U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the California State Water Resources Control Board

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

Status and Understanding of Groundwater Quality in the Klamath 

Mountains Study Unit, 2010: California GAMA Priority Basin Project

Photo placement

Scientific Investigations Report 2014–5065
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: Water-quality sampling vehicle and well house near Lewiston, California. (Photograph 

taken by Tracy Davis, U.S. Geological Survey.)

Back cover: Well house and deer near Lewiston, California. (Photograph taken by Tracy Davis, 

U.S. Geological Survey.)
Status and Understanding of Groundwater 

Quality in the Klamath Mountains Study Unit, 

2010: California GAMA Priority Basin Project

By George L. Bennett V, 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 2014–5065

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

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

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Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Bennett, G.L., V, Fram, M.S., and Belitz, Kenneth, 2014, Status and understanding of groundwater quality in the Klamath Mountains study unit, 2010—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014–5065, 58 p., http://dx.doi.org/10.3133/sir20145065

ISBN 978-1-4113-3790-9

ISSN 2328-0328 (online)

ISSN 2328-031X (print)
iii

Contents

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

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

Purpose and Scope ..............................................................................................................................4

Methods...........................................................................................................................................................6

Status Assessment...............................................................................................................................6

Water-Quality Benchmarks and Relative-Concentrations ...................................................6

Datasets Used for Status Assessment.....................................................................................7

U.S. Geological Survey Grid Sites....................................................................................7

California Department of Public Health Grid Sites........................................................7

Additional Data Used for Spatially Weighted Calculations .......................................10

Selection of Constituents for Additional Evaluation in the Status Assessment..............10

Calculation of Aquifer-Scale Proportions..............................................................................12

Understanding Assessment..............................................................................................................12

Selection of Constituents for Additional Evaluation in the 

Understanding Assessment .......................................................................................12

Statistical Tests of Relations between Potential Explanatory Factors and 

Groundwater Quality....................................................................................................13

Hydrogeologic Setting and Potential Explanatory Factors...................................................................13

Aquifer Lithology.................................................................................................................................14

Land Use...............................................................................................................................................16

Hydrologic Conditions........................................................................................................................19

Depth and Groundwater Age Characteristics of the Primary Aquifer System.........................21

Geochemical Conditions in the Primary Aquifer System .............................................................21

Status and Understanding of Groundwater Quality...............................................................................23

Inorganic Constituents.......................................................................................................................25

Trace Elements...........................................................................................................................28

Factors Affecting Boron ..................................................................................................28

Nutrients......................................................................................................................................28

Radioactive Constituents..........................................................................................................28

Constituents with SMCL Benchmarks....................................................................................30

Factors Affecting Iron and Manganese........................................................................30

Organic Constituents..........................................................................................................................32

Potential Factors Affecting Chloroform .................................................................................34

Summary........................................................................................................................................................34

Acknowledgments.......................................................................................................................................35

References....................................................................................................................................................35

Appendix A. Attribution of Potential Explanatory Factors ...................................................................41

Appendix B. Grid Cells and Sites .............................................................................................................50

Appendix C. Calculation of Aquifer-Scale Proportions .......................................................................55

Appendix D. Comparison of CDPH and USGS–GAMA Data................................................................56
iv

Figures

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

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project ..................3

2. Map showing geographic features and locations of sampled sites in the Klamath 

Mountains study unit, 2010, California GAMA Priority Basin Project..................................5

3. Map showing locations of grid sites, the understanding site, and CDPH sites 

sampled for the Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project.................................................................................................................................8

4. Map showing geology of the Klamath Mountains study unit, California 

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

5. Ternary diagram of the percentages of urban, agricultural, and natural land use 

surrounding individual USGS-grid and USGS-understanding sites, and land-use 

averages in the study unit, around grid sites, and around CDPH sites in the 

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project ................16

6. Map showing land use, CDWR groundwater basins, and locations of sampled 

sites within the Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project...............................................................................................................................17

7. Graph showing well depths and depths to tops of screened or open intervals for 

USGS-grid sites, Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project...............................................................................................................................21

8. Map showing groundwater age classes of sampled sites within the Klamath 

Mountains study unit, 2010, California GAMA Priority Basin Project................................22

9. Graph showing maximum relative-concentrations in USGS-grid sites for 

constituents detected, by type of constituent, Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project..................................................................................25

10. Graphs showing relative-concentrations of selected trace elements, radioactive 

constituents, and constituents with non-regulatory aesthetic-based benchmarks in 

USGS-grid sites, Klamath Mountains study unit, 2010, California GAMA Priority 

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

11. Graphs showing relations between dissolved oxygen concentration and iron 

and manganese, Klamath Mountains study unit, 2010, California GAMA 

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

12. Graph showing iron and manganese concentrations by groundwater age class, 

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project ................32

13. Graph showing detection frequency and maximum relative-concentration for 

organic constituents detected in USGS-grid sites, Klamath Mountains study unit, 

2010, California GAMA Priority Basin Project........................................................................33

14. Graphs showing maximum relative-concentration and detection frequency for the 

trihalomethane chloroform detected in USGS-grid sites, Klamath Mountains study 

unit, 2010, California GAMA Priority Basin Project...............................................................34
v

Tables

1. Summary of constituent groups and numbers of constituents sampled for each 

constituent group by the U.S. Geological Survey in the Klamath Mountains study 

unit, 2010, California GAMA Priority Basin Project.................................................................9

2. Numbers of constituents analyzed and detected, by benchmark and constituent 

type, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.......11

3. Constituents historically (June 14, 1984, to November 30, 2007) reported at 

concentrations greater than benchmarks in the California Department of Public Health 

database, but not during the 3-year period used in the status assessment, Klamath 

Mountains study unit, 2010, California GAMA Priority Basin Project................................11

4. Results of Wilcoxon rank-sum tests for differences in values of land-use factors, 

hydrologic conditions, geochemical conditions, and selected water-quality 

constituents between samples classified into groups by 2-factor age class, redox 

class, or aquifer lithology class, Klamath Mountains study unit, 2010, California 

GAMA Priority Basin Project....................................................................................................18

5. Results of Spearman’s rho (ρ) tests for correlations between selected potential 

explanatory factors and selected water-quality constituents, Klamath Mountains 

study unit, 2010, California GAMA Priority Basin Project ....................................................20

6. Constituents selected for additional evaluation in the status assessment of 

groundwater quality in the Klamath Mountains study unit, California GAMA 

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

7A. Summary of aquifer-scale proportions for inorganic constituent classes with 

health-based and aesthetic-based benchmarks, Klamath Mountains study unit, 

2010, California GAMA Priority Basin Program .....................................................................27

7B. Summary of aquifer-scale proportions for organic constituent classes with 

health-based benchmarks, Klamath Mountains study unit, 2010, California GAMA 

Priority Basin Program...............................................................................................................27

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

constituents that met criteria for additional evaluation in the status assessment, 

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project ................29
vi

Conversion Factors, Datums, and Abbreviations 

and Acronyms

Inch/foot/mile to International System of Units (SI)

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2

) 0.09290 square meter (m2)

square mile (mi2

) 2.590 square kilometer (km2) 

Radioactivity

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

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

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

°F=(1.8×°C)+32

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

°C=(°F–32)/1.8

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). One milligram per liter is equivalent to 1 part per million (ppm); 

1 microgram per liter is equivalent to 1 part per billion (ppb); 1 per mil is equivalent to 1 part per 

thousand.

Concentrations of noble gases used for modeling recharge temperatures are given as the 

atom ratio (for helium-3/helium-4) or as cubic centimeters of gas at standard temperature and 

pressure per gram of water (cm3 STP/g).

Activities of radioactive constituents in water (except uranium and tritium) are given in 

picocuries per liter (pCi/L).

Concentrations of tritium are presented in tritium units (TU). One TU equals 3.19 pCi/L.

Datums

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

(NAVD 88). Land-surface datum (LSD), as used in this report, refers to a horizontal plane that is 

approximately at land surface at each site, at a specific elevation relative to NAVD 88.

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

Abbreviations and Acronyms

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

E estimated or having a higher degree of uncertainty

GAMA Groundwater Ambient Monitoring and Assessment Program

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

HBSL health-based screening level

KLAM Klamath Mountains study unit

LRL laboratory reporting level

LSD land-surface datum

LUFT leaking (or formerly leaking) underground fuel tank

MCL maximum contaminant level

MCL-CA California Department of Public Health maximum contaminant level 

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

MDL method detection limit

na not available

NAVD 88 North American Vertical Datum of 1988

NL-CA California Department of Public Health notification level 

ns not significant

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

SI International System of Units

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

Organizations

CDPH California Department of Public Health 

CDPR California Department of Pesticide Regulation

CDWR California Department of Water Resources

LLNL Lawrence Livermore National Laboratory

SWRCB California State Water Resources Control Board 

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey
viii

Selected Constituent Names

14C carbon-14

DO dissolved oxygen

H2O water

MTBE methyl tert-butyl ether

TDS total dissolved solids

THM trihalomethane

VOC volatile organic compound

Selected Symbols and Units of Measure

α critical level

cm3 STP/g cubic centimeters of gas at standard temperature and pressure per gram 

 of water 

δiE delta notation; the ratio of a heavier isotope of an element, iE, to the more 

 common lighter isotope of an element, relative to a standard reference 

 material, expressed as per mil

L liter

m meter

mg/L milligrams per liter

μg/L micrograms per liter

μS/cm microsiemens per centimeter

p attained significance level (probability) 

pM percent modern

pmc percent modern carbon

ρ rho (test statistic from Spearman’s rank-order correlation test)

TU tritium unit

yr year

> greater than

< less than

≤ less than or equal to

% percent

‰ per mil
Status and Understanding of Groundwater Quality in the 

Klamath Mountains Study Unit, 2010: California GAMA 

Priority Basin Project

By George L. Bennett V, Miranda S. Fram, and Kenneth Belitz

Abstract

Groundwater quality in the Klamath Mountains (KLAM) 

study unit was investigated as part of the Priority Basin 

Project of the California Groundwater Ambient Monitoring 

and Assessment (GAMA) Program. The study unit is located 

in Del Norte, Humboldt, Shasta, Siskiyou, Tehama, and 

Trinity Counties. The GAMA Priority Basin Project is being 

conducted by the California State Water Resources Control 

Board in collaboration with the U.S. Geological Survey 

(USGS) and the Lawrence Livermore National Laboratory.

The GAMA Priority Basin Project was designed to 

provide a spatially unbiased, statistically robust assessment 

of the quality of untreated (raw) groundwater in the primary 

aquifer system. The assessment is based on water-quality data 

and explanatory factors for groundwater samples collected 

in 2010 by the USGS from 39 sites and on water-quality data 

from the California Department of Public Health (CDPH) 

water-quality database. The primary aquifer system was 

defined by the depth intervals of the wells listed in the CDPH 

water-quality database for the KLAM study unit. The quality 

of groundwater in the primary aquifer system may be different 

from that in the shallower or deeper water-bearing zones; 

shallow groundwater may be more vulnerable to surficial 

contamination.

This study included two types of assessments: (1) a 

status assessment, which characterized the status of the 

current quality of the groundwater resource by using data from 

samples analyzed for volatile organic compounds, pesticides, 

and naturally occurring inorganic constituents, such as major 

ions and trace elements, and (2) an understanding assessment, 

which evaluated the natural and human factors potentially 

affecting the groundwater quality. The assessments were 

intended to characterize the quality of groundwater resources 

in the primary aquifer system of the KLAM study unit, not the 

quality of treated drinking water delivered to consumers by 

water purveyors.

Relative-concentrations (sample concentrations divided 

by the health- or aesthetic-based benchmark concentrations) 

were used for evaluating groundwater quality for those 

constituents that have Federal or California regulatory or nonregulatory benchmarks for drinking-water quality. A relativeconcentration greater than (>) 1.0 indicates a concentration 

greater than a benchmark, and a relative-concentration less 

than or equal to (≤) 1.0 indicates a concentration less than 

or equal to a benchmark. Relative-concentrations of organic 

constituents were classified as “high” (relative-concentration 

> 1.0), “moderate” (0.1 < relative-concentration ≤ 1.0), 

or “low” (relative-concentration ≤ 0.1). For inorganic 

constituents, the boundary between low and moderate relativeconcentration was set at 0.5.

Aquifer-scale proportion was used in the status 

assessment as the primary metric for evaluating regional-scale 

groundwater quality. High aquifer-scale proportion is defined 

as the percentage of the area of the primary aquifer system 

with a relative-concentration greater than 1.0 for a particular 

constituent or class of constituents; percentage is based on 

an areal rather than a volumetric basis. Moderate and low 

aquifer-scale proportions were defined as the percentages of 

the primary aquifer system with moderate and low relativeconcentrations, respectively. 

The KLAM study unit includes more than 8,800 square 

miles (mi2

), but only those areas near the sampling sites, about 

920 mi2, are included in the areal assessment of the study 

unit. Two statistical approaches—grid-based and spatially 

weighted—were used to evaluate aquifer-scale proportions for 

individual constituents and classes of constituents. To confirm 

this methodology, 90 percent confidence intervals were 

calculated for the grid-based high aquifer-scale proportions 

and were compared to the spatially weighted results, which 

were found to be within these confidence intervals in all 

cases. Grid-based results were selected for use in the status 

assessment unless, as was observed in a few cases, a gridbased result was zero and the spatially weighted result was not 

zero, in which case, the spatially weighted result was used.

The status assessment showed that inorganic 

constituents with human-health benchmarks were detected 

at high relative-concentrations in 2.6 percent of the primary 
2 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

aquifer system and at moderate relative-concentrations in 

10 percent of the system. The high aquifer-scale proportion 

for inorganic constituents mainly reflected the high aquiferscale proportions of boron. Inorganic constituents with 

secondary maximum contaminant levels were detected at high 

relative-concentrations in 13 percent of the primary aquifer 

system and at moderate relative-concentrations in 10 percent 

of the system. The constituents present at high relativeconcentrations included iron and manganese.

Organic constituents with human-health benchmarks 

were not detected at high relative-concentrations, but were 

detected at moderate relative-concentrations in 1.9 percent 

of the primary aquifer system. The 1.9 percent reflected a 

spatially weighted moderate aquifer-scale proportion for the 

gasoline additive methyl tert-butyl ether. Of the 148 organic 

constituents analyzed, 14 constituents were detected. Only one 

organic constituent had a detection frequency of greater than 

10 percent—the trihalomethane, chloroform.

The second component of this study, the understanding 

assessment, identified the natural and human factors that may 

have affected the groundwater quality in the KLAM study unit 

by evaluating statistical correlations between water-quality 

constituents and potential explanatory factors. The potential 

explanatory factors evaluated were aquifer lithology, land 

use, hydrologic conditions, depth, groundwater age, and 

geochemical conditions. Results of the statistical evaluations 

were used to explain the occurrence and distribution of 

constituents in the KLAM study unit.

Groundwater age distribution (modern, mixed, or premodern), redox class (oxic, mixed, or anoxic), and dissolved 

oxygen concentration were the explanatory factors that best 

explained occurrence patterns of the inorganic constituents. 

High concentrations of boron were found to be associated 

with groundwater classified as mixed or pre-modern with 

respect to groundwater age. Boron was also negatively 

correlated to dissolved oxygen and positively correlated to 

specific conductance. Iron and manganese concentrations were 

strongly associated with low dissolved oxygen concentrations, 

anoxic and mixed redox classifications, and pre-modern 

groundwater. Specific conductance concentrations were 

found to be related to pre-modern groundwater, low dissolved 

oxygen concentrations, and high pH.

Chloroform was selected for additional evaluation in the 

understanding assessment because it was detected in more 

than 10 percent of wells sampled in the KLAM study unit. 

Septic tank density was the only explanatory factor that was 

found to relate to chloroform concentrations.

Introduction

To assess the quality of ambient groundwater in aquifers 

used for drinking-water supply and to establish a baseline 

groundwater-quality monitoring program, the California State 

Water Resources Control Board (SWRCB), in collaboration 

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

Livermore National Laboratory (LLNL), implemented the 

Groundwater Ambient Monitoring and Assessment (GAMA) 

Program (California State Water Resources Control Board, 

2010, website at http://www.waterboards.ca.gov/gama/). The 

statewide GAMA Program was initiated in 2000 in response 

to Legislative mandates (State of California, 1999, 2001a). 

The program currently consists of four projects: (1) the 

GAMA Priority Basin Project, conducted by the USGS 

(U.S. Geological Survey, 2010, 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 webbased groundwater information system, developed by the 

SWRCB. On a statewide basis, the GAMA Priority Basin 

Project focused on the primary aquifer system, typically the 

deep portion of the groundwater resource, and the SWRCB 

Domestic Well Project generally focused on the shallow 

aquifer systems.

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). The GAMA Priority 

Basin Project is a comprehensive assessment of statewide 

groundwater quality designed to improve the understanding 

of and to identify risks to groundwater resources and to 

increase the availability of information about groundwater 

quality to the public. 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), 

the California Department of Pesticide Regulation (CDPR), the 

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 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. 1). These hydrogeologic provinces 

include groundwater basins and subbasins designated by the 

CDWR (California Department of Water Resources, 2003). 

Groundwater basins generally consist of relatively permeable, 

unconsolidated deposits of alluvial origin. Eighty percent of 

California’s approximately 16,000 active or standby publicsupply wells or springs listed in the statewide water-quality 

database maintained by the CDPH (hereinafter referred 

to as CDPH sites) are located within CDWR-designated 

groundwater basins (Belitz and others, 2003). These basins 

were prioritized for sampling on the basis of the number 

of CDPH sites in the basin, with secondary consideration 

given to municipal groundwater use, agricultural pumping, 

the number of historically leaking underground fuel tanks, 
Introduction 3

and the number of square-mile sections having registered 

pesticide applications (Belitz and others, 2003). Of the 472 

CDWR-designated basins and subbasins, 116 basins contain 

approximately 95 percent of CDPH sites located in CDWRdesignated groundwater basins and were defined as priority 

basins (Belitz and others, 2003). The remaining 356 basins 

were defined as low-use basins. All of the priority basins, 

selected low-use basins, and selected areas outside of basins 

were grouped into 35 USGS–GAMA study units that together 

represent approximately 95 percent of all CDPH sites.

Pacific Ocean

NEVADA

ARIZONA

OREGON IDAHO

UTAH

MEXICO

124° 122° 120° 118° 116° 114°

42°

40°

38°

36°

34°

32°

0 50 100 200 Miles

0 50 100 200 Kilometers

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

North American Datum of 1983 (NAD 83)

Hydrogeologic provinces from Belitz and others, 2003

Desert

Sierra Nevada

Basin and Range

Central

Valley

Southern

Coast

Ranges

Northern Coast

Ranges

Cascades and

Modoc Plateau

San Diego

 Drainages

Transverse Ranges and 

selected Peninsular Ranges

Pacific Ocean

San Diego

Sacramento

Los Angeles

Bakersfield

San Francisco

Redding

Klamath Mountains

Study Unit

Figure 1. Hydrogeologic provinces of California and the location of the Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project.
4 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

The Klamath Mountains (KLAM) study unit corresponds 

to the Klamath Mountains hydrogeologic province described 

by Belitz and others (2003) (fig. 1), which is composed 

primarily of areas outside of CDWR-designated groundwater 

basins. About 99 percent of the total area and approximately 

85 percent of the CDPH sites in the province are outside of 

CDWR-designated groundwater basins (Belitz and others, 

2003). Of the approximately 16,000 CDPH sites throughout 

the State, only about 1 percent are located in the KLAM study 

unit. The KLAM study unit includes one priority basin (Scott 

River Valley) and six low-use basins (Seiad Valley, Hoopa 

Valley, Hyampom Valley, Happy Camp Town Area, Hayfork 

Valley, and Wilson Point Area) (Belitz and others, 2003; 

California Department of Water Resources, 2003) (fig. 2).

The goal of the GAMA Priority Basin Project is to 

produce three types of water-quality assessments for each 

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

groundwater resource, (2) Understanding: identification of the 

natural and human factors affecting groundwater quality and 

explanation of the relations between water quality and selected 

explanatory factors, and (3) Trends: detection of changes 

in groundwater quality (Kulongoski and Belitz, 2004). 

The assessments are intended to characterize the quality of 

groundwater within the primary aquifer system of the study 

unit, not the treated drinking water delivered to consumers by 

water purveyors. The primary aquifer system for a study unit 

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

the wells listed in the CDPH water-quality database for the 

study unit. The CDPH water-quality database lists wells used 

for public drinking-water supplies and includes wells from 

systems classified as community (such as cities, towns, and 

mobile-home parks), non-transient, non-community (such as 

schools, workplaces, and restaurants), and transient, noncommunity (such as campgrounds and parks). Groundwater 

quality in the primary aquifer system may differ from 

that in shallower or deeper parts of the aquifer system. In 

particular, shallower groundwater may be more vulnerable to 

contamination from the land surface.

Purpose and Scope

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

unit description: description of the hydrogeologic setting of 

the KLAM study unit, (2) status assessment: assessment of 

the status of the current quality of groundwater in the primary 

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

assessment: identification of the natural and anthropogenic 

factors affecting groundwater quality. Assessments are made 

for chemical constituents only; microbiological indicators of 

groundwater quality are not discussed in this report. Trends in 

groundwater quality are not discussed in this report.

Features of the hydrogeologic setting are described 

on the scale of the entire KLAM 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 aquifer lithology, land 

use, hydrologic conditions, depth, groundwater age, and 

geochemical conditions are described by using explanatory 

factor data compiled for the 39 groundwater sites sampled by 

USGS–GAMA for the study unit.

The status assessment includes analyses by the USGS 

of water-quality data for 39 sites, 38 of which were selected 

for spatial coverage of 1 site per grid cell (hereinafter referred 

to as USGS-grid sites), across the KLAM study unit. The 

details of sample collection, analysis, and quality-assurance 

procedures for the KLAM study unit and all of the waterquality data collected are reported by Mathany and Belitz 

(2014). Water-quality data from the CDPH water-quality 

database were used to supplement data collected by the USGS 

for the GAMA Program. The resulting set of water-quality 

data from USGS-grid sites and CDPH sites was considered 

to be representative of the primary aquifer system in the 

KLAM study unit; the primary aquifer system is defined by 

the depths of the screened or open intervals of the sites listed 

in the CDPH water-quality database for the KLAM study 

unit. GAMA status assessments were designed to provide a 

statistically robust characterization of groundwater quality 

in the primary aquifer system at the basin-scale (Belitz and 

others, 2003, 2010). The statistically robust design also 

allows basins to be compared and results to be synthesized 

regionally and statewide. This report describes methods used 

in designing the sampling network, identifying CDPH data 

for use in the status assessments, estimating aquifer-scale 

proportions of relative-concentrations, and assessing the status 

of groundwater quality by statistical and graphical approaches.

To provide context, the water-quality data discussed in 

this report were compared to California and Federal regulatory 

and non-regulatory benchmarks for drinking water. This study 

does not attempt to evaluate the quality of water delivered to 

consumers; after withdrawal from the ground, water typically 

is treated, disinfected, or blended with water from other 

sources to maintain acceptable water quality. Regulatory 

benchmarks apply to drinking water that is delivered to the 

consumer, not to untreated groundwater.

The understanding assessment is based on water-quality 

data from 39 sites sampled by the USGS for the GAMA 

Program (Mathany and Belitz, 2014). The potential explanatory 

factors affecting water quality in the primary aquifer system 

evaluated are aquifer lithology, land use, hydrologic conditions, 

depth, groundwater age, and geochemical conditions. 

Connections between potential explanatory factors and water 

quality were evaluated by using statistical tests for correlations 

and by analysis of graphical relations.
Introduction 5

124° 123°30' 123° 122°30' 122°

41°30'

40°30'

42°

41°

EXPLANATION

Mountain peak

USGS-grid site

USGS-understanding site

Cities

Counties

Gridded area

CDWR groundwater basin

Study unit boundary

Central Valley

Northern Coast Ranges

Cascades and Modoc Plateau

Hydrogeologic Province

Whiskeytown

Lake

Trinity

Lake

Shasta

Lake

Seiad Valley

Happy Camp 

Town Area

TRINITY ALPS

SALMON MTNS

SISKIYOU CO

HUMBOLDT CO

SHASTA CO

SISKIYOU CO

MOUNT 

SHASTA

0 10 20 MILES 5

0 10 20 KILOMETERS 5

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Gasquet

Yreka

Mount Shasta

Willow Creek

Redding

Smith River

Scott

River

Klamath River

North Fork Trinity River

Sacramento River

Trinity

River

Trinity River

South Fork Trinity River

DEL NORTE CO

HUMBOLDT CO

TRINITY CO

SHASTA CO

TEHAMA CO

SISKIYOU MTNS

MOUNT 

EDDY

Hyampom Valley

Hayfork Valley

Wilson Point

Area

Hoopa Valley

Scott River Valley MARBLE MTNS

SCOTT MTNS

OREGON

Pit River

Figure 2. Geographic features and locations of sampled sites in the Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project.
6 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Methods

This section describes the methods used for the status 

assessment and understanding assessment for water quality in 

the KLAM study unit. Methods used for compiling data for 

the potential explanatory factors are described in appendix A.

Status Assessment

The status assessment is intended to characterize the 

quality of groundwater resources in the primary aquifer 

system of the KLAM study unit. Methods used for the status 

assessment included (1) assembling water-quality benchmarks, 

(2) assembling datasets for use in the status assessment and 

calculating relative-concentrations, (3) selecting constituents 

for additional evaluation, and (4) calculating aquifer-scale 

proportions for these constituents. 

Water-Quality Benchmarks and 

Relative-Concentrations

To provide context for water-quality data, measured 

concentrations of constituents may be compared to waterquality benchmarks established by the U.S. Environmental 

Protection Agency (USEPA) and CDPH that are typically 

applied to finished drinking water (U.S. Environmental 

Protection Agency, 1999, 2009, 2012a; California Department 

of Public Health, 2010, 2013). The benchmarks used for each 

constituent were selected in the following order of priority:

1. Regulatory, health-based CDPH and USEPA maximum 

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

levels (AL-US), and treatment technique levels (TT-US).

2. Non-regulatory CDPH and USEPA secondary maximum 

contaminant levels (SMCL-CA and SMCL-US). For 

constituents with recommended and upper SMCL-CA 

levels, the values for the upper levels were used.

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

(NL-CA), USEPA lifetime health advisory levels 

(HAL-US), and USEPA risk-specific doses for 1:100,000 

(RSD5-US).

For constituents with multiple types of benchmarks, 

this hierarchy may not result in selection of the benchmark 

with the lowest concentration. Additional information on the 

types of benchmarks and listings of the benchmarks for all 

constituents analyzed are provided by Mathany and Belitz 

(2014).

Groundwater-quality data are presented as relativeconcentrations, the concentrations of constituents measured 

in groundwater relative to regulatory and non-regulatory 

benchmarks used to evaluate drinking-water quality:

Relative concentration Sample concentration

Benchmark conce - = ntration

(1)

Relative-concentrations less than 1.0 indicate a sample 

concentration less than the benchmark, and relativeconcentrations greater than 1.0 indicate a sample concentration 

greater than the benchmark. The use of relative-concentrations 

also permits comparison on a single scale of constituents 

present at a wide range of concentrations. Relativeconcentrations can only be computed for constituents with 

water-quality benchmarks; therefore, constituents without 

water-quality benchmarks are not included in the status 

assessment.

The two microbial indicators analyzed in samples from 

the KLAM study unit, total coliform bacteria and Escherichia 

coli (E. coli), have drinking-water-quality benchmarks, but are 

not included in the status assessment because the results will 

be presented in one report for all 35 GAMA Priority Basin 

Project public-supply aquifer study units (Carmen Burton, 

U.S. Geological Survey, written commun., 2014).

Toccalino and others (2004), Toccalino and Norman 

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

ratio of measured sample concentration to the benchmark 

concentration [either MCL-US or health-based screening 

levels (HBSLs)] and defined this ratio as the benchmark 

quotient. 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 may be used to calculate relative-concentrations 

and benchmark quotients, the terms are not interchangeable.
Methods 7

For ease of discussion, relative-concentrations of 

constituents were classified into low, moderate, and high 

categories:

Category

Relativeconcentrations for 

organic constituents

Relativeconcentrations 

for inorganic 

constituents

High > 1 > 1

Moderate > 0.1 and ≤ 1 > 0.5 and ≤ 1

Low ≤ 0.1 ≤ 0.5

For organic constituents, a relative-concentration of 

0.1 was used as a threshold to distinguish between low and 

moderate relative-concentrations for consistency with other 

studies and reporting requirements (U.S. Environmental 

Protection Agency, 1998; Toccalino and others, 2004). For 

inorganic constituents, a relative-concentration of 0.5 was 

used as a threshold to distinguish between low and moderate 

relative-concentrations. The primary reason for using a 

higher threshold was to focus attention on the inorganic 

constituents of greatest concern (Fram and Belitz, 2012). The 

naturally occurring inorganic constituents tend to be more 

prevalent than organic constituents in groundwater. 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.

Datasets Used for Status Assessment

Groundwater-quality data used for the status assessment 

came from sites sampled by the USGS and from the CDPH 

water-quality database. To obtain a spatially unbiased 

representation of the KLAM study unit, a grid-based approach 

was used, which relied on sites sampled by the USGS (USGSgrid sites) supplemented by data from CDPH sites (CDPH-grid 

sites) selected to provide a more complete coverage of the 

gridded area. Combined, they are referred to as the grid-site 

dataset. Additional data from the CDPH water-quality database 

were used for a spatially weighted approach described later. 

This section describes how these datasets was constructed. 

U.S. Geological Survey Grid Sites

The primary data used for the grid-based calculations 

of aquifer-scale proportions of relative-concentrations were 

from sites sampled by USGS–GAMA. Detailed descriptions 

of the methods used to identify sites for sampling are given 

in Mathany and Belitz (2014). Briefly, the KLAM study unit 

was divided into 40 equal-area grid cells, and the objective 

was for the USGS to collect water-quality samples from 

one CDPH site in each cell. The KLAM study unit had 

relatively few CDPH sites, and these CDPH sites were not 

evenly distributed (fig. 3). To minimize the number of cells 

without any sampled sites, only the parts of the study unit 

near CDPH sites were included in the gridded area. A 1.86-

mile (mi) (3-kilometer [km]) radius circle was drawn around 

each CDPH site, and the collective area encompassed by the 

circles was divided into forty 23-square-mile (mi2) (60-squarekilometer [km2

]) grid cells, as described by Scott (1990) 

and shown in appendix B, figs. B1–B5. One CDPH site was 

randomly selected for sampling in each cell. If a cell had no 

accessible CDPH sites, then an appropriate site was selected 

by door-to-door canvassing. The USGS sampled sites in 38 of 

the 40 grid cells (hereinafter referred to as USGS-grid sites). 

Of the 38 USGS-grid sites, 33 were listed in the CDPH waterquality database, and the other 5 sites were screened or had 

open intervals at depths similar to those of sites listed in the 

CDPH water-quality database. USGS-grid sites were named 

with an alphanumeric GAMA identification consisting of the 

prefix “KLAM” and a number indicating the order of sample 

collection (appendix B, figs. B1–B5). One additional site was 

sampled by USGS–GAMA. This “USGS-understanding” site 

was given the identification number KLAM-U-01. This site 

was sampled in error and is in the same cell as the USGSgrid site KLAM-15. Samples collected from USGS-grid sites 

were analyzed for 216 constituents (table 1). The collection, 

analysis, and quality-control data for the constituents listed in 

table 1 are described by Mathany and Belitz (2014).

California Department of Public Health Grid Sites

The CDPH data were used in three ways in the status 

assessment: (1) to supplement the USGS data for the gridbased calculations of aquifer-scale proportions, (2) to select 

constituents for additional evaluation in the assessment, and 

(3) to provide additional data used in the spatially weighted 

calculations of aquifer-scale proportions.
8 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

sac14-0524_fig 03

0 10 20 MILES 5

0 10 20 KILOMETERS 5

OREGON

124° 123°30' 123° 122°30' 122°

42°

41°30'

40°30'

41°

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Pit River

Sacramento Ri

T

ver

rinity

River

Trinity River

North Fork Trinity River

Klamath River

Scott

River

South Fork Trinity River

Smith River

EXPLANATION

USGS-grid site

USGS-understanding site

CDPH site

Gridded area

Study unit boundary

Figure 3. Locations of grid sites, the understanding site, and California Department of Public Health (CDPH) sites sampled for the 

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.
Methods 9

Table 1. Summary of constituent groups and numbers of constituents sampled for each constituent group by the U.S. Geological 

Survey (USGS) in the Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

[Abbreviations and symbols: B, boron; C, carbon; H, hydrogen; He, helium; O, oxygen; Sr, strontium; δ, delta notation, the ratio of a heavier isotope of an 

element. Unless otherwise noted, constituent analyses were performed at the USGS National Water Quality Laboratory]

Site summary

Total number of sites 39

Number of grid sites sampled 38

Number of understanding sites sampled 1

Number of 

constituents analyzed

Inorganic constituents

Alkalinity and total dissolved solids (TDS) 2

Gross alpha and beta radioactivity 1 2

Trace elements and major and minor ions 35

Nutrients 5

Radon-222 1

Specific conductance (field) 2 1

Uranium isotopes 3 1

Organic constituents

Pesticides and pesticide degradates 63

Volatile organic compounds (VOCs) 4 85

Tracers

Arsenic and iron species 2

δ11B in water 5 1

Carbon-14 and δ13C of dissolved carbonates 2

Dissolved oxygen, pH, and temperature (field) 2 3

δ2

H and δ18O stable isotopes of water 2

Dissolved noble gases (helium, neon, argon, krypton, xenon), 3

He/4He of helium, and tritium 6 7

87Sr/86Sr of dissolved strontium 5 1

Tritium 7 1

Microbial indicators

Total coliforms and Escherichia coli (E. coli) 2 2

Sum: 216

1

 Gross alpha particle and gross beta particle activities were measured after 72-hour and 30-day holding times; data from the 72-hour measurements are used 

in this report. 

2

 Analyzed by USGS field staff.

3

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

4

 Includes 10 constituents classified as fumigants or fumigant synthesis byproducts.

5

 Analyzed at the USGS Metals Isotope Research Laboratory, Menlo Park, California.

6

 Analyzed at Lawrence Livermore National Laboratory, Livermore, California.

7

 Analyzed at USGS Stable Isotope and Tritium Laboratory, Menlo Park, California.
10 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Data collected by USGS–GAMA at the USGS-grid sites 

(Mathany and Belitz, 2014) provided the majority of the data 

used for the status assessment for inorganic constituents. 

Although other organizations also collect water-quality 

data, the CDPH database is the only statewide database of 

groundwater-chemistry data available for comprehensive 

analysis. The CDPH water-quality database contains records 

from more than 25,000 sites, necessitating targeted retrievals 

to effectively access relevant water-quality data. For example, 

for the area representing the KLAM study unit, the CDPH 

water-quality database contains 16,801 records from 204 sites 

for the period of record before this study (June 14, 1984, 

to November 30, 2007). To provide additional data in grid 

cells that did not have wells sampled by USGS–GAMA, 

two CDPH sites were selected from the CDPH water-quality 

database to provide inorganic constituent data. CDPH sites 

with data available for the time period December 1, 2007, 

through December 31, 2010, were considered, and if a site had 

more than one analysis for a constituent, data from the most 

recent sampling event were selected. The selected CDPH sites 

(hereinafter referred to as CDPH-grid sites) were named with 

an alphanumeric GAMA identification consisting of the prefix 

“KLAM-DPH” and the next number in the sequence of grid 

sites. One of the cells without a USGS-grid site contained two 

CDPH sites, and both sites only had data for nutrients. One 

site was randomly selected from the two to be the CDPH-grid 

site. The other cell without a USGS-grid site contained one 

CDPH site. This site was selected as the CDPH-grid site, and 

it provided data for nutrients and a subset of trace elements 

(table C1).

CDPH data were not used to provide grid values for 

volatile organic compounds (VOCs) or pesticides because 

a larger number of VOCs and pesticide compounds were 

analyzed for the USGS–GAMA Program than were available 

from the CDPH water-quality database. In addition, method 

detection limits for USGS–GAMA analyses were one to two 

orders of magnitude less than the reporting levels for analyses 

compiled by the CDPH (Fram and Belitz, 2012).

Additional Data Used for Spatially Weighted Calculations

The spatially weighted calculations of aquifer-scale 

proportions of relative-concentrations used data from all 

KLAM study unit sites sampled by USGS–GAMA and from 

all sites in the CDPH water-quality database with waterquality data collected during the 3-year interval December 1, 

2007, through December 31, 2010. For sites and constituents 

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

Ninety-two CDPH sites that were not also USGS-grid sites 

had data for at least one water-quality constituent; however, 

for 66 of these sites, data were only available for nutrients. 

Water-quality information from the CDPH wells used in the 

spatially weighted analysis is available from the GeoTracker 

GAMA web-based groundwater information system, 

developed by the SWRCB (California State Water Resources 

Control Board, 2011). 

Selection of Constituents for Additional 

Evaluation in the Status Assessment

As many as 216 constituents were analyzed in samples 

from KLAM study unit sites; however, only subsets of 

these constituents were identified for additional evaluation 

in the status assessment. Of the 216 constituents analyzed, 

100 constituents did not have benchmarks (table 2). 

Because relative-concentrations cannot be calculated for 

constituents without benchmarks, these 100 constituents 

were not evaluated in this report. The 116 constituents having 

benchmarks were assessed, and a subset of these constituents 

were selected for additional evaluation in the status assessment 

on the basis of the following three criteria:

• Constituents present at high or moderate relativeconcentrations in the CDPH water-quality database 

within the 3-year interval (December 1, 2007, through 

December 31, 2010), hereinafter referred to as the 

current sampling period;

• Constituents present at high or moderate relativeconcentrations in the USGS-grid sites or USGSunderstanding site; or

• Organic constituents with detection frequencies of 

greater than 10 percent in the USGS-grid site dataset 

for the study unit.

These criteria identified 13 inorganic and 3 organic 

constituents for additional evaluation in the status assessment. 

A complete list of the constituents investigated by USGS–

GAMA in the KLAM study unit may be found in the data 

report (Mathany and Belitz, 2014).

The CDPH water-quality database also was used to 

identify constituents with high relative-concentrations 

historically, but not currently. The historical period was 

defined as extending from the earliest record maintained in 

the CDPH water-quality database for sites in the KLAM study 

unit to November 30, 2007 (June 14, 1984, to November 30, 

2007). Constituent concentrations may have been historically 

high, but not currently high, because of improvement of 

groundwater quality with time or abandonment of sites 

with high concentrations. Historically high concentrations 

of constituents that did not otherwise meet the criteria for 

additional evaluation are not considered representative of 

potential groundwater-quality concerns in the study unit from 

2007 to 2010.

For the KLAM study unit, eight inorganic constituents 

had high concentrations reported in the CDPH water-quality 

database during the historical period, but did not have high 

concentrations reported during the current period or in the 

USGS–GAMA dataset (table 3). Of these eight constituents, 

two were also detected at moderate relative-concentrations 

during the current period (chloride and gross alpha 

radioactivity). 
Table 2. Numbers of constituents analyzed and detected, by benchmark and constituent type, Klamath Mountains study unit, 2010, California GAMA [Benchmark type: Regulatory health-based benchmarks include: MCL-US, USEPA maximum contaminant level; AL-US, USEPA action level; MCL-CA, CDPH maximum conhealth-based benchmarks include HAL-US, USEPA lifetime health advisory level; NL-CA, CDPH notification level. Non-regulatory aesthetic benchmarks include SMCL-CA, Ccontaminant level. Abbreviations: USEPA, U.S. Environmental Protection Agency; CDPH, California Department of Public Health]

Benchmark 

type

Constituent type 

Inorganic constituents Organic constituents Age tracers Microbial indicators 

Number 

analyzed

Number 

detected

Number 

analyzed

Number 

detected

Number 

analyzed

Number 

detected

Number 

analyzed

Number 

detected

Regulatory health-based 20 20 36 11 1 1 2 2 

Non-regulatory health-based 5 5 42 2 0 0 0 0 

Non-regulatory aesthetic-based 9 9 0 0 1 1 0 0 

No benchmark 13 13 70 1 17 17 0 0 

Total: 47 47 148 14 19 19 2 2 

Table 3. Constituents historically (June 14, 1984, to November 30, 2007) reported at concentrations greater than benchmarks in the California Departdatabase, but not during the 3-year period used in the status assessment, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project[Benchmark type: Regulatory, health-based benchmarks: MCL-US, USEPA maximum contaminant level; AL-US, USEPA action level; MCL-CA, CDPH maximum contaminahealth-based benchmarks: HAL-US, USEPA lifetime health advisory level. Non-regulatory, aesthetic-based benchmarks: SMCL-CA, CDPH secondary maximum contaminant lmilligrams per liter; μg/L, micrograms per liter; pCi/L, picocuries per liter. Other abbreviations: GAMA, Groundwater Ambient Monitoring and Assessment Program; USEPAAgency; CDPH, California Department of Public Health]

Constituent Typical use 

or source

Benchmark Date of most 

recent high value

Number o

with histor

Type 1 Value Units 

Aluminum Naturally occurring MCL-CA 1,000 μg/L 05/19/98 58 

Chloride 2 Naturally occurring SMCL-CA 500 mg/l 06/24/99 57 

Fluoride Naturally occurring MCL-CA 2 μg/L 11/07/01 68 

Gross alpha particle activity 2 Naturally occurring MCL-US 15 pCi/L 05/05/89 41 

Lead Naturally occurring AL-US 15 μg/L 03/09/04 57 

Nickel Naturally occurring MCL-CA 100 μg/L 09/14/99 53 

Radium-226 Naturally occurring MCL-US 5 pCi/L 05/05/89 2 

Zinc Naturally occurring SMCL-CA 5,000 μg/L 03/10/98 57 

1 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-

Sources of benchmarks: MCL-CA: California Department of Public Health (2013); MCL-US and AL-US: U.S. Environmental Protection Agency (2012a); SMCL-CA: Californ(2013).

2 Constituent was detected at moderate relative-concentrations within the grid-site dataset and therefore was selected for additional evaluation in the status assessment for the 
12 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Calculation of Aquifer-Scale Proportions

Two statistical approaches, grid-based and spatially 

weighted (Belitz and others, 2010), were selected to 

evaluate the proportions of the primary aquifer system in 

the KLAM study unit with high, moderate, and low relativeconcentrations of constituents. For ease of discussion, these 

proportions are referred to as “high,” “moderate,” and “low” 

aquifer-scale proportions. Calculations of aquifer-scale 

proportions were made for individual constituents, as well as 

for classes of constituents. The classes consisted of groups of 

related individual constituents.

The grid-based calculation uses the grid-site dataset 

assembled from the USGS-grid and CDPH-grid sites. For 

each constituent, the high aquifer-scale proportion was 

calculated by dividing the number of cells represented by a 

high relative-concentration (> 1.0) for that constituent by the 

total number of grid cells with data for that constituent. The 

moderate and low aquifer-scale proportions were calculated 

using the numbers of cells with moderate and low relative 

concentrations, respectively. Confidence intervals on the 

grid-based results for the high aquifer-scale proportions for 

individual constituents were computed using the Jeffreys 

interval for the binomial distribution (Brown and others, 2001; 

Belitz and others, 2010). For calculation of high aquifer-scale 

proportion for a class of constituents, cells were considered 

high if any of the constituents in that class had high relative 

concentrations. Cells were considered moderate if any of the 

constituents in the class had moderate relative concentrations, 

but no high relative concentrations. The grid-based estimate 

is designed to be spatially unbiased. However, the grid-based 

approach may not detect constituents that are present at high 

or moderate concentrations in small proportions of the primary 

aquifer system; therefore, a spatially weighted calculation was 

performed to complement the grid-based approach.

The spatially weighted calculation used the dataset 

assembled from all CDPH and USGS–GAMA sites. For each 

constituent, the high aquifer-scale proportion was calculated 

by computing the proportion of sites with one or more high 

relative-concentrations in each cell and then averaging the 

proportions for all cells (Isaaks and Srivastava, 1989; Belitz 

and others, 2010). The moderate aquifer-scale proportion 

was calculated similarly. For calculation of high aquiferscale proportion for a class of constituents, the aquifer-scale 

proportion was considered high if any of the constituents 

in that class were high. The aquifer-scale proportion was 

considered moderate if any of the constituents in the class 

were moderate, but none were high.

In addition, for each constituent, the raw detection 

frequencies of high and moderate aquifer-scale proportions for 

individual constituents were calculated using the same dataset 

as used for the spatially weighted calculations. Raw detection 

frequencies are not spatially unbiased, however, because the 

sites in the CDPH water-quality database are not uniformly 

distributed throughout the KLAM study unit (fig. 3). For 

example, if a constituent were present at high concentrations 

in a small region of the aquifer with a high density of sites, the 

raw detection frequency of high values would be greater than 

the high aquifer-scale proportion. Raw detection frequencies 

are provided for reference but were not used to assess aquiferscale proportions (see appendix C for additional details about 

the statistical approaches).

The grid-based high aquifer-scale proportions were used 

to represent proportions in the primary aquifer system unless 

the spatially weighted proportions were significantly different 

from the grid-based values. Significantly different results were 

defined as follows:

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

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

situation can happen when the relative-concentration of 

a constituent is high in a small fraction of the primary 

aquifer system.

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

non-zero and the spatially weighted proportion was 

outside the 90 percent confidence interval (based on 

the Jeffreys interval for the binomial distribution), then 

the spatially weighted proportion was used.

The grid-based moderate and low aquifer-scale 

proportions were used in most cases because the reporting 

levels for many organic constituents and some inorganic 

constituents in the CDPH water-quality database were higher 

than the threshold between moderate and low categories. 

However, if the grid-based moderate proportion was zero and 

the spatially weighted proportion non-zero, then the spatially 

weighted value was used as a minimum estimate for the 

moderate proportion.

Understanding Assessment

Methods used for the understanding assessment 

included (1) selecting constituents for additional evaluation 

in the understanding assessment, and (2) applying statistical 

tests of relations between potential explanatory factors and 

groundwater quality.

Selection of Constituents for Additional 

Evaluation in the Understanding Assessment

The understanding assessment places groundwater quality 

within a physical and chemical context based on the potential 

explanatory factors. A subset of constituents was selected for 

additional evaluation in the understanding assessment on the 

basis of the following two criteria:

• Constituents with high aquifer-scale proportions 

of greater than 2 percent. These constituents were 

selected to focus the assessment for understanding 

on those constituents that have the greatest effect on 

groundwater quality.
Hydrogeologic Setting and Potential Explanatory Factors 13

• Classes of organic constituents that included 

constituents with study-unit detection frequencies of 

greater than 10 percent, regardless of concentration.

These criteria resulted in selection of three inorganic 

constituents and one organic constituent for additional 

evaluation in the understanding assessment. The understanding 

assessment was based on the 39 wells sampled by USGS–

GAMA (Mathany and Belitz, 2014). Other CDPH wells were 

not used because data for many of the potential explanatory 

factors were not available.

Statistical Tests of Relations between Potential 

Explanatory Factors and Groundwater Quality

Nonparametric statistical methods were used to test 

the significance of correlations among potential explanatory 

factors and between water-quality parameters and potential 

explanatory factors. 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 attained significance level 

(p), which was attained from the data and used for hypothesis 

testing for this report, was compared to a critical level (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, 

and oxidation-reduction class were treated as categorical 

variables. Land use, septic tank density, leaking (or formerly 

leaking) underground fuel tank (LUFT) density, aridity 

index, elevation, well depth, depth to top of screened or open 

interval, pH, and dissolved oxygen were treated as continuous 

variables. Concentrations of water-quality constituents were 

treated as continuous variables.

Correlations between potential explanatory factors and 

water-quality constituents were tested for significance.

• Correlations between continuous variables were 

evaluated by using the Spearman’s rho test to calculate 

the rank-order coefficient (ρ, rho) and to determine 

whether the correlation was significant (p < α). Values 

of ρ could range from –1 (complete correlation in 

opposite directions) to 0 (no correlation) to 1 (complete 

correlation in the same direction).

• Relations between categorical variables and continuous 

variables were evaluated by using the Wilcoxon 

rank-sum test. The null hypothesis for the test is that 

the median values of the continuous variable are not 

significantly different from one another.

• Relations between categorical variables were evaluated 

using contingency tables (Helsel and Hirsch, 2002). 

For a 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 entries in 

the cells of the matrix are the number of observations, 

Oij, which fall into the ith row and the jth column of the 

matrix. A test statistic (Xct) is computed by comparing 

the observed counts (Oij) to the counts expected if 

the two variables are independent, and significance 

is determined by comparing the test statistic to the 

(1–α) quantile of the chi-squared distribution. If the 

contingency table yielded a result of significance, the 

relation of the variables was determined by comparing 

the relative difference in magnitudes of the test 

statistics in each cell of the contingency table.

Hydrogeologic Setting and Potential 

Explanatory Factors

The KLAM study unit covers an area of approximately 

8,806 mi2 (22,809 km2) in parts of Del Norte, Humboldt, 

Shasta, Siskiyou, Tehama, and Trinity Counties in northern 

California (fig. 2) and consists primarily of mountainous 

terrain composed of relatively low-permeability rocks. The 

area of the study unit covered by grid cells (gridded area) is 

about 920 square miles (2,400 square kilometers). The gridded 

area is commonly located near rivers and lakes throughout 

the study unit. The study unit is bounded on the east by the 

volcanic rocks of the Cascades Range and Modoc Plateau, on 

the west by the Northern Coast Ranges, and on the south by 

the sediments of the Central Valley. The northern boundary is 

the Oregon State line.

Features of the hydrogeologic setting are described on 

the scale of the entire KLAM 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 are described using explanatory factor data 

compiled for the 39 sites sampled by USGS–GAMA for the 

study unit. Explanatory factors are grouped in three categories 

for discussion: geologic factors (aquifer lithology), land-use 

factors (percentages of agricultural, natural, and urban land 

use, and septic and underground fuel tank densities), and 

hydrologic conditions (elevation, aridity index, site type, 

well depth, groundwater age, and geochemical conditions). 

The presence of correlations among explanatory factors may 

confound interpretation of correlations between explanatory 

factors and groundwater quality, so correlations among 

explanatory factors are discussed in this section. The methods 

used for assigning values for each of the explanatory factors 

to the 39 sites sampled by USGS–GAMA in the KLAM study 

unit are described in appendix A.
14 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

For this report, the primary aquifer system is defined by 

the depth intervals over which public-supply wells listed in the 

CDPH water-quality database are screened or open. The use 

of the term “primary aquifer system” does not imply that there 

exists a discrete aquifer unit. In most groundwater basins, 

public-supply wells generally are screened or open at greater 

(deeper) depths than are domestic 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 used for 

public drinking-water supply and domestic drinking-water 

supply wells commonly does not apply in areas outside of 

groundwater basins defined by the CDWR. Wells in fracturedrock 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). The definition of the primary aquifer system in 

the KLAM study unit is further complicated by the abundance 

of spring sites among the CDPH sites and the sites sampled 

by USGS–GAMA. A screened or open interval cannot be 

defined for springs; although groundwater from a spring may 

be collected at or near land-surface datum, the depth interval 

of origin is generally unknown.

Aquifer Lithology

The geologic history of the Klamath Mountains is 

complex. It is characterized by multiple episodes of oceanic 

crustal accretion and plutonic emplacement along the Pacific 

Northwest tectonic boundary between the Juan de Fuca and 

North American tectonic plates. Accretionary episodes within 

the KLAM study unit likely began in the early Paleozoic and 

extended through the Late Jurassic if not middle Cenozoic 

(Snoke and Barnes, 2006). Each accretionary episode is 

generally recognized as a unique tectonostratigraphic terrane. 

The terranes are stacked against one another with high-angle 

east-dipping faults separating them, with the oldest terranes in 

the east and progressively younger terranes to the west (Irwin 

and Wooden, 1999). Regional studies conducted by the USGS 

and others often divide the Klamath Mountain geologic region 

into distinct geologic belts or terranes (Irwin and Wooden, 

1999; Alt and Hyndman, 2000; Snoke and Barnes, 2006). 

Each terrane is a complex of similar assemblages of rocks that 

share a similar history or origin. The terranes of the Klamath 

Mountains are primarily composed of metasedimentary 

(metamorphosed oceanic and other sedimentary rocks), 

granite, and ultramafic rock types (fig. 4). The granitic rocks 

are the result of intrusions into the terranes, which emplaced 

plutons of varying composition and size throughout the 

Klamath Mountains during their development, while the 

ultramafic rocks are remnants of oceanic seafloor (Alt and 

Hyndman, 2000; Snoke and Barnes, 2006). 
Hydrogeologic Setting and Potential Explanatory Factors 15

0 10 20 MILES 5

0 10 20 KILOMETERS 5

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

EXPLANATION

Geology

Undifferentiated rocks

Alluvial sediments

Granitic rocks

Metamorphic rocks

Metasedimentary rocks

Ultramafic/Mafic rocks

OREGON

124° 123°30' 123° 122°30' 122°

40°30'

41°30'

42°

41°

sac14-0524_fig 04

USGS-grid site

USGS-understanding site

CDPH site

Gridded area

Study unit boundary

Figure 4. Geology of the Klamath Mountains study unit, California GAMA Priority Basin Project (modified from Saucedo and others, 2000).
16 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

For the purpose of examining broad relations between 

aquifer lithology and groundwater quality, the geologic units 

represented on the State geologic map (Jennings, 1977; 

Saucedo and others, 2000) in the KLAM study unit were 

simplified into six rock types (fig. 4; appendix A):

• Granitic rocks: Primarily Mesozoic granitic rocks with 

some Paleozoic granitic rocks;

• Metamorphic rocks (other than metasedimentary): 

Mesozoic, Paleozoic, and pre-Cenozoic metavolcanic 

rocks;

• Metasedimentary rocks: Metamorphosed Mesozoic and 

Paleozoic marine rocks;

• Ultramafic/mafic rocks: Chiefly Mesozoic ultramafic, 

mafic, or gabbroic rocks;

• Alluvial sediments: Chiefly Quaternary alluvial 

sediments;

• Undifferentiated rocks.

The specific tectonostratigraphic terranes for each 

sampling site were not taken into account. In a previous 

GAMA study in the Sierra Nevada, significant differences in 

groundwater quality were observed when comparing results 

based on different rock types (Fram and Belitz, 2012).

The area of each rock type as a percentage of the 

total area of the KLAM study unit was metasedimentary, 

46 percent; metamorphic, 18 percent; ultramafic/mafic, 

16 percent; granitic, 13 percent; undifferentiated, 4 percent; 

and alluvial sediment, 2 percent. The percentages of wells 

sampled in each rock type were similar to the areal proportions 

of rock types identified in the study unit. Of the 38 cells 

with grid wells in the KLAM study unit, 17 wells represent 

the metasedimentary rock type (45 percent of grid wells), 

10 wells represent the metamorphic rock type (26 percent of 

grid wells), 7 wells represent the ultramafic/mafic rock type 

(18 percent of grid wells), and 4 wells represent the granitic 

rock type (10 percent of grid wells). No sampled wells 

represented either the alluvial sediment or undifferentiated 

rock types (table A1). About 12 percent of CDPH wells 

are located in alluvial sediments, and 6 percent are located 

in undifferentiated rocks; however, these aquifer lithology 

classes only represent 2 and 4 percent, respectively, of the 

KLAM study unit area. The understanding well was in the 

metasedimentary rock type.

Land Use

Land use was described by three land-use types: natural, 

urban, and agricultural (appendix A). Percentages of the 

three types were calculated for the study unit as whole and 

for areas within a radius of 500 meters (m) (500-m buffers) 

around sites (USGS and CDPH) (Johnson and Belitz, 2009). 

As of 1992, land use in the KLAM study unit was 97 percent 

natural, 2 percent urban, and 1 percent agricultural (figs. 5, 6; 

Nakagaki and others, 2007). Nearly all of the agricultural land 

was located in the Scott River Valley groundwater basin in 

the northeastern part of the study unit (fig. 2). No sites were 

sampled within the Scott River Valley groundwater basin.

Percent agriculture

100 80 60 40 20 0

Percent urban

Percent natural

0

20

40

60

80

100

0

20

40

60

80

100

Grid site

Understanding site

EXPLANATION

Average land use for study unit

Average for grid sites

Average for all CDPH sites

Individual sites Area averages

Land-use information obtained from Nakagaki and others, 2007

Figure 5. Percentages of urban, agricultural, and natural land 

use surrounding individual USGS-grid and USGS-understanding 

sites, and land-use averages in the study unit, around grid sites, 

and around CDPH sites in the Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.
Hydrogeologic Setting and Potential Explanatory Factors 17

sac14-0524_fig 06

124° 123°30' 123° 122°30' 122°

Seiad Valley

OREGON

EXPLANATION

USGS-grid site

USGS-understanding site

Gridded area

CDWR groundwater basin

Study unit boundary

Urban

Agricultural

Natural

Land use

0 5 10 20 MILES

0 10 20 KILOMETERS 5

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

41°30'

40°30'

41°

42°

Scott River Valley

Hoopa Valley

Hyampom Valley

Hayfork Valley

Wilson Point

Area

Happy Camp

Town Area

Figure 6. Land use, California Department of Water Resources (CDWR) groundwater basins, and locations of sampled sites within the 

Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.
18 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Table 4. Results of Wilcoxon rank-sum tests for differences in values of land-use factors, hydrologic conditions, geochemical 

conditions, and selected water-quality constituents between samples classified into groups by 2-factor age class, redox class, or 

aquifer lithology class, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

[The relation of median values in sample groups tested is shown if they were determined to be significantly different (two-sided test) on the basis of p-values 

(not shown) less than threshold value of (a) of 0.05; ns, test indicated no significant differences between the sample groups. Aquifer lithology class: G, granitic 

rocks; M, metamorphic rocks; MS, metasedimentary rocks; UM, ultra-mafic rocks. Other abbreviations: >, greater than; LUFT, leaking (or formerly leaking) 

underground fuel tank]

Significant differences

Age class

(Modern, Mixed/Pre-modern)

Redox class

(Oxic, Anoxic/Mixed)

Aquifer lithology class

(G, M, MS, UM)

Land-use factors

Percent agricultural land use ns ns ns

Percent natural land use ns ns ns

Percent urban land use ns ns ns

LUFT density ns ns ns

Septic tank density ns ns ns

Hydrologic conditions

Aridity index ns ns ns

Elevation of land-surface datum ns ns ns

Depth to top of screened or open interval ns ns ns

Well depth ns ns MS > M and G > M

Geochemical conditions

pH Mixed/Pre-modern > Modern ns ns

Dissolved oxygen (DO) Modern > Mixed/Pre-modern Oxic > Anoxic/Mixed ns

Selected water-quality constituents

Boron Mixed/Pre-modern > Modern ns ns

Iron Mixed/Pre-modern > Modern Anoxic/Mixed > Oxic ns

Manganese Mixed/Pre-modern > Modern Anoxic/Mixed > Oxic ns

Specific conductance Mixed/Pre-modern > Modern ns ns

Chloroform ns ns ns

Explanation: How to read results for significant differences. “Mixed/Pre-modern > Modern” for pH means the following: The pH values in mixed/pre-modern 

age class sites are significantly greater than pH values in modern age class sites. 

Similar to the study unit percentages, land use within the 

500-m buffers surrounding the sampled sites was primarily 

natural. The biggest difference was in the percentage of urban 

land use. Urban land use in the areas within 500 m of the grid 

sites was 4 percent, as compared to only 2 percent throughout 

the entire study unit. Around individual grid sites, urban land 

use ranged from less than 1 to 28 percent urban, with only 5 of 

39 wells surrounded by greater than 10 percent urban land use 

(fig. 6; table A1).

Septic tanks and LUFTs are also markers of land-use 

patterns. The density of LUFTs calculated using Thiessen 

polygons and the density of septic tanks in the 500-m radius 

area around a site may be indicators of potential sources 

of anthropogenic contaminants from the land surface. The 

density of LUFTs around grid sites ranged from 0 to 0.11 tanks 

per square kilometer (tanks/km2), and the median density was 

0.01 tanks/km2 (table A1). A description of how Thiessen 

polygons were used to calculate LUFT density is in included 

in appendix A. The density of septic tanks around grid sites 

ranged from 0.09 to 10.85 tanks/km2, and the median density 

was 0.54 tanks/km2 (table A1).

Results of Wilcoxon rank-sum tests indicate that none of 

the land-use factors were significantly correlated to any of the 

geologic rock types (table 4). Agricultural land use within the 

KLAM study unit was found to be primarily concentrated in 

areas of alluvial sediment rock type which generally coincide 

with CDWR groundwater basins in the KLAM study unit 

(fig. 6). The statistical analysis may not have identified a 

correlation with agricultural land use and geology because no 

wells were sampled in the CDWR-defined groundwater basins.
Hydrogeologic Setting and Potential Explanatory Factors 19

Hydrologic Conditions

Hydrologic conditions are represented by elevation and 

aridity index at the site (table A1). Land-surface elevations 

in the study area range from about 400 feet (ft) (122 m) 

near the town of Gasquet, to over 9,000 ft (2,743 m) on 

Mount Eddy, located just west of the city of Mount Shasta 

(fig. 2). The topography is characterized by high peaks and 

continuous ridgelines separated by deep river gorges. These 

gorges separate the study unit into several distinct mountain 

ranges, including the Trinity Alps and the Siskiyou, Scott, 

Marble, and Salmon Mountains. Most of the aquifer systems 

in the KLAM study unit consist of fractured hard rock and 

may not be interconnected, and recharge is not limited to the 

highest elevations. Because of the topographic and geologic 

complexity of the Klamath Mountains, many local flow cells 

of different scales are likely superimposed on an overall 

generalized regional groundwater flow pattern (Toth, 1963). 

In large groundwater basins, regional-scale groundwater flow 

patterns can develop; however, in steep mountainous terranes, 

groundwater flow patterns are controlled at much more 

localized scales that are dependent on local topography and 

the arrangement of discharge zones (Toth, 1963).

The primary aquifer system in the KLAM study unit 

is made up of localized areas of fractured bedrock that are 

confined to semi-confined. In addition to the production wells 

that are bored into the bedrock, there are numerous springs 

and horizontal wells. The CDWR-defined groundwater basins 

(Happy Camp Town Area, Hayfork Valley, Hoopa Valley, 

Hyampom Valley, Seiad Valley, Scott River Valley, and 

Wilson Point Area) consist of alluvial fan, stream channel, and 

floodplain deposits of Quaternary age (California Department 

of Water Resources, 2004a–c; fig. 2). No KLAM study unit 

sample sites were located within these groundwater basins, 

and the effect that these alluvial deposits have on the hard rock 

aquifer system is unknown. Groundwater recharge in the study 

unit occurs from the ambient recharge of runoff and snowmelt 

that penetrates the bedrock through faults and fractures at 

higher elevations (California Department of Water Resources, 

1984).

The climate in the study unit is typical of mountainous 

areas in northern California, with warm, dry summers and 

cold, wet winters (U.S. Department of Commerce, National 

Climatic Data Center, 2012). Average annual precipitation in 

the study unit ranges from about 69 inches (in.) on the western 

edge of the study unit along the Northern Coast Ranges to 

about 40 in. in the central and eastern parts of the study unit 

(Western Regional Climate Center, 2012; U.S. Department of 

Commerce, National Climatic Data Center, 2012). The general 

decrease in precipitation from west to east reflects the rainshadow effect of the mountain ranges within the study unit. 

The proportion of the annual precipitation that falls as snow 

ranges from 2 to 80 percent, with the greatest proportions of 

snow generally occurring at higher elevations in the central 

to northern parts of the study unit (U.S. Department of 

Commerce, National Climatic Data Center, 2012; Western 

Regional Climate Center, 2012).

The aridity index was used as an indicator of climate. 

Aridity index is defined as average annual precipitation 

divided by average annual evapotranspiration and is equal 

to the United Nations Educational, Scientific, and Cultural 

Organization aridity index (United Nations Educational, 

Scientific, and Cultural Organization, 1979; United Nations 

Environment Programme, 1997). The aridity index was 

inversely correlated to elevation in the KLAM study unit 

(table 5), meaning that drier conditions were observed at 

higher elevations. The inverse correlation is a result of the 

fact that the mountains in the central and eastern portions 

of the study unit are at higher elevations than those in the 

west. The central and eastern portions of the study unit are 

generally drier because of the rain-shadow effect caused by 

the westernmost mountain ranges.

Aridity index values at USGS–GAMA sampling sites 

ranged from 0.43 to 2.43 (table A1). Ninety percent of 39 sites 

sampled in the study unit had an aridity index in the humid or 

wet category (aridity index > 0.65) as defined by the United 

Nations Environment Programme (1997), with only four sites 

being dry subhumid or semi-arid.
Table 5. Results of Spearman’s rho (ρ) tests for correlations between selected potential explanatory factors and selected water-quality constituents

unit, 2010, California GAMA Priority Basin Project. [ρ values are shown for tests in which the variables were determined to be significantly correlated on the basis of ρ values (not shown) being less than the critical level (α) of 0.0

leaking) underground fuel tanks; ns, Spearman’s test indicates no significant correlation between factors; blue text, significant positive correlation; red text, significant negative c

ρ Elevation Depth to top of screened or open interval Well depth Percent agricultural land use Percent natural land use Percent urban land use Density of LUFTs Density of septic tanks pH Dissolved oxygen Boron Iron Mangan

Aridity index –0.54 ns ns ns ns ns ns ns ns ns ns ns ns 

Elevation of land- surface datum ns ns ns ns ns ns ns ns ns ns ns ns 

Depth to top of screened or open interval 0.80 ns ns ns ns ns ns ns ns ns ns 

Well depth ns ns ns ns ns ns ns ns ns ns 

Percent agricultural land use –0.42 ns ns ns ns ns 0.32 ns ns 

Percent natural land use –0.98 ns ns ns ns ns –0.34 ns 

Percent urban land use ns ns ns ns ns 0.38 ns 

Density of LUFTs 0.36 ns ns ns ns ns 

Density of septic tanks ns ns ns ns ns 

pH ns ns ns ns Dissolved oxygen –0.38 –0.42 –0.56 

Boron ns 0.33 Iron 0.78 Manganese Specific 

conductance
Hydrogeologic Setting and Potential Explanatory Factors 21

Depth and Groundwater Age Characteristics of 

the Primary Aquifer System

The primary aquifer system in the KLAM study unit is 

defined as the depth interval over which wells in the CDPH 

water-quality database are screened or open. Sites sampled by 

USGS–GAMA are considered representative of the primary 

aquifer system, thus, depth characteristics of these sites can be 

used to define the primary aquifer system.

Seven of the 39 sites sampled by USGS–GAMA are 

springs. In this report, springs are not assigned values for the 

depths to the top and bottom of screened or open intervals, 

and are therefore not included in tests involving depth as 

a continuous variable. Springs emerge at land surface, but 

the geometry of the fracture network in the subsurface is 

unknown.

Well depth information was available for 22 of the 

32 wells sampled. Depths of USGS-grid sites ranged from 25 

to 400 ft (8 to 122 m) below land surface; the median depth 

was 122 ft (37 m) (fig. 7; table A2). Depths of tops of screened 

or open intervals were available for 16 of those 22 wells with 

construction information. Depths to the tops of the screened 

or open intervals ranged from 24 to 300 ft (7 to 91 m), with a 

median of 74 ft (22 m). The screened or open interval length 

ranged from 8 to 223 ft (68 m), with a median of 46 ft (14 m) 

(Mathany and Belitz, 2014).

Groundwater “age” refers to the length of time that the 

water has resided in the aquifer system, which is the amount 

of time elapsed since the water was last in contact with the 

atmosphere. Groundwater samples were assigned age classes 

on the basis of the tritium and carbon-14 (14C) contents of 

the samples (see section “Groundwater Age” in appendix A). 

Groundwater with tritium activity greater than 1 tritium 

unit (TU) was defined as “modern,” and groundwater with 

tritium activity less than or equal to 1 TU was defined as 

“pre-modern.” Modern groundwater contains a substantial 

component of water recharged since 1952. The presence of 

pre-modern groundwater also was identified using the 14C 

data: samples with percent modern carbon (pmc) less than 

90 percent were considered to contain a substantial component 

of pre-modern groundwater. Samples with tritium activity 

greater than 1 TU and pmc less than 90 percent were classified 

as “mixed.” Samples from 26 sites were classified as modern, 

samples from 11 sites were classified as mixed, and samples 

from 2 sites were classified as pre-modern (table A4). Sites 

classified as pre-modern or mixed were mostly located in 

the eastern part of the study unit (fig. 8). Groundwater age 

was treated as a 2-factor classification for tests of statistical 

relations between potential explanatory factors and water 

quality. Because so few sites had pre-modern water, two of the 

three groundwater age classes (mixed and pre-modern) were 

merged for the statistical tests, resulting in two categories: 

modern and mixed/pre-modern.

Groundwater age was compared to the top of the 

screened or open interval to determine whether a classification 

system based on site depth could be established and used as an 

additional potential explanatory factor. However, the relative 

difference between the median depths to top-of-perforations 

among the three age classes was not significant enough 

to establish unique depth classes based on age. Wilcoxon 

rank-sum tests comparing the median depths to the top of the 

screened or open intervals in each groundwater age class did 

not indicate significant differences.

Geochemical Conditions in the Primary 

Aquifer System

Oxidation-reduction (redox) conditions for the 39 sites 

sampled by USGS–GAMA were classified by using the redox 

classification framework of McMahon and Chapelle (2008) 

and Jurgens and others (2009) (table A3). Groundwater 

conditions were primarily oxic (31 of 39 sites). Samples 

from four sites had anoxic conditions, and the remaining 

four sites had mixed redox conditions. The pH ranged from 

5.9 to 9.4 (table A3). Contingency table tests indicated that 

anoxic or mixed redox conditions were statistically more 

often associated with groundwater classified as mixed or premodern in age and that wells with oxic redox conditions were 

significantly associated with groundwater classified as modern 

in age (attained significance level [p] = 0.005).

22 16

Well

depth

400

500

300

200

100

0

Depth below land surface, feet

Top of screened

or open interval

EXPLANATION

22 number of sites

90th percentile

75th percentile

median

25th percentile

10th percentile

Figure 7. Well depths and depths to tops of screened or open 

intervals for USGS-grid sites, Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.
22 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

124° 123°30' 123° 122°30' 122°

42°

41°30'

40°30'

41°

sac14-0524_fig 08

OREGON

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

EXPLANATION

Modern

Mixed

Pre-modern

Gridded area

Study unit boundary

0 10 20 MILES 5

0 10 20 KILOMETERS 5

Figure 8. Groundwater age classes of sampled sites within the Klamath Mountains study unit, 2010, California GAMA Priority Basin 

Project.
Status and Understanding of Groundwater Quality 23

Status and Understanding of 

Groundwater Quality

The status assessment was designed to identify the 

constituents or classes of constituents most likely to be 

water-quality concerns because of their high relativeconcentrations or their prevalence. The assessment applies 

only to constituents having regulatory or non-regulatory 

health-based or aesthetic-based benchmarks established by 

the USEPA or the CDPH (U.S. Environmental Protection 

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

Health, 2010, 2013). USGS sample analyses, plus additional 

data from the CDPH water-quality database, were included in 

the assessment of groundwater quality for the KLAM study 

unit. The spatially distributed, randomized approach to gridsite selection and data analysis yields a view of groundwater 

quality in which all areas of the primary aquifer system are 

weighted equally; regions with a high density of groundwater 

use or with high density of potential contaminants were not 

preferentially sampled (Belitz and others, 2010).

The understanding assessment was designed to help 

answer the question of why selected constituents are, or 

are not, detected in the groundwater, and may improve 

understanding of how natural and anthropogenic factors affect 

groundwater quality. The assessment addresses a subset of 

the constituents selected for additional evaluation in the status 

assessment and is based on statistical correlations between 

water quality and a set of potential explanatory factors. The 

assessment was not designed to identify specific sources of 

specific constituents to specific wells.

The following discussion of the status and understanding 

assessment results is divided into two parts for inorganic and 

organic constituents. Each part begins with a survey of how 

many constituents in each constituent class were detected at 

any concentration compared to the number of constituents 

analyzed for in each constituent class and a graphical summary 

of the relative-concentrations of constituents detected in the 

grid sites. Results are presented for the subset of constituents 

that met criteria for selection for additional evaluation in 

the status assessment based on relative-concentration, or for 

organic constituents, prevalence. Of the 216 constituents 

analyzed and the 82 constituents detected, 16 met the criteria 

for additional evaluation in the status assessment (table 6). 

Of these 16 constituents, 4 met the criteria for further 

evaluation in the understanding assessment. The results of the 

understanding assessment for each of these four constituents 

are presented immediately following the status assessment 

results for each constituent.

The 216 constituents include 2 microbial indicators that 

were detected in samples from USGS grid sites (Mathany and 

Belitz, 2014). Microbial indicators were not evaluated in the 

status assessment because the drinking-water benchmarks 

for these constituents cannot be directly applied to the 

data collected for this study (see section “Water-Quality 

Benchmarks and Relative-Concentrations”).
24 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Table 6. Constituents selected for additional evaluation in the status assessment of groundwater quality in the Klamath Mountains 

study unit, California GAMA Priority Basin Project.

[Inorganic constituents selected if maximum concentration measured in USGS–GAMA samples or reported in CDPH database during the 3-year time period 

used for the status assessment was greater than 0.5 times the benchmark concentration. Organic constituents selected if maximum concentration was greater than 

0.1 times the benchmark concentration, or if detection frequency at any concentration was greater than 10 percent. Benchmark type: Regulatory, health-based 

benchmarks: MCL-US, USEPA maximum contaminant level; AL-US, USEPA action level; MCL-CA, CDPH maximum contaminant level. Non-regulatory 

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

SMCL-CA, CDPH secondary maximum contaminant level. Benchmark units: mg/L, milligrams per liter; μg/L, micrograms per liter; μS/cm, microsiemens 

per centimeter; pCi/L, picocuries per liter. Other abbreviations: USGS, U.S. Geological Survey; GAMA, Groundwater Ambient Monitoring and Assessment 

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

Constituent Source or typical use

Benchmarks

Type 1 Value Units

Inorganic constituents with health-based benchmarks

Trace elements

Antimony Naturally occurring MCL-US 6 μg/L

Arsenic Naturally occurring MCL-US 10 μg/L

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

Boron Naturally occurring NL-CA 1,000 μg/L

Copper Naturally occurring AL-US 1,300 μg/L

Nutrient

Nitrate 2 Natural, fertilizer, sewage MCL-US 10 mg/L

Radioactive constituents

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

Radon-222 Naturally occurring Proposed MCL-US 4,000 pCi/L

Inorganic constituents with aesthetic-based benchmarks

Chloride Naturally occurring SMCL-CA 500 mg/L

Iron Naturally occurring SMCL-CA 300 μg/L

Manganese Naturally occurring SMCL-CA 50 μg/L

Specific conductance, field Naturally occurring SMCL-CA 1,600 μS/cm

Total dissolved solids (TDS) Naturally occurring SMCL-CA 1,000 mg/L

Organic constituents with health-based benchmarks

Volatile organic compounds

Chloroform Disinfection byproduct MCL-US 3 80 μg/L

1,2-Dichloroethane Solvent, fumigant, plastics MCL-CA 0.5 μg/L

Methyl tert-butyl ether (MTBE) Gasoline oxygenate MCL-CA 13 μg/L

1

 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: California Department of Public Health (2013); MCL-US: U.S. 

Environmental Protection Agency (2012b); SMCL-CA: California Department of Public Health (2013); NL-CA: California Department of Public Health (2010); 

HAL-US: U.S. Environmental Protection Agency (2012b); Proposed MCL-US: U.S. Environmental Protection Agency (1999).

2

 Selected on the basis of concentrations reported in the CDPH database. Constituent also detected by USGS–GAMA at low relative-concentrations.

3

 MCL-US benchmark for trihalomethanes is for the sum of chloroform, bromodichloromethane, dibromochloromethane, and bromoform.
Status and Understanding of Groundwater Quality 25

Inorganic Constituents

Inorganic constituents generally occur naturally in 

groundwater, although their concentrations may be influenced 

by human as well as natural factors. All 47 inorganic 

constituents analyzed by the USGS–GAMA were detected 

in the KLAM study unit. Of these 47 constituents, 25 had 

regulatory or non-regulatory health-based benchmarks, 9 had 

non-regulatory aesthetic-based benchmarks, and 13 had no 

established benchmarks (table 2). Most of the constituents 

without benchmarks are major or minor ions that are present 

in nearly all groundwater.

Eight inorganic constituents were selected for additional 

evaluation in the status assessment because they were detected 

at moderate or high relative-concentrations in the grid 

sites: the trace elements barium and boron, the radioactive 

constituents gross alpha radioactivity and radon-222, and the 

constituents with aesthetic-based benchmarks, chloride, iron, 

manganese, and total dissolved solids (table 6; figs. 9, 10). 

Four other inorganic constituents—antimony, arsenic, copper, 

and nitrate—were selected for additional evaluation because 

they were reported at high or moderate concentrations in the 

CDPH water-quality database during the current sampling 

period, December 1, 2007, to December 31, 2010. Boron, iron, 

and manganese were selected for further evaluation in the 

understanding assessment because they were present at high 

relative-concentrations in greater than 2 percent of the primary 

aquifer system.

Volatile

organic

compounds

Pesticides Specialinterest

constituents

Nutrients Trace

elements

Inorganic

constituents

with

aesthetic-based

benchmarks

Radioactive

constituents

100

Maximum relative-concentration, dimensionless

Strontium

Barium

Molybdenum

Arsenic

Uranium

Vanadium

Lead

Nickel

Boron

Fluoride

Chromium

Selenium

Aluminum

Antimony

Cadmium

Beryllium

Thallium

Sulfate

Zinc

Manganese

Iron

Nitrate

Ammonia

Nitrite

Atrazine

Simazine

Radon-222

Uranium

Gross alpha radioactivity

Chloroform 

Bromodichloromethane

Dibromochloromethane

Styrene

Methyl tert-butyl ether

Tetrachloroethene

Trichloroethene

Trichlorofluoromethane

Chloride

High

Moderate

Low

Relative-concentration

Two volatile organic compounds (carbon disulfide and toluene), one pesticide (hexazinone), and one inorganic constituent (silver) 

with an aesthetic-based benchmark were detected at relative-concentrations less than 0.001 and are not shown on 

the figure. 

Upper water-quality benchmark used when calculating relative-concentrations for constituents with an upper and a recommended 

secondary maximum contaminant level.

Nitrate Name and center of symbol is location of data– 

unless indicated by following location line:

EXPLANATION

Gross beta radioactivity

High

Moderate

Moderate

Low

Total dissolved solids 

Copper

0.001

0.01

0.1

1

10

Figure 9. Maximum relative-concentrations in USGS-grid sites for constituents detected, by type of constituent, Klamath Mountains 

study unit, 2010, California GAMA Priority Basin Project.
26 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

sac14-0524_fig 10

0.001

0.01

0.1

1

10

100

Relative-concentration, dimensionless

0.001

0.01

0.1

1

10

100

Relative-concentration, dimensionless

0.001

0.01

0.1

1

10

100

Relative-concentration, dimensionless

Boron

EXPLANATION

USGS-grid site

High

Moderate

Low

Relative-concentration

High

Moderate

Low

Gross alpha radioactivity Radon-222

Chloride Total dissolved solids Iron Manganese

Radioactive constituents

Constituents with non-regulatory aesthetic-based benchmarks

Trace Elements

C

B

A

High

Moderate

Low

High

Moderate

Low

Figure 10. Relative-concentrations of selected trace elements, radioactive constituents, and constituents with non-regulatory 

aesthetic-based benchmarks in USGS-grid sites, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.
Status and Understanding of Groundwater Quality 27

Inorganic constituents having human-health benchmarks, 

as a group (trace elements and radioactive constituents), were 

detected at high relative-concentrations in 2.6 percent of the 

primary aquifer system, at moderate relative-concentrations 

in 10 percent, and at low relative-concentrations in 87 percent 

(table 7A). Inorganic constituents having aesthetic-based 

benchmarks, as a group, were detected at high relativeconcentrations in 13 percent of the primary aquifer system, 

at moderate relative-concentrations in 10 percent, and at low 

relative-concentrations in 77 percent.

Table 7A. Summary of aquifer-scale proportions for inorganic constituent classes with health-based and aesthetic-based 

benchmarks, Klamath Mountains study unit, 2010, California GAMA Priority Basin Program.

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

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

constituents in group are less than or equal to 0.5 of benchmark. Abbreviations: TDS, total dissolved solids]

Number 

of 

grid cells

Aquifer-scale proportion 

(percent) 1

Low Moderate High

Inorganic constituents with health-based benchmarks

Trace elements 2 39 92 5.2 2.6

Radioactive constituents 3 38 95 5.3 0

Any inorganic constituent with health-based benchmarks 39 87 10 2.6

Inorganic constituents with aesthetic-based benchmarks

Trace elements 39 77 10 13

Major ions and TDS 38 97 2.6 0

Any inorganic constituent with aesthetic-based benchmarks 39 77 10 13

1

 Aquifer-scale proportions by class calculated using the grid-based approach unless otherwise noted.

2

 Boron was only analyzed for 38 grid cells.

3

 Radon-222 was only analyzed for 37 grid cells.

Table 7B. Summary of aquifer-scale proportions for organic constituent classes with health-based benchmarks, Klamath Mountains 

study unit, 2010, California GAMA Priority Basin Program.

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

least one constituent in group greater than 0.1 of benchmark and no constituents in group with concentration greater than benchmark; low, concentrations of all 

constituents in group are less than or equal to 0.1 of benchmark]

Number 

of 

grid cells

Aquifer-scale proportion 

(percent) 1

Not detected Low Moderate High

Organic constituents with health-based benchmarks

Volatile organic compounds 38 53 45 1

 1.9 0

Pesticides and pesticide degradates 38 87 13 0 0

Any organic constituent 38 50 48 1

 1.9 0

1

 Spatially weighted aquifer-scale proportion.
28 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Trace Elements

Trace elements with health-based benchmarks, as a class, 

were detected at high relative-concentrations (for one or more 

constituents) in 2.6 percent of the primary aquifer system, at 

moderate relative-concentrations in 5.2 percent, and at low 

relative-concentrations in 92 percent (table 7A). Boron was 

the only trace element present at high relative-concentrations 

in the grid-site network (fig. 9).

Boron was detected at high relative-concentrations in 

2.6 percent of the primary aquifer system and at moderate 

relative-concentrations in 2.6 percent (table 8). Boron is a 

naturally occurring metalloid element that is highly soluble 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). Boron 

concentrations in seawater can be as high as 4,500 micrograms 

per liter (μg/L), and boron is also associated with thermal 

springs and volcanic activity (Hem, 1985). Because borax 

is a component of many detergents, boron can be associated 

with wastewater. Borosilicate glass, boric acid insecticides, 

chemical reagents, and fertilizers are other anthropogenic uses 

of boron. 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. 

Boron also has a HAL-US of 6,000 μg/L. High concentrations 

of boron may adversely affect fetal development (U.S. 

Environmental Protection Agency, 2008b).

Antimony and arsenic had high aquifer-scale proportions 

(spatially weighted) of 1.3 percent. Antimony is a naturally 

occurring semi-metallic trace element. Chemically, it behaves 

similarly to arsenic, but it is about one-tenth as prevalent 

in rocks as arsenic is (Hem, 1985). The most common 

natural source of antimony is the mineral stibnite. Common 

anthropogenic sources of antimony include brake linings, tires, 

and vehicle exhaust. Antimony is often added as an alloy to 

lead and tin to make those metals stronger and harder. The 

MCL-US for antimony is 6 μg/L. Arsenic is a semi-metallic 

trace element. Natural sources of arsenic in groundwater 

include dissolution of arsenic-bearing minerals and desorption 

of arsenic from mineral surfaces. Pyrite, the most common 

sulfide mineral in aquifer materials, is sometimes partially 

composed of arsenic. Potential anthropogenic sources of 

arsenic include copper ore smelting, coal combustion, and 

wood preservatives. The MCL-US for arsenic was lowered 

from 50 μg/L to 10 μg/L in 2002; 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, 2012a).

Barium and copper were not reported at high relativeconcentrations and were detected at moderate spatially 

weighted aquifer-scale proportions of 2.6 and 1.5 percent, 

respectively. Barium is a naturally occurring alkalineearth metal that occurs most commonly in the mineral 

barite. Concentrations of barium in natural waters appear 

to be controlled by the solubility of the mineral barite and 

adsorption of barium to metal oxides or hydroxides (Hem, 

1985). Anthropogenic sources of barium are numerous, with 

compounds containing barium being used in well drilling 

fluids, paints, rubber, and pyrotechnics. The MCL-CA for 

barium is 1,000 μg/L. Copper is a naturally occurring metallic 

element with a wide range of uses, from electronics and 

plumbing to agricultural pesticides. Organic and inorganic 

forms of copper are more abundant in the environment than its 

average abundance in rocks might suggest (Hem, 1985). The 

AL-US for copper is 1,300 μg/L.

Factors Affecting Boron

Boron concentrations were significantly greater in 

groundwater classified as mixed or pre-modern age than 

in groundwater classified as modern age (table 4). Boron 

concentrations were significantly negatively correlated with 

dissolved oxygen (DO) concentration (table 5). The negative 

correlation with DO likely reflects that DO concentrations 

were significantly lower in groundwater with mixed or premodern ages than in groundwater with modern ages (table 4). 

Boron was also significantly positively correlated with specific 

conductance (table 5), and the only site with a high relativeconcentration of boron also had a high relative-concentration 

of specific conductance (KLAM-06).

Nutrients

Nutrients, as a class, were not detected at high relativeconcentrations, but were detected at moderate relativeconcentrations in 0.7 percent (spatially weighted) of the 

primary aquifer system. Nitrate was the nutrient present 

at moderate relative-concentrations (table 8). Nitrate 

has anthropogenic and natural sources to groundwater; 

however, concentrations greater than 2 milligrams per liter 

(mg/L) as nitrogen (relative-concentration of 0.2) generally 

are considered to indicate the presence of nitrate from 

anthropogenic sources (Mueller and Helsel, 1996).

Radioactive Constituents

Radioactive constituents, as a class, were not detected at 

high relative-concentrations, but were detected at moderate 

relative-concentrations in 5.3 percent of the primary aquifer 

system (table 7A). The moderate aquifer-scale proportions 

for gross alpha radioactivity and radon-222 were 2.6 and 

2.7 percent, respectively (table 8).
Table 8. Aquifer-scale proportions from grid-based and spatially weighted methods for constituents that met criteria for additional evaluation in the Mountains study unit, 2010, California GAMA Priority Basin Project.[Grid-based aquifer-scale proportions for organic constituents are based on samples collected by the U.S. Geological Survey from 38 grid sites during October to December 201aquifer proportions are based on CDPH data from the period December 1, 2007, to December 31, 2010, in combination with grid site and understanding site data. Relative-conc

high, concentrations greater than benchmark; moderate, concentrations less than benchmark and greater than or equal to 0.1 (for organic constituents) or 0.5 (for inorganic const

concentrations less than 0.1 (for organic constituents) or 0.5 (for inorganic constituents) of benchmark; SMCL, secondary maximum contaminant level]

Constituent

Raw detection 

frequency 1

Spatially weighted 

aquifer-scale proportion 1

Grid-based 

aquifer-scale proportion 2

Number 

of sites

Percent Number 

of cells

Proportion, in percent Number 

of cells

Proportion, in percent 

Moderate High Moderate High Moderate High 

Trace elements

Antimony 57 0 1.8 39 0 1.3 39 0 0 

Arsenic 56 0 1.8 39 0 1.3 39 0 0 

Barium 56 1.8 0 39 2.6 0 39 2.6 0 

Boron 40 2.5 5.0 39 2.6 3.8 38 2.6 2.6 

Copper 55 3.7 0 39 1.5 0 39 0 0 

Nutrients

Nitrate 151 1.3 0 40 0.7 0 40 0 0 

Radioactive constituents

Gross alpha radioactivity 52 1.9 0 38 1.3 0 38 2.6 0 

Radon-222 38 2.6 0 38 2.6 0 37 2.7 0 

Inorganic constituents with aesthetic-based benchmarks

Chloride 51 1.9 0 38 2.6 0 38 2.6 0 

Iron 64 6.2 18 38 6.6 15 38 7.9 7.9 

Manganese 56 13 13 38 13 12 38 11 11 

Total dissolved solids (TDS) 54 3.7 1.9 38 2.6 0.9 38 2.6 0 

Volatile organic compounds

Chloroform 50 0 0 39 0 0 38 0 0 

1,2-Dichloroethane 49 0 0 39 0 0 38 0 0 

Methyl tert-butyl ether (MTBE) 50 4.0 0 39 1.9 0 38 0 0 

1 Based on most recent analyses for each California Department of Public Health (CDPH) site during December 1, 2007–December 31, 2010, combined with data from U.S. G

sites and USGS-understanding sites.

2 Grid-based aquifer-scale proportions for organic constituents are based on samples collected by the USGS from 38 grid sites between October and December 2010.3 Based on Jeffreys interval for the binomial distribution (Brown and others, 2001).
30 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Constituents with SMCL Benchmarks

The major ion chloride and total dissolved solids 

(TDS) have recommended and upper SMCL-CA values. 

In this report, data were compared to the upper SMCL-CA 

values. TDS had high relative-concentrations in 0.9 percent 

(spatially weighted) of the primary aquifer system (table 8). 

Chloride was detected at moderate relative-concentrations in 

2.6 percent of the primary aquifer system. Natural sources 

of TDS 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 TDS to groundwater include 

recharge of water used for irrigation, wastewater discharge, 

and evaporation (Hem, 1985).

Iron and manganese were present at high relativeconcentrations in 7.9 and 11 percent of the primary aquifer 

system, respectively, and at moderate relative-concentrations 

in 7.9 and 11 percent, respectively (table 8). Natural sources 

of iron and manganese to groundwater include weathering and 

dissolution of minerals in soils, sediments, and rocks. Iron 

and manganese oxyhydroxide minerals commonly occur as 

coatings on mineral and sediment grains. In addition, ironbearing silicate, sulfide, and (or) oxide minerals occur in most 

rocks and sediments, and manganese commonly substitutes 

for iron in silicate minerals. The solubilities of manganese and 

iron are strongly dependent on oxidation-reduction conditions; 

the more reduced species are much more soluble (McMahon 

and Chapelle, 2008).

Factors Affecting Iron and Manganese

Iron and manganese concentrations had significant 

negative correlations with DO concentrations and a significant 

positive correlation with each other (table 5; fig. 11). Eight of 

the nine sites with high or moderate relative-concentrations 

of iron or manganese were sites that had anoxic or mixed 

(oxic and anoxic) redox conditions. The predominant redox 

condition in the KLAM study unit was oxic.

The dominant form of iron in solution can be identified 

from the ratio of iron redox species, 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). Of 

the 39 samples with detections of iron, the 6 samples with 

moderate or high relative-concentrations all had Fe+3/Fe+2

≤ 0.09. Greater relative abundances of Fe+2 are indicative of 

reduced conditions (McMahon and Chapelle, 2008) (table A3). 

Three of the six samples with moderate or high relativeconcentrations of iron had DO concentrations greater than 

1 mg/L, indicating that these samples represented mixtures of 

oxic and iron-reducing anoxic groundwaters (table A3).

The amount of time groundwater spends in contact 

with aquifer materials may be related to concentrations of 

certain constituents. Iron and manganese concentrations 

were significantly greater in groundwater classified as mixed 

or pre-modern than in groundwater classified as modern 

(table 4; fig. 12). Contingency table testing showed that 

anoxic or mixed oxidation-reduction conditions and mixed 

or pre-modern age groundwater are significantly positively 

associated.

Reducing conditions in alluvial aquifers (which were 

not sampled in the KLAM study unit) typically are produced 

by consumption of DO by oxidation of sedimentary organic 

matter (Appelo and Postma, 2005). Reducing conditions 

in aquifers not containing organic matter, such as the hard 

rock aquifers of the KLAM study unit, can be produced by 

reactions with minerals containing ferrous (Fe+2) iron, given 

sufficiently long residence times (Gascoyne, 1997; Sidborn 

and Neretnieks, 2007; Fram and Belitz, 2012). In the KLAM 

study unit, anoxic or mixed conditions were found in sites 

with metasedimentary, metamorphic, and mafic/ultramafic 

geologic classifications. Minerals containing ferrous iron, 

such as biotite, chlorite, magnetite, pyrite, and hornblende, are 

commonly present in these rock types.

Aquifer materials can affect iron and manganese 

concentrations because the relative abundance of iron 

or manganese can vary between rock types. The sites 

with moderate or high relative-concentrations of iron 

or manganese were grouped by aquifer lithology class. 

The highest percentages of sites with high or moderate 

relative-concentrations of iron or manganese were located 

in metasedimentary (33 percent) and ultramafic/mafic 

(29 percent) aquifer lithologies. Of the 10 sites in the 

metamorphic category, only 1 site (KLAM-30) had high or 

moderate relative-concentrations of iron or manganese.
Status and Understanding of Groundwater Quality 31

sac14-0524_fig 11

0 2 4 6 8 10

Dissolved oxygen, milligrams per liter

0

100

200

300

400

500

2,500

3,000

Iron, micrograms per liter Manganese, micrograms per liter

Spearman’s correlation test

p-value = 0.01

rho = –0.42

0 2 4 6 8 10 12

Dissolved oxygen, milligrams per liter

Spearman’s correlation test

p-value = <0.01

rho = –0.56

12

Moderate

Low

High

Moderate

Low

High

B

A

0

25

50

75

100

125

150

Figure 11. Relations between dissolved oxygen concentration and (A) iron and (B) manganese, Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.
32 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Organic Constituents

The organic constituents assessed in this study 

primarily are VOCs and pesticides. VOCs may be present 

in paints, solvents, fuels, refrigerants, and fumigants or may 

be formed as byproducts of water disinfection. VOCs are 

characterized by a volatile nature, or tendency to evaporate, 

and they generally persist longer in groundwater than in 

surface water because groundwater is more isolated from 

the atmosphere. Pesticides are used to control weeds, fungi, 

or insects in agricultural and urban settings. One or more 

organic constituents were detected in 21 of the 38 grid sites 

(55 percent) sampled in the study unit. Of the 148 organic 

constituents analyzed, 14 were detected in the KLAM study 

unit (table 2). Of these 14 constituents, 11 have regulatory 

health-based benchmarks. Organic constituents as a group 

were not present at high relative-concentrations in the primary 

aquifer system (table 7B). Organic constituents were present 

at moderate relative-concentrations in 1.9 percent (spatially 

weighted) and were present at low relative-concentrations 

or not detected in 98 percent of the primary aquifer system. 

The moderate relative-concentration of 1.9 percent was 

due solely to detections of methyl tert-butyl ether (MTBE). 

Three organic constituents (chloroform, 1,2-dichloroethane, 

and MTBE) were selected for additional evaluation in the 

status assessment on the basis of relative-concentration or 

prevalence. Chloroform was selected for further evaluation in 

the understanding assessment on the basis of prevalence.

The trihalomethane chloroform was detected in more 

than 10 percent of the grid sites. Chloroform was the most 

commonly detected VOC in the KLAM study unit, with a 

detection frequency of 32 percent (figs. 13, 14). Chloroform 

is among the most commonly detected VOCs in groundwater 

nationally (Zogorski and others, 2006).Water used for drinking 

water and other household uses in domestic and public 

(municipal and community) systems commonly is disinfected 

with solutions that contain chlorine. In addition to disinfecting 

the water, the chlorine can react with organic matter to 

produce trihalomethanes (THMs) and other chlorinated or 

brominated disinfection byproducts. As a class, THMs were 

not present at high or moderate relative-concentrations in the 

primary aquifer system (table 8).

The solvent/fumigant 1,2-dichloroethane was reported 

at high relative-concentrations in the CDPH waterquality database during the period December 1, 2007, to 

December 31, 2010. 1,2-Dichloroethane was reported at high 

relative-concentrations twice in one CDPH site; however, 

the most recent result for that site was a non-detection, thus 

the high aquifer-scale proportion for 1,2-dichloroethane is 

0 percent (table 8).

The gasoline oxygenate MTBE also was reported at high 

relative-concentrations in the CDPH water-quality database. 

MTBE was reported at high relative-concentrations in one 

CDPH site; however, the most recent result was a moderate 

relative-concentration of MTBE. The high aquifer-scale 

proportion for MTBE is 0 percent, but MTBE was present at 

moderate relative-concentrations in 1.9 percent of the primary 

aquifer system (spatially weighted) (table 8). MTBE was 

detected in less than 10 percent of the grid sites (fig. 13).

sac14-0524_fig 12

Modern age 

category

Pre-modern or mixed 

age category

0.1

1

10

100

1,000

10,000

Concentration, micrograms per liter

Iron Manganese Iron Manganese

26 26 13 13

13

EXPLANATION

Number of

values

Value outside of

1.5 times the interquartile range

highest value

within 1.5 times the

interquartile range

75th percentile

median

25th percentile

lowest value

within 1.5 times the

interquartile range

Figure 12. Iron and manganese concentrations by groundwater age class, Klamath Mountains study unit, 2010, California GAMA 

Priority Basin Project.
Status and Understanding of Groundwater Quality 33

Atrazine

Simazine

Bromodichloromethane

Hexazinone

Carbon disulfide

Dibromochloromethane

Styrene

Methyl tert-butyl ether*

Tetrachloroethene

Trichloroethene

Trichlorofluoromethane

Moderate

Low

High

EXPLANATION

High

Moderate

Low

Relative-concentration

* MTBE had a high relative-concentration in the CDPH database 

 for the period December 1, 2007, to December 31, 2010, but 

 was not detected at high relative-concentrations during the 

 GAMA Priority Basin Project.

Chloroform Name and center of symbol is location of data

1 10 100

Detection frequency at any concentration, in percent

0.0001

0.001

0.01

0.1

1

10

Maximum relative-concentration, dimensionless

Chloroform

Figure 13. Detection frequency and maximum relative-concentration for organic constituents detected in USGS-grid sites, Klamath 

Mountains study unit, 2010, California GAMA Priority Basin Project.
34 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Potential Factors Affecting Chloroform

Chloroform concentrations were significantly positively 

correlated with septic tank location density and not with any 

other potential explanatory factors (table 5). Chloroform 

and other THMs are known byproducts of drinking-water 

disinfection and have commonly been detected in septic tank 

effluent (Moran and others, 2002). Septic tank densities are 

generally higher in less urbanized areas. In the KLAM study 

unit, the percentage of urban land use was less than 5 percent. 

The average septic tank density in the KLAM study unit was 

about 1 tank/km2 (0.38 per mi2).

sac14-0524_fig 14 Relative-concentration, dimensionless

Chloroform

EXPLANATION

USGS-grid site

High

Moderate

Low

Relative-concentration

High

Moderate

Low

0

20

40

60

80

100

Detection frequency, percent

0.0001

0.001

0.01

0.1

1

A 10

B

Figure 14. (A) Maximum relative-concentration and (B) detection 

frequency for the trihalomethane chloroform detected in USGSgrid sites, Klamath Mountains study unit, 2010, California GAMA 

Priority Basin Project.

Summary

Groundwater quality in the approximately 8,806-squaremile (22,809-square-kilometer) Klamath Mountains (KLAM) 

study unit was investigated as part of the Priority Basin Project 

of the Groundwater Ambient Monitoring and Assessment 

(GAMA) Program. The GAMA KLAM study provides a 

spatially unbiased characterization of untreated groundwater 

quality in the primary aquifer system. The assessment is 

based on water-quality data collected by the U.S. Geological 

Survey (USGS) from 39 sites in 2010 and water-quality 

data compiled in the California Department of Public Health 

(CDPH) database (for the period from December 1, 2007, to 

December 31, 2010).

The status of the current quality of the groundwater 

resource was assessed by using data from samples analyzed 

for volatile organic compounds (VOCs), pesticides, and 

naturally occurring inorganic constituents, such as trace 

elements and major and minor ions. The status assessment

characterized the quality of groundwater resources in the 

primary aquifer system of the KLAM study unit, not the 

treated drinking water delivered to consumers by water 

purveyors.

Relative-concentrations (sample concentration divided by 

the health- or aesthetic-based benchmark concentration) were 

used for evaluating groundwater quality for those constituents 

that have Federal and (or) California regulatory or nonregulatory benchmarks for drinking-water quality.

Aquifer-scale proportion was used as the primary 

metric in the status assessment for evaluating regionalscale groundwater quality. High aquifer-scale proportion 

is defined as the percentage of the primary aquifer system 

with a relative-concentration greater than 1.0 for a particular 

constituent or class of constituents; proportion is based 

on an areal rather than a volumetric basis. Moderate 

and low aquifer-scale proportions were defined as the 

percentages of the primary aquifer system with moderate 
References 35

and low relative-concentrations, respectively. Two statistical 

approaches, grid-based and spatially weighted, were used to 

evaluate aquifer-scale proportions for individual constituents 

and classes of constituents. Grid-based and spatially weighted 

estimates were comparable in the KLAM study unit (within 

90 percent confidence intervals for all constituents). However, 

the spatially weighted approach was better able to identify 

constituents with high or moderate relative concentrations in 

small fractions of the aquifer.

Inorganic constituents with regulatory health-based 

benchmarks were present at high relative-concentrations in 

2.6 percent of the primary aquifer system and at moderate 

relative-concentrations in 10 percent. The inorganic 

constituents with high aquifer-scale proportions included 

antimony, arsenic, and boron. The inorganic constituents with 

non-regulatory aesthetic-based benchmarks were present 

at high relative-concentrations in 13 percent of the primary 

aquifer system and at moderate relative-concentrations in 

10 percent. The high aquifer-scale proportion primarily 

reflected high aquifer-scale proportions of iron and 

manganese.

Relative-concentrations of organic constituents were 

not high, but were moderate in 1.9 percent of the primary 

aquifer system when using the spatially weighted approach. 

The gasoline oxygenate methyl tert-butyl ether was the only 

constituent detected at moderate relative-concentrations. 

Of the 148 organic constituents analyzed, 14 constituents 

were detected. Only one organic constituent had a detection 

frequency of greater than 10 percent—the trihalomethane 

chloroform.

Statistical correlations between concentrations of 

constituents and values of selected potential explanatory 

factors were used in the understanding assessment to 

identify the factors potentially affecting the concentrations 

and occurrences of constituents detected at high relativeconcentrations or with study-unit detections of organic 

constituents greater than 10 percent. The potential explanatory 

factors evaluated were aquifer lithology, land use, hydrologic 

conditions, depth, groundwater age, and geochemical 

conditions.

Groundwater age class (modern, mixed, or pre-modern), 

redox class (oxic, mixed, or anoxic), and dissolved oxygen 

concentration were the most significant explanatory factors 

with potential causative value for the inorganic constituents 

evaluated in the understanding assessment (boron, iron, 

manganese, and specific conductance). High concentrations 

of boron were associated with groundwater classified as 

mixed or pre-modern with respect to groundwater age. 

Boron was also negatively correlated to dissolved oxygen 

and positively correlated to specific conductance. Iron and 

manganese concentrations were strongly associated with 

low dissolved oxygen concentrations, anoxic and mixed 

redox classifications, and pre-modern groundwater. Specific 

conductance concentrations were related to pre-modern 

groundwater, low dissolved oxygen concentrations, and high 

pH. The relation of specific conductance to dissolved oxygen 

and pH likely reflects the lower DO concentrations and greater 

pH values found in older groundwater in the KLAM study 

unit. Septic tank density was the only potential explanatory 

factor with any potential causative value for the one organic 

constituent (chloroform) selected for the understanding 

assessment.

Acknowledgments

The authors thank the following cooperators for their 

support: the California State Water Resources Control 

Board, Lawrence Livermore National Laboratory, California 

Department of Public Health, and California Department 

of Water Resources. We especially thank the site owners 

and water purveyors for their cooperation in allowing the 

U.S. Geological Survey to collect samples from their sites. 

Funding for this work was provided by State of California 

bonds authorized by Proposition 50 and administered by the 

State Water Resources Control Board.

References

Alt, D., and Hyndman, D.W., 2000, Roadside geology of 

northern and central California: Mountain Press Publishing 

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Appelo, C.A.J., and Postma, D., 2005, Geochemistry, 

groundwater, and pollution (2d ed.): Leiden, Germany, 

A.A. Balkema Publishers, 649 p.

Belitz, K., Dubrovsky, N.M., Burow, K.R., Jurgens, B., 

and Johnson, T., 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.

Belitz, K., Jurgens, B., Landon, M.K., Fram, M.S., and 

Johnson, T., 2010, Estimation of aquifer-scale proportion 

using equal-area grids—Assessment of regionalscale groundwater quality: Water Resources Research, 

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Appendix A. Attribution of Potential Explanatory Factors 41

Appendix A. Attribution of Potential Explanatory Factors

Aquifer Lithology

Aquifer lithology was classified into four different 

categories on the basis of lithologic information from driller’s 

logs and on the California State geologic map (Jennings, 1977; 

Saucedo and others, 2000) (table A1). The State geologic map 

shows the lithologic unit exposed at the surface, which may or 

may not be the same as the lithologic unit at the depth range 

over which the well is screened or open. When available, 

the lithologic category estimated from the geologic map was 

compared to the lithology described in the driller’s log. If the 

lithology from the map disagreed with the lithology from the 

driller’s log, the category from the driller’s log was used. The 

six lithologic categories are 

• Granitic rocks (G): Primarily Mesozoic granitic rocks 

with some Paleozoic granitic rocks (California State 

geologic map units: gr, grMz, and grPz);

• Metamorphic rocks (other than metasedimentary) (M): 

Mesozoic, Paleozoic ,and pre-Cenozoic metavolcanic 

rocks (California State geologic map units: ls, m, mv, 

Mzv, Pzv, and sch);

• Metasedimentary rocks (MS): Metamorphosed 

Mesozoic and Paleozoic marine rocks (California State 

geologic map units: C, D, J, Kl, Ku, Pm, Pz, SO, and 

Tr);

• Ultramafic/mafic rocks (UM): Chiefly Mesozoic 

ultramafic, mafic, or gabbroic rocks (California State 

geologic map units: gb and um);

• Alluvial sediments (S): Chiefly Quaternary alluvial 

sediment (California State geologic map units: Q and 

Qg). No wells were sampled by USGS–GAMA in this 

unit.

• Undifferentiated rocks (X): Chiefly Franciscan 

formation (California State geologic map units: Ec, 

Kjf, Kjfs, M, Mc, Oc, QPc, Qv, Tc, Ti, Tv, and Tvp). 

No wells were sampled by USGS–GAMA in this unit.

Land Use

Land use was classified using an enhanced version of 

the satellite-derived (98-ft [30-m] pixel resolution) 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 dataset characterizes 

land cover during the early 1990s. The imagery was classified 

into 25 land-cover classifications (Nakagaki and Wolock, 

2005). These 25 land-cover classifications were aggregated 

into three principal land-use classes for the purpose of 

general categorization of land use: urban, agricultural, and 

natural. Average land use (proportions of urban, agricultural, 

and natural) for the study unit and for areas within a radius 

of 1,640 ft (500 m) surrounding each site (table A1) was 

calculated using ArcGIS (version 9.2) (Johnson and Belitz, 

2009).

LUFT and Septic Tank Densities

Density for LUFTs was determined by using a Thiessen 

polygon approach for spatial interpolation (Heywood 

and others, 1998; Tyler Johnson, U.S. Geological Survey, 

California Water Science Center, written commun., 2012) and 

data from the California Environmental Protection Agency 

(2001). Thiessen polygons were created by starting with the 

LUFT in the center of the polygon. The polygon edges were 

increased in all directions until they extended halfway to a 

neighboring LUFT (or they reached the edge of the State). 

The result is a unique shape for each LUFT. In most instances, 

there was only one LUFT per polygon, but occasionally 

there were multiple LUFTs in a polygon. The total number of 

LUFTs per polygon was divided by the area of the polygon. 

This generates a density of LUFTs for each polygon. The 

GAMA sites were then overlaid onto the Thiessen polygon 

map, and the GAMA site was assigned the LUFT density from 

the Thiessen polygon it was located within.

Septic tank density was determined from the 1990 

Census of Population and Housing: Summary Tape File 3A 

dataset (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 USGS–GAMA grid site was then calculated from 

the area-weighted mean of the block densities within a 500-m 

radius around the site location (Tyler Johnson, U.S. Geological 

Survey, California Water Science Center, written commun., 

2013) (table A1).
Table A1. Aquifer lithology class, land-use data, hydrologic conditions, leaking (or formerly leaking) underground fuel tank (LUFT) density, and septic Mountains study unit, 2010, California GAMA Priority Basin Project. [GAMA site identification number: KLAM, Klamath Mountains study unit; KLAM-U, Klamath Mountains study unit understanding site. Other abbreviations: ft, feet; m, me

kilometer; G, granitic rocks; LSD, land-surface datum; LUFT, leaking (or formerly leaking) underground fuel tank; M, metamorphic other; MS, metasedimentary; na, not availaultramafic/mafic] USGS–GAMA site identification number Aquifer lithology class Land use within 500 m of site 1 Hydrologic conditions 

(t

Agricultural (percent) Natural (percent) Urban (percent) Aridity index 2 Elevation of LSD (ft above NAVD 88) 3 Site type 4 Klamath Mountains study unit grid sites KLAM-01 UM 0 98 2 2.43 723 Spring 

KLAM-02 M 0 100 0 0.91 3,043 Spring 

KLAM-03 M 0 99 1 0.47 1,977 Production 

KLAM-04 MS 0 100 0 0.86 4,745 Spring 

KLAM-05 M 0 100 0 0.60 2,989 Production 

KLAM-06 MS 1 92 7 0.43 2,324 Production 

KLAM-07 M 0 100 0 1.07 2,235 Production 

KLAM-08 MS 0 98 2 2.18 2,152 Production 

KLAM-09 MS 0 100 0 1.48 713 Production 

KLAM-10 UM 0 100 0 2.03 1,063 Spring 

KLAM-11 MS 0 100 0 1.49 647 Production 

KLAM-12 MS 0 100 0 1.02 2,655 Spring 

KLAM-13 M 0 100 0 0.92 1,412 Production 

KLAM-14 MS 1 99 0 1.06 1,270 Production 

KLAM-15 MS 0 100 0 1.33 1,140 Production 

KLAM-16 MS 0 96 4 1.56 1,120 Production 

KLAM-17 G 0 100 0 0.59 3,321 Production 

KLAM-18 UM 0 78 22 1.14 3,301 Production 

KLAM-19 M 0 100 0 0.90 1,788 Production 

KLAM-20 UM 7 0 100 0 0.92 2,465 Spring 

KLAM-21 G 0 100 0 1.04 2,620 Production 

KLAM-22 M 0 95 5 1.48 457 Production 

KLAM-23 G 0 72 28 0.80 1,794 Production 
USGS–GAMA 

site identification 

number

Aquifer 

lithology 

class

Land use within 500 m of site 1 Hydrologic conditions 

(t

Agricultural 

(percent)

Natural 

(percent)

Urban 

(percent)

Aridity 

index 2

Elevation of LSD

(ft above NAVD 88) 3

Site 

type 4

Klamath Mountains study unit grid sites—Continued

KLAM-24 MS 0 100 0 0.71 3,436 Production 

KLAM-25 MS 0 96 4 1.39 1,085 Production 

KLAM-26 MS 8 48 35 17 0.96 1,093 Production 

KLAM-27 MS 0 100 0 1.49 1,143 Production 

KLAM-28 MS 0 99 1 1.73 1,091 Production 

KLAM-29 UM 0 83 17 1.56 2,611 Spring 

KLAM-30 M 0 96 4 1.59 2,008 Production 

KLAM-31 UM 0 100 0 1.31 3,971 Production 

KLAM-32 G 0 100 0 1.54 1,416 Production 

KLAM-33 MS 0 94 6 1.67 1,250 Production 

KLAM-34 MS 1 78 21 1.28 903 Production 

KLAM-35 M 0 100 0 1.43 1,331 Production 

KLAM-36 UM 0 91 9 1.32 2,479 Production 

KLAM-37 MS 0 100 0 0.81 1,926 Production 

KLAM-38 M 0 100 0 0.90 1,970 Production 

Klamath Mountains study unit understanding site

KLAM-U-01 MS 0 100 0 1.10 1,185 Production 

1 Land-use percentages within 500-m radius of sampled site (Nakagaki and others, 2007; Johnson and Belitz, 2009).2 Aridity index is average annual precipitation divided by average annual evapotranspiration (United Nations Educational, Scientific, and Cultural Organization, 1979).3 Land-surface datum (LSD) is a datum plane that is approximately at land surface at each site. The elevation of the LSD is described in feet above the North American Vertic4 Production sites had installed pumps which brought groundwater to the surface; springs had groundwater reaching the surface without pumps. 5 Leaking (or formerly leaking) underground fuel tank density within 500-m radius of sampled site (California Environmental Protection Agency, 2001).6 Septic tank density within 500-m radius of sampled site (U.S. Census Bureau, 1990).7 Originally identified as sedimentary rock type; however, it was reclassified based on proximity to adjacent rock type.8 Perforated interval of this well in the driller’s log describes its lithology as blue granite.

Table A1. Aquifer lithology class, land-use data, hydrologic conditions, leaking (or formerly leaking) underground fuel tank (LUFT) density, and septic Mountains study unit, 2010, California GAMA Priority Basin Project.—Continued[GAMA site identification number: KLAM, Klamath Mountains study unit; KLAM-U, Klamath Mountains study unit understanding site. Other abbreviations: ft, feet; m, me

kilometer; G, granitic rocks; LSD, land-surface datum; LUFT, leaking (or formerly leaking) underground fuel tank; M, metamorphic other; MS, metasedimentary; na, not availaultramafic/mafic]
44 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Hydrologic Conditions

Some of the hydrologic conditions at each site were 

represented by elevation and an aridity index. The aridity 

index is defined by the United Nations Environment 

Programme (1997) and United Nations Educational, Scientific, 

and Cultural Organization (1979) as

aridity index average annual precipitation

average annual e

 

 = vapotranspiration

. (A1)

Higher values of the index correspond to wetter 

conditions. Average annual precipitation for each site for 

1971–2000 was extracted from the PRISM average annual 

precipitation GIS coverage (PRISM Group, Oregon State 

University, 2007). Average annual evapotranspiration for each 

site was extracted from an ESRI® ArcGIS 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; Fram and Belitz, 

2012). Calculated aridity index values are listed in table A1.

The range of site land-surface altitudes was large, ranging 

from the minimum of 457 ft (140 m) to a maximum of 4,754 ft 

(1,450 m). Land-surface altitudes were obtained from the 

U.S. Geological Survey National Elevation Dataset (2006) and 

are reported in feet relative to NAVD 88 (table A1).

Well Construction

Well construction data primarily were obtained 

from drillers’ logs filed with CDWR. In some cases, well 

construction data were obtained from ancillary records of 

site owners or the USGS National Water Information System 

database. Well depths and depths to the tops and bottoms of 

the screened or open intervals for wells sampled by USGS–

GAMA are listed in table A2. Well construction data were 

not available for wells in the CDPH water-quality database. 

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. Springs 

were assigned a value of “at LSD” for the site depth and 

depth to top and bottom of the screened interval. Sites were 

classified as production wells or springs (table A1).

Table A2. Site construction information for USGS-grid and 

USGS-understanding sites, Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.

[GAMA site identification number: KLAM, Klamath Mountains study 

unit; KLAM-U, Klamath Mountains study unit understanding site. Other 

abbreviations: ft, feet; LSD, land-surface datum; na, not available]

USGS–

GAMA site 

identification 

number

Site construction information 

(ft below LSD1

)

Well depth

(ft below 

LSD) 2

Top of 

screened or 

open interval

(ft below LSD)

Bottom of 

screened or 

open interval

(ft below LSD)

Klamath Mountains study unit grid sites

KLAM-01 at LSD na na

KLAM-02 at LSD na na

KLAM-03 40 24 32

KLAM-04 at LSD na na

KLAM-05 80 57 80

KLAM-06 270 170 270

KLAM-07 na na na

KLAM-08 400 120 180

KLAM-09 48 36 48

KLAM-10 at LSD na na

KLAM-11 89 49 89

KLAM-12 at LSD na na

KLAM-13 45 na na

KLAM-14 na na na

KLAM-15 na na na

KLAM-16 278 55 278

KLAM-17 na na na

KLAM-18 320 240 300

KLAM-19 80 na na

KLAM-20 at LSD na na

KLAM-21 225 na na

KLAM-22 44 na na

KLAM-23 305 160 305

KLAM-24 na na na

KLAM-25 125 na na

KLAM-26 90 70 90

KLAM-27 320 300 320

KLAM-28 112 68 112

KLAM-29 at LSD na na

KLAM-30 120 60 120
Appendix A. Attribution of Potential Explanatory Factors 45

Geochemical Condition

Geochemical conditions were described by oxidationreduction (redox) characteristics and pH. Redox conditions 

influence the mobility of many organic and inorganic 

constituents (McMahon and Chapelle, 2008). Along 

groundwater flow paths, redox conditions commonly proceed 

along a well-documented sequence of terminal electron 

acceptor processes (TEAPs); one TEAP typically dominates 

at a particular time and aquifer location (Chapelle and 

others, 1995; Chapelle, 2001). The predominant TEAPs are 

oxygen-reducing, nitrate-reducing, manganese-reducing, ironreducing, sulfate-reducing, and methanogenesis. Groundwater 

samples may contain chemical species that suggest that more 

than one TEAP is occurring. Evidence for more than one 

TEAP may indicate mixing of waters from different redox 

zones upgradient of the site, a site that is screened across more 

than one redox zone, or spatial variability in microbial activity 

in the aquifer.

In this report, oxidation-reduction conditions were 

represented in three ways: by DO concentrations, by redox 

class, and by ratios of species of redox-sensitive trace 

elements (table A3). DO concentrations were measured in the 

Table A2. Site construction information for USGS-grid and 

USGS-understanding sites, Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.—Continued

[GAMA site identification number: KLAM, Klamath Mountains study 

unit; KLAM-U, Klamath Mountains study unit understanding site. Other 

abbreviations: ft, feet; LSD, land-surface datum; na, not available]

USGS–

GAMA site 

identification 

number

Site construction information 

(ft below LSD1

)

Well depth

(ft below 

LSD) 2

Top of 

screened or 

open interval

(ft below LSD)

Bottom of 

screened or 

open interval

(ft below LSD)

Klamath Mountains study unit grid sites—Continued

KLAM-31 nd na na

KLAM-32 227 187 227

KLAM-33 249 201 249

KLAM-34 177 77 177

KLAM-35 na na na

KLAM-36 25 na na

KLAM-37 na na na

KLAM-38 na na na

Klamath Mountains study unit understanding site

KLAM-U-01 na na na

1

 Land-surface datum (LSD) is a datum plane that is approximately at land 

surface at each site. The elevation of the LSD is described in feet above the 

North American Vertical Datum of 1988 (NAVD 88).

2

 Well depths reported as “at LSD” indicate spring sites.

Table A3. Oxidation-reduction classes, dissolved oxygen 

concentration, pH, and ratios of oxidation-reduction species of 

arsenic and iron, Klamath Mountains study unit, 2010, California 

GAMA Priority Basin Project.

[Oxidation-reduction classes: Fe-red, iron reducing; Mn-red, manganese 

reducing; Mn-Fe-red, manganese and iron reducing. Ratio of oxidized to 

reduced species of iron: 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) to 

the amount in the +2 oxidation state (ferrous). GAMA site identification 

number: KLAM, Klamath Mountains study unit; KLAM-U, Klamath 

Mountains study unit understanding site. Other abbreviations: mg/L, 

milligrams per liter; <, less than; >, greater than; na, not available; —, 

concentration too low to measure ratio]

USGS–

GAMA site 

identification 

number

pH 

(standard 

units)

Dissolved 

oxygen 

(mg/L)

Oxidationreduction class

Ratios of 

oxidized 

and reduced 

species of 

metals

As+5/

As+3

Fe+3/

Fe+2

Klamath Mountains study unit grid sites

KLAM-01 8.2 10.1 Oxic — >10

KLAM-02 6.1 10.6 Oxic — 0.11

KLAM-03 6.9 3.2 Oxic — 0.13

KLAM-04 6.3 7.9 Oxic — —

KLAM-05 7.2 8.7 Oxic — —

KLAM-06 8.3 0.5 Anoxic — <0.01

KLAM-07 7.1 8.4 Oxic >10 —

KLAM-08 7.3 0.9 Anoxic (Fe-red) — 0.09

KLAM-09 6.5 2.9 Mixed (Fe-red) — 0.02

KLAM-10 6.0 na Oxic — —

KLAM-11 6.9 9.4 Oxic >10 —

KLAM-12 6.6 7.5 Oxic — 0.83

KLAM-13 6.7 7.8 Oxic — 0.20

KLAM-14 7.2 6.9 Oxic >10 —

KLAM-15 6.8 9.3 Oxic — —

KLAM-16 5.9 4.5 Oxic — —

KLAM-17 6.2 2.2 Oxic >10 —

KLAM-18 6.1 6.1 Mixed (Fe-red) — 0.04

KLAM-19 7.2 2.0 Oxic >10 <0.01

KLAM-20 7.6 7.5 Oxic — —

KLAM-21 7.2 7.2 Oxic >10 —

KLAM-22 7.0 10.7 Oxic >10 0.23

KLAM-23 7.4 2.5 Oxic >10 1.3

KLAM-24 7.5 0.4 Anoxic

(Mn-Fe-red)

— 0.06

KLAM-25 7.0 2.4 Mixed

(Mn-Fe-red)

>10 0.05
46 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

field at all KLAM study unit grid sites (Mathany and Belitz, 

2014). Redox conditions were classified on the basis of DO, 

nitrate, manganese, and iron concentrations using a modified 

version of the classification scheme of McMahon and 

Chapelle (2008) and (Jurgens and others, 2009). Samples were 

classified as oxic, anoxic, or mixed according to the TEAPs 

inferred from the data (table A3).

Arsenic (As) and iron (Fe) can 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 provides 

information about the progress of the TEAP involving each 

constituent. The following ratios are reported in table A3:

• 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); and

• 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 in Mathany and Belitz (2014). The 

concentrations of As+5 and Fe+3 were calculated by difference. 

The ratio of As+5/As+3 was reported as greater than 10 if 

total arsenic was detected and As+3 was not detected, and 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 total iron was detected and Fe+2 was not detected, 

and as less than 0.01 if the total iron concentration equaled the 

Fe+2 concentration.

Groundwater Age

Groundwater dating techniques indicate the time since the 

groundwater was recharged into the primary aquifer system. 

The techniques used in this report to estimate groundwater 

residence times or ‘age’ were those based on tritium (for 

example, Tolstikhin and Kamensky, 1969; Torgersen and 

others, 1979) and carbon-14 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). 

Tritium is produced naturally in the atmosphere from the 

interaction of cosmogenic radiation with nitrogen (Craig and 

Lal, 1961) and anthropogenically by above-ground nuclear 

explosions and the operation of nuclear reactors. Tritium 

enters the hydrologic cycle following oxidation to 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 TU in 

the northern hemisphere (Michel, 1989). Radioactive decay 

over a period of 50 years would decrease tritium values of 

10 TU to 0.6 TU. Tritium values in precipitation under natural 

conditions in the KLAM study unit in 2010 were about 2 to 

3 TU (updated values from Michel, 1989). On the west coast, 

most of the storms are oceanic in origin, so the water from 

these storms is mostly from exchange with surface ocean 

water, which has relatively low tritium (Michel, 1989).

Previous investigations have used a range of tritium 

values from 0.2 to 1.0 TU as thresholds for indicating 

presence of water that has exchanged with the atmosphere 

since 1952 (Michel, 1989; Plummer and others, 1993; Michel 

and Schroeder, 1994; Clark and Fritz, 1997; Manning and 

Table A3. Oxidation-reduction classes, dissolved oxygen 

concentration, pH, and ratios of oxidation-reduction species of 

arsenic and iron, Klamath Mountains study unit, 2010, California 

GAMA Priority Basin Project.—Continued

[Oxidation-reduction classes: Fe-red, iron reducing; Mn-red, manganese 

reducing; Mn-Fe-red, manganese and iron reducing. Ratio of oxidized to 

reduced species of iron: 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) to 

the amount in the +2 oxidation state (ferrous). GAMA site identification 

number: KLAM, Klamath Mountains study unit; KLAM-U, Klamath 

Mountains study unit understanding site. Other abbreviations: mg/L, 

milligrams per liter; <, less than; >, greater than; na, not available; —, 

concentration too low to measure ratio]

USGS–

GAMA site 

identification 

number

pH 

(standard 

units)

Dissolved 

oxygen 

(mg/L)

Oxidationreduction class

Ratios of 

oxidized 

and reduced 

species of 

metals

As+5/

As+3

Fe+3/

Fe+2

Klamath Mountains study unit grid sites—Continued

KLAM-26 6.8 1.4 Oxic — 0.27

KLAM-27 6.2 6.1 Mixed Mn-red — 0.17

KLAM-28 6.5 3.4 Oxic — <0.01

KLAM-29 6.6 11.8 Oxic >10 0.75

KLAM-30 6.8 <0.2 Anoxic

(Mn-Fe-red)

— 0.02

KLAM-31 9.4 2.6 Oxic — —

KLAM-32 6.9 4.2 Oxic — 0.26

KLAM-33 7.6 0.9 Oxic >10 1.0

KLAM-34 7.4 5.6 Oxic — 0.70

KLAM-35 6.7 4.1 Oxic — —

KLAM-36 6.6 7.0 Oxic — 0.25

KLAM-37 6.1 2.3 Oxic — 0.48

KLAM-38 6.9 7.3 Oxic — <0.01

Klamath Mountains study unit understanding site

KLAM-U-01 7.2 7.4 Oxic >10 >10
Appendix A. Attribution of Potential Explanatory Factors 47

others, 2005). For samples collected for the KLAM study 

unit in 2010, tritium values greater than 1 TU were defined 

as indicating presence of some groundwater recharged since 

1952.

Carbon-14 (14C) is a widely used chronometer based 

on the radiocarbon content of organic and inorganic 

carbon. Dissolved inorganic carbon species, carbonic acid, 

bicarbonate, and carbonate typically are used for 14C dating 

of groundwater. 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. The 14C content of groundwater reflects the 

time since groundwater was last exposed to the atmospheric 

14C source. 14C has a half-life of 5,730 years and 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 percent modern carbon (pmc). 14C data 

for the KLAM study unit in Mathany and Belitz (2014) 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):

pmC

pM C

=

+





 



 1

0 975

13 2

2

δ

1,000

. (A2)

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:

radiocarbon age A

A

, Dsamp , = ( ) × 



 



 − 5 568 −

2

1 950

1 029

0

ln

ln .

(A3)

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 are not adjusted to consider waterrock 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 greater than 88 pmc is reported as having an age 

of less than 1,000 years; no attempt is made to refine 14C ages 

less than 1,000 years. Measured values of percent modern 

carbon can be greater than 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.

Although more sophisticated lumped parameter models 

used for analyzing age distributions that incorporate mixing 

are available (for example, Cook and Böhlke, 2000, and 

Jurgens and others, 2012), 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 the purposes of examining groundwater 

quality. Tritium concentrations, uncorrected 14C age, and 

sample age classifications are reported in table A4.
48 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Table A4. Tritium and carbon-14 data and groundwater age class, Klamath Mountains study unit, 2010, California GAMA Priority Basin 

Project.

[Groundwater age classes were based on tritium and carbon-14 data. Groundwater with tritium < 1 TU was defined as pre-modern, recharged before 1952. 

Groundwater with tritium > 1 TU and percent modern carbon (pmc) > 90 was defined as modern, recharged after 1952. Groundwater with tritium > 1 TU and 

pmc < 90 was defined as mixed, containing components recharged before and after 1952. GAMA site identification number: KLAM, Klamath Mountains 

study unit; KLAM-U, Klamath Mountains study unit understanding site. Other abbreviations: 14C, carbon-14; TU, tritium units; <, less than; >, greater than]

USGS–GAMA 

site identification 

number

Tritium 

(TU)

Percent 

modern carbon 

(pmc)

Radiocarbon 

age 

(years)

Radiocarbon 

age error 

(uncorrected, years)

Age class

Klamath Mountains study unit grid sites

KLAM-01 2.2 90 <1,000 na Modern

KLAM-02 2.4 104 <1,000 na Modern

KLAM-03 1.9 85 1,080 30 Mixed

KLAM-04 2.8 103 <1,000 na Modern

KLAM-05 2.5 98 <1,000 na Modern

KLAM-06 0.4 39 7,390 30 Pre-modern

KLAM-07 2.0 94 <1,000 na Modern

KLAM-08 2.1 48 5,590 30 Mixed

KLAM-09 2.3 76 2,090 30 Mixed

KLAM-10 2.3 95 <1,000 na Modern

KLAM-11 2.6 107 <1,000 na Modern

KLAM-12 3.5 95 <1,000 na Modern

KLAM-13 2.9 104 <1,000 na Modern

KLAM-14 2.8 100 <1,000 na Modern

KLAM-15 2.4 101 <1,000 na Modern

KLAM-16 3.3 97 <1,000 na Modern

KLAM-17 1.9 104 <1,000 na Modern

KLAM-18 2.3 96 <1,000 na Modern

KLAM-19 2.7 103 <1,000 na Modern

KLAM-20 1.4 95 <1,000 na Modern

KLAM-21 1.8 95 <1,000 na Modern

KLAM-22 2.0 96 <1,000 na Modern

KLAM-23 1.4 97 <1,000 na Modern

KLAM-24 1.5 78 1,760 30 Mixed

KLAM-25 2.8 77 1,920 30 Mixed

KLAM-26 2.4 111 <1,000 na Modern

KLAM-27 2.4 104 <1,000 na Modern

KLAM-28 2.8 97 <1,000 na Modern

KLAM-29 2.3 64 3,340 30 Mixed

KLAM-30 0.3 56 4,440 30 Pre-modern
Appendix A. Attribution of Potential Explanatory Factors 49

Table A4. Tritium and carbon-14 data and groundwater age class, Klamath Mountains study unit, 2010, California GAMA Priority Basin 

Project.—Continued

[Groundwater age classes were based on tritium and carbon-14 data. Groundwater with tritium < 1 TU was defined as pre-modern, recharged before 1952. 

Groundwater with tritium > 1 TU and percent modern carbon (pmc) > 90 was defined as modern, recharged after 1952. Groundwater with tritium > 1 TU and 

pmc < 90 was defined as mixed, containing components recharged before and after 1952. GAMA site identification number: KLAM, Klamath Mountains 

study unit; KLAM-U, Klamath Mountains study unit understanding site. Other abbreviations: 14C, carbon-14; TU, tritium units; <, less than; >, greater than]

USGS–GAMA 

site identification 

number

Tritium 

(TU)

Percent 

modern carbon 

(pmc)

Radiocarbon 

age 

(years)

Radiocarbon 

age error 

(uncorrected, years)

Age class

Klamath Mountains study unit grid sites—Continued

KLAM-31 2.8 76 2,010 20 Mixed

KLAM-32 3.4 88 <1,000 na Mixed

KLAM-33 1.6 47 5,850 40 Mixed

KLAM-34 2.9 71 2,460 30 Mixed

KLAM-35 2.5 97 <1,000 na Modern

KLAM-36 3.0 105 <1,000 na Modern

KLAM-37 2.5 101 <1,000 na Modern

KLAM-38 2.6 102 <1,000 na Modern

Klamath Mountains study unit understanding site

KLAM-U-01 2.6 88 <1,000 na Mixed
50 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Appendix B. Grid Cells and Sites

sac14-0524_fig B1

4

6

7

5

5

3

7

4

6

5

KLAM-11

KLAM-10

KLAM-08

KLAM-01

41°30'

124° 123°30'

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

B1

B1

B2

B3

B4

B5

0 3 6 12 Miles

0 6 12 Kilometers 3

USGS-grid site

Study unit boundary

1 10 Cell boundary 

and number

EXPLANATION

Figure B1. Identifiers and locations of cells, grid sites, and understanding sites sampled by the U.S. Geological Survey from October 

to December 2010, and grid sites for which data for inorganic constituents from the California Department of Public Health (CDPH) were 

used, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

The locations and identification numbers of grid and 

USGS-understanding sites are shown in figures B1-B5. 

Additionally, cell boundaries and cell numbers are also shown.
Appendix B. Grid Cells and Sites 51

Figure B2. Identifiers and locations of cells, grid sites, and understanding sites sampled by the U.S. Geological Survey from October 

to December 2010, and grid sites for which data for inorganic constituents from the California Department of Public Health (CDPH) were 

used, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

sac14-0524_fig B2

9

8

9

8

32

7

22

21

23

21

34

20

22

19

19

8

33

33

19

20

20

33

23

18

18

10

21

21

32

KLAM-31

KLAM-24

KLAM-17

KLAM-07

KLAM-05

KLAM-03

KLAM-02 KLAM-04

123° 122°30'

41°30'

0 3 6 12 Miles

0 6 12 Kilometers 3

B1

B2

B3

B4

B5

1 10 Cell boundary 

and number

EXPLANATION

USGS-grid site

Study unit boundary

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

B2

KLAM-06
52 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Figure B3. Identifiers and locations of cells, grid sites, and understanding sites sampled by the U.S. Geological Survey from October 

to December 2010, and grid sites for which data for inorganic constituents from the California Department of Public Health (CDPH) were 

used, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

sac14-0524_fig B3

1 10 Cell boundary 

and number

EXPLANATION

USGS-grid site

USGS-understanding site

Study unit boundary

!(

!

!

!

!

!

!

2

3

1

1

2

13

11

3

1

12

10

10

KLAM-22

KLAM-15

KLAM-14

KLAM-09

KLAM-U-01

124° 123°30'

40°30'

41°

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

B3

0 3 6 12 Miles

0 6 12 Kilometers 3

B1

B2

B3

B4

B5
Appendix B. Grid Cells and Sites 53

Figure B4. Identifiers and locations of cells, grid sites, and understanding sites sampled by the U.S. Geological Survey from October 

to December 2010, and grid sites for which data for inorganic constituents from the California Department of Public Health (CDPH) were 

used, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

sac14-0524_fig B4

1 10 Cell boundary 

and number

EXPLANATION

30

15 40

16

29

17

24

28

37

39

25

11

38

31

31

27

18

38

14

12

14

23

26

26

24

28

26

25

27

12

10

13

37 32

14

17

18

29

13

25

13

KLAM-38

KLAM-37

KLAM-36

KLAM-35

KLAM-34

KLAM-33

KLAM-32 KLAM-28

KLAM-27

KLAM-26

KLAM-25

KLAM-23

KLAM-21

KLAM-20

KLAM-19

KLAM-18

KLAM-16

KLAM-DPH-39

KLAM-13

KLAM-12

122°30'

40°30'

123°

41°

10

B1

B2

B3

B4

B4

B5

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

USGS-grid site

Study unit boundary

0 3 6 12 Miles

0 6 12 Kilometers 3
54 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Figure B5. Identifiers and locations of cells, grid sites, and understanding sites sampled by the U.S. Geological Survey from October 

to December 2010, and grid sites for which data for inorganic constituents from the California Department of Public Health (CDPH) were 

used, Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.

sac14-0524_fig B5

35

34

36

31

36

35

37

32

36

37

31

KLAM-DPH-40

KLAM-30

KLAM-29

0 2 4 8 Miles

0 2 4 8 Kilometers

1 10 Cell boundary 

and number

EXPLANATION

USGS-grid site

Study unit boundary

B5

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

122°30' 122°

41°

B1

B2

B3

B4

B5
Appendix C. Calculation of Aquifer-Scale Proportions 55

Appendix C. Calculation of Aquifer-Scale Proportions 

The methods used to calculate aquifer-scale proportions 

using the grid-based and spatially weighted approaches are 

described in this appendix.

Grid-Based Calculation

In the grid-based approach, one value in each grid 

cell, a “grid site,” was randomly selected to represent the 

primary aquifer system (Belitz and others, 2010). For organic 

constituents, the one value in each grid cell was obtained 

from the samples analyzed by USGS–GAMA from 38 grid 

sites. For inorganic constituents, one value in each grid cell 

was obtained from the samples analyzed by USGS–GAMA 

from 38 of the grid sites, and data were obtained from the 

CDPH water-quality database for 2 additional grid cells not 

sampled by USGS–GAMA (table C1). Confidence intervals 

for grid-based aquifer proportions were computed using the 

Jeffreys interval for the binomial distribution (Brown and 

others, 2001). The Jeffreys interval is only one of a small 

number of formulas that can be used to calculate a confidence 

interval for a proportion within a statistical population. Its use 

here is based on an analysis and comparison of other intervals 

by Belitz and others (2010); they concluded that the Jeffreys 

interval was ideal due to its narrower confidence window and 

better one-sided coverage probability. The grid-based estimate 

is designed to be spatially unbiased; however, the grid-based 

approach may not identify constituents that exist at high or 

moderate concentrations in small proportions of the primary 

aquifer system.

Spatially Weighted Calculation

The spatially weighted approach used data from the 38 

grid sites and 1 understanding site sampled and analyzed by 

USGS–GAMA in 2010 and data compiled in the CDPH waterquality database for samples collected between December 1, 

2007, and December 31, 2010. The most recent analyses were 

used for each constituent at each site. The spatially weighted 

approach uses all the sites in each cell to calculate the high, 

moderate, and low relative-concentrations for the cell.

For each constituent, the high aquifer-scale proportion 

was calculated by (1) computing the proportion of wells 

having high relative concentrations in each grid cell and then 

(2) averaging the grid cell values computed in step 1 (Isaaks 

and Srivastava, 1989):

P

W

W

C SU

high

total =

∑

(C1)

where

PSU is the aquifer-scale proportion for the study 

unit,

C is the number of cells with data for the 

constituent,

Wtotal is the number of wells in a given cell, and

Whigh is the number of wells in a given cell with 

high relative-concentrations for the 

constituent.

The same procedure was used to calculate the proportions 

of moderate and low relative-concentrations. The resulting 

proportions were spatially unbiased (Isaaks and Srivastava, 

1989).

Table C1. California Department of Public Health (CDPH) data 

used for the grid-based calculations of aquifer-scale proportions, 

Klamath Mountains study unit, 2010, California GAMA Priority 

Basin Project.

[CDPH data are from the most recent analysis for each constituent during 

the period December 1, 2007, through December 31, 2010. In the CDPH 

database, non-detections are reported as zero (0) for some samples. Units: 

mg/L, milligrams per liter; μg/L, micrograms per liter. Other abbreviations: 

na, not available]

USGS–GAMA 

site identification 

number

KLAM-DPH-39 KLAM-DPH-40

Date sampled 12/21/2009 10/20/2009

Cell 13 35

Trace elements (μg/L)

Antimony 0 na

Arsenic 0 na

Barium 570 na

Beryllium 0 na

Cadmium 0 na

Chromium 0 na

Copper 0 na

Fluoride 1 0 na

Lead 0 na

Mercury 0 na

Selenium 0 na

Thallium 0 na

Nutrients (mg/L)

Nitrate, as nitrogen 0 0

Nitrite, as nitrogen 0 na

1

 Concentrations of fluoride are presented in milligrams per liter (mg/L).
56 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Appendix D. Comparison of CDPH and USGS–GAMA Data

Although the ultimate contribution of CDPH data to the 

KLAM study unit was limited, the CDPH and USGS–GAMA 

data were compared to assess the validity of combining 

data for inorganic constituents from these different sources. 

Concentrations of inorganic constituents (alkalinity, calcium, 

magnesium, potassium, sodium, chloride, sulfate, and TDS), 

which generally are prevalent at concentrations substantially 

above reporting levels, were compared for each site using 

data from both sources. Four sites had alkalinity data from the 

USGS-database and the CDPH water-quality database, two 

sites had data for calcium, magnesium, and sodium from both 

databases, and only one site had chloride, sulfate, and TDS 

data from both databases. Wilcoxon signed-rank tests of paired 

analyses for these eight constituents indicated no significant 

differences between USGS–GAMA and CDPH data for these 

constituents. Differences between the paired datasets were 

very minor, and most sample pairs plotted very close to a 

1:1 line (fig. D1). These plots indicated that the USGS–GAMA 

and CDPH inorganic data were comparable.

Major-ion data for grid sites with sufficient data (USGS 

and CDPH data) were plotted on a trilinear diagram (Piper, 

1944) along with all CDPH major-ion data to determine 

whether the groundwater types in grid sites were similar 

to groundwater types observed in the study unit. Trilinear 

diagrams show the relative abundance of major cations and 

anions (on a charge equivalent basis) as a percentage of the 

total ion content of the water (fig. D2). Trilinear diagrams 

often are used to define groundwater type (Hem, 1985). All 

major-ion data in the CDPH water-quality database with a 

cation/anion imbalance of less than 10 percent were retrieved 

and plotted on the trilinear diagrams for comparison with 

USGS-grid site data.

The ranges of water types for USGS-grid sites and other 

sites from the CDPH water-quality database were generally 

similar (fig. D2). In both datasets, samples from most sites 

showed no single cation accounting for more than 60 percent 

of the total cations, and bicarbonate accounted for more 

than 80 percent of the total anions. Waters in these sites are 

described as mixed cation–bicarbonate type waters. Only a 

few sites from either dataset appeared dissimilar to the mixed 

cation–bicarbonate type observed in a majority of the sites. 

Four sites in the USGS–GAMA grid dataset had magnesium 

concentrations representing more than 60 percent of the cation 

total, which was not seen in any of the CDPH sites. These 

four sites could be classified as magnesium-bicarbonate type 

waters. One USGS–GAMA grid site had a sodium-chloride

type water (sodium and chloride representing greater than 

60 percent of the cation and anion totals, respectively), which 

was not seen in the CDPH dataset. With the exception of the 

USGS–GAMA grid sites which had magnesium-bicarbonate

type waters and the USGS–GAMA grid site with the sodiumchloride type water, the range and relative abundances of 

major cations and anions in a majority of USGS–GAMA 

grid sites were similar to the range of those in CDPH sites. 

Because relatively few CDPH sites are in the KLAM study 

unit and CDPH sites don’t always have the complete suite of 

constituents necessary for the determination of water type, 

the water types identified using the CDPH dataset may not be 

as complete as in other USGS–GAMA study units which had 

larger CDPH datasets.

0.1 1 10 100 1,000

Concentration, USGS-GAMA data, milligrams per liter

Concentration, CDPH data, milligrams per liter

0.1

1

10

100

1,000

Calcium

Magnesium

Potassium

Sodium

Alkalinity

Chloride

Sulfate

Total dissolved solids

1:1

EXPLANATION

Figure D1. Paired inorganic concentrations from USGS-grid sites and the most recent available analysis in the CDPH water-quality 

database for the same site in the Klamath Mountains study unit, 2010, California GAMA Priority Basin Project.
Appendix D. Comparison of CDPH and USGS–GAMA Data 

57

Figure D2. Piper diagram showing USGS-grid sites and all sites in the CDPH water-quality database that had major-ion data with 

acceptable cation/anion balances during the 3-year interval used in the status assessment for the Klamath Mountains study unit, 2010, 

California GAMA Priority Basin Project.

sac14-0524_fig D2

PERCENT

Calcium

 100 0 80 

 60 

 40 

 20 

 0 

 20 

 40 

 60 

 80 

 100 0 

 20 

 40 

 60 

 80 

 100 

Chloride

 0 

 20 

 40 

 60 

 80 

 100 

 100 

 80 

 60 

 40 

 20 

 0 

 100 

 80 

 60 

 40 

 20 

 0 

 0 

 20 

 40 

 60 

 80 

 100 

 0 

 20 

 40 

 60 

 80 

 100 100 

 80 

 60 

 40 

 20 

 0 

 100 

 80 

 60 

 40 

 20 

 0 

USGS-grid site

CDPH site (most recent analysis with

 cation/anion imbalance less than 10 percent)

EXPLANATION

PERCENT

PERCENT

Sulfate plus chloride

Bicarbonate

Magnesium

Calcium plus magnesium

Sodium plus potasium

Sulfate
58 Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010

Publishing support provided by the U.S. Geological Survey 

Science Publishing Network, Sacramento, Tacoma, and Raleigh Publishing Service Centers

For more information concerning the research in this report, contact the

 Director, California Water Science Center

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)

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20145065

Bennett and others—Status and Understanding of Groundwater Quality in the Klamath Mountains Study Unit, 2010: California GAMA Priority Basin Project—SIR 2014–5065

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