMETERS

100

100

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Provinces from Belitz and others, 2003

sac14-0538_Figure 01 loc map

A

Figure 1. (A) Location of the California hydrogeologic provinces and the Sierra Nevada Regional study unit, California Groundwater 

Ambient Monitoring and Assessment (GAMA) Priority Basin Project and (B) selected major geologic features in California.
4 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Melo

n

e s Fault Zone

Western

Metamorphic

Belt

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

North American Datum of 1983 (NAD 83)

Geology simplified from Saucedo and others (2000).

EXPLANATION

Geologic units

Mesozoic granitic rocks

Paleozoic and Mesozoic metamorphic and

 sedimentry rocks and non-granitic

 plutonic rocks

Cenozoic sedimentary deposits

Cenozoic volcanic and volcaniclastic rocks

Pacific Ocean

OREGON

NEVADA

MEXICO

ARIZONA UTAH

Owens

Valley

Central

Valley

S a n

A n d r e a s

F a u l t

Garlock Fault

B

0 200 MILES

0 200 KILOMETERS

Bakersfield

Los Angeles

San Diego

Redding

Sacramento

San

Francisco

sac14-0538_fig 01b Geologic units

Figure 1. —Continued
Introduction 5

and selected explanatory factors, and (3) trends: detection of 

changes in groundwater quality over time (Kulongoski and 

Belitz, 2004). These three objectives were modeled after those 

of the USGS National Water-Quality Assessment (NAWQA) 

Program (Hirsch and others, 1988). The GAMA Priority Basin 

Project 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 system for a study unit 

is defined by the depths of the screened or open intervals of 

the wells listed in the CDPH database for the study unit. The 

CDPH database lists wells used for public drinking-water supplies and includes wells from systems classified as “community” (such as those for cities, towns, and mobile-home parks), 

“non-transient, non-community” (such as those for schools, 

workplaces, and restaurants), and “transient, non-community” 

(such as those for campgrounds, parks, and highway rest 

areas) (California Department of Public Health, 2013a). 

Groundwater quality in shallower or deeper parts of the aquifer system may differ from that in the primary aquifer system. 

In particular, shallower groundwater may be more vulnerable 

to surface-derived contamination.

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

unit description: description of the hydrogeologic setting of 

the SNR study unit, (2) a status assessment: assessment of 

the status of the current quality of groundwater in the primary 

aquifer system in the study unit, and (3) an understanding 

assessment: discussion of statistical tests of correlations 

between water quality and potential explanatory factors. 

Trends in groundwater quality are not discussed in this report.

In this report, features of the hydrogeologic setting are 

described on the scale of the entire SNR study unit; features of 

specific alluvial basins and delineated hard-rock aquifers are 

not discussed. Geology, land-use patterns, and hydrology of 

the study unit are summarized. Characteristics of the primary 

aquifer system, including geology, land use, climate, depth, 

groundwater age distribution, and geochemical conditions are 

described by using ancillary data compiled for the 83 sites 

sampled by USGS-GAMA for the study unit.

GAMA status assessments are designed to provide a 

statistically representative characterization of groundwater 

quality in the primary aquifer system at the study-unit scale 

(Belitz and others, 2003, 2010). This report describes methods 

used in designing the sampling networks for the status 

assessment and estimating “aquifer-scale proportions” for constituents (Belitz and others, 2010). Aquifer-scale proportion is 

defined as the areal proportion of the primary aquifer system 

having groundwater of defined quality. Water-quality data for 

samples collected by the USGS for the SNR study unit and 

details of sample collection, analysis, and quality-assurance 

procedures are reported by Shelton and others (2010).

Water-quality data from 1,266 wells from 3 sources were 

used in the status assessment: (1) the 83 wells sampled by 

USGS-GAMA for the SNR study unit (appendix A; Shelton 

and others, 2010), (2) the 117 wells sampled in 2006–07 by 

USGS-GAMA for the Tahoe-Martis, Central Sierra Nevada, 

and Southern Sierra Nevada study units that are within the 

SNR (Fram and Belitz, 2012), and (3) the 1,066 wells in the 

CDPH database that had water-quality data during the period 

May 1, 2006, through October 31, 2008. The Tahoe-Martis, 

Central Sierra Nevada, and Southern Sierra Nevada study 

units are three small study units that are entirely contained 

within the SNR study unit (fig. 2). Two methods were used to 

calculate aquifer-scale proportions from these data, both of 

which were based on a 30-cell grid covering the SNR study 

unit: the methods either used data from one well per aquifer 

lithology per cell (grid-based method) or from many wells per 

aquifer lithology per cell (spatially weighted method) (Belitz 

and others, 2010). Aquifer-scale proportions for constituents 

and classes of constituents were computed for the SNR 

primary aquifer system as a whole and for the primary aquifer 

systems in granitic, metamorphic, sedimentary, and volcanic 

aquifer lithologies.

To provide context, the water-quality data discussed in 

this report are compared to California and Federal drinkingwater regulatory and non-regulatory benchmarks for treated 

drinking water. Groundwater quality is defined in terms 

of relative-concentrations (RCs), which are calculated by 

dividing the concentration of a constituent in groundwater 

by 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 units, not the treated drinking water delivered to 

consumers by water purveyors. After withdrawal from the 

ground, water may be treated, disinfected, and (or) blended 

with other waters to maintain acceptable water quality. 

Regulatory benchmarks apply to treated water that is served to 

the consumer, not to untreated groundwater.

Relations between water quality and potential explanatory 

factors were evaluated by using statistical tests for correlations 

and associations. Two types of evaluations were made. The 

first type examined differences in aquifer-scale proportions for 

constituents and classes of constituents between the granitic, 

metamorphic, sedimentary, and volcanic primary aquifer 

systems. The second type examined correlations between 

constituent concentrations and values of potential explanatory 

factors and differences in median concentrations of constituents between samples grouped into categories by potential 

explanatory factors. Results of these statistical tests have been 

tabulated and are briefly discussed and compared to results for 

the Tahoe-Martis, Central Sierra, and Southern Sierra study 

units. Detailed discussions of the factors affecting groundwater 

quality in the Sierra Nevada were presented by Fram and Belitz 

(2012) and thus are not repeated in this report.
6 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Chico

Sonora

Quincy

Bishop

Truckee

Oakhurst

Fresno

Tehachapi

Susanville

Placerville

Sacramento

Nevada

City

Bakersfield

South Lake Tahoe

Southern Sierra

study unit

Central Sierra

study unit

Tahoe-Martis

study unit

Yosemite

Sequoia

Kings Canyon

KERN CO

FRESNO CO

TULARE

CO

INYO

CO

MONO CO

PLUMAS CO

MONTEREY CO

MADERA CO

MERCED CO

SAN LUIS OBISPO CO

TUOLUMNE

CO

BUTTE CO

KINGS CO

PLACER CO

LASSEN

CO

EL DORADO CO

MARIPOSA

CO STANISLAUS CO

SIERRA CO

NEVADA CO

SANTA BARBARA CO

SAN BENITO CO

SAN JOAQUIN

CO

YUBA CO

ALPINE

CO

CALAVERAS CO

TEHAMA

CO

SACRAMENTO

CO

SANTA

CLARA

CO

AMADOR CO

SUTTER CO

CALIFORNIA

NEVADA

sac14-0538_Figure 02

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

EXPLANATION

Pacific Ocean

Sierra Nevada Regional

 study unit 

Sierra Nevada

Regional

study unit 

Small study units within

 the Sierra Nevada

 Regional study unit

National park

Lake or reservoir

County boundary

City or town

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Figure 2. County, national park, and California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project, 

Sierra Nevada Regional (SNR) study unit boundaries.
Hydrogeologic Setting of the SNR Study Unit 7

Hydrogeologic Setting of the SNR 

Study Unit

The SNR study unit covers an area of approximately 

25,000 mi2

 (66,000 square kilometers [km2]) and includes 

all or parts of 20 California counties: Lassen, Plumas, Butte, 

Sierra, Yuba, Nevada, Placer, El Dorado, Sacramento, 

Amador, Alpine, Calaveras, Tuolumne, Mono, Mariposa, 

Madera, Fresno, Inyo, Tulare, and Kern Counties (fig. 2). The 

study unit includes the Sierra Nevada, which is the mountain 

range extending along the eastern side of California, and 

the foothills on the western slope of the Sierra Nevada. The 

western boundary of the study unit is defined by the limit of 

late Tertiary and Quaternary sediments of the Central Valley 

(figs. 1A,B). The eastern boundary is defined by the limits of 

late Tertiary and Quaternary sediments in the Owens Valley, 

the Nevada State line, and the watersheds of the basins 

between the Owens Valley and the Nevada State line. The 

study unit is terminated at the southern end by the Garlock 

Fault (fig. 1B) and at the northern end by the Cascades Range 

and Modoc Plateau (fig. 1A). The SNR study unit encompasses 

a broad range of geologic, hydrologic, climatic, and land-use 

settings. Settings are described on the scale of the entire SNR 

study unit; features of specific alluvial basins and delineated 

hard-rock aquifers are not discussed.

Geology

The dominant geologic feature of the SNR study unit is 

the Sierra Nevada batholith, a complex of Mesozoic tonalite, 

granodiorite, quartz diorite, and granite plutons that intruded 

the North American Plate above the subducting Farallon 

Plate, mostly between 80 and 150 mega annum (Ma; million 

years ago) (Evernden and Kistler, 1970; Saleeby and others, 

2008). The batholith has regional variations in chemical and 

mineralogical composition that are in part due to variations in 

the composition of the terrain into which the plutons intruded 

(Ague and Brimhall, 1987, 1988).

The Western Metamorphic Belt occupies the foothills in 

the northern half of the study unit (fig. 1B) and consists of a 

deformed package of imbricate thrust slices of Mesozoic and 

Paleozoic ophiolites and oceanic sedimentary rocks that were 

accreted onto the western margin of the North American Plate 

as subduction proceeded (Day and others, 1985). The Mother 

Lode gold deposits are hosted by quartz veins injected along 

the Melones Fault zone, a major structural feature that likely 

marks the Mesozoic subduction plate boundary (Böhlke and 

Kistler, 1986). Roof pendants of older Mesozoic and Paleozoic 

metamorphic rocks, remnants of the terrain into which the 

plutons intruded, are scattered throughout the batholith, 

particularly in the southern part of the province (fig. 1B).

Late Cenozoic (approximately 35 Ma to 1 Ma) volcanism 

covered parts of the Sierra Nevada, particularly in the 

northern part of the study unit (Christiansen and others, 

1992). Geologic evidence suggests that by the Late Miocene 

(16 Ma to 12 Ma), areas to the east of the Sierra Nevada 

were in prominent rain shadow, indicating that most of the 

uplift of the modern Sierra Nevada range had occurred by 

that time (Crowley and others, 2008; Mulch and others, 

2008). Continued uplift has occurred within the last 5 Ma 

(Wakabayashi and Sawyer, 2001). Parts of the Sierra Nevada 

were glaciated in the multiple major glacial advances during 

the Pleistocene (Birkeland, 1964; Raub and others, 2006).

The organizing feature for SNR study-unit design was 

aquifer lithology. Public drinking-water supply wells in the 

SNR study unit are located in fractured hard-rock aquifers 

and in alluvial basins. In contrast, in nearly all other GAMA 

Priority Basin Project study units, the primary aquifer 

system consists solely of alluvial basins. For the purpose 

of examining broad relations between aquifer lithology and 

groundwater quality, aquifer lithology was classified into four 

categories: the fractured hard-rock aquifers were classified 

as granitic, metamorphic, or volcanic rocks, and the alluvial 

basins and other accumulations of sediment were classified as 

sedimentary deposits. The SNR study unit is approximately 

50 percent granitic rocks, 30 percent metamorphic rocks, 

13 percent volcanic rocks, and 7 percent sedimentary deposits 

(fig. 3A). These four rock types have different geochemical 

and hydrologic characteristics, and thus may host groundwater 

with different water-quality characteristics. The classifications 

were made from the California State geologic map (Jennings, 

1977; Saucedo and others, 2000) and are described in greater 

detail in appendix B.

Hydrology and Climate

The hydrologic features and the climate within the SNR 

study unit are closely related to the topography. The western 

side of the Sierra Nevada slopes gradually from the crest 

towards the Central Valley, and the eastern side is a steep 

escarpment that marks the western edge of active extension 

in the Basin and Range province. The elevation of the Sierra 

Nevada crest is highest in the south, with several peaks over 

14,000 feet (ft) (4,270 meters [m]), and decreases northward, 

with the highest peaks north of Lake Tahoe only about 8,000 ft 

in elevation (2,440 m) (fig. 3B).

Like much of California, the Sierra Nevada has a 

Mediterranean climate, with warm, dry summers and cool, 

wet winters. Annual precipitation ranges from 10 to 80 inches 

per year (in/yr) (25 to 200 centimeters per year [cm/yr]), and 

most of the precipitation falls in the winter season, between 

October and April (PRISM Climate Group, Oregon State 

University, 2007). At elevations above about 6,500 ft (about 

2,000 m), most of the precipitation falls as snow. Precipitation 

generally increases with elevation and latitude, reflecting the 

orographic effect in which moisture is drawn out of weather 

systems as they travel from west to east, up the western slope 

of the Sierra Nevada, and the regional north to south gradient. 

The eastern edge of the study unit is in the rain shadow of the 

Sierra Nevada crest and receives less precipitation than the 

west side.
8 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

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24

12

26

26

18

30

24

12

23

24

12

sac14-0538_Figure 03a

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Granitic

Metamorphic

Sedimentary

Volcanic

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Pacific Ocean

A

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit wells 

Grid well

Extra well

Sierra Nevada Regional

 study unit grid cell 

Water body

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Figure 3. (A) Simplified geology, (B) elevation and major hydrologic features, and (C) land use for the Sierra Nevada Regional study 

unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Hydrogeologic Setting of the SNR Study Unit 9

Fresno River

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

12

26

26

18

30

24

12

23

24

12

San Joaquin River

Kern River

Merced River

Owens River

Kern RiverKern River

Chowchilla River

Tuolumne River

Calaveras River Stanislaus River

Mok elumne River

Cosumnes River

Feather River

Bear River

American River

Sacramento River

Kings River

Tule River

sac14-0538_Figure 03b

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Granitic

Metamorphic

Sedimentary

Volcanic

Pacific Ocean

B

EXPLANATION

Sierra Nevada Regional

 study unit 

<2,000

>2,000 to 4,000

>4,000 to 6,000

>6,000 to 8,000

>8,000 to 10,000

Elevation, in feet

Major river

Water body

USGS-GAMA Sierra Nevada

 Regional study unit wells 

Grid well

Extra well

>10,000 

Sierra Nevada Regional

 study unit grid cell 

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Lake

Tahoe

Mono

Lake

Figure 3. —Continued
10 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

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28

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sac14-0538_Figure 03c

121° 120° 119° 118°

40°

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36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Granitic

Metamorphic

Sedimentary

Volcanic

Land use

Pacific Ocean

C

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit wells 

Grid well

Extra well

Sierra Nevada Regional

 study unit grid cell 

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 3. —Continued
Methods 11

Runoff from Sierra Nevada watersheds, primarily in 

the form of snow melt, provides approximately 50 percent 

of California’s developed water (Carle, 2004). River systems 

on the western slope of the Sierra Nevada drain into the 

Sacramento River, the San Joaquin River, or the Tulare Basin. 

Streams on the eastern side primarily feed Lake Tahoe or the 

Owens River (fig. 3B). Nearly all of the river systems have 

large dams and reservoirs that are operated to provide water 

supplies and (or) to control flooding outside of the Sierra 

Nevada.

Groundwater is used extensively for public and domestic 

drinking-water supplies in the Sierra Nevada, and much of 

this groundwater comes from granitic-, metamorphic-, or 

volcanic-rock aquifers, rather than from sediment deposits 

in groundwater basins. Granitic and metamorphic rocks of 

the Sierra Nevada have low permeability except where they 

are extensively fractured. Fractures and joints typically are 

most extensive in size and number in the upper few hundred 

feet of bedrock and typically decrease with depth (Page and 

others, 1984; Borchers, 1996). Fracture permeability tends to 

decrease with depth because of increased lithostatic pressure 

(Ingebritsen and Sanford, 1998); however, because crystalline 

rocks remain brittle to depths of several kilometers, some 

fracture permeability may persist to great depths (Freeze 

and Cherry, 1979). The three-dimensional complexity and 

variability of fracture systems can cause well yields and water 

quality to vary widely on a local scale. Recharge to fractured 

hard-rock aquifers of the SNR study unit occurs by direct 

infiltration of precipitation and snow melt and by infiltration 

from lakes and streams.

Although groundwater basins compose a small part of 

the SNR study unit, they typically have a greater density of 

groundwater use than other areas because they commonly 

contain greater population densities and (or) greater amounts 

of agricultural land compared to other areas. In addition, 

wells in groundwater basins typically have greater yields than 

those in the surrounding fractured-rock aquifers (for example, 

California Department of Water Resources, 2003). Recharge to 

groundwater basins of the Sierra Nevada occurs through two 

primary mechanisms: (1) mountain-front recharge, which is 

runoff from precipitation on the mountain that percolates into 

the basin through the coarser alluvial fan deposits along the 

basin margin and through stream channels crossing the basin; 

and (2) mountain-block recharge, which is water that has 

percolated through the mountain bedrock aquifer and enters 

the basin from the sub-surface (for example, Wilson and Guan, 

2004). Precipitation falling directly on the basin percolates 

vertically downward through the sediments of the basin or 

enters stream channels.

Land Use

Land use in the entire SNR study unit is 91.2 percent 

natural, 4.6 percent agricultural, and 4.2 percent urban 

(fig. 3C). 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; appendix B). Natural land in the Sierra Nevada consists 

mainly of shrub lands and grasslands at lower elevations, 

forests at higher elevations, and bare rock at the highest 

elevations. Approximately 40 percent of the area is managed 

by the U.S. Forest Service, and approximately 20 percent 

is under the jurisdiction of the National Park Service or the 

Bureau of Land Management (Sierra Nevada Ecosystem 

Project, 1996). Most of the remaining 40 percent is privately 

owned.

Agricultural land constitutes less than 5 percent of total 

land use and is concentrated in the valleys of the southern 

Sierra Nevada and areas of the foothills adjacent to the 

Central Valley (fig. 3C). Urban land also constitutes less 

than 5 percent of total land use, but this category is growing 

rapidly. The permanent population of the province rose from 

0.3 million in 1970 to 0.8 million in 2000 and is predicted to 

grow to 1.7–2.0 million by 2040 (Duane, 1996; Sierra Nevada 

Ecosystem Project, 1996). Much of the population growth has 

occurred along the Interstate 80 and Highway 50 corridors 

(highways that connect Sacramento to Reno, Nevada, and 

to the southern end of Lake Tahoe, respectively; fig. 3C). 

As of 1990, 80 percent of the permanent population lived on 

3 percent of the land area (Sierra Nevada Ecosystem Project, 

1996). Recreation and tourism are the primary industries in the 

Sierra Nevada, and the resulting transient population is much 

larger than the permanent population.

Methods

This section describes the methods used for the status 

assessment and for evaluating data for potential explanatory 

factors (the understanding assessment). Methods used to 

collect and analyze groundwater samples and results for the 

quality-control assessment are described by Shelton and others 

(2010).

Status Assessment

The status assessment was 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 

data used for the assessment, and (3) calculating aquiferscale proportions. Two statistical approaches were used 

for calculating aquifer-scale proportions: a “grid-based” 

approach that used one well to represent each grid sub-cell 

and a “spatially weighted” approach that used many wells to 

represent each grid sub-cell (Belitz and others, 2010).

The database contains historical records from more 

than 25,000 wells, requiring the use of targeted retrievals to 

effectively access relevant water-quality data. For example, 

for the area representing the SNR study unit, the historical 

CDPH database contains more than 500,000 records from 

about 1,500 wells. The CDPH data were used in the spatially 

weighted calculations of aquifer-scale proportions.
12 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Groundwater Quality Defined as 

Relative-Concentrations

In this study, groundwater-quality data are presented as 

relative-concentrations (RCs), the concentrations of constituents measured in groundwater relative to regulatory and 

non-regulatory benchmarks used to evaluate drinking-water 

quality. The use of RC is similar to the approaches employed 

by other studies to place the concentrations of constituents in 

groundwater within a toxicological context (for example, U.S. 

Environmental Protection Agency, 1986; Toccalino and others, 

2004; Toccalino and Norman, 2006; Rowe and others, 2007). 

RC is defined as:

Sample concentration Relative-concentration (RC) Benchmark concentration = .

An RC value less than 1 (<1.0) indicates that the sample concentration is less than the benchmark, and an RC value greater 

than 1 (>1.0) indicates that the sample concentration is greater 

than the benchmark. The use of RCs permits comparison on 

a single scale of multiple constituents present at a wide range 

of concentrations. RCs can only be computed for constituents 

with water-quality benchmarks; therefore, constituents without 

water-quality benchmarks were not included in the status 

assessment.

Regulatory and non-regulatory benchmarks apply to 

treated water that is served to the consumer, not to untreated 

groundwater. However, to place the results in a humanhealth context, concentrations of constituents measured in 

the untreated groundwater were compared to benchmarks 

established by the U.S. Environmental Protection Agency 

(USEPA) and CDPH (U.S. Environmental Protection Agency, 

1999a, 2009, 2012; California Department of Public Health, 

2010, 2013b). The benchmarks used for each constituent were 

selected in the following order of priority:

1. Regulatory, health-based levels established by the CDPH 

and USEPA: maximum contaminant levels (MCL-CA and 

MCL-US, where the prefix MCL indicates maximum contaminant level, and the suffixes “-CA” and “-US” indicate 

CDPH and USEPA, respectively), action levels (AL-US), 

and treatment technique levels (TT-US).

2. Non-regulatory, non-health-based, aesthetic-based 

levels established by the CDPH and USEPA: secondary 

maximum contaminant levels (SMCL-CA and 

SMCL-US). For constituents with both recommended and 

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

were used. 

3. Non-regulatory, health-based levels established by the 

CDPH and USEPA: CDPH notification levels (NL-CA), 

USEPA lifetime health advisory levels (HAL-US), and 

USEPA risk-specific doses for 1:100,000 (RSD5-US).

For constituents with multiple types of benchmarks, this 

hierarchy sometimes did not result in selection of the benchmark with the lowest concentration. Additional information on 

the types of benchmarks used and listings of the benchmark 

values for all constituents analyzed are provided by Shelton 

and others (2010).

Toccalino and others (2004), Toccalino and Norman 

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

ratio of the measured sample concentration to the benchmark 

concentration (either MCL-US or health-based screening level 

[HBSL]) and defined this ratio as the benchmark quotient 

(BQ). HBSLs were not used in this report because HBSLs 

are not currently used as benchmarks by California drinkingwater regulatory agencies. Because different water-quality 

benchmarks are used to calculate RCs and BQs, the terms 

are not interchangeable. For example, the RC and BQ values 

were different from one another for approximately half of the 

constituents detected in samples from USGS-GAMA study 

units in the Sierra Nevada hydrogeologic province (Fram and 

Belitz, 2012).

For ease of discussion, RCs of constituents were 

classified into low, moderate, and high categories (table 1). RC 

values >1.0 were defined as “high” for all constituents. For 

inorganic constituents (trace elements, nutrients, radioactive 

constituents, and inorganic constituents having SMCL 

benchmarks), RC values >0.5 and ≤1.0 were defined as 

“moderate,” and RC values ≤0.5 were defined as “low.” For 

organic and special-interest constituents, RC values >0.1 and 

≤1.0 were defined as “moderate,” and RC values ≤0.1 were 

defined as “low.” Although more complex classifications could 

be devised based on the properties and sources of individual 

constituents, use of a single moderate/low threshold value 

for each of the two major groups of constituents provided a 

consistent objective criteria for distinguishing constituents 

present at moderate rather than low concentrations.

Other studies have used the same boundary value 

between low and moderate RCs for inorganic and organic 

constituents—either 0.5 (for example, U.S. Environmental 

Protection Agency, 1999b) or 0.1 (for example, Toccalino and 

Table 1. Relative-concentration categories used for assessing 

groundwater quality in the Sierra Nevada Regional (SNR) study 

unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.

[Relative-concentration (RC) is defined as the measured value divided by a 

benchmark value. Abbreviations: >, greater than; ≤, less than or equal to]

RC category RCs for organic and specialinterest constituents

RCs for inorganic 

constituents

High >1 >1

Moderate >0.1 and ≤1 >0.5 and ≤1

Low ≤0.1 ≤0.5
Methods 13

others, 2010). The primary reason for using a higher boundary 

value for inorganic constituents in this study was to focus 

attention on the inorganic constituents most prevalent at concentrations closest to benchmark concentrations. In a national 

survey of water quality in aquifers used for public drinkingwater supply, Toccalino and others (2010) found that organic 

constituents (pesticides and volatile organic compounds 

[VOCs]) were present at BQ > 0.1 in approximately 10 percent 

of the samples and that inorganic constituents (nutrients, 

trace elements, and radioactive constituents) were present 

at BQ > 0.1 in approximately 80 percent of the samples. By 

setting the boundary between low and moderate BQs at 0.1, 

Toccalino and others (2010) produced a conservative assessment of water quality that is protective of human health and 

provides an early indication of potential groundwater contamination issues. Organic constituents generally are anthropogenic and enter groundwater as a result of human activities 

(intentional, such as pesticide applications, and unintentional, 

such as leaks and spills) at the land surface. Concentrations of 

the organic constituents may change rapidly in groundwater; 

therefore, such early warning may be vital for planning and 

implementing measures to protect aquifer systems from 

further contamination and to mitigate existing contamination. 

Resources may be appropriately focused on the 10 percent of 

wells that have BQ > 0.1 of organic constituents; however, a 

similar focusing of resources would be less feasible for the 

inorganic constituents because most of the wells (80 percent) 

have inorganic constituents present at BQ > 0.1. Inorganic 

constituents typically are naturally occurring in groundwater, 

and their concentrations usually are stable or change slowly 

compared to those of organic constituents. Having a boundary 

between low and moderate RCs (or BQs) of 0.5 allows 

identification of inorganic constituents—from among the 

many that may be present—that are most prevalent at concentrations close to benchmarks and therefore may warrant more 

immediate attention from water-resource managers.

The boundary between low and moderate RCs is not 

intended as a demarcation of the presence of contamination 

from anthropogenic sources. For example, concentrations 

of nitrate in groundwater greater than 1 milligram per liter 

(mg/L) generally are considered to indicate contamination 

from anthropogenic sources (Nolan and Hitt, 2003; Dubrovsky 

and others, 2010). Setting the boundary between low and 

moderate RCs at 0.5 for nitrate (which corresponds to 5 mg/L 

for nitrate) allows some contamination from anthropogenic 

sources in groundwater with a low RC for nitrate. Nitrate 

and the other nutrient constituents were treated as inorganic 

constituents, with the boundary between low and moderate 

RCs set at an RC of 0.5 for this study. Similarly, groundwater 

containing human-made anthropogenic organic constituents 

with RCs less than 0.1 is classified as having low RC for 

organic constituents, even though contamination from 

anthropogenic sources is present.

Setting the boundary between moderate and low RCs at 

0.5 for inorganic constituents, rather than 0.1, also facilitated 

the use of water-quality data from the CDPH database in 

the status assessment. Twenty-three inorganic constituents 

with health-based benchmarks had data from both the CDPH 

database and USGS-GAMA. RCs of reporting limits used by 

USGS-GAMA were <0.1 for all 23 constituents (Fram and 

Belitz, 2012); thus, the difference between low and moderate 

RCs in groundwater samples could be distinguished whether 

the boundary was set at 0.1 or 0.5. In contrast, the median RC 

of the most prevalent reporting limit reported in the CDPH 

database was 0.1, and 11 of the constituents had reporting 

limits with RCs >0.1 (Fram and Belitz, 2012). If the boundary 

were set at 0.1, then data from the CDPH database would yield 

only minimum estimates of the prevalence of groundwater 

with moderate RCs of these 11 constituents; therefore, the 

boundary value was set at 0.5.

Data Used for Status Assessment

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. Although other organizations also collect waterquality data, the CDPH data are the only data available from a 

Statewide database of groundwater chemistry that are suitable 

for comprehensive analysis.

Data for Grid-Based Calculations of Aquifer-Scale 

Proportions

The data used for the grid-based calculations of aquiferscale proportions were from wells sampled by USGS-GAMA. 

Detailed descriptions of the methods used to identify wells 

for sampling are given in Shelton and others (2010). Briefly, 

the SNR study unit was divided into 30 equal-area grid cells 

(2,200 km2 each; fig. 3A) (Scott, 1990), and each cell was 

subdivided into 1 to 4 sub-cells, 1 for each of the 4 aquifer 

lithologies (granitic rock, metamorphic rock, sedimentary 

deposits, and volcanic rock) present in the cell. All the CDPH 

wells in a cell were assigned random ranks, and the highest 

ranked well in each sub-cell for which permission to sample 

could be obtained and which met basic sampling criteria was 

selected as the lithologic-grid well to represent that sub-cell. 

Not all cells contained areas of all four aquifer lithologies, and 

not all aquifer lithologies present in a cell contained wells. 

The 30 grid cells each had 2 to 4 aquifer lithologies containing 

CDPH wells, resulting in total of 91 possible lithologic-grid 

sub-cells. USGS-GAMA sampled wells in 82 of the 91 

possible lithologic-grid sub-cells (table 2). One additional 

non-grid well was sampled in one sub-cell. Of the 83 wells 

sampled by USGS-GAMA, 76 were listed in the CDPH database, and 7 were unlisted public drinking-water supply wells.
14 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 2. Summary of numbers of wells used in the calculations of aquifer-scale proportions for the Sierra Nevada Regional (SNR) 

study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[A total of 132 wells were sampled by USGS-GAMA for the Tahoe-Martis, Central Sierra, and Southern Sierra study units; 11 of these wells were also sampled 

by USGS-GAMA for the Sierra Nevada Regional study unit, and 4 wells were monitoring wells not considered representative of the primary aquifer system. 

A total of 1,238 wells had data for at least one constituent in the CDPH database; 172 of those wells were also sampled by USGS-GAMA. Abbreviations: 

CDPH, California Department of Public Health; USGS, U.S. Geological Survey]

Aquifer 

lithology

Number of 

sub-cells

Grid wells sampled 

by USGS-GAMA for 

SNR study unit

Additional wells 

sampled by USGSGAMA for SNR 

study unit

Wells sampled by USGSGAMA for Tahoe-Martis, 

Central Sierra, Southern 

Sierra study units

Other wells in 

CDPH database

Granitic rocks 29 28 0 41 568

Metamorphic rocks 24 23 1 11 221

Sedimentary rocks 22 16 0 45 202

Volcanic rocks 19 15 0 20 75

Total 91 82 1 117 1,066 

The top-ranked lithologic-grid well in each cell also was 

member of a second network, the fundamental-grid network. 

These 30 wells were named with an alphanumeric GAMA_ID 

consisting of an initial prefix identifying the study unit 

(SIERRA), a second prefix indicating aquifer lithology (G, M, 

S, and V for granitic, metamorphic, sedimentary, and volcanic aquifer lithologies), and a number indicating the order of 

sample collection (appendix A; figs. A1A,B; table A1). The 

other 52 lithologic-grid wells (and the 1 extra well) were 

named in the same way, except that the second prefix included 

an “L” for lithologic grid (GL, ML, SL, and VL for granitic, 

metamorphic, sedimentary, and volcanic aquifer lithologies). 

The fundamental grid was used for data analysis by Shelton 

and others (2010), but was not used for data analysis in this 

report.

Samples collected from USGS-grid wells were analyzed 

for 211 or 214 constituents (table 3). Water-quality data collected by USGS-GAMA are tabulated in Shelton and others 

(2010) and also are available from the SWRCB’s online 

groundwater information system GeoTracker GAMA (website 

at http://www.waterboards.ca.gov/gama/geotracker_gama.

shtml). Twenty of the sites were developed springs, and 

63 were wells. For ease of discussion, all sites are referred to 

as wells unless the difference between wells and springs is 

important to the discussion.

Additional Data Used for Spatially Weighted Calculations 

of Aquifer-Scale Proportions

The spatially weighted calculations of aquifer-scale 

proportions used data from 1,266 wells having data for 

at least 1 water-quality constituent: 83 wells sampled by 

USGS-GAMA for the SNR study unit, 117 wells sampled by 

USGS-GAMA for the Tahoe-Martis, Central Sierra Nevada, 

and Southern Sierra Nevada study units (Fram and Belitz, 

2012), and 1,066 wells in the CDPH database having waterquality data for samples collected between May 1, 2006, and 

October 31, 2008 (table 2). This count of 1,066 CDPH wells 

does not include the 172 CDPH wells that were among the 

190 wells sampled by USGS-GAMA. Water-quality data 

collected by the CDPH are available from the SWRCB’s 

online groundwater information system GeoTracker GAMA 

(website at http://www.waterboards.ca.gov/gama/geotracker_

gama.shtml). Eleven of the wells sampled by USGS-GAMA 

for the SNR study unit also were sampled for the TahoeMartis, Central Sierra Nevada, or Southern Sierra Nevada 

study units; the data from the sampling for the SNR study 

unit in 2008 were used. For the 172 wells sampled by USGSGAMA that also had CDPH data for 1 or more constituents, 

the USGS-GAMA data were used.

Selection of Constituents for Evaluation

Aquifer-scale proportions are presented for a subset of 214 constituents analyzed in samples collected by 

USGS-GAMA for the SNR study unit (table 3). This subset 

was selected by using the following criteria:

• Constituents present at high or moderate RCs (table 1) 

in any well sampled by USGS-GAMA for the SNR 

study unit or the Tahoe-Martis, Central Sierra Nevada, 

or Southern Sierra Nevada study units, or in the CDPH 

database for any sample collected between May 1, 

2006, and October 31, 2008. 

• Organic constituents having area-weighted detection 

frequencies >10 percent in the USGS-GAMA samples 

collected for the SNR study unit for the study unit 

as a whole or for one or more of the four aquifer 

lithologies.

These criteria identified 27 inorganic constituents, 

7 organic constituents, and 1 special-interest constituent 

(table 4A). An additional 20 inorganic constituents and 

15 organic constituents were detected by USGS-GAMA in 

samples from the SNR study unit, but these constituents either 

have no drinking-water-quality benchmarks or were only 
Methods 15

Table 3. Summary of constituent groups and number of wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada 

Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[na, not analyzed]

Constituent groups Analytical schedule1

Regular Enhanced

Number of wells 55 28

Number of constituents

Inorganic constituents

Specific conductance 1 1

Nutrients 5 5

Major ions, alkalinity, and total dissolved solids 12 12

Trace elements2 24 24

Uranium activity3

 or uranium concentration2 1 1

Radon-222 activity na 1

Radium activity4 na 1

Gross alpha and beta particle activities5 2 2

Organic constituents6

Volatile organic compounds (VOCs)7 85 85

Pesticides and degradates 63 63

Constituents of special interest

Perchlorate 1 1

N-Nitrosodimethylamine (NDMA) na 1

Geochemical and age-dating tracers

Dissolved oxygen, pH, and temperature 3 3

Arsenic and iron redox species ratios 2 2

Carbon-14 and δ13C of dissolved carbonates 2 2

Tritium 1 1

Noble gases (helium, neon, argon, krypton, xenon) and 3

He/4He (8) 6 6

δ2

H and δ18O stable isotopes of water 2 2

87Sr/86Sr of dissolved strontium 1 1

Sum: 211 214

1

“Regular” and “enhanced” schedules correspond to the “intermediate” and “slow” schedules of Shelton and others (2010). Tiered sampling schedules were 

used to reduce costs.

2

Uranium was measured in two ways, as uranium concentration by the same analytical method used to measure trace elements, and as uranium activity. Uranium is not counted as a trace element.

3

Uranium activity equals the sum of the three isotopes measured: uranium-234, uranium-235, and uranium-238.

4

Radium activity equals the sum of the two isotopes measured: radium-226 and radium-228.

5

Both gross alpha particle and gross beta particle radiation were measured after 72-hour and 30-day holding times; data from the 72-hour measurement are 

used in this report.

6

The enhanced schedule also had 14 pharmaceutical compounds analyzed. Results are presented in Fram and Belitz (2011b).

7

Includes 10 constituents classified as fumigants or fumigant synthesis byproducts.

8

Noble gas and helium isotope data are presented in appendix F.
16 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 4A. Benchmark type and value and reporting levels for constituents detected at moderate or high relative-concentrations and 

organic constituents detected with more than 10 percent detection frequency in at least one primary aquifer system, Sierra Nevada 

Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Inorganic constituents selected if maximum value measured in USGS-GAMA samples or reported in CDPH database between May 2006 and October 2008 

had RC > 0.5. Organic and special-interest constituents selected if maximum value had RC > 0.1, or if detection frequency at any concentration was greater than 

10 percent. Relative-concentration (RC) is defined as the measured value divided by the benchmark value. Benchmark type: Non-regulatory, aesthetic-based 

benchmarks: SMCL-CA, California Department of Public Health (CDPH) secondary maximum contaminant level. Non-regulatory, health-based benchmarks: 

HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level. Regulatory, health-based benchmarks: MCL-US, USEPA maximum contaminant level; Prop AMCL-US, proposed USEPA alternative maximum contaminant level; AL-US, USEPA action level; MCL-CA, CDPH maximum contaminant 

level. Units: μg/L, micrograms per liter; mg/L, milligrams per liter; μS/cm, microsiemens per centimeter; pCi/L, picocuries per liter. Abbreviations: USGS, 

U.S. Geological Survey; USEPA, U.S. Environmental Protection Agency; N, nitrogen; na, not available; ssLc, sample-specific critical level; >, greater than]

Constituent1

Benchmarks

Units

Reporting levels3 Relations to 

explanatory 

factors tested Type2 Value USGS CDPH

Trace elements

Aluminum4 MCL-CA 1,000 μg/L 111.6 50 No

Antimony MCL-US 6 μg/L 0.02 6 No

Arsenic MCL-US 10 μg/L 0.03 2 Yes

Beryllium4 MCL-US 4 μg/L 0.01 1 No

Boron NL-CA 1,000 μg/L 2 na Yes

Cadmium4 MCL-US 5 μg/L 0.01 1 No

Chromium4 MCL-CA 50 μg/L 110.42 1 No

Copper4 AL-US 1,300 μg/L 111.7 50 No

Fluoride MCL-CA 2 mg/L 0.04 0.1 Yes

Lead4,5 AL-US 15 μg/L 110.65 5 No

Mercury4 MCL-US 2 μg/L 110.012 0.5 No

Molybdenum HAL-US 40 μg/L 0.02 na No

Nickel4 MCL-CA 100 μg/L 110.36 10 No

Selenium MCL-US 50 μg/L 0.02 5 No

Strontium5 HAL-US 4,000 μg/L 0.4 na No

Uranium and radioactive constituents

Gross alpha particle activity MCL-US 15 pCi/L ssLC 3 Yes

Radium activity MCL-US 5 pCi/L ssLC 1 No

Radon-222 activity Prop AMCL-US 4,000 pCi/L ssLC na Yes

Uranium6

 activity MCL-CA 20 pCi/L ssLC 1 Yes

Nutrients

Nitrate, as N7 MCL-US 10 mg/L 0.02 0.45 Yes

Inorganic constituents with secondary maximum contaminant levels (SMCL)

Specific conductance8 SMCL-CA 1,600 μS/cm 5 na No

Chloride4,5 SMCL-CA 500 mg/L 0.06 2 No

Total dissolved solids8

 (TDS) SMCL-CA 1,000 mg/L 5 na No

Sulfate SMCL-CA 500 mg/L 0.09 2 No

Iron SMCL-CA 300 μg/L 116 100 Yes

Manganese SMCL-CA 50 μg/L 110.2 20 Yes

Zinc4,5 SMCL-CA 5,000 μg/L 114.8 50 No
Methods 17

Table 4A. Benchmark type and value and reporting levels for constituents detected at moderate or high relative-concentrations and 

organic constituents detected with more than 10 percent detection frequency in at least one primary aquifer system, Sierra Nevada 

Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Inorganic constituents selected if maximum value measured in USGS-GAMA samples or reported in CDPH database between May 2006 and October 2008 

had RC > 0.5. Organic and special-interest constituents selected if maximum value had RC > 0.1, or if detection frequency at any concentration was greater than 

10 percent. Relative-concentration (RC) is defined as the measured value divided by the benchmark value. Benchmark type: Non-regulatory, aesthetic-based 

benchmarks: SMCL-CA, California Department of Public Health (CDPH) secondary maximum contaminant level. Non-regulatory, health-based benchmarks: 

HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level. Regulatory, health-based benchmarks: MCL-US, USEPA maximum contaminant level; Prop AMCL-US, proposed USEPA alternative maximum contaminant level; AL-US, USEPA action level; MCL-CA, CDPH maximum contaminant 

level. Units: μg/L, micrograms per liter; mg/L, milligrams per liter; μS/cm, microsiemens per centimeter; pCi/L, picocuries per liter. Abbreviations: USGS, 

U.S. Geological Survey; USEPA, U.S. Environmental Protection Agency; N, nitrogen; na, not available; ssLc, sample-specific critical level; >, greater than]

Constituent1

Benchmarks

Units

Reporting levels3 Relations to 

explanatory 

factors tested Type2 Value USGS CDPH

Volatile organic compounds

Chloroform9 MCL-US 80 μg/L 0.01 0.5 Yes12

Benzene10 MCL-CA 1 μg/L 0.008 0.5 No

Methyl tert-butyl ether4,9 (MTBE) MCL-CA 13 μg/L 0.05 3 Yes12

Carbon tetrachloride10 MCL-CA 0.5 μg/L 0.03 0.5 No

1,2-Dichloroethane MCL-CA 0.5 μg/L 0.03 0.5 No

Tetrachloroethene (PCE) MCL-US 5 μg/L 0.02 0.5 Yes12

Pesticides

Simazine9 MCL-US 4 μg/L 0.003 1 Yes12

Special-interest constituent

Perchlorate4,9 MCL-CA 6 μg/L 0.1 4 Yes

1

Typical uses and (or) potential sources of constituents to groundwater are briefly discussed in the text for some constituents. Additional information may be 

obtained from Hem (1985), U.S. Environmental Protection Agency (2014), and California Department of Public Health (2014).

2

Maximum contaminant level benchmarks are listed as MCL-US when the MCL-US and MCL-CA are identical and as MCL-CA when the MCL-CA is lower 

than the MCL-US or no MCL-US exists. Sources of benchmarks: 

MCL-CA, SMCL-CA: California Department of Public Health (2013b)

MCL-US, AL-US: U.S. Environmental Protection Agency (2009)

NL-CA: California Department of Public Health (2010)

HAL-US: U.S. Environmental Protection Agency (2012)

Prop AMCL-US: U.S. Environmental Protection Agency (1999a)

3

USGS reporting level for most constituents is the long-term method detection level (Shelton and others, 2010). CDPH reporting level is the most common 

reporting level used to report non-detections for the study unit.

4

Selected on the basis of concentrations reported in CDPH database. Constituent also detected in samples from the SNR study unit at low relativeconcentrations.

5

Selected on the basis of concentrations reported in samples from the Tahoe-Martis, Central Sierra, or Southern Sierra study units. Constituent also detected in 

samples from the SNR study unit at low relative-concentrations.

6

The MCL-US for uranium is 30 μg/L. Uranium data in the CDPH database generally are reported in units of picocuries per liter, and most USGS-GAMA 

samples also were analyzed for uranium isotope activity. For samples having only uranium measured in units of micrograms per liter, the data were converted to 

activities using a conversion factor of 0.79 (see appendix D).

7

Concentrations of nitrate, as nitrate, reported in the CDPH data are converted to concentrations of nitrate, as nitrogen (nitrate-N), for comparison with USGSGAMA data. 

8

Aquifer-scale proportions were not calculated for specific conductance (SC). For the 198 wells that had data for SC, but not TDS, SC was converted to TDS.

9

Selected on the basis of detection frequency in the Sierra Nevada Regional study unit.

10Selected on the basis of concentrations reported in samples from the Tahoe-Martis, Central Sierra, or Southern Sierra study units.

11USGS reporting level is a study reporting level (Olsen and others, 2010).

12The organic constituents are evaluated as constituent classes rather than as individual constituents because none of the individual organic constituents 

were present at high RC in greater than 2 percent of the primary aquifer system, but at least one member of the class had an area-weighted detection frequency 

>10 percent in at least one of the four aquifer lithologies or in the study unit as a whole. The four qualifying classes are: trihalomethanes (chloroform was the 

only constituent detected), gasoline oxygenates (MTBE was the only constituent detected), solvents (8 solvents detected), and pesticides (3 herbicides detected).
18 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 4B. Benchmark type and value and reporting levels for constituents detected only at low relative-concentrations and 

constituents that were detected and did not have benchmarks, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Low concentrations are defined as RC ≤ 0.5 for inorganic constituents and as RC ≤ 0.1 for organic constituents. Relative-concentration (RC) is defined as the 

measured value divided by the benchmark value. Benchmark type: Non-regulatory, aesthetic-based benchmarks: SMCL-CA, CDPH secondary maximum 

contaminant level. Non-regulatory, health-based benchmarks: HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level. Regulatory, 

health-based benchmarks: MCL-US, USEPA maximum contaminant level; Prop AMCL-US, proposed USEPA alternative maximum contaminant level; 

AL-US, USEPA action level; MCL-CA, California Department of Public Health (CDPH) maximum contaminant level. Units: μg/L, micrograms per liter; 

mg/L, milligrams per liter; μS/cm, microsiemens per centimeter; pCi/L, picocuries per liter. Abbreviations: N, nitrogen; na, not available.; P, phosphorus; ssLc, 

sample-specific critical level; ≤, less than or equal to]

Constituent1 Benchmarks

Units Reporting levels3

Type2 Value USGS CDPH

Inorganic constituents detected only at low concentrations

Ammonia, as N HAL-US 24.7 mg/L 0.01 1

Nitrite, as N MCL-US 1 mg/L 0.001 0.4

Barium MCL-CA 1,000 μg/L 0.1 100

Silver SMCL-CA 100 μg/L 0.1 10

Thallium MCL-US 2 μg/L 0.02 1

Vanadium NL-CA 50 μg/L 0.05 3

Gross beta particle activity MCL-US 50 pCi/L ssLC 3

Detected inorganic constituents without benchmarks

Total nitrogen na na mg/L 0.03 na

Orthophosphate, as P na na mg/L 0.003 na

Calcium na na mg/L 0.01 1

Magnesium na na mg/L 0.006 2

Potassium na na mg/L 0.01 2

Sodium na na mg/L 0.06 na

Alkalinity na na mg/L 1 20

Bromide na na mg/L 0.01 na

Iodide na na mg/L 0.001 na

Silica na na mg/L 0.009 na

Cobalt na na μg/L 0.02 na

Lithium na na μg/L 0.3 na

Tungsten na na μg/L 0.03 na

Organic constituents detected only at low concentrations and detection frequency less than 10 percent

Carbon disulfide NL-CA 160 μg/L 0.02 na

1,4-Dichlorobenzene MCL-CA 5 μg/L 0.01 0.5

1,1-Dichloroethane MCL-CA 5 μg/L 0.02 0.5

1,1-Dichloroethene MCL-CA 6 μg/L 0.01 0.5

cis-1,2-Dichloroethene MCl-CA 6 μg/L 0.01 0.5

1,1,1-Trichloroethane MCL-US 200 μg/L 0.01 0.5

Trichloroethene (TCE) MCL-US 5 μg/L 0.01 0.5

Trichlorofluoromethane MCL-CA 150 μg/L 0.04 5

Atrazine MCL-CA 1 μg/L 0.003 0.5

Hexazinone HAL-US 400 μg/L 0.004 na
Methods 19

Table 4B. Benchmark type and value and reporting levels for constituents detected only at low relative-concentrations and 

constituents that were detected and did not have benchmarks, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Low concentrations are defined as RC ≤ 0.5 for inorganic constituents and as RC ≤ 0.1 for organic constituents. Relative-concentration (RC) is defined as the 

measured value divided by the benchmark value. Benchmark type: Non-regulatory, aesthetic-based benchmarks: SMCL-CA, CDPH secondary maximum 

contaminant level. Non-regulatory, health-based benchmarks: HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level. Regulatory, 

health-based benchmarks: MCL-US, USEPA maximum contaminant level; Prop AMCL-US, proposed USEPA alternative maximum contaminant level; 

AL-US, USEPA action level; MCL-CA, California Department of Public Health (CDPH) maximum contaminant level. Units: μg/L, micrograms per liter; 

mg/L, milligrams per liter; μS/cm, microsiemens per centimeter; pCi/L, picocuries per liter. Abbreviations: N, nitrogen; na, not available.; P, phosphorus; ssLc, 

sample-specific critical level; ≤, less than or equal to]

Constituent1 Benchmarks

Units Reporting levels3

Type2 Value USGS CDPH

Detected organic constituents without benchmarks

Deethylatrazine na na μg/L 0.007 na

3,4-Dichloroaniline na na μg/L 0.002 na

Fipronil na na μg/L 0.01 na

Desulfinylfipronil na na μg/L 0.006 na

Fipronil sulfone na na μg/L 0.026 na

 1Typical uses and (or) potential sources of constituents to groundwater are briefly discussed in the text for some constituents. Additional information may be 

obtained from Hem (1992), U.S. Environmental Protection Agency (2014), and California Department of Public Health (2014).

2

Maximum contaminant level benchmarks are listed as MCL-US when the MCL-US and MCL-CA are identical and as MCL-CA when the MCL-CA is lower 

than the MCL-US or no MCL-US exists. Sources of benchmarks: 

MCL-CA, SMCL-CA: California Department of Public Health (2013b)

MCL-US, AL-US: U.S. Environmental Protection Agency (2009)

NL-CA: California Department of Public Health (2010)

HAL-US: U.S. Environmental Protection Agency (2012)

Prop AMCL-US: U.S. Environmental Protection Agency (1999a)

3

USGS reporting level for most constituents is the long-term method detection level (Shelton and others, 2010). CDPH reporting level is the most common 

reporting level used to report non-detections for the study unit.

detected at low RCs (table 4B). Aquifer-scale proportions 

are not presented for constituents only detected at low RCs 

because the proportion of the primary aquifer system having 

low RCs for those constituents is 100 percent. All 18 of the 

geochemical and age-dating tracers examined also were 

detected (table 3). The remaining 126 constituents were not 

detected by USGS-GAMA in the SNR study unit (Shelton and 

others, 2010). 

The CDPH database also was used to identify 

constituents that have been reported at high RCs historically 

but not currently (table 5). The historical period was defined 

as the period starting with the earliest record maintained in 

the CDPH electronic database and ending just prior to the 

interval used for the status assessment: January 12, 1977, to 

April 30, 2006. Constituent concentrations may have been 

higher in the past than at the present for several reasons, such 

as a general improvement of groundwater quality with time 

or the abandonment of wells with high concentrations of 

constituents. Constituents with historically high constituents 

that did not otherwise meet the criteria previously listed were 

not considered to be representative of potential groundwaterquality concerns in the study unit during the current period of 

interest (May 2006 through October 2008).

The SNR study unit had 20 historically high constituents 

(table 5). Of the five inorganic constituents, two also were 

reported at moderate RCs in the CDPH database between 

May 1, 2006, and October 31, 2008 (aluminum and mercury). 

Of the 10 VOCs, 2 also were reported at moderate RCs in the 

CDPH database between May 1, 2006, and October 31, 2008, 

or were detected at greater than 10 percent area-weighted 

detection frequency in the wells sampled by USGS-GAMA for 

the SNR study unit (chloroform, and methyl tert-butyl ether). 

Of the five other organic constituents, four are semi-volatile 

organic compounds that were not analyzed by USGS-GAMA. 

Eleven of the 20 historically high constituents were detected at 

high concentrations in only 1 well each.
20 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 5. Constituents reported at concentrations greater than benchmarks in the California Department of Public Health (CDPH) 

database prior to May 2006 but not during the time period used for the status assessment (May 2006 through October 2008), Sierra 

Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[Benchmark type: Non-regulatory, aesthetic/technical-based benchmarks: SMCL-CA, CDPH secondary maximum contaminant level. Non-regulatory, healthbased benchmarks: HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level; RSD5-US, USEPA risk-specific dose at a factor of 10–5. 

Regulatory, health-based benchmarks: MCL-US, U.S. Environmental Protection Agency (USEPA) maximum contaminant level; AL-US, USEPA action level; 

MCL-CA, CDPH maximum contaminant level. Units: μg/L, micrograms per liter. Abbreviations: USGS, U.S. Geological Survey]

Constituent1 Benchmark

Date of most 

recent value 

above 

benchmark

Number of wells 

with data prior to 

status assessment 

period

Number of wells 

with a value 

above benchmark Type2 Value Units

Inorganic constituents

Aluminum3 MCL-CA 1,000 μg/L 11/04/2005 1,136 16

Barium MCL-CA 1,000 μg/L 04/27/2005 1,159 2

Mercury3 MCL-US 2 μg/L 08/27/1996 1,156 6

Thallium MCL-US 2 μg/L 08/17/2004 1,018 5

Vanadium NL-CA 50 μg/L 11/16/2005 490 12

Volatile organic compounds

1,1,1-Trichloroethane MCL-US 200 μg/L 12/19/1988 1,183 1

1,1,2,2-Tetrachloroethane MCL-CA 1 μg/L 09/11/2002 1,184 1

1,1-Dichloroethane MCL-CA 5 μg/L 03/17/1993 1,183 2

1,1-Dichloroethene MCL-CA 6 μg/L 06/15/1989 1,179 1

Chloroform4 MCL-US 80 μg/L 07/16/1996 1,182 1

Dibromochloropropane (DBCP) MCL-US 0.2 μg/L 09/03/2004 411 1

Dichloromethane MCL-US 5 μg/L 03/16/2001 1,182 4

Methyl tert-butyl ether 3,4 (MTBE) MCL-CA 13 μg/L 05/28/2004 998 4

Trichloroethene (TCE) MCL-US 5 μg/L 01/17/1990 1,183 1

Vinyl chloride MCL-CA 0.5 μg/L 05/12/2003 1,183 1

Other organic compounds

Alachlor MCL-US 2 μg/L 11/28/2001 541 1

Aldrin5 RSD5-US 0.02 μg/L 07/17/2003 247 1

Di(2-ethylhexyl)phthalate5 MCL-CA 4 μg/L 08/22/1997 217 1

Diazinon5 HAL-US 1 μg/L 10/27/2004 495 1

Heptachlor epoxide5 MCL-CA 0.01 μg/L 11/25/1997 358 2

1

Typical uses and (or) potential sources of constituents to groundwater are briefly discussed in the text for some constituents. Additional information may be 

obtained from Hem (1992), U.S. Environmental Protection Agency (2013), and California Department of Public Health (2013).

2

Maximum contaminant level benchmarks are listed as MCL-US when the MCL-US and MCL-CA are identical and as MCL-CA when the MCL-CA is lower 

than the MCL-US or no MCL-US exists. Sources of benchmarks: 

MCL-CA, SMCL-CA: California Department of Public Health (2013b)

MCL-US, AL-US: U.S. Environmental Protection Agency (2009)

NL-CA: California Department of Public Health (2010)

HAL-US, RSD5-US: U.S. Environmental Protection Agency (2012)

Prop AMCL-US: U.S. Environmental Protection Agency (1999a)

3

Constituent detected at moderate relative-concentrations in the CDPH database or in the Sierra Nevada Regional Tahoe-Martis, Central Sierra, or Southern 

Sierra study units between May 2006 and October 2008. Reporting limits are in table 4A, and results for aquifer-scale proportions are in tables 7A, 7B, or 12.

4

Constituent detected at greater than 10 percent detection frequency in the Sierra Nevada Regional study unit. Reporting limits are in table 4A, and results for 

aquifer-scale proportions are in table 12.

5

Constituent not analyzed by USGS-GAMA.
Methods 21

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 SNR study unit. The primary aquifer 

system is defined by the depth intervals over which wells 

listed in the CDPH database are screened or open. The use of 

the term “primary aquifer system” does not mean that there 

exists a discrete aquifer unit. In most groundwater basins, 

public drinking-water supply wells typically are screened 

or open at greater depths than are domestic drinking-water 

supply wells (for example, Burow and others, 2008; Burton 

and others, 2012). Thus, the primary aquifer system generally 

corresponds to the deeper portion of the aquifer system 

tapped by public drinking-water supply wells. However, this 

segregation between the depths of public drinking-water 

supply wells and domestic drinking-water supply wells 

commonly does not apply in areas outside of groundwater 

basins. Wells in fractured-rock aquifers are most productive 

at depths where fractures in the local rock are saturated with 

water and the density of fractures typically decreases with 

depth (Freeze and Cherry, 1979; Page and others, 1984; 

Borchers, 1996; Ingebritsen and Sanford, 1998). Nearly all of 

the wells used in the status assessment for the SNR study unit 

are listed in the CDPH database, and are therefore classified 

as public drinking-water supply wells. To the extent that 

domestic drinking-water supply wells in the study unit are 

screened or open over the same depth intervals as the CDPH 

wells, the assessments presented in this report will also be 

applicable to the parts of the aquifer system used for domestic 

drinking-water supplies.

Five primary aquifer systems were defined for the SNR 

study unit: one to represent each of the four aquifer lithologies 

(granitic, metamorphic, sedimentary, and volcanic) and an 

aggregated system to represent the study unit as a whole. 

The proportions of these primary aquifer systems with high, 

moderate, and low RCs of constituents were calculated using 

a modified version of the grid-based and spatially weighted 

approaches of Belitz and others (2010). The modification 

consisted of area-weighting to account for the size differences 

among the sub-cells for a given aquifer lithology. Calculations 

of aquifer-scale proportions were made for individual 

constituents and for classes of constituents.

The grid-based calculations used data from one well 

per lithologic-grid sub-cell. Aquifer-scale proportions were 

calculated for each of the four aquifer lithologies separately. 

High-RC aquifer-scale proportion was calculated as the fraction 

of the area of the aquifer lithology in the study unit represented 

by lithologic-grid wells having high RCs for a constituent 

(eq. 1). The contribution of each cell to the aquifer-scale proportion for a given lithology was weighted according to the area 

of the sub-cell occupied by that lithology. The moderate-RC 

aquifer-scale proportion was calculated similarly.

N A

A

c L high c L c

c L c

, , ,

,

=

∑

∑ PLg, high , (1)

where

PLg,high is the grid-based high-RC aquifer-scale 

proportion for the lithologic type L primary 

aquifer system (granitic, metamorphic, 

sedimentary, or volcanic) in the SNR 

study unit,

NL,high,c is the number of wells in a given lithologic 

sub-cell of type L having high RC for the 

constituent (for the grid-based calculation, 

there is only one well per lithologic subcell, so the value of this parameter is either 

1 or 0),

AL,c is the area of a given lithologic sub-cell of 

type L, and

Σc refers to summation over all sub-cells having 

data for the constituent.

The spatially weighted calculations used the dataset of 

1,266 wells assembled from wells sampled by USGS-GAMA 

for the SNR, Tahoe-Martis, Central Sierra, and Southern 

Sierra study units and wells with data in the CDPH database 

(table 2). Aquifer-scale proportions were calculated for each of 

the four aquifer lithologies separately. High-RC aquifer-scale 

proportion was calculated for each constituent by computing the proportion of high RC wells in each sub-cell and then 

calculating the area-weighted average proportion for the subcells (eq. 2; Isaaks and Srivastava, 1989). The moderate-RC 

aquifer-scale proportion was calculated similarly.

P

N

N

A

A Ls high

c

L high c

L total c

L c

c L c

,

, ,

, ,

,

,

=

Σ

Σ

, (2)

where 

PLs,high is the spatially weighted high-RC aquiferscale proportion for the lithologic type 

L primary aquifer system (granitic, 

metamorphic, sedimentary, or volcanic) in 

the SNR study unit, and

NL,total,c is the number of wells in a given lithologic 

sub-cell of type L having data for the 

constituent.

The results for the granitic, metamorphic, sedimentary, 

and volcanic primary aquifer systems were combined to create 

an aggregated system that represents the study unit as a whole. 

High-RC aquifer-scale proportions for the aggregated system 

were calculated by combining either the grid-based (eq. 3) 

or the spatially weighted (eq. 4) results for the four aquifer 

lithologies. Moderate-RC aquifer-scale proportions for the 

aggregated system were calculated similarly
22 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

P

P A

A SUg high

L Lg high c L c

L c L c

,

, ,

,

( ) = ∑ ∑

∑ ∑ (3)

where 

PSUg,high is the grid-based high-RC aquifer-scale 

proportion for the aggregated primary 

aquifer system, and

ΣL refers to summation over the four aquifer 

lithologies.

P

P A

A SUs high

L Ls high c L c

L c L c

,

, ,

,

( ) = ∑ ∑

∑ ∑ (4)

where 

PSUs,high is the spatially weighted high-RC aquiferscale proportion for the aggregated primary 

aquifer system.

Aquifer-scale proportions for constituent classes were 

calculated using the maximum RC for any constituent in the 

class to represent the class. For example, a well having a high 

RC for arsenic, moderate RC for fluoride, and low RCs for 

molybdenum, boron, selenium, and other trace elements would 

be counted as having a high RC for the class of trace elements 

with health-based benchmarks. Datasets for wells commonly 

were incomplete; for example, of the 1,224 wells having 

data for at least 1 inorganic constituent with a health-based 

benchmark, 553 wells had data only for nutrients and had no 

data for any trace elements or radioactive constituents (fig. 4). 

Of the 530 wells having data for at least 1 trace element with 

a health-based benchmark, 95 wells had data for only 1 of the 

18 trace elements. The effects of these data gaps on calculated 

aquifer-scale proportions for constituent classes are discussed 

in appendix C.

For inorganic constituents, the spatially weighted aquiferscale proportions were used to represent proportions in the 

primary aquifer systems; results for grid-based aquifer-scale 

proportions are not presented. Results from status assessments 

for other GAMA Priority Basin Project study units indicated 

that the spatially weighted high-RC aquifer-scale proportion 

was within the 90 percent confidence interval for the gridbased high-RC aquifer-scale proportion in almost all cases (for 

example, Burton and others, 2012; Fram and Belitz, 2012). 

The largest differences between the grid-based and spatially 

weighted aquifer-scale proportions for inorganic constituents 

were found in the SNR study unit.

For organic constituents, the grid-based aquifer-scale 

proportions were used to represent proportions in the primary 

aquifer systems, unless the grid-based high-RC or moderateRC proportion was zero and the spatially weighted high-RC 

or moderate-RC proportion was non-zero. Both the grid-based 

and spatially weighted calculations have the potential to 

underestimate the proportions of the primary aquifer systems 

with high RCs or moderate RCs for organic constituents—

but for different reasons. The grid-based method can miss 

constituents present at high RCs or moderate RCs in a small 

proportion of the primary aquifer system. For equal-area cells, 

Belitz and others (2010) showed that a target of size 0.7/n, 

where n is the number of cells, has a 50 percent probability 

of being missed by the grid sampling. Organic constituents 

generally had high-RC and moderate-RC aquifer-scale proportions of less than 1 percent, and thus, had a substantial probability of being missed in the grid well sampling (each lithology 

was represented by 15 to 28 grid wells, table 2). The spatially 

weighted method can miss constituents present at high RCs 

or moderate RCs because the RCs of the reporting limits in 

the CDPH database were greater than 0.1 for many organic 

constituents (Fram and Belitz, 2012; tables 4A,B). Using 

the spatially weighted high-RC or moderate-RC proportion 

in cases where the grid-based high-RC or moderate-RC 

proportion was zero and the spatially weighted high-RC or 

moderate-RC proportion was non-zero may mitigate the 

tendency of the results to underestimate the high-RC and 

moderate-RC proportions.

Calculated aquifer-scale proportions were used for constituent classes unless the high-RC or moderate-RC aquiferscale proportion for any individual constituent in the class was 

greater than the calculated high-RC or moderate-RC aquiferscale proportion for the class as a whole. The high-RC aquiferscale proportion for an individual constituent may be greater 

than the calculated high-RC aquifer-scale proportion for the 

class in the case of data gaps (see appendix C). In such cases, 

the greatest high-RC or moderate-RC aquifer-scale proportion 

for an individual constituent in the class was assigned as the 

high-RC or moderate-RC aquifer-scale proportion for the class 

as a whole.

Area-weighted detection frequencies for organic 

constituents were calculated using data from the 82 USGSgrid wells:

,det, , ,

, ,

( ) and c L c Lc L L c Lc

L SU

c Lc L c Lc

N A D A

D D

A A

∑ ∑ ∑ = = ∑ ∑ ∑ , (5)

where 

DL is the area-weighted detection frequency for 

an organic constituent for the lithologic 

type L primary aquifer system (granitic, 

metamorphic, sedimentary, or volcanic) in 

the SNR study unit,

DSU is the area-weighted detection frequency for 

an organic constituent in the aggregated 

primary aquifer system, and

NL,det,c is the number of wells in a given lithologic 

sub-cell of type L having a detection of 

the constituent (there is only one well per 

lithologic sub-cell, so the value of this 

parameter is either 1 or 0).
Methods 23

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

12

26

26

18

30

24

12

23

24

12

sac14-0538_Figure 04

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

EXPLANATION

Sierra Nevada Regional

 study unit 

California Department of Public Health

 Sierra Nevada Regional study unit wells 

With nitrate data and number of trace

 elements or radioactive constituents 

Without nitrate data and number of trace

 elements or radioactive constituents 

6 to 20

1 to 5

0

1 to 5

0

Sierra Nevada Regional

 study unit grid cell 

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Figure 4. Locations of public-supply wells from the California Department of Public Health database, Sierra Nevada Regional study 

unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
24 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Understanding Assessment

The evaluation of relations between potential explanatory 

factors and groundwater quality included three types of 

evaluations: (1) correlations among potential explanatory 

factors; (2) correlations between potential explanatory factors 

and constituent concentrations; and (3) differences in aquiferscale proportions for individual constituents and constituent 

classes among the four aquifer lithologies.

A subset of constituents was selected for evaluation 

of relations between potential explanatory factors and 

groundwater quality. The constituents were selected on 

the basis of aquifer-scale proportions using the following 

approach:

• Constituents present at high RCs in greater than 

approximately 2 percent of the aggregated primary 

aquifer system (eqs. 3, 4); and

• Organic constituent classes and special-interest 

constituents having area-weighted detection frequency 

greater than 10 percent for the granitic, metamorphic, 

sedimentary, volcanic, or aggregated primary aquifer 

systems (eq. 5).

These criteria resulted in selection of nine individual 

inorganic constituents, four classes of organic constituents, 

and one special-interest constituent (table 4A). Relations 

for the following classes also were examined: any VOC, 

any organic constituent, any nutrient, any trace element, any 

radioactive constituent, any inorganic constituent with healthbased benchmarks, any metal with an SMCL benchmark, 

any salinity indicator, and any constituent with an SMCL 

benchmark.

Tests of Correlations Among Potential 

Explanatory Factors and Between Potential 

Explanatory Factors and Water Quality

The purpose of examining potential explanatory 

factors is to improve understanding of the natural and 

anthropogenic factors that affect groundwater quality. 

The potential explanatory factors evaluated were geology, 

land-use characteristics, hydrologic conditions, well depth, 

groundwater age distribution, and geochemical conditions. 

Correlations among these factors that could affect apparent 

relations between aquifer lithology and water quality are also 

described. Data were compiled for the 83 wells sampled by 

USGS-GAMA. Other CDPH wells were not used because 

data for many of the potential explanatory factors were not 

available. Wells sampled for the Tahoe-Martis, Central Sierra, 

and Southern Sierra study units were not included to avoid 

adding spatial bias to the dataset.

Nonparametric statistical methods were used to test the 

significance of correlations among the factors and between the 

factors and water-quality constituents. Nonparametric statistics 

are robust techniques that generally are 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 percent (α = 0.05) to evaluate 

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

Three different statistical tests were used because the 

set of potential explanatory factors included categorical and 

continuous variables. Groundwater age class, aquifer-lithology 

class, oxidation-reduction class, and depth class were treated 

as categorical variables; for example, groundwater ages were 

classified as modern, pre-modern, or mixed. Land use, septictank density, leaking or formerly leaking underground fuel 

tank (LUFT) density, aridity index, elevation, latitude, well 

depth, depth to top of screened or open interval, dissolved 

oxygen (DO), and pH were treated as continuous variables; for 

example, land use was represented by percentages of land-use 

types. Well depth and oxidation-reduction status were treated 

as continuous (depth in feet below land surface and DO concentration, respectively) and categorical (depth classified into 

four groups, and oxidation-reduction status as oxic or anoxic; 

appendix B) variables.

• Correlations between continuous variables were 

evaluated using the Spearman’s rho test to calculate 

the rank-order coefficient (ρ, rho) and the significance 

level of the correlation (p).

• Relations among categorical variables and continuous 

variables were evaluated using a multi-stage KruskalWallis test to determine whether one or more of the 

groups had a significantly different median. The 

Kruskal-Wallis test is equivalent to the Wilcoxon ranksum test for a categorical variable with two values. 

Pairwise Wilcoxon rank-sum tests were not used 

because the overall significance level for six pairwise 

tests with α = 0.05 for a categorical variable with four 

groups is α = 0.26 (Helsel and Hirsch, 2002). If the 

Kruskal-Wallis test showed a significant difference 

among the medians, then Tukey’s multiple comparison 

test was applied to the ranks of the data to determine 

which pairs had significantly different mean ranks 

(Helsel and Hirsch, 2002).

• Relations between categorical variables were evaluated 

by using contingency tables. For contingency table 

analysis, the data are recorded as a matrix of counts. 

One variable is assigned to the columns and the other 

to the rows, and the entry in each cell of the matrix 

represents the number of observations which are in the 

categories corresponding to the ith row and jth column 

of the matrix. A test statistic is computed by comparing 

the observed counts to the counts expected if the two 

variables are independent, and statistical significance 

is determined by comparing the test statistic to the 

(1–α)th quantile of a chi-square distribution (Helsel 

and Hirsch, 2002). If the contingency table test 

detected a significant difference between the observed 
Methods 25

counts and the expected counts, then the matrix cell(s) 

contributing most to the difference was determined 

by comparing magnitudes of the components of the 

test statistic. Contingency tables were constructed by 

assigning the groups for one categorical variable as 

the columns and the groups for the other as the rows; 

entries in the table correspond to the number of wells 

with each combination of characteristics.

Comparison of Aquifer-Scale Proportions Among 

Primary Aquifer Systems

Aquifer-scale proportions for the granitic, metamorphic, 

sedimentary, and volcanic primary aquifer systems also were 

compared by using contingency table tests. For inorganic 

constituents, the sum of the proportions of the primary aquifer 

system having high RCs or moderate RCs was compared 

to the proportion having low RCs. A 4×2 contingency table 

was constructed, with the four aquifer lithologies as the rows 

and the two proportions being compared as the columns. The 

entries in the table were the adjusted numbers of samples in 

each category. These adjusted numbers of samples in each 

category were calculated by applying the spatially weighted 

aquifer-scale proportions to the number of wells used in the 

spatially weighted calculations. For example, if 223 wells 

with granitic aquifer lithology were used in the calculation of 

aquifer-scale proportions and the resulting spatially weighted 

proportions for a constituent were 7.8 percent with high RCs, 

11.5 percent with moderate RCs, and 80.7 percent with low 

RCs, the granitic aquifer lithology row of the contingency 

table for that constituent would be [43.0, 180.0].

For organic constituents, the proportion with detection 

of any organic constituent was compared to the proportions 

with no detections. The adjusted numbers of samples were 

calculated using the numbers of wells having USGS-GAMA 

data for organic constituents. The RCs of USGS-GAMA 

reporting limits were <0.1 for all 16 of the detected organic 

constituents and <0.01 for 14 of the 16 (tables 4A,B). Because 

the USGS-GAMA reporting limits are so much lower than 

the CDPH reporting limits, the two datasets could not be 

combined for this comparison of detections.

If the contingency table test indicated a significant 

difference in aquifer-scale proportions among the four 

lithologies, then the pairs with significant differences were 

identified by pair-wise 2×2 contingency table tests.

Characteristics of the Primary Aquifer System

Characteristics of the primary aquifer system, including 

geology, land use, climate, depth, groundwater age 

distribution, and geochemical conditions are described using 

data compiled for the 83 sites sampled by USGS-GAMA for 

the SNR study unit. The methods used to compile the data are 

described in appendix B. Correlations between explanatory 

factors are important to identify because an apparent 

correlation between an explanatory factor and a water-quality 

constituent could reflect correlations among explanatory 

factors.

Geology

The 83 wells sampled for the SNR study unit were 

assigned one of four aquifer lithologic classes (appendix B):

• Granitic rocks (28 wells): Mesozoic granitic rocks of 

the Sierra Nevada batholith;

• Metamorphic rocks (24 wells): Mesozoic and Paleozoic 

metavolcanic, metasedimentary, mafic, and ultramafic 

rocks;

• Sedimentary deposits (16 wells): Cenozoic alluvial, 

glacial, fluvial, and lacustrine sediments; and

• Volcanic rocks (15 wells): Cenozoic volcanic and 

volcaniclastic rocks.

Because the study design called for sampling one well in 

each lithologic sub-cell present in a cell, the numbers of wells 

representing each aquifer lithology are not proportional to the 

areal percentages of the four geologic units in the study unit. 

The 82 sub-cells in which USGS sampled a well for the SNR 

study unit represent 94 percent of the area of the study unit 

(fig. 5). In comparison, the sub-cells containing wells with 

data in the CDPH database for 10 or more inorganic constituents represent less than two-thirds of the area of the study unit. 

The combination of the two datasets covers 95 percent of the 

area of the study unit (fig. 5). 

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 the early 1990s. The imagery is classified into 25 landcover classifications (Nakagaki and Wolock, 2005). These 

25 land-cover classifications were condensed into 3 principal 

land-use categories: urban, agricultural, and natural (see 

appendix B).

Average land use around wells differs from the overall 

land use in the study unit because wells are preferentially 

located where people are living, working, or recreating. The 

average amount of urban land use in the 500-m buffers around 

all of the CDPH wells and around the USGS-GAMA wells 

was more urban than for overall land use (fig. 6A). 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 more biased 

towards urban land use because urbanized areas typically have 

a higher density of CDPH wells.
26 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

35,000

30,000

25,000

20,000

15,000

10,000

5,000

0

Area, in square kilometers

Total area of 

SNR study unit

Area of sub-cells

with USGS well 

with inorganic data

Area of sub-cells

with CDPH well

with inorganic data

Area of sub-cells

with USGS or CDPH

well with 

inorganic data

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

sac14-0538_Figure 05

EXPLANATION

Figure 5. Area assigned to the four aquifer lithologies in the study unit as a whole, and the areas represented by wells sampled 

by the U.S. Geological Survey (USGS) having data for 24 or more inorganic constituents with health-based benchmarks, by wells in 

the California Department of Public Health (CDPH) database having data for 10 or more inorganic constituents with health-based 

benchmarks, and by any well having data for 10 or more inorganic constituents with health-based benchmarks, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

Land use and aquifer lithology are correlated. 

Agricultural land use is significantly associated with 

sedimentary aquifer lithology compared to the other 

lithologies for the study unit area as a whole (contingency 

table test, p < 0.001) and for the area within the 500-m buffers around the USGS-GAMA wells (table 6A; fig. 6A). 

Natural land use and aquifer lithology also are significantly 

associated for the area within the 500-m buffers around the 

USGS-GAMA wells: areas with granitic aquifer lithology 

have significantly more natural land use than areas with 

sedimentary aquifer lithology.

The percentage of natural land within the 500-m buffers 

around the USGS-GAMA wells was expected to be lower 

than the percentage of natural land for the study unit as a 

whole because wells are preferentially located in areas with 

developed land. While this is the case for areas with granitic, 

sedimentary, and volcanic aquifer lithologies, it is not true 

for areas with metamorphic aquifer lithology (fig. 6A). For 

the study unit as a whole, areas with metamorphic aquifer 

lithology have the greatest percentage of urban land because 

the Western Metamorphic Belt, which composes the majority 

of the area occupied by metamorphic rocks in the SNR 

study unit (fig. 3A), is adjacent to the major population 

centers in the Central Valley that extend into the foothills 

(Sacramento, Stockton, Modesto; fig. 3C). However, wells 

with metamorphic aquifer lithology were sampled in 24 cells, 

and the Western Metamorphic Belt is in only 4 of those cells 

(cells 1, 2, 3, and 12; figs. 3A,B).

Of the 83 USGS-GAMA wells, 73 have more than 

80 percent natural land in the 500-m buffer around the well, 

and for most of those wells, the remainder consists of urban 

land (table B1). Land use surrounding the other 10 wells 

ranges from more than 80 percent urban or agricultural land to 

nearly an equal mixture of the three land-use types (fig. 6B). 

Half of the wells with less than 80 percent natural land have 

sedimentary aquifer lithology, reflecting that most of the areas 

with sedimentary aquifer lithology are groundwater basins that 

are conducive to agricultural and urban development.

Septic tanks and LUFTs are also markers of land-use 

patterns. Septic systems generally are associated with dispersed residences and may occur in areas classified as natural 

or agricultural land in additional to areas classified as urban 

land. The density of septic tanks in the 500-m buffers around 

the USGS-GAMA wells in the study unit ranged from 0 to 

117 tanks per square kilometer (tanks/km2

) (table B1). The 

wells with septic tank density greater than 7 tanks/km2

 were 
Methods 27

Natural

Agricultural

Urban

0

20

40

60

80

100

0 20 40 60 80 100

0

20

40

60

80

100

Entire

area

Within

500 meters

of wells

Wells

Aggregated

Granitic

Metamorphic

Sedimentary

Volcanic

California Department of

Public Health wells

Natural

Agricultural

Urban

0

20

40

60

80

100

0 20 40 60 80 100

0

20

40

60

80

100

Granitic

Metamorphic

Sedimentary

Volcanic

A

B

sac14-0538_Figure 06 Trenary LU

Figure 6. Percentage of urban, agricultural, and natural land use in the Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project in (A) the aquifer lithologic units, and (B) the areas 

surrounding each USGS-GAMA well.
28 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 6A. Results from multi-stage Kruskal-Wallis tests for differences in median values of selected potential explanatory factors 

among samples classified into groups by aquifer lithology class, oxidation-reduction class, depth class, or groundwater age class, 

Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.

[Factors yielding a result of significance in the Kruskal-Wallis test were evaluated with Tukey’s test on the single-factor analysis of variance of the ranks. 

Significance defined as p-value less than threshold value (α) of 0.05. Aquifer lithology class: G, granitic; M, metamorphic; S, sedimentary; V, volcanic (see 

appendix B). Oxidation-reduction class: see appendix B for definitions of oxic and anoxic. Depth class: deep, well depth > 170 ft bls and top of perforations

> 170 ft bls; overlapping, top of perforations < 170 ft bls and well depth > 170 ft bls; shallow, well depth < 170 ft bls; spring, site is a spring. Age class: 

see appendix B for explanation of classes. Abbreviations: ft bls, feet below land surface; LUFT, leaking or formerly leaking underground fuel tank; ns, no 

significant differences; >, greater than; <, less than]

Potential 

explanatory 

factors

Aquifer lithology 

class

(G, M, S, V)

Oxidation-reduction 

class

(oxic, anoxic)

Depth class 

[spring (SP), shallow 

(SH), overlapping (OL), 

deep (DP)]

Age class 

[modern (MOD), 

mixed (MIX), 

pre-modern (PRE)]

p Significant 

differences p Significant differences p Significant differences p Significant differences

Land-use characteristics

Percent agricultural land 

use

0.013 S > G

S > M

S > V

0.425 ns 0.063 ns 0.381 ns

Percent natural land use 0.027 G > S 0.776 ns 0.007 SP > SH

SP > OL

0.705 ns

Percent urban land use 0.090 ns 0.484 ns 0.003 SH > SP

OL > SP

0.209 ns

Density of septic tanks 0.380 ns 0.259 ns 0.079 ns 0.813 ns

Density of LUFTs 0.839 ns 0.874 ns 0.131 ns 0.244 ns

Climate and hydrology variables

Aridity index 0.046 G > S 0.050 oxic > anoxic 0.029 SP > SH 0.069 ns

Elevation 0.128 ns 0.004 oxic > anoxic <0.001 SP > SH

SP > OL

SP > DP

0.635 ns

Latitude 0.132 ns ns ns 0.282 ns 0.048 MIX > PRE

Characteristics of primary aquifer system

Depth to top of open or 

screened interval

0.225 ns 0.889 ns <0.001 DP > SH

DP > OL

0.015 PRE > MOD

Depth to bottom of open 

or screened interval

0.685 ns 0.987 ns <0.001 DP > OL > SH 0.122 ns

pH 0.057 ns 0.001 anoxic > oxic 0.019 DP > SP

DP > SH

DP > OL

<0.001 MIX > MOD

PRE > MOD

Dissolved oxygen 

concentration

0.333 ns <0.001 oxic > anoxic <0.001 SP > SH

SP > OL

SP > DP

0.003 MOD > PRE

MIX > PRE
Methods 29

Table 6B. Results from Spearman’s rho tests for correlations between selected potential explanatory factors, Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[ρ (rho), Spearman’s correlation statistic. Significance defined as p-value less than threshold value (α) of 0.05. Tests in which the variables were determined to be significantly correlated on the basis of p-values (not shown) have ρ-values underlined and shown in bold font. Black values denote positive correlations; red values denote negative correlations. Abbreviations: LUFT, leaking or formerly leaking underground fuel tank] 

ρ

Percentage 

agricultural 

land use

Percentage 

natural 

land use

Percentage 

urban land 

use

Density 

of septic 

tanks

Density 

of LUFTs

Aridity 

index Elevation Latitude

Depth 

to top of 

open or 

screen

Depth to 

bottom of 

open or 

screen

pH

Dissolved 

oxygen 

concentration

Percentage agricultural land use –0.49 0.09 –0.02 –0.10 –0.48 –0.24 –0.34 0.09 –0.30 0.19 –0.11

Percentage natural 

land use –0.86 –0.34 –0.26 0.33 0.38 0.14 0.13 0.08 –0.06 0.19

Percentage urban 

land use 0.41 0.36 –0.15 –0.36 –0.02 –0.10 –0.02 –0.06 –0.20

Density of septic 

tanks 0.55 –0.08 –0.58 0.04 –0.30 0.08 –0.12 –0.23

Density of LUFTs 0.10 –0.43 0.21 0.16 –0.14 –0.10 –0.05

Aridity index 0.36 0.59 0.00 –0.19 –0.28 0.36

Elevation 0.06 0.18 0.10 –0.05 0.42Latitude 0.15 0.20 –0.03 0.12

Depth to top of open 

or screen

0.36 0.45 0.05

Depth to bottom of 

open or screen

0.18 –0.10

pH –0.33

Dissolved oxygen 

concentration
30 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 6C. Results of contingency table tests for association between selected potential explanatory factors, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[For factors determined to be significantly associated on the basis of p-values less than threshold value (a) of 0.05 for contingency table test, the association 

or absence of association that contributes most to significance of the the test statistic is described. Aquifer lithology class: G, granitic; M, metamorphic; S, 

sedimentary; V, volcanic. Depth class: deep, well depth > 170 ft bls and top of perforations > 170 ft bls; overlapping top of perforations < 170 ft bls and well 

depth > 170 ft bls; shallow, well depth < 170 ft bls; spring, site is a spring. Groundwater age class: See appendix B for explanation of classes. Oxidationreduction class: See appendix B for explanation of classes. Abbreviations: ft bls, feet below land surface; <, less than; >, greater than]

Factor

Groundwater age

(modern, mixed, 

pre-modern)

Oxidation-reduction

(oxic, anoxic)

Depth class 

 (spring, shallow, 

overlapping, deep)

Site type 

(spring, well)

Aquifer lithology

(G, M, S, V)

0.092 0.614 0.227 0.568

Groundwater age

(modern, mixed, 

pre-modern)

0.003

Modern groundwater is 

not associated with anoxic 

conditions

<0.001

Deep wells are associated 

with pre-modern groundwater

0.268

Oxidation-reduction

(oxic, anoxic)

0.089 0.009

Springs are not associated 

with anoxic conditions

located in the foothills east of the Central Valley population 

centers of Sacramento, Stockton, Modesto, and Fresno and 

in the Lake Isabella area of the southern Sierra Nevada. The 

foothills east of the Central Valley population centers and 

the Lake Isabella area are among the few areas in California 

that have population densities of greater than 100 people per 

square mile, yet have almost no cities with populations greater 

than 5,000 people (U.S. Census Bureau, 1990). Dispersed residential developments outside of cities are more likely to have 

individual septic systems rather than a collective sewer system 

because of the large costs associated with constructing sewage 

collection and treatment systems. The density of documented 

LUFTs in the 500-m buffers around the USGS-GAMA 

wells in the study unit ranges from 0 to 0.7 tanks/km2

(table B1). Most of the wells with LUFT densities greater 

than 0.05 tank/km2

 were located in the foothills or along 

major roads leading from Central Valley urban centers into the 

Sierra Nevada or around Lake Tahoe. As expected from these 

occurrence patterns, the densities of septic tanks and LUFTs 

were positively correlated with each other and with percentage 

of urban land use and negatively correlated with elevation and 

percentage of natural land use (table 6B).

Climate and Hydrology

Climate and hydrologic conditions were represented 

by the United Nations Educational, Scientific, and Cultural 

Organization aridity index (United Nations Educational, 

Scientific, and Cultural Organization, 1979; United Nations 

Environment Programme, 1997), latitude, and elevation 

at the well site (table B3). Aridity index is average annual 

precipitation divided by average annual evapotranspiration; 

higher values correspond to wetter conditions. As expected, 

aridity index showed significant positive correlations with 

elevation and latitude (table 6B). Values of aridity index were 

greater for wells in granitic aquifer lithology compared to 

sedimentary aquifer lithology (table 6A).

Elevation may be used as a proxy for relative position 

in a generalized regional groundwater flow system. Given 

the fact that water moves from higher elevations to lower 

elevations, elevation is generally expected to be inversely 

related to residence time in many groundwater flow systems. 

This is approximately true in areas like the eastern San 

Joaquin Valley where natural recharge primarily occurs on the 

eastern margin and groundwater flows through alluvial aquifer 

systems towards the central part of the valley (Landon and 

others, 2010, 2011). In the Sierra Nevada, however, most of 

the aquifer systems consist of fractured hard rock with variable 

porosity and permeability and may not be interconnected, and 

recharge is not limited to the highest elevations. Because of 

the topographic and geologic complexity of the Sierra Nevada, 

there are likely to be many local flow cells of different scales 

superimposed on the regional groundwater flow system (Tóth, 

1963). Thus, the relation between elevation and relative 

position in the regional groundwater flow system in the SNR 

study unit is likely to be more complex than a simple, inverse 

proportionality.

Depth and Groundwater Age

As noted earlier, the primary aquifer system in the SNR 

study unit is defined as the depth interval over which wells 

in the CDPH database are screened or open. Because the 

wells sampled by USGS-GAMA for the SNR study unit were 

considered representative of wells in the CDPH database, the 

depth and groundwater age characteristics of these wells were 
Methods 31

used to define the depth and groundwater age characteristics of 

the primary aquifer system.

Groundwater age refers to residence time in the aquifer 

system, which is the amount of time elapsed since the water 

was last in contact with the atmosphere (either directly, 

while it was at the ground surface, or indirectly, as it passed 

through the vadose zone). Data for the age-dating tracers 

tritium and carbon-14 (14C) were used to classify groundwater 

age into three categories: modern, mixed, and pre-modern 

(appendix B). Of the 83 wells sampled by USGS-GAMA, 

42 were classified as having modern groundwater, 31 as 

having mixed groundwater, and 7 as having pre-modern 

groundwater (table B5). Three samples were classified as 

modern or mixed because they had insufficient data to confirm 

the presence or absence of pre-modern groundwater, either 

because 14C data were not collected or because the δ13C values 

suggested that substantial interaction with sedimentary carbon 

may have occurred (table B5).

Twenty of the 83 USGS-GAMA sites were springs, 

and all 4 aquifer lithologies included springs (fig. 7). Sites 

that were springs had significantly higher elevations, wetter 

conditions, and greater percentages of natural land use around 

the sites than did sites that were wells (table 6A). Springs 

emerge at the land surface, but the geometry of the fracture 

networks in the subsurface from which their water is derived 

is usually unknown. For the sites that were wells, the median 

depth to the bottom of the screened or open interval was 

300 ft, and the median depth to the top of the open or screened 

interval was 77 ft (table B3). There were no significant 

relations between aquifer lithology and either measure of well 

depth (tables 6A,C).

Groundwater ages typically increase with depth below 

the water table, and thus, in general with well depth and the 

depth to the top of the screened or open interval. Pre-modern 

groundwater came from wells with significantly greater depths 

to the top and the bottom of the screened or open interval 

compared to modern or mixed groundwater (tables 6A,C). 

There were no significant associations between aquifer 

lithology and groundwater age class (table 6C).

Groundwater age categories were combined with 

information on well depths to create a system for classifying 

different types of sites. Wells with depth less than a critical 

value were defined as shallow; wells with screened or 

open intervals beginning above the critical depth and ending below the critical value were defined as overlapping; 

and wells with screened or open intervals entirely below 

the critical value were defined as deep. The critical depth 

value of 170 feet below land surface (ft bls) was selected 

by optimizing the segregation of modern groundwater into 

shallow wells, mixed-age groundwater into overlapping wells, 

and pre-modern groundwater into deep wells and was selected 

for consistency with previous work (Fram and Belitz, 2012). 

Springs were considered a separate class.

Number of wells

0

5

10

15

20

25

30

Unknown well 

Deep well 

Overlapping or

 deep well

Overlapping well 

Shallow well 

Spring 

Primary aquifer system

Granitic Metamorphic Sedimentary Volcanic

Depth class

EXPLANATION

Figure 7. Numbers of sites sampled by the U.S. Geological Survey (USGS) in each aquifer lithologic class and depth class, Sierra 

Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
32 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Springs, shallow wells, and overlapping wells were 

represented in all four aquifer lithologies, and deep wells 

occurred in three of the four aquifer lithologies (fig. 7). 

Most springs, shallow wells, and overlapping wells yielded 

modern groundwater, and a majority of deep wells yielded 

pre-modern groundwater (fig. 8). Mixed-age groundwater was 

found in 30–45 percent of sites in all four well depth classes. 

Pre-modern groundwater was not found in springs or shallow 

wells, but modern groundwater was found in deep wells.

Comparison between the wells sampled for the SNR 

study unit and the wells sampled for the Tahoe-Martis, Central 

Sierra, and Southern Sierra study units indicated that the two 

studies sampled different populations of wells in granitic 

aquifer lithology. The SNR study unit sites in granitic aquifer 

lithology included a significantly greater proportion of sites 

that were springs or shallow wells (54 percent) than did the 

sites in granitic aquifer lithology in the Tahoe-Martis, Central 

Sierra, and Southern Sierra study units (17 percent) (contingency table test, p = 0.002). In addition, the SNR study unit 

sites in granitic aquifer lithology included a significantly 

smaller proportion of sites with pre-modern groundwater 

(4 percent) than did the sites in granitic aquifer lithology in the 

Tahoe-Martis, Central Sierra, and Southern Sierra study units 

(23 percent) (contingency table test, p = 0.025). The difference 

reflects the occurrence of relatively deep wells in the Central 

Sierra study unit; deep wells in granitic lithology are not typical in the SNR study unit.

Geochemical Conditions

Oxidation-reduction conditions were classified on 

the basis of DO, nitrate, manganese, and iron concentrations by using a modified version of the classification 

scheme of McMahon and Chapelle (2008) and Jurgens 

and others (2009) (appendix B). The primary modification 

was that the DO threshold for separating oxic from anoxic 

groundwater was increased from 0.5 mg/L to 1 mg/L (Fram 

and Belitz, 2012). For a majority of the sites (66 of the 83 

sites [80 percent]), the groundwater was classified as oxic 

(DO ≥ 1 mg/L). Anoxic conditions (DO < 1 mg/L), present 

in 17 of the 83 wells (20 percent), were further classified 

as either suboxic, nitrate-reducing, manganese-reducing, or 

manganese- and iron-reducing (table B7).

DO concentrations were greater in samples from 

springs than in samples from shallow, overlapping, or deep 

wells and were greater in modern and mixed groundwater 

than in pre-modern groundwater (table 6A). In contrast, 

pH values were greater in samples from deep wells than in 

samples from springs or shallow and overlapping wells and 

were greater in pre-modern groundwater than in modern or 

mixed groundwater. Neither DO concentration nor pH was 

significantly related to aquifer lithology, which was expected 

given the lack of significant relations between aquifer 

lithology and depth class or groundwater age (table 6C).

Number of wells

0 2 4 6 8 10 12 14 16 18

Spring

Shallow well

Overlapping well

Deep well

Depth class

Modern

Mixed

Pre-modern

Groundwater age

 classification

EXPLANATION

Figure 8. Relation between depth classification and groundwater age classification for the Sierra Nevada Regional study unit, 2008, 

California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Status and Understanding of Groundwater Quality 33

The positive correlations among DO concentration, 

elevation, and springs may be related to the fact that springs 

commonly represent the intersection of the water table 

with the land surface, discharging water that tends to have 

had extensive, recent interaction with the atmosphere. 

Groundwater newly entering the aquifer system likely has 

not interacted extensively with organic matter or reduced 

inorganic aquifer materials, and thus would not have had its 

DO consumed.

pH values were significantly higher in deep wells 

compared to other site types, in anoxic groundwater compared 

to oxic groundwater, and in mixed or pre-modern groundwater 

compared to modern groundwater (table 6A). Precipitation in the Sierra Nevada is dilute: median specific conductance values were less than 5 microsiemens per centimeter 

at 25 degrees Celsius (μS/cm), and median pH values were 

approximately 5.6 for annual wet deposition at National 

Atmospheric Deposition Program sites within the boundaries 

of the SNR study unit (National Atmospheric Deposition 

Program, 2012). These low pH values are primarily controlled 

by the equilibrium between atmospheric carbon dioxide and 

dissolved carbonate species. As the length of contact time 

between groundwater and the aquifer materials increases, 

pH values generally rise as acid is consumed by weathering 

reactions of silicate minerals and dissolution of carbonate 

minerals (if present) (Stumm and Morgan, 1996).

Status and Understanding of 

Groundwater Quality

The following discussion is divided into two parts, 

one for inorganic constituents and the other for organic 

constituents, and each part has a tiered structure. Each part 

begins with a summary of the number of constituents that 

were detected at any concentration in USGS-GAMA samples 

compared to the number analyzed and graphical summaries 

of the RCs of constituents detected in the lithologic-grid 

wells. Aquifer-scale proportions then are presented for constituent classes and individual constituents. Lastly, results 

of statistical tests for relations between water quality and 

potential explanatory factors are presented for a subset of 

individual constituents and constituent classes. Discussions 

of the geochemical and hydrologic processes that may affect 

constituent concentrations are beyond the scope of this report 

and can be found in Fram and Belitz (2012) for many of the 

constituents evaluated here.

Inorganic Constituents

Inorganic constituents generally occur naturally in 

groundwater, although their concentrations may be influenced 

by human activities as well as by natural factors. Of the 

47 inorganic constituents analyzed by USGS-GAMA, 26 had 

regulatory or non-regulatory health-based benchmarks, 8 had 

non-regulatory aesthetic-based benchmarks, and 13 had 

no established benchmarks. Of these 34 constituents with 

benchmarks, 27 were detected at moderate or high RCs in 

samples collected by USGS-GAMA for the SNR study unit 

or the Tahoe-Martis, Central Sierra, and Southern Sierra study 

units, or were reported in the CDPH database at moderate 

or high RCs in samples collected between May 1, 2006, 

and October 31, 2008 (table 4A). The other 20 inorganic 

constituents either had no established benchmarks or were 

only detected at low RCs (table 4B). Most of the inorganic 

constituents without benchmarks are ions that are present in 

nearly all groundwater.

Sixteen of the 27 inorganic constituents were detected at 

moderate or high RCs in samples collected by USGS-GAMA 

for the SNR study unit: the trace elements antimony, arsenic, 

boron, fluoride, molybdenum, and selenium; the radioactive 

constituents gross alpha particle activity, radium, radon-222, 

and uranium; the nutrient nitrate; and the constituents 

having SMCL benchmarks (hereinafter referred to as SMCL 

constituents)—specific conductance, total dissolved solids, 

sulfate, iron, and manganese (table 4A; figs. 9, 10A–C). The 

majority of these 16 constituents were detected at moderate 

or high RCs in more than 10 percent of the wells in at least 

1 of the 4 lithologic-grid well networks (figs. 10A–C). The 

remaining 11 inorganic constituents (the trace elements 

aluminum, beryllium, cadmium, chromium, copper, lead, 

mercury, nickel, and strontium and the SMCL constituents 

chloride and zinc) were included because they were reported 

at high or moderate RCs in the CDPH database between 

May 1, 2006, and October 31, 2008, or in the USGS-GAMA 

Tahoe-Martis, Central Sierra, and Southern Sierra study 

units (table 4A). Aquifer-scale proportions are summarized 

in tables 7A,B for the individual inorganic constituents 

listed in table 4A, and in tables 8A,B for classes of inorganic 

constituents.

Inorganic constituents with health-based benchmarks, 

as a group, were present at high RCs in 16 percent of the 

primary aquifer system and at moderate RCs in 21 percent 

(table 8A). The proportion of the primary aquifer system 

having high or moderate RCs of any inorganic constituent was 

greater for the granitic and sedimentary systems than for the 

metamorphic system, and for the granitic system compared 

to the volcanic system (tables 8A, 9). Inorganic constituents 

with SMCL benchmarks, as a group, were present at high RCs 

in 18 percent of the primary aquifer system and at moderate 

RCs in 6.8 percent (table 8B). The proportion of the primary 

aquifer system having high or moderate RCs was greater for 

the metamorphic system than for the granitic, sedimentary, and 

volcanic systems (tables 8B, 9).
34 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Moderate

Low

Moderate

Low

High High

Organic and specialinterest constituents

Inorganic

constituents

Maximum relative-concentration, dimensionless

Volatile

organic

compounds

Special

interest

Nutrients Trace

elements

with HBB

Radioactive

constituents

0.001

0.01

0.1

1

10

60

Pesticides Inorganic

constituents

having

SMCLs

Constituent class

Molybdenum

Perchlorate

Tetrachloroethene

Trichloroethene

cis-1,2-Dichloroethene

Carbon disulfide

Chloroform

Methyl tert-butyl ether

Simazine

Atrazine

Nitrite

Ammonia

Nitrate

TDS

Silver

Sulfate

Iron

Manganese

Chloride

Fluoride

Boron

Zinc

Copper

Mercury

Radon-222

Gross alpha

Uranium

Gross beta

Radium Vanadium

Antimony

Selenium

Arsenic

Beryllium

Barium

Lead

Nickel

Strontium

Chromium

1,1-Dichloroethene

1,1-Dichloroethane

1,2-Dichloroethane

Cadmium

Thallium

Aluminum

Silver

EXPLANATION

sac14-0538_Figure 09

HBB, health-based benchmark; SMCL, secondary maximum contaminant level; upper water-quality benchmark 

used for calculating relative-concentrations for constituents with an upper and recommended SMCL

Constituent with analyses in 82 grid wells—Name and center of symbol 

is location of data unless indicated by following location line:

1,4-Dichlorobenzene

Radium Constituent with analyses in 28 grid wells—Name and center of symbol 

is location of data.

Figure 9. Maximum relative-concentrations of constituents detected in lithologic-grid wells by constituent class for the Sierra Nevada 

Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project. [HBB, healthbased benchmarks; SMCL, secondary maximum contaminant level]
Methods 35

A

0.0 0.5 1.0 1.5 2.0 > 2.0

Antimony

Arsenic

Boron

Fluoride

Molybdenum

Selenium

Relative-concentration (dimensionless)

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

sac14-0538_Figure 10a

EXPLANATION

Trace elements

Low Moderate High

Figure 10. Relative-concentrations of selected (A) trace elements with regulatory and non-regulatory health-based benchmarks, 

(B) nutrients and radioactive constituents with regulatory health-based benchmarks, and (C) salinity indicators and trace elements with 

non-regulatory secondary maximum contaminant level (SMCL) benchmarks, in USGS-grid wells, Sierra Nevada Regional study unit, 

2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
36 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

B

0.0 0.5 1.0 1.5 2.0 > 2.0

Relative-concentration (dimensionless)

Nutrients

Radioactive constituents

Nitrate

Gross alpha

particle

activity

Radium

activity

Radon-222

activity

Uranium

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

sac14-0538_Figure 10b

EXPLANATION

Low Moderate High

Low Moderate High

Figure 10. —Continued
Methods 37

0.0 0.5 1.0 1.5 2.0 > 2.0

Iron

Manganese

Sulfate

Total

dissolved

solids

Relative-concentration (dimensionless)

Salinity indicators with SMCL benchmarks

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

sac14-0538_Figure 10c

EXPLANATION

C Trace metals with SMCL benchmarks

Low Moderate High

Low Moderate High

Figure 10. —Continued
38 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008 Table 7A. Aquifer-scale proportions for inorganic constituents for the granitic, metamorphic, sedimentary, and volcanic primary aquifer systems, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued [Aquifer-scale proportions calculated with the spatially weighted method (equation 2). Relative-concentration (RC) categories: high, RC > 1.0, moderate, RC > 0.5 and RC ≤ 1.0; low, RC ≤ 0.5. RC defined as measured value divided by benchmark value. Inorganic constituents not listed in this table either do not have benchmarks or were detected only at low RCs. Benchmark types and values listed in table 4A. Abbreviations: CDPH, California Department of Public Health; SMCL, secondary maximum contaminant level; USGS, U.S. Geological Survey; >, greater than; ≤, less than or equal to] Constituent Granitic primary aquifer system Metamorphic primary aquifer system Sedimentary primary aquifer system Volcanic primary aquifer system Number Aquifer-scale proportion (in percent) Number Aquifer-scale proportion (in percent) Number Aquifer-scale proportion (in percent) Number Aquifer-scale proportion (in percent) Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC Trace elements with health-based benchmarks Aluminum 204 29 3.1 0 70 23 0.4 0 91 17 0 0 42 16 0 0 Antimony 202 29 0 0.3 64 23 0.9 0 89 17 0 0.8 39 16 0 0 Arsenic 223 29 11.5 7.8 79 23 9.7 8.6 118 18 17.7 5.8 45 16 1.4 22.1 Beryllium 202 29 0 0 65 23 0 0.7 90 17 0 0 39 16 0 0 Boron 74 28 2.5 2.3 38 23 1.2 1.2 58 16 7.1 0 34 15 0.7 3.6 Cadmium 202 29 0 0.3 66 23 0 0 90 17 0 0.5 40 16 0 0 Chromium 209 29 0.5 0 66 23 0 0 92 17 0 0 39 16 0 0 Copper 190 29 0 0 59 23 0 0 97 18 0 17.3 42 16 0 12.4 Fluoride 220 29 0.2 2.1 70 23 0 1.7 100 18 7.1 3.7 44 16 0 0 Lead 199 29 1.5 1.6 59 23 0.8 0.4 93 16 0 0 38 16 0 0 Mercury 197 29 0 0 67 23 0.3 0 71 17 0 0 22 16 0 0 Molybdenum 61 28 12.9 1.5 29 23 0 0 52 16 7.3 0.8 34 15 9.8 0 Nickel 201 29 0.1 0 66 23 0 0 90 17 0 0 39 16 0 0 Selenium 203 29 0 0 66 23 0 11.2 91 17 0 0 40 16 0 0 Strontium 61 28 0 0 29 23 0 0 52 16 0 0 34 15 0 12.9 Uranium and radioactive constituents with health-based benchmarks Gross alpha particle 

activity

171 28 20.9 12.9 66 23 6.4 0 92 16 11.9 10.6 23 16 7.9 3.2

Adjusted gross alpha 

particle activity

171 28 1.0 1.4 66 23 3.4 0 92 16 3.5 2.2 23 16 0 0

Radium activity 150 17 2.6 0.3 49 9 2.5 0 83 5 0 0.8 22 5 0 0

Radon-222 activity 36 17 41.8 19.9 7 5 0 0 38 4 6.2 11.4 23 4 0 0

Uranium activity 147 29 11.1 5.2 32 23 0.8 0 87 16 11.5 3.8 35 16 7.9 0
Methods 39

Table 7A. Aquifer-scale proportions for inorganic constituents for the granitic, metamorphic, sedimentary, and volcanic primary aquifer systems, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued[Aquifer-scale proportions calculated with the spatially weighted method (equation 2). Relative-concentration (RC) categories: high, RC > 1.0, moderate, RC > 0.5 and RC ≤ 1.0; low, RC ≤ 0.5. RC defined 

as measured value divided by benchmark value. Inorganic constituents not listed in this table either do not have benchmarks or were detected only at low RCs. Benchmark types and values listed in table 4A. 

Abbreviations: CDPH, California Department of Public Health; SMCL, secondary maximum contaminant level; USGS, U.S. Geological Survey; >, greater than; ≤, less than or equal to]

Constituent

Granitic primary aquifer system Metamorphic primary aquifer system Sedimentary primary aquifer system Volcanic primary aquifer system

Number

Aquifer-scale 

proportion 

(in percent)

Number

Aquifer-scale 

proportion 

(in percent)

Number

Aquifer-scale 

proportion 

(in percent)

Number

Aquifer-scale 

proportion

(in percent)

Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC Wells Cells Moderate RC High RC

Nutrients with health-based benchmarks

Nitrate 576 29 3.7 2.2 227 24 1.6 0.7 230 22 8.1 1.3 98 16 1.7 0

Inorganic constituents with SMCL benchmarks

Chloride 197 29 0.7 0.1 63 23 0 0 98 18 0 0 43 16 0 0

Total dissolved 

solids (TDS)

297 29 2.5 1.3 101 23 2.0 1.4 142 18 7.6 0 58 16 3.4 1.2

Sulfate 196 29 0 0 64 23 0.8 0 96 18 0 0 42 16 0 1.7

Iron 224 29 4.7 13.0 70 23 5.8 25.9 100 18 0.8 8.5 45 16 2.2 7.5

Manganese 218 29 3.8 7.6 62 23 3.7 32.2 95 18 0.9 8.4 45 16 1.5 9.9

Zinc 191 29 0.1 0.1 58 23 0.8 1.0 92 18 0 0 42 16 0 0

1Selenium was detected at high RC by USGS-GAMA in one metamorphic aquifer lithology well, and the other 399 wells with USGS-GAMA or CDPH data for selenium had low RCs. Strontium was 

detected at high RC by USGS-GAMA in 1 volcanic aquifer lithology well, and the other 175 wells with USGS-GAMA data for strontium had low RCs. Copper was reported at high RCs by the CDPH in 

1 sedimentary and 1 volcanic aquifer lithology well, and the other 386 wells with USGS-GAMA or CDPH data for copper had low RCs. In all of these cases, the 1 well with high RC was located in a cell 

having few wells in that particular lithology and having a relatively large area for the lithology.
40 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 7B. Aquifer-scale proportions for inorganic constituents for the aggregated primary aquifer system, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[Aquifer-scale proportions calculated with the spatially weighted method (equation 4). Relative-concentration (RC) categories: high, RC > 1.0; moderate, 

RC > 0.5 and RC ≤ 1.0; low, RC ≤ 0.5. RC defined as measured value divided by benchmark value. Inorganic constituents not listed in this table either do not 

have benchmarks or were detected only at low RCs. Benchmark types and values listed in table 4A. Abbreviations: SMCL, secondary maximum contaminant 

level; >, greater than; ≤, less than or equal to]

Constituent

Aggregated lithologic primary aquifer system

Number Aquifer-scale proportion (in percent)

Wells Cells Moderate RC High RC

Trace elements with health-based benchmarks

Aluminum 407 30 1.7 0

Antimony 394 30 0.3 0.2

Arsenic 465 30 10.1 9.7

Beryllium 396 30 0 0.2

Boron 204 30 2.2 2.0

Cadmium 398 30 0 0.2

Chromium 406 30 0.3 0

Copper 388 30 0 0.8

Fluoride 434 30 0.5 1.8

Lead 389 30 1.0 1.0

Mercury 357 30 0.1 0

Molybdenum 176 30 8.4 0.9

Nickel 396 30 0.03 0

Selenium 400 30 0 0.3

Strontium 176 30 0 0.3

Uranium and radioactive constituents with health-based benchmarks

Gross alpha particle activity 352 30 14.5 7.8

Adjusted gross alpha particle activity 352 30 1.7 0.9

Radium activity 304 30 2.2 0.2

Radon-222 activity 104 30 28.8 14.1

Uranium activity 301 30 7.7 2.9

Nutrients with health-based benchmarks

Nitrate 1,131 30 3.1 1.4

Inorganic constituents with SMCL benchmarks

Chloride 401 30 0.4 0.1

Total dissolved solids (TDS) 598 30 2.8 1.3

Sulfate 398 30 0.2 0.2

Iron 439 30 4.4 15.8

Manganese 420 30 3.3 15.1

Zinc 383 30 0.3 0.3
Methods 41

Table 8A. Summary of aquifer-scale proportions in the granitic, metamorphic, sedimentary, volcanic, and aggregated primary aquifer 

systems for inorganic constituent classes with health-based benchmarks, Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[Aquifer-scale proportions calculated with the spatially weighted method (equations 2 and 4). Relative-concentration (RC) categories for inorganic 

constituents: high, RC > 1.0; moderate, RC > 0.5 and RC ≤ 1.0; low, RC ≤0.5. RC defined as measured value divided by benchmark value. Abbreviations: >, 

greater than; ≤, less than or equal to]

Constituent class and primary 

aquifer system

Number of 

wells

Aquifer-scale proportion (in percent)

Low Moderate High

Nutrients

Granitic 579 93 3.7 2.2

Metamorphic 233 98 1.6 0.7

Sedimentary 232 91 8.1 1.3

Volcanic 99 98 1.7 0

Aggregated 1,143 95 3.1 1.4

Trace elements

Granitic 252 68 22 10

Metamorphic 97 81 1

9.7 9.5

Sedimentary 130 67 18 15

Volcanic 51 68 1

9.8 122

Aggregated 530 73 16 11

Uranium and radioactive constituents2

Granitic 239 54 32 14

Metamorphic 82 94 1

6.4 0

Sedimentary 133 76 1

12 12

Volcanic 48 89 7.9 1

3.2

Aggregated 502 72 20 8.2

Any inorganic constituent2,3

Granitic 327 50 30 20

Metamorphic 120 79 12 9.5

Sedimentary 167 60 20 20

Volcanic 57 68 1

9.8 122

Aggregated 671 63 21 16

1

Moderate or high aquifer-scale proportion for the constituent class was set equal to the greatest moderate or high aquifer-scale proportion for an individual 

component of the class. The calculated proportion for the class was smaller than the greatest proportion for an individual component in the class. This situation may occur when not all wells have data for all components of the class (see appendix C for discussion).

2

Aquifer-scale proportions for radioactive constituents and any inorganic constituent with health-based benchmarks were calculated using unadjusted gross 

alpha particle activity. If adjusted gross alpha particle activity is used instead of unadjusted gross alpha particle activity, the results are:

Lithology

Radioactive 

constituents

Any inorganic 

constituent

Moderate High Moderate High

Granitic 22 11 29 17

Metamorphic 3.7 0 11 10

Sedimentary 1

11 8.3 22 17

Volcanic 7.9 0 1

9.8 122

Aggregated 14 6.2 21 15

3

Aquifer-scale proportions for any inorganic constituent were calculated with wells having data for trace elements or radioactive constituents. Wells having 

data only for nutrients were not included (appendix C).
42 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 8B. Summary of aquifer-scale proportions in the granitic, 

metamorphic, sedimentary, volcanic, and aggregated primary 

aquifer systems for inorganic constituent classes with secondary 

maximum contaminent level (SMCL) benchmarks, Sierra Nevada 

Regional (SNR) study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project.

[Aquifer-scale proportions calculated with the spatially weighted method 

(equations 2 and 4). Relative-concentration (RC) categories for inorganic

constituents: high, RC > 1.0; moderate, RC > 0.5 and RC ≤ 1.0; low, 

RC ≤ 0.5. RC defined as measured value divided by benchmark value. 

Abbreviations: >, greater than; ≤, less than or equal to]

Constituent 

class and aquifer 

lithology

Number 

of wells

Aquifer-scale proportion 

(in percent)

Low Moderate High

Salinity indicators with SMCL benchmarks1

Granitic 297 96 2.6 1.3

Metamorphic 104 96 2.0 1.4

Sedimentary 144 92 7.4 0

Volcanic 59 95 3.4 1.2

Aggregated 604 96 2.8 1.3

Trace metals with SMCL benchmarks2

Granitic 231 78 7.2 15

Metamorphic 73 62 5.2 4

32

Sedimentary 102 90 0 8.9

Volcanic 45 88 2.1 9.9

Aggregated 451 76 5.5 18

Any inorganic constituent with SMCL benchmarks3

Granitic 212 77 7.9 15

Metamorphic 67 62 5.2 4

32

Sedimentary 99 84 7.3 4

8.9

Volcanic 45 85 5.5 9.9

Aggregated 423 76 6.8 18

1

Salinity indicators with SMCL benchmarks: total dissolved solids, specific 

conductance, chloride, and sulfate.

2

Trace metals with SMCL benchmarks: iron, manganese, and zinc.

3

Aquifer-scale proportions for any inorganic constituent with SMCL 

benchmarks were calculated using only wells with data for at least one salinity 

indicator and at least one trace metal with SMCL benchmarks. 

4

High-RC aquifer-scale proportion for the constituent class was set equal to 

the greatest high-RC aquifer-scale proportion for an individual component of 

the class. The calculated proportion for the class was smaller than the greatest 

proportion for an individual component in the class. This situation may occur 

when not all wells have data for all components of the class (see appendix C

for discussion). 

Table 9. Results of contingency table tests for differences in 

aquifer-scale proportions of selected inorganic constituents and 

constituent classes between granitic, metamorphic, sedimentary, 

and volcanic primary aquifer systems, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project.

[Significance defined as p-value less than threshold value (α) of 0.05. Aquifer 

lithology class: G, granitic; M, metamorphic, S, sedimentary; V, volcanic. 

Abbreviations: ns, no significant differences; SMCL, secondary maximum 

contaminant levels; >, greater than; <, less than]

Constituent

Proportion high or 

moderate compared 

to proportion low

Significant 

differences

p-value

Individual inorganic constituents with health-based benchmarks

Arsenic 0.725 ns

Boron 0.774 ns

Fluoride 0.001 S > G, S > M, S > V

Gross alpha particle 

activity1

<0.001 G > M, G > V, 

S > M

Radon-222 <0.001 G > M, G > S, 

G > V, S > V

Uranium 0.050 G > M, S > M

Individual inorganic constituents with SMCL benchmarks

Iron 0.001 M > G, M > S, 

M > V

Manganese <0.001 M > G, M > S, 

M > V

Classes of inorganic constituents with health-based benchmarks2

Nutrients (nitrate) 0.003 G > M, S > M, 

S > V

Trace elements 0.079 ns

Uranium and 

radioactive 

constituents1

<0.001 G > M, G > S, 

G > V, S > M

Any inorganic 

constituent1

<0.001 G > M, G > V, 

S > M

Classes of inorganic constituents with SMCL benchmarks2

Salinity indicators 0.472 ns

Metals <0.001 M > G, M > S, 

M > V, G > S

Any inorganic SMCL 

constituent

<0.001 M > S, M > V

1

Aquifer-scale proportions for gross alpha particle activity, uranium and 

radioactive constituents, and any inorganic constituent with health-based 

benchmarks were calculated using unadjusted gross alpha particle activity and 

without radon-222 data. If adjusted gross alpha particle activity is used instead 

of unadjusted gross alpha particle activity, the results are:

Constituent or class p-value Significant differences

Adjusted gross alpha particle activity 0.435 ns

Uranium and radioactive constituents <0.001 G > M, G > S, G > V, S > M

Any inorganic constituent <0.001 G > M, S > M

2

For classes of constituents, statistical test performed with the maximum 

relative-concentration for any constituent in the class for each sample.
Status and Understanding of Groundwater Quality 43

Trace Elements

The trace element constituent class includes a variety 

of metallic and non-metallic constituents that typically are 

present in groundwater at concentrations less than 1 mg/L 

(Hem, 1985). Trace elements with health-based benchmarks 

had high-RC aquifer-scale proportion of 11 percent and 

moderate-RC aquifer-scale proportion of 16 percent in the 

SNR study unit (table 8A). The sum of the proportions of the 

primary aquifer system with high RCs or moderate RCs of 

any trace element was not significantly different among the 

four aquifer lithologies (table 9). Arsenic, boron, and fluoride 

were the only trace elements having high-RC aquifer-scale 

proportions of greater than approximately 2 percent for the 

SNR study unit as a whole (table 7B). Twelve other trace 

elements were detected at high RCs in less than 2 percent of 

the primary aquifer system or were only detected at moderate 

RCs (table 7B).

Arsenic

Arsenic is a semi-metallic trace element. Natural sources 

to groundwater include dissolution of arsenic-bearing minerals 

and desorption of arsenic from mineral surfaces. Pyrite, an 

iron-sulfide mineral, is a common accessory mineral in 

aquifer materials and may contain up to several percent (by 

weight) of arsenic (Smedley and Kinniburgh, 2002). Potential 

anthropogenic sources of arsenic include copper ore smelting, 

coal combustion, arsenical pesticides, arsenical veterinary 

pharmaceuticals, and wood preservatives (Welch and 

Stollenwerk, 2003). In addition, mining for copper, gold, and 

other metals may increase the rate of dissolution of naturally 

occurring arsenic-bearing minerals (Smedley and Kinniburgh, 

2002). The MCL-US for arsenic was lowered from 

50 micrograms per liter (μg/L) to 10 μg/L in 2002, and chronic 

exposure to arsenic concentrations between 10 and 50 μg/L in 

drinking water has been linked to increased cancer risk and to 

non-cancerous effects including skin damage and circulatory 

problems (U.S. Environmental Protection Agency, 2010). 

An estimated 8 percent of groundwater resources used for 

drinking water in the United States have high RCs of arsenic 

(>10 μg/L) (Focazio and others, 2000; Welch and others, 

2000), and high concentrations of arsenic in groundwater 

resources used for drinking water are a worldwide concern 

(Smedley and Kinniburgh, 2002; Welch and others, 2006).

In the SNR study unit, arsenic was present at high RCs 

in 9.7 percent of the aggregated primary aquifer system and 

at moderate RCs in 10.1 percent of the system (table 7B; 

fig. 11A) and was present at high and moderate RCs in all 

four lithologic primary aquifer systems (table 7A; fig. 11A). 

The sum of the proportions of the primary aquifer system 

with high RCs or moderate RCs of arsenic was not significantly different among the four aquifer lithologies (table 9). 

However, the high-RC aquifer-scale proportion for arsenic in 

the volcanic system was significantly greater than the high-RC 

aquifer-scale proportions in the granitic, metamorphic, and 

sedimentary systems (contingency table test, p = 0.010; 

table 7A; fig. 11A).

The cells contributing most to the high-RC and 

moderate-RC aquifer-scale proportions of arsenic were 

different for the four aquifer lithologic types. For the granitic 

system, the greatest contribution to high-RC and moderate-RC 

aquifer-scale proportions of arsenic came from cells located in 

the southern half of the SNR study unit (cells 26, 30, 13, 23, 

24; fig. 12A). This region includes the Central Sierra study unit 

and Lake Isabella area of the Southern Sierra study unit, which 

are areas known to have high and moderate RCs of arsenic in 

groundwater from granitic aquifers (Fram and Belitz, 2012). 

The majority of the cells contributing most to the high and 

moderate RCs of arsenic in the metamorphic system contained 

metamorphic rocks of the Western Metamorphic Belt (cells 1, 

2, 12, 11). The cells contributing most to the high-RC and 

moderate-RC aquifer-scale proportions of arsenic in the 

volcanic system were located near Lake Tahoe (cells 17, 18, 

9). High and moderate RCs of arsenic in the sedimentary 

system were located near areas with high and moderate RCs 

of arsenic in the hard-rock areas; the cells contributing most 

to high-RC and moderate-RC aquifer-scale proportions in 

the sedimentary system were cell 26 in the southern part of 

the study unit, which presumably is dominated by sediments 

derived from the surrounding granitic rocks in cell 26, 

and cells 8 and 18 near Lake Tahoe, where sediments are 

presumably dominated by the nearby volcanic rocks.

Arsenic concentrations showed significant negative 

correlations with aridity index, elevation, and latitude 

(table 10B). These correlations likely reflect the positive 

correlations between aridity index and both elevation and latitude (table 6B) and the association between higher arsenic concentrations and location in a particular compositional band in 

the Sierra Nevada batholith that is along the southwestern side 

of the SNR study unit (Fram and Belitz, 2012; fig. 12A). In this 

part of the Sierra Nevada batholith, granitic magmas appear to 

have assimilated reduced sedimentary materials (reduced phyllites and pelitic schists) (Ague and Brimhall, 1987, 1988). The 

sedimentary protoliths for these materials, black shales, commonly contain higher concentrations of many trace elements, 

such as arsenic, boron, copper, chromium, molybdenum, vanadium, selenium, uranium, and zinc (Tourtelot, 1970).

Arsenic concentrations also were significantly correlated 

with geochemical conditions: arsenic concentration was 

positively correlated with pH and negatively correlated with 

DO (table 10B). These correlations between arsenic and 

geochemical conditions are consistent with the two primary 

mechanisms affecting arsenic concentrations in groundwater 

(Smedley and Kinniburgh, 2002; Welch and others, 2006; 

Fram and Belitz, 2012). One mechanism is release of arsenic 

resulting from reductive dissolution of iron or manganese 

oxyhydroxides under reducing conditions, and the other is 

pH-dependent desorption of arsenic from the oxyhydroxides in 

alkaline, oxic groundwater. Fram and Belitz (2012) observed a 

significant relation between arsenic concentration and groundwater age class in the Tahoe-Martis, Central Sierra, and Southern Sierra study units (higher arsenic in pre-modern groundwater) that was not seen in the SNR study unit, likely because 
44 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Arsenic Boron Fluoride Uranium

Aggregated

Granitic

Metamorphic

Sedimentary

Volcanic

Constituent

Primary aquifer system

Low

Moderate

High

Proportion of primary aquifer system with

relative-concentrations in each category

sac14-0538_Figure 11a

EXPLANATION

A

Figure 11. Aquifer-scale proportions for (A) arsenic, boron, fluoride, and uranium and for (B) nitrate, total dissolved solids, manganese, 

and organic constituents in the aggregated, granitic, metamorphic, sedimentary, and volcanic primary aquifer systems, Sierra Nevada 

Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Status and Understanding of Groundwater Quality 45

Low

Moderate

High

Proportion of primary aquifer system with

relative-concentrations in each category

Nitrate Total dissolved

solids

Manganese Organic

constituents

Aggregated

Granitic

Metamorphic

Sedimentary

Volcanic

Constituent

Primary aquifer system

Not detected (organic constituents only)

sac14-0538_Figure 11b

EXPLANATION

B

Figure 11. —Continued
46 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

IP004884_Figure 12a

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

Aquifer lithology

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Arsenic concentration, in micrograms per liter

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

A

Sierra Nevada Regional

 study unit grid cell 

17

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. Concentrations of (A) arsenic, (B) boron, (C) fluoride, (D) nitrate, (E) uranium, and (F) manganese for wells sampled by 

USGS-GAMA for the Sierra Nevada Regional study unit in 2008, the Tahoe-Martis study unit in 2007, and the Central Sierra and Southern 

Sierra study units in 2006 and all wells in the California Department of Public Health (CDPH) database with data during the period 

May 2006 through October 2008, Sierra Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment 

(GAMA) Priority Basin Project.
Status and Understanding of Groundwater Quality 47

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 12b

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

Aquifer lithology

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Boron concentration, in micrograms per liter

< 500 (Low) 

>500 to <1,000 (Moderate) 

>1,000 (High) 

< 500 (Low) 

>500 to <1,000 (Moderate) 

>1,000 (High) 

< 500 (Low) 

>500 to <1,000 (Moderate) 

>1,000 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

B

Sierra Nevada Regional

 study unit grid cell 

17

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. —Continued
48 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 12c

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

Aquifer lithology

EXPLANATION

Sierra Nevada Regional

 study unit 

Sierra Nevada Regional

 study unit grid cell 

USGS-GAMA Sierra Nevada

 Regional study unit

Fluoride concentration, in milligrams per liter

< 1 (Low) 

>1 to <2 (Moderate) 

< 1 (Low) 

>1 to <2 (Moderate) 

< 1 (Low) 

>1 to <2 (Moderate) 

>2 (High) 

>2 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

C

17

Granitic

Metamorphic

Sedimentary

Volcanic

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. —Continued
Status and Understanding of Groundwater Quality 49

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 12d

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

EXPLANATION

Sierra Nevada Regional

 study unit 

Sierra Nevada Regional

 study unit grid cell 

USGS-GAMA Sierra Nevada

 Regional study unit

Nitrate concentration, in milligrams per liter

< 5 (Low) 

>5 to <10 (Moderate) 

< 5 (Low) 

>5 to <10 (Moderate) 

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

D

17

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. —Continued
50 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 12e

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

EXPLANATION

Sierra Nevada Regional

 study unit 

Sierra Nevada Regional

 study unit grid cell 

USGS-GAMA Sierra Nevada

 Regional study unit

Uranium concentration, in picocuries per liter

< 10 (Low) 

>10 to < 20 (Moderate) 

< 10 (Low) 

>10 to < 20 (Moderate) 

< 10 (Low) 

>10 to < 20 (Moderate) 

>20 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

E

17

>20 (High) 

>20 (High) 

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. —Continued
Status and Understanding of Groundwater Quality 51

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 12f

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Pacific Ocean

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Manganese concentration, in micrograms per liter

< 25 (Low) 

>25 to < 50 (Moderate) 

>50 (High) 

< 25 (Low) 

>25 to < 50 (Moderate) 

>50 (High) 

< 25 (Low) 

>25 to < 50 (Moderate) 

>50 (High) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

F

Sierra Nevada Regional

 study unit grid cell 

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 12. —Continued
52 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 10A. Results of multi-stage Kruskal-Wallis tests for differences in median values of selected potential explanatory factors and 

water-quality constituents between samples classified into groups by aquifer lithologic class, oxidation-reduction class, site type class, 

or groundwater age class, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment 

(GAMA) Priority Basin Project.—Continued

[Factors yielding a result of significance in the Kruskal-Wallis test were evaluated with Tukey’s test on the single-factor analysis of varience of the ranks. 

Significance defined as p-value less than threshold value (α) of 0.05. Aquifer lithology class: G, granitic; M, metamorphic; S, sedimentary; V, volcanic (see 

appendix B). Oxidation-reduction class: see appendix B for definitions of oxic and anoxic. Depth class: spring (SP), site is a spring; shallow (SH), well 

depth < 170 ft bls; overlapping (OL), top of perforations < 170 ft bls and well depth > 170 ft bls; Deep (DP), well depth > 170 ft bls and top of perforations

> 170 ft bls. Age class: see appendix B for explanation of classes. Abbreviations: ft bls, feet below land surface; ns, no significant differences; SMCL, 

secondary maximum contaminant levels; >, greater than; <, less than; ns, no significant differences]

Constituent

Aquifer lithology class

(G, M, S, V)

Oxidation-reduction 

class

[oxic (OX), 

anoxic (AN)]

Depth class 

[spring (SP), 

shallow (SH), 

overlapping (OL), 

deep (DP)]

Age class 

[modern (MOD), 

mixed (MIX), 

pre-modern (PRE)]

p Significant 

differences p Significant differences p Significant differences p Significant differences

Individual inorganic constituents

Fluoride 0.133 ns <0.001 AN > OX <0.001 SH > SP

OL > SP

DP > SP

0.036 PRE > MOD

Arsenic 0.036 M > G, 

V > G

0.013 AN > OX 0.065 ns 0.139 ns

Boron 0.119 ns <0.001 AN > OX 0.003 SH > SP

OL > SP

DP > SP

0.002 PRE > MOD

PRE > MIX

Gross alpha particle activity 0.295 ns 0.289 ns 0.281 ns 0.279 ns

Radon-222 activity 0.004 G > V 0.185 ns 0.258 ns 0.370 ns

Uranium activity 0.087 ns 0.059 ns 0.678 ns 0.575 ns

Individual inorganic constituents with SMCL benchmarks

Iron 0.223 ns <0.001 AN > OX 0.108 ns 0.300 ns

Manganese 0.180 ns <0.001 AN > OX 0.037 OL > SP 0.055 ns

Classes of inorganic constituents1

Trace elements with health-based 

benchmarks

0.031 M > G, 

S > G

<0.001 AN > OX 0.002 SH > SP

OL > SP

DP > SP

0.008 PRE > MOD

PRE > MIX

Nutrients (nitrate) 0.312 ns 0.001 OX > AN 0.029 SH > SP 0.111 ns

Uranium and radioactive 

constituents

0.375 ns 0.370 ns 0.398 ns 0.221 ns

Any inorganic constituent with 

health-based benchmarks

0.380 ns 0.001 AN > OX 0.054 ns 0.056 ns

Classes of inorganic constituents with SMCL benchmarks1

Metals 0.090 ns <0.001 AN > OX 0.087 ns 0.143 ns

Salinity indicators 0.072 ns <0.001 AN > OX <0.001 SH > SP

OL > SP

DP > SP

0.035 PRE > MOD

Any inorganic constituent with 

SMCL benchmarks

0.008 M > G, 

V > G

<0.001 AN > OX <0.001 SH > SP

OL > SP

DP > SP

0.021 PRE > MOD
Status and Understanding of Groundwater Quality 53

Table 10A. Results of multi-stage Kruskal-Wallis tests for differences in median values of selected potential explanatory factors and 

water-quality constituents between samples classified into groups by aquifer lithologic class, oxidation-reduction class, site type class, 

or groundwater age class, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment 

(GAMA) Priority Basin Project.—Continued

[Factors yielding a result of significance in the Kruskal-Wallis test were evaluated with Tukey’s test on the single-factor analysis of varience of the ranks. 

Significance defined as p-value less than threshold value (α) of 0.05. Aquifer lithology class: G, granitic; M, metamorphic; S, sedimentary; V, volcanic (see 

appendix B). Oxidation-reduction class: see appendix B for definitions of oxic and anoxic. Depth class: spring (SP), site is a spring; shallow (SH), well 

depth < 170 ft bls; overlapping (OL), top of perforations < 170 ft bls and well depth > 170 ft bls; Deep (DP), well depth > 170 ft bls and top of perforations

> 170 ft bls. Age class: see appendix B for explanation of classes. Abbreviations: ft bls, feet below land surface; ns, no significant differences; SMCL, 

secondary maximum contaminant levels; >, greater than; <, less than; ns, no significant differences]

Constituent

Aquifer lithology class

(G, M, S, V)

Oxidation-reduction 

class

[oxic (OX), 

anoxic (AN)]

Depth class 

[spring (SP), 

shallow (SH), 

overlapping (OL), 

deep (DP)]

Age class 

[modern (MOD), 

mixed (MIX), 

pre-modern (PRE)]

p Significant 

differences p Significant differences p Significant differences p Significant differences

Classes of organic and special-interest constituents1

Trihalomethanes (chloroform) 0.918 ns 0.110 ns 0.097 ns 0.251 ns

Gasoline oxygenates 

(methyl tert-butyl ether)

0.810 ns 0.504 ns 0.169 ns 0.233 ns

Solvents 0.050 ns 0.802 ns 0.324 ns 0.687 ns

Any VOC 0.508 ns 0.374 ns 0.003 OL > SP 0.060 ns

Pesticides 0.534 ns 0.640 ns 0.057 ns 0.169 ns

Any organic constituent 0.605 ns 0.460 ns 0.003 OL > SP 0.026 MOD > PRE

MIX > PRE

Special-interest constituent

Perchlorate 0.374 ns 0.086 ns 0.007 SH > SP

OL > SP

0.017 MOD > MIX

1

For classes of constituents, statistical test performed with the maximum relative-concentration for any constituent in the class for each sample.
54 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008 Table 10B. Results of Spearman’s rho tests for correlations between selected potential explanatory factors and selected water-quality constituents, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued [ρ (rho), Spearman’s correlation statistic. Significance defined as p-value less than threshold value (α) of 0.05. Tests in which the variables were determined to be significantly correlated on the basis of p-values (not shown) have ρ-values underlined and in bold font. Black values, positive correlation; red values, negative correlation. Abbreviations: LUFT, leaking or formerly leaking underground fuel tank; SMCL, secondary maximum contaminant level; VOC, volatile organic compound]

ρ

Land-use factors Geography factors Primary aquifer system factors

Percentage 

agricultural 

land use

Percentage 

natural land 

use

Percentage 

urban land 

use

Density 

of septic 

tanks

Density 

of 

LUFTs

Aridity 

Index Elevation Latitude

Depth 

to top of 

open or 

screen1

Depth to 

bottom of 

open or 

screen1

pH

Dissolved 

oxygen 

concentration

Individual inorganic constituents

Fluoride 0.29 –0.22 0.11 0.18 0.03 –0.69 –0.55 –0.53 –0.02 –0.16 0.33 –0.64

Arsenic 0.02 –0.10 0.11 0.02 0.03 –0.38 –0.23 –0.23 0.10 –0.09 0.41 –0.34Boron 0.32 –0.33 0.23 0.14 0.03 –0.52 –0.41 –0.33 0.00 –0.06 0.41 –0.59Gross alpha particle activity 0.07 –0.12 0.11 –0.19 –0.22 –0.38 0.01 –0.36 –0.09 –0.06 0.19 –0.22Radon-222 activity1 –0.10 0.12 –0.05 –0.08 –0.38 –0.04 0.33 –0.36 –0.75 –0.03 –0.54 0.21Uranium activity 0.18 –0.19 0.11 –0.11 –0.16 –0.43 0.06 –0.44 –0.15 0.02 0.17 0.02

Individual inorganic constituents with SMCL benchmarks

Iron –0.17 0.00 0.12 0.22 0.13 0.06 –0.11 0.11 –0.09 0.03 0.03 –0.47

Manganese –0.12 0.06 0.01 0.15 0.05 –0.05 –0.26 0.06 –0.02 0.05 0.08 –0.61

Classes of inorganic constituents2

Trace elements with healthbased benchmarks 0.16 –0.19 0.15 0.05 0.06 –0.53 –0.39 –0.35 0.18 –0.10 0.50 –0.49

Nutrients (nitrate) 0.20 –0.33 0.31 0.16 0.08 –0.40 –0.30 –0.32 –0.28 –0.22 –0.17 0.11Uranium and radioactive 

constituents

0.08 –0.11 0.09 –0.18 –0.22 –0.37 0.04 –0.38 –0.11 –0.05 0.22 –0.20

Any inorganic constituent with 

health-based benchmarks

0.22 –0.17 0.10 –0.07 –0.07 –0.56 –0.25 –0.38 0.11 –0.11 0.45 –0.37

Classes of inorganic constituents with SMCL benchmarks2

Metals –0.16 0.09 0.01 0.17 0.07 –0.01 –0.21 0.03 0.07 0.04 0.03 –0.54

Salinity indicators 0.28 –0.32 0.24 0.36 0.22 –0.64 –0.70 –0.35 –0.05 –0.17 0.36 –0.57Any inorganic constituent with 

SMCL benchmarks

0.16 –0.24 0.24 0.34 0.25 –0.45 –0.63 –0.20 –0.08 –0.15 0.34 –0.65
Status and Understanding of Groundwater Quality 55

Table 10B. Results of Spearman’s rho tests for correlations between selected potential explanatory factors and selected water-quality constituents, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[ρ (rho), Spearman’s correlation statistic. Significance defined as p-value less than threshold value (α) of 0.05. Tests in which the variables were determined to be significantly correlated on the basis of p-values (not shown) have ρ-values underlined and in bold font. Black values, positive correlation; red values, negative correlation. Abbreviations: LUFT, leaking or formerly leaking underground fuel tank; SMCL, secondary maximum contaminant level; VOC, volatile organic compound]

ρ

Land-use factors Geography factors Primary aquifer system factors

Percentage 

agricultural 

land use

Percentage 

natural land 

use

Percentage 

urban land 

use

Density 

of septic 

tanks

Density 

of 

LUFTs

Aridity 

Index Elevation Latitude

Depth 

to top of 

open or 

screen1

Depth to 

bottom of 

open or 

screen1

pH

Dissolved 

oxygen 

concentration

Classes of organic constituents2

Trihalomethanes (chloroform) –0.09 –0.14 0.23 0.28 0.18 0.00 0.17 0.09 0.04 0.15 –0.14 –0.10

Gasoline oxygenates 

(methyl tert-butyl ether)

–0.07 –0.26 0.28 0.05 0.17 0.06 0.09 0.10 –0.09 0.03 –0.09 –0.07

Solvents –0.02 –0.28 0.22 0.19 0.15 –0.07 –0.10 0.18 –0.06 0.12 –0.06 –0.15Any VOC –0.03 –0.37 0.37 0.27 0.32 –0.03 –0.15 0.09 –0.21 0.06 –0.12 –0.13

Pesticides 0.18 –0.33 0.31 0.26 0.19 –0.23 –0.30 –0.18 –0.32 –0.11 0.03 –0.15

Any organic constituent 0.07 –0.43 0.40 0.31 0.34 –0.13 –0.27 0.02 –0.28 0.02 –0.04 –0.17

Special-interest constituent

Perchlorate 0.17 –0.22 0.20 0.27 0.19 –0.41 –0.37 –0.39 –0.26 –0.24 –0.14 –0.01

1The rho values corresponding to p-values less than 0.05 are higher for tests involving radon-222, chloroform, depth to top of screened or open interval, and depth to bottom of screened or open interval 

because not all samples had data for those parameters; tests not involving those parameters used 83 samples. Twenty-eight samples were analyzed for radon-222, 74 samples had accepted data for chloroform (see text for discussion), 63 sites were wells, and of those, 61 had data for bottom of interval and 49 had data for top of interval.

2For classes of constituents, statistical test performed with the maximum relative-concentration for any constituent in the class for each sample.
56 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

the SNR study unit had significantly fewer pre-modern 

groundwater samples (8.5 percent) than these other study 

units (24 percent) (contingency table test, p = 0.005). Arsenic, 

boron, fluoride, and uranium all show strong positive correlations with one another (table 11), primarily reflecting that all 

are found in higher concentrations in groundwater in the same 

compositional band of the Sierra Nevada batholith.

Boron

Boron is a naturally occurring semi-metallic element 

with high solubility in water. Natural sources of boron include 

evaporate minerals, such as borax, ulexite, and colemanite, and boron-bearing silicate minerals, such as tourmaline, that are primarily found in igneous rocks (Hem, 1985; 

Klein and Hurlbut, 1993). Seawater contains approximately 

4,500 μg/L of boron, and boron also is associated with thermal 

springs and volcanic activity (Hem, 1992). Boron occurs in 

wastewater because borax is a component of many detergents. 

Other anthropogenic uses of boron compounds include 

borosilicate glass, boric acid insecticide, chemical reagents, 

semi-conductors, and fertilizers. Boron is an essential nutrient 

for plants, but is toxic to plants at high concentrations. The 

comparison benchmark used for boron in this study was 

the NL-CA of 1,000 μg/L (California Department of Public 

Health, 2010). At concentrations greater than the HAL-US 

of 6,000 μg/L, boron may adversely affect fetal development 

(U.S. Environmental Protection Agency, 2008).

Boron was present at high RCs in 2.0 percent and 

moderate RCs in 2.2 percent of the aggregated primary 

aquifer system (table 7B; fig. 11A). Boron was present at 

high or moderate RCs in all four lithologic primary aquifer 

systems (table 7A; figs. 11A, 12B). The sum of the proportions 

of the primary aquifer system with high RCs or moderate 

RCs of boron was not significantly different among the four 

aquifer lithologies (table 9).The cells contributing most to the 

high-RC and moderate-RC aquifer-scale proportions of boron 

in the primary aquifer system as a whole were cells 24, 25, and 

26 in the southern end of the SNR study unit, cells 13 and 20 

in the central part of the study unit, and cells 2 and 17 in the 

northern part (fig. 12B).

The pattern of significant relations between boron and 

potential explanatory factors observed for SNR study unit 

was similar to that observed for the Tahoe-Martis, Central 

Sierra, and Southern Sierra study units by Fram and Belitz 

(2012). Boron concentrations were negatively correlated with 

aridity index, elevation, and latitude (table 10B), reflecting 

location of groundwater with higher boron concentrations in 

the southern and southwestern parts of the study unit (fig. 12B). 

The absence of correlation between boron and nitrate (table 11) 

suggests that the positive correlation between boron and the 

percentage of agricultural land use (table 10B) reflects the fact 

that many of the SNR wells in agricultural lands were in the 

southern valleys, rather than an input of boron from agricultural processes. Boron was negatively correlated with DO and 

positively correlated with pH (table 10B), and higher concentrations of boron were associated with pre-modern groundwater 

rather than modern or mixed-age groundwater, and with sites 

that were wells rather than springs (table 10A). These correlations are consistent with inferred mechanisms for increasing 

boron concentrations in groundwater. Boron concentrations 

Table 11. Results of Spearman’s rho tests for correlations between selected water-quality constituents, Sierra Nevada Regional (SNR) 

study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[ρ (rho), Spearman’s correlation statistic. Significance defined as p-value less than threshold value (α) of 0.05. Tests in which the variables were determined to 

be significantly correlated on the basis of p-values (not shown) have ρ-values underlined and in bold font. Black values, positive correlation; red values, negative correlation. Abbreviations: MTBE, methyl tert-butyl ether]

Constituent Arsenic Boron Iron Manganese

Gross 

alpha 

particle 

activity

Uranium Herbicides Perchlorate MTBE Chloroform Nitrate

Fluoride 0.52 0.69 0.22 0.34 0.29 0.17 0.19 0.29 –0.17 –0.05 0.20

Arsenic 0.59 0.16 0.14 0.53 0.38 0.04 0.12 –0.02 0.01 0.08

Boron 0.17 0.30 0.38 0.31 0.25 0.11 –0.10 –0.09 0.12

Iron 0.68 0.16 –0.20 –0.02 0.00 0.04 0.25 –0.19

Manganese 0.13 –0.24 –0.03 –0.15 0.04 0.03 –0.28

Gross alpha 

particle activity

0.73 0.12 0.18 0.13 –0.06 0.29

Uranium 0.15 0.27 0.13 –0.10 0.48

Herbicides 0.41 0.05 0.07 0.33

Perchlorate 0.11 0.24 0.67

MTBE 0.29 0.14

Chloroform 0.26
Status and Understanding of Groundwater Quality 57

may increase because of evaporative concentration of groundwater in dry climates (low aridity index), or because of longer 

residence times in contact with aquifer materials containing 

boron-bearing minerals or fluids (Fram and Belitz, 2012).

Fluoride

Fluoride is the anionic form of the element fluorine. 

Natural sources of fluoride in groundwater include dissolution 

of fluoride-bearing minerals, such as fluorite (CaF2

) and 

fluorapatite [Ca5

(PO4)

3

(F,OH)] (Hem, 1992). The main 

anthropogenic source of fluoride to water is addition of 

sodium fluoride or hexafluorosilicic acid during drinkingwater treatment as a public health measure to reduce dental 

caries (National Research Council, 2006). Hexafluorosilicic 

acid is a byproduct of the production of phosphate fertilizers 

and hydrofluoric acid and the processing of aluminum. The 

MCL-CA for fluoride, 2 mg/L (table 4A), is lower than the 

MCL-US for fluoride, 4 mg/L. Chronic exposure to fluoride 

concentrations in drinking water above the MCL-US may 

result in bone disease and tooth discoloration (National 

Research Council, 2006).

Fluoride was present at high RCs in 1.8 percent and 

moderate RCs in 0.5 percent of the aggregated primary aquifer 

system (table 7B; fig. 11A). It was detected at high RCs in 

the granitic, metamorphic, and sedimentary primary aquifers 

systems, but not in the volcanic system (table 7A; figs. 11A, 

12C). The proportion of the sedimentary primary aquifer system with high or moderate RCs of fluoride was significantly 

greater than the proportions with high or moderate RCs in the 

granitic, metamorphic, or volcanic systems (table 9).

The cells contributing most to the high-RC and 

moderate-RC aquifer-scale proportions of fluoride in the 

primary aquifer system as a whole were cells 24, 26, and 27 

in the southern end of the SNR study unit and cells 2 and 5 in 

the northern part (fig. 12C). Fluoride has nearly the same set 

of significant correlations with potential explanatory factors 

as does boron (tables 10A,B), and fluoride and boron were 

strongly correlated with one another (table 11).

Other Trace Elements

Eight other trace elements had high-RC aquifer-scale 

proportions of 1 percent or less in the aggregated primary 

aquifer system: antimony, beryllium, cadmium, copper, 

lead, molybdenum, selenium, and strontium (table 7B). Of 

these eight trace elements, molybdenum was the only one 

that also had a moderate-RC aquifer-scale proportion of 

greater than 1 percent. Molybdenum has a non-regulatory 

HAL-US benchmark (table 4A), and all data used in the status 

assessment were from USGS-GAMA because constituents 

with only HAL-US benchmarks commonly are not analyzed 

in regulatory sampling for CDPH. Molybdenum was present 

at high RCs in the granitic and sedimentary primary aquifer 

systems and at moderate RCs in the granitic, sedimentary, and 

volcanic systems (table 7A).

Nutrients

Nutrients in groundwater have natural and anthropogenic 

sources. Natural sources include precipitation, animal waste, 

and dissolution of organic material in soils. Anthropogenic 

sources include fertilizer application, livestock and human 

waste, sewage and septic effluents, and combustion of fossil 

fuels (which emits nitrogen oxides to the atmosphere). Nitrate 

and nitrite have MCL-US benchmarks, and high levels of 

either constituent in drinking water can cause “blue baby” 

syndrome. Nitrate is the more oxidized form, and thus, is the 

most common form in oxic groundwater systems. Although 

evapotranspiration from shallow groundwater can increase 

concentrations of nutrients in groundwater, concentrations of 

nitrate greater than about 1 mg/L (corresponding to an RC of 

0.1) generally are the result of anthropogenic inputs (Nolan 

and Hitt, 2003; Dubrovsky and others, 2010). For this study, 

nitrate was classified as an inorganic constituent, and the 

boundary between low RC and moderate RC for inorganic 

constituents was defined as an RC of 0.5 (see section 

“Groundwater Quality Defined as Relative-Concentrations”).

Nutrients were detected at high RCs in 1.4 percent of 

the aggregated primary aquifer system and at moderate RCs 

in 3.1 percent (table 8A), and the only nutrient reported at 

high or moderate RCs was nitrate (table 7B; fig. 11B). The 

proportions of the granitic and sedimentary primary aquifer 

systems with high or moderate RCs of nitrate were significantly greater than the proportions of the metamorphic system 

with high or moderate RCs of nitrate, and the proportion with 

high or moderate RCs of nitrate in the sedimentary system 

was greater than that in the volcanic system (table 9). Median 

nitrate concentrations in samples from the four aquifer lithologies were not significantly different (table 10A).

The cells contributing most to the high-RC and 

moderate-RC aquifer-scale proportions of nitrate in both 

granitic and sedimentary primary aquifer systems were all in 

the southern part of the SNR study unit: cells 22, 23, 24, 25, 

and 26 (fig. 12D). Nitrate concentrations were significantly 

negatively correlated with aridity index, elevation, and latitude 

(table 10B), which is consistent with location of groundwater 

with higher nitrate concentrations in the southern part of the 

study unit. Nitrate concentrations were significantly greater 

in shallow wells than in springs (table 10A). Because values 

of aridity index and elevation were significantly higher for 

springs than for shallow wells (table 6A), the relation between 

nitrate concentration and site type may reflect location 

rather than an inherent difference in susceptibility to nitrate 

contamination between shallow wells and springs.

Nitrate concentrations were positively correlated with 

percentage of urban land use and negatively correlated with 

percentage of natural land use (table 10B). Nitrate concentrations also showed positive correlations with chloroform, total 

herbicide, and perchlorate concentrations (table 11). There 

were no significant relations between nitrate concentrations 

and groundwater age class, percentage of agricultural land use, 

density of septic tanks or LUFTs, or depth to the top or bottom 
58 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

of the screened or open interval in wells (tables 10A,B). The 

lack of correlation between nitrate concentrations and groundwater age class likely reflects the dominance of samples with 

modern groundwater.

Uranium and Radioactive Constituents

Most of the radioactivity in groundwater comes from 

decay of naturally occurring uranium and thorium in the rocks 

or sediments of the aquifers. Radioactive decay of uranium 

and thorium isotopes produces long series of radioactive 

daughter products, including isotopes of radium, uranium, 

and radon. These elements have different chemical properties, 

and their solubility in groundwater varies with geochemical 

conditions, water chemistry, and aquifer mineralogy (for 

example, Hem, 1992). This study included data for the 

individual radioactive constituents uranium, radium, and 

radon-222 and for gross alpha and beta particle activities, 

which are measures of the activities of all radioactive 

elements in the water sample that decay by alpha or beta 

particle emission. Uranium was compared to the MCL-CA of 

20 picocuries per liter (pCi/L), rather than to the MCL-US of 

30 μg/L, and gross alpha particle activities were not adjusted 

for uranium activity (see appendix D).

Radioactive constituents with health-based benchmarks 

were present at high RCs in 8.2 percent of the aggregated 

primary aquifer system and at moderate RCs in 20 percent 

(table 8A). Granitic and sedimentary primary aquifer systems 

had significantly greater proportions with high or moderate RCs 

of uranium and radioactive constituents than did metamorphic 

and volcanic primary aquifer systems (tables 8A, 9).

Uranium

Sources of uranium to groundwater include dissolution of 

uranium-bearing minerals, such as uraninite (UO2

), zircon, and 

titanite, and desorption of uranium from mineral surfaces in the 

presence of bicarbonate (Hem, 1992; Jurgens and others, 2010). 

Chronic exposure to uranium in drinking water at concentrations greater than the MCL-US or activities greater than the 

MCL-CA may result in toxic effects to the kidneys or increased 

cancer risks (U.S. Environmental Protection Agency, 2009).

Uranium was present at high RCs in 2.9 percent of the 

aggregated primary aquifer system and at moderate RCs in 

7.7 percent (table 7B; fig. 11A). There were no significant 

differences in aquifer-scale proportions among the four 

lithologic primary aquifer systems (fig. 11A), largely because 

of the relatively small number of wells in volcanic and 

metamorphic aquifer lithologies that had data for uranium 

(tables 7A, 9).

The cells contributing most to the high-RC aquifer-scale 

proportions of uranium were not the same for the granitic 

and sedimentary primary aquifer systems. Cells 23, 24, and 

14, located along the western side of the southern portion of 

the study unit, contributed the most to the high aquifer-scale 

proportion for uranium in granitic rocks (fig. 12E). This area 

is part of a band within the Sierra Nevada batholith that has 

previously been identified as having high RCs of uranium in 

groundwater (for example, California Department of Water 

Resources, 1990; Fram and Belitz, 2012). The only significant 

relations between uranium and potential explanatory factors in 

the SNR study unit dataset were the negative correlations of 

uranium concentrations with aridity index and latitude, which 

are consistent with location in this part of the study unit.

Cells 26 and 23 in the southern portion of the study unit 

and cell 18 around Lake Tahoe contributed the most to the 

high-RC aquifer-scale proportion for uranium in sedimentary 

deposits (fig. 12E).

Gross Alpha Particle Activity

Gross alpha particle activity was present at high RCs in 

7.8 percent of the aggregated primary aquifer system and at 

moderate RCs in 14.5 percent (table 7B). The proportions of 

the granitic and sedimentary systems having high or moderate 

RCs of gross alpha particle activity were significantly greater 

than the proportions of the metamorphic systems having high 

or moderate RCs of uranium, and proportions in the granitic 

system were greater than the proportions in the volcanic 

system (tables 7A, 9). Of the 88 wells having high or moderate 

RCs of gross alpha particle activity and data for uranium, 

55 (63 percent) also had high or moderate RCs of uranium. 

Adjusted gross alpha particle activity was present at high RCs 

in 0.9 percent of the aggregated primary aquifer system and 

at moderate RCs in 1.7 percent, indicating that most of the 

unadjusted gross alpha particle activity was due to uranium 

activity. Gross alpha particle activity and uranium were 

positively correlated (table 11). Radium may also contribute 

to gross alpha particle activity and was present at high RCs in 

0.2 percent of the aggregated primary aquifer system and at 

moderate RCs in 2.2 percent (table 7B).

Radon-222

The source of radon-222 in groundwater is the decay of 

naturally occurring radium-226 (a member of the uranium-238 

decay series) in aquifer materials. Radon-222 was present at 

high RCs in 14.1 percent of the aggregated primary aquifer 

system and at moderate RCs in 28.8 percent (table 7B). The 

proportion of the granitic primary aquifer system with high 

or moderate RCs of radon-222 was significantly greater than 

the proportions of the metamorphic, sedimentary, or volcanic 

systems with high or moderate RCs (table 9). Results for 

the proportion of the aggregated primary aquifer system 

as a whole with high or moderate RCs of radon-222 likely 

were biased towards greater values because of the unequal 

distribution of the data: 60 percent of the granitic sub-cells 
Status and Understanding of Groundwater Quality 59

had at least one well with radon-222 data, and 20 percent of 

the metamorphic, sedimentary, and volcanic sub-cells had at 

least one well with radon-222 data. Granitic sub-cells having 

radon-222 data composed 68 percent of the total area of 

sub-cells having radon-222 data, whereas granitic sub-cells 

constitute 51 percent of the total area of the study unit. 

Therefore, data from wells in granitic rocks—the lithology 

with the highest RCs of radon-222—were over-represented 

in the calculation of high-RC and moderate-RC aquifer-scale 

proportions in the study unit as a whole (eq. 4).

Radon-222 activity showed significant negative correlations with the depth to top of open or screened interval 

(table 10B). This relation likely reflects the occurrence of 

radon-222’s parent isotope, radium-226, in aquifer materials, 

and the high degree of mobility of radon-222 in groundwater. 

In oxic, low salinity groundwater, radium is strongly sorbed 

to the surfaces of iron and manganese oxyhydroxides 

and to clays formed during weathering of feldspars 

(Krishnaswami and others, 1982; Szabo and Zapecza, 1991; 

Thomas and others, 1993). Of the 28 USGS-GAMA SNR 

study unit samples having radon-222 data, 25 are from 

fractured-rock aquifers (granitic, metamorphic, or volcanic 

aquifer lithologies). The amount of weathering of primary 

minerals in fractured rocks is likely to be greatest near 

the surface, decreasing with depth. Increased weathering 

results in the dissolution of more uranium-bearing minerals, 

the formation of more secondary iron and manganese 

oxyhydroxide coatings on mineral grains and fracture surfaces, 

and the alteration of more feldspar to clays. Thus, the greater 

amount of weathering that occurs at shallower depths in 

the aquifer system could result in the presence of greater 

amounts of radium-226 on aquifer fracture surfaces and grain 

boundaries and, therefore, greater amounts of radon-222 in the 

groundwater (Focazio and others, 2001).

Constituents with SMCL Benchmarks

The class of constituents with SMCL benchmarks 

includes salinity indicators and several trace metals that are 

commonly present in groundwater. These constituents affect 

the aesthetic properties of water, such as taste, color, and odor, 

or may create technical problems, such as scaling and staining. 

SMCL benchmarks are based on these aesthetic and technical 

concerns and are not health-based benchmarks. SMCL constituents that are salinity indicators include total dissolved solids 

(TDS), specific conductance, chloride, and sulfate. SMCL 

constituents that are trace metals include iron, manganese, 

and zinc. Constituents with SMCL benchmarks were present 

at high RCs in 18 percent of the aggregated primary aquifer 

system and at moderate RCs in 6.8 percent (table 8B).

Natural sources of salinity to groundwater include weathering and dissolution of minerals in soils, sediments, and rocks; 

mixing with saline or brackish waters from the ocean, estuaries, 

or saline lakes; interactions with marine or lacustrine sediments; mixing with hydrothermal solutions; and concentration 

by evapotranspiration of shallow groundwater (Hem, 1985). 

Anthropogenic sources of salinity to groundwater include 

recharge of water used for irrigation, wastewater discharge, and 

increased evaporation caused by changes in land use (Hem, 

1985). All samples with high RCs of chloride or sulfate also had 

high RCs of TDS, and all samples with moderate RCs of chloride or sulfate also had moderate RCs of TDS; thus, the aquiferscale proportions for salinity indicators as a group are the same 

as those for TDS. Salinity indicators were present at high RCs 

in 1.3 percent of the aggregated primary aquifer system and at 

moderate RCs in 2.8 percent (table 8B; fig. 11B). No significant 

differences were observed in aquifer-scale proportions among 

the four aquifer lithologies (table 9; fig. 11B).

Trace metals with SMCL benchmarks were present at 

high RCs in 18 percent of the aggregated primary aquifer system and at moderate RCs in 5.5 percent (table 8B). The proportion of the metamorphic primary aquifer system with trace metals with SMCL benchmarks present at high or moderate RCs 

was significantly greater than the proportions of the granitic, 

sedimentary, and volcanic systems with high or moderate RCs 

of trace metals with SMCL benchmarks (tables 8B, 9). Manganese and iron were the trace metals with SMCL benchmarks 

most commonly present at high and moderate RCs (table 7B). 

Zinc was present at high or moderate RCs in less than 1 percent of the primary aquifer system.

Manganese and Iron

Manganese and iron were present at high RCs in 

15.1 percent and 15.8 percent, respectively, of the aggregated 

primary aquifer system, and at moderate RCs in 3.3 percent 

and 4.4 percent, respectively (table 7B; fig. 11B). The proportions of the metamorphic primary aquifer system with high 

RCs of manganese and iron were significantly greater than the 

proportions of the granitic, sedimentary, and volcanic systems 

with high RCs of manganese and iron (tables 7A, 9; fig. 11B). 

Groundwater with high or moderate RCs of manganese was 

found in most parts of the SNR study unit (fig. 12F).

Natural sources of manganese and iron to groundwater 

include weathering and dissolution of minerals in soils, 

sediments, and rocks. Iron-bearing silicate, sulfide, and 

(or) oxide minerals occur in most rocks and sediments, and 

manganese commonly substitutes for iron in silicate minerals. 

Iron and manganese oxyhydroxide minerals commonly occur 

as coatings on mineral and sediment grains. The solubilities 

of manganese and iron are strongly dependent on oxidationreduction conditions; the more reduced species are much 

more soluble. As expected, the concentrations of manganese 

and iron both showed significant, negative correlations with 

DO, and manganese and iron concentrations were strongly 

correlated with each other (tables 10B, 11).
60 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Organic and Special-Interest Constituents

The organic constituents include two constituent classes: 

volatile organic compounds (VOCs) and pesticides. VOCs are 

characterized by their tendency to evaporate and are present in 

paints, solvents, fuels, fuel additives, refrigerants, fumigants, 

and disinfected water. VOCs typically persist longer in groundwater than in surface water because groundwater is more 

isolated from the atmosphere. Pesticides include herbicides, 

insecticides, and fungicides and are used to control unwanted 

vegetation (weeds), insects, fungi, and other pests in agricultural, urban, and suburban settings. The special-interest group 

includes two chemically unrelated constituents, perchlorate and 

N-nitrosodimethylamine (NDMA) that are of interest in California because they recently have been detected in groundwater 

at concentrations that may affect human health.

The GAMA Priority Basin Project included analysis of 

a large number of organic constituents, many of which are 

not currently (as of 2013) subject to regulation in California 

drinking water. USGS-GAMA analytical methods for organic 

constituents had lower reporting levels than those required 

for sampling for compliance with CDPH regulations. In the 

SNR study unit, the majority of organic constituents detected 

were ones that are already subject to regulation in California 

drinking water. Of the 85 VOCs analyzed, 12 were detected 

at least once, and of these, 11 have MCL-US or MCL-CA 

benchmarks (tables 4A,B). Of the 63 pesticides and pesticide 

degradates analyzed, 8 were detected at least once, and of 

these, 2 were parent compounds with MCL-US or MCL-CA 

benchmarks. In all, of the 70 organic constituents analyzed 

that had no health-based benchmarks, 5 were detected in 

groundwater (table 4B; Shelton and others, 2010).

Figure 13 summarizes the maximum RCs of all organic 

and special-interest constituents detected in USGS-GAMA SNR 

study unit samples and the area-weighted detection frequencies for these constituents in the study unit as a whole (eq. 5). 

Figure 14 shows RCs for detections and area-weighted detection 

frequencies in the four aquifer lithologies for the six organic 

and special-interest constituents either detected at moderate RCs 

in the USGS-GAMA SNR study unit wells (tetrachloroethene 

[PCE], 1,2-dichloroethane [1,2-DCA], and perchlorate) or having an area-weighted detection frequency greater than 10 percent 

in at least one of the four aquifer lithologies (methyl tert-butyl 

ether [MTBE], chloroform, and simazine). The CDPH database 

reported detections of high RCs of PCE, 1,2-DCA, and perchlorate in samples collected between May 1, 2006, and October 31, 

2008, and benzene and carbon tetrachloride were detected at 

moderate RCs in USGS-GAMA Tahoe-Martis, Central Sierra, or 

Southern Sierra study units (Fram and Belitz, 2012).

Aquifer-scale proportions for the eight individual 

constituents either detected at moderate or high RCs or with 

area-weighted detection frequencies greater than 10 percent 

are listed in table 12, and by constituent classes in table 13.

Organic constituents with health-based benchmarks were 

present at high RCs in <1 percent of the aggregated primary 

aquifer system, at moderate RCs in 3.0 percent, at low RCs in 

about 25 percent, and were not detected in about 72 percent of 

the aggregated primary aquifer system (table 13; fig. 11B).

Relations between water quality and potential 

explanatory factors were investigated for chloroform, MTBE, 

maximum RC for solvents, maximum RC for herbicides, 

maximum RC for any VOC, maximum RC for any organic 

constituent, and perchlorate (tables 10A,B). The proportions 

of the sedimentary and metamorphic primary aquifer systems 

having detections of organic constituents at any concentration 

were significantly greater than the proportion of the volcanic 

system having detection of organic constituents at any 

concentration (tables 13, 14; fig. 11B).

Herbicides

All of the pesticides detected in the SNR study unit 

that had health-based benchmarks were herbicides (Shelton 

and others, 2010). Herbicides were not detected at high or 

moderate RCs in the SNR study unit (table 13). No detections 

of any of the herbicides analyzed by USGS-GAMA were 

reported in the CDPH database. The absence of detections 

in the CDPH database was expected because the maximum 

RC of an herbicide detected by USGS-GAMA in the SNR 

study unit was 0.015 (atrazine; Shelton and others, 2010), 

and the reporting levels for all of the herbicides in the CDPH 

database had values with RCs greater than or equal to 0.25 

(tables 4A,B). The only herbicide with a detection frequency 

greater than or equal to 10 percent in a primary aquifer system 

was simazine (table 12; fig. 14). The USGS NAWQA Program 

found simazine to be one of the most frequently detected 

pesticide compounds in groundwater across the United States 

(Gilliom and others, 2006). In California, simazine is most 

commonly used on orchards and vineyards and on rights-ofway for weed control (Kegley and others, 2010).

The area-weighted detection frequencies of herbicides 

did not differ significantly among the four primary aquifer 

system lithologies (table 14). The detection frequencies were 

calculated using all herbicides with health-based benchmarks 

that were detected in the SNR study unit: simazine, atrazine, 

and hexazinone (Shelton and others, 2010). Most detections of 

herbicides occurred in the southern two-thirds of the western 

side of the SNR study unit (fig. 15A).

Most of the correlations between herbicide concentrations 

and potential explanatory factors reflected the importance of 

location. Herbicide concentrations showed significant negative 

correlations with aridity index, elevation, and percentage of natural land (table 10B), which is consistent with the observation 

that most of the herbicide detections occurred in the southern 

two-thirds of the western side of the SNR study unit (fig. 15A). 

Herbicide concentrations were not significantly correlated 

with agricultural land use (table 10B); however, the detection 

frequency of herbicides in samples from wells with greater 

than 5 percent agricultural land use in the 500-m buffer around 

the well (30 percent) was significantly greater than the detection frequency in samples from wells with less than 5 percent 

agricultural land use (5.5 percent) (contingency table test, p = 

0.009). Herbicide concentrations were positively correlated 
Status and Understanding of Groundwater Quality 61

Perchlorate

Methyl tert-butyl ether

Chloroform

Simazine

Atrazine

Tetrachloroethene

1,2-Dichloroethane

Trichloroethene

cis-1,2-Dichloroethene

1,4-Dichlorobenzene

1,1-Dichloroethane

1,1-Dichloroethene

Trichlorofluoromethane

Hexazinone

1,1,1-Trichloroethane

Carbon disulfide

0.1 1 10 100

0.1

1

0.01

0.001

0.0001

0.00001

Maximum relative-concentration

Area-weighted detection frequency (percent)

Moderate

Low

Volatile organic compound

Pesticide

Special-interest constituent

Constituent class

EXPLANATION

sac14-0538_Figure 13

Figure 13. Area-weighted detection frequency and maximum relative-concentration of organic and special-interest constituents 

detected by the U.S. Geological Survey in samples collected for the Sierra Nevada Regional study unit, 2008, California Groundwater 

Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
62 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

0 10 20 30 40 50 0.0001 0.001 0.01 0.1 1

Area-weighted detection

frequency (percent)

Relative-concentration (dimensionless)

Chloroform

Tetrachloroethene (PCE)

1,2-Dichloroethane (1,2-DCA)

Simazine

Perchlorate

Methyl tert-butyl 

ether (MTBE)

Aggregated

Granitic 

Metamorphic

Sedimentary

Volcanic 

Primary aquifer system

Low Moderate

sac14-0538_Figure 14

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

EXPLANATION

Figure 14. Area-weighted detection frequencies and relative-concentrations of selected organic and special-interest constituents, 

Sierra Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Status and Understanding of Groundwater Quality 63

Table 12. Aquifer-scale proportions of organic and special-interest constituents for the granitic, metamorphic, sedimentary, volcanic, 

and aggregated primary aquifer systems, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.—Continued

[Relative-concentration (RC) categories: high, RC > 1.0; moderate, RC > 0.1 and RC ≤ 1.0; low, RC ≤ 0.1. RC defined as measured value divided by benchmark value. Organic and special-interest constituents not listed in this table either do not have benchmarks or were detected only at low RCs. Benchmark types 

and values listed in table 4A]

Constituent and primary aquifer system

Grid-based Spatially weighted

Proportion 

not detected 

(in percent)

Proportion detected (in percent) Number 

of wells

Proportion detected 

(in percent)

Low RC Moderate RC High RC Moderate RC High RC

Granitic primary aquifer system

Simazine 95.0 5.0 0 0 111 0 0

Tetrachloroethene (PCE) 97.0 2.2 0.7 0 145 0.3 0

Carbon tetrachloride 100 0 0 0 145 0 0

1,2-Dichloroethane 95.0 0 5.0 0 145 0.8 0

Methyl tert-butyl ether (MTBE) 86.6 13.4 0 0 145 0.1 0

Benzene 100 0 0 0 145 0 0

Chloroform 90.5 9.5 0 0 145 0.2 0

Perchlorate 59.4 40.6 0 0 349 0.7 0

Metamorphic primary aquifer system

Simazine 84.0 16.0 0 0 39 0 0

Tetrachloroethene (PCE) 100 0 0 0 46 0 0

Carbon tetrachloride 100 0 0 0 46 0 0

1,2-Dichloroethane 100 0 0 0 46 0 0

Methyl tert-butyl ether (MTBE) 91.1 8.9 0 0 46 0 0

Benzene 100 0 0 0 46 0.6 0

Chloroform 83.2 16.8 0 0 46 0 0

Perchlorate 73.5 24.7 1.8 0 154 1.8 0

Sedimentary primary aquifer system

Simazine 90.9 9.1 0 0 61 0 0

Tetrachloroethene (PCE) 90.7 9.3 0 0 82 0.8 0.6

Carbon tetrachloride 100 0 0 0 82 0.9 0

1,2-Dichloroethane 100 0 0 0 82 0 0.6

Methyl tert-butyl ether (MTBE) 74.6 25.4 0 0 82 0 0

Benzene 100 0 0 0 82 0 0

Chloroform 97.4 2.6 0 0 82 0 0

Perchlorate 83.8 7.1 9.1 0 185 1.6 0.1

Volcanic primary aquifer system

Simazine 100 0 0 0 37 0 0

Tetrachloroethene (PCE) 100 0 0 0 38 0 0

Carbon tetrachloride 100 0 0 0 38 0 0

1,2-Dichloroethane 100 0 0 0 38 0 0

Methyl tert-butyl ether (MTBE) 99.4 0.6 0 0 38 0 0

Benzene 100 0 0 0 38 0 0

Chloroform 85.7 14.3 0 0 38 0 0

Perchlorate 81.5 18.5 0 0 69 0 0
64 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 12. Aquifer-scale proportions of organic and special-interest constituents for the granitic, metamorphic, sedimentary, volcanic, 

and aggregated primary aquifer systems, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.—Continued

[Relative-concentration (RC) categories: high, RC > 1.0; moderate, RC > 0.1 and RC ≤ 1.0; low, RC ≤ 0.1. RC defined as measured value divided by benchmark value. Organic and special-interest constituents not listed in this table either do not have benchmarks or were detected only at low RCs. Benchmark types 

and values listed in table 4A]

Constituent and primary aquifer system

Grid-based Spatially weighted

Proportion 

not detected 

(in percent)

Proportion detected (in percent) Number 

of wells

Proportion detected 

(in percent)

Low RC Moderate RC High RC Moderate RC High RC

Aggregated lithologic primary aquifer system

Simazine 92.1 7.9 0 0 248 0 0

Tetrachloroethene (PCE) 97.9 1.7 0.4 0 311 0.2 0.03

Carbon tetrachloride 100 0 0 0 311 0.05 0

1,2-Dichloroethane 97.4 0 2.6 0 311 0.4 0.03

Methyl tert-butyl ether (MTBE) 88.8 11.2 0 0 311 0.1 0

Benzene 100 0 0 0 311 0.2 0

Chloroform 88.1 11.9 0 0 311 0.1 0

Perchlorate 67.6 31.4 1.0 0 757 1.0 0.01

with percentage of urban land use; however, the detection 

frequencies in samples from wells with greater than 10 percent 

urban land use (21 percent) and in samples from wells with less 

than 10 percent urban land use (6.0 percent) were not significantly different (contingency table test, p = 0.061). The thresholds of 5 percent agricultural land use and 10 percent urban 

land use were selected because they were empirically found to 

have explanatory power by Fram and Belitz (2012).

Solvents

Solvents were detected at high RCs in 0.1 percent of the 

aggregated primary aquifer system and at moderate RCs in 

3.0 percent (table 13). PCE and 1,2-DCA each were detected 

at high RCs in 0.03 percent of the aggregated primary aquifer 

system (table 12). PCE, 1,2-DCA, and carbon tetrachloride 

were the solvents detected at moderate RCs. The detection 

frequencies of solvents as a class were significantly greater 

in granitic and sedimentary primary aquifer systems than 

in metamorphic and volcanic systems (tables 13, 14). No 

individual solvents had detection frequencies greater than 

10 percent (figs. 13, 14). Solvent concentrations were 

significantly positively correlated with percentage of urban 

land use and negatively correlated with percentage of natural 

land use; there were no significant relations with any other 

potential explanatory factors (tables 10A,B; fig. 15B).

Gasoline Oxygenates

Gasoline oxygenates are added to gasoline to increase the 

efficiency of combustion, thereby enhancing the octane rating 

of gasoline and reducing pollutant emissions. In 1990, the Clean 

Air Act mandated the use of oxygenated gasoline in areas out 

of compliance with air-quality standards for carbon monoxide 

or ozone (Clean Air Act Amendments of 1990, 1990). Oxygenated gasoline is used throughout California, and until 2004, the 

most commonly used oxygenate was MTBE. Use of MTBE was 

phased out starting December 31, 2003, because of concerns 

over the degradation of groundwater quality caused by the leakage of MTBE from LUFTs and other point sources (California 

Air Resources Board, 2003). The only gasoline oxygenate 

detected in the SNR study unit was MTBE (tables 4A,B); three 

other gasoline oxygenates without benchmarks were analyzed, 

but not detected (Shelton and others, 2010).

MTBE was not detected at high RCs in the SNR study 

unit, but was detected at moderate RCs in 0.1 percent of 

the aggregated primary aquifer system (table 12). The areaweighted detection frequency of MTBE was 11 percent for the 

study unit as a whole (table 13; figs. 13, 14), and the areaweighted detection frequencies of MTBE in the sedimentary 

and granitic primary aquifer systems were significantly greater 

than the frequency in the volcanic system (table 14; fig. 14). 

Detections of MTBE occurred in all geographic areas of the 

SNR study unit (fig. 15C). Concentrations of MTBE showed 

significant positive correlation with percentage of urban land 

and negative correlation with percentage of natural land. No 

significant relations were observed with any other potential 

explanatory factors (tables 10A,B).

The data suggest that the MTBE detected in the 

groundwater sampled for this study could have been derived 

from the atmosphere, although contributions from LUFTs or 

other point sources cannot be ruled out. Compared to most 

other VOCs that are commonly detected in groundwater, 

MTBE has a relatively low Henry’s Law constant (Baehr 
Status and Understanding of Groundwater Quality 65

Table 13. Summary of aquifer-scale proportions for organic constituent classes for the granitic, metamorphic, sedimentary, volcanic, 

and aggregated primary aquifer systems, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.

[Relative-concentration (RC) categories for organic constituents: high, RC > 1.0; moderate, RC > 0.1 and RC ≤ 1.0; low, RC ≤ 0.5. RC defined as measured 

value divided by benchmark value]

Constituent class and 

primary aquifer system

Proportion not detected 

(in percent)

Proportion detected (in percent)

Low RC Moderate RC High RC

Pesticides

Granitic 92.8 7.2 0 0

Metamorphic 84.0 16.0 0 0

Sedimentary 90.9 9.1 0 0

Volcanic 100 0 0 0

Aggregated 90.9 9.1 0 0

Solvents

Granitic 89.3 5.0 5.7 0

Metamorphic 100 0 0 0

Sedimentary 90.7 6.5 1

1.7 11.1

Volcanic 100 0 0 0

Aggregated 93.8 3.1 3.0 1

0.1

Gas oxygenates

Granitic 86.6 13.3 1

0.1 0

Metamorphic 91.1 8.9 0 0

Sedimentary 74.6 25.4 0 0

Volcanic 99.4 0.6 0 0

Aggregated 88.8 11.1 1

0.1 0

Trihalomethanes

Granitic 91.0 8.8 1

0.2 0

Metamorphic 83.8 16.2 0 0

Sedimentary 97.8 2.2 0 0

Volcanic 72.6 27.4 0 0

Aggregated 87.0 12.9 1

0.1 0

Volatile organic compounds

Granitic 77.9 16.3 5.7 0

Metamorphic 82.0 17.4 1,20.6 0

Sedimentary 72.5 24.7 1

1.7 11.1

Volcanic 72.6 27.4 0 0

Aggregated 78.2 18.7 3.0 1

0.1

Organic constituents

Granitic 76.4 17.8 5.7 0

Metamorphic 66.0 33.4 1,20.6 0

Sedimentary 65.5 31.7 1

1.7 11.1

Volcanic 72.6 27.4 0 0

Aggregated 72.3 24.7 3.0 1

0.1

1

A spatially weighted value of aquifer-scale proportion was used because the grid-based value was zero and the spatially weighted value was non-zero.

2

Includes one detection of benzene at moderate RC.
66 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table 14. Results of contingency table tests for differences in 

aquifer-scale proportions of selected organic constituents and 

constituent classes between granitic, metamorphic, sedimentary, 

and volcanic primary aquifer systems, Sierra Nevada Regional 

(SNR) study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project.

[Significance defined as p-value less than threshold value (α) of 0.05. Aquifer

lithology class: G, granitic; M, metamorphic; S, sedimentary; V, volcanic. 

Abbreviations: ns, no significant differences; >, greater than]

Constituent class or 

individual constituent

Proportion detected compared 

to proportion not detected

p-value Significant 

differences

Chloroform 0.092 ns

Methyl tert-butyl ether 0.007 G > V, S > V

Solvents 0.034 G > M, G > V

S > M, S > V

Any volatile organic compound 0.129 ns

Herbicides 0.073 ns

Any organic constituent 0.020 M > V, S > V

Perchlorate 0.260 ns

and others, 1999). The Henry’s Law constant quantifies the 

partitioning of a compound between air and water; the lower 

its value, the more the compound is partitioned into water. 

Studies of shallow groundwater during the 1990s concluded 

that the concentrations of MTBE measured in groundwater 

were similar to the concentrations that were expected to have 

resulted from Henry’s Law partitioning of MTBE between 

urban air and falling precipitation (Squillace and others, 1996, 

1997; Baehr and others, 1999; Belitz and others, 2004).

During the period that MTBE was used as a gasoline 

oxygenate (1992–2003), maximum annual average MTBE 

concentrations in the air of Central Valley cities monitored 

by the California Air Resources Board ranged from 2.8 

to 5.2 parts per billion by volume (ppbv) (California Air 

Resources Board, 2004). Prevailing weather patterns move 

air from the Central Valley to the Sierra Nevada, and local 

use of oxygenated gasoline in the Sierra Nevada would also 

have contributed MTBE to the atmosphere. The Henry’s 

Law constant for MTBE is temperature dependent, increasing from about 0.062 atmosphere-liters per mol (atm-L/

mol) at 0 degrees Celsius (°C) to about 0.425 (atm-L/mol) 

at 20 °C (Robbins and others, 1993; Squillace and others, 

1996). This range of Henry’s Law constant predicts that air 

containing 2.8 to 5.2 ppbv of MTBE would be in equilibrium 

with raindrops containing approximately 0.6 to 7 μg/L of 

MTBE. The maximum concentration of MTBE measured 

in USGS-GAMA samples from the SNR study unit was 

0.8 μg/L (Shelton and others, 2010). If the samples having 

MTBE detections contained a large proportion of groundwater 

recharged during the period when MTBE was added to 

California gasoline, then the source of the MTBE could have 

been atmospheric deposition, rather than LUFTs or other point 

sources.

The lack of statistically significant correlation between 

MTBE concentration and groundwater age (table 10A) likely 

reflects the predominance of modern groundwater in the SNR 

study unit. Of the 42 USGS-GAMA SNR study unit samples 

classified as modern groundwater, 7 had detections of MTBE. 

Two of the 31 mixed-age groundwater samples had detections 

of MTBE, and none of the 7 pre-modern groundwater samples 

had detections of MTBE. Samples classified as modern and 

as mixed both contain modern groundwater and therefore 

could have been exposed to sources of MTBE. However, the 

detection frequencies of MTBE in groundwater classified as 

pre-modern (0 percent) and groundwater classified as modern 

or mixed (13 percent) were not significantly different (contingency table test, p = 0.33) perhaps because of the small 

number of samples classified as pre-modern groundwater.

Trihalomethanes

Water used for drinking water and other household uses 

in domestic and public (municipal and community) systems 

may be disinfected by using chlorine in a variety of chemical 

forms (such as sodium hypochlorite [bleach], hypochlorous 

acid, chlorine gas, chloramines, or chlorine dioxide). In 

addition to disinfecting the water, the chlorine compounds 

react with organic matter to produce trihalomethanes and other 

chlorinated and (or) brominated disinfection byproducts (for 

example, Ivahnenko and Barbash, 2004). Chloroform was the 

only trihalomethane detected in the SNR study unit (Shelton 

and others, 2010). The area-weighted detection frequency 

of chloroform in the aggregated primary aquifer system was 

12 percent, and chloroform was detected at moderate RCs 

in 0.1 percent of the system (tables 12, 13). Chloroform was 

the most frequently detected VOC in groundwater across the 

United States (Zogorski and others, 2006).

The detection frequencies for chloroform were calculated by using 73 of the lithologic-grid wells because 

chloroform detections in the other 9 wells may have been 

the result of contamination from well-head chlorination 

systems. Of the 16 sites with well-head chlorination systems, 9 had chloroform detections even though chlorinated 

water was not used for irrigation near any of the sites. For 

six of the nine sites, chloroform was the only organic constituent detected, and for two sites, chloroform and MTBE 

were the only organic constituents detected. The well-head 

chlorination systems generally were located within a few feet 

of the well head, and in most cases, were downstream of the 

point where the samples were collected. Some backflow of 

chlorinated water was possible. The presence of chloroform 

in wells sampled for this study could also have been a consequence of intentional introduction of chlorine solutions 

into wells. Shock chlorination (often carried out by pouring 

bleach down a well) is a recommended procedure for treating 
Status and Understanding of Groundwater Quality 67

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 15a

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Pacific Ocean

A

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Maximum relative-concentration of herbicides

< 0.1 (Low) 

Not detected 

< 0.1 (Low) 

Not detected 

Not detected 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

Sierra Nevada Regional

 study unit grid cell 

17

Water body

USGS RL CDPH RL

Simazine 4 MCL-US

Atrazine 1 MCL-CA

Hexazinone 400 HAL-US

Prometon 100

0.005

0.003

0.004

0.005

1

0.5

na

HAL-US 0.05

Herbicides detected in USGS-GAMA study units,

concentrations in micrograms per liter

Herbicide Benchmark

Figure 15. Maximum relative-concentrations of (A) herbicides, (B) solvents, (C) the gasoline oxygenate methyl tert-butyl ether (MTBE), 

(D) the trihalomethane chloroform, and (E) perchlorate for USGS-GAMA wells, and all wells in the California Department of Public 

Health (CDPH) database with data during the period May 2006 through October 2008, Sierra Nevada Regional study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project. [Abbreviations: HAL-US, U.S. Environmental 

Protection Agency (USEPA) lifetime health advisory level; MCL-CA, CDPH maximum contaminiant level; MCL-US, USEPA maximum 

contaminant level; na, not available; RL, reporting level; μg/L, micrograms per liter]
68 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 15b

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Pacific Ocean

B

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Maximum relative-concentration of solvents

< 0.1 (Low) 

Not detected 

< 0.1 (Low) 

Not detected 

> 1 (High) 

> 0.1 and < 1 (Moderate) 

Not detected 

> 0.1 and < 1 (Moderate) 

> 1 (High) 

> 0.1 and < 1 (Moderate) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

Sierra Nevada Regional

 study unit grid cell 

17

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

USGS

RL

CDPH

RL

Tetrachloroethene (PCE) 5 MCL-US

MCL-US

MCL-US

1,1-Dichloroethane 5 MCL-CA

MCL-CA

MCL-CA

MCL-CA

1,2-Dichloroethane

1,1,1-Trichloroethane

Trichloroethene (TCE)

Tetrachloromethane

0.5

cis-1,2-Dichloroethene 6

200

5

0.5

0.02

0.02

0.03

0.03

0.01

0.01

0.01

0.5

0.5

0.5

0.5

0.5

0.5

0.5

Solvents detected in USGS-GAMA study units,

concentrations in micrograms per liter

Solvent Benchmark

Figure 15. —Continued
Status and Understanding of Groundwater Quality 69

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 15c

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Pacific Ocean

C

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Concentration of methyl tert-butyl ether (MTBE),

in micrograms per liter

> 0.05 and < 1.3 (Low) 

Not detected (< 0.05) 

> 0.05 and < 1.3 (Low) 

Not detected (< 0.05) 

Not detected (< 3) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

Sierra Nevada Regional

 study unit grid cell 

17

> 3 and < 13 (Moderate) 

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 15. —Continued
70 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 15d

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Pacific Ocean

D

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Concentration of chloroform,

in micrograms per liter

> 0.02 and < 8 (Low) 

Not detected (< 0.02) 

> 0.02 and < 8 (Low) 

Not detected (< 0.02) 

Not detected (< 0.5) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

Sierra Nevada Regional

 study unit grid cell 

17

> 8 and < 80 (Moderate) 

> 0.5 and < 8 (Low) 

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 15. —Continued
Status and Understanding of Groundwater Quality 71

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

26

26

24

24

sac14-0538_Figure 15e

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

Urban

Agricultural

Natural (forest)

Natural (grass, shrub, rock)

Land use

Pacific Ocean

E

EXPLANATION

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit

Concentration of perchlorate,

in micrograms per liter

> 0.1 and < 0.6 (Low) 

Not detected (< 0.1) 

Not detected (< 0.5) 

Not detected (< 4) 

> 0.6 and < 6 (Moderate) 

USGS-GAMA Tahoe-Martis, Central

 Sierra, Southern Sierra

 study units (Fram and Belitz, 2012)

California Department of

 Public Health wells

> 0.6 and < 6 (Moderate) 

Sierra Nevada Regional

 study unit grid cell 

17

> 4 and < 6 (Moderate) 

> 6 (High) 

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Water body

Figure 15. —Continued
72 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

bacterial contamination and odor problems in domestic 

drinking-water supply wells (Centers for Disease Control and 

Prevention, 2006) and could result in formation of a reservoir 

of chlorinated water in the well bore and surrounding aquifer 

material. Small public systems, such as those for schools, 

campgrounds, restaurants, and community associations, could 

be more likely to maintain their wells following guidelines 

for domestic wells than guidelines for larger systems, such as 

those for municipalities. Of the 18 samples with detections 

of chloroform, 12 were from wells in schools, camps, meeting halls, and other types of systems serving between 30 and 

220 people.

The area-weighted frequencies of chloroform detection did not differ significantly among the four aquifer 

lithologies (table 14; fig. 14). Detections of chloroform were 

distributed across the SNR study unit (fig. 15D). Chloroform 

concentrations showed significant positive correlations with 

the percentage of urban land use and the density of septic 

tanks, and there were no significant relations with any other 

potential explanatory factors (tables 10A,B). The correlations 

with the percentage of urban land and the density of septic 

tanks are likely to be consequences of the use of chlorination 

to disinfect water, as well as the widespread use of bleach for 

domestic purposes (such as laundry and cleaning).

Perchlorate

Perchlorate is an inorganic anion that is highly soluble in 

water. It was classified as a special-interest constituent because 

at the inception of the GAMA Priority Basin Project in 2003, 

perchlorate had recently been detected in public-supply wells 

in several areas of the State and the CDPH was evaluating 

whether or not an MCL-CA should be established. The MCLCA of 6 μg/L was established in 2007. Perchlorate has natural 

and anthropogenic sources to groundwater. It forms naturally 

in the atmosphere and is present at very low concentrations in 

precipitation (Dasgupta and others, 2005; Parker and others, 

2009; Rajagopalan and others, 2009). Naturally deposited 

perchlorate salts in the soils and unsaturated zones of aquifers 

in areas with arid to semi-arid climates can be re-solubilized 

and carried into deeper groundwater by recharge of applied 

irrigation water (Rao and others, 2007; Fram and Belitz, 

2011a). Perchlorate is a component of solid rocket fuel and is 

used in explosives, fireworks, safety flares, and other products 

(U.S. Environmental Protection Agency, 2005; Dasgupta 

and others, 2006). It also may be present in some fertilizers 

(Dasgupta and others, 2006; Böhlke and others, 2009) and can 

form in the chlorine solutions used for drinking-water disinfection (Massachusetts Department of Environmental Protection, 2006; Greiner and others, 2008).

Less than 0.1 percent of the aggregated primary aquifer 

system had high RCs of perchlorate, and about 1.0 percent 

had moderate RCs (table 11). The area-weighted detection 

frequency for perchlorate in the primary aquifer system 

was 32 percent, and there were no significant differences 

in detection frequencies among the four aquifer lithologies 

(table 14; fig. 14). Nearly all detections of perchlorate 

occurred along the western margin of the study unit, and most 

were in the southern two-thirds of the study unit (fig. 15E). As 

expected from this spatial pattern of detections, concentrations 

of perchlorate showed significant negative correlations 

with aridity index, elevation, latitude, and percentage of 

natural land and positive correlation with septic tank density 

(table 10B).

Perchlorate occurrence frequencies were consistent 

with those expected from the distribution of perchlorate in 

groundwater under natural conditions (Fram and Belitz, 

2011a). The occurrence frequencies of perchlorate at concentrations greater than threshold concentrations of 0.1, 0.5, 

and 1.0 μg/L were compared to the predicted probability of 

perchlorate occurring under natural conditions as a function of 

aridity index (Fram and Belitz, 2011a). The 83 USGS-GAMA 

wells were divided into 4 groups of 20 or 21 samples by aridity index. The average aridity index and the observed occurrence frequencies of perchlorate at concentrations greater 

than 0.1, 0.5, and 1.0 μg/L were calculated for each group. 

The average aridity indices corresponded to climates ranging 

from semi-arid (0.32) to wet (1.38). The observed detection 

frequencies were compared to the predicted probabilities of 

perchlorate occurring under natural conditions at those aridity 

indices (Fram and Belitz, 2011a). The observed occurrence 

frequencies were close to the predicted probabilities (fig. 16), 

indicating that the occurrence of perchlorate over this wide 

range of climate conditions in the SNR study unit can be 

accounted for by natural processes. Anthropogenic sources of 

perchlorate are not required to explain the occurrence pattern 

of perchlorate, although contribution from anthropogenic 

sources cannot be ruled out.
Status and Understanding of Groundwater Quality 73

60

50

40

30

20

10

0

0 10 20 30 40 50 60

Predicted probability of detecting perchlorate

at concentrations greater than threshold concentration

under natural conditions, in percent

Observed detection frequency of perchlorate at concentrations

greater than threshold concentration, in percent

Threshold perchlorate

concentration, in

micrograms per liter

Average

aridity index 

0.32

0.1 0.5 1.0

0.65

0.88

1.38

x-error bars are predicted probabilities for plus/minus one standard

deviation of average aridity index.

y-error bars are the 90% confidence

interval for observed frequencies.

1:1 correlation line

sac14-0538_Figure 16 Figure 16. Predicted probability of detecting perchlorate at concentrations above three threshold concentrations in groundwater 

under natural conditions at four aridity indices to observed detection frequencies of perchlorate at concentrations above the four 

threshold concentrations and average aridity indices for sets of 21 or 20 groundwater samples, Sierra Nevada Regional study unit, 2008, 

California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
74 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Summary

Groundwater quality in the Sierra Nevada Regional 

(SNR) study unit was investigated as part of the California 

State Water Resources Control Board’s Groundwater Ambient 

Monitoring and Assessment (GAMA) Program Priority Basin 

Project. The SNR study unit covers an area of approximately 

25,000 square miles (mi2

) (66,000 square kilometers [km2]) 

and includes all or parts of 20 California counties: Lassen, 

Plumas, Butte, Sierra, Yuba, Nevada, Placer, El Dorado, 

Sacramento, Amador, Alpine, Calaveras, Tuolumne, Mono, 

Mariposa, Madera, Fresno, Inyo, Tulare, and Kern Counties.

The GAMA Priority Basin Project is designed to provide 

a statistically unbiased assessment of untreated groundwater 

quality in the primary aquifer system that is used for public 

drinking-water supplies statewide. The primary aquifer system 

is defined by the range of depths of the screened or open 

intervals of wells listed in the State of California’s database 

of wells used for public drinking-water supply. Two types of 

assessments were made for the SNR study unit: (1) a status 

assessment yielding quantitative estimates of the current 

status of groundwater quality in the primary aquifer system 

and (2) an evaluation of relations between water quality and 

potential explanatory factors describing land use, geography, 

depth, geochemical conditions, groundwater age, and other 

characteristics of the primary aquifer system.

The assessments were based on data collected by the 

USGS for the GAMA Priority Basin Project (USGS-GAMA) 

and data compiled in the State’s database. (The California 

Department of Public Health [CDPH] Drinking Water Program was transferred to the SWRCB Division of Drinking 

Water on July 1, 2014; however, the label “CDPH” is retained 

in this report for consistency with other GAMA Priority Basin 

Project publications and because the CDPH had jurisdiction 

over public-supply wells at the time that samples were collected for this study.) Water-quality and ancillary data were 

collected by USGS-GAMA from 83 wells in the SNR study 

unit during 2008. The organizing feature for examining these 

data was aquifer lithology. Drinking-water supply wells in 

the SNR study unit are located in fractured hard-rock aquifers 

and alluvial basins. The fractured hard-rock aquifers were 

classified as granitic, metamorphic, or volcanic rocks, and the 

alluvial basins and other accumulations of sediment were classified as sedimentary deposits. The study unit was divided into 

30 equal-area grid cells, and in each cell, 1 well was randomly 

selected from each of the 4 aquifer lithologies that contained 

wells. USGS-GAMA sampled wells in 82 of the 91 possible 

lithologic-grid sub-cells. Samples from the 82 USGS-grid 

wells and 1 additional well were analyzed for organic constituents (volatile organic compounds and pesticides), inorganic 

constituents (major ions, trace elements, and radioactive 

constituents), special-interest constituents (perchlorate and 

N-nitrosodimethylamine [NDMA]) and geochemical and agedating tracers. Additional water-quality data were obtained 

from 117 wells sampled by USGS-GAMA in 2006–07 for 

3 small study units inside the SNR study unit and from 

1,066 wells in the CDPH database having data for samples 

collected between May 1, 2006, and October 31, 2008.

Relative-concentrations (defined as sample concentration 

divided by benchmark concentration for the constituent) were 

used for evaluating groundwater quality for those constituents 

having Federal and (or) California regulatory or nonregulatory benchmarks for drinking-water quality. A relativeconcentration (RC) of > 1.0 indicates a concentration above a 

benchmark. Organic and special-interest constituent RCs were 

classified as “high” (RC > 1.0), “moderate” (1.0 ≥ RC > 0.1), 

or “low” (RC ≤ 0.1). For inorganic constituents, the boundary 

between low and moderate RCs was set at 0.5.

Aquifer-scale proportion was used as the primary 

metric in the status assessment for evaluating regional-scale 

groundwater quality. High-RC aquifer-scale proportion is 

defined as the areal percentage of the primary aquifer system 

having RC > 1.0 for a particular constituent or class of constituents; moderate-RC and low-RC aquifer-scale proportions 

were defined as the areal percentages of the primary aquifer 

system with moderate and low RCs, respectively. Aquiferscale proportions were calculated on an area-weighted basis 

for the primary aquifer systems, corresponding to the four 

aquifer lithologies (granitic rocks, metamorphic rocks, 

sedimentary deposits, and volcanic rocks), and the aggregated 

system, corresponding to the study unit as a whole. Both gridbased, which used one value per grid cell per lithology, and 

spatially weighted, which used multiple values per cell per 

lithology, approaches were used.

The status assessment showed that inorganic constituents 

had greater high-RC and moderate-RC aquifer-scale proportions than did organic constituents and that there were 

significant differences in aquifer-scale proportions for many 

constituents between the four aquifer lithologies. In the SNR 

study unit as a whole, one or more inorganic constituents with 

health-based benchmarks had high RCs in 16 percent of the 

primary aquifer system and moderate RCs in 21 percent. As 

classes, trace elements, radioactive constituents, and nutrients were present at high RCs in 11 percent, 8.2 percent, and 

1.4 percent of the aggregated primary aquifer system, respectively. The proportions of the granitic and sedimentary systems 

having high or moderate RCs of any inorganic constituent 

with health-based benchmarks were significantly greater than 

the proportions of the metamorphic system.

Among inorganic constituents with health-based benchmarks, arsenic had the greatest high-RC (9.7 percent) and 

moderate-RC (10 percent) aquifer-scale proportions in the 

study unit as a whole. The high-RC aquifer-scale proportion 

for arsenic in the volcanic primary aquifer system was 

significantly greater than in the other three systems. Boron 

was present at high RCs in 2.0 percent and at moderate RCs 

in 2.2 percent of the aggregated primary aquifer system. 

Fluoride was present at high RCs in 1.8 percent and moderate RCs in 0.5 percent of the aggregated primary aquifer 

system, and the sedimentary primary aquifer system had a 

greater combined high and moderate aquifer-scale proportion 
References 75

than the other systems. Nitrate was present at high RCs in 

1.4 percent and moderate RCs in 3.1 percent of the aggregated 

primary aquifer system, and the granitic and sedimentary 

systems had significantly greater combined high and moderate 

aquifer-scale proportions than the metamorphic and volcanic 

systems (2.3 percent and 1.7 percent, respectively). Uranium 

was present at high RCs in 2.9 percent and moderate RCs in 

7.7 percent of the aggregated primary aquifer system.

For inorganic constituents with aesthetic-based benchmarks (secondary maximum contaminant levels, SMCLs), 

18 percent of the aggregated primary aquifer system had 

high RCs of one or more constituents, and 6.8 percent had 

moderate RCs. Trace elements (primarily iron and manganese) 

and salinity indicators with SMCL benchmarks were present 

at high RCs in 18 percent and 1.3 percent of the aggregated 

primary aquifer system, respectively. The metamorphic 

primary aquifer system had significantly greater combined 

high and moderate aquifer-scale proportions of manganese and 

iron than the other systems.

One or more organic constituents with health-based 

benchmarks had high RCs in 0.1 percent of the aggregated 

primary aquifer system, moderate RCs in 3.0 percent, and low 

RCs in 23 percent. Organic constituents were not detected 

in 74 percent of the aggregated primary aquifer system. The 

metamorphic and sedimentary systems had significantly greater 

frequencies of occurrence of organic constituents than the 

granitic and volcanic systems. Solvents were present at high 

RCs in 0.1 percent of the aggregated primary aquifer system 

and at moderate RCs in 3.0 percent. Chloroform and gasoline 

oxygenates (methyl tert-butyl ether, MTBE) were not detected 

at high RCs, and each was present at moderate RCs in 0.1 percent of the aggregated primary aquifer system. Pesticides were 

not detected at high or moderate RCs. Three organic constituents (MTBE, chloroform, and simazine) had area-weighted 

detection frequencies greater than 10 percent in the aggregated 

primary aquifer system or at least one of the four lithologic primary aquifer systems. The special-interest constituent perchlorate was detected at high RCs in 0.01 percent of the aggregated 

primary aquifer system and at moderate RCs in 1.0 percent.

Statistical tests were used to evaluate relations between 

concentrations of constituents and potential explanatory 

factors descriptive of land use, geography, depth, geochemical conditions, and groundwater age. For inorganic 

constituents, the potential explanatory factors most commonly having significant relations were factors describing 

geochemical conditions and geographic location. Higher 

concentrations of trace elements, radioactive constituents, 

and constituents with SMCL benchmarks generally were 

associated with anoxic conditions, higher pH, and location 

within a particular compositional band in the Sierra Nevada 

batholith corresponding to the southwestern part of the study 

unit. Patterns of significant relations were somewhat different 

from those obtained previously for the three study units contained within the SNR study unit, largely because of differences in characteristics of sites with granitic aquifer lithology. 

For organic constituents, higher concentrations of organic 

constituents generally were associated with greater percentage 

of urban land use. The high proportions of springs and modern 

groundwater in the dataset likely account for the absence of 

significant relations between concentrations of organic constituents and measures of well depth or groundwater age.

Acknowledgments

The authors thank the following cooperators for their 

support: the State Water Resources Control Board (SWRCB), 

Lawrence Livermore National Laboratory, California 

Department of Public Health, and California Department of 

Water Resources. We especially thank the cooperating well 

owners and water purveyors for their generosity in allowing 

the 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.

References 

Ague, J.J., and Brimhall, G.H., 1987, Granites of the 

batholiths of California—Products of local assimilation 

and regional-scale crustal contamination: Geology, v. 15, 

p. 63–66, accessed November 2012 at http://dx.doi.

org/10.1130/0091-7613(1987)15<63:GOTBOC>2.0.CO;2.

Ague, J.J., and Brimhall, G.H., 1988, Regional variations in bulk 

chemistry, mineralogy, and the compositions of mafic and 

accessory minerals in the batholiths of California: Geological 

Society of America Bulletin, v. 100, no. 6, p. 891–911, 

accessed November 2012 at http://dx.doi.org/10.1130/0016-

7606(1988)100<0891:RVIBCM>2.3.CO;2.

Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E., 

1976, A land use and land cover classification system 

for use with remote sensor data: U.S. Geological Survey 

Professional Paper 964, 28 p. (Also available at http://pubs.

er.usgs.gov/publication/pp964.)

Appelo, C.A.J., and Postma, D., 2005, Geochemistry, 

groundwater, and pollution (2d ed.): Leiden, Germany, A.A. 

Balkema Publishers, 649 p.

Arndt, M.F., 2010, Evaluation of gross alpha and uranium 

measurements for MCL compliance: Water Research 

Foundation, 299 p., accessed November 2012 at http://

www.waterrf.org/PublicReportLibrary/3028.pdf. 

Baehr, A.L., Stackelberg, P.E., and Baker, R.J., 1999, 

Evaluation of the atmosphere as a source of volatile organic 

compounds in shallow groundwater: Water Resources 

Research, v. 35, no. 1, p. 127–136, accessed November 2012 

at http://dx.doi.org/10.1029/1998WR900030.
76 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Belitz, Kenneth, Dubrovsky, N.M., Burow, Karen, Jurgens, 

Bryant, and Johnson, Tyler, 2003, Framework for a 

ground-water quality monitoring and assessment program 

for California: U.S. Geological Survey Water-Resources 

Investigations Report 03–4166, 78 p. (Also available at 

http://pubs.usgs.gov/wri/wri034166/.)

Belitz, Kenneth, Hamlin, S.N., Burton, C.A., Kent, Robert, 

Fay, R.G., and Johnson, Tyler, 2004, Water quality in the 

Santa Ana Basin, California, 1999–2001: U.S. Geological 

Survey Circular 1238, 37 p. (Also available at http://pubs.

usgs.gov/circ/2004/1238/.)

Belitz, Kenneth, Jurgens, Bryant, Landon, M.K., Fram, M.S., 

and Johnson, Tyler, 2010, Estimation of aquifer scale 

proportion using equal area grids—Assessment of regional 

scale groundwater quality: Water Resources Research, v. 46, 

no. 11, accessed November 2012 at http://onlinelibrary.

wiley.com/doi/10.1029/2010WR009321/abstract. 

Birkeland, P.W., 1964, Pleistocene glaciation of the northern 

Sierra Nevada, north of Lake Tahoe, California: Journal of 

Geology, v. 72, no. 6, p. 810–825.

Böhlke, J.K., Hatzinger, P.B., Sturchio, N.C., Gu, Baohua, 

Abbene, Irene, and Mroczkowski, S.J., 2009, Atacama 

perchlorate as an agricultural contaminant in groundwater—

Isotopic and chronologic evidence from Long Island, New 

York: Environmental Science & Technology, v. 43, no. 15, 

p. 5619–5625, accessed November 2012 at http://dx.doi.

org/10.1021/es9006433.

Böhlke, J.K., and Kistler, R.W., 1986, Rb-Sr, K-Ar, and 

stable isotope evidence for the ages and sources of 

fluid components of gold-bearing quartz veins in the 

northern Sierra Nevada foothills metamorphic belt, 

California: Economic Geology, v. 81, no. 2, p. 296–322, 

accessed November 2012 at http://dx.doi.org/10.2113/

gsecongeo.81.2.296.

Borchers, J.W., 1996, Ground-water resources and 

water-supply alternatives in the Wawona area of Yosemite 

National Park, California: U.S. Geological Survey WaterResources Investigations Report 95–4229, 77 p. (Also 

available at http://pubs.er.usgs.gov/publication/wri954229.)

Burow, K.R., Shelton, J.L., and Dubrovsky, N.M., 2008, 

Regional nitrate and pesticide trends in ground water 

in the eastern San Joaquin Valley, California: Journal 

of Environmental Quality, v. 37, no. 5, p. S-249–S-263, 

accessed November 2012, at http://dx.doi.org/10.2134/

jeq2007.0061.

Burton, C.A., Shelton, J.L., and Belitz, Kenneth, 2012, Status 

and understanding of groundwater quality in the two 

southern San Joaquin Valley study units, 2005–2006—

California GAMA Priority Basin Project: U.S. Geological 

Survey Scientific Investigations Report 2011–5218, 106 p. 

(Also available at http://pubs.usgs.gov/sir/2011/5218/.)

California Air Resources Board, 2003, California Code of 

Regulations, Title 13, Division 3 Air Resources Board, 

Chapter 5, Standards for motor vehicle fuels, Article 1, 

Standards for gasoline, §2262.6 Prohibition of MTBE and 

oxygenates other than ethanol in California gasoline starting 

December 31, 2003.

California Air Resources Board, 2004, Monitoring sites with 

ambient toxics summaries—Methyl tertiary-butyl ether, 

accessed October 1, 2012, at http://www.arb.ca.gov/adam/

toxics/sitelists/mtbesites.html.

California Department of Public Health, 2010, Drinking water 

notification levels and response levels—An overview: 

California Department of Public Health Drinking Water 

Program, accessed March 2013 at http://www.cdph.ca.gov/

certlic/drinkingwater/Documents/Notificationlevels/

notificationlevels.pdf.

California Department of Public Health, 2012, Indoor radon 

program, accessed March 2013 at http://www.cdph.ca.gov/

HealthInfo/environhealth/Pages/Radon.aspx.

California Department of Public Health, 2013a, California 

Code of Regulations, Title 22, Division 4, Environmental 

Health, Chapter 15, Domestic water quality and monitoring 

regulations, Article 1, Definitions, accessed December 2013 

at http://www.cdph.ca.gov/certlic/drinkingwater/Pages/

Lawbook.aspx.

California Department of Public Health, 2013b, California 

Code of Regulations, Title 22, Division 4, Environmental 

Health, Chapter 15, Domestic water quality and monitoring 

regulations, Article 4, Primary standards—Inorganic 

chemicals, §64431 Maximum contaminant levels—

inorganic chemicals; Article 5 Radioactivity, §64442 MCLs 

and monitoring—gross alpha particle activity, radium-226, 

radium-228, and uranium; Article 5.5 Primary standards—

organic chemicals, §64444 Maximum contaminant levels—

organic chemicals; and Article 16 Secondary drinking water 

standards, §64449 Secondary maximum contaminant levels 

and compliance, accessed December 2013 at http://www.

cdph.ca.gov/certlic/drinkingwater/Pages/Lawbook.aspx.

California Department of Public Health, 2013c, California 

Code of Regulations, Title 22, Division 4, Environmental 

Health, Chapter 15, Domestic water quality and monitoring 

regulations, Article 4, Primary standards—Inorganic 

chemicals, §64432 Monitoring and compliance—inorganic 

chemicals, accessed December 2013 at http://www.

waterboards.ca.gov/drinking_water/certlic/drinkingwater/

documents/lawbook/dwregulations-2014-07-01.pdf.

California Department of Public Health, 2014, Chemicals 

and contaminants in drinking water, accessed July 2014 

at http://www.cdph.ca.gov/certlic/drinkingwater/Pages/

Chemicalcontaminants.aspx.
References 77

California Department of Water Resources, 1990, Natural 

radioactivity in groundwater of the western Sierra Nevada: 

California Department of Water Resources San Joaquin 

District Report, 21 p.

California Department of Water Resources, 2003, California’s 

groundwater: California Department of Water Resources 

Bulletin 118, 246 p., accessed July 9, 2014, at http://www.

water.ca.gov/pubs/groundwater/bulletin_118/california's_

groundwater__bulletin_118_-_update_2003_/bulletin118_

entire.pdf.

California Irrigation Management Information System, 2005, 

CIMIS Reference Evapotranspiration Zones, accessed 

April 16, 2009, at http://wwwcimis.water.ca.gov/App_

Themes/images/etozonemap.jpg.

California State Water Resources Control Board, 2003, A 

comprehensive groundwater quality monitoring program for 

California: Assembly Bill 99, Report to the Governor and 

Legislature, March 2003, 100 p., accessed November 2012 

at http://www.waterboards.ca.gov/water_issues/programs/

gama/docs/final_ab_599_rpt_to_legis_7_31_03.pdf.

California State Water Resources Control Board, 2007, 

GeoTracker—Cleanup sites download, accessed 

November 2007 at http://geotracker.waterboards.ca.gov/

data_download.asp.

Carle, D., 2004, Introduction to water in California: Berkeley, 

Calif., University of California Press, 261 p.

Centers for Disease Control and Prevention, 2006, 

Chapter 8—Rural water supplies and water-quality issues, 

in Health Housing Reference Manual, accessed July 9, 

2014, at http://www.cdc.gov/nceh/publications/books/

housing/housing_ref_manual_2012.pdf.

Chapelle, F.H., 2001, Ground-water microbiology and 

geochemistry (2d ed.): New York, John Wiley and Sons, 

Inc., 477 p.

Chapelle, F.H., McMahon, P.B., Dubrovsky, N.M., Fujii, 

R.F., Oaksford, E.T., and Vroblesky, D.A., 1995, Deducing 

the distribution of terminal electron-accepting processes 

in hydrologically diverse groundwater systems: Water 

Resources Research, v. 31, no. 2, p. 359–371, accessed 

November 2012 at http://dx.doi.org/10.1029/94WR02525.

Christiansen, R.L., Yeats, R.S., Graham, S.A., Niem, W.A., 

Niem, A.R., and Snavely, P.D. Jr., 1992, Post-Laramie 

geology of the U.S. Cordilleran region, in Burchfiel, B.C., 

Lipman, P.W., and Zoback, M.L.C., eds., The Cordilleran 

Orogen, conterminous U.S., The Geology of North America, 

Geological Society of America, v. G-3, p. 169–406.

Clark, I.D., and Fritz, Peter, 1997, Environmental isotopes in 

hydrogeology: New York, CRC Press, 328 p.

Clean Air Act Amendments of 1990, 1990, U.S. Code, Title 42 

(Public Health and Welfare), Chapter 85 (Air pollution 

prevention and control), accessed December 2012 at http://

uscode.house.gov/view.xhtml?path=/prelim@title42/

chapter85&edition=prelim.

Cook, P.G., and Böhlke, J.K., 2000, Determining timescales 

for groundwater flow and solute transport, in Cook, 

P.G., and Herczeg, A.L., eds., Environmental tracers 

in subsurface hydrology: Boston, Kluwer Academic 

Publishers, p. 1–30.

Craig, Harmon, and Lal, Devendra, 1961, The production 

rate of natural tritium: Tellus, v. 13, p. 85–105, accessed 

July 9, 2014, at http://dx.doi.org/10.1111/j.2153-3490.1961.

tb00068.x.

Crowley, B.E., Koch, P.L., and Davis, E.B., 2008, Stable 

isotope constraints on the elevation history of the Sierra 

Nevada Mountains, California: Geological Society of 

America Bulletin, v. 120, no. 5–6, p. 588–598, accessed 

November 2012 at http://dx.doi.org/10.1130/B26254.1.

Dasgupta, P.K., Dyke, J.V., Kirk, A.B., and Jackson, W.A., 

2006, Perchlorate in the United States—Analysis of relative 

source contributions to the food chain: Environmental 

Science & Technology, v. 40, p. 6608–6614, accessed 

November 2012 at http://dx.doi.org/10.1021/es061321z.

Dasgupta, P.K., Martinelango, P.K., Jackson, W.A., Anderson, 

T.A., Tian, Kang, Tock, R.W., and Rajagopalan, Srinath, 

2005, The origin of naturally occurring perchlorate—The 

role of atmospheric processes: Environmental Science 

& Technology, v. 39, no. 6, p. 1569–1575, accessed 

November 2012 at http://dx.doi.org/10.1021/es048612x.

Day, H.W., Moores, E.M., and Tuminas, A.C., 1985, Structure 

and tectonics of the northern Sierra Nevada: Geological 

Society of America Bulletin, v. 96, no. 4, p. 436–450, 

accessed November 2012 at http://dx.doi.org/10.1130/0016-

7606(1985)96<436:SATOTN>2.0.CO;2.

Duane, T.P., 1996, Human settlement, 1850–2040, in Sierra 

Nevada Ecosystem Project—Final report to Congress, 

vol. II, Assessments and scientific basis for management 

options: Davis, University of California, Centers for Water 

and Wildland Resources, chap. 11, p. 235–360.

Dubrovsky, N.M., Burow, K.R., Clark, G.M., Gronberg, J.M., 

Hamilton P.A., Hitt, K.J., Mueller, D.K., Munn, M.D., 

Nolan, B.T., Puckett, L.J., Rupert, M.G., Short, T.M., Spahr, 

N.E., Sprague, L.A., and Wilber, W.G., 2010, The quality 

of our Nation’s waters—Nutrients in the Nation’s streams 

and groundwater, 1992–2004: U.S. Geological Survey 

Circular 1350, 174 p. (Also available at http://pubs.usgs.

gov/circ/1350/.)
78 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Evernden, J.F., and Kistler, R.W., 1970, Chronology and 

emplacement of Mesozoic batholithic complexes in 

California and western Nevada: U.S. Geological Survey 

Professional Paper 623, 42 p. (Also available at http://pubs.

er.usgs.gov/publication/pp623.)

Flint, L.E., and Flint, A.L., 2007, Regional analysis of groundwater recharge: U.S. Geological Survey Professional 

Paper 1703-B, p. 29–60. (Also available at http://pubs.usgs.

gov/pp/pp1703/b/.)

Focazio, M.J., Szabo, Zoltan, Kraemer, T.F., Mullin, A.H., 

Barringer, T.H., and dePaul, V.T., 2001, Occurrence of 

selected radionuclides in ground water used for drinking 

water in the United States—A reconnaissance survey, 1998: 

U.S. Geological Survey Water-Resources Investigations 

Report 2000–4273, 39 p. (Also available at http://pubs.usgs.

gov/wri/wri004273/.)

Focazio, M.J., Welch, A.H., Watkins, S.A., Helsel, D.R., 

and Horn, M.A., 2000, A retrospective analysis on the 

occurrence of arsenic in ground-water resources of the 

United States and limitations in drinking-water-supply 

characterizations: U.S. Geological Survey Water-Resources 

Investigations Report 99–4279, 21 p. (Also available at 

http://pubs.usgs.gov/wri/wri994279/.)

Fontes, J.-C., and Garnier, J.-M., 1979, Determination of 

the initial 14C activity of the total dissolved carbon—A 

review of the existing models and a new approach: 

Water Resources Research, v. 15, no. 2, p. 399–413, 

accessed November 2012 at http://dx.doi.org/10.1029/

WR015i002p00399.

Fram, M.S., and Belitz, K., 2011a, Probability of detecting 

perchlorate under natural conditions in deep groundwater 

in California and the southwestern United States: 

Environmental Science & Technology, v. 45, no. 4, p. 1271–

1277, accessed November 2012 at http://dx.doi.org/10.1021/

es103103p.

Fram, M.S., and Belitz, K., 2011b, Occurrence and 

concentrations of pharmaceutical compounds in 

groundwater used for public drinking-water supply in 

California: Science of the Total Environment, v. 409, no. 18, 

p. 3409–3417, accessed November 2012 at http://dx.doi.

org/10.1016/j.scitotenv.2011.05.053.

Fram, M.S., and Belitz, Kenneth, 2012, Status and 

understanding of groundwater quality in the TahoeMartis, Central Sierra, and Southern Sierra study units, 

2006–2007—California GAMA Priority Basin Project: 

U.S. Geological Survey Scientific Investigations Report 

2011–5216, 222 p. (Also available at http://pubs.usgs.gov/

sir/2011/5216/.)

Freeze, R.A., and Cherry, J.A., 1979, Groundwater: 

Englewood Cliffs, New Jersey, Prentice Hall, Inc., 604 p.

Gildersleeve, R., 2006, Chapter 12—Irrigated pasture, in

Drake, D.J., and Phillips, R.L., Fundamentals of beef 

management: University of California Agriculture and 

Natural Resources Publication 3495, p. 67–74.

Gilliom, R.J., Barbash, J.E., Crawford, C.G., Hamilton, 

P.A., Martin, J.D., Nakagaki, Naomi, Nowell, L.H., Scott, 

J.C., Stackelberg, P.E., Thelin, G.P., and Wolock, D.M., 

2006, The quality of our Nation’s waters—Pesticides in 

the Nation’s streams and ground water, 1992–2001: U.S. 

Geological Survey Circular 1291, 173 p. (Also available at 

http://pubs.usgs.gov/circ/2005/1291/.)

Greiner, Peter, McClellan, Clif, Bennett, Dale, and Ewing, 

Angie, 2008, Occurrence of perchlorate in sodium 

hypochlorite: Journal of the American Water Works 

Association, v. 100, no. 11, p. 68–74.

Helsel, D.R., and Hirsch, R.M., 2002, Statistical methods in 

water resources: U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 4, chap. A3, 523 p. 

(Also available at http://water.usgs.gov/pubs/twri/twri4a3/.)

Hem, J.D., 1985, Study and interpretation of the chemical 

characteristics of natural water (3d ed.): U.S. Geological 

Survey Water-Supply Paper 2254, 263 p. (Also available at 

http://pubs.er.usgs.gov/publication/wsp2254.)

Hirsch, R.M., Alley, W.M., and Wilber, W.G., 1988, Concepts 

for a National Water-Quality Assessment Program: U.S. 

Geological Survey Circular 1021, 42 p. (Also available at 

http://pubs.er.usgs.gov/publication/cir1021.)

Ingebritsen, S.E., and Sanford, W.E., 1998, Groundwater in 

geologic processes: Cambridge, New York, N.Y., USA, 

Cambridge University Press, 341 p.

Isaaks, E.H., and Srivastava, R.M., 1989, Applied 

geostatistics: New York, Oxford University Press, 561 p.

Ivahnenko, Tamara, and Barbash, J.E., 2004, Chloroform in 

the hydrologic system—Sources, transport, fate, occurrence, 

and effects on human health and aquatic organisms: 

U.S. Geological Survey Scientific Investigations Report 

2004–5137, 34 p. (Also available at http://pubs.usgs.gov/

sir/2004/5137/.)

Jennings, C.W., 1977, Geologic map of California: California 

Department of Conservation, Division of Mines and 

Geology Geologic Data Map No. 2, scale 1:750,000.

Johnson, T.D., and Belitz, Kenneth, 2009, Assigning land 

use to supply wells for the statistical characterization of 

regional groundwater quality—Correlating urban land use 

and VOC occurrence: Journal of Hydrology, v. 370, no. 1–4, 

p. 100–108, accessed November 2012 at http://dx.doi.

org/10.1016/j.jhydrol.2009.02.056.
References 79

Jurgens, B.C., Fram, M.S., Belitz, Kenneth, Burow, K.R., and 

Landon, M.K., 2010, Effects of groundwater development 

on uranium—Central Valley, California, USA: Ground 

Water, v. 48, no. 6, p. 913–928, accessed November 2012 at 

http://dx.doi.org/10.1111/j.1745-6584.2009.00635.x.

Jurgens, B.C., McMahon, P.B., Chapelle, F.H., and Eberts, 

S.M., 2009, An Excel® workbook for identifying redox 

processes in ground water: U.S. Geological Survey OpenFile Report 2009–1004, 8 p. (Also available at http://pubs.

usgs.gov/of/2009/1004/.)

Kegley, S.E., Hill, B.R., Orme, S., and Choi, A.H., 2010, 

PAN Pesticide Database: Pesticide Action Network, 

North America, accessed January 2011 at http://www.

pesticideinfo.org.

Kenny, J.F., Barber, N.L., Hutson, S.S., Linsey, K.S., 

Lovelace, J.K., and Maupin, M.A., 2009, Estimated use of 

water in the United States in 2005: U.S. Geological Survey 

Circular 1344, 53 p. (Also available at http://pubs.usgs.gov/

circ/1344/.)

Klein, Cornelis, and Hurlbut, C.S., Jr., 1993, Manual of 

mineralogy (after James D. Dana) (21st ed.): New York, 

John Wiley & Sons, 681 p.

Krishnaswami, S., Graustein, W.C., Turekian, K.K., and 

Dowd, J.F., 1982, Radium, thorium and radioactive lead 

isotopes in groundwaters—Application to the in situ 

determination of adsorption-desorption rate constants and 

retardation factors: Water Resources Research, v. 18, no. 6, 

p. 1663–1675, accessed November 2012 at http://dx.doi.

org/10.1029/WR018i006p01663.

Kulongoski, Justin, and Belitz, Kenneth, 2004, GroundWater Ambient Monitoring and Assessment Program: 

U.S. Geological Survey Fact Sheet 2004–3088, 2 p. (Also 

available at http://pubs.usgs.gov/fs/2004/3088/.)

Landon, M.K., Belitz, Kenneth, Jurgens, B.C., Kulongoski, 

J.T., and Johnson, T.D., 2010, Status and understanding 

of groundwater quality in the Central–Eastside San 

Joaquin Basin, 2006—California GAMA Priority Basin 

Project: U.S. Geological Survey Scientific Investigations 

Report 2009–5266, 97 p. (Also available at http://pubs.usgs.

gov/sir/2009/5266/.)

Landon, M.K., Green, C.T., Belitz, Kenneth, Singleton, M.J., 

and Esser, B.K., 2011, Relations of hydrogeologic factors, 

groundwater reduction-oxidation conditions, and temporal 

and spatial distributions of nitrate, Central-Eastside San 

Joaquin Valley, California, USA: Hydrogeology Journal, 

v. 19, no. 6, p. 1203–1224, accessed November 2012 at 

http://dx.doi.org/10.1007/s10040-011-0750-1.

Lindberg, R.D., and Runnels, D.D., 1984, Ground water redox 

reactions—An analysis of equilibrium state applied to Eh 

measurements and geochemical modeling: Science, v. 225, 

no. 4665, p. 925–927, accessed November 2012 at http://

dx.doi.org/10.1126/science.225.4665.925.

Lucas, L.L., and Unterweger, M.P., 2000, Comprehensive 

review and critical evaluation of the half-life of tritium: 

Journal of Research of the National Institute of Standards 

and Technology, v. 105, no. 4, p. 541–549, accessed 

November 2012 at http://dx.doi.org/10.6028/jres.105.043.

Manning, A.H, Solomon, D.K., and Thiros, S.A., 2005, 3

H/3He age data in assessing the susceptibility of wells 

to contamination: Groundwater, v. 43, no. 3, p. 353–367, 

accessed November 2012 at http://dx.doi.org/10.1111/

j.1745-6584.2005.0028.x.

Massachusetts Department of Environmental Protection, 2006, 

The occurrence and sources of perchlorate in Massachusetts, 

draft report, accessed November 2007 at http://www.mass.

gov/eea/docs/dep/cleanup/sites/percsour.pdf.

McMahon, P.B., and Chapelle, F.H., 2008, Redox processes 

and water quality of selected principal aquifer systems: 

Groundwater, v. 46, no. 2, p. 259–271, accessed 

November 2012 at http://dx.doi.org/10.1111/j.1745-

6584.2007.00385.x.

Michel, R.L., 1989, Tritium deposition in the continental 

United States, 1953–83: U.S. Geological Survey WaterResources Investigations Report 89–4072, 46 p. (Also 

available at http://pubs.er.usgs.gov/publication/wri894072.)

Michel, R.L., and Schroeder, R.A., 1994, Use of long-term 

tritium records from the Colorado River to determine 

timescales for hydrologic processes associated with irrigation 

in the Imperial Valley, California: Applied Geochemistry, 

v. 9, no. 4, p. 387–401, accessed November 2012 at http://

dx.doi.org/10.1016/0883-2927(94)90061-2.

Mulch, A., Sarna-Wojcicki, A.M., Perkins, M.E., and 

Chamberlain, C.P., 2008, A Miocene to Pleistocene climate 

and elevation record of the Sierra Nevada (California): 

Proceedings of the National Academy of Sciences of the 

United States of America, v. 105, no. 19, p. 6819–6824, 

accessed November 2012 at http://dx.doi.org/10.1073/

pnas.0708811105.

Nakagaki, Naomi, Price, C.V., Falcone, J.A., Hitt, K.J., and 

Ruddy, B.C., 2007, Enhanced National Land Cover Data 

1992 (NLCDe 92): U.S. Geological Survey raster digital 

data, accessed November 2012 at http://water.usgs.gov/

lookup/getspatial?nlcde92.

Nakagaki, Naomi, and Wolock, D.M., 2005, Estimation of 

agricultural pesticide use in drainage basins using land 

cover maps and county pesticide data: U.S. Geological 

Survey Open-File Report 2005–1188, 46 p. (Also available 

at http://pubs.usgs.gov/of/2005/1188/.)
80 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

National Atmospheric Deposition Program, 2012, National 

Trends Network data retrieval for sites CA28 (Kings 

River Experimental Watershed), CA50 (Sagehen Creek), 

CA75 (Sequoia National Park—Giant Forest), and CA99 

(Yosemite National Park—Hodgdon Meadow), accessed 

March 2013 at http://nadp.sws.uiuc.edu/NTN/ntnData.aspx.

National Research Council, 2006, Fluoride in drinking 

water—A scientific review of EPA’s standards: Washington, 

D.C., The National Academies Press, 530 p.

Nolan, B.T., and Hitt, K.J., 2003, Nutrients in shallow 

ground waters beneath relatively undeveloped areas in the 

conterminous United States: U.S. Geological Survey WaterResources Investigations Report 2002–4289, 17 p. (Also 

available at http://pubs.usgs.gov/wri/wri024289/.)

Olsen, L.D., Fram, M.S., and Belitz, Kenneth, 2009, Review 

of trace-element field-blank data collected for the California 

Groundwater Ambient Monitoring and Assessment 

(GAMA) Program, May 2004–January 2008: U.S. 

Geological Survey Scientific Investigations Report 2009–

5220, 47 p. (Also available at http://pubs.usgs.gov/

sir/2009/5220/.)

Page, R.W., Anttila, P.W., Johnson, K.L., and Pierce, 

M.J., 1984, Ground-water conditions and well yields in 

fractured rocks, southwestern Nevada County, California: 

U.S. Geological Survey Water-Resources Investigations 

Report 83–4262, 38 p. (Also available at http://pubs.er.usgs.

gov/publication/wri834262.)

Parker, D.R., Seyfferth, A.L., and Reese, B.K., 2009, 

Perchlorate in groundwater—A synoptic survey of 

“pristine” sites in the coterminous United States: 

Environmental Science & Technology, v. 42, no. 5, 

p. 1465–1471, accessed November 2012, at http://dx.doi.

org/10.1021/es7021957. 

Piper, A.M., 1944, A graphic procedure in the geochemical 

interpretation of water analyses: American Geophysical 

Union Transactions, v. 25, p. 914–923.

Plummer, L.N., Bexfield, L.M.,Anderholm, S.K., Sanford, 

W.E., and Busenberg, Eurybiades, 2004, Geochemical 

characterization of ground-water flow in the Santa Fe Group 

aquifer system, Middle Rio Grande Basin, New Mexico: 

U.S. Geological Survey Water-Resources Investigations 

Report 03–4131, 395 p. (Also available at http://pubs.usgs.

gov/wri/wri034131/.)

Plummer, L.N., Michel, R.L., Thurman, E.M., and Glynn, 

P.D., 1993, Environmental tracers for age-dating young 

ground water, in Alley, W.M., ed., Regional ground-water 

quality: New York, Van Nostrand Reinhold, p. 255–294.

PRISM Climate Group, Oregon State University, 2007, 

United States average annual precipitation, maximum and 

minimum temperature, 1971–2000, accessed August 9, 

2007, at http://prism.oregonstate.edu/.

Rajagopalan, Srinath, Anderson, Todd, Cox, Stephen, 

Harvey, Greg, Cheng, Qiuqiong, and Jackson, W.A., 2009, 

Perchlorate in wet deposition across North America: 

Environmental Science & Technology, v. 43, no. 3, p. 616–

622, accessed November 2012 at http://dx.doi.org/10.1021/

es801737u.

Rao, Balaji, Anderson, T.A., Orris, G.J., Rainwater, K.A., 

Rajagopalan, Srinath, Sandvig, R.M., Scalon, B.R., 

Stonestrom, D.A., Walvoord, M.A., and Jackson, W.A., 

2007, Widespread natural perchlorate in unsaturated zones 

of the southwest United States: Environmental Science 

& Technology, v. 41, no. 13, p. 4522–4528, accessed 

November 2012 at http://dx.doi.org/10.1021/es062853i.

Raub, William, Brown, C.S., and Post, Austin, 2006, Inventory 

of glaciers in the Sierra Nevada, California: U.S. Geological 

Survey Open-File Report 2006–1239, 228 p. (Also available 

at http://pubs.usgs.gov/of/2006/1239/.)

Robbins, G.A., Wang, Suya, and Stuart, J.D., 1993, Using 

the static headspace method to determine Henry’s law 

constants: Analytical Chemistry, v. 65, no. 21, p. 3113–

3118, accessed November 2012 at http://dx.doi.org/10.1021/

ac00069a026.

Rowe, B.L., Toccalino, P.L., Moran, M.J., Zogorski, J.S., and 

Price, C.V., 2007, Occurrence and potential human-health 

relevance of volatile organic compounds in drinking water 

from domestic wells in the United States: Environmental 

Health Perspectives, v. 115, no. 11, p. 1539–1546, accessed 

November 2012 at http://dx.doi.org/10.1289/ehp.10253.

Rupert, M.G., 2003, Probability of detecting atrazine/

desethyl-atrazine and elevated concentrations of nitrate in 

ground water in Colorado: U.S. Geological Survey WaterResources Investigations Report 2002–4269, 35 p. (Also 

available at http://pubs.usgs.gov/wri/wri02-4269/.)

Saleeby, J.B., Ducea, M.N., Busby, C.J., Nadin, E.S., and 

Wetmore, P.H., 2008, Chronology of pluton emplacement 

and regional deformation in the southern Sierra Nevada 

batholith, California, in Wright, J.E., and Shervais, J.S., 

eds., Ophiolites, arcs, and batholiths—A tribute to Cliff 

Hopson: Geological Society of America Special Papers, 

v. 438, p. 397–427, accessed November 2012 at http://

dx.doi.org/10.1130/2008.2438(14).

Saucedo, G.J., Bedford, D.R., Raines, G.L., Miller, R.J., and 

Wentworth, C.M., 2000, GIS data for the geologic map of 

California: California Department of Conservation, Division 

of Mines and Geology, CD-ROM 2000-007.

Scott, J.C., 1990, Computerized stratified random siteselection approaches for design of a ground-water-quality 

sampling network: U.S. Geological Survey Water-Resources 

Investigations Report 90–4101, 109 p. (Also available at 

http://pubs.er.usgs.gov/publication/wri904101.)
References 81

Shelton, J.L., Fram, M.S., Munday, C.M., and Belitz, Kenneth, 

2010, Groundwater-quality data for the Sierra Nevada study 

unit, 2008—Results from the California GAMA Program: 

U.S. Geological Survey Data Series 534, 106 p. (Also 

available at http://pubs.usgs.gov/ds/534/.)

Sierra Nevada Ecosystem Project, 1996, Status of the Sierra 

Nevada, Summary of the Sierra Nevada Ecosystem Project 

Report, in Sierra Nevada Ecosystem Project—Final report 

to Congress, v. I, Assessments and scientific basis for 

management options: Davis, University of California, 

Centers for Water and Wildland Resources, p. 1–22.

Smedley, P.L., and Kinniburgh, D.G., 2002, A review of the 

source, behaviour and distribution of arsenic in natural 

waters: Applied Geochemistry, v. 17, no. 5, p. 517–568, 

accessed November 2012 at http://dx.doi.org/10.1016/

S0883-2927(02)00018-5.

Squillace, P.J., Pankow, J.F., Korte, N.E., and Zogorski, 

J.S., 1997, Review of the environmental behavior 

and fate of methyl tert-butyl ether: Environmental 

Toxicology and Chemistry, v. 16, no. 9, p. 1836–1844, 

accessed November 2012 at http://dx.doi.org/10.1002/

etc.5620160911.

Squillace, P.J., Zogorski, J.S., Wilber, W.G., and Price, 

C.V., 1996, Preliminary assessment of the occurrence and 

possible sources of MTBE in groundwater in the United 

States, 1993–1994: Environmental Science & Technology, 

v. 30, no. 5, p. 1721–1730, accessed November 2012 at 

http://dx.doi.org/10.1021/es9507170.

State of California, 1999, Supplemental report of the 1999 

Budget Act, 1999–00 Fiscal Year, Item 3940-001-0001, 

State Water Resources Control Board, accessed August 11, 

2010, at http://www.swrcb.ca.gov/gama/docs/ab_599_

bill_20011005_chaptered.pdf.

State of California, 2001a, Assembly Bill No. 599, 

Chapter 522, accessed August 11, 2010, at http://www.lao.

ca.gov/1999/99-00_supp_rpt_lang.html#3940.

State of California, 2001b, Groundwater Monitoring Act 

of 2001 (California Water Code, division 6, part 2.76, 

sections 10780–10782.3), accessed August 11, 2010, at 

http://www.leginfo.ca.gov/cgi-bin/displaycode?section=wat

&group=10001-11000&file=10780-10783.

Stumm, W., and Morgan, J.J., 1996, Aquatic chemistry—

Chemical equilibria and rates in natural waters: New York, 

John Wiley & Sons, 1022 p.

Szabo, Zoltan, and Zapecza, O.S., 1991, Geologic and 

geochemical factors controlling uranium, radium-226, and 

radon-222 in ground water, Newark Basin, New Jersey, in

Gunderson, L.C.S., and Wanty, R.B., eds., Field studies of 

radon in rocks, soils, and water: U.S. Geological Survey 

Bulletin 1971, p. 243–265, accessed November 2012 at 

http://pubs.er.usgs.gov/publication/b1971.

Thomas, J.M., Welch, A.H., Lico, M.S., Hughes, J.L., and 

Whitney, Rita, 1993, Radionuclides in ground water of the 

Carson River Basin, western Nevada and eastern California, 

U.S.A.: Applied Geochemistry, v. 8, no. 5, p. 447–471, 

accessed November 2012 at http://dx.doi.org/10.1016/0883-

2927(93)90075-R.

Toccalino, P.L., and Norman, J.E., 2006, Health-based 

screening levels to evaluate U.S. Geological Survey 

ground water quality data: Risk Analysis, v. 26, no. 5, 

p. 1339–1348, accessed November 2012, at http://dx.doi.

org/10.1111/j.1539-6924.2006.00805.x.

Toccalino, P.L., Norman, J.E., and Hitt, K.J., 2010, Quality 

of source water from public-supply wells in the United 

States, 1993–2007: U.S. Geological Survey Scientific 

Investigations Report 2010–5024, 206 p. (Also available at 

http://pubs.usgs.gov/sir/2010/5024/.)

Toccalino, P.L., Norman, J.E., Phillips, R.H., Kauffman, 

L.J., Stackelberg, P.E., Nowell, L.H., Krietzman, S.J., and 

Post, G.B., 2004, Application of health-based screening 

levels to ground-water quality data in a state-scale pilot 

effort: U.S. Geological Survey Scientific Investigations 

Report 2004–5174, 14 p. (Also available at http://pubs.usgs.

gov/sir/2004/5174/.)

Tolstikhin, I.N., and Kamenskiy, I.L., 1969, Determination 

of groundwater ages by the T-3He method: Geochemistry 

International, v. 6, p. 810–811.

Torgersen, T., Clarke, W.B., and Jenkins, W.J.,1979, The 

tritium/helium-3 method in hydrology: IAEA-SM-228, 

v. 49, p. 917–930.

Tóth, J., 1963, A theoretical analysis of groundwater flow in 

small drainage basins: Journal of Geophysical Research, 

v. 68, no. 16, p. 4795–4812, accessed November 2012 at 

http://dx.doi.org/10.1029/JZ068i016p04795.

Tourtelot, E.B., 1970, Selected annotated bibliography of 

minor-element content of marine black shales and related 

sedimentary rocks, 1930–65: U.S. Geological Survey 

Bulletin 1293, 118 p. (Also available at http://pubs.er.usgs.

gov/publication/b1293.)

U.S. Census Bureau, 1990, Census of population and housing, 

summary tape file 3A, accessed August 11, 2011, at ftp://

ftp2.census.gov/census_1990/.

U.S. Environmental Protection Agency, 1986, Guidelines 

for the health risk assessment of chemical mixtures: U.S. 

Environmental Protection Agency, Office of Research and 

Development, Risk Assessment Forum EPA/630/R-98/002, 

September 1986, 28 p., accessed November 2012 at http://

www.epa.gov/raf/publications/pdfs/CHEMMIX_1986.PDF.
82 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

U.S. Environmental Protection Agency, 1998, Code of 

Federal Regulations, title 40—Protection of environment, 

chapter 1—Environmental protection agency, subchapter E—

Pesticide programs, part 159—Statements of policies and 

interpretations, subpart D—Reporting requirements for risk/

benefit information, 40 CFR 159.184: National Archives 

and Records Administration, September 19, 1997; amended 

June 19, 1998, accessed September 5, 2008, at http://www.

epa.gov/EPA-PEST/1997/September/Day-19/p24937.htm. 

U.S. Environmental Protection Agency, 1999a, Proposed 

radon in drinking water regulation, accessed January 2011 

at http://water.epa.gov/lawsregs/rulesregs/sdwa/radon/

regulations.cfm.

U.S. Environmental Protection Agency, 1999b, A review 

of contaminant occurrence in public water systems: 

U.S. Environmental Protection Agency, Office of Water 

EPA 816-R-99-006, November 1999, 78 p., accessed 

November 2012 at http://www.epa.gov/safewater/occur/

occur.html.

U.S. Environmental Protection Agency, 2005, List of known 

perchlorate releases in the U.S., March 25, 2005, accessed 

November 2007 at http://www.epa.gov/swerffrr/documents/

perchlorate_releases_us_20050325.htm.

U.S. Environmental Protection Agency, 2008, Drinking water 

health advisory for Boron: U.S. Environmental Protection 

Agency 822-R-08-013, 53 p., accessed November 2012 at 

http://www.epa.gov/safewater/ccl/pdfs/reg_determine2/

healthadvisory_ccl2-reg2_boron.pdf.

U.S. Environmental Protection Agency, 2009, National primary 

drinking water regulations, accessed January 2011 at http://

water.epa.gov/drink/contaminants/upload/mcl-2.pdf.

U.S. Environmental Protection Agency, 2010, Arsenic in 

drinking water, accessed December 2010 at http://water.epa.

gov/lawsregs/rulesregs/sdwa/arsenic/index.cfm.

U.S. Environmental Protection Agency, 2012, 2012 Edition of 

the drinking water standards and health advisories, accessed 

March 2013 at http://water.epa.gov/action/advisories/

drinking/upload/dwstandards2012.pdf.

U.S. Environmental Protection Agency, 2014, Basic 

information about regulated drinking water contaminants 

and indicators, accessed July 2014 at http://water.epa.gov/

drink/contaminants/basicinformation/.

U.S. Government Accounting Office, 2005, Livestock 

grazing—Federal expenditures and receipts vary, depending 

on the agency and the purpose of the fee charged: GAO05-869, accessed August 11, 2011, at http://www.gao.gov/

products/GAO-05-869.

United Nations Educational, Scientific, and Cultural 

Organization (UNESCO), 1979, Map of the world 

distribution of arid regions—Explanatory note: MAB 

Technical Notes, v. 7, 42 p.

United Nations Environment Programme, 1997, World atlas of 

desertification (2d ed.): London, Edward Arnold, 182 p.

Vogel, J.C., and Ehhalt, D., 1963, The use of the carbon 

isotopes in ground water studies, in Radioisotopes in 

Hydrology: Tokyo, International Atomic Energy Agency, 

p. 383–395.

Wakabayashi, John, and Sawyer, T.L., 2001, Stream incision, 

tectonics, uplift, and evolution of topography of the Sierra 

Nevada, California: The Journal of Geology, v. 109, no. 5, 

p. 539–562, accessed November 2012, at http://dx.doi.

org/10.1086/321962.

Walker, J.D., and Geissman, J.W., comps., 2009, Geologic 

time scale: Geological Society of America, doi: 

10.1130/2009.CTS004R2C, accessed August 2011 at http://

www.geosociety.org/science/timescale/timescl.pdf.

Welch, A.H., Oremland, R.S., Davis, J.A., and Watkins, 

S.A., 2006, Arsenic in ground water—A review of current 

knowledge and relation to the CALFED solution area 

with recommendations for needed research: San Francisco 

Estuary & Watershed Science, v. 4, no. 2, article 4, 32 p., 

accessed November 2012 at http://www.escholarship.org/

uc/item/8342704q.

Welch, A.H., and Stollenwerk, K.G., eds., 2003, Arsenic in 

ground water—Geochemistry and occurrence: Springer, 

475 p.

Welch, A.H., Westjohn, D.B., Helsel, D.R., and Wanty, R.B., 

2000, Arsenic in ground water of the United States—

Occurrence and geochemistry: Ground Water, v. 38, no. 4, 

p. 589–604, accessed November 2012 at http://water.usgs.

gov/nawqa/trace/pubs/gw_v38n4/.

Wilson, J.L., and Guan, Huade, 2004, Mountain-block 

hydrology and mountain-front recharge, in Hogan, J.F., 

Phillips, F.M., and Scanlon, B.R., eds., Groundwater 

recharge in a desert environment—The southwestern United 

States: Washington, D.C., American Geophysical Union, 

Water Science and Application Series, v. 9, p. 113–137.

Zogorski, J.S., Carter, J.M., Ivahnenko, Tamara, Lapham, 

W.W., Moran, M.J., Rowe, B.L., Squillace, P.J., and 

Toccalino, P.L., 2006, Volatile organic compounds in the 

Nation’s ground water and drinking-water supply wells: 

U.S. Geological Survey Circular 1292, 101 p. (Also 

available at http://pubs.usgs.gov/circ/circ1292/.)
Appendix A. Lithologic-Grid Wells 83

The status assessments for other GAMA Priority Basin 

Project study units calculated aquifer-scale proportions for 

inorganic constituents by using both the grid-based and 

spatially weighted methods (for example, Landon and others, 

2010; Burton and others, 2012; Fram and Belitz, 2012). The 

grid-based calculations required supplementing the data 

collected by the USGS with data from the CDPH database 

because the USGS generally did not have a grid well in every 

grid cell and data for inorganic constituents were not collected 

at every well sampled by the USGS. Data to complete the grid 

dataset were obtained from selected wells in the CDPH database (hereinafter referred to as CDPH-grid wells). Although 

grid-based calculations of aquifer-scale proportions for inorganic constituents were not used for the SNR study unit status 

assessment presented in this report, a set of CDPH-grid wells 

was selected to complete the grid dataset for potential use in 

multi-study-unit synthesis reports.

The SNR study unit was divided into 30 equal-area grid 

cells (2,200 km2

 each; fig. A1) (Scott, 1990), and each cell was 

subdivided into 1 to 4 sub-cells, 1 for each of the 4 aquifer 

lithologies (granitic rock, metamorphic rock, sedimentary 

deposits, and volcanic rock) present in the cell. All of the 

CDPH wells in a cell were assigned random ranks, and the 

highest-ranked well in each sub-cell for which permission 

to sample could be obtained and which met basic sampling 

criteria was selected as the lithologic-grid well to represent 

that sub-cell. Not all cells contained areas of all four aquifer 

lithologies, and not all aquifer lithologies present in a cell 

contained wells. The 30 grid cells each had 2 to 4 aquifer 

lithologies containing CDPH wells, resulting in total of 91 

possible lithologic-grid sub-cells. USGS-GAMA sampled 

wells in 82 of the 91 possible lithologic-grid sub-cells 

(table A1). One additional well was sampled in sub-cell 1M.

All 82 USGS-grid wells were part of the lithologic-grid 

network. Thirty of the USGS-grid wells also composed the 

fundamental-grid network, which was used for data analysis 

by Shelton and others (2010), but was not used in this study. 

The fundamental-grid network consisted of 30 wells, 1 from 

each cell. The highest-ranked grid well from among the 2 to 

4 lithologic sub-cells present in the cell was defined as the 

fundamental-grid well. Fundamental-grid wells were named 

with an alphanumeric GAMA_ID consisting of an initial 

prefix identifying the study unit (SIERRA), a second prefix 

indicating aquifer lithology (G, M, S, and V for granitic, 

metamorphic, sedimentary, and volcanic aquifer lithologies, 

respectively), and a number indicating the order of sample collection (figs. A1A,B; table A1). The other 52 USGS-grid wells 

(and the 1 extra well) were named in the same way, except 

that the second prefix included an “L” for lithologic grid (GL, 

ML, SL, and VL for granitic, metamorphic, sedimentary, and 

volcanic aquifer lithologies, respectively).

The CDPH database was queried to provide data for 

inorganic constituents to represent the nine sub-cells that did 

not have a USGS-grid well. The CDPH database also was 

queried to provide data for the two inorganic constituents not 

analyzed for every USGS-grid well: radon-222 and radium 

activities. Only CDPH wells with data during the period 

May 1, 2006, through October 31, 2008, were considered. If 

the well had more than one analysis for a constituent in that 

interval, then the most recent data were selected.

CDPH-grid wells were selected for the nine sub-cells 

without USGS-grid wells (sub-cells 1G, 1S, 3S, 9M, 9S, 10S, 

11V, 13S, 20S; table A1) as follows:

1. For four of the nine sub-cells (sub-cells 9M, 10S, 11V, 

13S), there was only one CDPH well with any of the 

needed data; those wells were selected as the CDPHgrid well to represent their respective sub-cells.

2. For 3 of the 9 sub-cells (sub-cells 1G, 9S, 20S), there 

were 7 to 13 wells with data; however, in each subcell, 1 well had data for many inorganic constituents, 

and the others had data for few inorganic constituents 

(usually only nutrients). The wells with data for the 

largest number of constituents were selected as the 

CDPH grid wells to represent these sub-cells.

3. For the remaining two of the nine sub-cells, the 

wells in the sub-cell had data for the same number 

of constituents (sub-cell 3S had three wells with data 

for nutrients only, and sub-cell 1S had two wells with 

data for nitrate and arsenic only). For each sub-cell, 

the well with the highest random rank was selected as 

the CDPH-grid well to represent the sub-cell.

The CDPH wells were given names consisting of the 

same prefix used by the USGS wells in the study area or 

study unit, the second prefix “DPH,” and the next number in 

the series after the USGS-grid well numbers (table A1). The 

“DPH” prefix indicates that the CDPH-grid well is not also a 

USGS-grid well. The data from these nine CDPH-grid wells 

are listed in tables A2 and A3. Of the nine CDPH-grid wells, 

four had data only for nutrients, and five had data for nutrients 

and some trace elements and (or) constituents with SMCL 

benchmarks (tables A2, A3). 

The CDPH database also was queried to provide data for 

the two inorganic constituents not analyzed at every lithologicgrid well (radon-222 and radium activities). USGS-GAMA 

sampled for radon-222 at 28 of the 82 sites on the lithologicgrid network, and none of the remaining 54 wells had data 

for radon-222 in the CDPH database. USGS-GAMA sampled 

for radium in 30 wells, and 6 of the remaining 52 wells had 

data for radium in the CDPH database (sub-cells 1M, 5M, 7V, 

8S, 18V, 26M; table A1). The CDPH radium data for these 

six wells were used to supplement the USGS-GAMA data for 

those wells (table A2).

Appendix A. Lithologic-Grid Wells
84 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

V-02

V-01

S-03

S-02

M-06

M-05

M-04

M-03

M-02

M-01

G-15

G-14

G-13

G-12

G-11

G-10

VL-12

VL-11

VL-10

VL-09

VL-08

VL-07

VL-06

VL-05

VL-04

VL-03

VL-02

SL-12

SL-09

SL-08

SL-07

SL-06

SL-05

ML-18

ML-17

ML-15

ML-14

ML-13

ML-12

ML-10

GL-10

GL-09

GL-08

GL-07

GL-06

GL-05

GL-04

GL-03

GL-02

7

6

2

5

1

4 8

9

3

11 16

15

10

17

18

12 19

14

18 18

5

18

VL-DPH-13

SL-DPH-14

GL-DPH-11

SL-DPH-17

SL-DPH-16

ML-DPH-19

SL-DPH-15

sac14-0538_Figure A01a wells_north

121° 120°

40°

39°

38°

0 10 20 30 MILES

0 10 20 30 KILOMETERS

A

Granitic

Metamorphic

Sedimentary

Volcanic

Granitic

Metamorphic

Sedimentary

Volcanic

Granitic

Metamorphic

Sedimentary

Aquifer lithology

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit wells 

CDPH well with data used

 in grid dataset 

 (tables A2 and A3)

EXPLANATION

Grid well

Sierra Nevada Regional

 study unit grid cell 

17

1

2

3

4

5

6 7

8

9

10

14

15

16

17

19

20 13

12

11

21

22

23

24

25

26

27

28

29

30

A

B

CALIFORNIA

18

Figure A1. Locations of grid cells (USGS) Public Health (CDPH) lithologic-grid wells in the Sierra Nevada Regional (SNR) study unit, 

California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Appendix A. Lithologic-Grid Wells 85

V-03

S-01

G-18

G-17

G-16

G-09

G-08

G-07

G-06

G-05

G-04

G-03

G-02

G-01

VL-01

SL-13

SL-11

SL-10

SL-04

SL-03

SL-02

SL-01

ML-16

ML-11

ML-09

ML-08

ML-07

ML-06

ML-05

ML-04

ML-03

ML-02

ML-01

GL-01

20

22

27

28

13

21

14

25

29

23

30

26

24

19 12

24

24

15

12

26

26

30

24

12

23

24

12

SL-DPH-18

SL-DPH-19

sac14-0538_Figure A01b wells_south

B

Granitic

Metamorphic

Sedimentary

Volcanic

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Sierra Nevada Regional

 study unit 

USGS-GAMA Sierra Nevada

 Regional study unit wells 

EXPLANATION

Grid well

Sierra Nevada Regional

 study unit grid cell 

17

0 10 20 30 MILES

0 10 20 30 KILOMETERS

120° 119° 118°

35°

36°

37°

Sedimentary

CDPH well with data used

 in grid dataset 

 (tables A2 and A3)

1

2

3

4

5

6 7

8

9

10

14

15

16

17

18

19

20 13

12

11

21

22

23

24

25

26

27

28

29

30

A

B

CALIFORNIA

Figure A1. —Continued
86 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table A1. Nomenclature for lithologic grid wells, Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project.

[California Department of Public Health (CDPH) data refers to the number of constituents for which the CDPH database was the source of data for the well. 

Fifteen wells had CDPH data for 1 or more constituents. The nine wells that are not also U.S. Geological Survey (USGS) wells have “DPH” in the identification

number prefix. Identification number prefixes: SIERRA, Sierra Nevada Regional study unit; G, granitic aquifer lithology in fundamental and lithologic grids; 

GL, granitic aquifer lithology in lithologic grid; M, metamorphic aquifer lithology in fundamental and lithologic grids; ML, metamorphic aquifer lithology in 

lithologic grid; S, sedimentary aquifer lithology in fundamental and lithologic grids; SL, sedimentary aquifer lithology in lithologic grid; V, volcanic aquifer 

lithology in fundamental and lithologic grids; VL, volcanic aquifer lithology in lithologic grid. Abbreviations: –, no CDPH data selected]

Cell

Granitic

aquifer lithology

Metamorphic

aquifer lithology

Sedimentary

aquifer lithology

Volcanic

aquifer lithology

GAMA well 

identification number

CDPH 

data

GAMA well 

identification number

CDPH 

data

GAMA well 

identification number

CDPH 

data

GAMA well 

identification number

CDPH 

data

1 SIERRA-GL-DPH-11 25 SIERRA-M-021

SIERRA-ML-171

1 SIERRA-SL-DPH-14 2 no wells –

2 SIERRA-G-15 – SIERRA-ML-18 – no wells – SIERRA-VL-12 –

3 SIERRA-GL-07 – SIERRA-M-05 – SIERRA-SL-DPH-15 1 SIERRA-VL-10 –

4 SIERRA-GL-09 – SIERRA-M-06 – no wells – no wells –

5 SIERRA-GL-08 – SIERRA-ML-15 1 SIERRA-SL-12 – SIERRA-V-02 –

6 no wells – SIERRA-M-03 – SIERRA-SL-08 – SIERRA-VL-08 –

7 SIERRA-GL-10 – no wells – SIERRA-S-03 – SIERRA-VL-09 1

8 SIERRA-GL-06 – SIERRA-M-04 – SIERRA-SL-09 1 SIERRA-VL-07 –

9 SIERRA-GL-05 – SIERRA-ML-DPH-19 1 SIERRA-SL-DPH-16 23 SIERRA-V-01 –

10 SIERRA-G-13 – SIERRA-ML-13 – SIERRA-SL-DPH-17 2 SIERRA-VL-05 –

11 SIERRA-G-11 – SIERRA-ML-10 – no wells – SIERRA-VL-DPH-13 26

12 SIERRA-GL-02 – SIERRA-M-01 – no wells – SIERRA-VL-11 –

13 SIERRA-G-07 – SIERRA-ML-09 – SIERRA-SL-DPH-18 1 no wells –

14 SIERRA-G-06 – SIERRA-ML-08 – no wells – no wells –

15 SIERRA-G-12 – SIERRA-ML-12 – SIERRA-SL-07 – SIERRA-VL-04 –

16 SIERRA-G-10 – no wells – SIERRA-SL-05 – SIERRA-VL-02 –

17 SIERRA-G-14 – no wells – SIERRA-SL-06 – SIERRA-VL-03 –

18 SIERRA-GL-04 – SIERRA-ML-14 – SIERRA-S-02 – SIERRA-VL-06 1

19 SIERRA-GL-03 – SIERRA-ML-16 – no wells – SIERRA-V-03 –

20 SIERRA-G-18 – no wells – SIERRA-SL-DPH-19 11 no wells –

21 SIERRA-G-08 – no wells – SIERRA-SL-13 – no wells –

22 SIERRA-G-09 – SIERRA-ML-05 – no wells – no wells –

23 SIERRA-G-05 – SIERRA-ML-06 – SIERRA-SL-03 – no wells –

24 SIERRA-G-03 – SIERRA-ML-03 – SIERRA-SL-04 – no wells –

25 SIERRA-G-01 – SIERRA-ML-01 – SIERRA-SL-01 – SIERRA-VL-01 –

26 SIERRA-GL-01 – SIERRA-ML-02 1 SIERRA-S-01 – no wells –

27 SIERRA-G-02 – SIERRA-ML-04 – SIERRA-SL-02 – no wells –

28 SIERRA-G-04 – SIERRA-ML-07 – no wells – no wells –

29 SIERRA-G-16 – SIERRA-ML-11 – SIERRA-SL-10 – no wells –

30 SIERRA-G-17 – no wells – SIERRA-SL-11 – no wells –

1

SIERRA-M-02 is used for the grid-based calculation of aquifer-scale proportion; both wells are used for the spatially weighted calculation.
Appendix A. Lithologic-Grid Wells 87

Table A2. California Department of Public Health (CDPH) data for nutrients and radioactive constituents used for the grid-based 

calculations of aquifer-scale proportions on the fundamental-grid and lithologic-grid networks, Sierra Nevada Regional (SNR) study 

unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[Wells having “DPH” in the GAMA well identification number were not sampled by U.S. Geological Survey (USGS); the other wells were sampled by USGS. 

CDPH data are the most recent analysis for each constituent during the period May 1, 2006, through October 31, 2008. In the CDPH database, non-detections

are reported as 0 for some samples and as less than the reporting limit for other samples. Units: mg/L, milligrams per liter; pCi/L, picocuries per liter. 

Abbreviations: USGS, data provided by U.S. Geological Survey (Shelton and others, 2010); na, not available; <, less than]

GAMA well 

identification number Cell

Nitrate, as 

nitrogen 

(mg/L)

Nitrite, as 

nitrogen 

(mg/L)

Radium 

(pCi/L)

Uranium 

(pCi/L)

Gross alpha 

(pCi/L)

Granitic aquifer lithology

SIERRA-GL-DPH-11 1 0.8 <0.05 na 5.6 na

Metamorphic aquifer lithology

SIERRA-M-02 1 USGS USGS 2.2 USGS USGS

SIERRA-ML-15 5 USGS USGS 0 USGS USGS

SIERRA-ML-DPH-19 9 0 na na na na

SIERRA-ML-02 26 USGS USGS 0.03 USGS USGS

Sedimentary aquifer lithology

SIERRA-SL-DPH-14 1 0.6 <0.05 na na na

SIERRA-SL-DPH-15 3 0.6 na na na na

SIERRA-SL-09 8 USGS USGS 0.1 USGS USGS

SIERRA-SL-DPH-16 9 0.4 0 na na na

SIERRA-SL-DPH-17 10 0 0 na na na

SIERRA-SL-DPH-18 13 13.2 na na na na

SIERRA-SL-DPH-19 20 3.9 na na na na

Volcanic aquifer lithology

SIERRA-VL-09 7 USGS USGS 0.25 USGS USGS

SIERRA-VL-DPH-13 11 0 0 na 11.5 13.8

SIERRA-VL-06 18 USGS USGS <1 USGS USGS
88 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table A3. California Department of Public Health (CDPH) data for trace elements with health-based benchmarks and inorganic 

constituents with secondary maximum contaminent level (SMCL) benchmarks used for the grid-based calculations of aquiferscale proportions on the fundamental-grid and lithologic-grid networks, Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

[Wells having “DPH” in the GAMA well identification number were not sampled by the U.S. Geological Survey (USGS). CDPH data are the most recent 

analysis for each constituent during the period May 1, 2006, through October 31, 2008. In the CDPH database, non-detections are reported as 0 for some 

samples and as less than the reporting limit for other samples. Units: μg/L, micrograms per liter; mg/L, milligrams per liter; μS/cm, microsiemens per 

centimeter. Abbreviations: na, not available; <, less than]

Constituent Units

GAMA well identification number

SIERRAGL-DPH-11

(cell 1)

SIERRASL-DPH-15

(cell 3)

SIERRASL-DPH-16

(cell 9)

SIERRASL-DPH-19

(cell 20)

SIERRAVL-DPH-13

(cell 11)

Trace elements with health-based benchmarks

Aluminum μg/L <50 na 0 na 0

Antimony μg/L <5 na 0 na 0

Arsenic μg/L 2.4 na 0 na 3.3

Barium μg/L <50 na 34 na 0

Beryllium μg/L <1 na 0 na 0

Boron μg/L na na na na na

Cadmium μg/L <1 na 0 na 0

Chromium μg/L <2 na 7.3 na 19

Copper μg/L <3 na 0 1,400 0

Fluoride mg/L 0.11 na 0 0 0

Lead μg/L <3 na na na 0

Mercury μg/L <1 na 0 na 0

Molybdenum μg/L na na na na na

Nickel μg/L <5 na 0 na 0

Selenium μg/L <2 na 0 na 0

Strontium μg/L na na na na na

Thallium μg/L <1 na 0 na 0

Vanadium μg/L na na na na na

Inorganic constituents with SMCL benchmarks

Iron μg/L <20 na 0 0 0

Manganese μg/L <5 na 0 0 0

Silver μg/L <2 na 0 0 0

Zinc μg/L 23 na 0 400 0

Chloride mg/L 4.9 na 9.6 6.3 1.6

Specific conductance μS/cm 437 140 138 45 366

Sulfate mg/L 4.8 na 12.7 5.1 5.1

Total dissolved solids mg/L 324 na 79 120 75
Appendix B. Attribution of Ancillary Data 89

Appendix B. Attribution of Ancillary Data

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 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. 

Land-use statistics for the study unit, study areas, and areas 

within a 500-m radius around each study well (500-m buffers) 

were calculated for classified datasets using ArcGIS. A 500-m 

radius centered on the well has been shown to be effective 

for correlating land use with contaminant occurrence (for 

example, Rupert, 2003; Johnson and Belitz, 2009). Land-use 

data for wells are listed in table B1.

Land-cover classes are based on features distinguishable 

in Level II remote sensing data (high-elevation aerial 

photography; Anderson and others, 1976). Urban land use 

includes high-, moderate-, and low-intensity development and 

developed open space. Agricultural land includes cultivated 

crops and land used for pasture or hay. Natural land includes 

everything else. In this classification, open-range grazing, such 

as that practiced on U.S. Forest Service and Bureau of Land 

Management lands in the Sierra Nevada, is classified as natural 

land, not agricultural land. In the seven national forests entirely 

within the Sierra Nevada hydrogeologic province (Plumas, 

Tahoe, Lake Tahoe Basin Management Unit, El Dorado, 

Stanislaus, Sierra, and Sequoia), there were approximately 

3,640,000 acres of grazing allotments and approximately 

165,000 billed animal-unit months in 2004 (U.S. Government 

Accounting Office, 2005). This corresponds to a density of 

approximately 0.05 cattle per acre per month. For comparison, 

cattle density on irrigated pasture in the San Joaquin Valley 

averages 8 cattle per acre per month (Gildersleeve, 2006).

Septic Systems and LUFTs

Septic tank density was determined using housing 

characteristics data from the 1990 U.S. Census (U.S. Census 

Bureau, 1990). The density of septic tanks in each housing census block was calculated from the number of tanks and block 

area. The density of septic tanks around each well was then calculated from the area-weighted mean of the block densities for 

blocks within a 500-m buffer around the well (Tyler Johnson, 

U.S. Geological Survey, written commun., 2009) (table B1).

The density of leaking or formerly leaking underground 

fuel tanks (LUFTs) was determined from the locations of 

tanks in the SWRCB’s GeoTracker database of environmental 

cleanup sites (California State Water Resources Control Board, 

2007). The density of LUFTs was calculated using Theissen 

polygons (Tyler Johnson, U.S. Geological Survey, written commun., 2007). The boundaries of the Theissen polygon around a 

particular LUFT were created by bisecting the linear distances 

between the LUFT and all the surrounding LUFTs. The density 

of LUFTs in the polygon was the number of tanks in the polygon (nearly always one) divided by the area of the polygon in 

square kilometers. A well was assigned the LUFT density of 

the Theissen polygon in which it is located (table B1).

Aquifer Lithology

Aquifer lithology was classified into four categories on 

the basis of lithologic information from driller’s logs and the 

California State geologic map (Jennings, 1977; Saucedo and 

others, 2000). The State geologic map shows the lithologic unit 

exposed at the surface, which may not be the same as the lithologic unit at the depth range over which the well is screened or 

open. In those cases where the lithologic category estimated 

from the geologic map disagreed with the lithology described 

in the driller’s log, the category from the driller’s log was used. 

In addition, several sites located near lakes plotted in the lake 

on the map; the lithologic category for each of these sites was 

estimated from the geologic units mapped surrounding the 

lake. The 83 wells sampled by USGS-GAMA were located in 

areas classified into 16 of the 66 geologic units defined on the 

California State geologic map (Jennings, 1977; Saucedo and 

others, 2000). These 16 geologic units were grouped into 4 

lithologic categories on the basis of rock type and age:

• Granitic rocks: Mesozoic granitic rocks (California 

State geologic map unit: grMz).

• Metamorphic rocks: Paleozoic and Mesozoic metavolcanic, metasedimentary, ultramafic, and mafic rocks 

(California State geologic map units: mv, Mzv, Pzv, m, 

J, Pz).

• Sedimentary deposits: Cenozoic sedimentary deposits, 

including alluvial, fluvial, lacustrine, and glacial sediments (California State geologic map units: Q, Qg, Tc, 

Ec, Mc). The Quaternary age non-marine sedimentary 

deposits (Q, Qg) are Pleistocene and Holocene in age. 

The Tertiary age non-marine sedimentary deposits (Ec, 

Mc, Tc) are Eocene, Miocene, and unspecified Tertiary 

in age, respectively.

• Volcanic rocks: Cenozoic volcanic rocks, including 

lava flows and pyroclastic deposits (California State 

geologic map units: Ti, Tv, Tvp, Qv). The Tertiary age 

volcanic rocks (Ti, Tv, Tvp) are primarily Miocene and 

Pliocene in age, and the Quaternary age volcanic rocks 

(Qv) are Pleistocene and Holocene in age.
90 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B1. Land-use percentages, septic tank density, leaking or formerly leaking underground fuel tank (LUFT) density, and geologic 

unit for wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.

Table B1. Land-use percentages, septic tank density, leaking or formerly leaking underground fuel tank (LUFT) density, and geologic 

unit for wells sampled by the USGS for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.—Continued

[Geologic unit: Granitic aquifer lithology: grMz, Mesozoic granitic rocks. Metamorphic aquifer lithology: J, Jurassic marine metasedimentary rocks; m, 

Mesozoic/Paleozoic metavolcanic/metasedimentary rocks; mv, Mesozoic/Paleozoic metavolcanic rocks; Mzv, Mesozoic metavolcanic rocks; Pz, Paleozoic 

marine metasedimentary rocks; Pzv, Paleozoic metavolcanic rocks; um, ultramafic rocks. Sedimentary aquifer lithology: Q, Holocene alluvial sediment; Qg, 

Holocene/Quaternary glacial sediment; Tc, Tertiary non-marine sediment; Mc, Miocene non-marine sediment; Ec, Eocene non-marine sediment. Volcanic

aquifer lithology: Q, Quaternary volcanic rocks; Tv, Tertiary volcanic rocks; Tvp, Tertiary pyroclastic rocks; Ti, Tertiary volcanic dikes. Abbreviations: 

tanks/km2, number of tanks per square kilometer; –, not available]

GAMA well 

identification number

Land-use percentages1 Septic density2

(tanks/km2)

LUFT density3

(tanks/km2) Geologic unit4

Agricultural Natural Urban

Granitic aquifer lithology

SIERRA-G-01 0 100 0 4.0 0.004 grMz

SIERRA-G-02 0 98 2 1.1 0.008 grMz

SIERRA-G-03 0 100 0 5.5 0.001 grMz

SIERRA-G-04 0 100 0 1.1 0.001 grMz

SIERRA-G-05 0 100 0 3.6 0.193 grMz

SIERRA-G-06 0 87 13 3.2 0.003 grMz

SIERRA-G-07 0 95 5 9.3 0.056 grMz

SIERRA-G-08 0 18 82 8.4 0.040 grMz

SIERRA-G-09 0 100 0 0.8 0.001 grMz

SIERRA-G-10 0 100 0 0.0 0.002 grMz

SIERRA-G-11 0 100 0 0.9 0.055 grMz5

SIERRA-G-12 0 100 0 0.2 0.004 grMz

SIERRA-G-13 0 100 0 0.9 0.007 grMz

SIERRA-G-14 0 100 0 7.4 0.023 grMz

SIERRA-G-15 53 47 0 3.6 0.036 grMz

SIERRA-G-16 1 99 0 0.3 0.004 grMz

SIERRA-G-17 0 100 0 0.5 0.001 grMz

SIERRA-G-18 0 100 0 0.3 0.001 grMz

SIERRA-GL-01 0 100 0 4.5 0.008 grMz

SIERRA-GL-02 0 31 69 17.8 0.349 grMz

SIERRA-GL-03 0 100 0 0.1 0.004 grMz

SIERRA-GL-04 0 100 0 0.0 0.008 grMz

SIERRA-GL-05 0 100 0 0.4 0.004 grMz

SIERRA-GL-06 0 100 0 0.7 0.010 grMz

SIERRA-GL-07 0 100 0 2.8 0.038 grMz

SIERRA-GL-08 0 100 0 0.7 0.001 grMz

SIERRA-GL-09 0 91 9 5.6 0.010 grMz

SIERRA-GL-10 0 100 0 0.3 0.002 grMz

Metamorphic aquifer lithology

SIERRA-M-01 0 100 0 4.2 0.070 mv

SIERRA-M-02 0 100 0 2.7 0.005 Mzv

SIERRA-M-03 0 100 0 1.5 0.011 Pzv6

SIERRA-M-04 0 100 0 5.4 0.010 Pzv

SIERRA-M-05 0 100 0 6.0 0.011 J7

SIERRA-M-06 0 90 10 1.9 0.011 Mzv8
Appendix B. Attribution of Ancillary Data 91

Table B1. Land-use percentages, septic tank density, leaking or formerly leaking underground fuel tank (LUFT) density, and geologic 

unit for wells sampled by the USGS for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.—Continued

[Geologic unit: Granitic aquifer lithology: grMz, Mesozoic granitic rocks. Metamorphic aquifer lithology: J, Jurassic marine metasedimentary rocks; m, 

Mesozoic/Paleozoic metavolcanic/metasedimentary rocks; mv, Mesozoic/Paleozoic metavolcanic rocks; Mzv, Mesozoic metavolcanic rocks; Pz, Paleozoic 

marine metasedimentary rocks; Pzv, Paleozoic metavolcanic rocks; um, ultramafic rocks. Sedimentary aquifer lithology: Q, Holocene alluvial sediment; Qg, 

Holocene/Quaternary glacial sediment; Tc, Tertiary non-marine sediment; Mc, Miocene non-marine sediment; Ec, Eocene non-marine sediment. Volcanic

aquifer lithology: Q, Quaternary volcanic rocks; Tv, Tertiary volcanic rocks; Tvp, Tertiary pyroclastic rocks; Ti, Tertiary volcanic dikes. Abbreviations: 

tanks/km2, number of tanks per square kilometer; –, not available]

GAMA well 

identification number

Land-use percentages1 Septic density2

(tanks/km2)

LUFT density3

(tanks/km2) Geologic unit4

Agricultural Natural Urban

Metamorphic aquifer lithology—Continued

SIERRA-ML-01 0 94 6 0.3 0.002 m

SIERRA-ML-02 0 87 13 28.7 0.003 m

SIERRA-ML-03 16 84 0 1.1 0.007 m

SIERRA-ML-04 0 100 0 0.0 0.001 m

SIERRA-ML-05 0 100 0 0.5 0.013 m

SIERRA-ML-06 9 91 0 3.9 0.006 m

SIERRA-ML-07 0 100 0 1.1 0.001 m

SIERRA-ML-08 0 100 0 1.5 0.005 J

SIERRA-ML-09 0 100 0 3.5 0.029 m

SIERRA-ML-10 0 100 0 3.1 0.016 mv

SIERRA-ML-11 0 100 0 0.2 0.002 mv

SIERRA-ML-12 0 86 14 0.9 0.004 Pz

SIERRA-ML-13 0 92 8 11.0 0.032 Pz

SIERRA-ML-14 0 100 0 0.0 0.019 Mzv

SIERRA-ML-15 47 30 22 0.5 0.004 Pz

SIERRA-ML-16 0 100 0 0.0 0.001 Mzv

SIERRA-ML-17 0 99 1 1.6 0.117 Mzv

SIERRA-ML-18 0 96 4 29.6 0.213 J

Sedimentary aquifer lithology

SIERRA-S-01 89 9 2 0.5 0.004 Q

SIERRA-S-02 0 61 39 0.0 0.398 Q

SIERRA-S-03 0 87 13 1.6 0.005 Q

SIERRA-SL-01 28 71 1 2.0 0.098 Q

SIERRA-SL-02 1 93 6 26.3 0.080 Q9

SIERRA-SL-03 11 56 32 3.3 0.006 Q

SIERRA-SL-04 0 100 0 0.6 0.008 Q10

SIERRA-SL-05 0 100 0 0.0 0.002 Qg

SIERRA-SL-06 0 100 0 0.3 0.002 Q

SIERRA-SL-07 0 91 9 0.1 0.009 Q

SIERRA-SL-08 30 38 32 1.6 0.002 Q

SIERRA-SL-09 13 87 0 0.5 0.004 Q

SIERRA-SL-10 1 99 0 0.1 0.000 Qg

SIERRA-SL-11 0 89 11 0.5 0.003 Qg

SIERRA-SL-12 0 94 6 4.0 0.042 Tc

SIERRA-SL-13 0 100 0 0.1 0.001 Qg
92 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B1. Land-use percentages, septic tank density, leaking or formerly leaking underground fuel tank (LUFT) density, and geologic 

unit for wells sampled by the USGS for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring 

and Assessment (GAMA) Priority Basin Project.—Continued

[Geologic unit: Granitic aquifer lithology: grMz, Mesozoic granitic rocks. Metamorphic aquifer lithology: J, Jurassic marine metasedimentary rocks; m, 

Mesozoic/Paleozoic metavolcanic/metasedimentary rocks; mv, Mesozoic/Paleozoic metavolcanic rocks; Mzv, Mesozoic metavolcanic rocks; Pz, Paleozoic 

marine metasedimentary rocks; Pzv, Paleozoic metavolcanic rocks; um, ultramafic rocks. Sedimentary aquifer lithology: Q, Holocene alluvial sediment; Qg, 

Holocene/Quaternary glacial sediment; Tc, Tertiary non-marine sediment; Mc, Miocene non-marine sediment; Ec, Eocene non-marine sediment. Volcanic

aquifer lithology: Q, Quaternary volcanic rocks; Tv, Tertiary volcanic rocks; Tvp, Tertiary pyroclastic rocks; Ti, Tertiary volcanic dikes. Abbreviations: 

tanks/km2, number of tanks per square kilometer; –, not available]

GAMA well 

identification number

Land-use percentages1 Septic density2

(tanks/km2)

LUFT density3

(tanks/km2) Geologic unit4

Agricultural Natural Urban

Volcanic aquifer lithology

SIERRA-V-01 0 96 4 1.2 0.695 Tvp

SIERRA-V-02 0 39 61 117.3 0.018 Tvp

SIERRA-V-03 0 100 0 0.0 0.001 Qv

SIERRA-VL-01 7 93 0 0.3 0.002 Ti

SIERRA-VL-02 0 100 0 16.3 0.006 Tvp

SIERRA-VL-03 0 100 0 0.3 0.002 Tvp

SIERRA-VL-04 0 99 1 14.8 0.015 Tvp

SIERRA-VL-05 0 100 0 1.4 0.007 Tvp

SIERRA-VL-06 0 100 0 1.3 0.007 Tv

SIERRA-VL-07 0 100 0 0.2 0.006 Tvp

SIERRA-VL-08 0 97 3 1.9 0.004 Qv

SIERRA-VL-09 0 100 0 1.2 0.005 Tvp

SIERRA-VL-10 0 100 0 5.8 0.018 Tvp

SIERRA-VL-11 0 84 16 30.7 0.075 Tvp

SIERRA-VL-12 0 100 0 0.3 0.004 Tvp

1

Land-use percentages within 500-meter radius of well site (Johnson and Belitz, 2009).

2

Septic tank density within 500-meter radius of well site, based on data from U.S. Census Bureau (1990).

3

LUFT density with 500-meter radius of well site, based on locations from California State Water Resources Control Board (2007).

4

Geologic units from geologic map of California (Saucedo and others, 2000).

5

Geologic unit based on geologic map was Tvp (volcanic aquifer lithology); geologic unit changed to grMz (granitic aquifer lithology) based on driller’s 

log.

6

Geologic unit based on geologic map was Q (sedimentary aquifer lithology); geologic unit changed to Pzv (metamorphic aquifer lithology) based on 

driller’s log and geologic map.

7

Geologic unit based on geologic map was Ec (sedimentary aquifer lithology); geologic unit changed to J (metamorphic aquifer lithology) based on driller’s 

log and geologic map.

8

Geologic unit based on geologic map was um (metamorphic aquifer lithology); geologic unit changed to Mzv (metamorphic aquifer lithology) based on 

driller’s log and geologic map.

9

Geologic unit based on geologic map was water; geologic unit changed to Q (sedimentary aquifer lithology) based on driller’s log.

10Geologic unit based on geologic map was M (metamorphic aquifer lithology); changed to Q (sedimentary aquifer lithology) based on driller’s log.
Appendix B. Attribution of Ancillary Data 93

Geologic time is divided into four eras: Cenozoic 

(65.5 Ma to present), Mesozoic (251 Ma to 65.5 Ma), 

Paleozoic (542 Ma to 251 Ma), and Precambrian 

(approximately 3,900 Ma to 542 Ma) (Walker and Geissman, 

2009). The Cenozoic Era consists of the Tertiary (65.5 Ma 

to 2.6 Ma) and Quaternary (2.6 Ma to present) periods. The 

Tertiary period consists of the Paleocene (65.5 Ma to 55.8 Ma), 

Eocene (55.8 Ma to 33.9 Ma), Oligocene (33.9 Ma to 

23.0 Ma), Miocene (23.0 to 5.3 Ma), and Pliocene (5.3 Ma to 

2.6 Ma) epochs. The Quaternary period consists of the Pleistocene (2.6 Ma to 10 ka) and Holocene (10 ka to present) epochs.

Table B1 lists the geologic units for wells in the four 

aquifer lithologic classes (granitic, metamorphic, sedimentary, 

and volcanic). The percentage of each grid cell assigned to 

each of the four aquifer lithologies is listed in table B2.

Site Information and Hydrologic Conditions

Well construction data were obtained primarily from driller’s logs. In locations where driller’s logs were not available, 

well construction data were obtained from ancillary records 

from well owners or the USGS National Water Information System database. The procedures used to verify well identifications 

were described by Shelton and others (2010). Well depths and 

the depths to the top and bottom of the screened or open interval 

for the USGS-grid wells are listed in table B3. Wells drilled in 

hard rock commonly do not have casings; the borehole is left 

open. For these wells, the top of the screened or open interval 

was defined as the base of the sanitary seal, and the bottom was

defined as the depth of the well. 

Sites were classified as either production wells or springs. 

Production wells pump the groundwater from the aquifer 

into a distribution system. Sites were classified as springs if 

water could flow from the aquifer into the distribution system 

without a pump and if the well was either drilled horizontally 

or had no borehole. Driller’s logs for springs reported 

installation of horizontal boreholes.

The climate at each well site was represented by an 

aridity index (United Nations Educational, Scientific, and 

Cultural Organization, 1979; United Nations Environment 

Programme, 1997) (table B3):

average annual precipitation aridity index average annual evapotranspiration = .

Higher values of the index correspond to wetter conditions. 

Average annual precipitation for each well site was 

quantified using the PRISM average annual precipitation for 

1971–2000 geographic information system (GIS) coverage 

(PRISM Climate Group, Oregon State University, 2007). 

Average annual evapotranspiration for each well site was 

extracted from a GIS coverage modified from Flint and 

Flint (2007). The modification consisted of calibrating the 

evapotranspiration values to the measured California Irrigation 

Management Information System reference evapotranspiration 

values (California Irrigation Management Information System, 

2005; Alan Flint, U.S. Geological Survey California Water 

Science Center, oral commun., 2009).

Table B2. Percentage of area of grid cells assigned to the four 

aquifer lithologic classes, Sierra Nevada Regional (SNR) study 

unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.

[Average cell area is 2,160 square kilometers (km2) (standard deviation 

20 km2)]

Cell

Aquifer lithology (percent of cell area)

Granitic 

rocks

Metamorphic 

rocks

Sedimentary 

deposits

Volcanic 

rocks

1 10 87 2 1

2 17 76 1 5

3 18 64 4 14

4 24 61 3 12

5 22 58 0 20

6 12 59 10 19

7 33 3 15 49

8 22 16 27 34

9 25 37 8 30

10 36 28 3 33

11 25 60 0 16

12 11 86 1 2

13 66 32 1 1

14 50 49 2 0

15 63 24 10 3

16 65 2 2 31

17 56 1 2 41

18 27 7 26 40

19 72 16 8 3

20 82 4 13 1

21 75 12 12 1

22 75 24 0 0

23 75 22 3 0

24 74 15 11 0

25 63 14 11 12

26 78 11 11 0

27 83 11 5 1

28 82 15 1 2

29 90 5 4 1

30 75 12 10 3

Hydrologic conditions in the Sierra Nevada 

hydrogeologic province vary with elevation and latitude, 

among other factors. The elevation of the well head or spring 

at the land surface was used as a proxy for relative position in 

the groundwater flow system. Elevations were obtained from 

U.S. Geological Survey digital elevation GIS coverage and 

are reported in feet relative to the North American Vertical 

Datum of 1988 (NAVD 88) (table B3). Latitude was reported 

in degrees relative to the North American Datum of 1983 

(NAD 83) and used as a proxy for position in the north-tosouth gradient of precipitation and temperature in California.
94 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B3. Hydrologic conditions and well construction information for wells sampled by the U.S. Geological Survey (USGS) for 

the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Depth classification: spring, no vertically drilled hole and groundwater emerges at the land surface without a pump; shallow well, bottom of screened or open 

interval < 170 feet below land surface datum (ft bls); overlapping well, top of screened or open interval < 170 ft bls and bottom of screened or open interval 

> 170 ft bls; deep well, top of screened or open interval > 170 ft bls; unknown well, no construction information available for the well. Abbreviations: NAD 83, 

North American Datum of 1983; NAVD 88, North American Vertical Datum of 1988; –, no data available; na, not applicable; <, less than; >, greater than]

GAMA well 

identification 

number

Well construction information Hydrologic conditions

Well 

depth

(ft bls)

Top of 

screened or 

open interval

(ft bls)

Bottom of 

screened or 

open interval

(ft bls)

Depth classification

[spring (SP), 

shallow well (SH), 

overlapping well (OL), 

deep well (DP)]

Elevation of 

land-surface 

datum

(ft above 

NAVD 88)

Aridity index

(dimensionless)

Latitude

(degrees in 

NAD 83)

Granitic aquifer lithology

SIERRA-G-01 600 300 600 DP 3,248 0.28 35.25

SIERRA-G-02 na na na SP 5,964 0.76 35.72

SIERRA-G-03 300 30 300 OL 2,985 0.50 35.88

SIERRA-G-04 na na na SP 7,600 0.93 36.13

SIERRA-G-05 120 120 120 SH 823 0.38 36.44

SIERRA-G-06 900 100 900 OL 3,105 0.75 37.46

SIERRA-G-07 700 52 700 OL 3,401 0.76 37.33

SIERRA-G-08 120 57 120 SH 5,606 0.78 37.11

SIERRA-G-09 na na na SP 7,460 0.99 36.70

SIERRA-G-10 105 105 105 SH 6,248 1.73 38.33

SIERRA-G-11 650 – – OL or DP 3,777 0.88 38.09

SIERRA-G-12 675 57 675 OL 3,870 0.76 37.86

SIERRA-G-13 400 60 400 OL 2,763 1.00 38.66

SIERRA-G-14 400 50 400 OL 6,755 1.29 38.80

SIERRA-G-15 480 60 480 OL 200 0.47 38.89

SIERRA-G-16 na na na SP 8,596 0.55 36.58

SIERRA-G-17 na na na SP 9,800 0.66 37.18

SIERRA-G-18 na na na SP 10,110 0.75 37.46

SIERRA-GL-01 280 160 280 OL 3,646 0.27 35.68

SIERRA-GL-02 400 52 400 OL 2,079 0.69 37.97

SIERRA-GL-03 na na na SP 10,280 1.18 37.80

SIERRA-GL-04 na na na SP 6,584 1.13 38.95

SIERRA-GL-05 150 50 150 SH 5,637 1.37 38.92

SIERRA-GL-06 na na na SP 6,019 1.69 39.63

SIERRA-GL-07 100 65 100 SH 1,687 0.84 39.14

SIERRA-GL-08 100 – – SH 5,267 1.99 39.88

SIERRA-GL-09 205 50 205 OL 2,320 1.28 39.63

SIERRA-GL-10 610 470 610 DP 5,647 0.58 39.87

Metamorphic aquifer lithology

SIERRA-M-01 400 – – OL or DP 1,521 0.59 37.93

SIERRA-M-02 440 – – OL or DP 1,103 0.59 38.47

SIERRA-M-03 na na na SP 3,903 0.98 40.17

SIERRA-M-04 na na na SP 6,424 1.60 39.70

SIERRA-M-05 – – – Unknown well 3,075 1.29 39.28
Appendix B. Attribution of Ancillary Data 95

Table B3. Hydrologic conditions and well construction information for wells sampled by the U.S. Geological Survey (USGS) for 

the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Depth classification: spring, no vertically drilled hole and groundwater emerges at the land surface without a pump; shallow well, bottom of screened or open 

interval < 170 feet below land surface datum (ft bls); overlapping well, top of screened or open interval < 170 ft bls and bottom of screened or open interval 

> 170 ft bls; deep well, top of screened or open interval > 170 ft bls; unknown well, no construction information available for the well. Abbreviations: NAD 83, 

North American Datum of 1983; NAVD 88, North American Vertical Datum of 1988; –, no data available; na, not applicable; <, less than; >, greater than]

GAMA well 

identification 

number

Well construction information Hydrologic conditions

Well 

depth

(ft bls)

Top of 

screened or 

open interval

(ft bls)

Bottom of 

screened or 

open interval

(ft bls)

Depth classification

[spring (SP), 

shallow well (SH), 

overlapping well (OL), 

deep well (DP)]

Elevation of 

land-surface 

datum

(ft above 

NAVD 88)

Aridity index

(dimensionless)

Latitude

(degrees in 

NAD 83)

Metamorphic aquifer lithology—Continued

SIERRA-M-06 190 150 190 OL 3,361 1.56 39.52

SIERRA-ML-01 130 70 130 SH 3,848 0.26 35.10

SIERRA-ML-02 165 140 165 SH 2,967 0.24 35.59

SIERRA-ML-03 190 50 190 OL 3,522 0.41 35.72

SIERRA-ML-04 – – – Unknown well 3,554 0.37 35.93

SIERRA-ML-05 300 60 300 OL 4,203 0.71 36.70

SIERRA-ML-06 75 30 75 SH 962 0.35 36.43

SIERRA-ML-07 300 – – OL or DP 4,813 0.74 36.14

SIERRA-ML-08 122 – – SH 872 0.44 37.61

SIERRA-ML-09 250 124 250 OL 3,699 0.74 37.27

SIERRA-ML-10 275 – – OL or DP 1,546 0.61 38.04

SIERRA-ML-11 na na na SP 8,120 1.07 36.45

SIERRA-ML-12 360 100 360 OL 3,094 0.83 37.82

SIERRA-ML-13 1000 60 890 OL 2,080 0.75 38.44

SIERRA-ML-14 na na na SP 6,780 1.18 38.88

SIERRA-ML-15 171 – – SH 3,443 0.88 39.94

SIERRA-ML-16 70 – – SH 8,309 0.87 37.68

SIERRA-ML-17 245 100 245 OL 1,343 0.58 38.36

SIERRA-ML-18 225 55 225 OL 1,920 0.88 39.01

Sedimentary aquifer lithology

SIERRA-S-01 120 78 120 SH 2,653 0.20 35.67

SIERRA-S-02 600 130 310 OL 6,304 0.89 38.86

SIERRA-S-03 520 110 520 OL 4,845 0.51 39.81

SIERRA-SL-01 400 200 400 DP 4,183 0.25 35.11

SIERRA-SL-02 55 10 55 SH 2,643 0.19 35.74

SIERRA-SL-03 155 20 155 SH 783 0.24 36.10

SIERRA-SL-04 360 259 360 DP 563 0.14 35.44

SIERRA-SL-05 na na na SP 5,920 1.11 38.34

SIERRA-SL-06 490 260 490 DP 5,633 0.49 38.77

SIERRA-SL-07 800 360 780 DP 3,944 0.91 37.74

SIERRA-SL-08 200 110 196 OL 3,550 0.94 40.08

SIERRA-SL-09 na na na SP 5,174 0.65 39.56

SIERRA-SL-10 163 – – SH 9,918 0.41 36.45

SIERRA-SL-11 300 50 280 OL 5,212 0.20 37.32
96 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B3. Hydrologic conditions and well construction information for wells sampled by the U.S. Geological Survey (USGS) for 

the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Depth classification: spring, no vertically drilled hole and groundwater emerges at the land surface without a pump; shallow well, bottom of screened or open 

interval < 170 feet below land surface datum (ft bls); overlapping well, top of screened or open interval < 170 ft bls and bottom of screened or open interval 

> 170 ft bls; deep well, top of screened or open interval > 170 ft bls; unknown well, no construction information available for the well. Abbreviations: NAD 83, 

North American Datum of 1983; NAVD 88, North American Vertical Datum of 1988; –, no data available; na, not applicable; <, less than; >, greater than]

GAMA well 

identification 

number

Well construction information Hydrologic conditions

Well 

depth

(ft bls)

Top of 

screened or 

open interval

(ft bls)

Bottom of 

screened or 

open interval

(ft bls)

Depth classification

[spring (SP), 

shallow well (SH), 

overlapping well (OL), 

deep well (DP)]

Elevation of 

land-surface 

datum

(ft above 

NAVD 88)

Aridity index

(dimensionless)

Latitude

(degrees in 

NAD 83)

Sedimentary aquifer lithology—Continued

SIERRA-SL-12 77 77 77 SH 505 0.87 39.74

SIERRA-SL-13 na na na SP 7,980 0.86 37.03

Volcanic aquifer lithology

SIERRA-V-01 na na na SP 6,758 1.34 39.18

SIERRA-V-02 702 280 702 DP 2,364 1.34 39.82

SIERRA-V-03 220 60 220 OL 7,654 0.60 37.63

SIERRA-VL-01 93 – – SH 2,801 0.21 35.31

SIERRA-VL-02 580 – – OL or DP 5,570 0.90 38.15

SIERRA-VL-03 280 131 280 OL 5,677 0.57 38.69

SIERRA-VL-04 307 57 307 OL 3,072 0.81 37.85

SIERRA-VL-05 500 445 500 DP 3,591 0.95 38.58

SIERRA-VL-06 383 363 383 DP 5,596 0.59 39.37

SIERRA-VL-07 380 51 380 OL 5,391 1.79 39.32

SIERRA-VL-08 na na na SP 4,551 0.39 40.42

SIERRA-VL-09 na na na SP 5,340 0.71 39.83

SIERRA-VL-10 na na na SP 4,564 1.59 39.32

SIERRA-VL-11 400 50 400 OL 4,015 0.89 38.04

SIERRA-VL-12 930 235 930 DP 3,991 1.17 39.06

Groundwater Age Classification

As noted earlier, groundwater dating techniques 

provide estimates of the time elapsed since a given parcel 

of groundwater entered the saturated zone. The techniques 

used in this report to estimate groundwater residence times 

or “age” were those based on tritium (for example: Tolstikhin 

and Kamenskiy, 1969; Torgersen and others, 1979) and 14C 

activities (for example: Vogel and Ehhalt, 1963; Plummer and 

others, 1993).

Tritium is a short-lived radioactive isotope of hydrogen 

with a half-life of 12.32 years (Lucas and Unterweger, 2000). 

Produced naturally in the atmosphere from the interaction of 

cosmogenic radiation with nitrogen (Craig and Lal, 1961), or 

anthropogenically through above-ground nuclear explosions 

and the operation of nuclear reactors, tritium enters the 

hydrologic cycle following exchange with protium (1

H) 

in water to form “tritiated water.” Above-ground nuclear 

explosions resulted in a large increase in tritium values in 

precipitation, beginning in about 1952 and peaking in 1963 at 

values over 1,000 tritium units (TU) in the northern hemisphere (Michel, 1989).

A range of tritium values from 0.2 to 1.0 TU have been 

used in previous investigations as minimum thresholds for 

indicating the presence of water that has been in contact 

with the atmosphere since 1952 (Michel, 1989; Plummer 

and others, 1993; Michel and Schroeder, 1994; Clark and 

Fritz, 1997; Manning and others, 2005; Landon and others, 

2010). For samples collected for the SNR study unit in 

2008, two groundwater age thresholds were defined on the 

basis of tritium values: tritium values greater than 0.25 TU 

were deemed to indicate the presence of some groundwater 

recharged since 1952, and tritium values greater than 1.5 

were considered to indicate a predominance of groundwater 

recharged since 1952. The lower threshold of 0.25 TU was 

selected because background tritium values in California 

precipitation under natural conditions are expected to range 
Appendix B. Attribution of Ancillary Data 97

from 2 to 6 TU (Robert Michel, U.S. Geological Survey, 

written commun., 2013), and values in precipitation at the 

latitudes and longitudes corresponding to the SNR study unit 

are approximately 5 to 6 TU (Michel, 1989). Radioactive 

decay of tritium in water with a tritium value of 6 TU in 

1950 would have a tritium value of 0.25 TU in 2008. The 

upper threshold of 1.5 TU was selected because all samples 

with tritium less than 1.5 TU had 14C activities of less than 

100 percent modern carbon (pmC), as determined using the 

approach described below. 14C is a widely used chronometer that is based on the 

radiocarbon content of organic and inorganic carbon. 14C is 

formed in the atmosphere by the interaction of cosmic-ray 

neutrons with nitrogen and, to a lesser degree, with oxygen 

and carbon. 14C is incorporated into carbon dioxide and mixed 

throughout the atmosphere. The carbon dioxide enters the 

hydrologic cycle because it dissolves in precipitation and 

surface water in contact with the atmosphere. As a result, 

dissolved inorganic carbon species (primarily carbonic acid, 

bicarbonate, and carbonate) are commonly used for 14C 

dating of groundwater. 14C activity in groundwater, expressed 

as pmC, reflects the time elapsed since groundwater was 

last exposed to the atmospheric 14C. 14C has a half-life of 

5,730 years and, as such, can be used to estimate groundwater 

ages ranging from 1,000 to approximately 30,000 years before 

present (Clark and Fritz, 1997). 14C data may be reported in units of percent modern (pM) 

or in units of pmC. 14C data for the SNR study unit in Shelton 

and others (2010) are given in pM units as reported by the analyzing laboratory. 14C data in pM units have been normalized 

for carbon isotopic fractionation based on a δ13C value of –25 

per mil (‰). The un-normalized 14C data in pmC units are used 

in this report. Data were converted from pM to pmC using following equation derived from Plummer and others (2004): 2 13

2

1

1,000

0.975

C pM

pmC

  δ   +

  = , (B1)

where 

pM is the 14C value in units of pM, and

δ13C is the measured 13C composition in units of 

per mil.

The 14C age (residence time, presented in years) is calculated based on the decrease in 14C content as a result of radioactive decay since groundwater recharge, relative to an assumed 

initial 14C content (Clark and Fritz, 1997). Groundwater ages 

are reported as radiocarbon ages, in years before 1950:

0 5,568 1950

radiocarbon age ln ln(2) 1.029

A Dsamp

A

  − =× −     , (B2)

where 

5,568 is the Libby half-life for 14C, in years,

A0 is the initial 14C content, assumed to be 

99 pmC,

A is the measured 14C content, in pmC, and

Dsamp is the date of sample collection in 

decimal years.

Calculated radiocarbon ages in this study are referred 

to as “uncorrected” because they have not been adjusted to 

consider water-rock interactions, such as exchanges with 

sedimentary sources of carbon (Fontes and Garnier, 1979). 

Estimated errors in radiocarbon ages are up to ±20 percent. 

Groundwater with a 14C content 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 

content in “modern” carbon does not include the excess 14C 

produced in the atmosphere by above-ground nuclear weapons 

testing (Clark and Fritz, 1997). For samples collected for 

the SNR study unit in 2008, 14C values greater than 90 pmC 

were defined as indicating the presence of some groundwater 

recharged since 1952. This threshold of 90 pmC was selected 

because all samples with tritium values less than 0.25 TU also 

had 14C values less than 90 pmC.

The age distributions in groundwater samples were 

classified as pre-modern, modern, and mixed using the 

thresholds for tritium and 14C values as shown in table B4. 

Samples with tritium ≥1.5 TU and 14C ≥ 90 pmC were 

classified as modern; samples with tritium <0.25 TU and 

14C < 90 pmC were classified as pre-modern; all other samples 

were classified as mixed. Tritium concentrations, uncorrected 

14C age, and age classifications for the samples are listed in 

table B5.

Although more sophisticated lumped parameter models 

have been introduced for analyzing age distributions that 

incorporate mixing (for example, Cook and Böhlke, 2000), 

use of these alternative models to characterize age mixtures 

was beyond the scope of this report. Rather, classification 

into modern (recharged after 1952), mixed, and pre-modern 

(recharged before 1952) categories was sufficient to provide 

an appropriate and useful characterization for examining 

groundwater quality.

Table B4. Tritium and carbon-14 threshold values used for 

groundwater age classification for the Sierra Nevada Regional 

study (SNR) unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project.

[Abbreviations: TU, tritium units; pmC, percent modern carbon; >, greater 

than; <, less than; ≥, greater than or equal to]

Age class Number of 

samples

Threshold values

Tritium (TU) 14C (pmC)

Pre-modern 7 <0.25 <90

Mixed 14 >0.25 and <1.5 any

Mixed 17 ≥1.5 <90

Modern 42 ≥1.5 ≥90

Modern or mixed 3 ≥1.5 No data
98 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B5. Tritium and carbon-14 data and groundwater age classifications for wells sampled by the U.S. Geological Survey (USGS) 

for the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Groundwater age classification based on tritium and carbon-14 data (see table B4). Abbreviations: δ13C, delta carbon-13 ; 14C, carbon-14; TU, tritium units; 

–, not available; <, less than]

GAMA well 

identification number Tritium (TU) Percent modern carbon

Uncorrected 14C age 

(years) δ13C Groundwater age 

classification

Granitic aquifer lithology

SIERRA-G-01 0.25 60 4,110 –14.5 Pre-modern

SIERRA-G-02 4.16 90 <1,000 –16.7 Modern

SIERRA-G-03 0.34 72 2,540 –14.4 Mixed

SIERRA-G-04 2.85 110 <1,000 –20.7 Modern

SIERRA-G-05 2.13 111 <1,000 –17.9 Modern

SIERRA-G-06 0.68 82 1,520 –19.1 Mixed

SIERRA-G-07 3.63 107 <1,000 –20.9 Modern

SIERRA-G-08 2.44 106 <1,000 –20.9 Modern

SIERRA-G-09 2.88 111 <1,000 –20.7 Modern

SIERRA-G-10 2.94 103 <1,000 –16.3 Modern

SIERRA-G-11 3.04 105 <1,000 –19.5 Modern

SIERRA-G-12 2.50 107 <1,000 –17.4 Modern

SIERRA-G-13 2.60 110 <1,000 –19.6 Modern

SIERRA-G-14 2.69 108 <1,000 –20.8 Modern

SIERRA-G-15 1.50 66 3,270 –17.7 Mixed

SIERRA-G-16 4.51 80 1,700 –18.3 Mixed

SIERRA-G-17 3.54 101 <1,000 –16.4 Modern

SIERRA-G-18 4.76 88 <1,000 –15.3 Mixed

SIERRA-GL-01 1.53 106 <1,000 –15.5 Modern

SIERRA-GL-02 2.69 107 <1,000 –19.7 Modern

SIERRA-GL-03 4.89 76 2,180 –13.2 Mixed

SIERRA-GL-04 3.85 106 <1,000 –17.0 Modern

SIERRA-GL-05 5.42 106 <1,000 –21.1 Modern

SIERRA-GL-06 2.47 115 <1,000 –21.1 Modern

SIERRA-GL-07 3.22 117 <1,000 –19.0 Modern

SIERRA-GL-08 2.53 110 <1,000 –19.8 Modern

SIERRA-GL-09 2.69 116 <1,000 –22.2 Modern

SIERRA-GL-10 4.04 81 1,590 –15.4 Mixed

Metamorphic aquifer lithology

SIERRA-M-01 1.37 74 2,380 –15.3 Mixed

SIERRA-M-02 1.47 62 3,730 –16.2 Mixed

SIERRA-M-03 0.56 – – – Mixed

SIERRA-M-04 3.22 66 3,290 –14.1 Mixed

SIERRA-M-05 1.34 71 2,720 –20.5 Mixed

SIERRA-M-06 3.10 96 <1,000 –20.4 Modern

SIERRA-ML-01 1.56 73 2,520 –11.5 Mixed

SIERRA-ML-02 2.47 110 <1,000 –15.3 Modern

SIERRA-ML-03 2.10 98 <1,000 –16.1 Modern

SIERRA-ML-04 2.53 44 6,470 –6.6 Modern or Mixed1

SIERRA-ML-05 3.47 119 <1,000 –18.9 Modern

Table B5. Tritium and carbon-14 data and groundwater age classifications for wells sampled by the U.S. Geological Survey (USGS) 

for the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.
Appendix B. Attribution of Ancillary Data 99

Table B5. Tritium and carbon-14 data and groundwater age classifications for wells sampled by the U.S. Geological Survey (USGS) 

for the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Groundwater age classification based on tritium and carbon-14 data (see table B4). Abbreviations: δ13C, delta carbon-13 ; 14C, carbon-14; TU, tritium units; 

–, not available; <, less than]

GAMA well 

identification number Tritium (TU) Percent modern carbon

Uncorrected 14C age 

(years) δ13C Groundwater age 

classification

Metamorphic aquifer lithology—Continued

SIERRA-ML-06 2.85 111 <1,000 –16.1 Modern

SIERRA-ML-07 0.21 51 5,310 –10.4 Pre-modern

SIERRA-ML-08 3.00 65 3,430 –14.1 Mixed

SIERRA-ML-09 1.59 91 <1,000 –19.7 Modern

SIERRA-ML-10 2.75 79 1,880 –16.5 Mixed

SIERRA-ML-11 3.73 89 <1,000 –15.6 Mixed

SIERRA-ML-12 2.88 – – –17.8 Modern or Mixed

SIERRA-ML-13 2.31 93 <1,000 –14.9 Modern

SIERRA-ML-14 4.07 94 <1,000 –18.5 Modern

SIERRA-ML-15 2.94 83 1,470 –15.3 Mixed

SIERRA-ML-16 1.84 96 <1,000 –15.7 Modern

SIERRA-ML-17 2.10 92 <1,000 –17.5 Modern

SIERRA-ML-18 2.94 82 1,580 –18.2 Mixed

Sedimentary aquifer lithology

SIERRA-S-01 2.50 123 <1,000 –13.1 Modern

SIERRA-S-02 2.50 101 <1,000 –19.9 Modern

SIERRA-S-03 1.37 93 <1,000 –17.1 Mixed

SIERRA-SL-01 0.18 88 1,000 –12.4 Pre-modern

SIERRA-SL-02 3.82 24 11,340 –5.1 Modern or Mixed1

SIERRA-SL-03 2.66 106 <1,000 –12.5 Modern

SIERRA-SL-04 -0.09 1 38,860 –14.3 Pre-modern

SIERRA-SL-05 2.82 99 <1,000 –17.5 Modern

SIERRA-SL-06 0.34 92 <1,000 –16.3 Mixed

SIERRA-SL-07 2.75 105 <1,000 –17.6 Modern

SIERRA-SL-08 1.97 96 <1,000 –19.5 Modern

SIERRA-SL-09 0.28 89 <1,000 –17.8 Mixed

SIERRA-SL-10 5.26 85 1,230 –17.3 Mixed

SIERRA-SL-11 2.19 98 <1,000 –15.2 Modern

SIERRA-SL-12 0.62 98 <1,000 –18.0 Mixed

SIERRA-SL-13 2.75 109 <1,000 –19.8 Modern

Volcanic aquifer lithology

SIERRA-V-01 1.66 99 <1,000 –18.2 Modern

SIERRA-V-02 0.90 92 <1,000 –20.5 Mixed

SIERRA-V-03 3.73 61 3,910 –11.8 Mixed

SIERRA-VL-01 2.10 86 1,140 –11.5 Mixed

SIERRA-VL-02 1.69 91 <1,000 –17.9 Modern

SIERRA-VL-03 2.31 62 3,840 –12.6 Mixed

SIERRA-VL-04 -0.12 86 1,170 –19.4 Pre-modern

SIERRA-VL-05 0.84 60 4,070 –19.9 Mixed

SIERRA-VL-06 0.06 27 10,390 –15.8 Pre-modern
100 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B5. Tritium and carbon-14 data and groundwater age classifications for wells sampled by the U.S. Geological Survey (USGS) 

for the Sierra Nevada Regional (SNR) study unit, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin 

Project.—Continued

[Groundwater age classification based on tritium and carbon-14 data (see table B4). Abbreviations: δ13C, delta carbon-13 ; 14C, carbon-14; TU, tritium units; 

–, not available; <, less than]

GAMA well 

identification number Tritium (TU) Percent modern carbon

Uncorrected 14C age 

(years) δ13C Groundwater age 

classification

Volcanic aquifer lithology—Continued

SIERRA-VL-07 2.28 65 3,370 –14.1 Mixed

SIERRA-VL-08 1.22 97 <1,000 –16.1 Mixed

SIERRA-VL-09 0.34 98 <1,000 –18.3 Mixed

SIERRA-VL-10 2.35 111 <1,000 –23.4 Modern

SIERRA-VL-11 3.60 102 <1,000 –18.8 Modern

SIERRA-VL-12 0.25 54 4,910 –17.1 Pre-modern

1

Samples are classified as modern or mixed because the δ13C value suggests the dissolved carbonate system has been strongly affected by interaction with 

sedimentary carbon, which likely also altered the 14C percent modern carbon value (for example, Clark and Fritz, 1997).

Geochemical Conditions

Oxidation-reduction (redox) conditions may influence 

the mobility of many organic and inorganic constituents 

(McMahon and Chapelle, 2008). Redox conditions along 

groundwater flow paths commonly proceed along a welldocumented sequence of Terminal Electron Acceptor 

Processes (TEAPs), in which a single TEAP typically 

dominates at a particular time and aquifer location (Chapelle 

and others, 1995; Chapelle, 2001). As electron acceptors are 

depleted along groundwater flow paths, the typical TEAP 

sequence is oxygen reduction (oxic), followed in turn by 

nitrate reduction, manganese reduction, iron reduction, sulfate 

reduction, and methanogenesis. This sequence is the order 

predicted from equilibrium thermodynamics and corresponds 

to progressively decreasing oxidation-reduction potentials. 

However, the kinetics of many TEAPs are slow, and the reactions typically only proceed at significant rates when mediated 

by biological catalysis (Stumm and Morgan, 1996; Appelo 

and Postma, 2005). Microbes present in groundwater and on 

aquifer sediment or rock produce enzymes that catalyze the 

reactions. The microbes couple reduction of each of these 

electron acceptors with the oxidation of organic matter to produce energy needed for metabolism or growth. Groundwater 

samples may contain redox-active chemical species that suggest that more than one TEAP is operating. Evidence for more 

than one TEAP may indicate mixing of waters from different 

redox zones upgradient of the well, a well that is screened 

across more than one redox zone, or spatial heterogeneity in 

microbial activity in the aquifer. In addition, different redox 

couples may not be consistent with one another, indicating the 

presence of electrochemical disequilibrium and complicating 

the assessment of redox conditions (Lindberg and Runnels, 

1984; Appelo and Postma, 2005).

Oxidation-reduction conditions were classified on the basis 

of DO, nitrate, manganese, and iron concentrations by using a 

modified version of the classification scheme of McMahon and 

Chapelle (2008) and Jurgens and others (2009) (table B6). The 

modification was that the DO threshold for separating oxic from 

anoxic groundwater was increased from 0.5 mg/L to 1 mg/L 

(Fram and Belitz, 2012). For a majority of the sites (66 of the 

83 sites [80 percent]), the groundwater was classified as oxic 

(DO ≥ 1 mg/L). Anoxic conditions (DO < 1 mg/L), present in 

17 of the 83 wells (20 percent), were further classified as either 

suboxic, nitrate-reducing, manganese-reducing, or manganeseand iron-reducing (table B7).

Arsenic and iron occur as different species depending on 

the redox state of the groundwater. The ratio of the amount of 

the more oxidized species to the amount of the more reduced 

species for each constituent may provide information about the 

progress of the TEAP involving the constituent. The following 

ratios are reported in table B7:

• As+5/As+3, where As+5 is the amount of arsenic present in the more oxidized +5 oxidation state (arsenate) 

and As+3 is the amount of arsenic present in the more 

reduced +3 oxidation state (arsenite);

• Fe+3/Fe+2, where Fe+3 is the amount of iron present in 

the more oxidized +3 oxidation state (ferric iron) and 

Fe+2 is the amount of iron present in the more reduced 

+2 oxidation state (ferrous iron).

Total concentrations of As and Fe and concentrations of 

As+3 and Fe+2 were reported by Shelton and others (2010). The 

concentrations of As+5 and Fe+3 were calculated from these 

data by difference. As+5/As+3 was reported as greater than 

10 if the total arsenic concentration was above the reporting 

limit and As+3 was not detected. As+5/As+3 was reported as less 

than 0.01 if the total arsenic concentration equaled the As+3

concentration. Similarly, Fe+3/Fe+2 was reported as greater than 

10 if the total iron was above the reporting limit and Fe+2 was 

not detected, and as less than 0.01 if the total iron concentration equaled the Fe+2 concentration.
Appendix B. Attribution of Ancillary Data 101

Table B6. Dissolved oxygen, nitrate, manganese, and iron concentration threshold values used for oxidation-reduction classification 

for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority 

Basin Project.

[Anoxic sub-classes: NO3-red, nitrate-reducing; Mn-red, manganese-reducing; MnFe-red, manganese and iron reducing. Units: mg/L, milligrams per liter; 

μg/L, micrograms per liter. Abbreviations: <, less than; ≥, greater than or equal to]

Class Number 

of samples

Threshold values

Dissolved oxygen 

(mg/L)

Nitrate-N 

(mg/L)

Manganese 

(μg/L)

Iron 

(μg/L)

Oxic 66 ≥1 Any <50 <100

Anoxic—suboxic 6 <1 <0.5 <50 <100

Anoxic—NO3

-red 3 <1 ≥0.5 <50 <100

Anoxic—Mn-red 1 <1 <0.5 ≥50 <100

Anoxic—MnFe-red 7 <1 <0.5 ≥50 ≥100

Table B7. Oxidation-reduction classification, dissolved oxygen concentrations, pH, and oxidation-reduction species ratios for arsenic 

and iron for wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Oxidation-reduction classification: NO3-red, nitrate-reducing; Mn-red, manganese-reducing; MnFe-red, manganese- and iron-reducing. See table B6 for 

definitions of classes. Ratios of oxidized to reduced species of metals: As+5/As+3, ratio of the amount of arsenic in the +5 oxidation state (arsenate) to the 

amount in the +3 oxidation state (arsenite); Fe+3/Fe+2, ratio of the amount of iron in the +3 oxidation state (ferric iron) to the amount in the +2 oxidation state 

(ferrous iron). Abbreviations: μg/L, micrograms per liter; mg/L, milligrams per liter; >, greater than; <, less than; ≤, less than or equal to; na, not available; –, 

concentration too low to measure ratio; x, not anoxic]

GAMA well 

identification 

number

pH

(standard units)

Dissolved oxygen

(mg/L)

Oxidationreduction 

classification

Sub-class for 

anoxic samples

Ratios of oxidized and reduced 

species of metals

As+5/As+3 Fe+3/Fe+2

Granitic aquifer lithology

SIERRA-G-01 7.7 0.3 Anoxic Suboxic – –

SIERRA-G-02 5.9 7.3 Oxic x – –

SIERRA-G-03 6.6 ≤0.2 Anoxic NO3

-red – –

SIERRA-G-04 7.5 na1 Oxic x – –

SIERRA-G-05 6.5 5.8 Oxic x – –

SIERRA-G-06 7.5 ≤0.2 Anoxic Suboxic – –

SIERRA-G-07 6.2 2.1 Oxic x – 0.18

SIERRA-G-08 5.8 5.2 Oxic x – –

SIERRA-G-09 5.4 7.6 Oxic x – –

SIERRA-G-10 6.4 4.7 Oxic x – –

SIERRA-G-11 6.3 9.4 Oxic x – –

SIERRA-G-12 6.6 7.5 Oxic x – –

SIERRA-G-13 6.2 9.8 Oxic x – –

SIERRA-G-14 6.3 4.8 Oxic x – –

SIERRA-G-15 9.1 ≤0.2 Anoxic Suboxic – –

SIERRA-G-16 6.4 8.4 Oxic x – –

SIERRA-G-17 8.6 9.9 Oxic x 2

>10 –

SIERRA-G-18 6.3 8.1 Oxic x – –

SIERRA-GL-01 6.9 6.6 Oxic x 3

>10 –

SIERRA-GL-02 6.3 2.6 Oxic x – –

SIERRA-GL-03 7.3 9.2 Oxic x – –

Table B7. Oxidation-reduction classification, dissolved oxygen concentrations, pH, and oxidation-reduction species ratios for arsenic 

and iron for wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
102 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table B7. Oxidation-reduction classification, dissolved oxygen concentrations, pH, and oxidation-reduction species ratios for arsenic 

and iron for wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Oxidation-reduction classification: NO3-red, nitrate-reducing; Mn-red, manganese-reducing; MnFe-red, manganese- and iron-reducing. See table B6 for 

definitions of classes. Ratios of oxidized to reduced species of metals: As+5/As+3, ratio of the amount of arsenic in the +5 oxidation state (arsenate) to the 

amount in the +3 oxidation state (arsenite); Fe+3/Fe+2, ratio of the amount of iron in the +3 oxidation state (ferric iron) to the amount in the +2 oxidation state 

(ferrous iron). Abbreviations: μg/L, micrograms per liter; mg/L, milligrams per liter; >, greater than; <, less than; ≤, less than or equal to; na, not available; –, 

concentration too low to measure ratio; x, not anoxic]

GAMA well 

identification 

number

pH

(standard units)

Dissolved oxygen

(mg/L)

Oxidationreduction 

classification

Sub-class for 

anoxic samples

Ratios of oxidized and reduced 

species of metals

As+5/As+3 Fe+3/Fe+2

Granitic aquifer lithology—Continued

SIERRA-GL-04 6.0 3.4 Oxic x – –

SIERRA-GL-05 6.9 7.9 Oxic x – –

SIERRA-GL-06 5.8 8.8 Oxic x – –

SIERRA-GL-07 6.8 7.6 Oxic x – –

SIERRA-GL-08 6.0 9.5 Oxic x – –

SIERRA-GL-09 5.5 7.3 Oxic x – –

SIERRA-GL-10 7.5 2.4 Oxic x – 2.00

Metamorphic aquifer lithology

SIERRA-M-01 7.7 ≤0.2 Anoxic Suboxic – –

SIERRA-M-02 7.2 ≤0.2 Anoxic MnFe-red – 3

0.23

SIERRA-M-03 7.4 3.9 Oxic x – –

SIERRA-M-04 7.4 6.5 Oxic x – –

SIERRA-M-05 7.0 0.3 Anoxic MnFe-red – 3

0.01

SIERRA-M-06 6.0 9.6 Oxic x – –

SIERRA-ML-01 7.3 3.1 Oxic x 2

– –

SIERRA-ML-02 7.1 6.3 Oxic x 2

>10 –

SIERRA-ML-03 7.0 0.3 Anoxic NO3

-red 2– –

SIERRA-ML-04 6.3 3.3 Oxic x – –

SIERRA-ML-05 5.9 10.0 Oxic x – –

SIERRA-ML-06 7.0 5.6 Oxic x – –

SIERRA-ML-07 7.6 1.9 Oxic x – –

SIERRA-ML-08 6.9 0.3 Anoxic NO3

-red – –

SIERRA-ML-09 6.7 4.5 Oxic x – –

SIERRA-ML-10 7.1 7.3 Oxic x 2

>10 –

SIERRA-ML-11 7.5 11.6 Oxic x – –

SIERRA-ML-12 6.8 ≤0.2 Anoxic MnFe-red – 3

<0.01

SIERRA-ML-13 7.0 2.7 Oxic x – 0.29

SIERRA-ML-14 6.9 10.8 Oxic x – –

SIERRA-ML-15 6.5 6.5 Oxic x – –

SIERRA-ML-16 7.3 ≤0.2 Anoxic MnFe-red 2

0.26 30.04

SIERRA-ML-17 6.6 7.1 Oxic x – 3.33

SIERRA-ML-18 6.6 2.1 Oxic x – –

Sedimentary aquifer lithology

SIERRA-S-01 7.3 6.6 Oxic x – –

SIERRA-S-02 8.7 3.6 Oxic x 2

>10 –

SIERRA-S-03 6.9 2.7 Oxic x – –
Appendix B. Attribution of Ancillary Data 103

Table B7. Oxidation-reduction classification, dissolved oxygen concentrations, pH, and oxidation-reduction species ratios for arsenic 

and iron for wells sampled by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued

[Oxidation-reduction classification: NO3-red, nitrate-reducing; Mn-red, manganese-reducing; MnFe-red, manganese- and iron-reducing. See table B6 for 

definitions of classes. Ratios of oxidized to reduced species of metals: As+5/As+3, ratio of the amount of arsenic in the +5 oxidation state (arsenate) to the 

amount in the +3 oxidation state (arsenite); Fe+3/Fe+2, ratio of the amount of iron in the +3 oxidation state (ferric iron) to the amount in the +2 oxidation state 

(ferrous iron). Abbreviations: μg/L, micrograms per liter; mg/L, milligrams per liter; >, greater than; <, less than; ≤, less than or equal to; na, not available; –, 

concentration too low to measure ratio; x, not anoxic]

GAMA well 

identification 

number

pH

(standard units)

Dissolved oxygen

(mg/L)

Oxidationreduction 

classification

Sub-class for 

anoxic samples

Ratios of oxidized and reduced 

species of metals

As+5/As+3 Fe+3/Fe+2

Sedimentary aquifer lithology—Continued

SIERRA-SL-01 7.5 6.1 Oxic x – –

SIERRA-SL-02 6.3 0.5 Anoxic MnFe-red 3

0.12 3<0.01

SIERRA-SL-03 7.3 1.7 Oxic x 2

>10 –

SIERRA-SL-04 8.9 ≤0.2 Anoxic Suboxic – –

SIERRA-SL-05 6.4 9.2 Oxic x – –

SIERRA-SL-06 6.8 4.8 Oxic x – –

SIERRA-SL-07 7.1 7.7 Oxic x – –

SIERRA-SL-08 6.7 2.5 Oxic x – –

SIERRA-SL-09 7.5 9.7 Oxic x – –

SIERRA-SL-10 7.0 7.5 Oxic x – –

SIERRA-SL-11 7.2 4.5 Oxic x – –

SIERRA-SL-12 7.3 0.3 Anoxic MnFe-red 2

0.05 30.15

SIERRA-SL-13 5.7 5.8 Oxic x – –

Volcanic aquifer lithology

SIERRA-V-01 7.4 9.3 Oxic x – –

SIERRA-V-02 7.0 6.2 Oxic x – –

SIERRA-V-03 6.5 4

>1 Oxic x 3>10 –

SIERRA-VL-01 7.1 4.4 Oxic x – –

SIERRA-VL-02 6.6 6.2 Oxic x – –

SIERRA-VL-03 7.9 ≤0.2 Anoxic Suboxic 0.18 0.33

SIERRA-VL-04 6.4 4.2 Oxic x – –

SIERRA-VL-05 7.2 6.4 Oxic x – –

SIERRA-VL-06 7.9 ≤0.2 Anoxic Mn-red 3

2.91 3.84

SIERRA-VL-07 7.5 0.3 Anoxic MnFe-red – 3

0.07

SIERRA-VL-08 7.1 8.6 Oxic x – –

SIERRA-VL-09 7.2 8.8 Oxic x – –

SIERRA-VL-10 5.2 8.8 Oxic x – –

SIERRA-VL-11 6.2 5.6 Oxic x – 2

0.16

SIERRA-VL-12 7.5 4.0 Oxic x – 0.67

1

The median dissolved oxygen concentration of USGS-GAMA samples from springs with granitic aquifer lithology and oxic conditions was assigned to 

SIERRA-G-04 for the statistical tests of relations between dissolved oxygen concentrations and potential explanatory factors and water-quality constituents.

2

Moderate relative-concentration (5–10 μg/L arsenic or 150–300 μg/L iron).

3

High relative-concentration (>10 μg/L arsenic or >300 μg/L iron).

4

The median dissolved oxygen concentration of USGS-GAMA samples from wells with volcanic aquifer lithology and oxic conditions was assigned to 

SIERRA-V-03 for the statistical tests of relations between dissolved oxygen concentrations and potential explanatory factors and water-quality constituents.
104 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Appendix C. Effect of Data Gaps on Aquifer-Scale Proportions for 

Inorganic Constituents

Of the 1,266 wells used in this study, 1,224 had data for 

at least 1 inorganic constituent with a health-based benchmark 

during the period May 2006 through October 2008. For 176 

of these wells, the source of the nutrient and trace element 

data used in this study was samples collected by the USGS for 

the SNR study unit (83 samples; Shelton and others, 2010) or 

the Tahoe-Martis, Central Sierra, and Southern Sierra study 

units (83 samples; Fram and Belitz, 2012). Seventy-two of the 

Tahoe-Martis, Central Sierra, and Southern Sierra study unit 

wells were in just 4 SNR study unit sub-cells (13G, 18S, 18V, 

25S). Samples collected by the USGS were analyzed for 21 to 

26 inorganic constituents with health-based benchmarks. Of 

the 1,048 wells for which the source of the nutrient and trace 

element data was the CDPH database, only 224 wells had 

data for 10 or more inorganic constituents with health-based 

benchmarks. Wells with data for inorganic constituents with 

health-based benchmarks were unevenly distributed among the 

SNR study unit sub-cells (table C1). 

The reason that so many of the CDPH wells do not 

have data for the full suite of inorganic constituents is that 

the CDPH has different reporting requirements for different 

types of public-supply wells. All public water systems 

using groundwater are required to monitor annually for 

nitrate concentrations, and all community and non-transient, non-community water systems also are required to 

monitor once during each 3-year period for other inorganic 

constituents (California Department of Public Health, 2013c). 

Approximately 45 percent of the public-supply wells listed 

in the CDPH database for the SNR study unit are classified 

as transient, non-community, and are therefore not required 

to monitor for concentrations of other inorganic constituents. 

In addition, water systems may apply for a waiver to reduce 

the frequency of monitoring for inorganic constituents other 

than nitrate to once during every 9-year period if there have 

been no past exceedences of MCLs. As a result, the CDPH 

database contains nitrate data for samples collected from 1,040 

wells during the period May 2006 through October 2008, but 

trace element, major ion, and radioactive constituent data for 

samples from only 225 to 275 wells during the same period. 

The uneven distribution of data may affect the results 

of calculations of aquifer-scale proportions for classes of 

constituents if the aquifer-scale proportions of the constituents within the class are not similar. In the SNR study 

unit, this situation occurred most notably in the calculation 

of aquifer-scale proportions for the class of any inorganic 

constituent with health-based benchmarks. The high-RC 

aquifer-scale proportion for nitrate, 1.4 percent, was calculated 

using 1,131 wells, whereas the high-RC proportions for 

trace elements (11 percent) and radioactive constituents 

(8.2 percent) were calculated using 530 and 502 wells, respectively (table 7B). The high-RC aquifer-scale proportion for 

any inorganic constituent is 9.5 percent if it is calculated using 

all 1,224 wells with data for any inorganic constituent and is 

16 percent if it is calculated using only the 671 wells with data 

for at least 1 trace element or radioactive constituent.

Figure C1 illustrates a simple example of the problem. 

Out of 20 wells, 10 have data for both nitrate and arsenic, and 

10 only have data for nitrate. Of the 20 wells with nitrate data, 

2 have a high RC for nitrate, resulting in a high-RC proportion 

of 10 percent for nitrate. Of the 10 wells with arsenic data, 

5 have a high RC for arsenic, giving a high-RC proportion 

for arsenic. There are two ways to calculate the high-RC 

proportion for any inorganic constituent—and they make 

different assumptions about the water-quality characteristics of 

the wells lacking arsenic data. 

The first method is to calculate the high-RC proportion 

using only the wells that have data for both nitrate and arsenic, 

which yields a result of 50 percent for the high-RC proportion 

for any inorganic constituent. This method assumes that wells 

1–10 are a representative subset of wells 1–20 and that the 

water-quality characteristics of wells 11–20 are the same as 

those of wells 1–10.

The second method is to calculate the high-RC proportion 

using all of the wells, which yields a result of 30 percent for the 

high-RC proportion for any inorganic constituent. This method 

assumes that the distribution of high RCs for nitrate in wells 

11–20 is representative of the distribution of high RCs for other 

constituents in wells 11–20 and that the addition of arsenic data 

for wells 11–20 would not change the proportion of wells with 

high RCs for any inorganic constituent. In wells 1–10, however, the distribution of high RCs of nitrate is not representative of the distribution of high RCs of arsenic. In other words, 

this method assumes that the water-quality characteristics of 

wells 11–20 are not the same as those of wells 1–10.

Returning to the SNR study unit, assessment of major-ion 

data suggested that the subset of CDPH wells having data for 

major ions (and other inorganic constituents) may be biased 

towards wells at lower elevations (appendix E). In particular, 

wells from the western part of the central and southern Sierra 

Nevada may be over-represented in the dataset of wells with 

data for inorganic constituents. Concentrations of nitrate, 

arsenic, boron, and fluoride all showed significant negative correlations with elevation (table 10B). These relations suggest that 

the dataset as a whole may contain a higher proportion of wells 

with high RCs of these constituents than it would if all wells in 

the dataset had data for all constituents. However, the structure 

of the spatially weighted calculations mitigates the effect of having more data in one part of the study unit compared to another. 

For this study, nothing indicates that within a given 

sub-cell, the water-quality characteristics of wells with more 

data should be different from those of wells with less data. 

Therefore, aquifer-scale proportions for the class of inorganic 

constituents with health-based benchmarks was calculated using 

only the 671 wells having data for at least 1 trace element or 

radioactive constituent (and generally for nitrate as well), rather 

than using the 1,224 wells having data for at least 1 inorganic 

constituent (only nitrate for nearly half of the wells).
Appendix C. Effect of Data Gaps on Aquifer-Scale Proportions for Inorganic Constituents 105

Table C1. Sources of data for inorganic constituents with health-based benchmarks for Sierra Nevada Regional (SNR) study unit sub-cells, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued[Sources of data for inorganic constituents with health-based benchmarks: USGS SNR, samples collected and analyzed by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit (24 or 26 constituents); USGS TCS, samples collected and analyzed by USGS for the Tahoe-Martis, Central Sierra, and Southern Sierra study units (21 to 26 constituents); CDPH many, wells with data reported for 10 to 21 constituents in the California Department of Public Health (CDPH) database; CDPH few, wells with data reported for 1 to 7 constituents in the CDPH database. Inorganic constituents with health-based benchmarks include trace elements, nutrients, and radioactive constituents. —, no wells in that aquifer lithology sub-cell]

Cell

Granitic aquifer lithology

(number of wells with data)

Metamorphic aquifer lithology

(number of wells with data)

Sedimentary aquifer lithology

(number of wells with data)

Volcanic aquifer lithology

(number of wells with data)

USGS 

SNR

USGS 

TCS

CDPH 

many

CDPH 

few

USGS 

SNR

USGS 

TCS

CDPH 

many

CDPH 

few

USGS 

SNR

USGS 

TCS

CDPH 

many

CDPH 

few

USGS 

SNR

USGS 

TCS

CDPH 

many

CDPH 

few

Number of 

inorganic 

constituents

24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7

1 0 0 1 12 2 0 4 8 0 0 0 2 —

—

—

—

2 1 0 3 10 1 0 1 14

—

—

—

— 1 0 0 3

3 1 0 2 15 1 0 3 34 0 0 0 3 1 0 0 94 1 0 0 11 1 0 0 12

—

—

—

—

—

—

—

—

5 1 0 0 4 1 0 1 14 1 0 0 0 1 0 0 56 —

—

—

— 1 0 0 11 1 0 1 1 1 0 0 2

7 1 0 0 5 —

—

—

— 1 0 0 9 1 0 0 1

8 1 0 0 3 1 0 2 2 1 0 0 15 1 2 1 69 1 1 1 7 0 0 0 1 0 0 1 6 1 2 1 810 1 0 0 10 1 0 0 8 0 0 0 1 1 0 1 511 1 0 5 1 1 0 7 9 —

—

—

— 0 0 1 0

12 1 0 5 40 1 0 3 14

—

—

—

— 1 0 0 1

13 1 20 59 69 1 3 1 5 0 0 0 1 —

—

—

—

14 1 4 26 45 1 0 4 20

—

—

—

—

—

—

—

—

15 1 0 1 5 1 0 1 3 1 0 0 2 1 0 0 016 1 0 3 15

—

—

—

— 1 0 2 1 1 0 1 6

17 1 2 4 14

—

—

—

— 1 0 0 3 1 0 0 14

18 1 3 0 0 1 0 0 0 1 19 12 22 1 15 0 419 1 0 0 1 1 0 0 0 —

—

—

— 1 0 0 0

20 1 2 0 17

—

—

—

— 0 0 0 7 —

—

—

—

21 1 0 8 44

—

—

—

— 1 0 0 2 —

—

—

—

22 1 0 7 23 1 0 0 1 —

—

—

—

—

—

—

—

23 1 0 2 15 1 0 1 12 1 0 2 14

—

—

—

—

Table C1. Sources of data for inorganic constituents with health-based benchmarks for Sierra Nevada Regional (SNR) study unit sub-cells, 2008, California Groundwater 

Ambient Monitoring and Assessment (GAMA) Priority Basin Project. 
106 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008 Table C1. Sources of data for inorganic constituents with health-based benchmarks for Sierra Nevada Regional (SNR) study unit sub-cells, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.—Continued [Sources of data for inorganic constituents with health-based benchmarks: USGS SNR, samples collected and analyzed by the U.S. Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit (24 or 26 constituents); USGS TCS, samples collected and analyzed by USGS for the Tahoe-Martis, Central Sierra, and Southern Sierra study units (21 to 26 constituents); CDPH many, wells with data reported for 10 to 21 constituents in the California Department of Public Health (CDPH) database; CDPH few, wells with data reported for 1 to 7 constituents in the CDPH database. Inorganic constituents with health-based benchmarks include trace elements, nutrients, and radioactive constituents. —, no wells in that aquifer lithology sub-cell] Cell Granitic aquifer lithology (number of wells with data) Metamorphic aquifer lithology (number of wells with data) Sedimentary aquifer lithology (number of wells with data) Volcanic aquifer lithology (number of wells with data) USGS SNR USGS TCS CDPH many CDPH few USGS SNR USGS TCS CDPH many CDPH few USGS SNR USGS TCS CDPH many CDPH few USGS SNR USGS TCS CDPH many CDPH few Number of inorganic constituents 24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7 24 or 26 21 to 26 10 to 21 1 to 7 24 1 0 2 3 1 0 0 0 1 0 0 1 —

—

—

—

25 1 0 5 17 1 1 3 0 1 15 12 21 1 0 0 226 1 0 2 5 1 1 3 5 1 1 6 31

—

—

—

—

27 1 1 1 17 1 0 2 9 1 1 3 18

—

—

—

—

28 1 0 4 7 1 0 0 1 —

—

—

—

—

—

—

—

29 1 0 1 0 1 0 0 0 1 0 0 0 —

—

—

—

30 1 0 0 0 —

—

—

— 1 0 2 0 —

—

—

—
Appendix C. Effect of Data Gaps on Aquifer-Scale Proportions for Inorganic Constituents 107

Low

High

No data

Relative-concentration category

Well

number

Nitrate

relativeconcentration

Arsenic

relativeconcentration

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Well

number

Nitrate

relativeconcentration

Arsenic

relativeconcentration

sac14-0538_Figure C-01

Figure C1. Hypothetical case of 20 wells used to illustrate the effect of uneven distribution of data on calculation of aquifer-scale 

proportions.
108 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Appendix D. Radioactivity

The class of radioactive constituents includes constituents 

whose abundances commonly are measured as activities rather 

than concentrations. Activity is measured in units of picocuries 

per liter, and 1 picocurie equals approximately two atoms 

decaying per minute. When atoms decay, they release alpha or 

beta particles and (or) gamma radiation. Gross alpha particle 

activity is a measure of the total activity of non-volatile 

isotopes decaying by alpha emission. 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, 2009). Data collected by USGS-GAMA 

and data compiled in the CDPH database are reported as 

gross alpha particle activity without correction for uranium 

activity (“unadjusted”). Gross alpha is used as a screening 

tool to determine whether other radioactive constituents must 

be analyzed. For regulatory purposes, analysis of uranium is 

only required if gross alpha particle activity is greater than 

15 pCi/L (California Department of Public Health, 2013b); 

therefore, the CDPH database contains substantially more data 

for gross alpha particle activity than for uranium. As a result, 

calculation of adjusted gross alpha particle activity is not 

always possible. For this reason, results for unadjusted gross 

alpha particle activity (that is, without correction for uranium) 

are the primary data used in the status assessments made by 

USGS-GAMA for Priority Basin Project study units. Results 

for adjusted gross alpha particle activity also are given in this 

report for comparison.

USGS-GAMA reports data for two measurements of 

gross alpha particle activity: counted 72 hours and 30 days 

after sample collection. Regulatory sampling for gross alpha 

particle activity permits use of quarterly composite samples 

(California Department of Public Health, 2013b). The 

composite samples sent by water agencies to laboratories for 

analysis may be mixtures of four samples collected 9 months, 

6 months, 3 months, and a few days before submission. 

Because of these long holding times for CDPH data, the 

USGS-GAMA gross alpha 30-day count data may be more 

appropriate to use when combining USGS-GAMA and CDPH 

datasets. The 30-day count data were used in this study. 

Gross alpha particle activity in a groundwater sample may 

change with time after sample collection due to radioactive 

decay of parent isotopes and ingrowth and subsequent decay 

of radioactive daughter isotopes (activity may increase or 

decrease depending on sample composition and holding time) 

(Arndt, 2010).

Most uranium results in the CDPH databases are reported 

as activities because the MCL-CA for uranium is 20 pCi/L. 

For samples having only uranium data in units of micrograms 

per liter, a conversion factor of 0.74 picocurie per microgram 

(pCi/μg) was used to convert the data to uranium activities. 

This conversion factor was obtained from the relation between 

uranium activities and concentrations in USGS-GAMA SNR 

study unit samples (Shelton and others, 2010):

2 0.74 ( 0.988) U UR act =× = mass , (D1)

where

Umass is the concentration of uranium in micrograms 

per liter, and

Uact is the activity of uranium in picocuries per 

liter. Total uranium activity is assumed 

to equal the sum of the activities of the 

three uranium isotopes, uranium-234, 

-235, and -238.
Appendix E. Comparison of Major-Ion Data 109

Appendix E. Comparison of Major-Ion Data

Major-ion data for the 83 wells sampled by 

USGS-GAMA were compared with major-ion data from all 

wells in the CDPH database within the SNR study unit to 

determine whether the two datasets were representative of the 

same population of public-supply wells in the SNR study unit. 

The CDPH well dataset consisted of all wells within the study 

unit with a complete major-ion analysis between May 2006 

and October 2008. If multiple analyses were available, the 

most recent one with an acceptable cation-anion balance was 

selected. The datasets were compared using Piper diagrams 

(Piper, 1944; Hem, 1992). Groundwater types are defined on 

a Piper diagram according to the cations and anions present in 

the greatest proportions (fig. E1).

To minimize the use of poor-quality data, only majorion analyses with acceptable cation-anion balances were 

plotted on the Piper diagrams. For electroneutrality, the 

total concentrations of positive charges in a water sample, 

expressed as milliequivalents of cations per liter, must equal 

the total concentration of negative charges, expressed as 

milliequivalents of anions per liter; thus, cation-anion balance 

is a test of the internal consistency of a major-ion analysis 

(Hem, 1992). An acceptable cation-anion balance was defined 

as one for which the difference between the total cation and 

anion concentrations, both expressed in milliequivalents per 

liter, was no greater than 10 percent of the total.

Major-ion analyses from the CDPH database occasionally 

required adjustment of the reported alkalinity value to achieve 

acceptable cation-anion balance. The CDPH database has 

fields for bicarbonate alkalinity and total alkalinity, but the 

data in these fields were not always populated correctly. Total 

alkalinity is a measured value, and bicarbonate alkalinity is a 

calculated value that is typically 1.22 times the total alkalinity (in units of milligrams per liter as CaCO3

) for water with 

pH values in the range of pH values for most groundwater. 

This relation was not consistently observed in the CDPH 

database for the SNR study unit. In particular, total alkalinity and bicarbonate alkalinity were commonly reported as 

the same value. The second type of inconsistency was a 

total alkalinity value that was greater than the bicarbonate 

alkalinity, without the presence of sufficient sources of noncarbonate alkalinity to account for the difference. The third 

type of inconsistency was the presence of values for total 

alkalinity or bicarbonate alkalinity, but not both. For major-ion 

analyses with unacceptable cation-anion balances, cationanion balance was recalculated by substituting trial values of 

total alkalinity. These trial values were calculated by assuming 

that the reported total alkalinity and bicarbonate alkalinity 

values were reversed or were incorrectly calculated from one 

another. Calculations were done assuming pKa1 = 6.35 and 

pKa2 = 10.33 for the carbonate equilibia and measured pH 

values. If no pH value was available, a pH of 7 was assumed. 

If any substitution resulted in an acceptable cation-anion 

balance, the major-ion analysis with the substituted value 

was used for plotting the data on the Piper diagram. Of the 

2,239 wells listed in the CDPH database for the SNR study 

unit, 1,236 wells have water-quality data for one or more 

constituents for samples collected between May 1, 2006, and 

October 31, 2008. Of these 1,236 wells, 234 have data for at 

least 1 complete major-ion analysis, and of those, 226 wells 

had a major-ion analysis with acceptable cation-anion balance. 

The distribution of groundwater types represented 

by the USGS-GAMA wells was different from the 

distribution of groundwater types with major-ion data in 

the CDPH database (fig. E2). The anion composition of 

the water sampled from most of the wells in both datasets 

was classified as bicarbonate-type (HCO3

); however, the 

percentage of HCO3

-type wells in the USGS-GAMA dataset 

(93 percent) was significantly greater than the percentage of 

HCO3

-type wells in the CDPH dataset (82 percent) (fig. E3; 

contingency table test, p = 0.020). The cation compositions 

of wells in the USGS-GAMA and CDPH datasets also were 

significantly different (fig. E2; contingency table test, p = 

0.043). Most of the difference between the datasets was due 

to the USGS-GAMA dataset having a significantly higher 

proportion of wells with calcium+magnesium (Ca+Mg) cation 

composition and a significantly lower proportion of wells with 

calcium+sodium+potassium (Ca+NaK) cation composition 

than the CDPH dataset (fig. E3).

The differences in anion and cation compositions 

between the USGS-GAMA and CDPH wells may be related 

to differences in the geographic distribution of wells in 

the two datasets. The USGS-GAMA wells are spatially 

distributed across the study unit. In contrast, the 226 CDPH 

wells predominantly are located on the western side of the 

central and southern parts of the study unit (fig. E4). Median 

elevation and latitude of the 83 USGS-GAMA wells were 

significantly greater than the median elevation and latitude 

of the 224 CDPH wells (Wilcoxon rank-sum test; p < 0.001). 

In the USGS-GAMA dataset, the fraction of HCO3

 in the 

anions showed positive correlations with elevation and with 

latitude (Spearman’s rho test, p < 0.001, rho = 0.43 and 0.47, 

respectively). The 226 CDPH wells with complete major-ion 

analyses included a significantly lower percentage of wells 

located at elevations greater than 7,000 ft than did the 1,010 

CDPH wells with data for at least 1 constituent, but not a 

complete major-ion analysis (contingency table test, p = 

0.047). The under-representation of wells located at elevations 

greater than 7,000 ft among the CDPH wells with major-ion 

analyses could therefore account for smaller proportion of 

wells having HCO3

 as the dominant anion class in the CDPH 

wells compared to the USGS-GAMA dataset.
110 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

sac14-0538_fig E01

Calcium Chloride

Percent

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

Calcium plus magnesium

Sulfate plus chloride

Magnesium

Sodium plus potassium

Sulfate

Bicarbonate

Percent

Percent

80

100

60

40

0

20

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

0

20

40

60

80

100

20

0

80

100

80

100 0

20

60 40

40 60

Ca

Mg

NaK

Ca + Mg

NaK + Mg

mixed

Ca + NaK

mixed

HCO3 HCO3 + CI

HCO3 

+ SO4 SO4 

CI + SO4 CI

EXPLANATION

Cations

Calcium

Magnesium

Sodium plus potassium

Ca

Mg

NaK

Anions

Bicarbonate

Chloride

Sulfate

HCO3

CI

SO4

Figure E1. Definitions of groundwater types.
Appendix E. Comparison of Major-Ion Data 111

sac14-0538_fig E02

Calcium Chloride

Percent

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

Calcium plus magnesium

Sulfate plus chloride

Magnesium

Sodium plus potassium

Sulfate

Bicarbonate

Percent

Percent

80

100

60

40

0

20

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

0

20

40

60

80

100

20

0

80

100

80

100 0

20

60 40

40 60

EXPLANATION

USGS-GAMA SNR study unit wells

CDPH wells (May 1, 2006–October 31, 2008)

Figure E2. Groundwater types for samples collected by USGS-GAMA for the study unit and samples in the California Department of 

Public Health (CDPH) database having major-ion chemical analyses with acceptable cation-anion balance during May 2006 through 

October 2008, Sierra Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority 

Basin Project.
112 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

sac14-0538_fig E03

Cation type

Percentage of wells

0

10

20

30

40

50

USGS-GAMA Sierra Nevada Regional

 study unit wells (n=83)

California Department of

 Public Health wells (n=226)

Anion type

Percentage of wells

0

20

40

60

80

100

Ca + NaK Ca Mixed Ca + Mg NaK Mg HCO3 HCO3-Cl HCO3-SO4 Cl Mixed SO4

n is number of wells with data

EXPLANATION

A B

Figure E3. Percentages of USGS-GAMA and California Department of Public Health (CDPH) wells classified by groundwater type 

on the basis of (A) cation composition and (B) anion composition for the Sierra Nevada Regional (SNR) study unit, 2008, California 

Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Appendix E. Comparison of Major-Ion Data 113

7

6

2

5

1

4 8

9

3

11 16

20

22

27

28

13

14

15

10

21

17

25

19

29

23

30

26

12

18

24

24

24

12

26

26

18

30

24

12

23

24

12

sac14-0538_Figure E04

121° 120° 119° 118°

40°

39°

38°

37° 

36°

35°

0 25 50 MILES

0 5025 KILOMETERS

EXPLANATION

Pacific Ocean

Sierra Nevada Regional

 study unit 

Lake or reservoir

USGS-GAMA SNR wells

CDPH wells with major-ion data

CDPH wells without major-ion data

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006,

Albers Equal Area Conic Projection

Sierra Nevada Regional

 study unit grid cell 

17

Figure E4. Locations of USGS-GAMA wells sampled for the Sierra Nevada Regional study unit, 2008, California Groundwater Ambient 

Monitoring and Assessment (GAMA) Priority Basin Project and wells in the California Department of Public Health (CDPH) database 

having major-ion chemical analyses with acceptable cation-anion balance during May 2006 through October 2008.
114 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

sac14-0538_fig E05

Calcium Chloride

Percent

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

Calcium plus magnesium

Sulfate plus chloride

Magnesium

Sodium plus potassium

Sulfate

Bicarbonate

Percent

Percent

80

100

60

40

0

20

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

0

20

40

60

80

100

20

0

80

100

80

100 0

20

60 40

40 60

EXPLANATION

Granitic

Metamorphic

Sedimentary

Volcanic

Aquifer lithology

Figure E5. Groundwater types for samples collected by USGS-GAMA for the study unit from wells in the four aquifer lithologies, Sierra 

Nevada Regional study unit, 2008, California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project.
Appendix F. Additional Water-Quality Data 115

Appendix F. Additional Water-Quality Data

Noble gas data provided by Lawrence Livermore National Laboratory that were not available at the time of publication of the 

Data Series Report (Shelton and others, 2010) are tabulated in this appendix (table F1). These data were not used in this report; 

they are provided herein to complete the publication of all of the data collected for the study.

Table F1. Results for analyses of noble gases by Lawrence Livermore National Laboratory for samples collected by the U.S. 

Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.—Continued

[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. Abbreviations: cm3 STP/g H2O, cubic centimeters at standard temperature and pressure per gram of water; na, not available]

GAMA well 

identification 

number

Helium-3/ Helium-4

(atom ratio) 

(61040)

Helium-4 

(cm3

 STP/g H2O) 

(85561)

Neon 

(cm3 STP/g H2O) 

(61046)

Argon 

(cm3 STP/g H2O) 

(85563)

Krypton 

(cm3 STP/g H2O) 

(85565)

Xenon 

(cm3 STP/g H2O) 

(85567)

x 10–7 x 10–7 x 10–7 x 10–4 x 10–8 x 10–8

Granitic aquifer lithology

SIERRA-G-01 12.72 1.04 4.00 4.86 9.93 1.25

SIERRA-G-02 13.89 0.41 1.82 3.41 8.12 1.18

SIERRA-G-03 1.12 39.42 2.53 3.39 7.27 0.94

SIERRA-G-04 na na na na na na

SIERRA-G-05 13.26 0.53 3.46 3.81 7.76 1.02

SIERRA-G-06 5.71 40.53 2.75 3.81 8.47 1.15

SIERRA-G-07 14.22 0.43 1.65 3.26 7.69 1.06

SIERRA-G-08 13.71 0.59 2.60 4.04 9.15 1.26

SIERRA-G-09 14.00 0.44 2.07 3.46 7.10 1.14

SIERRA-G-10 11.81 0.76 1.95 3.43 8.06 1.16

SIERRA-G-11 12.88 0.40 1.77 3.09 7.42 1.04

SIERRA-G-12 13.15 0.39 1.75 2.89 6.53 0.91

SIERRA-G-13 na na na na na na

SIERRA-G-14 2.87 3.16 2.13 3.77 8.69 1.27

SIERRA-G-15 1.68 108.04 2.39 3.59 7.68 1.06

SIERRA-G-16 10.76 0.38 1.35 2.67 6.83 1.05

SIERRA-G-17 13.81 0.67 2.77 3.52 7.78 1.08

SIERRA-G-18 13.74 0.73 2.92 4.06 8.82 1.11

SIERRA-GL-01 13.61 0.43 1.89 2.90 6.67 0.99

SIERRA-GL-02 8.51 1.03 2.73 3.92 8.51 1.15

SIERRA-GL-03 13.90 0.31 1.52 3.05 7.61 1.09

SIERRA-GL-04 13.71 0.38 1.75 3.22 7.53 1.11

SIERRA-GL-05 18.55 0.54 2.18 3.66 8.84 1.27

SIERRA-GL-06 13.95 0.39 1.80 3.46 8.34 1.22

SIERRA-GL-07 14.41 1.80 6.72 6.64 11.56 1.72

SIERRA-GL-08 13.90 0.40 1.78 3.40 8.23 1.23

SIERRA-GL-09 15.85 0.51 2.22 3.63 7.96 1.15

SIERRA-GL-10 18.36 0.78 2.96 4.28 9.03 1.25

Table F1. Results for analyses of noble gases by Lawrence Livermore National Laboratory for samples collected by the U.S. 

Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.
116 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

Table F1. Results for analyses of noble gases by Lawrence Livermore National Laboratory for samples collected by the U.S. 

Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.—Continued

[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. Abbreviations: cm3 STP/g H2O, cubic centimeters at standard temperature and pressure per gram of water; na, not available]

GAMA well 

identification 

number

Helium-3/ Helium-4

(atom ratio) 

(61040)

Helium-4 

(cm3

 STP/g H2O) 

(85561)

Neon 

(cm3 STP/g H2O) 

(61046)

Argon 

(cm3 STP/g H2O) 

(85563)

Krypton 

(cm3 STP/g H2O) 

(85565)

Xenon 

(cm3 STP/g H2O) 

(85567)

x 10–7 x 10–7 x 10–7 x 10–4 x 10–8 x 10–8

Metamorphic aquifer lithology

SIERRA-M-01 0.55 116.31 3.13 3.99 8.16 1.14

SIERRA-M-02 0.67 70.00 3.39 4.37 9.00 1.10

SIERRA-M-03 na na na na na na

SIERRA-M-04 16.56 0.50 2.19 3.92 8.89 1.39

SIERRA-M-05 8.91 1.00 2.73 3.89 8.52 1.24

SIERRA-M-06 16.66 0.51 2.42 3.69 8.44 1.19

SIERRA-ML-01 8.71 1.78 3.70 4.30 8.42 1.04

SIERRA-ML-02 15.52 0.65 2.76 3.78 8.17 1.12

SIERRA-ML-03 13.18 0.79 3.11 3.87 7.84 1.01

SIERRA-ML-04 10.24 0.83 2.04 3.02 6.64 0.94

SIERRA-ML-05 13.78 0.37 2.53 3.12 6.72 0.94

SIERRA-ML-06 na na na na na na

SIERRA-ML-07 5.04 3.25 2.22 3.49 7.69 1.14

SIERRA-ML-08 2.17 8.25 2.94 3.94 8.06 1.13

SIERRA-ML-09 14.60 1.00 4.06 4.62 9.52 1.16

SIERRA-ML-10 10.06 3.08 6.71 5.43 9.96 1.20

SIERRA-ML-11 14.01 1.68 6.33 6.39 12.30 1.48

SIERRA-ML-12 12.09 0.74 2.29 3.42 7.53 0.98

SIERRA-ML-13 1.64 21.93 2.03 3.42 7.74 1.10

SIERRA-ML-14 13.86 0.39 9.88 3.68 7.38 1.00

SIERRA-ML-15 3.73 10.14 2.64 3.78 8.06 1.06

SIERRA-ML-16 5.57 6.11 2.33 3.70 8.24 1.20

SIERRA-ML-17 14.57 3.60 9.54 8.67 14.03 1.59

SIERRA-ML-18 6.59 1.41 2.57 3.80 8.25 1.13

Sedimentary aquifer lithology

SIERRA-S-01 12.45 1.22 3.29 4.10 8.14 1.08

SIERRA-S-02 5.82 2.43 2.13 3.66 8.23 1.20

SIERRA-S-03 4.63 7.07 2.37 3.76 8.42 1.21

SIERRA-SL-01 13.41 0.65 2.62 3.58 7.70 1.04

SIERRA-SL-02 3.40 38.56 2.02 3.31 7.36 1.04

SIERRA-SL-03 2.28 6.81 2.30 3.29 7.06 0.97

SIERRA-SL-04 3.75 12.22 2.25 3.65 8.41 1.21

SIERRA-SL-05 na na na na na na

SIERRA-SL-06 15.11 0.59 2.15 3.59 8.27 1.12

SIERRA-SL-07 4.73 2.58 2.21 3.77 8.75 1.23

SIERRA-SL-08 17.84 0.54 2.17 3.68 8.49 1.19

SIERRA-SL-09 13.56 0.39 1.72 3.39 8.01 1.13
Appendix F. Additional Water-Quality Data 117

Table F1. Results for analyses of noble gases by Lawrence Livermore National Laboratory for samples collected by the U.S. 

Geological Survey (USGS) for the Sierra Nevada Regional (SNR) study unit, 2008, California Groundwater Ambient Monitoring and 

Assessment (GAMA) Priority Basin Project.—Continued

[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. Abbreviations: cm3 STP/g H2O, cubic centimeters at standard temperature and pressure per gram of water; na, not available]

GAMA well 

identification 

number

Helium-3/ Helium-4

(atom ratio) 

(61040)

Helium-4 

(cm3

 STP/g H2O) 

(85561)

Neon 

(cm3 STP/g H2O) 

(61046)

Argon 

(cm3 STP/g H2O) 

(85563)

Krypton 

(cm3 STP/g H2O) 

(85565)

Xenon 

(cm3 STP/g H2O) 

(85567)

x 10–7 x 10–7 x 10–7 x 10–4 x 10–8 x 10–8

Sedimentary aquifer lithology—Continued

SIERRA-SL-10 23.83 0.55 1.93 3.20 7.45 1.07

SIERRA-SL-11 11.28 0.58 1.69 3.03 7.09 0.98

SIERRA-SL-12 13.92 0.59 3.45 3.77 7.70 1.02

SIERRA-SL-13 na na na na na na

Volcanic aquifer lithology

SIERRA-V-01 17.67 0.44 2.02 3.60 8.51 1.24

SIERRA-V-02 2.74 7.02 2.17 3.52 8.19 1.11

SIERRA-V-03 7.34 4.96 1.89 3.33 7.55 1.32

SIERRA-VL-01 3.47 5.27 1.92 2.95 6.62 0.90

SIERRA-VL-02 14.00 0.42 1.87 3.19 7.46 1.12

SIERRA-VL-03 8.30 1.27 2.54 3.64 8.32 1.09

SIERRA-VL-04 10.57 0.66 2.04 3.40 7.78 1.14

SIERRA-VL-05 10.92 0.53 1.88 3.19 7.73 1.08

SIERRA-VL-06 33.66 4.92 1.98 3.40 7.74 1.11

SIERRA-VL-07 9.77 1.21 2.55 4.11 9.32 1.31

SIERRA-VL-08 13.25 0.39 1.69 3.06 7.13 1.04

SIERRA-VL-09 13.83 0.37 1.70 3.28 7.92 1.12

SIERRA-VL-10 na na na na na na

SIERRA-VL-11 14.98 0.39 1.73 3.36 7.69 1.10

SIERRA-VL-12 7.71 1.01 2.42 3.68 8.14 1.13
118 Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008

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For more information concerning the research in this report, contact the

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U.S. Geological Survey

6000 J Street, Placer Hall

Sacramento, California 95819

http://ca.water.usgs.gov

Author—Spine Title—Report Series Name 0000

ISBN

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ISSN 2328-031X (print)

http://dx.doi.org/10.3133/sir20145174

Fram and Belitz—Status and Understanding of Groundwater Quality in the Sierra Nevada Regional Study Unit, 2008: California GAMA Priority Basin Project—SIR 2014–5174

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