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Scientific Investigations Report 2014–5065

A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program
Prepared in cooperation with the California State Water Resources Control Board

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

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

Thumbnail of and link to report PDF (10 MB)Abstract

Groundwater quality in the Klamath Mountains (KLAM) study unit was investigated as part of the Priority Basin Project of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in Del Norte, Humboldt, Shasta, Siskiyou, Tehama, and Trinity Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.

The GAMA Priority Basin Project was designed to provide a spatially unbiased, statistically robust assessment of the quality of untreated (raw) groundwater in the primary aquifer system. The assessment is based on water-quality data and explanatory factors for groundwater samples collected in 2010 by the USGS from 39 sites and on water-quality data from the California Department of Public Health (CDPH) water-quality database. The primary aquifer system was defined by the depth intervals of the wells listed in the CDPH water-quality database for the KLAM study unit. The quality of groundwater in the primary aquifer system may be different from that in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.

This study included two types of assessments: (1) a status assessment, which characterized the status of the current quality of the groundwater resource by using data from samples analyzed for volatile organic compounds, pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements, and (2) an understanding assessment, which evaluated the natural and human factors potentially affecting the groundwater quality. The assessments were intended to characterize the quality of groundwater resources in the primary aquifer system of the KLAM study unit, not the quality of treated drinking water delivered to consumers by water purveyors.

Relative-concentrations (sample concentrations divided by the health- or aesthetic-based benchmark concentrations) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents were classified as “high” (relative-concentration > 1.0), “moderate” (0.1 < relative-concentration ≤ 1.0), or “low” (relative-concentration ≤ 0.1). For inorganic constituents, the boundary between low and moderate relative-concentration was set at 0.5.

Aquifer-scale proportion was used in the status assessment as the primary metric for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentages of the primary aquifer system with moderate and low relative-concentrations, respectively.

The KLAM study unit includes more than 8,800 square miles (mi2), but only those areas near the sampling sites, about 920 mi2, are included in the areal assessment of the study unit. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. To confirm this methodology, 90 percent confidence intervals were calculated for the grid-based high aquifer-scale proportions and were compared to the spatially weighted results, which were found to be within these confidence intervals in all cases. Grid-based results were selected for use in the status assessment unless, as was observed in a few cases, a grid-based result was zero and the spatially weighted result was not zero, in which case, the spatially weighted result was used.

The status assessment showed that inorganic constituents with human-health benchmarks were detected at high relative-concentrations in 2.6 percent of the primary aquifer system and at moderate relative-concentrations in 10 percent of the system. The high aquifer-scale proportion for inorganic constituents mainly reflected the high aquifer-scale proportions of boron. Inorganic constituents with secondary maximum contaminant levels were detected at high relative-concentrations in 13 percent of the primary aquifer system and at moderate relative-concentrations in 10 percent of the system. The constituents present at high relative-concentrations included iron and manganese.

Organic constituents with human-health benchmarks were not detected at high relative-concentrations, but were detected at moderate relative-concentrations in 1.9 percent of the primary aquifer system. The 1.9 percent reflected a spatially weighted moderate aquifer-scale proportion for the gasoline additive methyl tert-butyl ether. Of the 148 organic constituents analyzed, 14 constituents were detected. Only one organic constituent had a detection frequency of greater than 10 percent—the trihalomethane, chloroform.

The second component of this study, the understanding assessment, identified the natural and human factors that may have affected the groundwater quality in the KLAM study unit by evaluating statistical correlations between water-quality constituents and potential explanatory factors. The potential explanatory factors evaluated were aquifer lithology, land use, hydrologic conditions, depth, groundwater age, and geochemical conditions. Results of the statistical evaluations were used to explain the occurrence and distribution of constituents in the KLAM study unit.

Groundwater age distribution (modern, mixed, or pre-modern), redox class (oxic, mixed, or anoxic), and dissolved oxygen concentration were the explanatory factors that best explained occurrence patterns of the inorganic constituents. High concentrations of boron were found to be associated with groundwater classified as mixed or pre-modern with respect to groundwater age. Boron was also negatively correlated to dissolved oxygen and positively correlated to specific conductance. Iron and manganese concentrations were strongly associated with low dissolved oxygen concentrations, anoxic and mixed redox classifications, and pre-modern groundwater. Specific conductance concentrations were found to be related to pre-modern groundwater, low dissolved oxygen concentrations, and high pH.

Chloroform was selected for additional evaluation in the understanding assessment because it was detected in more than 10 percent of wells sampled in the KLAM study unit. Septic tank density was the only explanatory factor that was found to relate to chloroform concentrations.

First posted September 5, 2014

For additional information, contact:
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

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Suggested citation:

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

ISSN 2328-031X (print)

ISSN 2328-0328 (online)





Hydrogeologic Setting and Potential Explanatory Factors

Status and Understanding of Groundwater Quality




Appendix A. Attribution of Potential Explanatory Factors

Appendix B. Grid Cells and Sites

Appendix C. Calculation of Aquifer-Scale Proportions

Appendix D. Comparison of CDPH and USGS–GAMA Data

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