U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2014–5215

Prepared in cooperation with the California State Water Resources Control Board and the 

U.S. Geological Survey National Water-Quality Assessment Program

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

Status and Understanding of Groundwater Quality in the Northern 

Coast Ranges Study Unit, 2009: California GAMA Priority Basin Project
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: Trinidad Head Memorial, Trinidad, California. (Photograph taken by George Bennett V, 

U.S. Geological Survey.)

Back cover: Eel River from California Highway 162, near Covelo, California. (Photograph taken by 

Barbara Dawson, U.S. Geological Survey.)
Status and Understanding of Groundwater 

Quality in the Northern Coast Ranges Study 

Unit, 2009: California GAMA Priority Basin 

Project

By Timothy M. Mathany and Kenneth Belitz

Prepared in cooperation with the California State Water Resources Control Board 

and the U.S. Geological Survey National Water-Quality Assessment Program

Scientific Investigations Report 2014–5215

U.S. Department of the Interior

U.S. Geological Survey

A product of the California Groundwater Ambient Monitoring and Assessment 

(GAMA) Program
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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

Suggested citation:

Mathany, T.M., and Belitz, Kenneth, 2015, Status and understanding of groundwater quality in the Northern Coast 

Ranges study unit, 2009—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations 

Report 2014–5215, 86 p., http://dx.doi.org/10.3133/sir20145215.

ISSN 2328-031X (print)

ISSN 2328-0328 (online)

ISBN 978-1-4113-3904-0
iii

Contents

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

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

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

Hydrogeologic Setting of the Northern Coast Ranges Study Unit.........................................................5

Northern Coast Ranges—Interior Basins Study Area ...................................................................5

Northern Coast Ranges—Coastal Basins Study Area ...................................................................9

Methods.........................................................................................................................................................10

Status Assessment.............................................................................................................................10

Relative-Concentrations and Water-Quality Benchmarks .................................................10

Datasets Used for Status Assessment...................................................................................11

USGS-GAMA Grid Sites...................................................................................................11

Additional Data Used for Spatially Weighted Calculation .........................................11

Selection of Constituents for Additional Evaluation in the Status Assessment..............13

Calculation of Aquifer-Scale Proportions..............................................................................15

Understanding-Assessment Methods ............................................................................................16

Statistical Analysis ....................................................................................................................17

Potential Explanatory Factors ...................................................................................................................17

Land Use...............................................................................................................................................17

Well Construction Information..........................................................................................................20

Hydrologic Conditions........................................................................................................................20

Groundwater Age................................................................................................................................20

Geochemical Conditions....................................................................................................................23

Correlations Between Explanatory Factors ...................................................................................23

Status and Understanding of Water Quality............................................................................................28

Inorganic Constituents.......................................................................................................................28

Inorganic Constituents with Health-Based Benchmarks ...................................................28

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

Understanding Assessment for Boron.................................................................32

Understanding Assessment for Arsenic..............................................................39

Nutrients.............................................................................................................................42

Uranium and Other Radioactive Constituents..............................................................42

Inorganic Constituents with Aesthetic-Based Benchmarks..............................................42

Understanding Assessment for Iron and Manganese ...............................................42

Organic Constituents with Health-Based Benchmarks ...............................................................45

Volative Organic Compounds...................................................................................................47

Understanding Assessment for Chloroform.................................................................49

Pesticides and Pesticide Degradates ....................................................................................51

Understanding Assessment for Simazine.....................................................................51

Special-Interest Constituent with Health-Based Benchmark............................................53

Understanding Assessment for Perchlorate................................................................53
iv

Contents—Continued

Summary........................................................................................................................................................54

Acknowledgments.......................................................................................................................................55

References....................................................................................................................................................55

Appendix A. Map of the Northern Coast Ranges Study Unit ...........................................................65

Appendix B. Ancillary Datasets .............................................................................................................71

Appendix C. Calculation of Aquifer-Scale Proportions......................................................................81

Appendix D. Comparison of CDPH and GAMA Priority Basin Data .................................................83

Appendix E. Additional Water-Quality Data.........................................................................................85

Figures

1. Map showing location of the Northern Coast Ranges study unit and the 

California hydrogeologic provinces, California GAMA Priority Basin Project...................3

2. Map showing location of the Coastal Basins and Interior Basins study areas, 

major cities and towns, major roads, and hydrologic features in the Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project.............................6

3. Maps showing geologic formations and locations of the Coastal Basins study 

area and Interior Basins study area, locations of hot springs and 

geothermal wells, and approximate boundaries of the Napa and Sonoma 

Valleys and the Geysers Steam Field, Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project..........................................................................7

4. Map showing locations of study area grid cells, USGS-GAMA grid sites, and 

CDPH sites, Northern Coast Ranges study unit, 2009, California GAMA 

Priority Basin Project.................................................................................................................12

5. Map showing land use and the location of leaking or formerly leaking 

underground fuel tanks in the Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project........................................................................18

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

uses for the study unit and study areas and the area surrounding each 

USGS-GAMA grid site in the Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project..................................................................................19

7. Boxplots showing construction characteristics for USGS-GAMA grid sites in 

the Interior Basins study area and Coastal Basins study area, Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project...........................21

8. Boxplots showing relation of groundwater age classification to well depth and 

depth to top-of-perforations for wells in the Interior Basins study area, 

well depth and depth to top-of-perforations for wells in the Coastal Basins 

study area, and bar chart showing the depth class of all wells in the Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project...........................22

9. Graphs showing groundwater age classification and well depth in relation to 

pH and dissolved oxygen concentrations, Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project ............................................................................27

10. Graph showing maximum relative-concentration of constituents detected in 

USGS-GAMA grid sites, by constituent class, Northern Coast Ranges study 

unit, 2009, California GAMA Priority Basin Project...............................................................30
v

Figures—Continued

11. Graphs showing relative-concentrations of selected constituents with 

health-based benchmarks and constituents with aesthetic-based 

benchmarks in USGS-GAMA grid sites, Northern Coast Ranges study 

unit, 2009, California GAMA Priority Basin Project...............................................................31

12. Maps showing relative-concentrations of boron in USGS-GAMA grid sites and 

geologic features in the Coastal Basins study area and Interior Basins study 

area, and geologic formations, locations of hot springs and geothermal wells, 

and approximate boundaries of the Napa and Sonoma Valleys and the 

Geysers Steam Field, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project....................................................................................................34

13. Maps showing relative-concentrations of arsenic in USGS-GAMA grid sites, 

CDPH sites for the period June 1, 2006–June 1, 2009, from the CDPH water-quality 

database, and geologic features in the Coastal Basins study area and Interior 

Basins study area and geologic formations, locations of hot springs and 

geothermal wells, and approximate boundaries of the Napa and Sonoma Valleys 

and the Geysers Steam Field Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project..................................................................................36

14. Plots showing boron concentrations relative to field water temperature, 

field water temperature and distance to nearest hot spring, field water 

temperature and distance to nearest geothermal well, and redox classification 

in USGS-GAMA grid sites sampled for the Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project........................................................................38

15. Plots showing arsenic concentrations relative to groundwater age classification 

and redox classification in USGS-GAMA grid sites sampled for the Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project...........................41

16. Maps showing relative-concentrations of iron in USGS-GAMA grid sites and CDPH 

sites for the period June 1, 2006–June 1, 2009, from the CDPH water-quality 

database in the Coastal Basins study area and Interior Basins study area, 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project .........43

17. Maps showing relative-concentrations of manganese in USGS-GAMA grid sites and 

CDPH sites for the period June 1, 2006–June 1, 2009, from the CDPH water-quality 

database in the Coastal Basins study area and Interior Basins study area, 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project .........44

18. Graph showing maximum relative-concentration of organic and 

special-interest constituents detected in USGS-GAMA grid sites, Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project...........................45

19. Graphs showing detection frequency and maximum relative-concentration 

of organic and special-interest constituents detected in USGS-GAMA 

grid sites, Northern Coast Ranges study unit, 2009, California GAMA 

Priority Basin Project.................................................................................................................46

20. Maps showing relative-concentrations of chloroform detected in USGS-GAMA 

grid sites and CDPH sites for the period June 1, 2006–June 1, 2009, from the 

CDPH water-quality database, and locations of leaking or formerly leaking 

underground fuel tanks, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project....................................................................................................48

21. Plots showing trihalomethane chloroform concentrations relative to groundwater 

age classification and depth to top-of-perforations in USGS-GAMA grid sites 

sampled for the Northern Coast Ranges study unit, 2009, California GAMA 

Priority Basin Project.................................................................................................................49
vi

Figures—Continued

22. Map showing relative-concentrations of simazine detected in USGS-GAMA 

grid sites and CDPH sites for the period June 1, 2006–June 1, 2009, from the 

CDPH water-quality database, and locations of leaking or formerly leaking 

underground fuel tanks, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project....................................................................................................50

23. Plot showing the herbicide simazine concentrations relative to groundwater 

age classification and depth to top-of-perforations in USGS-GAMA grid sites 

sampled for the Northern Coast Ranges study unit, 2009, California GAMA 

Priority Basin Project.................................................................................................................51

24. Maps showing relative-concentrations of perchlorate in USGS-GAMA grid sites 

and CDPH sites for the period June 1, 2006–June 1, 2009, from the CDPH 

water-quality database, and land use, Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project........................................................................52

 25. Plot showing the special-interest constituent perchlorate concentrations 

relative to geochemical condition and depths to top-of-perforations in 

USGS-GAMA grid sites sampled for the Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project........................................................................53

Tables

1. Constituent classes and numbers of constituents analyzed for the 58 sites sampled, 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project .........11

2. Numbers of constituents analyzed and detected in each constituent class with 

each type of benchmark, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project....................................................................................................13

3. Constituents selected for additional evaluation in the status assessment, 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project .........14

4. Constituents reported at concentrations greater than benchmarks historically 

in the California Department of Public Health database, but not during the 

3-year time period used in the status assessment, Northern Coast Ranges 

study unit, California GAMA Priority Basin Project ..............................................................15

5. Results of non-parametric analysis of correlations between selected potential 

explanatory factors, Northern Coast Ranges study unit, 2009, California 

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

6. Results of Wilcoxon rank-sum tests on USGS-GAMA grid site data used to 

determine significant differences between constituent values grouped by 

potential explanatory factors, Northern Coast Ranges study unit, 2009, 

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

7. Aquifer-scale proportions calculated using grid-based and spatially weighted 

methods for those constituents that met criteria for additional evaluation in the 

status assessment, Northern Coast Ranges study unit, 2009, California GAMA 

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

8A. Summary of aquifer-scale proportions for inorganic constituent classes, 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project .........33

8B. Summary of aquifer-scale proportions for organic and special-interest 

constituent classes, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project....................................................................................................33

9. Results of non-parametric analysis for correlations between selected 

water-quality constituents and potential explanatory factors, Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project...........................40
vii

Conversion Factors, Datums, and Abbreviations and Acronyms

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 2.590 square kilometer (km2) 

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

Area

square kilometer (km2

) 0.3861 square mile (mi2)

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

°F=(1.8×°C)+32

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

°C=(°F–32)/1.8

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).

Concentrations of dissolved noble gases in water are given in standard pressure per gram of 

water (g–1 H2O).

Datums

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

(NAVD 88).

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

Land-surface altitude, as used in this report, refers to distance above the vertical datum and is 

reported as feet above mean sea level (ft above msl).

Depth, as used in this report, refers to distance below the land-surface datum and is reported as 

feet below land surface (ft bls).
viii

Selected terms and symbols

= equal to

> greater than 

≥ greater than or equal to

< less than

≤ less than or equal to

Abbreviations and Acronyms

AB Assembly Bill (through the California State Assembly)

AL-US action level (USEPA)

DO dissolved oxygen

DOGGR California Department of Conservation Division of Oil, Gas, and Geothermal 

Resources

DOM domestic site

GWSI Groundwater Site Inventory database (USGS)

HAL lifetime health advisory level

HAL-US lifetime health advisory level (USEPA)

HBSL health-based screening level

IND industrial site

INS institutional site

IRR irrigation site

LRL laboratory reporting level

LT-MDL long-term method detection level

LUFT leaking or formerly leaking underground fuel tank

MCL maximum contaminant level

MCL-CA maximum contaminant level (CDPH)

MCL-US maximum contaminant level (USEPA)

MDL method detection limit

MRDS Mineral Resources Data System (USGS)

MRL minimum reporting level

MTBE methyl tert-butyl ether

NLCD National Land Cover Dataset (USGS)

NL-CA notification level (CDPH)

NOCO Northern Coast Ranges study unit

NOCO-CO Coastal Basins study area of the Northern Coast Ranges study unit
ix

Abbreviations and Acronyms—Continued

NOCO-IN Interior Basins study area of the Northern Coast Ranges study unit

ns no significant difference 

NWIS National Water Information System (USGS)

p significance level

pmc percent modern carbon

RSD5-US risk-specific dose at a risk factor of 10–5 (USEPA)

SMCL secondary maximum contaminant level

SMCL-CA secondary maximum contaminant level (CDPH)

SMCL-US secondary maximum contaminant level (USEPA)

TDS total dissolved solids

TEAP terminal electron acceptor process

THM trihalomethane

TT-US treatment technique level (USEPA)

TU tritium unit

VOC volatile organic compound

Z test statistic for Wilcoxon test

Organizations

CDPH California Department of Public Health (California Department of Health 

Services prior to July 1, 2007)

CDPR California Department of Pesticide Regulation

CDWR California Department of Water Resources

GAMA Groundwater Ambient Monitoring and Assessment Program (USGS)

LLNL Lawrence Livermore National Laboratory, Livermore, California

NAWQA National Water-Quality Assessment Program (USGS)

SWRCB California State Water Resources Control Board 

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey
x
Status and Understanding of Groundwater Quality in the 

Northern Coast Ranges Study Unit, 2009: California GAMA 

Priority Basin Project

By Timothy M. Mathany and Kenneth Belitz

Abstract

Groundwater quality in the 633-square-mile 

(1,639-square-kilometer) Northern Coast Ranges (NOCO) 

study unit was investigated as part of the Priority Basin 

Project (PBP) of the Groundwater Ambient Monitoring and 

Assessment (GAMA) Program and the U.S. Geological 

Survey (USGS) National Water-Quality Assessment Program. 

The study unit is composed of two study areas (Interior Basins 

and Coastal Basins) and is located in northern California in 

Napa, Sonoma, Lake, Colusa, Mendocino, Glenn, Humboldt, 

and Del Norte Counties. The GAMA-PBP is being conducted 

by the California State Water Resources Control Board in 

collaboration with the USGS and the Lawrence Livermore 

National Laboratory. 

The GAMA NOCO study was designed to provide a 

spatially unbiased assessment of the quality of untreated 

(ambient) groundwater in the primary aquifer system within 

the study unit. The assessment is based on water-quality and 

ancillary data collected in 2009 by the USGS from 58 sites 

and on water-quality data from the California Department of 

Public Health (CDPH) database. The primary aquifer system is 

defined by the perforation intervals of sites listed in the CDPH 

water-quality database for the NOCO study unit. Groundwater 

quality in the primary aquifer system may differ from the 

quality in the shallow or deep water-bearing zones. 

The first component of this study, the status assessment

of the current quality of the groundwater resource, was 

performed by using data from samples analyzed for inorganic 

constituents (such as trace elements and major and minor 

ions), organic constituents (volatile organic compounds and 

pesticides and pesticide degradates), the special-interest 

constituent perchlorate, and microbial indicators. This 

status assessment is intended to characterize the quality of 

groundwater resources in the primary aquifer system of the 

NOCO study unit, not the quality of 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 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 and perchlorate were classified as “high” 

(relative-concentration >1.0), “moderate” (0.1 < relativeconcentration ≤1.0), or “low” (relative-concentration ≤0.1). 

Relative-concentrations of inorganic constituents were 

classified as “high” (relative-concentration >1.0), “moderate” 

(0.5 < relative-concentration ≤1.0), or “low” (relativeconcentration ≤0.5).

Aquifer-scale proportion was used as the primary 

metric in the status assessment for evaluating regional-scale 

groundwater quality. High aquifer-scale proportion was 

defined as the percentage of the area of the primary aquifer 

system with a relative-concentration >1.0 for a particular 

constituent or class of constituents; the percentage is based 

on an aerial rather than a volumetric basis. Moderate and low 

aquifer-scale proportions were defined as the percentage of 

the primary aquifer system with moderate and low relativeconcentrations, 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 NOCO study unit (within 

90 percent confidence intervals).

Inorganic constituents (one or more) with health-based 

benchmarks were detected at high relative-concentrations 

in 10.3 percent and at moderate relative-concentrations in 

13.8 percent of the primary aquifer system. The high aquiferscale proportion of inorganic constituents primarily reflected 

high aquifer-scale proportions of boron (in 8.6 percent of the 

primary aquifer system), arsenic (in 3.4 percent), and barium 

(in 1.7 percent). Inorganic constituents with aesthetic-based 

benchmarks were detected at high relative-concentrations 

in 39.7 percent and at moderate relative-concentrations in 

10.3 percent of the primary aquifer system. The constituents 

present at high relative-concentrations were iron (25.9 percent) 

and manganese (39.7 percent). 
2 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Relative-concentrations of organic constituents with 

health-based benchmarks (one or more) were high in 

0.2 percent, moderate in 1.7 percent, and low in 39.7 percent 

of the primary aquifer system. Organic constituents were not 

detected in 58.4 percent of the primary aquifer system. Of 

the 168 organic constituents analyzed, 11 constituents were 

detected. Two organic constituents had detection frequencies 

>10 percent: the trihalomethane chloroform and the herbicide 

simazine. For the 10 detected organic constituents that had 

health-based benchmarks, nearly all detections had low 

relative-concentrations. The special-interest constituent 

perchlorate was detected at moderate relative-concentrations 

in 1.7 percent and at low relative-concentrations in 

22.4 percent of the primary aquifer system. Perchlorate was 

not detected in 75.9 percent of the primary aquifer system.

The second component of this study, the understanding 

assessment, evaluated relations between constituent 

concentrations and values of selected potential explanatory 

factors to identify the factors potentially affecting the 

concentrations and occurrences of constituents found at high 

relative-concentrations or, for organic constituents, with 

detection frequencies >10 percent. The potential explanatory 

factors evaluated were land use (including density of septic 

tanks and leaking or formerly leaking underground fuel 

tanks), well construction (well depth and depth to the top of 

the perforated interval in the well), hydrologic conditions 

(aridity index, field water temperature, and distance to nearest 

hot spring and geothermal well), pH, dissolved oxygen 

concentration, study area, groundwater age distribution, and 

geochemical conditions. 

High and moderate relative-concentrations of boron 

primarily occurred in the Interior Basins study area and may 

be attributed to groundwater interacting with hydrothermal 

systems. High and moderate relative-concentrations of boron 

were associated with elevated groundwater temperatures, 

groundwater chemistry characteristics similar to those 

of geothermal waters, and distance to known geothermal 

areas. Boron concentrations generally were higher where 

low dissolved oxygen concentrations or anoxic conditions 

exist. High and moderate relative-concentrations of arsenic 

predominantly occur in the Interior Basins study area under 

reducing conditions. Arsenic concentrations also may be 

influenced by hydrothermal systems (when present).

Chloroform, simazine, and perchlorate were observed 

in the Interior Basins and Coastal Basins study areas, 

predominantly at shallow sites with top-of-perforation depths 

≤70 feet below land surface, with modern water (post-1950s), 

and with oxic groundwater conditions. 

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, 

2011, website at http://www.waterboards.ca.gov/water_issues/

programs/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 

(GAMA-PBP), conducted by the USGS (U.S. Geological 

Survey, 2011, California Water Science Center 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 

web-based groundwater information system, developed by the 

SWRCB. On a statewide basis, the GAMA-PBP 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. 

In response to the Groundwater Quality Monitoring 

Act of 2001, the GAMA-PBP was initiated in 2003 to assess 

and monitor the quality of groundwater in California (State 

of California, 2001b). The USGS, in collaboration with the 

SWRCB, designed the GAMA-PBP as a means 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). The GAMA-PBP is a comprehensive assessment 

of statewide groundwater quality designed to improve 

understanding and identification of risks to groundwater 

resources and to increase the availability of information about 

groundwater quality to the public. Additional partners in the 

GAMA-PBP 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). All of these hydrogeologic provinces include 

groundwater basins designated by the CDWR (California 

Department of Water Resources, 2003). The CDWR-defined 

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). The CDPH Drinking Water 

Program, which regulates water quality in public-supply wells, 

was transferred to the SWRCB Division of Drinking Water on 

July 1, 2014; however, the term ‘CDPH sites’ is retained in this 

report for consistency with other GAMA-PBP publications and 

because the CDPH had jurisdiction over public-supply wells at 

the time that samples were collected for this study. These basins 
Introduction 3

Basin and Range

Central

Valley

Klamath

Mountains

Desert

Cascades and

Modoc Plateau

Transverse Ranges and

selected Peninsular Ranges

Southern Coast

Ranges

Sierra

Northern Nevada

Coast

Ranges

San Diego

Drainages

Bakersfield

San

Francisco

Sacramento

OREGON

NEVADA

MEXICO

ARIZONA

Redding

Los Angeles

San Diego

PA C I F I C O C E A N

0 200 MILES

0 200 KILOMETERS

Shaded relief derived from from National Elevation

Dataset (U.S. Geological Survey, 2006) 

Albers Equal-Area Conic Projection

Provinces from Belitz and others, 2003

Northern Coast Ranges,

Coastal Basins 

study area

(figure A1D–F)

Northern Coast Ranges,

Interior Basins

study area

(figure A1A–C)

sac14-0547_Figure 01

Figure 1. Location of the Northern Coast Ranges study unit and the California hydrogeologic provinces (modified from Belitz and 

others, 2003), California GAMA Priority Basin Project.
4 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

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, and the number 

of square-mile sections having registered pesticide applications 

(Belitz and others, 2003). Of the 472 CDWR-designated 

basins, 116 basins contain approximately 95 percent of CDPH 

sites located in CDWR-designated 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 GAMA-PBP study 

units that together represent approximately 95 percent of all 

CDPH sites. The Northern Coast Ranges (NOCO) study unit 

is composed of 34 groundwater basins and subbasins in the 

Northern Coast Ranges hydrogeologic province (fig. 1).

The goal of the GAMA-PBP 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 over time (Kulongoski and Belitz, 2004). The 

assessments are intended to characterize the quality of 

groundwater in 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 and springs 

used for public drinking-water supplies and includes wells 

and springs from systems classified as community (such as 

those in cities, towns, and mobile-home parks), non-transient, 

non-community (such as those in schools, workplaces, and 

restaurants), and transient, non-community (such as those in 

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.

In addition to being selected for study as part of the 

GAMA-PBP, the Northern Coast Ranges (NOCO) study unit 

(fig. 1) was considered a high priority for sampling to complete 

an assessment of groundwater quality in the California Coastal 

Basins Principal Aquifer of the United States (U.S. Geological 

Survey, 2003) by the USGS National Water-Quality Assessment 

(NAWQA) Program (Lapham and others, 2005). As a result, the 

NAWQA Program collaborated with the GAMA-PBP to assess 

groundwater quality in the NOCO study unit.

Purpose and Scope

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

unit description: description of the hydrogeologic setting 

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

of the status of the current (2009) quality of groundwater 

in the primary aquifer system in the NOCO study unit, and 

(3) understanding assessment: identification of the natural and 

human factors affecting groundwater quality and explanation 

of the relations between water quality and selected explanatory 

factors. Assessments are made for chemical constituents only; 

microbiological indicators of groundwater quality are not 

discussed in this report.

The status assessment includes analyses of water-quality 

data for 58 sites selected by the USGS for spatial coverage of 

1 site per grid cell (hereinafter referred to as USGS-GAMA 

grid sites) across the NOCO study unit and water-quality 

data from the CDPH database for samples collected between 

June 1, 2006, and June 1, 2009, at 276 sites. The details of 

sample collection, analysis, and quality-assurance procedures 

for the NOCO study unit and all of the water-quality data 

collected by the USGS are reported by Mathany and others 

(2011). GAMA-PBP status assessments are designed to 

provide a statistically robust characterization of groundwater 

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

(Belitz and others, 2003). 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 are compared to California and Federal regulatory 

and nonregulatory benchmarks for drinking water by using 

relative-concentrations (the ratio of the concentration of a 

constituent in groundwater to the benchmark concentration). 

The assessments in this report are intended to characterize 

the quality of untreated groundwater resources in the primary 

aquifer system within the study unit, not the drinking water 

delivered to consumers by water purveyors. This study does 

not attempt to evaluate the quality of water delivered to 

consumers; after withdrawal from the ground, water typically 

is treated, disinfected, 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 and data for potential explanatory factors from the 58 sites 

sampled by the USGS for the GAMA Program. The potential 

explanatory factors affecting water quality in the primary 

aquifer system evaluated are land use (including density of 

septic tanks and leaking or formerly leaking underground fuel 

tanks), well construction (well depth and depth to the top of the 

perforated interval in the well), hydrologic conditions (aridity 

index, field water temperature, and distance to nearest known 

geothermal reservoir), pH, dissolved oxygen concentration, 

groundwater age distribution, 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. 
Hydrogeologic Setting of the Northern Coast Ranges Study Unit 5

Hydrogeologic Setting of the Northern 

Coast Ranges Study Unit

The NOCO study unit covers approximately 633 square 

miles (mi2

) (1,639 square kilometers; km2) in Napa, Sonoma, 

Lake, Colusa, Mendocino, Glenn, Humboldt, and Del Norte 

Counties in northern California. The NOCO study unit lies 

within the Northern Coast Ranges hydrogeologic province 

(fig. 1; Belitz and others, 2003) and includes 35 groundwater 

basins and subbasins (California Department of Water 

Resources, 2003). For the purpose of this study, these 

35 groundwater basins and subbasins were grouped into 

2 study areas based on location. The groundwater basins and 

subbasins located inland, not adjacent to the Pacific Ocean, 

were aggregated into the Interior Basins study area. The 

groundwater basins and subbasins adjacent to the Pacific 

Ocean were aggregated into the Coastal Basins study area. As 

part of the GAMA-PBP, untreated groundwater samples were 

collected from 58 sites in the NOCO study unit from June 1, 

2009, to October 8, 2009 (Mathany and others, 2011). 

Northern Coast Ranges—Interior Basins 

Study Area

The Interior Basins study area (hereinafter referred to 

as the NOCO-IN study area) is 256 mi2

 in area and contains 

24 CDWR-defined basins (California Department of Water 

Resources, 2004a–w, ii). The NOCO-IN study area is located 

in the Coast Ranges Mountains region of northern California 

stretching approximately 25 to 60 miles (mi) inland of the 

Pacific Ocean and 60 to 130 mi north of San Francisco. The 

study area consists primarily of noncontiguous inland valleys 

whose boundaries are the surrounding hills and (or) mountains. 

In the central part of the study area, some of the inland valleys 

share Clear Lake or other lakes as a border (fig. 2B). Landsurface altitudes in the study area range from about 475 feet 

above mean sea level (ft above msl) near the town of Hopland, 

to over 4,200 ft above msl on Mount Konocti, located just east 

of the town of Kelseyville (fig. A1B). 

In the NOCO-IN study area, the climate is classified as 

Mediterranean, with warm to hot, dry summers and cold, wet 

winters (National Oceanic and Atmospheric Administration, 

2011). Most precipitation in the study area occurs in the fall 

and winter months, with average annual precipitation ranging 

from about 22 inches (in.) near the town of Stonyford to more 

than 65 in. near the town of Laytonville (fig. A1A) (California 

Department of Water Resources, 2004i, r; U.S. Department of 

Commerce, 2011).

The main surface drainage features of the study area are 

the Eel, Russian, and Navarro Rivers and their tributaries, 

all of which have their headwaters outside of the study area 

and terminate in the Pacific Ocean (figs. A1A–A1C). Large 

creeks (Outlet, Mill, Stoney, Scotts, St. Helena, and Pope) and 

numerous small creeks drain the valleys of the study area.

The primary aquifer system in the study area is in 

Quaternary alluvial groundwater basins made up of sand, silt, 

gravel, and clay eroded from the surrounding hills. These 

deposits interfinger with and grade into alluvial fan and terrace 

deposits along the sides of the valleys, and into older, more 

consolidated alluvium at depth, and in some valleys, these 

deposits grade into finer-grained lake deposits towards the center 

of the basins. Groundwater conditions are mostly unconfined, 

with some confined areas towards the center of valleys and 

at depth. The major rock types surrounding the alluvial 

valleys are the Jurassic-Cretaceous Franciscan Formation 

(mudstone, greywacke sandstones, and chert) and ophiolitic and 

metamorphosed volcanic rocks (Muir and Webster, 1977; Farrar, 

1986; California Department of Water Resources, 2004e–w). 

In groundwater basins near Clear Lake, groundwater is also 

found in Quaternary volcanic flow rocks and thin volcanic ash 

layers/lenses interbedded with low-permeability sediments 

(Soil Mechanics and Foundation Engineers, Inc., 1967; Earth 

Sciences Associates, 1978) (fig. 3B). 

The general direction of groundwater flow in the study 

area is from areas of high topographic relief to the center 

of the valleys (areas of low topographic relief), following 

the direction of surface-water features. The study area has 

several northwest trending faults and fault zones, which act 

as hydrologic barriers to groundwater movement (California 

Department of Water Resources, 2004a–w; fig. 3C).

Groundwater recharge in the study area occurs from a 

mixture of ambient sources, including direct percolation of 

precipitation and irrigation waters, infiltration of runoff from 

surrounding hills/areas, and seepage from rivers and creeks 

(California Department of Water Resources, 2004a–w).

Most of the central and southern parts of the NOCO-IN 

study area are located within the boundaries of the 

Geysers–Clear Lake area (fig. 3C), known to be an active 

geothermal region of northern California (Goff and others, 

1993; Hodgson, 2003; California Department of Water 

Resources, 2004a–d; U.S. Geological Survey, 2004; California 

Department of Conservation, 2013). The Geysers–Clear 

Lake area is characterized by recent volcanism (late-Pliocene 

to early Holocene), high heat flux, and high geothermal 

gradients that are enhanced locally by fault-controlled zones 

of convective heat (geothermal fluid) transport (Wood and 

Kienle, 1992; Stimac and others, 1997; Erkan and others, 

2005; Smithsonian Institution, National Museum of Natural 

History, Global Volcanism Program, 2013). Hydrothermal 

systems (rather than one large underlying geothermal 

reservoir) are known to influence the groundwater within the 

Geysers–Clear Lake area (Goff and others, 1993). 

Three geothermal water types have been identified 

within the Geysers–Clear Lake area: thermal meteoric, steam 

condensate, and connate/metamorphic (Donnelly-Nolan and 

others, 1993; Goff and others, 1993; Peters, 1993). Thermal 

meteoric water is most commonly found near the main mass 

of the Clear Lake volcanic field and issues from Quaternary 

volcanic rocks. These waters appear to be a mixture of highertemperature geothermal water that has resided at depth for 
6 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

299

101

101

199

HUMBOLDT CO

DEL NORTE CO

Crescent City

Eureka

Arcata

Fortuna

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

20

20

128

128

29

1

1

101

101

Ukiah

Covelo

Lakeport

Fort Bragg

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Clear

Lake

sac14-0547_Figure 02ab

A A

B

B

EXPLANATION

NOCO-IN study area

NOCO-CO study area

Cities

Counties

0 10 205 KILOMETERS

0 10 20 5 MILES

Figure 2. Location of the (A) Coastal Basins (NOCO-CO) and (B) Interior Basins (NOCO-IN) study areas, major cities and towns, major 

roads, and hydrologic features in the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
Introduction 7

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Clear

Lake

sac14-0547_Figure 03ab

A A

B

C

B

EXPLANATION

NOCO study unit

0 10 205 KILOMETERS

0 10 20 5 MILES

Franciscan complex

Plio-Pleistocene sediment

Quaternary alluvium

Quaternary other sediment

Quarternary, mafic volcanics

Pyroclastic volcanics

Tertiary, mafic volcanics

Tertiary nonmarine sediment

Tertiary marine sediment

Granitic rocks

Metamorphic other

Metasediment

Ultramafic/mafic

Fault

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Figure 3. Geologic formations and locations of the (A) Coastal Basins study area, (B) and (C) Interior Basins study area, locations of 

hot springs and geothermal wells, and approximate boundaries of the Napa and Sonoma Valleys and the Geysers Steam Field, Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
8 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

C

 Geysers

steam field

Geysers-Clear

Lake Area

Calistoga

Aetna

Springs

Soda Spring

Cooks Spring

Vichy

Springs

Walter

Springs

Ornbaun

Springs

Napa and

Sonoma

Valleys

Deadhot

Springs

Orrs Hot Spring

Unnamed

Location

Salt Spring No.2

Baker Soda

Spring

One-Shot

Mining Co.

Crabtree

Hotsprings

Pinches Spring

Point Arena

Hot Spring

Wilbur

Hot Springs

Area

sac14-0547_Figure 03c

123°30’ 123°15’ 123° 122°45’ 122°30’

39°

45’

39°

30’

39°

15’

39°

38°

45’

EXPLANATION

Geothermal well

Hot spring 

NOCO study unit

Fault

Lakes

Franciscan complex

Plio-Pleistocene sediment

Quaternary alluvium

Quaternary other sediment

Quarternary, mafic volcanics

Pyroclastic volcanics

Tertiary, mafic volcanics

Tertiary marine sediment

Metamorphic other

Metasediment

Ultramafic/mafic

0 5 10 20 MILES

0 10 20 5 KILOMETERS

Geology from Saucedo and others, 2000

Clear

Lake

Figure 3. —Continued
Hydrogeologic Setting of the Northern Coast Ranges Study Unit 9

relatively short time periods and a cooler, near-surface meteoric 

water. Steam condensate waters are most commonly found near 

the Geysers steam field along the southwestern portion of the 

Geysers–Clear Lake area (fig. 3C). These waters are a mixture of 

groundwater, condensed steam from an underlying hydrothermal 

system, and heated groundwater. Connate and metamorphic (a 

subclass of connate) waters are commonly found in the eastern 

reaches of the Geysers–Clear Lake area. Connate waters 

typically issue from rocks of the Great Valley sequence and 

are most common in the eastern Clear Lake region, whereas 

metamorphic waters typically issue from rocks of the Franciscan 

Formation near the main Clear Lake volcanic field. These three 

geothermal water types are unique in distribution and origin, 

but they share common chemical signatures of hydrothermal 

activity—near-neutral pH and elevated concentrations of boron, 

bromide, arsenic, and lithium (Donnelly-Nolan and others, 1993; 

Goff and others, 1993; Peters, 1993). 

The NOCO-IN study area is just north of of the Napa 

and Sonoma Valleys (fig. 3C), a hydrothermally active area 

with similar Tertiary to Holocene age volcanic processes as 

in the Geysers–Clear Lake area (U.S. Geological Survey, 

2004). Similar to the Geysers–Clear Lake area, the Napa and 

Sonoma Valleys are characterized by localized hydrothermal 

systems associated with fault zones, high geothermal 

gradients, and high heat flux (Kulongoski and others, 2010). 

A study by Forrest and others (2013) used USGS-GAMA data 

from the Napa and Sonoma Valleys (North San Francisco 

Bay study unit: Kulongoski and others, 2006) to determine 

which constituents were most indicative of hydrothermal 

contamination of public supply wells. The study identified 

water temperature, concentrations of boron, arsenic, lithium, 

and chloride, and helium isotope ratios as the constituents 

that were most useful in evaluating the contribution of the 

hydrothermal system to the public supply wells. 

Northern Coast Ranges—Coastal Basins 

Study Area

The Coastal Basins study area (hereinafter referred 

to as the NOCO-CO study area) is 377 mi2

 in area and 

contains 11 CDWR-defined basins and subbasins (California 

Department of Water Resources, 2004x–hh). The study area 

is located along the northern California coast beginning 

north of Point Arena and extending to the Oregon border 

(figs. A1D–A1F). The study area has three distinct sections 

(northern, central, and southern), each bordered on the west 

by the Pacific Ocean and on the north, east, and south by the 

hills surrounding the coastal valleys (fig. 2A). Land-surface 

altitudes in the study area range from sea level where the study 

area boundary touches the Pacific Ocean, to approximately 

500 ft above msl in the hills above the city of Fortuna (fig. 2). 

In the NOCO-CO study area, the climate is classified as 

coastal (National Oceanic and Atmospheric Administration, 

2011), with cool to mild summers and cold, wet winters. 

Coastal fog and low clouds are common throughout the year. 

Average annual precipitation in the study area ranges from 

about 38 in. near the town of Trinidad to about 79 in. near 

the town of Klamath (figs. A1D, A1E; U.S. Department of 

Commerce, 2011).

The major surface drainage features of the study area are 

the Smith, Klamath, Mad, Eel, Noyo, and Big Rivers and their 

tributaries, all of which have their headwaters outside of the 

study area and terminate in the Pacific Ocean (figs. A1D–A1F).

The primary aquifer system in the northern part of 

the study area principally occurs in the Smith River Plain, 

a marine terrace made up of Holocene alluvial fan and 

floodplain deposits; in the Pleistocene terrace deposits; and in 

the Pleistocene Battery Formation (California Department of 

Water Resources, 1987, 2004x). The Smith River Plain and 

the Pleistocene terrace deposits are included in Quaternary 

alluvium and Pleistocene-Pliocene nonmarine deposits, and 

the Pleistocene Battery Formation is mapped as Tertiary 

marine sediment (fig. 3A). In the central part of the study 

area, the primary aquifer system occurs in groundwater basins 

consisting of alluvial deposits associated with drowned river 

mouths of the Klamath, Mad, and Eel Rivers. The alluvial 

deposits consist of Holocene alluvium, dune sand, the 

Pleistocene Hookton Formation, and the deeper PliocenePleistocene Carlotta Formation (Johnson, 1978; California 

Department of Water Resources, 2004y–dd). The primary 

aquifer system in the southern part of the study area is in the 

Fort Bragg Terrace deposits. These deposits are discontinuous, 

uplifted, and dissected Pleistocene marine terraces along 

the Pacific Ocean. The terrace deposits consist of Tertiary 

marine sediment, dune sand, and semi-consolidated clay, silt, 

sand, and gravel derived from adjacent formations (largely 

the Franciscan complex) that are up to 150 feet (ft) thick 

(California Department of Water Resources, Northern District, 

1982; California Department of Water Resources, 2004ff–gg). 

The general direction of groundwater-flow in the study 

area is from east to west towards the Pacific Ocean. In the 

northern part of the study area, dune sand accumulation has 

created Lake Earl, which acts as a restrictive structure to 

groundwater movement (fig. A1D). In the central and southern 

parts of the study area, several northwest trending faults and 

fault zones act as hydrologic barriers (California Department 

of Water Resources, 2004x–gg; fig. 3A).

Groundwater recharge in the study area comes from 

a mixture of ambient sources including direct percolation 

of precipitation and irrigation waters, infiltration of runoff 

from surrounding hills/areas, seepage from rivers and creeks, 

and subsurface inflow (from non-alluvial geologic units that 

underlie the alluvial basins) (California Department of Water 

Resources, 2004x–gg).

The groundwater basins in the northern and central parts 

of the study area are in hydraulic connection with the Pacific 

Ocean, and seawater extends landward as a wedge underneath 

fresh groundwater in some of the basins. In the southern part of 

the study area, the uplifted terrace deposits prevent hydraulic 

connection between groundwater basins and the Pacific Ocean 

(California Department of Water Resources, 2004x–gg).
10 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Methods

This section describes the methods used for the status 

assessment and understanding assessment for water quality in 

the NOCO study unit. Methods used for compiling data for the 

potential explanatory factors are described in appendix B.

Status Assessment

The status assessment provides a spatially unbiased 

assessment of groundwater quality in the primary aquifer 

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

assessment included (1) assembling water-quality benchmarks 

and calculating relative-concentrations, (2) assembling 

datasets for use in the status assessment, (3) selecting 

constituents for additional evaluation, and (4) calculating 

aquifer-scale proportions for these constituents. 

Relative-Concentrations and Water-Quality 

Benchmarks

To provide context for the groundwater-quality data, 

concentrations of constituents measured in the untreated 

groundwater were compared to benchmarks established 

by the U.S. Environmental Protection Agency (USEPA) 

and CDPH for evaluation of the quality of drinking water 

(U.S. Environmental Protection Agency, 2008, 2009a, b, 2012; 

California Department of Public Health, 2006, 2008, 2010). 

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) and action 

levels (AL-US).

2. Nonregulatory, aesthetic-based 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. Nonregulatory, health-based CDPH notification levels 

(NL-CA), USEPA lifetime health advisory levels 

(HAL-US), and USEPA risk-specific doses for a risk of 

1 in 100,000 (RSD5-US). Risk-specific doses for 1 in 

100,000 (1 in 105

) were calculated by dividing USEPA 

values for estimated excess lifetime cancer risk from 

drinking water of 1 in 104

 by 10. 

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 is provided by Mathany and others (2011).

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

in groundwater relative to regulatory and nonregulatory 

benchmarks used to evaluate drinking-water quality:

Relative-concentration= Sample concentration

Benchmark concentration . (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 four microbial indicators analyzed in samples 

from the NOCO study unit, total coliforms, Escherichia 

coli (E. coli), and coliphage (somatic and f-specific), have 

water-quality benchmarks, but are not included in the status 

and understanding assessments because the results will be 

presented in 1 report for all 25 GAMA-PBP 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.

For ease of discussion, relative-concentrations of 

constituents were classified into low, moderate, and high 

categories:

[Abbreviations: >, less than; ≤, greater than or equal to]

Category

Relative-concentrations 

for organic and specialinterest constituents

Relative-concentrations 

for inorganic constituents

High >1 >1

Moderate >0.1 and ≤1 >0.5 and ≤1

Low ≤0.1 ≤0.5

For organic and special-interest constituents, a relativeconcentration 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, which tend to be more 

prevalent than organic constituents in groundwater (Toccalino 

and others, 2010), a relative-concentration of 0.5 was used as 

a threshold to distinguish between low and moderate relativeconcentrations. The primary reason for using a higher threshold 
Methods 11

for inorganic constituents was to focus attention on those 

inorganic constituents that are of most immediate concern 

(Fram and Belitz, 2012). 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 and objective criteria for distinguishing constituents 

at moderate rather than low concentrations.

Datasets Used for Status Assessment

Two datasets were used in the status assessments: 

(1) data from USGS-GAMA grid sites and (2) data combined 

from USGS-GAMA grid sites and CDPH sites. This section 

explains how each dataset was assembled. Comparisons of 

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

USGS-GAMA Grid Sites

The grid-based calculations of aquifer-scale proportions 

used data from 58 sites sampled by the USGS for spatial 

coverage of one well per grid cell across the study unit (grid 

sites). Detailed descriptions of the methods used to identify 

sites for sampling are given in Mathany and others (2011). 

Briefly, each study area was divided into equal-area grid 

cells (Interior Basins, 8.5-mi2

 [22.0-km2] cells and Coastal 

Basins, 12.5-mi2

 [32.4-km2] cells), and in each cell, one site 

was randomly selected to represent the cell (Scott, 1990) 

(figs. 4, A1A–A1F). Sites were selected from those in the 

statewide database of public-supply wells maintained by the 

CDPH. If a cell had no accessible sites listed in the CDPH 

water-quality database, then appropriate sites were selected 

from the USGS Groundwater Site Inventory (GWSI) database. 

The NOCO study unit contained 60 grid cells, and the USGS 

sampled sites in 58 of those cells. Of the 58 USGS-GAMA 

grid sites, 31 were listed in the CDPH water-quality database, 

and 27 were non-CDPH sites perforated at depths similar to 

the depths of CDPH sites in their respective cells. One of the 

USGS-GAMA grid sites that was listed in the CDPH database 

was a spring. USGS-GAMA grid sites were named with an 

alphanumeric GAMA-ID consisting of a prefix identifying 

the study area and a number indicating the order of sample 

collection (figs. A1A–A1F). The following prefixes were used 

to identify the study area: NOCO-IN (Interior Basins study 

area) and NOCO-CO (Coastal Basins study area).

Samples collected from USGS-GAMA grid sites were 

analyzed for 234 constituents (table 1). The collection, analysis, 

and quality-control data for the constituents listed in table 1 are 

described by Mathany and others (2011). Because samples from 

all USGS-GAMA grid sites were analyzed for the full suite of 

constituents, it was not necessary to supplement the grid site 

dataset with data from the CDPH database, as was done in 

the status assessments in many other GAMA-PBP study units 

(Landon and others, 2010; Burton and others, 2011; Kulongoski 

and Belitz, 2011). The two grid cells without USGS-GAMA 

grid sites had no CDPH sites with water-quality data for the 

3-year interval June 1, 2006, through June 1, 2009.

Additional Data Used for Spatially Weighted Calculation

The spatially weighted calculations of aquifer-scale 

proportions of relative-concentrations used data from the 

58 USGS-GAMA grid sites and from the 276 sites in the 

CDPH water-quality database having water-quality data during 

the 3-year interval June 1, 2006, through June 1, 2009. For the 

27 sites with USGS-GAMA and CDPH data, only the USGSGAMA data were used. Many of the 249 sites having only 

CDPH data had data for a limited number of constituents. For 

example, 162 sites had data for nitrate, but only 72 sites had 

data for at least 1 trace element. Water-quality data collected 

by the CDPH are available from the SWRCB’s publicallyaccessible Internet database GeoTracker GAMA (California 

State Water Resources Control Board, 2009, website at https://

geotracker.waterboards.ca.gov/gama/). 

Table 1. Constituent classes and numbers of constituents 

analyzed for the 58 sites sampled, Northern Coast Ranges study 

unit, 2009, California GAMA Priority Basin Project.

[GAMA, Groundwater Ambient Monitoring and Assessment Program]

Constituent class Number of 

constituents1

Inorganic constituents

Trace elements 23

Major and minor ions, alkalinity, specific 

conductance, and total dissolved solids

13

Nutrients and dissolved organic carbon 6

Uranium and other radioactive constituents2 7

Organic constituents

Volatile organic compounds 85

Pesticides and pesticide degradates 83

Special-interest constituent

Perchlorate 1

Geochemical and age-dating tracers

Dissolved oxygen, pH, temperature, and turbidity 4

Tritium 1

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

He/4He of helium, and tritium

7

δ2

H and δ18O of water 2

Carbon-14 and δ13C of dissolved carbonates 2

Sum 234

1

All sites also were analyzed for 12 pharmaceutical compounds and 

4 microbial indicators. Assessment results for these constituents are not being 

presented for individual study units, therefore, they are not included in the 

count of constituents. A statewide synthesis of GAMA Priority Basin Project 

results for pharmaceuticals was presented by Fram and Belitz (2011), and a 

synthesis of results for microbial indicators will be presented at a later date 

(Carmen Burton, U.S. Geological Survey California Water Science Center, 

written commun., 2013).

2

Activities of radon-222, radium, gross alpha and gross beta particles, 

lead-210, and polonium-210 and uranium concentrations were measured. 

Gross alpha and gross beta particle activities were measured after 72-hour 

and 30-day holding times; data from the 30-day measurement are used in 

this report. Radium activity equals the sum of the two isotopes measured: 

radium-226 and radium-228.
12 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

299

101

101

199

HUMBOLDT CO

DEL NORTE CO

Crescent City

Eureka

Arcata

Fortuna

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

20

20

128

128

29

1

1

101

101

Ukiah

Covelo

Lakeport

Fort Bragg

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

sac14-0547_Figure 04ab

A A

B

B

EXPLANATION

NOCO-IN study area

NOCO-CO study area

Cities

Counties

0 10 205 KILOMETERS

0 10 20 5 MILES

USGS grid sites

CDPH site

Figure 4. Locations of study area grid cells, USGS-GAMA grid sites, and CDPH sites, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, Coastal Basins study area]
Methods 13

Selection of Constituents for Additional 

Evaluation in the Status Assessment

As many as 234 constituents were analyzed by USGSGAMA in samples from sites in the NOCO study unit as part 

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

these constituents were identified for additional evaluation in 

this report. Of the 238 constituents analyzed, 114 constituents 

did not have benchmarks (table 2). Because relativeconcentrations cannot be calculated for constituents without 

benchmarks, these 114 constituents were not evaluated in this 

report. The 126 constituents having benchmarks were assessed, 

Table 2. Numbers of constituents analyzed and detected in each constituent class with each type of benchmark, Northern Coast 

Ranges study unit, 2009, California GAMA Priority Basin Project.

[GAMA, Groundwater Ambient Monitoring and Assessment Program]

Benchmark type

Groups of inorganic constituents Sum of inorganic 

constituents Trace elements and 

major and minor ions Nutrients Uranium and other radioactive constituents

Number of constituents

Analyzed Detected Analyzed Detected Analyzed Detected Analyzed Detected

Regulatory, health-based 14 14 2 2 5 5 21 21

Nonregulatory, health-based 4 4 1 1 0 0 5 5

Nonregulatory, aesthetic-based 8 8 0 0 0 0 8 8

None 10 10 3 3 2 2 15 15

Total: 36 36 6 6 7 7 49 49

Benchmark type

Groups of organic constituents Sum of organic 

constituents Volatile organic 

compounds

Pesticides and 

pesticide degradates

Number of constituents

Analyzed Detected Analyzed Detected Analyzed Detected

Regulatory, health-based 33 7 6 2 39 9

Nonregulatory, health-based 26 1 18 0 44 1

Nonregulatory, aesthetic-based 0 0 0 0 0 0

None 26 0 59 1 85 1

Total: 85 8 83 3 168 11

Benchmark type

Other constituent groups

Geochemical and 

age-dating tracers

Special-interest 

constituent

Number of constituents

Analyzed Detected Analyzed Detected

Regulatory, health-based 1 1 1 1

Nonregulatory, health-based 0 0 0 0

Nonregulatory, aesthetic-based 1 1 0 0

None 14 14 0 0

Total: 16 16 1 1

Benchmark type

Sum of all constituents

Number of constituents

Analyzed Detected

Regulatory, health-based 62 32

Nonregulatory, health-based 49 6

Nonregulatory, aesthetic-based 9 9

None 114 30

Total: 234 77
14 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

and a subset of these constituents was selected for additional 

evaluation (table 3) on the basis of the following two criteria:

• Constituents present at high or moderate relativeconcentrations at the USGS-GAMA grid sites or in the 

CDPH water-quality database for any sample collected 

between June 1, 2006, and June 1, 2009;

• Organic constituents with detection frequencies of 

greater than 10 percent in the USGS-GAMA grid site 

dataset for the study unit.

The USGS conducted a review of the CDPH waterquality database (January 1, 1976, to May 31, 2006) to 

identify constituents with high relative-concentrations 

historically, but not currently. Constituent concentrations 

may be 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 in the status assessment 

are not considered representative of potential groundwaterquality concerns in the study unit from 2006 to 2009. 

For the NOCO study unit, nine constituents had high 

relative-concentrations reported in the CDPH database during 

the historical period, but did not also have high concentrations 

reported during the current period or in the USGS-GAMA 

dataset (table 4). 

Table 3. Constituents selected for additional evaluation in the status assessment, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project.

[Benchmark type: Regulatory, health-based benchmarks: MCL-US, USEPA maximum contaminant level; MCL-CA, CDPH maximum contaminant level. 

Nonregulatory, health-based benchmarks: NL-CA, CDPH notification level. Nonregulatory, aesthetic-based benchmarks: SMCL-CA, CDPH secondary 

maximum contaminant level. Benchmark units: μg/L, micrograms per liter; mg/L, milligrams per liter. 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; TDS, total dissolved solids; MTBE, methyl tert-butyl ether]

Constituent class Typical use or source

Benchmark Criteria for 

selection 

for status 

assessment

Selected for 

understanding 

Type assessment 1 Value Units

Inorganic constituents with health-based benchmarks

Trace elements

Arsenic Naturally occuring MCL-US 10 μg/L Concentration Yes

Barium Naturally occuring MCL-CA 1,000 μg/L Concentration No

Boron Naturally occuring NL-CA 1,000 μg/L Concentration Yes

Nickel Naturally occuring MCL-CA 100 μg/L Concentration No

Nutrients

Nitrate (as nitrogen) Fertilizer, human and animal 

waste, naturally occuring

MCL-US 10 mg/L Concentration No

Inorganic constituents with aesthetic-based benchmarks

Iron Naturally occuring SMCL-CA 300 μg/L Concentration Yes

Manganese Naturally occuring SMCL-CA 50 μg/L Concentration Yes

TDS Naturally occuring SMCL-CA 1,000 mg/L Concentration No

Organic constituents with health-based benchmarks

Volatile organic compounds

Chloroform (Trichloromethane) Disinfection byproduct, 

trihalomethane

MCL-US 2

80 μg/L Concentration, 

frequency

Yes

Vinyl chloride (Chloroethene) Organic synthesis reagent MCL-CA 0.5 μg/L Concentration No

MTBE Gasoline oxygenate MCL-CA 13 μg/L Concentration3 No

Pesticides and pesticide degradates

Simazine Herbicide MCL-US 4 μg/L Frequency Yes

Special-interest constituent with health-based benchmark

Perchlorate Naturally occuring, rocket fuel, 

fireworks, fertilizer

MCL-CA 6 μg/L Concentration, 

frequency

Yes

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, NL-CA, and SMCL-CA: California Department of Public Health (2006, 2008, 2010)

MCL-US: U.S. Environmental Protection Agency (2008, 2009a, 2009b, 2012).

2

Benchmark value is the sum of four trihalomethanes (chloroform, bromodichloromethane, dibromochloromethane, and bromoform).

3

High values were found in the CDPH database during the current period of study. MTBE was detected only at low relative-concentrations by USGS-GAMA.
Methods 15

Table 4. Constituents reported at concentrations greater than benchmarks historically (January 1, 1976 to May 31, 2006) in the 

California Department of Public Health database, but not during the 3-year time period used in the status assessment, Northern Coast 

Ranges study unit, California GAMA Priority Basin Project.

[Benchmark type: Regulatory, health-based benchmarks: MCL-US, USEPA maximum contaminant level; AL-US, USEPA action level; RSD5-US, USEPA 

risk-specific dose at a risk factor of 10–5; MCL-CA, CDPH maximum contaminant level. Nonregulatory, aesthetic-based benchmark: SMCL-CA, CDPH 

secondary maximum contaminant level. Benchmark units: μg/L, micrograms per liter; mg/L, milligrams per liter. 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; TTHM, total trihalomethanes]

Constituent class Typical use or source

Benchmark Number of 

sites with 

historical 

data

Number of 

sites with a 

high value

Date of most 

recent high 

value Type1 Value Units

Inorganic constituents

Aluminum Naturally occuring MCL-CA 1,000 μg/L 348 2 07/22/2002

Copper Naturally occuring AL-US 1,300 μg/L 358 1 10/22/2002

Chloride Naturally occuring SMCL-CA 500 mg/L 363 1 02/18/2004

Fluoride Naturally occuring MCL-CA 2 μg/L 462 1 11/25/2003

Lead Naturally occuring AL-US 15 μg/L 330 10 10/08/2003

Organic constituents

Aldrin2 Insecticide RSD5-US 0.02 μg/L 104 1 04/04/1978

Di(2-ethylhexyl)phthalate2 Plasticizer MCL-CA 4 μg/L 49 2 09/04/1992

Lindane2 Insecticide MCL-US 0.2 μg/L 185 1 04/03/1990

TTHMs Disinfection byproduct MCL-US3 80 μg/L 373 1 06/01/1988

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 and SMCL-CA: California Department of Public Health (2006, 2008, 2010)

MCL-US, AL-US, and RSD5-US: U.S. Environmental Protection Agency (2008, 2009a, 2009b, 2012).

2

Constituent not analyzed by USGS-GAMA in the Northern Coast Ranges study unit.

3

MCL-US benchmark for TTHMs is for the sum of chloroform, bromodichloromethane, dibromochloromethane, and bromoform.

Calculation of Aquifer-Scale Proportions

The status assessment is intended to characterize the 

quality of groundwater resources in the primary aquifer 

system of the NOCO study unit. The primary aquifer system 

is defined by the depth intervals over which wells listed in the 

CDPH database are screened or perforated; these wells are 

primarily classified as municipal and community drinkingwater supply wells. The use of the term “primary aquifer 

system” does not imply that a discrete aquifer unit exists. 

In most groundwater basins, municipal and community 

supply wells generally are perforated at greater depths than 

domestic wells. However, to the extent that domestic wells are 

perforated over the same depth intervals as the CDPH wells, 

the assessments presented in this report also may be applicable 

to the portions of the aquifer system used for domestic 

drinking-water supplies.

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 NOCO study unit with high, moderate, and low relativeconcentrations of constituents relative to benchmarks. Aquiferscale proportions are defined as the percentage of the area 

(rather than the volume) of the primary aquifer systems with 

high, moderate, and low relative-concentrations. 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. For 

constituents with human-health benchmarks, the classes 

included trace elements, nutrients, radioactive constituents, 

volatile organic compounds, and pesticides. 

Both statistical approaches use equal-area grids. The 

grid-cell sizes in the two study areas of the NOCO study 

unit were not the same; therefore, aquifer-scale proportions 

were calculated separately for the two study areas and then 

combined on an area-weighted basis to obtain aquifer-scale 

proportions for the study unit as a whole (Bennett and others, 

2010; Fram and Belitz, 2012): 

PSU=ƩPSA FSA, (2)

where: 

PSU is the aquifer-scale proportion for the 

study unit,

PSA is the aquifer-scale proportion for a study 

area, and

FSA is the fraction of the total study unit area 

occupied by the study area.
16 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Aquifer-scale proportions for individual constituents and 

constituent classes in the NOCO-CO and NOCO-IN study areas 

are presented in appendix C (tables C1, C2); results for the study 

unit as a whole are presented in the main body of the report.

The grid-based calculation uses the USGS-GAMA 

grid-well dataset. For each constituent, the high aquiferscale proportion was calculated by dividing the number of 

cells represented by a high relative-concentration for that 

constituent by the total number of grid cells with data for that 

constituent. The moderate and low aquifer-scale proportions 

were calculated similarly. Confidence intervals for the 

high aquifer-scale proportions for individual constituents 

were computed using the Jeffrey’s 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 relativeconcentrations for any of the constituents in that class were 

high. Cells were considered moderate if values for any of the 

constituents were moderate, but no values were high. The 

grid-based estimate is spatially unbiased. However, the gridbased approach may not detect constituents that are present at 

high concentrations in small proportions of the primary aquifer 

systems. 

The spatially weighted calculation uses the dataset 

assembled from the USGS-GAMA grid sites and data 

compiled in the CDPH database for samples collected between 

June 1, 2006, and June 1, 2009 (the most recent analysis was 

used for each constituent at each well). For each constituent, 

the high aquifer-scale proportion was calculated by computing 

the proportion of sites with 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. 

Confidence intervals for spatially weighted detection 

frequencies of high concentrations are not described in this 

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

class of constituents, the aquifer-scale proportions for sites 

were considered high if the relative-concentrations for any 

of the constituents in that class were high. Aquifer-scale 

proportions for sites were considered moderate if the relativeconcentrations for any of the constituents were moderate, but 

none were high.

In addition, for each constituent, the raw detection 

frequencies of high and moderate values 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 database are not uniformly distributed 

throughout the NOCO study unit (fig. 4). 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. 

Aquifer-scale proportions discussed in this report were 

estimated primarily by using the grid-based approach and 

secondarily by using the spatially weighted approach. The 

grid-based aquifer-scale proportions were used unless the 

spatially weighted proportions were significantly different. 

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, then the 

spatially weighted proportion was used.

The grid-based moderate and low proportions were used 

in most cases because the reporting levels for many organic 

constituents and some inorganic constituents in the CDPH 

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

The understanding assessment is designed to evaluate 

natural and anthropogenic factors that may affect groundwater 

quality. A finite set of potential explanatory factors was 

considered: study area, land use, well depth, depth to the top of 

well casing perforation (top of perforation), density of septic 

tanks, density of leaking (or formerly leaking) underground 

fuel tanks (LUFTs), aridity index, groundwater age, oxidationreduction condition (redox), field water temperature, distance 

to nearest hot spring listed in the USGS Mineral Resources 

Data System (MRDS), distance to nearest geothermal well 

listed in the California Department of Conservation Division 

of Oil, Gas, and Geothermal Resources (DOGGR) database, 

dissolved oxygen concentration, and pH. Statistical tests 

were used to identify significant correlations between the 

constituents of interest and these potential explanatory factors. 

A subset of the constituents examined in the status 

assessment and selected classes of constituents were examined 

in the understanding assessment: 

• Constituents with high aquifer-scale proportions 

of greater than 2 percent. These constituents were 

selected to focus the understanding assessment on 

those constituents that may have the greatest effect on 

groundwater quality. 

• Classes of organic constituents and special-interest 

constituents detected in 10 percent or more of the 

USGS-GAMA grid sites, regardless of concentration. 
Potential Explanatory Factors 17

The understanding assessment was based on the 58 grid 

sites sampled by USGS-GAMA. CDPH sites were not used 

because data for many of the potential explanatory factors 

were not available. In particular, data for age-dating tracers, 

dissolved oxygen, well depth, and depth to the top of screened 

interval are not maintained in the CDPH database.

Statistical Analysis

Nonparametric statistical methods were used to test the 

significance of correlations among water-quality variables 

and potential explanatory variables. Nonparametric statistics 

are robust techniques that are generally not affected by 

outliers and do not require that the data follow any particular 

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

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

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

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

Two different statistical tests were used because the 

set of potential explanatory factors included categorical and 

continuous variables. Correlations among continuous variables 

(land use, septic tank density, LUFT density, well depth, depth 

to top-of-perforations, dissolved oxygen concentration, pH, 

field water temperature, aridity index, and distance to the 

nearest hot spring listed in the USGS MRDS and geothermal 

well listed in the DOGGR database) were investigated 

by using Spearman’s method to calculate the rank-order 

correlation coefficients (ρ) among continuous variables. 

The values of ρ can range from +1.0 (perfect positive 

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

negative correlation). For potential explanatory factors that 

were classified into categories (study area, groundwater age, 

geochemical conditions, and well depth class), the values 

of water-quality parameters between the categories were 

compared by using the Wilcoxon rank-sum test. The Wilcoxon 

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

independent data groups (categories) to determine whether 

one group contains larger values than the other (Helsel and 

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

observations of the two independent data groups being tested. 

All statistical analyses were done using TIBCO Spotfire S+®

8.1 for Windows (TIBCO Software Inc., 2008).

Potential Explanatory Factors 

Brief descriptions of potential explanatory factors (land 

use, well construction, hydrologic conditions, groundwater 

age, and geochemical conditions) are given in this section. 

Correlations among these potential explanatory factors that 

could affect apparent relations between potential explanatory 

factors and water quality also are described. The data 

sources and methods used for assigning values for potential 

explanatory factors are described in appendix B.

Land Use

Land use was quantified as the percentages of three 

land-use types: agricultural, urban, and natural. Land-use 

percentages were calculated for the study unit, the study areas, 

and within a radius of 500 meters (m) (500-m buffers) around 

sites (Johnson and Belitz, 2009). 

In the NOCO study unit, natural lands are mostly 

grasslands, wetlands, beaches, and forests, and the primary 

use of agricultural land is for pasture (cattle, sheep, and poultry), 

row crops, hay, vineyards, and timberlands (Nakagaki and others, 

2007). The largest urban areas are the cities of Crescent City, 

Arcata, Eureka, Fort Bragg, Willits, Ukiah, and Lakeport (fig. 5). 

Land use based on all of the land within the NOCO 

study unit was 60 percent natural, 29 percent agricultural, 

and 11 percent urban (fig. 6A). Compared to the land use in 

the entire study unit, the average land use in 500-m buffer 

areas around the CDPH sites was less natural (56 percent), 

less agricultural (19 percent), and more urban (25 percent). 

The average land use in the 500-m buffer areas around the 

USGS-GAMA grid sites was 46 percent natural, 37 percent 

agricultural, and 17 percent urban. The difference between 

overall land use in the NOCO study unit and land use 

around the CDPH sites and USGS-GAMA grid sites reflects 

the fact that CDPH sites and USGS-GAMA grid sites are 

preferentially located where people are living and working. 

The difference between the average land use around the 

CDPH sites and around the USGS-GAMA grid sites reflects 

the spatially distributed nature of the USGS-GAMA grid 

sites. The CDPH sites are more biased towards urban land use 

because more urban areas typically have a higher density of 

CDPH sites.

The 58 USGS-GAMA grid sites showed a wide 

variation in land use (fig. 6B). In the NOCO-IN study area, 

approximately two-thirds of the sites were primarily mixtures 

of agricultural and natural land use, and most of the other sites 

were primarily mixtures of urban and agricultural land use. 

In the NOCO-CO study area, approximately one-half of the 

sites were primarily mixtures of urban and natural land use, 

and most of the other sites were dominated by agricultural 

land use. The median amount of percent urban land use was 

significantly greater in the areas surrounding the NOCO-CO 

sites than for the NOCO-IN sites (p = 0.022; table B2). 

Septic tanks and LUFTs within the 500-m buffers around 

the USGS-GAMA grid sites also were used as markers of 

land-use patterns. Generally, areas with greater percentages 

of urban land use have more septic tanks and LUFTs on 

average, and areas with natural land use have fewer septic 

tanks and LUFTs. The density of septic tanks the NOCO-IN 

study area ranged from 0.1 to 30.8 tanks per square kilometer 

(tanks/km2

), with a median of 4.8 tanks/km2 (table B2). In 

the NOCO-CO study area, the density of septic tanks ranged 

from 0.4 to 44.9 tanks/km2, with a median of 6.6 tanks/km2. 

There were no significant differences in the density of septic 

tanks (p = 0.54) between the NOCO-IN and NOCO-CO study 
18 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

Crescent City

Eureka

Arcata

Fortuna

HUMBOLDT CO

DEL NORTE CO

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Ukiah

Wilits

Covelo

Lakeport

Fort Bragg

sac14-0547_Figure 05ab LU

A

B

EXPLANATION

NOCO study unit

0 10 205 KILOMETERS

0 10 20 5 MILES

A

B

Cities

Counties

LUFT

Natural

Land Use

Urban

Agricultural

Land use from Nakagaki and others, 2007

Land use from Nakagaki and others, 2007

Figure 5. Land use and the location of leaking or formerly leaking underground fuel tanks (LUFTs) in the Northern Coast Ranges 

(NOCO) study unit, 2009, California GAMA Priority Basin Project.
Potential Explanatory Factors 19

Natural

Agricultural

Urban

0

20

40

60

80

100

0 20 40 60 80 100

0

20

40

60

80

100

EXPLANATION

Natural

Agricultural

Urban

0

20

40

60

80

100

0 20 40 60 80 100

0

20

40

60

80

100

A

B

Average by individual study unit and study area

All wells by individual study area

NOCO study unit 

NOCO-IN study area 

NOCO-CO study area 

Based on 500-meter buffer surrounding

 USGS-GAMA grid sites

NOCO study unit 

NOCO-IN study area 

NOCO-CO study area 

Based on 500-meter buffer surrounding

 CDPH sites

NOCO study unit 

NOCO-IN study area 

NOCO-CO study area 

NOCO-IN study area 

NOCO-CO study area 

Figure 6. sac14-0547_Figure 06ab Trenary LU Percentage of urban, agricultural, and natural land uses for the (A) study unit and study areas and (B) the area surrounding 

each USGS-GAMA grid site in the Northern Coast Ranges (NOCO) study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, 

Interior Basins study area; NOCO-CO, Coastal Basins study area]
20 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

areas. The density of LUFTs was significantly greater in the 

areas surrounding the NOCO-CO sites than for the NOCO-IN 

sites (p = 0.003). In the NOCO-IN study area, the density of 

LUFTs ranged from 0 to 1.77 tanks/km2, with a median of 

0.02 tanks/km2

. In the more urban NOCO-CO study area, the 

density of LUFTs ranged from 0.01 to 1.49 tanks/km2

, with a 

median of 0.160 tanks/km2

. 

Well Construction Information

In the NOCO study unit, depths of the USGS-GAMA 

grid wells (not including the spring) ranged from 15 to 

400 ft below land surface (bls), with a median of 100 ft bls 

(figs. 7A, B). Depths to the top-of-perforations ranged from 

10 to 356 ft bls, with a median of 40 ft bls. The perforation 

length was as much as 237 ft (median: 35 ft; table B3).

Well depths in the NOCO-IN study area ranged from 

36 to 400 ft bls, with a median of 116 ft bls. Depths to top-ofperforations ranged from 15 to 148 ft bls, with a median of 

40 ft bls and perforation lengths as much as 237 ft (median: 

60 ft). In the NOCO-CO study area, wells were shallower and 

had shorter perforation lengths than the wells in the NOCO-IN 

study area. Well depths ranged from 15 to 400 ft bls, with a 

median of 85 ft bls. Depths to top-of-perforations ranged from 

10 to 356 ft bls, with a median of 35 ft bls and perforation 

lengths up to 120 ft (median: 20 ft; table B3).

Hydrologic Conditions

Hydrologic conditions are represented by aridity index, 

field water temperature, and distance to nearest hot spring 

listed in the USGS MRDS and geothermal well listed in the 

DOGGR database (appendix B). The aridity index was used as 

an indicator of climate and is the average annual precipitation 

(PRISM Group, Oregon State University, 2012) divided by 

average annual evapotranspiration (Flint and Flint, 2007). 

Higher values indicate wetter conditions: values <0.05 are 

defined as hyper-arid, 0.05–0.20 as arid, 0.20–0.50 as semiarid, 0.50–0.65 as dry sub-humid, 0.65–1.00 as humid, and 

>1.00 as wet. In the NOCO-IN study area, the aridity index 

ranged from 0.48 to 1.73, with a median of 0.83 (table B3). 

The aridity index in the NOCO-CO study area ranged from 

0.86 to 2.17, with a median of 1.26. 

Field water temperature was used as a potential indicator 

of groundwater interacting with hydrothermal systems (Forrest 

and others, 2013). In the NOCO-IN study area, field water 

temperatures ranged from 12.5 to 25.0 degrees Celsius (°C), 

with a median of 18.0 °C (table B3). Field water temperatures 

in the NOCO-CO study area ranged from 10.5 to 18.0 °C, with 

a median of 13.0 °C. 

Distance to the nearest hot spring listed in the USGS 

MRDS and geothermal well listed in the DOGGR database 

was also used as a potential indicator of groundwater 

interacting with hydrothermal systems (fig. 3C). Previous 

investigations in the Coast Range Mountains of northern 

California by the USGS and others have shown that water 

discharged from thermal/mineral springs are commonly 

enriched with dissolved trace elements such as boron, arsenic, 

bromide, lithium, silver, and gold, among other trace elements 

and major and minor ions (Berkstresser, 1968; Thompson 

and others, 1978; Goff and others, 1993; Peters, 1993). 

While being near a hot spring or geothermal well alone does 

not prove direct mixing with thermal spring waters, it may 

indicate a greater probability that groundwater at a site may 

be influenced to some degree by the underlying hydrothermal 

system supplying the hot spring or geothermal well. In the 

NOCO-IN study area, distance to the nearest hot spring listed 

in the USGS MRDS ranged from 0.61 to 30.9 kilometers 

(km), with a median of 13.5 km. Distance to the nearest 

geothermal well listed in the DOGGR database ranged from 

0.37 to 93.7 km, with a median of 26.5 km. In the NOCO-CO 

study area, the distance to the nearest hot spring ranged from 

20.2 to 142 km, with a median of 103 km, and the distance to 

the nearest geothermal well ranged from 51.1 to 341 km, with 

a median of 223 km (table B3; U.S. Geological Survey, 2005; 

California Department of Conservation, 2013).

Hydrologic condition data indicate that the climate was 

drier, the field water temperatures were warmer, and the hot 

springs and geothermal wells were closer to the USGS-GAMA 

sites in the NOCO-IN study area (inland) compared to sites in 

the NOCO-CO study area (coastal) (tables 6, B3). 

Groundwater Age

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

were used to classify groundwater age distributions into three 

categories: modern, mixed, and pre-modern (appendix B). 

Groundwater with tritium activity >0.5 tritium unit (TU) 

was defined as “modern,” and groundwater with tritium 

activity <0.5 TU was defined as “pre-modern.” Modern 

groundwater contains a substantial component of water 

recharged since 1952 (Michel, 1989). The presence of premodern groundwater also was identified using the carbon-14 

data: samples with percentage of modern carbon <88 percent 

were considered to contain a substantial component of premodern groundwater. Samples with tritium activity >0.5 TU 

and modern carbon percentage <88 percent were classified as 

“mixed-age.” Samples with tritium activity >0.5 TU but no 

carbon-14 data were classified as “modern or mixed-age.” Of 

the 58 samples collected by USGS-GAMA, 24 were classified 

as modern, 20 were mixed-age (evidence of modern and 

pre-modern groundwater in the same sample), 13 were premodern, and 1 was modern or mixed-age (table B4). 

Classified groundwater ages generally increased with 

well depth and depth to the top of the well perforations. 

Groundwater with pre-modern-age distributions came from 

wells with significantly greater depths to top of the perforation 

than groundwater with modern (p = <0.001) or mixed-age 

distributions (p = 0.008) (figs. 8B, C). Groundwater with 

modern-age distributions came from wells with significantly 

shallower depths than groundwater with mixed-age (p = 0.006) 

or pre-modern-age distributions (p = 0) (figs. 8A, C). 
Potential Explanatory Factors 21

Well depth Top-of-perforations Perforation length

USGS-GAMA grid wells—NOCO-IN study area

28 21 21

400

300

200

100

0

Depth below land surface or length of perforated interval, in feet

28 Number of wells

 with data

EXPLANATION

sac14-0547_Figure 07a_box plot

A

Well depth Top-of-perforations Perforation length

USGS-GAMA grid wells—NOCO-CO study area

29 21 21

400

300

200

100

0

Depth below land surface or length of perforated interval, in feet

B

75th percentile

Median

25th percentile

Data point that is

 outside of 1.5 × IQR

 of the 25th percentile

Nearest data point

 that is within

 1.5 × IQR of the

 75th percentile

Nearest data point

 that is within

 1.5 × IQR of the

 25th percentile

Interquartile

range (IQR)

Figure 7. Construction characteristics for USGS-GAMA grid sites in the (A) Interior Basins study area and (B) Coastal Basins study 

area, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
22 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Modern Mixed Pre-modern

Modern Mixed Pre-modern

Groundwater age classification

240

180

120

60

0

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

10 8 3

Modern Mixed Pre-modern

400

300

200

100

0

Depth of well, in feet below land surface

11 11 6

13 8 7 11 6 3

A

Modern Mixed Pre-modern

Groundwater age classification

400

300

200

100

0

400

300

200

100

0

Depth of well, in feet below land surface

C

B

D

NOCO-IN study area NOCO-IN study area

NOCO-CO study area NOCO-CO study area

sac14-0547_Figure 08abcd box plots

19 Number of wells with data

75th percentile

Median

25th percentile

Data point that is outside of

1.5 × IQR of the 25th percentile

Nearest data point that is within

1.5 × IQR of the 75th percentile

Nearest data point that is within

1.5 × IQR of the 25th percentile

Interquartile

range (IQR)

EXPLANATION

Figure 8. Relation of groundwater age classification to (A) well depth and (B) depth to top-of-perforations for wells in the Interior 

Basins study area, (C) well depth and (D) depth to top-of-perforations for wells in the Coastal Basins study area, and (E) bar chart 

showing the depth class of all wells in the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
Potential Explanatory Factors 23

Number of wells

0 2 4 6 8 10 12 14 16 18

<70

<70 to >70

>70

Depth class

Modern

Mixed

Pre-modern

Groundwater age

 classification in

 the NOCO study unit

EXPLANATION

sac14-0547_Figure 08e

E

Figure 8. —Continued

Classified groundwater ages were used to create a 

classification system for well depth. Wells of depth less 

than a critical depth were defined as shallow; wells with 

perforations beginning above the critical depth and ending 

below the critical depth were defined as mixed-depth; wells 

with perforations entirely below the critical depth were 

defined as deep. Wells with total well depth below the critical 

depth and unknown perforation information were defined as 

mixed-depth or deep. The critical depth of 70 ft bls (depth to 

top of the perforation interval) was selected by optimizing the 

segregation of modern-age groundwater into shallow wells, 

mixed-age groundwater into mixed-depth wells, and premodern-age groundwater into deep wells.

Classification system for well depth

[Abbreviations: ft bls, feet below land surface; ≥, greater than or equal to; 

<, less than]

Well depth 

classification Well depth Depth to top of the perforation 

Shallow <70 ft bls <70 ft bls

Mixed-depth ≥70 ft bls <70 ft bls

Deep ≥70 ft bls ≥70 ft bls

Mixed-depth or deep ≥70 ft bls Unknown

In the NOCO study unit, 57 percent of the shallow wells 

had modern-age groundwater, 41 percent of the mixed-depth 

wells had mixed-age groundwater, and 55 percent of the deep 

wells had pre-modern-age groundwater (fig. 8E; table B4). 

Eight wells were classified as mixed-depth or deep; three 

had mixed-age groundwater, and five had pre-modern-age 

groundwater. The spring had mixed-age groundwater and is 

not represented in figure 8.

Geochemical Conditions

Sufficient chemical data, including dissolved oxygen 

(DO) concentration, were available and used to classify 

groundwater oxidation-reduction (redox) conditions into 

three categories: oxic, mixed, and anoxic (appendix B). 

Groundwater was oxic at 31 of the sites, mixed at 1 of the 

sites, and anoxic at 26 of the sites. Anoxic conditions were 

further subdivided into suboxic; manganese-reducing; 

iron-reducing; manganese- and iron-reducing; nitrate- and 

manganese-reducing; and nitrate-, manganese-, and ironreducing conditions (table B5). 

Correlations Between Explanatory Factors

Apparent correlations between potential explanatory 

factors and water-quality constituents could result from 

correlations among potential explanatory factors; therefore, 

identification of statistically significant correlations between 

potential explanatory factors is important (tables 5, 6).

Implications of correlations between explanatory variables 

are discussed later in the report as part of analysis of factors 

affecting individual water-quality constituents.
Table 5. Results of non-parametric (Spearman’s rho method) analysis of correlations between selected potential explanatory factors, Northern Coas

California GAMA Priority Basin Project. [Explanation: Spearman’s rho test used and rho values shown. Significance level (p ≤ 0.05); Correlations with rho > 0.2 and (or) p-values ≤ 0.05 are shown in bold. Abbreviat

Ambient Monitoring and Assessment Program; USGS, U.S. Geological Survey; ≤, less than or equal to; >, greater than; ns, no significant correlation; black text, significant posicant negative correlation; DOGGR, Division of Oil, Gas, and Geothermal Resources (California Department of Conservation)] rho: Spearman’s correlation statistic Percent urban land use Percent agricultural land use Percent natural land use Density of septic tanks Density of leaking underground fuel tanks Well depth Depth to top of perforations Dissolved oxygen concentration pH Field water temperature Aridity index1 

sD

Percent urban land use ns –0.36 0.50 0.51 ns ns ns ns ns 0.30 Percent agricultural land use –0.80 ns ns ns ns ns ns 0.39 –0.29 

Percent natural land use –0.36 –0.41 ns ns ns ns ns ns 

Density of septic tanks 0.37 ns ns ns ns ns ns Density of leaking underground fuel tanks ns ns ns ns ns ns Well depth 0.82 ns 0.56 0.34 ns 

Depth to top of perforations ns 0.68 0.39 ns Dissolved oxygen concentration ns ns ns pH ns ns 

Field water temperature –0.66 Aridity index1 

Distance to nearest hot spring listed in the USGS Mineral Resources Data System Distance to nearest geothermal well 

listed in the DOGGR database

1Aridity index is average annual precipitation (PRISM Group, Oregon State University, 2012) divided by average annual evapotranspiration (Flint and Flint, 2007).
Potential Explanatory Factors 25

Table 6. Results of Wilcoxon rank-sum tests on USGS-GAMA grid site data used to determine significant differences between constituent 

values grouped by potential explanatory factors, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.

[Explanation: Potential explanatory factors without significant correlations are not shown on this table. Only results with p-values ≤ 0.05 are considered 

significant in this study; Wilcoxon rank-sum tests with exact distribution and continuity correction; Z, test statistic for Wilcoxon test; a significantly positive 

Z value in a column to the right indicates that the entry in the leftmost column has larger values in the first classification in the column to the right compared to 

the second classification; a significantly negative Z value in a column to the right indicates that the entry in the leftmost column has larger values in the second 

classification in the column to the right compared to the first classification. USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges 

study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges study unit, Coastal Basins study area. Abbreviations: USGS, U.S. Geological 

Survey; GAMA, Groundwater Ambient Monitoring and Assessment Program; <, less than; >, greater than; ≤, less than or equal to; ns, no significant difference 

(p-value > 0.05); DOGGR, Division of Oil, Gas, and Geothermal Resources (California Department of Conservation); %, percent]

Selected potential 

explanatory factors and 

water-quality constituents

Potential explanatory factors

Study area Groundwater age classifications Redox 

classifications

NOCO-IN compared 

with NOCO-CO

Modern age 

compared with 

mixed-age

Mixed-age 

compared with 

pre-modern age

Modern age 

compared with 

pre-modern age

Oxic conditions 

compared with 

anoxic conditions

Z: Test statistic for 

Wilcoxon test Z: Test statistic for Wilcoxon test Z: Test statistic for Wilcoxon test

Potential explanatory factors

Percent urban land use –2.29 ns ns ns ns

Density of leaking underground 

fuel tanks

–2.92 ns ns ns ns

Well depth 5.77 –3.00 –2.46 –3.98 –2.05

Depth to top of perforations 4.93 –3.49 –2.53 –3.65 –2.98

Dissolved oxygen ns 3.18 ns 3.83 6.47

pH ns –3.75 ns –4.37 –2.32

Aridity index1 –5.36 ns ns ns –6.14

Field water temperature 5.36 –2.04 ns ns ns

Distance to the nearest hot spring 

listed in the USGS Mineral 

Resources Data System

–6.40 ns ns ns ns

Distance to nearest geothermal 

well listed in the DOGGR 

database

–6.23 ns ns ns ns

Water-quality constituents

Boron2 4.23 ns ns ns –3.53

Arsenic2 ns –4.65 ns –3.50 –3.36

Iron2 ns –2.79 ns –2.32 –5.26

Manganese2 ns –2.89 ns –3.48 –6.24

Chloroform3 ns 2.00 ns ns 3.36

Simazine3 ns 2.35 ns ns 2.11

Perchlorate3 ns ns ns ns 2.63

1

Aridity index is average annual precipitation (PRISM Group, Oregon State University, 2012) divided by average annual evapotranspiration (Flint and Flint, 2007).

2

Constituents with ≥ 2% high aquifer-scale proportion. 

3

Organic constituents (special-interest constituent) with detection frequencies ≥ 10%, including detections below reporting levels.
26 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

The NOCO-IN study area generally had deeper wells 

and deeper depth to top-of-perforations than the NOCO-CO 

study area. Samples from the NOCO-IN study area also had 

higher groundwater temperatures, and the climate was drier in 

the NOCO-IN study area as indicated by a lower aridity index 

(table 6). The NOCO-IN study area sites generally were located 

closer to hot springs or geothermal wells. The NOCO-CO study 

area had a higher percentage of urban land use and density of 

LUFTs than the NOCO-IN study area (table 6). 

In the NOCO study unit, relations were observed between 

well depth and groundwater age. The median depth of wells 

with groundwater classified as pre-modern was deeper than 

the depths of wells with groundwater classified as modern or 

mixed-ages (table 6; figs. 8A, C). In addition, groundwater 

classified as mixed-age was deeper than groundwater classified 

as modern. The median depth to the top-of-perforations of 

wells with groundwater classified as pre-modern also was 

deeper than the depth to the top-of-perforations of wells with 

groundwater classified as modern or mixed-age (table 6; 

figs. 8B, D). Well depths or depths to top-of-perforations in 

wells with groundwater samples classified as modern and 

mixed-age were not significantly different.

Groundwater ages for most wells perforated entirely at 

depths <70 ft bls (15 of 19 wells, 79 percent) were modern 

age (figs. 8B, D). Groundwater ages for wells with the topof-perforations <70 ft but with the bottom-of-perforations 

≥70 ft were modern or mixed-age. Groundwater ages for most 

wells perforated entirely at depths ≥70 ft were pre-modern or 

mixed-age.

The densities of septic tanks and LUFTs were positively 

correlated with percent urban land use and negatively 

correlated with natural land use (table 5). 

Field water temperature was significantly positively 

correlated with well depth, depth to top-of-perforations, 

and the percentage of agricultural land use (table 5). Field 

water temperature was negatively correlated with the aridity 

index and distances to nearest hot spring and geothermal 

well. Groundwater temperatures also were significantly 

lower in sites with modern ages than in sites with mixed 

ages, indicating that groundwater temperatures generally 

increase with depth (table 6). The aridity index was positively 

correlated with distances to the nearest hot spring and 

geothermal well (table 5). 

pH was positively correlated with well depth and depth 

to top-of-perforations (table 5), indicating increasing pH with 

increasing depth (fig. 9A). These correlations were expected 

based on previous studies in other aquifers in California 

(Jurgens and others, 2008) and reflect dissolution of primary 

aquifer minerals, causing the pH of groundwater to increase 

with depth and continued contact of groundwater with aquifer 

materials. pH values also were higher for groundwater 

with mixed or pre-modern ages and for groundwater with 

anoxic conditions (table 6; fig. 9A). DO concentrations were 

significantly greater in groundwater with modern or mixed 

ages than in groundwater with pre-modern ages (table 6; 

fig. 9B), indicating that DO has been consumed in older waters 

that have had more time to interact with oxidizable material in 

the groundwater flow system.
Potential Explanatory Factors 27

5.0 5.5 6.0 6.5 7.0 7.5 8.0

pH, in standard units

400

300

200

100

0

Depth of well, in feet below land surface

NOCO-CO

NOCO-IN

Modern

Modern or mixed-age

Mixed

Pre-modern

Groundwater age

 classification

EXPLANATION

A

0 2 4 6 8 10 12

Dissolved oxygen, in milligrams per liter

400

300

200

100

0

Depth of well, in feet below land surface

NOCO-CO

NOCO-IN

Modern

Modern or mixed-age

Mixed

Pre-modern

Groundwater age

 classification

EXPLANATION

B

Figure 9. sac14-0547_Figure 09ab depth plots Groundwater age classification and well depth in relation to (A) pH and (B) dissolved oxygen concentrations, Northern Coast 

Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, Coastal Basins study area]
28 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Status and Understanding of 

Water Quality

The status assessment was designed to identify the 

constituents or classes of constituents most likely to be 

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

only to constituents having regulatory or nonregulatory 

health-based or aesthetic-based benchmarks established by the 

USEPA or the CDPH (California Department of Public Health, 

2006, 2008, 2010; U.S. Environmental Protection Agency, 

2008, 2009a, b, 2012). The spatially distributed, randomized 

approach to site 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 sites.

The following discussion of the status and understanding 

assessment results is divided into two parts—inorganic 

constituents and organic constituents—and each part has 

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

many constituents were detected at any concentration in 

USGS-GAMA samples compared to the number analyzed 

and a graphical summary of the relative-concentrations 

of constituents detected in the grid sites. Aquifer-scale 

proportions are presented for the subset of constituents that 

met criteria for additional evaluation based on relativeconcentration, or for organic (special-interest) constituents, 

prevalence. For constituents that have understanding 

assessment results, those results are presented immediately 

following the status assessment results for that constituent. 

The aquifer-scale proportions calculated by using the 

spatially weighted approach were within the 90 percent 

confidence intervals for their respective grid-based aquifer 

proportions for all 13 of the constituents listed in tables 7, 

C1, and C2, providing evidence that the grid-based approach 

yields statistically equivalent results to the spatially weighted 

approach.

Inorganic Constituents

Inorganic constituents typically occur naturally in 

groundwater, although their concentrations may be influenced 

by human activities as well as by natural factors. All 

49 inorganic constituents analyzed by USGS-GAMA were 

detected at least once in the NOCO study unit. Of these 

49 constituents, 26 had regulatory or nonregulatory healthbased benchmarks, 8 had nonregulatory aesthetic-based 

benchmarks, and 15 had no established benchmarks (table 2). 

Eight inorganic constituents were identified for additional 

evaluation in the status assessment because they were 

detected at moderate or high relative-concentrations in the 

USGS-GAMA grid sites. The constituents with health-based 

benchmarks are arsenic, barium, boron, nickel, and nitrate, 

and the constituents with aesthetic-based benchmarks are 

iron, manganese, and total dissolved solids (TDS) (figs. 10, 

11; tables 3, 7). Four of these inorganic constituents were 

selected for further evaluation in the understanding assessment 

because they were present at high relative-concentrations in 

>2 percent of the primary aquifer system: boron, arsenic, iron, 

and manganese.

Inorganic Constituents with Health-Based 

Benchmarks

Inorganic constituents with health-based benchmarks, 

as a group, had high relative-concentrations in 10.3 percent, 

moderate relative-concentrations in 13.8 percent, and low 

relative-concentrations (or non-detections) in 75.9 percent of 

the primary aquifer system (table 8A). 

Trace Elements

Trace elements, as a class, were detected at high 

relative-concentrations (for one or more constituents) in 

10.3 percent of the primary aquifer system, moderate relativeconcentrations in 8.6 percent, and low relative-concentrations 

in 81.1 percent (table 8A). Boron and arsenic were detected 

at high relative-concentrations in more than 2 percent of the 

primary aquifer system, and barium was detected at high 

relative-concentrations in 1.7 percent of the primary aquifer 

system (table 7). The spatial distributions of selected trace 

elements for USGS-GAMA grid sites and the CDPH sites are 

shown in figures 12 and 13. Note that boron was not sampled 

by the CDPH from June 1, 2006, to June 1, 2009. 
Table 7. Aquifer-scale proportions calculated using grid-based and spatially weighted methods for those constituents that met criteria for additionaassessment, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.[Relative-concentration categories: high, concentration greater than water-quality benchmark; moderate, concentration is less than the benchmark and is greater than or equal torganic and special-interest constituents) or 0.5 of the benchmark (for inorganic constituents); low, concentration less than 0.1 of benchmark (for organic constituents and speciathe benchmark (for inorganic constituents). Abbreviations: GAMA, Groundwater Ambient Monitoring and Assessment Program; CDPH, California Department of Public HealtMTBE, methyl tert-butyl ether; μg/L, micrograms per liter]

Constituent

Raw detection 

frequency, 

in percent1

Spatially weighted 

aquifer-scale proportion, 

in percent1

Grid-based 

aquifer-scale proportion, 

in percent

Number 

of sites Moderate High Number of cells Moderate aquifer proportion High aquifer proportion Number of sites Moderate aquifer proportion High aquife

proportion 

Inorganic constituents with health-based benchmarksTrace ElementsArsenic 130 3.1 3.1 58 6.0 3.5 58 6.9 3.4 

Barium 131 0 0.8 58 0 1.7 58 0 1.7 

Boron3 58 5.2 8.6 58 5.2 8.6 58 5.2 8.6 

Nickel 133 0.8 0 58 1.7 0 58 1.7 0 

NutrientsNitrate 220 1.8 0 58 1.4 0 57 3.5 0 

Inorganic constituents with aesthetic-based benchmarksIron 121 6.6 21.5 58 6.4 25.7 58 5.2 25.9 

Manganese 123 4.1 30.9 58 7.8 41.2 58 8.6 39.7 

TDS 118 5.1 0 58 6.9 0 58 6.9 0 

Organic constituents with health-based benchmarksVolatile organic compoundsChloroform (Trichloromethane) 118 1.7 0 58 2.2 0 58 1.7 0 

Vinyl chloride (Chloroethene) 115 0.9 0 58 1.7 0 58 1.7 0 

MTBE4 134 0 0.7 58 0 0.2 58 0 0 

Pesticides and pesticide degradatesSimazine 123 0 0 58 0 0 58 0 0 

Special-interest constituent with health-based benchmarkPerchlorate 162 0.6 0 58 0.6 0 58 1.7 0 

1Based on most recent analyses for each CDPH site during June 1, 2006−June 1, 2009, combined with data from USGS-GAMA grid sites.2Based on the Jeffrey’s interval for the binomial distribution (Brown and others, 2001).3Boron was not sampled by the CDPH during June 1, 2006−June 1, 2009.4High relative-concentrations of MTBE were reported multiple times in the CDPH water-quality database from one site in the NOCO-IN study area during the current period 

samples were collected by the CDPH between August 16, 2006, and May 20, 2009, from this site for analysis of MTBE; 15 had concentrations of MTBE between 13 and 21 μg/1 was a non-detection (most recent value, May 20, 2009). On that basis, it was determined that the non-detection of MTBE reported as the most recent value in the CDPH water

represent present-day conditions. The MTBE sample collected on April 30, 2009 (17 μg/L) was substituted in order to more accurately reflect present-day conditions.
30 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

0.001

0.01

0.1

1

10

100

Zinc Name and center of symbol is the maximum relative-concentration for that constituent-

 Unless indicated by following location line:

EXPLANATION

Moderate

Low

Moderate

Low

Moderate

High High

Organic and specialinterest constituentsInorganic

constituents

Maximum relative-concentration, dimensionless

Volatile

organic

compounds

Pesticides Special

interest

Nutrients Trace

elements

with HHB

Major and

minor ions

and trace

elements

with SMCL

Radioactive

constituents

Number of 

compounds

detected

< 0.001

1 0 0 0 0 1 0

sac14-0547_Figure 10_MaxRCs

Abbreviations: N, nitrogen; TDS, total dissolved solids; HHB, human-health-based benchmark;

 SMCL, secondary maximum contaminant levels

Chloroform

Vinyl chloride

1,1-Dichloroethane

Bromodichloromethane

1,1,1-Trichloroethane

Methyl tert-butyl ether

Atrazine

Simazine

Nitrate-N

Ammonia-N

Nitrite-N

Gross beta

Radon-222

Gross alpha

Uranium

Radium

Boron

Arsenic

Barium

Strontium

Fluoride

Nickel

Chromium

Vanadium

Lead

Copper

Antimony

Molybdenum

Beryllium

Cadmium

Selenium

Aluminum

Chloride

Sulfate

TDS

Manganese

Zinc

Iron

Perchlorate

Tetrachloroethene

(PCE)

Figure 10. Maximum relative-concentration of constituents detected in USGS-GAMA grid sites, by constituent class, Northern Coast 

Ranges study unit, 2009, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 31

0.001

0.01

0.1

1

10

Maximum relative-concentration

Arsenic Barium Boron Nickel Nitrate

sac14-0547_Figure 11a

A

Study areas Relative-concentration

High

Moderate

Low

NOCO-CO

NOCO-IN

Figure 11. Relative-concentrations of (A) selected constituents with health-based benchmarks and (B) constituents with aestheticbased benchmarks in USGS-GAMA grid sites, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. 

[NOCO-IN, Interior Basins study area; NOCO-CO, Coastal Basins study area; TDS, total dissolved solids]
32 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

0.001

0.01

0.1

1

10

Maximum relative-concentration

Iron Manganese TDS

sac14-0547_Figure 11b

B

Study areas Relative-concentration

High

Moderate

Low

NOCO-CO

NOCO-IN

Figure 11. —Continued

Understanding Assessment for Boron

Boron is a naturally occurring semi-metallic element 

with high solubility in water. Natural sources of boron 

include igneous rocks, such as granite and pegmatite (as 

the mineral tourmaline), and evaporite minerals, such as 

borax, kernite, and colemanite (Hem, 1985; Reimann and 

de Caritat, 1998). Seawater contains 4,500 micrograms per 

liter (μg/L) of boron (Summerhayes and others, 1996), and 

groundwater from marine sediments and shales average about 

0.1 μg/L boron (Ryan and Langmuir, 1993). Boron also is 

associated with shallow thermal springs, deep thermal waters, 

and volcanic activity (Hem, 1989; Webster and Nordstrom, 

2003; Kulongoski and others, 2010; Forrest and others, 

2013). Boron can occur in wastewater because borax is a 

component of many detergents. Other anthropogenic uses 

of boron compounds include semiconductors, insecticides, 

preservatives, chemical reagents, and fertilizers. Boron is 

an essential nutrient for plants, but is toxic to plants at high 

concentrations (Hem, 1989). The comparison benchmark 

used for boron in this study was the CDPH NL-CA of 

1,000 μg/L (California Department of Public Health, 2010). At 

concentrations greater than the HAL-US of 6,000 μg/L, boron 

may adversely affect fetal development (U.S. Environmental 

Protection Agency, 2008). Boron is highly mobile because no 

mineral has a low enough solubility to provide an upper limit 

to its concentration range (Ryan and Langmuir, 1993). 

Boron was detected at high relative-concentrations in 

8.6 percent of the primary aquifer system and at moderate 

relative-concentrations in 5.2 percent (table 7). Boron 

concentrations generally are higher in the NOCO-IN study 

area than in the NOCO-CO study area (table 6). All of the 

high relative-concentrations of boron were detected in the 

NOCO-IN study area, but moderate relative-concentrations 

were detected in both study areas (figs. 11A, 12; tables C1, 

C2). Boron concentrations were found to be negatively 

correlated with DO (table 9) and were significantly higher in 

groundwater with anoxic rather than oxic conditions (table 6; 

fig. 14D). All of the sites with high and moderate relativeconcentrations of boron had anoxic groundwater conditions 

(table B5). 

Multiple lines of evidence suggest that the elevated boron 

concentrations found in the NOCO study unit are most likely 

due to groundwater mixing with hydrothermal systems within 

the NOCO-IN study area, including (1) elevated groundwater 

temperatures, (2) groundwater chemistry characteristics 

similar to those of geothermal waters, and (3) proximity to 

known geothermal areas. 

Samples with high and moderate relative-concentrations 

of boron have elevated groundwater temperatures. Boron 

concentrations were significantly positively correlated with 

field water temperature (table 9; fig. 14A). The median 

temperature (18.0 °C) for the 7 samples with high and 

moderate relative-concentrations of boron was significantly 

greater than the median temperature (14.5 °C) for the other 

51 groundwater samples in the NOCO study unit (Wilcoxon 

rank-sum: p = 0.006). Specifically, the site with the highest 
Status and Understanding of Water Quality 33

Table 8A. Summary of aquifer-scale proportions for inorganic constituent classes, Northern Coast Ranges study unit, 2009, California 

GAMA Priority Basin Project.

[Relative-concentration categories: high, concentration of at least one constituent in the class greater than its benchmark; moderate, concentration of at 

least one constituent in the class was greater than half of its benchmark and no constituents in the class had concentrations greater than their benchmarks; 

low, concentrations of all constituents in the class were less than or equal to half of the benchmark, including non-detections. Abbreviation: GAMA, 

Groundwater Ambient Monitoring and Assessment Program]

Constituent class Aquifer-scale proportion, in percent

Low values Moderate values High values

Inorganic constituents with health-based benchmarks

Trace elements1 81.1 8.6 10.3

Nutrients 96.5 3.5 0

Uranium and other radioactive constituents 100 0 0

Any inorganic constituent with health-based benchmark 75.9 13.8 10.3

Inorganic constituents with aesthetic-based benchmarks

Iron, manganese, silver, and zinc 51.7 8.6 39.7

Total dissolved solids, specific conductance, sulfate, and chloride 93.1 6.9 0

Any inorganic constituent with aesthetic-based benchmark 50.0 10.3 39.7

1

Includes the minor element fluoride because it has a health-based benchmark.

Table 8B. Summary of aquifer-scale proportions for organic and special-interest constituent classes, Northern Coast Ranges study 

unit, 2009, California GAMA Priority Basin Project.

[Relative-concentration categories: high, concentration of at least one constituent in the class greater than its benchmark; moderate, concentration of at least 

one constituent in the class was greater than one-tenth of its benchmark and no constituents in the class had concentrations greater than their benchmarks; 

low, concentrations of all constituents in the class were less than or equal to one-tenth of the benchmark. Abbreviation: GAMA, Groundwater Ambient 

Monitoring and Assessment Program]

Constituent class

Aquifer-scale proportion, in percent

Not 

detected

Low 

values 

Moderate 

values

High 

values

Organic constituents with health-based benchmarks

Volatile organic compounds 

Solvents 91.4 8.6 0 0

Organic synthesis reagents 98.3 0 1.7 0

Gasoline components 92.9 6.9 0 1

0.2

Trihalomethanes 75.9 22.4 1.7 0

Any volatile organic compound with health-based benchmark 61.9 36.2 1.7 1

0.2

Pesticides and pesticide degradates2 89.7 10.3 0 0

Any organic constituent with health-based benchmark 58.4 39.7 1.7 1

0.2

Special-interest constituent with health-based benchmark

Perchlorate 75.9 22.4 1.7 0

1

Spatially weighted aquifer-scale proportion value.

2

Only herbicides were detected.
34 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

125° 124° 123°

42°

41°

40°

39°

0 40 80 20 MILES

0 40 8020 KILOMETERS

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

sac14-0547_Figure 12ab

A A

B

C

B

EXPLANATION

NOCO study unit

0 10 205 KILOMETERS

0 10 20 5 MILES

Franciscan

 complex

Plio-Pleistocene

 sediment

Quaternary alluvium

Quaternary other

 sediment

Quarternary, mafic

 volcanics

Pyroclastic volcanics

Tertiary, mafic

 volcanics

Tertiary nonmarine

 sediment

Tertiary marine

 sediment

Granitic rocks

Metamorphic

 other

Metasediment

Ultramafic/mafic

Fault

USGS-GAMA grid well

 NOCO study unit

Boron concentration,

in micrograms per liter

< 500 (Low) 

Hot spring 

>500 to <1,000 (Moderate) 

>1,000 (High) 

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Figure 12. Relative-concentrations of boron in USGS-GAMA grid sites and geologic features in the (A) Coastal Basins study area and 

(B) Interior Basins study area, and (C) geologic formations, locations of hot springs and geothermal wells, and approximate boundaries 

of the Napa and Sonoma Valleys and the Geysers Steam Field, Northern Coast Ranges (NOCO) study unit, 2009, California GAMA Priority 

Basin Project.
Status and Understanding of Water Quality 35

Calistoga

Soda Spring

Cooks Spring

Aetna

Springs

Vichy

Springs

Walter

Springs

Ornbaun

Springs

Deadhot

Springs

Orrs Hot Spring

Unnamed

Location

Salt Spring No.2

Baker Soda

Spring

One-Shot

Mining Co.

Crabtree

Hotsprings

Pinches Spring

Point Arena

Hot Spring

Wilbur

Hot Springs

Area

 Geysers

steam field

Geysers-Clear

Lake Area

Napa and

Sonoma

Valleys

sac14-0547_Figure 12c

123°30’ 123°15’ 123° 122°45’ 122°30’

39°

45’

39°

30’

39°

15’

39°

38°

45’

EXPLANATION

Geothermal well

Hot spring 

NOCO study unit

Fault

Lakes

Franciscan complex

Plio-Pleistocene sediment

Quaternary alluvium

Quaternary other sediment

Quarternary, mafic volcanics

Pyroclastic volcanics

Tertiary, mafic volcanics

Tertiary marine sediment

Metamorphic other

Metasediment

Ultramafic/mafic

0 5 10 20 MILES

0 10 20 5 KILOMETERS

USGS-GAMA grid well

 NOCO study unit

Boron concentration,

in micrograms per liter

< 500 (Low) 

>500 to <1,000 (Moderate) 

>1,000 (High) 

Geology from Saucedo and others, 2000

C

Figure 12. —Continued
36 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

125° 124° 123°

42°

41°

40°

39°

0 40 80 20 MILES

0 40 8020 KILOMETERS

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

sac14-0547_Figure 13ab

A A

B

C

B

EXPLANATION

0 10 205 KILOMETERS

0 10 20 5 MILES

NOCO study unit

Franciscan

 complex

Plio-Pleistocene

 sediment

Quaternary alluvium

Quaternary other

 sediment

Quarternary, mafic

 volcanics

Pyroclastic volcanics

Tertiary, mafic

 volcanics

Tertiary nonmarine

 sediment

Tertiary marine

 sediment

Granitic rocks

Metamorphic

 other

Metasediment

Ultramafic/mafic

Fault

USGS-GAMA grid well

 NOCO study unit

Arsenic concentration,

in micrograms per liter

Hot spring 

CDPH site

Non-detection

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

< 5 (Low) 

>10 (High) 

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Figure 13. Relative-concentrations of arsenic in USGS-GAMA grid sites, CDPH sites for the period June 1, 2006–June 1, 2009, from 

the CDPH water-quality database, and geologic features in the (A) Coastal Basins study area and (B) Interior Basins study area and 

(C) geologic formations, locations of hot springs and geothermal wells, and approximate boundaries of the Napa and Sonoma Valleys 

and the Geysers Steam Field Northern Coast Ranges (NOCO) study unit, 2009, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 37

C

Calistoga

Soda Spring

Cooks Spring

Aetna

Springs

Vichy

Springs

Walter

Springs

Ornbaun

Springs

Deadhot

Springs

Orrs Hot Spring

Unnamed

Location

Salt Spring No.2

Baker Soda

Spring

One-Shot

Mining Co.

Crabtree

Hotsprings

Pinches Spring

Point Arena

Hot Spring

Wilbur

Hot Springs

Area

 Geysers

steam field

Geysers-Clear

Lake Area

Napa and

Sonoma

Valleys

sac14-0547_Figure 13c

123°30’ 123°15’ 123° 122°45’ 122°30’

39°

45’

39°

30’

39°

15’

39°

38°

45’

EXPLANATION

Geothermal well

Hot spring 

NOCO study unit

Fault

Lakes

Franciscan complex

Plio-Pleistocene sediment

Quaternary alluvium

Quaternary other sediment

Quarternary, mafic volcanics

Pyroclastic volcanics

Tertiary, mafic volcanics

Tertiary marine sediment

Metamorphic other

Metasediment

Ultramafic/mafic

0 5 10 20 MILES

0 10 20 5 KILOMETERS

USGS-GAMA grid well

 NOCO study unit

Arsenic concentration,

in micrograms per liter

CDPH site

Non-detection

< 5 (Low) 

>5 to <10 (Moderate) 

>10 (High) 

< 5 (Low) 

>10 (High) 

Geology from Saucedo and others, 2000

Figure 13. —Continued
38 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Anoxic Mixed Oxic

Redox classification

1

10

100

1,000

10,000

Boron concentration, in micrograms per liter

Boron concentration, in micrograms per liter

10

1

Distance to nearest hot spring, in kilometers

0

0 20 40 60 80 100 120 140

40 80 120 160 200 240 280 320 360

10 100 1,000 10,000

12

14

16

18

20

22

24

26

Field water temperature, in degrees Celsius

10

12

14

16

18

20

22

24

26

Field water temperature, in degrees Celsius

10

12

14

16

18

20

22

24

26

Field water temperature, in degrees Celsius

26 1 31

A

Distance to nearest geothermal well, in kilometers

C

B

D

NOCO-CO

NOCO-IN

sac14-0547_Figure 14abcd box plots

26 Number of wells with data

75th percentile

Median

25th percentile

Data point that is outside of

1.5 × IQR of the 25th percentile

Nearest data point that is within

1.5 × IQR of the 75th percentile

Nearest data point that is within

1.5 × IQR of the 25th percentile

Interquartile

range (IQR)

NOCO-CO

NOCO-IN

EXPLANATION

Boron concentration,

in micrograms per liter

< 500 (Low) 

>500 to <1,000 (Moderate) 

>1,000 (High) 

Figure 14. Boron concentrations relative to (A) field water temperature, (B) field water temperature and distance to nearest hot spring, 

(C) field water temperature and distance to nearest geothermal well, and (D) redox classification in USGS-GAMA grid sites sampled for 

the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, 

Coastal Basins study area]
Status and Understanding of Water Quality 39

boron concentration (NOCO-IN-22; 8,470 μg/L) had a field 

water temperature of 25.0 °C (table B3). These results follow 

the findings in previous studies in the Geysers–Clear Lake 

area, which classified groundwater as being under geothermal 

influence if temperatures were >19.0 °C (Goff and others, 

1993; Donnelly-Nolan and others, 1993).

Samples with high and moderate relative-concentrations 

of boron exhibit groundwater chemistry characteristics similar 

to those of geothermal waters. Groundwater data appear to 

show a similar pattern of occurrences of hydrothermal system 

indicators as that noted in the Geysers–Clear Lake area 

(Donnelly-Nolan and others, 1993; Goff and others, 1993; 

Peters, 1993) and in the Napa and Sonoma Valleys (Forrest 

and others, 2013). The shared characteristics of geothermal 

waters in these hydrothermal systems include raised water 

temperatures, near neutral pH, elevated concentrations of 

boron, arsenic, and lithium (in varied degrees), and high 

helium isotope ratios. 

Samples with high and moderate relative-concentrations 

of boron all had near-neutral pH values, which ranged from 

6.0 to 7.5 and had a median of 6.8 (table B5). Boron and 

arsenic concentrations were significantly correlated with 

each other (Spearman’s rho test, p = 0.002, rho = 0.56). 

Two of the sites with high relative-concentrations of boron 

(NOCO-IN-05 and NOCO-IN-27) also had high relativeconcentrations of arsenic, and two additional sites with 

high relative-concentrations of boron (NOCO-IN-11 and 

NOCO-IN-15) had moderate relative-concentrations of arsenic 

(figs. 12, 13). Boron and lithium concentrations were also 

significantly correlated with each other (Spearman’s rho test, 

p = 0.001, rho = 0.43). Helium isotope ratios (3

He/4He) are 

often discussed as R/Ra rather than as the ratio itself. R/Ra is 

the ratio in the sample (R) divided by the 3

He/4He ratio in the 

atmosphere (Ra = 1.4 x 10–6). R/Ra >1.0 generally indicates 

contribution from the Earth’s mantle (Kulongoski and others, 

2003), and median mantle helium in the western United 

States has an R/Ra = 6.0 (Dodson and others, 1998). The 

sample from NOCO-IN-22 (the sample with the highest boron 

concentration) had an R/Ra = 5.0 (table E1). 

Samples with high and moderate relative-concentrations of 

boron are located near known hydrothermal areas. Proximity of 

USGS-GAMA sites to known hydrothermal areas was assessed 

in three ways: (1) sample sites located within the approximate 

physical boundaries of geothermal areas, (2) distance from 

hot spring listed in the USGS MRDS, and (3) distance from 

geothermal well listed in the DOGGR database. 

Four of the seven samples with high and moderate 

relative-concentrations of boron are from sites that are 

spatially located within the approximate boundaries of 

the Geysers–Clear Lake area (figs. 12B, C). Specifically, 

NOCO-IN-27 is located in the central portion of the study 

area, within the main mass of the Clear Lake volcanic field; 

NOCO-IN-22 and NOCO-IN-25 are located in the southern 

portion of the study area, near the Geysers steam field; and 

NOCO-IN-26 is located in the portion of the study area, in the 

eastern Clear Lake region (fig. 12B). 

Boron concentrations were negatively correlated 

with the distance to nearest hot spring listed in the USGS 

MRDS and distance to nearest geothermal well listed in 

the DOGGR database (table 9; figs. 14B, C). The median 

distance from the nearest hot spring for the 7 samples with 

high and moderate relative-concentrations of boron was 

5.3 km; the median distance for the other 51 groundwater 

samples was 66.1 km. Three of the sites with high relativeconcentrations of boron were relatively near named hot 

springs (NOCO-IN-05: Pinches Spring; NOCO-IN-15: Soda 

Spring; NOCO-IN-22: Aetna Springs) as was one of the sites 

with a moderate relative-concentration (NOCO-IN-26: Salt 

Spring No. 2; U.S. Geological Survey, 2005; fig. 12; table B3). 

The median distance from nearest geothermal well for the 

7 samples with high and moderate relative-concentrations 

of boron was 38.5 km; the median distance for the other 51 

groundwater samples was 145 km. Specifically, NOCO-IN-22 

was within 1 km of a geothermal well, and NOCO-IN-25 was 

0.37 km from a geothermal well (California Department of 

Conservation, 2013). 

There does not appear to be a causative relation between 

boron concentrations and aridity index, although they had a 

significant negative correlation (table 9). This result is most 

likely a function of aridity index being correlated with the 

geothermal explanatory factors (groundwater temperature and 

distance to nearest hot spring and geothermal well) rather than 

a causative relation that is explanatory of boron distribution in 

groundwater in the NOCO study unit.

The elevated groundwater temperatures, close relations 

among boron, arsenic, and lithium concentrations in the 

groundwater, helium isotope ratios, and proximity to known 

geothermal areas suggest that the primary source of boron in 

the NOCO study unit is geothermal waters. 

Understanding Assessment for Arsenic

Arsenic is a naturally occurring semi-metallic trace 

element. Potential sources of arsenic to groundwater are natural 

or anthropogenic. Natural sources include the dissolution 

of arsenic-bearing minerals and desorption of arsenic from 

mineral surfaces. Potential anthropogenic sources of arsenic 

include mining of copper and gold ores, coal combustion, 

arsenical pesticides, arsenical veterinary pharmaceuticals, and 

wood preservatives (Welch and others, 2000). The MCL-US 

for arsenic was lowered from 50 to 10 μg/L in 2002, and 

chronic exposure to arsenic concentrations between 10 and 

50 μg/L in drinking water has been linked to increased cancer 

risk and to non-cancerous effects including skin damage and 

circulatory problems (U.S. Environmental Protection Agency, 

2012). Arsenic solubility increases with increasing water 

temperature, such that geothermal systems often exhibit high 

arsenic concentrations (Ballantyne and Moore, 1988; Goff 

and others, 1993; Peters, 1993; Webster and Nordstrom, 2003; 

Forrest and others, 2013).

Arsenic was detected at high relative-concentrations in 

3.4 percent of the primary aquifer system and at moderate 

relative-concentrations in 6.9 percent (table 7). All of the 
40 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

high relative-concentrations of arsenic were detected in 

the NOCO-IN study area (figs. 11, 13; tables C1, C2). 

Arsenic concentrations were significantly lower in modern 

groundwater than in groundwater with mixed or pre-modern 

ages (table 6; fig. 15A). Additionally, arsenic concentrations 

were positively correlated with well depth and depth to top-ofperforations (table 9). Arsenic concentrations were negatively 

correlated to DO (table 9), and arsenic concentrations were 

significantly higher in groundwater with anoxic conditions 

rather than oxic conditions (table 6).

Arsenic mobilization and distribution in groundwater 

is affected by the oxidation-reduction (redox) and pH 

conditions of the groundwater system. Arsenic concentrations 

are commonly found to be positively correlated with pH as 

a result of the desorption of arsenic from aquifer sediments 

with increasing pH (Belitz and others, 2003; Welch and 

others, 2006). Previous investigations and reviews of arsenic 

(for example, Welch and others, 2000, 2006; Frankenberger, 

2002; Ravenscroft and others, 2009; Forrest and others, 

2013) have attributed elevated arsenic concentrations in 

groundwater to three mechanisms: (1) the release of arsenic 

from dissolution of iron or manganese oxides under iron- or 

manganese-reducing (anoxic) conditions, (2) groundwater 

mixing with hydrothermal systems, and (3) arsenic desorption 

from aquifer sediments or inhibition of arsenic sorption to 

aquifer sediments as a result of oxic and alkaline groundwater 

conditions (pH values ≥8.0). 

Whether arsenic was released by dissolution under anoxic 

conditions, groundwater mixing with hydrothermal systems, or 

desorption under oxic, high-pH conditions, the accumulation 

of elevated concentrations of arsenic in groundwater 

also requires favorable hydrologic conditions. Arsenic 

accumulation is favored by longer contact times between 

groundwater and aquifer materials and minimizing the amount 

of flushing of the system (Smedley and Kinniburgh, 2002). 

Evidence for the first mechanism, release of arsenic 

under reducing conditions, in the NOCO study unit includes 

the association of high and moderate concentrations of 

arsenic with groundwater having iron- or manganesereducing conditions. Both of the sites having high 

relative-concentrations of arsenic (NOCO-IN-05 and 

NOCO-IN-27) and three of the four sites having moderate 

relative-concentrations (NOCO-IN-11, NOCO-IN-15, 

and NOCO-CO-21) had anoxic groundwater conditions 

(table B5). For these five sites with anoxic conditions and 

high or moderate relative-concentrations of arsenic, pH 

values ranged from 6.0 to 7.1. Four of these five sites also had 

high relative-concentrations of iron and manganese (all but 

NOCO-IN-15). The association of high iron and manganese 

Table 9. Results of non-parametric (Spearman’s rho method) analysis for correlations between selected water-quality constituents 

and potential explanatory factors, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.

[Explanation: Potential explanatory factors without significant correlations are not shown on this table. Spearman’s rho test used and rho values shown. 

Significance level (p ≤ 0.05); Correlations with rho > 0.2 and (or) p-values ≤ 0.05 are shown in bold. Abbreviations: GAMA, Groundwater Ambient 

Monitoring and Assessment Program; USGS, U.S. Geological Survey; ≤, less than or equal to; >, greater than; ≥, greater than or equal to; ns, no significant 

correlation between factors; black text, significant positive correlation; red text, significant negative correlation; DOGGR, Division of Oil, Gas, and Geothermal 

Resources (California Department of Conservation); %, percent]

Constituent

Percent 

agricultural 

land use1

Well 

depth

Depth 

to top of 

perforations 

Dissolved 

oxygen 

(DO)

pH Field water 

temperature

Aridity 

index

Distance to 

nearest hot 

spring listed 

in the USGS 

Mineral 

Resources Data 

System

Distance 

to nearest 

geothermal 

well listed in 

the DOGGR 

database

rho: Spearman’s correlation statistic

Inorganic constituents with health-based benchmarks

Boron2 ns ns ns –0.54 ns 0.62 –0.68 –0.53 –0.64

Arsenic2 ns 0.34 0.58 –0.41 0.51 ns ns ns ns

Inorganic constituents with aesthetic-based benchmarks

Iron2 ns ns ns –0.60 ns ns ns ns ns

Manganese2 ns ns 0.37 –0.73 ns ns ns ns ns

Organic constituents with health-based benchmarks

Chloroform3 ns –0.31 –0.56 0.46 –0.31 ns ns ns ns

Simazine3 ns –0.37 ns ns –0.30 ns ns ns ns

Special-interest constituent with health-based benchmark

Perchlorate3 0.33 ns –0.39 0.27 ns ns ns ns ns

1

Land-use percentages are within circles with buffers of 500 meters centered around each site included in analysis. 

2

Constituents with ≥2% high aquifer-scale proportion. 

3

Organic constituents (or constituent of special interest) with detection frequencies at any concentration ≥10%.
Status and Understanding of Water Quality 41

0.01

0.1

1

10

100

A

B

Modern Mixed Pre-modern

Groundwater age classification

24 20 13

Arsenic, in micrograms per liter

0.01

0.1

1

10

100

Anoxic Mixed Oxic

Redox classification

1 31

Arsenic, in micrograms per liter

sac14-0547_Figure 15ab depth plots

13 Number of wells with data

75th percentile

Median

25th percentile

Data point that is outside of

1.5 × IQR of the 25th percentile

Nearest data point that is within

1.5 × IQR of the 75th percentile

Nearest data point that is within

1.5 × IQR of the 25th percentile

Interquartile

range (IQR)

EXPLANATION

Figure 15. Arsenic concentrations relative to (A) groundwater age classification and (B) redox classification in USGS-GAMA grid sites 

sampled for the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
42 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

relative-concentrations, low DO (anoxic conditions), and 

pH <7.0 at NOCO-IN-05, NOCO-IN-11, and NOCO-IN-27 

suggests that reductive dissolution of iron and manganese 

oxides may account for portions of the high and moderate 

relative-concentrations of arsenic detected at these sites.

Evidence for the second mechanism, groundwater 

mixing with hydrothermal systems includes the association 

of high and moderate relative-concentrations of arsenic 

co-occurring with hydrothermal system indicators. As 

previously mentioned, arsenic and boron concentrations 

were significantly correlated with one other. Four of the 

sites in the NOCO-IN study area having high (NOCO-IN-05 

and NOCO-IN-27) and moderate (NOCO-IN-11 and 

NOCO-IN-15) relative-concentrations of arsenic also had 

high relative-concentrations of boron (figs. 12, 13). Arsenic 

and lithium concentrations also were significantly correlated 

(Spearman’s rho test, p = 0.002, rho = 0.41).

There is minimal evidence for the third mechanism, 

desorption of arsenic from aquifer sediments or inhibition 

of arsenic sorption to aquifer sediments with increasing pH. 

Arsenic concentrations were positively correlated with pH 

(table 9). Because only one site (NOCO-CO-03) had moderate 

relative-concentrations of arsenic, with oxic and relatively 

alkaline conditions (pH of 7.7; table B5), the relation of 

arsenic concentrations and pH is most likely a result of 

the relation of pH to anoxic conditions, well depth, and 

groundwater age. 

In summary, high and moderate relative-concentrations 

of arsenic can result from release of arsenic from aquifer 

sediments under iron- and manganese-reducing conditions, 

contribution from hydrothermal systems (when present), and 

accumulation with groundwater age, or from other sources that 

are not fully understood. 

Nutrients

Nutrients, as a class, were not detected at high relativeconcentrations in the primary aquifer system of the NOCO 

study unit. Moderate relative-concentrations were detected in 

3.5 percent of the primary aquifer system, and low relativeconcentrations were detected in 94.8 percent of the primary 

aquifer system (table 8A). Moderate relative-concentrations 

of nitrate occurred in the NOCO-CO study area (table C2; 

Mathany and others, 2011).

Uranium and Other Radioactive Constituents

The relative-concentrations of uranium and other 

radioactive constituents are low in the primary aquifer system 

of the NOCO study unit (table 8A). No detections of uranium 

or other radioactive constituents were greater than their 

associated water-quality benchmark during the current period 

of study or in the historical data (table 4). 

Inorganic Constituents with Aesthetic-Based 

Benchmarks

Inorganic constituents with aesthetic-based benchmarks, 

as a class, were detected at high relative-concentrations 

(for one or more constituents) in 39.7 percent, moderate 

relative-concentrations in 10.3 percent, and low relativeconcentrations in 50.0 percent of the primary aquifer system 

(table 8A). High (39.7 percent) and moderate (8.6 percent) 

relative-concentrations of trace metals (iron and manganese) 

accounted for all of the high and most of the moderate aquiferscale proportions. Inorganic constituents with aesthetic-based 

benchmarks that are indicators of salinity (TDS, field specific 

conductance, sulfate, and chloride) had a moderate aquiferscale proportion of 6.9 percent of the primary aquifer system 

(table 8A). Among the salinity indicators, TDS was detected at 

moderate relative-concentrations in 6.9 percent of the primary 

aquifer system (table 7). Chloride had a concentration greater 

than its benchmark in at least one site in the CDPH waterquality database prior to June 1, 2006 (table 4), but not during 

the current period of study.

Understanding Assessment for Iron and Manganese

Potential natural sources of iron and manganese 

in groundwater include the dissolution of igneous and 

metamorphic rocks as well as the dissolution of various 

secondary minerals (Hem, 1989). Some rocks that contain 

significant amounts of iron and manganese have a relatively 

high composition of the minerals olivine, biotite, and 

hornblende. Potential anthropogenic sources of iron and 

manganese in groundwater include effluents associated with 

the steel and mining industries (Reimann and de Caritat, 

1998) and soil amendments in the form of iron and manganese 

sulfates that are added to deficient soils to stimulate crop 

growth. Distributions of iron and manganese concentrations 

in groundwater are strongly influenced by redox conditions 

in the aquifer. In sediments, the oxyhydroxides of iron and 

manganese are common as coatings on mineral surfaces and as 

suspended particles (Sparks, 1995). Under anoxic conditions, 

however, the process of reductive dissolution can release these 

elements from mineral surfaces, and iron and manganese may 

remain in solution in aquifer systems (Sparks, 1995).

In the NOCO study unit, iron was detected at high 

relative-concentrations in 25.9 percent of the primary 

aquifer system and moderate relative-concentrations in 

5.2 percent (table 7). Manganese was detected at high 

relative-concentrations in 39.7 percent and at moderate 

relative-concentrations in 8.6 percent of the primary aquifer 

system. High relative-concentrations of iron and manganese 

occurred in both study areas (figs. 11, 16, 17; tables C1, 

C2). Iron and manganese were significantly correlated with 

each other (Spearman’s rho test, p <0.001, rho = 0.74). 

Iron and manganese concentrations were significantly 

higher in pre-modern and mixed-age groundwater than 

in modern groundwater (table 6). In addition, manganese 

concentrations had a significant positive correlation with 
Status and Understanding of Water Quality 43

Pacific Ocean

125° 124° 123°

42°

41°

40°

39°

0 40 80 20 MILES

0 40 8020 KILOMETERS

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

sac14-0547_Figure 16ab

A A

B

B

EXPLANATION

0 10 205 KILOMETERS

0 10 20 5 MILES

NOCO study unit

Franciscan

 complex

Plio-Pleistocene

 sediment

Quaternary alluvium

Quaternary other

 sediment

Quarternary, mafic

 volcanics

Pyroclastic volcanics

Tertiary, mafic

 volcanics

Tertiary nonmarine

 sediment

Tertiary marine

 sediment

Granitic rocks

Metamorphic

 other

Metasediment

Ultramafic/mafic

Fault

USGS-GAMA grid well

 NOCO study unit

Iron concentration,

in micrograms per liter

< 150 (Low) 

Non-detection 

Hot spring 

>150 to < 300 (Moderate) 

>300 (High) 

CDPH site

Non-detection

>150 and <300 (Moderate) 

>300 (High) 

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Figure 16. Relative-concentrations of iron in USGS-GAMA grid sites and CDPH sites for the period June 1, 2006–June 1, 2009, from the 

CDPH water-quality database in the (A) Coastal Basins study area and (B) Interior Basins study area, Northern Coast Ranges study unit, 

2009, California GAMA Priority Basin Project.
44 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

125° 124° 123°

42°

41°

40°

39°

0 40 80 20 MILES

0 40 8020 KILOMETERS

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

sac14-0547_Figure 17

ab

A A

B

B

EXPLANATION

0 10 205 KILOMETERS

0 10 20 5 MILES

NOCO study unit

Franciscan

 complex

Plio-Pleistocene

 sediment

Quaternary alluvium

Quaternary other

 sediment

Quarternary, mafic

 volcanics

Pyroclastic volcanics

Tertiary, mafic

 volcanics

Tertiary nonmarine

 sediment

Tertiary marine

 sediment

Granitic rocks

Metamorphic

 other

Metasediment

Ultramafic/mafic

Fault

USGS-GAMA grid well

 NOCO study unit

Manganese concentration,

in micrograms per liter

< 25 (Low) 

Non-detection 

Hot spring 

>25 to < 50 (Moderate) 

>50 (High) 

CDPH site

Non-detection

< 25 (Low) 

>50 (High) 

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Geology from Saucedo and others, 2000

Figure 17. Relative-concentrations of manganese in USGS-GAMA grid sites and CDPH sites for the period June 1, 2006–June 1, 2009, 

from the CDPH water-quality database in the (A) Coastal Basins study area and (B) Interior Basins study area, Northern Coast Ranges 

study unit, 2009, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 45

depth to top-of-perforations (table 9). Iron and manganese 

concentrations were negatively correlated with DO (table 9), 

with significantly higher iron and manganese concentrations 

in groundwater with anoxic compared with oxic conditions 

(table 6). This suggests reductive dissolution from aquifer 

sediments as the primary process for mobilizing iron and 

manganese into the groundwater.

Organic Constituents with Health-Based 

Benchmarks

The organic constituents with health-based benchmarks 

assessed in this study are volatile organic compounds (VOCs) 

and pesticides and pesticide degradates. VOCs may be 

present in paints, solvents, fuels, refrigerants, and fumigants, 

and 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 isolated from 

the atmosphere. Pesticides and pesticide degradates are used 

to control weeds, fungi, or insects in agricultural, urban, and 

suburban settings. Of the 168 organic constituents analyzed, 

11 were detected at 1 or more USGS-GAMA grid sites. Of 

these 11 constituents, 10 have health-based benchmarks 

(table 2). 

Four organic constituents with health-based benchmarks 

were identified for additional evaluation in the status 

assessment because they were detected at moderate or high 

relative-concentrations or detected in 10 percent or more of 

the USGS-GAMA grid sites: the VOCs chloroform, vinyl 

chloride, and methyl tert-butyl ether (MTBE) and the pesticide 

simazine (figs. 10, 18, 19; tables 3, 7).

Detection frequency, in percent

0.001

0.0001

0 5 10 15 20 25

0.01

0.1

1

10

Moderate

Low

High

Maximum relative-concentration, dimensionless

Simazine

Chloroform

Perchlorate

1,1,1-Trichloroethane

Methyl tert-butyl ether

1,1-Dichloroethane

Bromodichloromethane

Atrazine

Tetrachloroethene

(PCE)

Vinyl chloride

Carbon disulfide

Figure 18. Maximum relative-concentration of organic and special-interest constituents detected in USGS-GAMA grid sites, Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, Coastal Basins 

study area]
46 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

10% detection line

sac14-0547_Fig19ab

0.0001 0.001 0.01 0.1 1 10

Maximum relative-concentration

Chloroform

(THM)

Perchlorate

Simazine

Vinyl chloride

0 10 20 30 40

Perchlorate 

Simazine 

Chloroform 

Vinyl chloride 

NOCO-IN

NOCO-CO

A

B

Study area

Relative-concentration

High

Moderate

Low

Study unit detection frequency, in percent

Figure 19. (A) Detection frequency and (B) maximum relative-concentration of organic and special-interest constituents detected 

in USGS-GAMA grid sites, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins 

study area; NOCO-CO, Coastal Basins study area]
Status and Understanding of Water Quality 47

Organic constituents with health-based benchmarks, 

as a group, were detected at high relative-concentrations in 

0.2 percent (spatially weighted) of the primary aquifer system, 

at moderate relative-concentrations in 1.7 percent, and at low 

relative-concentrations in 39.7 percent. Organic constituents 

were not detected in 58.4 percent of the primary aquifer 

system (table 8B).

Volative Organic Compounds

VOCs, as a class, were detected at high relativeconcentrations in 0.2 percent (spatially weighted) of the 

primary aquifer system, at moderate relative-concentrations in 

1.7 percent, and at low relative-concentrations in 36.2 percent. 

VOCs were not detected in 61.9 percent of the primary 

aquifer system (table 8B). The gasoline component MTBE 

was detected at high relative-concentrations at one CDPH 

site during the current period of study. The trihalomethane 

chloroform and the organic synthesis reagent vinyl chloride 

were detected at moderate relative-concentrations in one grid 

site in the NOCO-IN study area (figs. 10, 19B; table C1). 

Solvents are used for a variety of industrial, commercial, 

and domestic purposes (Zogorski and others, 2006). 

Historically, chlorinated solvents have had a wide variety 

of applications, including dry cleaning, vapor degreasing of 

metal parts, hand cleaning of metal parts, paint stripping, fire 

extinguishers, adhesives, lubricants, and silicones (Petrisor 

and Wells, 2008). No solvents were detected at high or 

moderate relative-concentrations in the primary aquifer 

system (table 8B). Solvents were detected at low relativeconcentrations in 8.6 percent of the primary aquifer system. 

Solvents were not detected in 91.4 percent of the primary 

aquifer system. 

Organic synthesis reagents are compounds used in the 

manufacture or preparation of organic compounds. Organic 

compounds (such as vinyl chloride) are commonly used to 

make polyvinyl chloride (PVC) pipes. PVC pipes are regularly 

used in drinking-water systems, and organic synthesis reagents 

are commonly released from the PVC pipes into the water 

system (U.S. Environmental Protection Agency, 2013). No 

organic synthesis reagents were detected at high relativeconcentrations in the primary aquifer system (table 8B). One 

organic synthesis reagent (vinyl chloride) was detected at 

moderate relative-concentrations in 1.7 percent of the primary 

aquifer system (fig. 18). Organic synthesis reagents were 

not detected in 98.3 percent of the primary aquifer system 

(table 8B).

Gasoline components include gasoline hydrocarbons 

and oxygenates. Gasoline hydrocarbons are straight, 

branched, or cyclic-structured VOCs containing only 

carbon and hydrogen atoms and are common ingredients in 

gasoline and other petroleum product formulations. Gasoline 

oxygenates are compounds that contain oxygen and are 

added to gasoline to increase the efficiency of combustion 

in order to meet the requirements of the 1990 Clean Air 

Act Amendments (Zogorski and others, 2006). Gasoline 

components were detected at high relative-concentrations in 

0.2 percent (spatially weighted) of the primary aquifer system 

(table 8B). The gasoline component detected at high relativeconcentration was the gasoline oxygenate MTBE. MTBE was 

also detected at low relative-concentrations in 6.9 percent of 

the primary aquifer system (fig. 18). Gasoline components 

were not detected in 92.9 percent of the primary aquifer 

system (table 8B).

Water used for drinking water and other household uses 

in domestic and municipal systems commonly is disinfected 

with chlorine solutions. As a side effect to disinfecting the 

water, the chlorine may react with natural organic matter 

to produce trihalomethanes (THMs) and other chlorinated 

and (or) brominated disinfection byproducts. No THMs 

were detected at high relative-concentrations in the primary 

aquifer system of the NOCO study unit. THMs were detected 

at moderate relative-concentrations in 1.7 percent of the 

primary aquifer system and at low relative-concentrations in 

22.4 percent. THMs were not detected in 75.9 percent of the 

primary aquifer system (table 8B). 
48 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

Crescent City

Eureka

Arcata

Fortuna

HUMBOLDT CO

DEL NORTE CO

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Ukiah

Covelo

Lakeport

Fort Bragg

sac14-0547_Figure 20ab Chloroform

A

B

EXPLANATION

NOCO study

 unit

0 10 205 KILOMETERS

0 10 20 5 MILES

A

B

Cities

Counties

LUFT

Natural

Land Use

Urban

Agricultural

USGS-GAMA grid well

 NOCO study unit

CDPH site

Not detected (< 0.5) 

Not detected (< 0.02) 

> 0.02 and < 8 (Low) 

> 8 and < 80 (Moderate) 

> 8 and < 80 (Moderate) 

Concentration of chloroform,

in micrograms per liter

Land use from Nakagaki and others, 2007

Land use from Nakagaki and others, 2007

Figure 20. Relative-concentrations of chloroform detected in USGS-GAMA grid sites and CDPH sites for the period June 1, 2006–

June 1, 2009, from the CDPH water-quality database, and locations of leaking or formerly leaking underground fuel tanks (LUFTs), 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, 

Coastal Basins study area]
Status and Understanding of Water Quality 49

Understanding Assessment for Chloroform

Chloroform has been widely detected in national, 

regional, and local studies of VOCs in ground, surface, 

source, and drinking waters (Ivahnenko and Barbash, 2004). 

Additionally, chloroform was the most frequently detected 

VOC in groundwater nationwide in studies conducted by 

the USGS NAWQA Program (Zogorski and others, 2006). 

Chloroform was detected in the NOCO study unit at a high 

relative-concentration in the CDPH water-quality database 

prior to June 1, 2006, but was not detected at high relativeconcentrations during the current period of study (fig. 20). 

Chloroform was detected in 24 percent of the primary aquifer 

system (figs. 10, 18, 19).

Chloroform concentrations were significantly negatively 

correlated with well depth and depth to top-of-perforations 

(table 9). Seven of the 14 sites in which chloroform was 

detected had depths <70 ft bls. Thirteen of these sites had 

depth to top-of-perforation information available, and 

all had depths to top-of-perforations ≤70 ft bls (fig. 21). 

Chloroform concentrations were positively correlated with 

DO (table 9) and were significantly higher in groundwater 

with oxic compared with anoxic conditions (table 6). Thirteen 

of the 14 sites in which chloroform was detected had oxic 

groundwater conditions. Chloroform concentrations also were 

significantly greater in sites with groundwater classified as 

modern age than in sites with mixed ages (table 6). This result 

was expected because chloroform concentrations and DO also 

were significantly correlated. Chloroform concentrations had 

a negative correlation with pH (table 9), and this relation is 

likely caused by the positive correlations between pH and well 

depth and depth to top-of-perforations (table 5). In summary, 

most sites containing chloroform have depth to top-ofperforations ≤70 ft bls with oxic, modern-age groundwater.

Chloroform, in micrograms per liter

400

300

200

100

0

Depth of top-of-perforations, in feet below land surface

Non-detection 0.01 0.1 1 10

EXPLANATION

NOCO-CO

NOCO-IN

Modern

Mixed

Pre-modern

Groundwater age

 classification

Study area

Figure 21. Trihalomethane chloroform concentrations relative to groundwater age classification and depth to top-of-perforations in 

USGS-GAMA grid sites sampled for the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
50 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

Crescent City

Eureka

Arcata

Fortuna

HUMBOLDT CO

DEL NORTE CO

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Ukiah

Covelo

Lakeport

Fort Bragg

sac14-0547_Figure 22ab simazine

A

B

EXPLANATION

NOCO study

 unit

0 10 205 KILOMETERS

0 10 20 5 MILES

A

B

Cities

Counties

LUFT

Natural

Land Use

Urban

Agricultural

USGS-GAMA grid well

 NOCO study unit

CDPH site

Not detected

< 0.1 (Low) 

Concentration of simazine,

in micrograms per liter

Not detected 

Land use from Nakagaki and others, 2007

Land use from Nakagaki and others, 2007

Figure 22. Relative-concentrations of simazine detected in USGS-GAMA grid sites and CDPH sites for the period June 1, 2006–

June 1, 2009, from the CDPH water-quality database, and locations of leaking or formerly leaking underground fuel tanks (LUFTs), 

Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [NOCO-IN, Interior Basins study area; NOCO-CO, 

Coastal Basins study area]
Status and Understanding of Water Quality 51

Pesticides and Pesticide Degradates

Pesticides and pesticide degradates include herbicides, 

insecticides, and fungicides and are used in agricultural 

applications on orchards and vineyards and in urban settings 

for weed control (Gilliom and others, 2006). Pesticides and 

pesticide degradates, as a class, were detected at low relativeconcentrations in 10.3 percent of the primary aquifer system 

and not detected in 89.7 percent of the primary aquifer system 

(table 8B). No pesticides or pesticide degradates were detected 

at high or moderate relative-concentrations in the primary 

aquifer system.

Understanding Assessment for Simazine

Simazine was the most frequently detected triazine 

herbicide in groundwater in California (Troiano and others, 

2001). In addition, simazine was among the most commonly 

detected herbicides in groundwater in major aquifers across 

the United States (Gilliom and others, 2006). Simazine 

was detected in 10.3 percent of the primary aquifer system 

(figs. 18, 19, 22).

Simazine was detected at six wells with depths and 

depths to the top-of-perforations of ≤70 ft bls (fig. 23; one of 

these wells was not plotted on figure 23, due to the lack of 

depth to the top-of-perforation information), and five of these 

wells also had depths of <70 ft bls. All six simazine detections 

occurred in sites with groundwater classified as modern age 

(fig. 23), so it is not surprising that simazine concentrations 

were significantly higher at sites with modern groundwater 

than at sites with mixed-age groundwater (table 6).

Simazine concentrations were greater in groundwater 

with oxic redox conditions than in groundwater with anoxic 

conditions (table 6). Five simazine detections were from sites 

having groundwater classified as oxic, and one detection was 

from a site with groundwater with mixed redox conditions. In 

summary, most sites containing simazine may be characterized 

as shallow (<70 ft bls), with depth to top-of-perforations 

≤70 ft bls and oxic, modern-age groundwater.

Simazine, in micrograms per liter

400

300

200

100

0

Depth of top-of-perforations, in feet below land surface Non-detection 0.005 0.01 0.015 0.02 0.025 0.03

EXPLANATION

NOCO-CO

NOCO-IN

Modern

Mixed

Pre-modern

Groundwater age

 classification

Study area

Figure 23. The herbicide simazine concentrations relative to groundwater age classification and depth to top-of-perforations in 

USGS-GAMA grid sites sampled for the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
52 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Pacific Ocean

0 40 80 20 MILES

0 40 8020 KILOMETERS

125° 124° 123°

42°

41°

40°

39°

124°30’ 124°15’ 124°

41°

30’

41°

40°

30’

Pacific Ocean

Crescent City

Eureka

Arcata

Fortuna

HUMBOLDT CO

DEL NORTE CO

MENDOCINO CO

LAKE CO

GLENN CO

SONOMA CO

COLUSA CO

NAPA CO

TEHAMA CO

YOLO

CO

123°30’ 123° 122°30’

39°

30’

39°

38°

30’

Pacific Ocean

Ukiah

Covelo

Lakeport

Fort Bragg

sac14-0547_Figure 24ab perchlorate

A

B

EXPLANATION

NOCO study

 unit

0 10 205 KILOMETERS

0 10 20 5 MILES

A

B

Cities

Counties

LUFT

Natural

Land Use

Urban

Agricultural

USGS-GAMA grid well

 NOCO study unit

CDPH site

Not detected (< 0.1) 

> 0.1 and < 0.6 (Low) 

> 0.6 and < 6 (Moderate) 

Concentration of perchlorate,

in micrograms per liter

Not detected 

Land use from Nakagaki and others, 2007

Land use from Nakagaki and others, 2007

Figure 24. Relative-concentrations of perchlorate in USGS-GAMA grid sites and CDPH sites for the period June 1, 2006–June 1, 2009, 

from the CDPH water-quality database, and land use, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
Status and Understanding of Water Quality 53

Special-Interest Constituent with Health-Based 

Benchmark

Perchlorate was considered a special-interest constituent 

at the inception of the GAMA-PBP because it had recently 

been detected in some drinking-water supplies in California 

and the CDPH was evaluating whether or not an MCL-CA was 

warranted (California Department of Public Health, 2008). 

An MCL-CA of 6 μg/L was established in 2007. Perchlorate 

was not detected at high relative-concentrations in the primary 

aquifer system in the NOCO study unit (fig. 24). Perchlorate 

was detected at moderate relative-concentrations in 

1.7 percent of the primary aquifer system and at low relativeconcentrations in 22.4 percent (table 8B). Perchlorate was not 

detected in 75.9 percent of the primary aquifer system. 

Understanding Assessment for Perchlorate

Potential sources of perchlorate to groundwater can be 

natural or anthropogenic. Perchlorate is formed naturally in 

the atmosphere, and very low concentrations are found in 

precipitation (Dasgupta and others, 2005; Parker and others, 

2008; Rajagopalan and others, 2009). The distribution of 

perchlorate under natural conditions in groundwater is likely 

correlated with climate because the extent of evaporative 

concentration of precipitation in the hydrologic cycle is likely 

to increase with increasing aridity (Fram and Belitz, 2011). 

Perchlorate salts accumulate in unsaturated zones and soils (Rao 

and others, 2007). Most of the known sites of anthropogenic 

contamination of groundwater with perchlorate are associated 

with facilities that manufacture or use solid rocket fuels; other 

anthropogenic sources include military munitions storage, use, 

and disposal, and manufacturing and disposal of pyrotechnics, 

safety flares, and explosives (Parker and others, 2008). Potential 

agricultural sources include the Chilean nitrate fertilizer applied 

extensively in the early to mid-1900s (Dasgupta and others, 

2005). Irrigation can also be considered an agricultural source 

if it redistributes perchlorate salts that were originally naturally 

present in the unsaturated zone (Fram and Belitz, 2011). 

Perchlorate concentrations were significantly positively 

correlated with percentage of agricultural land use (table 9). 

Agricultural land use (within 500-m-radius buffer areas around 

each of the sites) was the dominant land-use classification for 

8 of the 14 sites in which perchlorate was detected.

Perchlorate concentrations had a significant negative 

correlation with depth to top-of-perforations (table 9). All 

14 wells in which perchlorate was detected had depths to the 

top-of-perforations of ≤70 ft bls (fig. 25), and 7 of these wells 

had well depths of <70 ft bls.

Non-detection 0.15 0.3 0.45 0.6 0.75

Perchlorate, in micrograms per liter

400

300

200

100

0

Depth to top-of-perforations, in feet below land surface

Anoxic

Oxic

NOCO-CO

NOCO-IN

EXPLANATION

Redox class Study area

Figure 25. The special-interest constituent perchlorate concentrations relative to geochemical condition and depths to top-ofperforations in USGS-GAMA grid sites sampled for the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.
54 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Perchlorate concentrations were positively correlated 

with DO (table 9). Perchlorate concentrations were 

significantly higher in sites with oxic groundwater than in 

anoxic groundwater (table 6; fig. 25). While perchlorate 

biodegrades under anoxic conditions in some aquifers 

(Sturchio and others, 2007), the apparent relation between 

perchlorate and DO in the NOCO study unit may be a 

result of its occurrence predominantly in relatively shallow 

groundwater. 

Fram and Belitz (2011) developed a model for predicting 

the probability of detecting perchlorate in groundwater 

under natural conditions as a function of climate. Although 

perchlorate was often detected in sites having land use 

classified as agricultural, the observed detection frequencies of 

perchlorate in the NOCO-IN and NOCO-CO study areas are 

close to the predicted climate-based detection probabilities, 

thus, the occurrence of perchlorate in the NOCO study unit is 

consistent with natural sources of perchlorate. 

Summary

Groundwater quality in the approximately 633-squaremile (1,639-square-kilometer) Northern Coast Ranges 

(NOCO) study unit was investigated as part of the Priority 

Basin Project of the Groundwater Ambient Monitoring and 

Assessment (GAMA) Program and the U.S. Geological 

Survey (USGS) National Water-Quality Assessment 

(NAWQA) Program. The GAMA Northern Coast Ranges 

study provides a spatially unbiased characterization of 

untreated groundwater quality in the primary aquifer system. 

The assessment is based on water-quality and ancillary data 

collected in 2009 by the USGS from 58 sites and on data from 

the California Department of Public Health (CDPH) waterquality database. 

The first component of this study, the status of the 

current quality of the groundwater resource, was assessed 

by using data from samples analyzed for naturally occurring 

inorganic constituents (such as trace elements and major 

and minor ions), organic constituents (volatile organic 

compounds [VOCs] and pesticides and pesticide degradates), 

and the special-interest constituent perchlorate. The status 

assessment characterizes the quality of groundwater resources 

in the primary aquifer system of the NOCO 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 

for evaluating regional-scale groundwater quality. High 

aquifer-scale proportion was defined as the percentage of the 

primary aquifer system with relative-concentration greater 

than (>) 1.0 for a particular constituent or class of constituents; 

proportion is based on an aerial rather than a volumetric basis. 

Moderate and low aquifer-scale proportions were defined as 

the percentage of the primary aquifer system with moderate 

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 NOCO study unit (within 

90 percent confidence intervals). 

Inorganic constituents with health-based benchmarks were 

detected at high relative-concentrations in 10.3 percent of the 

primary aquifer system, moderate relative-concentrations in 

13.8 percent, and low relative-concentrations in 75.9 percent. 

The high aquifer-scale proportion of inorganic constituents 

primarily reflected high aquifer-scale proportions of boron 

(8.6 percent), arsenic (3.4 percent), and barium (1.7 percent). 

The inorganic constituents with aesthetic-based benchmarks—

iron and manganese—were detected at high relativeconcentrations in 25.9 percent and 39.7 percent of the primary 

aquifer system, respectively. 

Relative-concentrations of organic constituents with 

health-based benchmarks (one or more) were high in 

0.2 percent of the primary aquifer system, moderate in 

1.7 percent, and low in 39.7 percent. Organic constituents 

were not detected in 58.4 percent of the primary aquifer 

system. Of the 168 organic constituents analyzed, 

11 constituents were detected. Nearly all detections were at 

low relative-concentrations. The VOC chloroform and the 

herbicide simazine were the only organic constituents detected 

in more than 10 percent of grid sites. The special-interest 

constituent perchlorate was detected at moderate relativeconcentrations in 1.7 percent of the primary aquifer system 

and at low relative-concentrations in 22.4 percent. 

The second component of this work, the understanding 

assessment, used statistical correlations between 

concentrations of constituents and values of selected potential 

explanatory factors to identify the factors potentially affecting 

the concentrations and occurrences of constituents detected at 

high relative-concentrations or, for organic constituents, with 

detection frequencies >10 percent. The potential explanatory 

factors evaluated were land use, density of septic tanks, 

density of leaking (or formerly leaking) underground fuel 

tanks, well depth and depth to the top of the perforated interval 

in the well, aridity index, field water temperature, distance to 

nearest hot spring and geothermal well, pH, dissolved oxygen 

concentration, study (geographic) area, groundwater age 

distribution, and redox condition.

The understanding assessment indicated that high 

and moderate relative-concentrations of boron primarily 

occurred in the Interior Basins study area and may be 

attributed to groundwater interacting with hydrothermal 

systems. High and moderate relative-concentrations of boron 

were associated with elevated groundwater temperatures, 

groundwater chemistry characteristics similar to those of 

geothermal waters, and proximity to known geothermal 

areas. Boron concentrations generally were higher where 

low dissolved oxygen concentrations or anoxic conditions 
References 55

exist. The understanding assessment also indicated that 

high and moderate relative-concentrations of arsenic occur 

predominantly in the Interior Basins study area under reducing 

conditions and possibly are enhanced by hydrothermal 

systems (when present). 

Chloroform, simazine, and perchlorate were detected 

predominantly in shallow sites with depths to top-ofperforations less than or equal to 70 feet below land surface, 

modern groundwater, and oxic groundwater conditions.

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 and generosity 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 

California State Water Resources Control Board.

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64 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009
Appendix A. Map of the Northern Coast Ranges (NOCO) Study Unit 65

Appendix A. Map of the Northern Coast Ranges (NOCO) Study Unit 

101

20

Covelo

Willits

Stonyford

Laytonville

Potter Valley

NOCO-IN28

NOCO-IN26

NOCO-IN23

NOCO-IN16

NOCO-IN15

NOCO-IN11

NOCO-IN06

NOCO-IN05

NOCO-IN03

NOCO-IN04

Bartlett Springs fault zone

0 5 10 Miles

0 5 10 Kilometers

MENDOCINO CO

LAKE CO

LAKE CO

GLENN CO

GLENN CO

TEHAMA CO

COLUSA CO

Lake

Pillsbury

Eel River

Eel River

STUDY AREA

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

sac14-0547_Figure A01a

Mill Creek

Outlet Creek

Randomized

 sampling

 grid cell 

Water bodies

Stream or river

Northern Coast

Ranges—

Interior Basins

Shown on

 figure A1B

NOCO-IN15

Faults—Dashed where uncertain;

 Dotted where concealed 

Stoney Creek

A

California Department

 of Public Health (CPDH) site

NOCO grid site and identifier

Figure A1. Northern Coast Ranges (NOCO) Groundwater Ambient Monitoring and Assessment (GAMA) study unit showing the location 

of (A) the northern part, (B) the central part, and (C) the southern part of the Interior Basins (NOCO-IN) study area and (D) the northern 

part, (E) the central part, (F) the southern part of the Coastal Basins (NOCO-CO) study area, the boundaries of the California Department 

of Water Resources (CDWR) defined groundwater basins, the distribution of the study area grid cells, the location of California 

Department of Public Health (CDPH) sites, and the location of sampled U.S. Geological Survey (USGS) grid sites, major cities, major 

roads, topographic features, and hydrologic features.
66 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Maacama Fault

Clover Valley Fault Zone

Russian River

Russian River

101

101

29

20

20

128

Mt.

Big Valley Konocti

Basin

Ukiah

Lakeport

Boonville

Kelseyville

Redwood Valley

Hopland

NOCO-IN27

NOCO-IN24

NOCO-IN21 NOCO-IN18

NOCO-IN20

NOCO-IN19

NOCO-IN17

NOCO-IN14

NOCO-IN13

NOCO-IN12

NOCO-IN10

NOCO-IN09

NOCO-IN08

NOCO-IN07

NOCO-IN02

NOCO-IN01

0 5 10 Miles

0 5 10 Kilometers

LAKE CO

MENDOCINO CO

COLUSA CO

SONOMA CO

GLENN

CO

Lake

Pillsbury

Lake

Mendocino

Clear Lake

Navarro River

Scotts Creek

Scotts Creek

Big Valley Fault

Wight Way Fault

STUDY AREA

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

sac14-0547_Figure A01b

Randomized

 sampling

 grid cell 

Water bodies

Stream or river

Northern Coast

Ranges—

Interior Basins

Shown on

 figure A1A

NOCO-IN08

Faults—Dashed where uncertain;

 Dotted where concealed 

B

California Department

 of Public Health (CPDH) site

NOCO grid site and identifier

Figure A1. —Continued
Appendix A. Map of the Northern Coast Ranges (NOCO) Study Unit 67

29

128

Middletown

Pope Valley

Aetna Springs

NOCO-IN25

NOCO-IN22

0 2.5 5 Miles

0 2.5 5 Kilometers

122°40' 122°30'

38°

40'

NAPA CO

LAKE CO

Pope Creek

St. Helena Creek

STUDY AREA

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

sac14-0547_Figure A01c

SONOMA CO

Collayomi Fault Zone

Randomized

 sampling

 grid cell 

Water bodies

Stream or river

Northern Coast

Ranges—

Interior Basins

NOCO-IN22

Faults—Dashed where

 uncertain

C

California Department

 of Public Health (CPDH) site

NOCO grid site and identifier

Figure A1. —Continued
68 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

199

101

NOCO-CO24

NOCO-CO23

NOCO-CO22

NOCO-CO16

NOCO-CO15

NOCO-CO14

0 5 10 Miles

0 5 10 Kilometers

Pacific Ocean

Fort Dick

Klamath

Crescent City

Randomized

 sampling

 grid cell 

Water bodies

Stream or river

STUDY AREA

Northern Coast

Ranges—

Coastal Basins

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

SAC14-0547_Figure A01d

NOCO-CO15

Lake

Earl

Smith River

KlamathRiver

DEL NORTE CO

HUMBOLDT CO

D

California Department

 of Public Health (CPDH) site

NOCO grid site and identifier

Figure A1. —Continued
Appendix A. Map of the Northern Coast Ranges (NOCO) Study Unit 69

299

96

101

Eureka

Arcata

Fortuna

Trinidad

HUMBOLDT CO

NOCO-CO29

NOCO-CO27

NOCO-CO26

NOCO-CO25

NOCO-CO20

NOCO-CO18

NOCO-CO13

NOCO-CO10

NOCO-CO09

NOCO-CO04

NOCO-CO30

NOCO-CO28

NOCO-CO21

NOCO-CO19

NOCO-CO17

NOCO-CO12

NOCO-CO11

NOCO-CO08

NOCO-CO07

NOCO-CO03

0 2.5 5 10 Miles

0 5 10 2.5 Kilometers

Pacific Ocean

Arcata

Bay

Humboldt

Bay

Big Lagoon

Eel River

Mad River

Table Bluff Fault

Freshwater Fault

Little Salmon Fault Zone

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

sac14-0547_Figure A01e

Randomized

 sampling

 grid cell 

Water bodies

Stream or river

STUDY AREA

Northern Coast

Ranges—

Coastal Basins

NOCO-CO11

Faults—Dashed where uncertain;

 Dotted where concealed

E

California Department

 of Public Health (CPDH) site

NOCO grid site and identifier

Figure A1. —Continued
70 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

San Andreas Fault Zone

1

128

Mendocino

Manchester

Fort Bragg

NOCO-CO06

NOCO-CO05

NOCO-CO02

NOCO-CO01

Point Arena

0 5 10 Miles

0 5 10 Kilometers

Pacific Ocean

Big River

Noyo River

MENDOCINO CO

Shaded relief derived from U.S. Geological Survey

National Elevation Dataset, 2006. 

Albers Equal Area Conic Projection

EXPLANATION

sac14-0547_Figure A01f

Randomized

 sampling

 grid cell 

California Department

 of Public Health (CPDH) site

Water bodies

Stream or river

NOCO grid site and identifier

STUDY AREA

Northern Coast

Ranges—

Coastal Basins

NOCO-CO05

Faults—Dashed where uncertain

F

Figure A1. —Continued
Appendix B. Ancillary Datasets 71

Appendix B. Ancillary Datasets

Land-Use Classification

Land use was classified by using an enhanced version of 

the satellite-derived (30-m pixel resolution) nationwide USGS 

National Land Cover Dataset (NLCD) (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 use during the early 1990s. One pixel in 

the dataset imagery represents a land area of 9,688 square feet 

(ft2

) (900 square meters [m2]), calculated from the pixel of 

98 ft (30 m). The imagery was classified into 25 land-cover 

classifications (Nakagaki and Wolock, 2005). These 25 landcover classifications were aggregated into three principal landuse classes—urban, agricultural, and natural. 

Percentages of the three land-use classes in the study 

unit and study areas, in areas within a radius of 500 m (500-m 

buffers) of each USGS-GAMA Program grid site, and in areas 

within 500-m buffers of each CDPH site were calculated by 

using Esri ArcGIS® (Johnson and Belitz, 2009; tables B1, 

B2). A 500-m buffer surrounding a site has been shown to be 

effective at correlating urban land use with VOC occurrence 

for the purposes of statistical characterization (Johnson and 

Belitz, 2009). 

Septic Tank and Leaking or Formerly Leaking 

Underground Fuel Tank Density

Septic tanks generally are associated with dispersed 

residences and may occur in areas classified as natural or 

agricultural in addition to areas classified as urban. Septic 

tank density was determined from the 1990 Census of 

Population and Housing: Summary Tape File 3A dataset (U.S. 

Department of Commerce, 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 

buffer around the site (Tyler Johnson, U.S. Geological Survey, 

California Water Science Center, written commun., 2013; 

table B2).

LUFTs generally are associated with urban land use, 

although they may occur in areas classified as natural 

or agricultural. LUFT density was determined from the 

locations of tanks in the SWRCB’s GeoTracker database of 

environmental cleanup sites (California State Water Resources 

Control Board, 2012). The density of LUFTs was calculated 

by using Theissen polygons (Tyler Johnson, U.S. Geological 

Survey, California Water Science Center, written commun., 

2007). The boundaries of the Theissen polygon around a 

particular LUFT were created by bisecting the linear distances 

between the LUFT and all the surrounding LUFTs. The 

density of LUFTs in the polygon is the number of tanks in the 

polygon (generally one) divided by the area of the polygon in 

square kilometers. Each USGS-GAMA grid site was assigned 

the LUFT density of the Theissen polygon in which it is 

located (table B2). 

Well Construction Information

Most well-construction data were from drillers’ logs 

filed with the CDWR. For some wells, well construction 

data were obtained from ancillary records of site owners 

or the USGS National Water Information System (NWIS) 

database. Well depths and depths to the top and bottom of 

perforations for USGS-GAMA grid sites are listed in table B3.

The spring was assigned a value of “at LSD” (at land-surface 

datum) for the well depth and depths to the top and bottom 

of the perforations, equivalent to 0 ft bls. USGS-GAMA grid 

site verification procedures are described by Mathany and 

others (2011). Land-surface altitudes were obtained from 

USGS digital elevation GIS coverages and are reported in 

feet relative to the North American Vertical Datum of 1988 

(NAVD 88) (table B3).

Aridity Index

The climate at each USGS-GAMA grid site was 

represented by an aridity index (United Nations Educational, 

Scientific, and Cultural Organization, 1979; Grove, 1999; 

table B3):

 

 

average annual precipitation aridity index average annual evapotranspiration = . (B1)

Higher values of the index correspond to wetter 

conditions. Average annual precipitation for each site was 

extracted from the PRISM average annual precipitation for 

1971–2000 GIS coverage (PRISM Group, Oregon State 

University, 2012). 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; Alan Flint, U.S. 

Geological Survey, California Water Science Center, oral 

commun., 2009).

Distance to Nearest Hot Spring and 

Geothermal Well

Distances to nearest hot spring and geothermal well 

were used as potential direct indicators of groundwater 

interaction with the localized geothermal systems located 

within the Geysers–Clear Lake area. Hot spring locations 

were obtained from the USGS MRDS, which is a collection of 

reports describing metallic and nonmetallic mineral resources 

throughout the world. Included in the MRDS are deposit 

name, location, commodity, deposit description, geologic 

characteristics, production, reserves, resources, and references 

(U.S. Geological Survey, 2005). Geothermal well locations 

were obtained from the California Department of Conservation 

DOGGR database. DOGGR oversees the drilling, operation, 

maintenance, and plugging and abandonment of oil, natural 

gas, and geothermal wells. Each USGS-GAMA grid site was 

assigned the Euclidean distance, in kilometers, to the nearest 

hot spring and geothermal well using the “Near” tool in the 

Esri ArcGIS® software package (table B3).
72 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Groundwater Age Classification

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 Kamenskiy, 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), by aboveground nuclear explosions, and by the 

operation of nuclear reactors. Tritium enters the hydrologic 

cycle following oxidation to tritiated water. Aboveground 

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 NOCO 

study unit in 2009 would be about 2 to 5 TU (Robert Michel, 

U.S. Geological Survey, California Water Science Center, 

Menlo Park Stable Isotope and Tritium Laboratories, written 

commun., 2013).

Previous investigations have used a range of tritium 

values from 0.3 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 others, 

2005). For groundwater samples collected for the NOCO 

study unit in 2009 (Mathany and others, 2011), tritium values 

greater than a threshold of 0.5 TU were defined as indicating 

presence of 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. 14C activity in groundwater, expressed as percent 

modern carbon (pmc), 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. 

The 14C age (residence time, presented in years) is 

calculated on the basis of the decrease in 14C activity as 

a result of radioactive decay since groundwater recharge, 

relative to an assumed initial 14C concentration (Clark and 

Fritz, 1997). An average initial 14C activity of 100 pmc is 

assumed for this study, with estimated errors on calculated 

groundwater ages up to ±20 percent. Calculated 14C ages in 

this study are referred to as “uncorrected” because they have 

not been adjusted to consider exchanges with sedimentary 

sources of carbon (Fontes and Garnier, 1979). Groundwater 

with a 14C activity of >88 pmc is reported as having an age 

of <1,000 years; no attempt has been made to refine 14C ages 

<1,000 years. Measured values of pmc can be >100 pmc 

because the definition of the 14C activity in “modern” carbon 

does not include the excess 14C produced in the atmosphere by 

aboveground nuclear weapons testing. For the NOCO study 

unit, 14C activity <88 pmc was defined as indicative of the 

presence of groundwater recharged before 1952. 

In this study, the age distributions of samples are 

classified as pre-modern, modern, or mixed ages (table B4). 

Groundwater with tritium activity <0.5 TU and 14C <88 pmc 

is designated as pre-modern, defined as having been recharged 

before 1952. Groundwater with tritium activities >0.5 TU and 

14C >88 pmc is designated as modern, defined as having been 

recharged after 1952. Samples with pre-modern and modern 

components are designated as mixed-age groundwater, which 

includes substantial fractions of old and young waters. In 

reality, pre-modern groundwater could contain very small 

fractions of modern groundwater, and modern groundwater 

could contain small fractions of pre-modern groundwater. 

Although more sophisticated lumped parameter models 

that incorporate mixing are available for analyzing age 

distributions (for example, Cook and Böhlke, 2000), use of 

these alternative models to characterize age mixtures was 

beyond the scope of this report. Rather, classification into 

modern (recharged after 1952), mixed-age, and pre-modern 

(recharged before 1952) categories was sufficient to provide 

an appropriate and useful characterization for the purposes of 

examining groundwater quality.

Classification of Geochemical Condition

Geochemical conditions investigated as potential 

explanatory variables in this report include oxidationreduction (redox) characteristics, pH, and DO (table B5). 

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 (in order of 

least to most reducing) are oxygen-reducing, nitrate-reducing, 

manganese-reducing, iron-reducing, sulfate-reducing, and 

methanogenesis. The presence of redox-sensitive chemical 

species suggesting more than one TEAP may indicate mixed 

waters from different redox zones upgradient of the site, a 

well screened across more than one redox zone, or spatial 

heterogeneity in microbial activity in the aquifer. Different 

redox elements (for example, iron, manganese, and sulfur) 

tend not to reach overall equilibrium in most natural water 

systems (Lindberg and Runnels, 1984); therefore, a single 

redox measurement usually cannot represent the system, 

further complicating the assessment of redox conditions. pH 

is the measure of hydrogen-ion activity in a water sample and 

is sensitive to a number of geochemical reactions in addition 

to redox conditions. DO is a measure of how much oxygen is 

dissolved in a water sample.
Appendix B. Ancillary Datasets 73

Table B2. Land-use percentages, septic tank density, and leaking (or formerly leaking) underground fuel tank (LUFT) density for 

areas within a 500-meter radius of the U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project.—Continued

[USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges 

study unit, Coastal Basins study area. Abbreviation: tanks/km2, tanks per square kilometer]

USGS-GAMA site 

identification number

Land-use percentages1

Septic tank density 

(tanks/km2

)

LUFT density 

(tanks/km2

Agricultural Natural Urban )

Interior Basins study area

NOCO-IN-01 52 27 21 30.8 0.05

NOCO-IN-02 42 6 52 8.0 1.71

NOCO-IN-03 6 93 1 12.5 0.01

NOCO-IN-04 49 14 37 10.7 0.01

NOCO-IN-05 28 9 63 21.6 0.81

NOCO-IN-06 0 100 0 4.1 0.02

NOCO-IN-07 22 78 0 3.5 0.01

NOCO-IN-08 80 20 0 2.3 0.79

NOCO-IN-09 56 44 0 24.9 0.22

NOCO-IN-10 82 18 0 4.3 0.02

NOCO-IN-11 60 2 38 14.7 1.77

NOCO-IN-12 80 19 1 3.8 0.01

NOCO-IN-13 69 22 9 21.8 0.80

NOCO-IN-14 70 25 5 4.7 0.02

NOCO-IN-15 0 99 1 0.1 0

NOCO-IN-16 1 99 0 0.1 0

NOCO-IN-17 88 10 2 4.9 0.08

NOCO-IN-18 93 4 3 12.1 0.01

NOCO-IN-19 78 22 0 5.4 0.05

NOCO-IN-20 0 100 0 3.3 0.02

Table B1. Land-use classification for the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.

[GAMA, Groundwater Ambient Monitoring and Assessment Program]

Land-use category

Agricultural Classification

(percent)

Natural 

(percent)

Urban 

(percent)

Northern Coast Ranges (NOCO) study unit

Study unit as a whole 29 60 11 Natural

Study unit based on buffer areas surrounding grid sites 37 46 17 Mixed

Study unit based on buffer areas surrounding California Department of 

Public Health (CDPH) sites

19 56 25 Natural

Interior Basins (NOCO-IN) study area

Study area as a whole 33 60 7 Natural

Study area based on buffer areas surrounding grid sites 43 47 10 Mixed

Study area based on buffer areas surrounding CDPH sites 36 45 19 Mixed

Coastal Basins (NOCO-CO) study area

Study area as a whole 25 60 14 Natural

Study area based on buffer areas surrounding grid sites 31 46 23 Mixed

Study area based on buffer areas surrounding CDPH sites 11 61 28 Natural
74 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Table B2. Land-use percentages, septic tank density, and leaking (or formerly leaking) underground fuel tank (LUFT) density for 

areas within a 500-meter radius of the U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project.—Continued

[USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges 

study unit, Coastal Basins study area. Abbreviation: tanks/km2, tanks per square kilometer]

USGS-GAMA site 

identification number

Land-use percentages1

Septic tank density 

(tanks/km2

)

LUFT density 

(tanks/km2

Agricultural Natural Urban )

Interior Basins study area—Continued

NOCO-IN-21 84 2 14 11.4 0.01

NOCO-IN-22 23 77 0 1.7 0.01

NOCO-IN-23 0 100 0 12.4 0

NOCO-IN-24 48 29 23 7.2 0.06

NOCO-IN-25 56 44 0 4.8 0.08

NOCO-IN-26 0 100 0 0.3 0

NOCO-IN-27 46 54 0 1.3 0.07

NOCO-IN-28 0 100 0 4.1 0.02

Coastal Basins study area

NOCO-CO-01 0 23 77 21.4 0.40

NOCO-CO-02 78 22 0 0.4 0.02

NOCO-CO-03 34 19 47 7.6 0.57

NOCO-CO-04 0 89 11 3.2 0.14

NOCO-CO-05 0 40 60 39.3 0.50

NOCO-CO-06 0 97 3 7.7 0.43

NOCO-CO-07 0 78 22 1.2 0.02

NOCO-CO-08 58 1 41 31.1 0.79

NOCO-CO-09 37 46 17 7.8 0.45

NOCO-CO-10 5 95 0 3.5 0.02

NOCO-CO-11 61 9 30 8.1 1.49

NOCO-CO-12 49 31 21 20.3 0.03

NOCO-CO-13 0 14 86 23.1 0.04

NOCO-CO-14 0 47 53 44.9 0.10

NOCO-CO-15 0 83 17 0.6 0.01

NOCO-CO-16 0 100 0 0.4 0.02

NOCO-CO-17 90 10 0 17.3 0.02

NOCO-CO-18 2 63 35 9.5 0.11

NOCO-CO-19 99 1 0 2.1 0.46

NOCO-CO-20 1 80 19 1.7 0.18

NOCO-CO-21 80 1 19 2.0 1.17

NOCO-CO-22 88 11 1 5.8 0.05

NOCO-CO-23 44 22 34 24.9 0.37

NOCO-CO-24 1 99 0 12.4 0.11

NOCO-CO-25 9 50 41 7.3 0.63

NOCO-CO-26 0 82 18 1.3 0.33

NOCO-CO-27 93 5 2 1.1 0.04

NOCO-CO-28 0 100 0 1.4 0.19

NOCO-CO-29 95 5 0 3.4 0.10

NOCO-CO-30 1 58 41 4.8 0.19

1

Land-use data from Nakagaki and others (2007). Land-use percentages within 500-meter radius of each USGS-GAMA grid site (Johnson and Belitz, 2009).
Table B3. Well and construction information and hydrologic conditions for U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast RaCalifornia GAMA Priority Basin Project.—Continued[USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges study unit, Coastal B

GAMA, Groundwater Ambient Monitoring and Assessment Program; ft bls, feet below land surface; DOGGR, Division of Oil, Gas, and Geothermal Resources (California Depkilometer; LSD, land-surface datum; na, not available; DOM, domestic well; PSW, public-supply well (California Department of Health); IRR, irrigation well; IND, industrial wspring site; STK, stock well; UNS, unused site; °C, degrees Celsius]

General information Construction information Hydrologic condition

USGSGAMA site 

identification 

number

Altitude 

of LSD 

(ft above 

NAVD 88)1

Site 

type

Well 

depth 

(ft bls)

Depth to 

top of 

perforations 

(ft bls)

Depth to 

bottom of 

perforations 

(ft bls)

Length from top 

of uppermost 

perforated interval 

to bottom of well 

(ft bls)

Aridity 

index2

Field water 

temperature 

(°C) 

Distance to neares

hot spring listed i

the USGS Minera

Resources 

Data System 

(km)

Interior Basins study area

NOCO-IN-01 748 IRR 165 79 157 78 0.85 20.0 12.3 NOCO-IN-02 363 PSW 120 60 120 60 0.88 17.5 12.8 NOCO-IN-03 1,673 DOM 58 33 58 25 1.71 12.5 4.9 NOCO-IN-04 1,385 DOM 55 na na na 1.16 14.0 19.8 NOCO-IN-05 1,633 UNS 60 na na na 1.73 16.0 1.3 NOCO-IN-06 1,342 DOM 136 na na na 0.97 15.0 24.4 

NOCO-IN-07 523 PSW 40 23 38 15 0.83 14.5 12.0 NOCO-IN-08 483 PSW 40 25 40 15 0.82 14.0 18.6 NOCO-IN-09 713 PSW 400 148 385 237 0.84 20.0 9.8 NOCO-IN-10 553 PSW 101 35 94 59 0.80 16.0 8.4 NOCO-IN-11 958 DOM 100 60 100 40 0.92 18.0 15.2 NOCO-IN-12 558 IRR 215 40 215 175 0.82 19.0 10.2 NOCO-IN-13 599 PSW 36 15 36 21 0.82 16.0 3.0 NOCO-IN-14 658 IRR 135 75 135 60 0.81 18.5 4.9 NOCO-IN-15 1,856 PSW 300 80 220 140 1.07 15.5 4.2 NOCO-IN-16 1,845 PSW 152 39 152 113 1.03 15.0 4.0 NOCO-IN-17 1,368 DOM 75 na na na 0.78 18.5 18.3 NOCO-IN-18 1,360 IRR 170 50 160 110 0.65 19.0 30.6 

NOCO-IN-19 823 DOM 80 21 80 59 0.88 18.5 14.2 NOCO-IN-20 1,470 DOM 75 na na na 0.75 23.0 27.7 

Table B3. Well and construction information and hydrologic conditions for U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast RaCalifornia GAMA Priority Basin Project.
Table B3. Well and construction information and hydrologic conditions for U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast RaCalifornia GAMA Priority Basin Project.—Continued [USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges study unit, Coastal B

GAMA, Groundwater Ambient Monitoring and Assessment Program; ft bls, feet below land surface; DOGGR, Division of Oil, Gas, and Geothermal Resources (California Depkilometer; LSD, land-surface datum; na, not available; DOM, domestic well; PSW, public-supply well (California Department of Health); IRR, irrigation well; IND, industrial wspring site; STK, stock well; UNS, unused site; °C, degrees Celsius] General information Construction information Hydrologic condition

USGS- GAMA site identification number Altitude of LSD (ft above NAVD 88)1 Site type Well depth (ft bls) Depth to top of perforations (ft bls) Depth to bottom of perforations (ft bls) Length from top of uppermost perforated interval to bottom of well (ft bls) Aridity index2 Field water temperature (°C) Distance to neares

hot spring listed i

the USGS Minera

Resources Data System (km) 

Interior Basins study area—Continued NOCO-IN-21 361 IRR 52 40 48 8 0.64 18.5 30.9 

NOCO-IN-22 801 IRR 180 na na na 0.80 25.0 0.61 NOCO-IN-23 1,399 DOM 142 40 142 102 0.98 15.0 23.7 NOCO-IN-24 1,380 PSW 116 70 115 45 0.61 18.5 28.5 

NOCO-IN-25 1,072 PSW 283 56 217 161 0.83 19.0 16.0 NOCO-IN-26 1,154 PSW 126 30 114 84 0.48 18.0 5.3 

NOCO-IN-27 1,776 PSW 155 40 115 75 0.71 18.0 22.0 NOCO-IN-28 1,345 DOM 41 na na na 0.98 15.5 24.3 

Coastal Basins study area NOCO-CO-01 71 DOM 25 16 18 2 0.93 13.0 36.8 

NOCO-CO-02 48 PSW 55 35 55 20 0.86 13.5 20.2 NOCO-CO-03 38 PSW 380 280 370 90 1.19 11.0 111 

NOCO-CO-04 243 PSW 325 na na na 1.28 12.5 109 NOCO-CO-05 126 PSW 15 10 10 0 0.99 12.0 42.3 NOCO-CO-06 95 PSW 37 20 37 17 1.01 12.0 37.2 NOCO-CO-07 124 PSW 130 10 130 120 1.54 11.5 102 

NOCO-CO-08 33 PSW 215 150 210 60 1.29 14.5 98.6 NOCO-CO-09 5 IND 397 356 376 20 na 18.0 102 

NOCO-CO-10 115 IRR 225 210 220 10 1.49 13.0 89.8 

NOCO-CO-11 50 PSW 115 43 103 60 1.23 14.5 103 

NOCO-CO-12 56 DOM 62 na na na 1.25 15.5 109 NOCO-CO-13 318 PSW 100 34 100 66 1.48 13.0 99.1 NOCO-CO-14 42 INS 32 20 32 12 1.73 13.0 135 NOCO-CO-15 27 PSW 85 30 85 55 2.15 10.5 113 
Table B3. Well and construction information and hydrologic conditions for U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast RaCalifornia GAMA Priority Basin Project.—Continued[USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges study unit, Coastal B

GAMA, Groundwater Ambient Monitoring and Assessment Program; ft bls, feet below land surface; DOGGR, Division of Oil, Gas, and Geothermal Resources (California Depkilometer; LSD, land-surface datum; na, not available; DOM, domestic well; PSW, public-supply well (California Department of Health); IRR, irrigation well; IND, industrial wspring site; STK, stock well; UNS, unused site; °C, degrees Celsius]

General information Construction information Hydrologic condition

USGSGAMA site 

identification 

number

Altitude 

of LSD 

(ft above 

NAVD 88)1

Site 

type

Well 

depth 

(ft bls)

Depth to 

top of 

perforations 

(ft bls)

Depth to 

bottom of 

perforations 

(ft bls)

Length from top 

of uppermost 

perforated interval 

to bottom of well 

(ft bls)

Aridity 

index2

Field water 

temperature 

(°C) 

Distance to neares

hot spring listed i

the USGS Minera

Resources 

Data System 

(km)

Coastal Basins study area—Continued

NOCO-CO-16 56 PSW 75 38 58 20 2.17 13.0 132 NOCO-CO-17 153 PSW 50 23 50 27 1.28 15.0 96.0 NOCO-CO-18 39 PSW 65 55 60 5 1.26 14.5 106 NOCO-CO-19 37 DOM 50 na na na 1.17 13.5 109 NOCO-CO-20 93 SPR at LSD at LSD at LSD at LSD 1.24 12.5 113 

NOCO-CO-21 24 PSW 168 146 166 20 1.18 14.5 112 

NOCO-CO-22 15 IRR 35 na na na 1.87 13.0 142 NOCO-CO-23 39 PSW 45 35 45 10 2.00 14.5 142 

NOCO-CO-24 24 STK 15 na na na 1.70 12.5 139 NOCO-CO-25 13 IND 193 175 193 18 1.20 14.0 99.8 NOCO-CO-26 267 PSW 15 15 15 0 1.55 12.0 102 NOCO-CO-27 8 DOM 400 na na na 1.20 15.5 110 NOCO-CO-28 18 DOM 120 na na na 1.21 14.0 103 NOCO-CO-29 10 IRR 200 na na na 1.26 13.0 101 NOCO-CO-30 390 PSW 196 166 196 30 1.38 15.5 99.6 

1LSD is a datum plane that is approximately at land surface at each site. The altitude of the LSD is described in feet above the North American Vertical Datum of 1988.2 Aridity index is average annual precipitation (PRISM Group, Oregon State University, 2012) divided by average annual evapotranspiration (Flint and Flint, 2007).
78 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Table B4. Groundwater age classification and the associated data for U.S. Geological Survey (USGS) GAMA grid sites in the Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project.—Continued

[Groundwater age classification: Modern, groundwater recharged since 1952; Pre-modern, groundwater recharged before 1952; Mixed-age, groundwater 

recharged before and after 1952. Well depth classifications: Shallow, wells with depth above 70 ft bls; Mixed-depth, wells with perforations beginning above 

70 ft bls and ending below 70 ft bls; Deep, wells with perforations entirely below 70 ft bls; Mixed-depth or Deep, wells with total well depth below 70 ft bls 

and unknown perforation information. USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; 

NOCO-CO, Northern Coast Ranges study unit, Coastal Basins study area. Abbreviations: ft bls, feet below land surface; 14C, carbon-14; TU, tritium units; 

nc, not collected; <, less than; LSD, land-surface datum]

USGS-GAMA site 

identification number

Tritium 

(TU)

Percent 

modern 

carbon

Uncorrected 14C age 

(years)

Groundwater age 

classification 

Well depth 

classifications

Interior Basins study area 

NOCO-IN-01 0.09 40 7,260 Pre-modern Deep

NOCO-IN-02 1.41 83 1,460 Mixed-age Mixed-depth

NOCO-IN-03 1.31 106 <1,000 Modern Shallow

NOCO-IN-04 1.81 99 <1,000 Modern Shallow

NOCO-IN-05 1.47 58 4,310 Mixed-age Shallow

NOCO-IN-06 –0.06 32 8,970 Pre-modern Mixed-depth or Deep

NOCO-IN-07 2.82 105 <1,000 Modern Shallow

NOCO-IN-08 2.16 88 <1,000 Modern Shallow

NOCO-IN-09 0.09 22 12,030 Pre-modern Deep

NOCO-IN-10 2.16 103 <1,000 Modern Mixed-depth

NOCO-IN-11 1.37 84 1,380 Mixed-age Mixed-depth

NOCO-IN-12 1.06 86 1,130 Mixed-age Mixed-depth

NOCO-IN-13 3.57 105 <1,000 Modern Shallow

NOCO-IN-14 0.81 57 4,520 Mixed-age Deep

NOCO-IN-15 0.37 28 10,290 Pre-modern Deep

NOCO-IN-16 1.78 79 1,850 Mixed-age Mixed-depth

NOCO-IN-17 0.47 77 2,060 Pre-modern Mixed-depth or Deep

NOCO-IN-18 1.31 78 1,900 Mixed-age Mixed-depth

NOCO-IN-19 2.06 105 <1,000 Modern Mixed-depth

NOCO-IN-20 1.41 29 1

9,930 Mixed-age Mixed-depth or Deep

NOCO-IN-21 1.81 106 <1,000 Modern Shallow

NOCO-IN-22 1.00 25 11,200 Mixed-age Mixed-depth or Deep

NOCO-IN-23 2.03 93 <1,000 Modern Mixed-depth

NOCO-IN-24 1.97 89 <1,000 Modern Mixed-depth

NOCO-IN-25 1.78 59 4,120 Mixed-age Mixed-depth

NOCO-IN-26 2.53 99 <1,000 Modern Mixed-depth

NOCO-IN-27 1.06 5 23,780 Mixed-age Mixed-depth

NOCO-IN-28 0.21 10 17,980 Pre-modern Shallow
Appendix B. Ancillary Datasets 79

Table B4. Groundwater age classification and the associated data for U.S. Geological Survey (USGS) GAMA grid sites in the Northern 

Coast Ranges study unit, 2009, California GAMA Priority Basin Project.—Continued

[Groundwater age classification: Modern, groundwater recharged since 1952; Pre-modern, groundwater recharged before 1952; Mixed-age, groundwater 

recharged before and after 1952. Well depth classifications: Shallow, wells with depth above 70 ft bls; Mixed-depth, wells with perforations beginning above 

70 ft bls and ending below 70 ft bls; Deep, wells with perforations entirely below 70 ft bls; Mixed-depth or Deep, wells with total well depth below 70 ft bls 

and unknown perforation information. USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; 

NOCO-CO, Northern Coast Ranges study unit, Coastal Basins study area. Abbreviations: ft bls, feet below land surface; 14C, carbon-14; TU, tritium units; 

nc, not collected; <, less than; LSD, land-surface datum]

USGS-GAMA site 

identification number

Tritium 

(TU)

Percent 

modern 

carbon

Uncorrected 14C age 

(years)

Groundwater age 

classification 

Well depth 

classifications

Coastal Basins study area 

NOCO-CO-01 1.00 57 4,410 Mixed-age Shallow

NOCO-CO-02 1.50 107 <1,000 Modern Shallow

NOCO-CO-03 0.09 75 2,270 Pre-modern Deep

NOCO-CO-04 0.00 14 15,540 Pre-modern Mixed-depth or Deep

NOCO-CO-05 1.94 108 <1,000 Modern Shallow

NOCO-CO-06 2.25 92 <1,000 Modern Shallow

NOCO-CO-07 3.91 103 <1,000 Modern Mixed-depth

NOCO-CO-08 0.68 70 2,760 Mixed-age Deep

NOCO-CO-09 –0.03 9 19,060 Pre-modern Deep

NOCO-CO-10 1.15 75 2,290 Mixed-age Deep

NOCO-CO-11 1.69 95 <1,000 Modern Mixed-depth

NOCO-CO-12 0.37 79 1,830 Pre-modern Shallow

NOCO-CO-13 1.72 90 <1,000 Modern Mixed-depth

NOCO-CO-14 1.47 nc nc Modern or Mixed-age Shallow

NOCO-CO-15 1.88 101 <1,000 Modern Mixed-depth

NOCO-CO-16 2.31 104 <1,000 Modern Mixed-depth

NOCO-CO-17 2.38 93 <1,000 Modern Shallow

NOCO-CO-18 1.78 86 1,110 Mixed-age Shallow

NOCO-CO-19 1.63 104 <1,000 Modern Shallow

NOCO-CO-20 1.66 67 3,210 Mixed-age at LSD

NOCO-CO-21 0.75 58 4,280 Mixed-age Deep

NOCO-CO-22 1.47 107 <1,000 Modern Shallow

NOCO-CO-23 1.88 102 <1,000 Modern Shallow

NOCO-CO-24 1.25 103 <1,000 Mixed-age Shallow

NOCO-CO-25 –0.03 10 18,510 Pre-modern Deep

NOCO-CO-26 1.94 107 <1,000 Modern Shallow

NOCO-CO-27 –0.06 5 23,550 Pre-modern Mixed-depth or Deep

NOCO-CO-28 –0.06 53 1

5,010 Pre-modern Mixed-depth or Deep

NOCO-CO-29 2.88 77 1,990 Mixed-age Mixed-depth or Deep

NOCO-CO-30 3.22 60 4,100 Mixed-age Deep

1

Sample oxidation-reduction state was anoxic (table B5), and stable carbon isotope ratio was greater than –10 per mil, suggesting that the carbon isotope 

composition of the sample may have been altered by methanogenesis. The uncorrected carbon-14 apparent age thus may be too old.
80 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Table B5. Oxidation-reduction classification based on McMahon and Chapelle (2008), dissolved oxygen concentration, and pH for 

U.S. Geological Survey (USGS) GAMA grid sites in the Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.

[Oxidation-reduction classification: Mn-red, manganese-reducing; Fe-red, iron-reducing; MnFe-red, manganese- and iron-reducing; NO3MnFe-red, nitrate-, 

manganese-, and iron-reducing; NO3Mn-red, nitrate- and manganese-reducing. USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges 

study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges study unit, Coastal Basins study area. Abbreviations: GAMA, Groundwater Ambient 

Monitoring and Assessment Program; mg/L, milligrams per liter; <, less than]

USGSGAMA site 

identification 

number

Dissolved 

oxygen 

(mg/L)

pH 

(standard 

units) 

Oxidation-reduction 

classification1

Interior Basins study area

NOCO-IN-01 0.7 7.5 Anoxic Mn-red

NOCO-IN-02 7.0 7.2 Oxic

NOCO-IN-03 0.7 6.1 Anoxic Fe-red

NOCO-IN-04 10.9 6.3 Mixed (Oxic/Anoxic Fe-red) 

NOCO-IN-05 0.3 6.7 Anoxic MnFe-red

NOCO-IN-06 0.4 7.2 Anoxic MnFe-red

NOCO-IN-07 1.3 6.0 Oxic

NOCO-IN-08 5.5 6.6 Oxic

NOCO-IN-09 0.1 7.5 Anoxic MnFe-red

NOCO-IN-10 5.0 6.4 Oxic

NOCO-IN-11 0.3 6.8 Anoxic NO3

MnFe-red

NOCO-IN-12 2.2 6.9 Oxic

NOCO-IN-13 3.8 6.1 Oxic

NOCO-IN-14 <0.2 7.3 Anoxic MnFe-red

NOCO-IN-15 <0.2 7.1 Anoxic suboxic

NOCO-IN-16 1.9 6.4 Oxic

NOCO-IN-17 6.2 6.9 Oxic

NOCO-IN-18 1.3 6.7 Oxic

NOCO-IN-19 2.6 6.0 Oxic

NOCO-IN-20 0.3 6.3 Anoxic MnFe-red

NOCO-IN-21 <0.2 6.8 Anoxic MnFe-red

NOCO-IN-22 0.5 7.4 Anoxic MnFe-red

NOCO-IN-23 1.9 7.2 Oxic

NOCO-IN-24 3.8 7.3 Oxic

NOCO-IN-25 0.7 7.5 Anoxic Fe-red

NOCO-IN-26 4.8 6.7 Oxic

NOCO-IN-27 <0.2 6.0 Anoxic MnFe-red

NOCO-IN-28 <0.2 7.2 Anoxic Mn-red

USGSGAMA site 

identification 

number

Dissolved 

oxygen 

(mg/L)

pH 

(standard 

units) 

Oxidation-reduction 

classification1

Coastal Basins study area

NOCO-CO-01 <0.2 7.2 Anoxic MnFe-red

NOCO-CO-02 11.8 6.5 Oxic

NOCO-CO-03 1.3 7.7 Oxic

NOCO-CO-04 <0.2 7.5 Anoxic MnFe-red

NOCO-CO-05 5.2 5.6 Oxic

NOCO-CO-06 4.1 6.5 Oxic

NOCO-CO-07 10.4 6.5 Oxic

NOCO-CO-08 <0.2 7.5 Anoxic suboxic

NOCO-CO-09 <0.2 7.5 Anoxic MnFe-red

NOCO-CO-10 3.3 7.8 Oxic

NOCO-CO-11 1.3 6.7 Oxic

NOCO-CO-12 1.1 6.8 Oxic

NOCO-CO-13 7.1 6.3 Oxic

NOCO-CO-14 9.7 7.7 Oxic

NOCO-CO-15 6.9 6.4 Oxic

NOCO-CO-16 7.9 6.7 Oxic

NOCO-CO-17 3.1 6.5 Oxic

NOCO-CO-18 0.3 6.5 Anoxic NO3

MnFe-red

NOCO-CO-19 0.2 6.6 Anoxic NO3

Mn-red

NOCO-CO-20 6.1 7.5 Oxic

NOCO-CO-21 0.4 7.0 Anoxic NO3

MnFe-red

NOCO-CO-22 7.5 6.7 Oxic

NOCO-CO-23 6.3 6.2 Oxic

NOCO-CO-24 0.8 6.8 Anoxic MnFe-red

NOCO-CO-25 0.3 6.7 Anoxic Mn-red

NOCO-CO-26 4.2 5.5 Oxic

NOCO-CO-27 0.2 6.8 Anoxic MnFe-red

NOCO-CO-28 0.4 7.2 Anoxic MnFe-red

NOCO-CO-29 0.4 7.3 Anoxic NO3

Mn-red

NOCO-CO-30 4.6 7.1 Oxic

1

Data from Mathany and others (2011) were used for the classification, in 

addition to the dissolved oxygen and pH data presented in this table.
Appendix C. Calculation of Aquifer-Scale ProportionsTable C1. Aquifer-scale proportions calculated for the Interior Basins study area, using grid-based and spatially weighted methods for those constitadditional evaluation in the status assessment, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project.[Relative-concentration categories: high, concentration greater than water-quality benchmark; moderate, concentration is less than the benchmark and is greater than or equal torganic and special-interest constituents) or 0.5 of the benchmark (for inorganic constituents); low, concentration less than 0.1 of benchmark (for organic constituents and speciathe benchmark (for inorganic constituents). Abbreviations: Groundwater Ambient Monitoring and Assessment Program; CDPH, California Department of Public Health; TDS, methyl tert-butyl ether; μg/L, micrograms per liter]

Constituent

Raw detection frequency,

in percent1

Spatially weighted 

aquifer-scale proportion,

in percent1

Grid-based aquifer-scale proportion,

in percent

Number 

of sites Moderate High Number of cells Moderate aquifer proportion High aquifer proportion Number of sites Moderate aquifer proportion High aquifer proportion 

Inorganic constituents with health-based benchmarksTrace ElementsArsenic 71 2.8 4.2 28 5.4 7.1 28 7.1 7.1 

Barium 71 0 1.4 28 0 3.6 28 0 3.6 

Boron3 28 7.1 17.9 28 7.1 17.9 28 7.1 17.9 

Nickel 71 0 0 28 0 0 28 0 0 

NutrientsNitrate 92 0 0 28 0 0 28 0 0 

Inorganic constituents with aesthetic-based benchmarksIron 60 8.3 26.7 28 12.2 27.7 28 10.7 25.0 

Manganese 62 3.2 37.1 28 7.1 46.1 28 7.1 42.9 

TDS 58 8.6 0 28 13.7 0 28 14.3 0 

Organic constituents with health-based benchmarksVolatile organic compoundsChloroform (Trichloromethane) 53 1.9 0 28 2.3 0 28 3.7 0 

Vinyl chloride (Chloroethene) 52 1.9 0 28 3.6 0 28 3.6 0 

MTBE4 67 0 1.5 28 0 0.5 28 0 0 

Pesticides and pesticide degradatesSimazine 70 0 0 28 0 0 28 0 0 

Special-interest constituent with health-based benchmarkPerchlorate 78 0 0 28 0 0 28 0 0 

1Based on most recent analyses for each CDPH site during June 1, 2006−June 1, 2009, combined with data from USGS-GAMA grid sites.2Based on the Jeffrey’s interval for the binomial distribution (Brown and others, 2001).3Boron was not sampled by the CDPH during June 1, 2006−June 1, 2009.4High relative-concentrations of MTBE were reported multiple times in the CDPH water-quality database from one site in the NOCO-IN study area during the current period 

samples were collected by the CDPH between August 16, 2006, and May 20, 2009, from this site for analysis of MTBE; 15 had concentrations of MTBE between 13 and 21 μg/was a non-detection (most recent value, May 20, 2009). On that basis, it was determined that the non-detection of MTBE reported as the most recent value in the CDPH water-q

sent present-day conditions. The MTBE sample collected on April 30, 2009 (17 μg/L) was substituted in order to more accurately reflect present-day conditions.
Table C2. Aquifer-scale proportions calculated for the Coastal Basins study area, using grid-based and spatially weighted methods for those constitadditional evaluation in the status assessment, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. [Relative-concentration categories: high, concentration greater than water-quality benchmark; moderate, concentration is less than the benchmark and is greater than or equal torganic and special-interest constituents) or 0.5 of the benchmark (for inorganic constituents); low, concentration less than 0.1 of benchmark (for organic constituents and speciathe benchmark (for inorganic constituents). Abbreviations: GAMA, Groundwater Ambient Monitoring and Assessment Program; CDPH, California Department of Public Healt

solved solids; MTBE, methyl tert-butyl ether] Constituent Raw detection frequency, in percent1 Spatially weighted aquifer-scale proportion, in percent1 Grid-based aquifer-scale proportion, in percent 

Number of sites Moderate High Number of cells Moderate aquifer proportion High aquifer proportion Number of sites Moderate aquifer proportion High aquifer proportion 

Inorganic constituents with health-based benchmarks Trace Elements Arsenic 59 3.4 1.7 30 6.7 0.2 30 6.7 0 

Barium 60 0 0 30 0 0 30 0 0 

Boron3 30 3.3 0 30 3.3 0 30 3.3 0 

Nickel 62 1.7 0 30 3.3 0 30 3.3 0 

Nutrients Nitrate 128 3.1 0 30 2.7 0 29 6.9 0 

Inorganic constituents with aesthetic-based benchmarks Iron 61 4.9 16.4 30 1.0 23.9 30 0 26.7 

Manganese 61 4.9 24.6 30 8.3 36.7 30 10.0 36.7 

TDS 60 1.7 0 30 0.6 0 30 0 0 

Organic constituents with health-based benchmarks Volatile organic compounds Chloroform (Trichloromethane) 65 1.5 0 30 0.8 0 30 0 0 

Vinyl chloride (Chloroethene) 63 0 0 30 0 0 30 0 0 

MTBE 67 0 0 30 0 0 30 0 0 

Pesticides and pesticide degradates Simazine 53 0 0 30 0 0 30 0 0 

Special-interest constituent with health-based benchmark Perchlorate 84 1.2 0 30 1.1 0 30 3.3 0 

1Based on most recent analyses for each CDPH site during June 1, 2006−June 1, 2009, combined with data from USGS-GAMA grid sites.2Based on the Jeffrey’s interval for the binomial distribution (Brown and others, 2001).3Boron was not sampled by the CDPH during June 1, 2006−June 1, 2009.
Appendix D. Comparison of CDPH and GAMA Priority Basin Data 83

Appendix D. Comparison of CDPH and GAMA Priority Basin Data

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 (calcium, magnesium, sodium, alkalinity, chloride, 

sulfate, TDS, and nitrate), which generally are prevalent at 

concentrations substantially greater than reporting levels, were 

compared for each site by using data from both sources. The 

USGS and CDPH water-quality databases contained data for 

major ions, trace elements, TDS, or nitrate (as nitrogen) for 

17 of 58 sites. Wilcoxon rank-sum tests of paired analyses for 

these eight constituents indicated no significant differences 

between USGS-GAMA and CDPH data for these constituents. 

Although differences between the paired datasets occurred 

for some sites (most notably nitrate, as nitrogen), most 

sample pairs plotted close to a 1:1 line (fig. D1). These direct 

comparisons indicated that the USGS-GAMA and CDPH 

inorganic data were not significantly different.

Major-ion data from USGS-GAMA grid sites were 

plotted on a trilinear diagram (Piper, 1944) along with all 

CDPH major-ion data to determine whether the groundwater 

types in the USGS-GAMA grid sites were similar to 

groundwater types observed historically 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, 1989). All cation and anion data in the CDPH waterquality database with a cation and anion imbalance less than 

10 percent were retrieved and plotted on the trilinear diagram 

for comparison with USGS-GAMA grid site data.

Concentration, USGS data, in milligrams per liter

Concentration, CDPH data, in milligrams per liter

0.1

1

10

100

1,000

0.1 1 10 100 1,000 

Calcium 

Magnesium 

Sodium 

Chloride Alkalinity 

Sulfate TDS 

Nitrate 1-to-1 line

EXPLANATION

Figure D1. Paired inorganic constituent concentrations from sites sampled by the USGS-GAMA Program from June to November 2009 

and from the CDPH database for the same sites during the period June 1, 2006–June 1, 2009, Northern Coast Ranges study unit, 

California GAMA Priority Basin Project. 
84 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Percent

Calcium

 100 

 80 

 60 

 40 

 20  0 

 0 

 20 

 40 

 60 

 80 

 100 

Magnesium

 0 

 20 

 40 

 60 

 80 

 100 

Sodium plus Potassium

Chloride, Fluoride, Nitrite plus Nitrate

 0 

 20 

 40 

 60 

 80 

 100 

 100 

 80 

 60 

 40 

 20 

 0 

Bicarbonate

 100 

 80 

 60 

 40 

 20 

 0 

Sulfate

 0 

 20 

 40 

 60 

 80 

 100 

Sulfate plus Chloride

 0 

 20 

 40 

 60 

 80 

 100 

Calcium plus Magnesium

 100 

 80 

 60 

 40 

 20 

 0 

 100 

 80 

 60 

 40 

 20 

 0 

Percent

Percent

EXPLANATION

USGS-grid site

CDPH site

sac14-0547_Figure D02 Grid wells_NOCO

Figure D2. Selected inorganic data from USGS-GAMA grid sites and from all sites in the CDPH database that have a charge imbalance 

of less than 10 percent, Northern Coast Ranges study unit, 2009, California GAMA Priority Basin Project. 

The ranges of water types for USGS-GAMA grid sites 

and other sites from the CDPH water-quality database were 

similar (fig. D2). In most water samples from the sites, no 

single cation accounted for more than 60 percent of the total 

cations, and bicarbonate accounted for more than 60 percent 

of the total anions. Waters in these sites are described as mixed 

cation–bicarbonate type waters. Some sites contained calcium/

magnesium–bicarbonate type waters, for which calcium 

plus magnesium and bicarbonate accounted for more than 

60 percent of the cations and anions, respectively. Waters in 

a minority of sites were classified as sodium-chloride type 

waters, indicating that sodium and chloride accounted for more 

than 60 percent of the total cations and anions, respectively. 

The determination that the range of relative abundance of 

major cations and anions in USGS-GAMA grid sites (58 sites) 

is similar to the range of those in all CDPH sites (60 sites) 

indicates that the grid sites represent the types of water present 

in the NOCO study unit.
Appendix E. Additional Water-Quality Data 85

Appendix E. Additional Water-Quality Data

Table E1 presents the data generated at Lawrence Livermore National Laboratory (LLNL) for dissolved noble gases (argon, 

helium-4, krypton, neon, and xenon) and helium isotope ratios. These results were not completed in time for inclusion in the 

U.S. Geological Survey (USGS) Data Series Report for the Northern Coast Ranges (NOCO) study unit (U.S. Geological Survey 

Data Series 609, Mathany and others, 2011) and are included in this report for completeness.

Table E1. Results from the Lawrence Livermore National Laboratory (LLNL) analyses of dissolved noble gases and helium isotope 

ratios in samples from U.S. Geological Survey (USGS) GAMA grid sites collected for the Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project.—Continued

[The five-digit number in parentheses below the constituent name is the USGS parameter code used to uniquely identify a specific constituent or property. 

USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges 

study unit, Coastal Basins study area. Measurement errors: Helium-3/Helium-4 ratios: 1% error; helium-4 and argon concentrations: 2% error; krypton 

concentrations: 3% error; neon and xenon concentrations: 4% error. Abbreviations: g–1 H2O, pressure per gram of water; R, helium-3/helium-4 ratio of the 

groundwater sample; Ra, helium-3/helium-4 ratio in the atmosphere; na, not available]

USGS-GAMA site 

identification 

number

Helium-4 

(g–1H2

O) 

(85561)

x 10–8

Neon 

(g–1H2

O) 

(61046)

x 10–7

Argon 

(g–1H2

O) 

(85563)

x 10–4

Krypton 

(g–1H2

O) 

(85565)

x 10–8

Xenon 

(g–1H2

O) 

(85567)

x 10–8

Helium-3/

Helium-4 

(atom ratio) 

(61040)

x 10–6

Helium-3/

Helium-4 

(R/Ra) 

Interior Basins study area

NOCO-IN-01 9.38 2.83 4.18 8.48 1.13 1.10 0.8

NOCO-IN-02 19.75 7.27 7.20 0.13 1.59 1.44 1.0

NOCO-IN-03 5.38 3.49 4.05 8.28 1.16 1.43 1.0

NOCO-IN-04 20.28 7.25 8.46 18.22 2.37 1.37 1.0

NOCO-IN-05 38.48 1.73 8.42 7.34 1.27 0.32 0.2

NOCO-IN-06 13.23 3.58 4.56 9.53 1.25 1.01 0.7

NOCO-IN-07 5.71 2.12 3.60 8.13 1.25 1.24 0.9

NOCO-IN-08 4.88 2.15 3.51 7.38 1.12 1.37 1.0

NOCO-IN-09 18.85 2.51 3.79 8.10 1.14 0.52 0.4

NOCO-IN-10 4.56 2.85 3.61 7.54 1.01 1.39 1.0

NOCO-IN-11 55.56 3.71 3.54 6.52 0.77 0.16 0.1

NOCO-IN-12 4.37 1.80 2.98 6.63 0.95 1.37 1.0

NOCO-IN-13 5.40 2.31 3.78 8.44 1.27 1.39 1.0

NOCO-IN-14 10.84 3.63 4.71 9.53 1.48 1.18 0.8

NOCO-IN-15 13.27 2.75 4.13 8.61 1.33 0.71 0.5

NOCO-IN-16 5.23 2.26 3.41 7.30 1.03 1.40 1.0

NOCO-IN-17 137.4 38.39 9.14 17.19 1.74 1.45 1.0

NOCO-IN-18 8.00 2.72 3.89 8.22 1.14 1.62 1.2

NOCO-IN-19 5.49 2.33 3.74 8.17 1.23 1.39 1.0

NOCO-IN-20 na na na na na na na

NOCO-IN-21 5.54 2.11 3.41 7.73 1.07 1.74 1.2

NOCO-IN-22 65.36 2.65 4.19 7.74 1.04 6.95 5.0

NOCO-IN-23 8.44 3.79 4.37 9.01 1.17 1.44 1.0

NOCO-IN-24 6.86 2.67 3.22 6.65 0.97 1.39 1.0

NOCO-IN-25 25.40 2.37 3.64 7.19 0.99 0.53 0.4

NOCO-IN-26 4.69 2.05 3.25 7.15 0.99 1.29 0.9

NOCO-IN-27 3.87 1.74 1.16 2.78 4.27 1.15 0.8

NOCO-IN-28 49.62 3.34 4.45 9.21 1.29 0.40 0.3
86 Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009

Table E1. Results from the Lawrence Livermore National Laboratory (LLNL) analyses of dissolved noble gases and helium isotope 

ratios in samples from U.S. Geological Survey (USGS) GAMA grid sites collected for the Northern Coast Ranges study unit, 2009, 

California GAMA Priority Basin Project.—Continued

[The five-digit number in parentheses below the constituent name is the USGS parameter code used to uniquely identify a specific constituent or property. 

USGS-GAMA site identification numbers: NOCO-IN, Northern Coast Ranges study unit, Interior Basins study area; NOCO-CO, Northern Coast Ranges 

study unit, Coastal Basins study area. Measurement errors: Helium-3/Helium-4 ratios: 1% error; helium-4 and argon concentrations: 2% error; krypton 

concentrations: 3% error; neon and xenon concentrations: 4% error. Abbreviations: g–1 H2O, pressure per gram of water; R, helium-3/helium-4 ratio of the 

groundwater sample; Ra, helium-3/helium-4 ratio in the atmosphere; na, not available]

USGS-GAMA site 

identification 

number

Helium-4 

(g–1H2

O) 

(85561)

x 10–8

Neon 

(g–1H2

O) 

(61046)

x 10–7

Argon 

(g–1H2

O) 

(85563)

x 10–4

Krypton 

(g–1H2

O) 

(85565)

x 10–8

Xenon 

(g–1H2

O) 

(85567)

x 10–8

Helium-3/

Helium-4 

(atom ratio) 

(61040)

x 10–6

Helium-3/

Helium-4 

(R/Ra) 

Coastal Basins study area

NOCO-CO-01 3.70 1.45 3.30 8.24 1.43 1.21 0.9

NOCO-CO-02 5.15 2.20 3.58 7.93 1.09 1.30 0.9

NOCO-CO-03 5.17 2.22 3.81 8.70 1.22 1.37 1.0

NOCO-CO-04 6.59 2.84 4.46 10.09 1.70 1.26 0.9

NOCO-CO-05 3.70 1.55 3.19 7.34 1.22 1.45 1.0

NOCO-CO-06 24.91 8.06 6.68 11.73 1.44 1.46 1.0

NOCO-CO-07 5.91 2.55 3.96 8.92 1.24 2.13 1.5

NOCO-CO-08 5.95 2.24 3.87 8.42 1.25 1.59 1.1

NOCO-CO-09 76.99 2.41 8.30 7.80 1.44 0.24 0.2

NOCO-CO-10 6.37 2.93 4.36 9.42 1.27 1.63 1.2

NOCO-CO-11 10.53 4.25 4.72 9.76 1.30 1.42 1.0

NOCO-CO-12 4.80 2.15 3.67 8.67 1.20 1.37 1.0

NOCO-CO-13 5.76 2.09 3.62 8.43 1.09 1.20 0.9

NOCO-CO-14 na na na na na na na

NOCO-CO-15 5.17 2.30 3.72 8.46 1.18 1.30 0.9

NOCO-CO-16 5.63 2.86 4.00 9.24 1.23 1.40 1.0

NOCO-CO-17 4.77 2.08 3.52 7.92 1.28 1.36 1.0

NOCO-CO-18 5.61 2.35 3.93 8.76 1.35 1.39 1.0

NOCO-CO-19 6.16 2.62 4.32 9.42 1.54 1.40 1.0

NOCO-CO-20 4.42 1.99 3.67 8.37 1.21 1.39 1.0

NOCO-CO-21 6.81 2.58 4.85 7.36 1.31 1.31 0.9

NOCO-CO-22 6.66 2.60 4.28 9.33 1.41 1.37 1.0

NOCO-CO-23 4.54 1.97 3.43 7.41 1.04 1.41 1.0

NOCO-CO-24 72.59 2.70 4.66 9.15 1.45 0.35 0.3

NOCO-CO-25 40.69 2.38 4.20 9.27 1.37 0.41 0.3

0.0

NOCO-CO-26 5.05 2.11 3.87 9.03 1.38 1.36 1.0

NOCO-CO-27 23.28 2.36 8.75 8.47 1.66 0.43 0.3

NOCO-CO-28 na na na na na na na

NOCO-CO-29 4.27 4.06 4.62 2.97 0.37 2.64 1.9

NOCO-CO-30 6.19 3.24 4.14 7.78 0.88 1.40 1.0
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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

Printed on recycled paper

Mathany and Belitz—Status and Understanding of Groundwater Quality in the Northern Coast Ranges Study Unit, 2009: 

California GAMA Priority Basin Project—SIR 2014–5215

Printed on recycled paper

ISSN 2328-031X (print)

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20145215