Geology Reports⌕ Search

USGS · sir20145215

Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project

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 relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (&le;) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents and perchlorate were classified as &ldquo;high&rdquo; (relative-concentration >1.0), &ldquo;moderate&rdquo; (0.1 < relative-concentration &le;1.0), or &ldquo;low&rdquo; (relative-concentration &le;0.1). Relative-concentrations of inorganic constituents were classified as &ldquo;high&rdquo; (relative-concentration >1.0), &ldquo;moderate&rdquo; (0.5 < relative-concentration &le;1.0), or &ldquo;low&rdquo; (relative-concentration &le;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 relative-concentrations, respectively. Two statistical approaches&mdash;grid-based and spatially weighted&mdash;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 aquifer-scale 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). 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 &le;70 feet below land surface, with modern water (post-1950s), and with oxic groundwater conditions.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 38.66835610151509° to 41.96765920367816° latitude; -124.541015625° to -121.79443359375° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Timothy M. Mathany, Kenneth Belitz. 2015. Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project. https://doi.org/10.3133/sir20145215

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Analysis of groundwater geochemistry in the Lansing, Michigan, area

Groundwater resources in the Lansing, Michigan, area are protected by a wellhead protection plan, but previous studies have indicated that groundwater in this area may be susceptible to surface contamination. The U.S. Geological Survey, in cooperation with the Lansing Board of Water & Light, analyzed geochemical and aquifer characteristics to assess the potential for contamination of groundwater resources. Recharge age categories were determined from tritium concentrations for some wells, and by using ternary diagrams and principal component analysis for other wells. These age classifications, combined with hydrogeologic and geochemical data, were analyzed by using statistical methods to identify trends that may indicate areas of increased groundwater susceptibility. Wells with modern recharge tended to have higher sodium, chloride, and chloride:bromide ratios than did wells with mixed recharge, suggesting greater surface connectivity and potential influence from anthropogenic sources such as road salt. In contrast, wells in the mixed age category exhibited more stable geochemistry and lower constituent concentrations. Classification and regression tree models identified aquifer geometry—particularly the thickness of the uppermost bedrock unit and presence of confining layers—as key predictors of recharge age and geochemical indicators. The trends identified from these analyses could help to reveal locations in the Lansing area that are among the most susceptible to contamination.

Scientific Investigations Report↗

Evaluating the number of realizations (train-test splits) necessary to ensure robust estimates of conventional hydrothermal resource favorability using Monte Carlo cross-validation, the Great Basin, Western USA

Supervised machine learning approaches used to produce favorability maps in resource assessments commonly partition an input dataset into training and testing subsets (that is, through train-test splits). However, if a single split is not representative of underlying resource conditions, the resulting favorability map may be biased, particularly with sparse or heterogeneous datasets. To mitigate the potential for unrepresentative favorability maps, recent works by U.S. Geological Survey researchers have used Monte Carlo cross-validation to implement a large number ( n) of randomized train-test splits to produce n realizations. The realizations are then aggregated using cell-wise median predictions to produce the resulting final favorability map, recognizing that the median will remove extreme values that might have been estimated from a comparatively few unrepresentative realizations. Theoretically, the median prediction at every cell converges to a single estimate as n approaches infinity, and the question addressed herein is: How many realizations are necessary to get a robust estimate (that is, an estimate unaffected by additional realizations)? Therefore, convergence metrics are described to identify the number of train-test splits and realizations needed to make a reliable map using the data and supervised machine learning workflow for conventional hydrothermal resource assessment of the Great Basin of the Western United States. For this study, robust prediction occurs with n approximately equal to 600 realizations, and smaller ensembles (for example, n is approximately equal to 200 or even 100) may be suitable during preliminary or exploratory analyses. Although the resulting threshold numbers will vary depending on the data and modeling approach used, the convergence metrics proposed and applied herein are applicable to other supervised machine learning studies that use Monte Carlo cross-validation.

California, Idaho, Nevada, Oregon, Utah↗

Groundwater budget for the Portneuf River Basin, southeastern Idaho

The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, developed the first groundwater budget for the upper Portneuf River Basin in southeastern Idaho, a tributary of the Snake River. A groundwater budget for the Portneuf River Basin supports water resource and administrative management decisions within the basin and for downstream users of the eastern Snake River Plain aquifer. The analysis quantifies inflows, outflows, and residuals for an aquifer system defined by the Idaho Department of Water Resources under three recent precipitation conditions: an average year (2016), a dry year (2021), and a wet year (2023). The budget was calculated for the basin and for two subbasins delineated by the U.S. Geological Survey streamgage Portneuf River at Topaz, Idaho (13073000): the above Topaz subbasin, which includes the Portneuf-Gem valley, and the below Topaz subbasin, which includes Marsh Valley. Aquifer inflows include mountain-front recharge; areal recharge; recharge from applied water, including recharge from irrigation, canal seepage, and effluent returns; groundwater flow into the basin; and reservoir seepage. Outflows include groundwater pumping for agricultural, municipal, and domestic uses; subsurface outflow through the Portneuf gap; and discharge to streams as base flow. Estimated annual inflows for the full basin ranged from 116,880 acre-feet in 2021 to 154,880 acre-feet in 2023, and outflows ranged from 132,190 acre-feet in 2016 to 158,490 acre-feet in 2023. Basinwide residuals, the change in storage plus uncertainty, were −2,410 acre-feet in 2016, −18,410 acre-feet in 2021, and −3,610 acre-feet in 2023, and each subbasin had a mixture of negative and positive residuals. These basinwide results, interpreted as change in storage plus water-budget uncertainty, indicate minor net losses that increase with dry conditions, consistent with well depth-to-water measurements indicating gradual multi-decadal declines. Patterns in subbasin residuals are driven by irrigation practices and surface-water management; for example, the above Topaz subbasin relies more on groundwater for irrigation, resulting in more negative residuals during dry years. In contrast, the below Topaz subbasin depends more on surface water, producing positive residuals during dry years because of irrigation losses and canal seepage. The analyses for both subbasins indicate decades-long groundwater declines, which agree with the overall negative residuals calculated. The largest sources of uncertainty include climate inputs (precipitation and evapotranspiration) and poorly constrained components such as groundwater inflow and tributary stream infiltration. These findings provide insight into how climatic variables and irrigation practices affect groundwater inflows and outflows within the Portneuf River Basin.

Idaho↗