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USGS2011

Groundwater-quality data in the northern Coast Ranges study unit, 2009: Results from the California GAMA Program

Groundwater quality in the 633-square-mile Northern Coast Ranges (NOCO) study unit was investigated by the U.S. Geological Survey (USGS) from June to November 2009, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program's Priority Basin Project (PBP) and the U.S. Geological Survey National Water-Quality Assessment Program (NAWQA). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The NOCO study unit was the thirtieth study unit to be sampled as part of the GAMA-PBP. The GAMA Northern Coast Ranges study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer systems, and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer systems (hereinafter referred to as primary aquifers) are defined as that part of the aquifer corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the NOCO study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from the quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to surficial contamination. In the NOCO study unit, groundwater samples were collected from 58 wells in 2 study areas (Interior Basins and Coastal Basins) in Napa, Lake, Mendocino, Glenn, Humboldt, and Del Norte Counties. The 58 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study areas. GAMA-PBP wells sampled as part of the spatially-distributed, randomized grid-cell network are referred to as "grid wells."The groundwater samples were analyzed for organic and special-interest constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, and perchlorate), naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and alkalinity), radioactive constituents (radon-222, radium isotopes, gross alpha and gross beta radioactivity, lead-210, and polonium-210), and microbial indicators (F-specific and somatic coliphage, Escherichia coli [E. coli] and total coliform). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), and dissolved noble gases also were measured to identify the sources and ages of the sampled groundwater. In total, 239 constituents and 12 field water-quality indicators were measured. Three types of quality-control samples (blanks, replicates, and matrix-spikes) were collected at up to 12 percent of the wells in the NOCO study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 89 percent of the compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwa

Data Series↗

USGS2015

Spatial occupancy models for predicting metapopulation dynamics and viability following reintroduction

The reintroduction of a species into its historic range is a critical component of conservation programmes designed to restore extirpated metapopulations. However, many reintroduction efforts fail, and the lack of rigorous monitoring programmes and statistical models have prevented a general understanding of the factors affecting metapopulation viability following reintroduction. Spatially explicit metapopulation theory provides the basis for understanding the dynamics of fragmented populations linked by dispersal, but the theory has rarely been used to guide reintroduction programmes because most spatial metapopulation models require presence–absence data from every site in the network, and they do not allow for observation error such as imperfect detection. We develop a spatial occupancy model that relaxes these restrictive assumptions and allows for inference about metapopulation extinction risk and connectivity. We demonstrate the utility of the model using six years of data on the Chiricahua leopard frog Lithobates chiricahuensis , a threatened desert-breeding amphibian that was reintroduced to a network of sites in Arizona USA in 2003. Our results indicate that the model can generate precise predictions of extinction risk and produce connectivity maps that can guide conservation efforts following reintroduction. In the case of L. chiricahuensis , many sites were functionally isolated, and 82% of sites were characterized by intermittent water availability and high local extinction probabilities (0·84, 95% CI: 0·64–0·99). However, under the current hydrological conditions and spatial arrangement of sites, the risk of metapopulation extinction is estimated to be <3% over a 50-year time horizon. Low metapopulation extinction risk appears to result from the high dispersal capability of the species, the high density of sites in the region and the existence of predator-free permanent wetlands with low local extinction probabilities. Should management be required, extinction risk can be reduced by either increasing the hydroperiod of existing sites or by creating new sites to increase connectivity. Synthesis and applications . This work demonstrates how spatio-temporal statistical models based on ecological theory can be applied to forecast the outcomes of conservation actions such as reintroduction. Our spatial occupancy model should be particularly useful when management agencies lack the funds to collect intensive individual-level data.

Arizona, New Mexico↗

USGS2011

Geographic profiling to assess the risk of rare plant poaching in natural areas

We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities.

Environmental Management↗

USGS2011

Status of groundwater quality in the Southern, Middle, and Northern Sacramento Valley study units, 2005-08: California GAMA Priority Basin Project

Groundwater quality in the Southern, Middle, and Northern Sacramento Valley study units was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study units are located in California’s Central Valley and include parts of Butte, Colusa, Glenn, Placer, Sacramento, Shasta, Solano, Sutter, Tehama, Yolo, and Yuba 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 and the Lawrence Livermore National Laboratory. The three study units were designated to provide spatially-unbiased assessments of the quality of untreated groundwater in three parts of the Central Valley hydrogeologic province, as well as to provide a statistically consistent basis for comparing water quality regionally and statewide. Samples were collected in 2005 (Southern Sacramento Valley), 2006 (Middle Sacramento Valley), and 2007–08 (Northern Sacramento Valley). The GAMA studies in the Southern, Middle, and Northern Sacramento Valley were designed to provide statistically robust assessments of the quality of untreated groundwater in the primary aquifer systems that are used for drinking-water supply. The assessments are based on water-quality data collected by the USGS from 235 wells in the three study units in 2005–08, and water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer systems (hereinafter, referred to as primary aquifers) assessed in this study are defined by the depth intervals of the wells in the CDPH database for each study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to contamination from the surface. The status of the current quality of the groundwater resource was assessed by using data from samples analyzed for volatile organic compounds (VOC), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. This status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the three Sacramento Valley study units, not the treated drinking water delivered to consumers by water purveyors. Relative-concentrations (sample concentrations divided by 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. For organic (volatile organic compounds and pesticides) and special-interest (perchlorate) constituents, relative-concentrations were classified as high (greater than 1.0); moderate (equal to or less than 1.0 and greater than 0.1); or low (equal to or less than 0.1). For inorganic (major ion, trace element, nutrient, and radioactive) constituents, the boundary between low and moderate relative-concentrations was set at 0.5. Aquifer-scale proportions were used in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifers that have 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 percentage of the primary aquifers that have moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based, which used one value per grid cell, and spatially-weighted, which used the full dataset—were used to calculate aquifer-scale proportions for individual constituents and classes of constituents. High and moderate aquifer-scale proportions were significantly greater for inorganic constituents than organic constituents in all three study units. In the Southern Sacramento Valley study unit, relative-concentrations for one or more inorganic constituents with health-based benchmarks (HBBs) were high in 30 percent (%), moderate in 30%, and low in 40% of the primary aquifer. In the Middle Sacramento Valley study unit, aquifer-scale proportions for inorganic constituents with HBBs were high in 24%, moderate in 38%, and low in 38% of the primary aquifer. Arsenic, boron, and nitrate were detected at high relative-concentrations in the Southern and Middle Sacramento Valley study units. In the Northern Sacramento Valley study unit, high, moderate, and low relative-concentrations of inorganic constituents relative to HBBs were 2.1, 12, and 86% of the primary aquifer, respectively. Arsenic was the only constituent detected at high relative-concentrations. The high aquifer-scale proportions for inorganic constituents with non-health-based benchmarks were 32, 27, and 4.6% of the primary aquifer for the Southern, Middle, and Northern Sacramento Valley study units, respectively. The high aquifer-scale proportions for organic constituents with HBBs were less than 1% in the Southern, Middle, and Northern Sacramento Valley study units. Organic constituents were detected at moderate relative-concentrations in about 3% of the Southern and Middle Sacramento Valley study units and in 1% of the Northern Sacramento Valley study unit. Of the 227 organic constituents analyzed for, 86 were detected, and of those detected, 56 have HBBs. Six organic constituents (atrazine, bentazon, chloroform, simazine, tetrachloroethene, and trichloroethene) were detected in 10% or more of the sampled wells in one or more of the three Sacramento Valley study units.

California↗

USGS2010

Groundwater-quality data in the Colorado River study unit, 2007: Results from the California GAMA Program

Groundwater quality in the 188-square-mile Colorado River Study unit (COLOR) was investigated October through December 2007 as part of the Priority Basin Project of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Project was developed in response to the Groundwater Quality Monitoring Act of 2001, and the U.S. Geological Survey (USGS) is the technical project lead. The Colorado River study was designed to provide a spatially unbiased assessment of the quality of raw groundwater used for public water supplies within COLOR, and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 28 wells in three study areas in San Bernardino, Riverside, and Imperial Counties. Twenty wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the Study unit; these wells are termed ‘grid wells’. Eight additional wells were selected to evaluate specific water-quality issues in the study area; these wells are termed ‘understanding wells.’ The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOC], gasoline oxygenates and degradates, pesticides and pesticide degradates, pharmaceutical compounds), constituents of special interest (perchlorate, 1,4-dioxane, and 1,2,3-trichlorpropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), and radioactive constituents. Concentrations of naturally occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water), and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, approximately 220 constituents and water-quality indicators were investigated. Quality-control samples (blanks, replicates, and matrix spikes) were collected at approximately 30 percent of the wells, and the results were used to evaluate the quality of the data obtained from the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a significant source of bias in the data. Differences between replicate samples were within acceptable ranges and matrix-spike recoveries were within acceptable ranges for most compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, raw groundwater typically is treated, disinfected, or blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to water that is served to the consumer, not to raw groundwater. However, to provide some context for the results, concentrations of constituents measured in the raw groundwater were compared to regulatory and nonregulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and the California Department of Public Health (CDPH) and to thresholds established for aesthetic concerns by CDPH. Comparisons between data collected for this study and drinking-water thresholds are for illustrative purposes only and do not indicate compliance or noncompliance with those thresholds. The concentrations of most constituents detected in groundwater samples were below drinking-water thresholds. Volatile organic compounds (VOC) were detected in approximately 35 percent of grid well samples; all concentrations were below health-based thresholds. Pesticides and pesticide degradates were detected in about 20 percent of all samples; detections were below health-based thresholds. No concentrations of constituents of special interest or nutrients were detected above health-based thresholds. Most of the major and minor ion constituents sampled do not have health-based thresholds; the exception is chloride. Concentrations of chloride, sulfate, and total dissolved solids detected in some of the well samples were above the nonenforceable thresholds for aesthetic concerns. Concentrations of fluoride were detected in 5 samples (from 4 grid wells and 1 understanding well) above the maximum contaminant level for California (MCL-CA). Concentrations of most of the trace elements in samples from the COLOR study were below health-based thresholds; exceptions included arsenic above the MCL-US, boron above the notification level for California (NL-CA), iron and manganese above the secondary maximum contaminant level for California (SMCL-CA), and molybdenum and strontium above the lifetime health advisory level (HAL-US) threshold. Most detections of radioactive constituents were below health-based thresholds; exceptions were alpha, uranium, and radon radioactivity. Alpha radioactivity with 72 hour count detections occurred in four grid wells and one understanding well, and 30-day count detections in two grid wells above the MCL-US. Uranium was detected twice in grid wells above the MCL-US threshold. Also, radon-222 was detected at concentrations above the proposed MCL-US in 19 samples (14 grid and 5 understanding wells). No radon-222 was detected above the proposed MCL-US upper threshold.

California↗

USGS2009

Groundwater-quality data in the Antelope Valley study unit, 2008: Results from the California GAMA Program

Groundwater quality in the approximately 1,600 square-mile Antelope Valley study unit (ANT) was investigated from January to April 2008 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Project was developed in response to the Groundwater Quality Monitoring Act of 2001, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The study was designed to provide a spatially unbiased assessment of the quality of raw groundwater used for public water supplies within ANT, and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 57 wells in Kern, Los Angeles, and San Bernardino Counties. Fifty-six of the wells were selected using a spatially distributed, randomized, grid-based method to provide statistical representation of the study area (grid wells), and one additional well was selected to aid in evaluation of specific water-quality issues (understanding well). The groundwater samples were analyzed for a large number of organic constituents (volatile organic compounds [VOCs], gasoline additives and degradates, pesticides and pesticide degradates, fumigants, and pharmaceutical compounds), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), and radioactive constituents (gross alpha and gross beta radioactivity, radium isotopes, and radon-222). Naturally occurring isotopes (strontium, tritium, and carbon-14, and stable isotopes of hydrogen and oxygen in water), and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, 239 constituents and water-quality indicators (field parameters) were investigated. Quality-control samples (blanks, replicates, and samples for matrix spikes) were collected at 12 percent of the wells, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a noticeable source of bias in the data for the groundwater samples. Differences between replicate samples generally were within acceptable ranges, indicating acceptably low variability. Matrix spike recoveries were within acceptable ranges for most compoundsThis study did not evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to raw groundwater. However, to provide some context for the results, concentrations of constituents measured in the raw groundwater were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. Comparisons between data collected for this study and drinking-water thresholds are for illustrative purposes only, and are not indicative of compliance or non-compliance with drinking water standards. Most constituents that were detected in groundwater samples were found at concentrations below drinking-water thresholds. Volatile organic compounds (VOCs) were detected in about one-half of the samples and pesticides detected in about one-third of the samples; all detections of these constituents were below health-based thresholds. Most detections of trace elements and nutrients in samples from ANT wells were below health-based thresholds. Exceptions include: one detection of nitrite plus nitrate as nitrogen (NO 2 +NO 3 ) above the USEPA maximum contaminant level (MCL-US: 10 mg/L), five detections of arsenic above the MCL-US (6 μg/L), one detection of boron above the CDPH notification level (NL-CA: 1,000 μg/L), and two detections of vanadium above the NL-CA (50 μg/L). Most detections of radioactive constituents were below health-based thresholds. Exceptions include two detections of gross alpha radioactivity (72-hour and 30-day counts) above the MCL-US (15 pCi/L). Also, radon-222 was detected above the proposed MCL-US (300 pCi/L) in 14 grid wells and the understanding well, but no wells had detections above the proposed alternative MCL-US (4,000 pCi/L). Most of the samples from ANT wells had concentrations of major elements, total dissolved solids (TDS), and trace elements below the non-enforceable thresholds set for aesthetic concerns. Three samples contained sulfate and four samples contained total dissolved solids at concentrations above the SMCL-CA thresholds (250 mg/L and 500 mg/L, respectively). Two of the total dissolved solids detections were above the upper SMCL-CA (1,000 mg/L). Samples from four wells had field pH values above the SMCL-US (>pH 8.5). Field-measured specific conductance values were above the SMCL-CA (900 μS/cm at 25°C) at eight wells with four of these measurements above the upper SMCL-CA threshold (1,600 μS/cm at 25°C).

California↗

USGS2017

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Ecosphere↗

USGS2016

Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations

Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses ( Equus caballus ) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.

Colorado, Nevada, Utah, Wyoming↗

USGS2014

Groundwater-quality data in seven GAMA study units: results from initial sampling, 2004-2005, and resampling, 2007-2008, of wells: California GAMA Program Priority Basin Project

The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The GAMA-PBP began sampling, primarily public supply wells in May 2004. By the end of February 2006, seven (of what would eventually be 35) study units had been sampled over a wide area of the State. Selected wells in these first seven study units were resampled for water quality from August 2007 to November 2008 as part of an assessment of temporal trends in water quality by the GAMA-PBP. The initial sampling was designed to provide a spatially unbiased assessment of the quality of raw groundwater used for public water supplies within the seven study units. In the 7 study units, 462 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study area. Wells selected this way are referred to as grid wells or status wells. Approximately 3 years after the initial sampling, 55 of these previously sampled status wells (approximately 10 percent in each study unit) were randomly selected for resampling. The seven resampled study units, the total number of status wells sampled for each study unit, and the number of these wells resampled for trends are as follows, in chronological order of sampling: San Diego Drainages (53 status wells, 7 trend wells), North San Francisco Bay (84, 10), Northern San Joaquin Basin (51, 5), Southern Sacramento Valley (67, 7), San Fernando–San Gabriel (35, 6), Monterey Bay and Salinas Valley Basins (91, 11), and Southeast San Joaquin Valley (83, 9). The groundwater samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOCs], pesticides, and pesticide degradates), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally-occurring inorganic constituents (nutrients, major and minor ions, and trace elements). Naturally-occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. Nearly 300 constituents and water-quality indicators were investigated. Quality-control samples (blanks, replicates, and samples for matrix spikes) were collected at 24 percent of the 55 status wells resampled for trends, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a noticeable source of bias in the data for the groundwater samples. Differences between replicate samples were mostly within acceptable ranges, indicating acceptably low variability in analytical results. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for 75 percent of the compounds for which matrix spikes were collected. This study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and blended with other waters to maintain acceptable water quality. The benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH). Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most constituents that were detected in groundwater samples from the trend wells were found at concentrations less than drinking-water benchmarks. Four VOCs—trichloroethene, tetrachloroethene, 1,2-dibromo-3-chloropropane, and methyl tert-butyl ether—were detected in one or more wells at concentrations greater than their health-based benchmarks, and six VOCs were detected in at least 10 percent of the samples during initial sampling or resampling of the trend wells. No pesticides were detected at concentrations near or greater than their health-based benchmarks. Three pesticide constituents—atrazine, deethylatrazine, and simazine—were detected in more than 10 percent of the trend-well samples during both sampling periods. Perchlorate, a constituent of special interest, was detected more frequently, and at greater concentrations during resampling than during initial sampling, but this may be due to a change in analytical method between the sampling periods, rather than to a change in groundwater quality. Another constituent of special interest, 1,2,3-TCP, was also detected more frequently during resampling than during initial sampling, but this pattern also may not reflect a change in groundwater quality. Samples from several of the wells where 1,2,3-TCP was detected by low-concentration-level analysis during resampling were not analyzed for 1,2,3-TCP using a low-level method during initial sampling. Most detections of nutrients and trace elements in samples from trend wells were less than health-based benchmarks during both sampling periods. Exceptions include nitrate, arsenic, boron, and vanadium, all detected at concentrations greater than their health-based benchmarks in at least one well during both sampling periods, and molybdenum, detected at concentrations greater than its health-based benchmark during resampling only. The isotopic ratios of oxygen and hydrogen in water and tritium and carbon-14 activities generally changed little between sampling periods, suggesting that the predominant sources and ages of groundwater in most trend wells were consistent between the sampling periods.

California↗

USGS2015

Groundwater quality data in 15 GAMA study units: results from the 2006–10 Initial sampling and the 2009–13 resampling of wells, California GAMA Priority Basin Project

The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). From May 2004 to March 2012, the GAMA-PBP collected samples from more than 2,300 wells in 35 study units across the State. Selected wells in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. This triennial (every 3 years) trend sampling of GAMA-PBP study units concluded in December 2013. Fifteen of the study units, initially sampled between January 2006 and June 2010 and sampled a second time between April 2009 and April 2013 to assess temporal trends, are the subject of this report. The initial sampling was designed to provide a spatially unbiased assessment of the quality of untreated groundwater used for public water supplies in the 15 study units. In these study units, 730 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the areas assessed (grid wells, also called “status wells”). Approximately 3 years after the initial sampling, 93 of the previously sampled status wells (approximately 10 percent in each study unit) were randomly selected for trend sampling (“trend wells”). The 15 study units sampled for trends were distributed among 4 hydrogeologic provinces: Central Valley, Basin and Range, Desert, and Transverse and selected Peninsular Ranges. The total number of status wells sampled, along with those sampled again for trends, varied by study unit. In the Central Valley hydrogeologic province, the numbers of status wells and trend wells in each study unit were as follows: Kern County subbasin study unit—47 status wells, 5 trend wells Central Eastside San Joaquin Basin study unit—58 status wells, 6 trend wells Middle Sacramento Valley study unit—71 status wells, 8 trend wells Northern Sacramento Valley study unit—43 status wells, 4 trend wells Madera–Chowchilla study unit—30 status wells, 4 trend wells Western San Joaquin Valley study unit—39 status wells, 4 trend wells. The Basin and Range hydrogeologic province had only one study unit: Owens and Indian Wells Valleys study unit—53 status wells, 6 trend wells. In the Desert hydrogeologic province, the numbers of wells were as follows: Coachella Valley study unit—19 status wells 4 trend wells Colorado River study unit—20 status wells, 3 trend wells Antelope Valley study unit—56 status wells, 6 trend wells Mojave study unit—52 status wells, 7 trend wells Borrego Valley, Central Desert and Low-Use Basins of the Mojave and Sonoran Deserts study unit—49 status wells, 6 trend wells. In the Transverse and Selected Peninsular Ranges hydrogeologic province, the numbers of wells were as follows: Coastal Los Angeles Basin study unit—61 status wells, 8 trend wells Upper Santa Ana Watershed study unit—90 status wells, 16 trend wells Santa Clara River Valley study unit—42 status wells, 6 trend wells. The groundwater samples were analyzed for a number of synthetic organic constituents (volatile organic compounds, pesticides, and pesticide degradates), constituents of special interest (perchlorate, N -nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements). Naturally occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. More than 200 constituents and water-quality indicators were investigated. Quality-control samples (blanks, replicates, or samples for matrix spikes) were collected at 34 percent of the trend wells, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. On the basis of detections in laboratory and field blanks in samples from GAMA-PBP study units, including the study units presented here, some groundwater results were adjusted in this report. Differences between replicate samples were mostly within acceptable ranges, indicating acceptably low variability in analytical results. Median matrix-spike recoveries were within the acceptable range (70 to 130 percent) for 189 of the 224 compounds for which matrix spikes were analyzed (84 percent). This study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater used for drinking water typically is treated, disinfected, and blended with other waters to attain acceptable water quality. The benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency and California Department of Public Health. Comparisons between data collected for this study and benchmarks for drinking-water quality are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most constituents that were detected in groundwater samples from the trend wells were found at concentrations less than drinking-water benchmarks. Two volatile organic compounds (VOCs)—tetrachloroethene and trichloroethene—were detected in samples from one or more wells at concentrations greater than their health-based benchmarks, and three VOCs—chloroform, tetrachloroethene, and trichloroethene—were detected in at least 10 percent of the trend-well samples from the initial sampling period and the later trend sampling period. No pesticides were detected at concentrations near or greater than their health-based benchmarks. Three pesticide constituents—atrazine, deethylatrazine, and simazine—were detected in more than 10 percent of the trend-well samples in both sampling periods. Perchlorate, a constituent of special interest, was detected at a concentration greater than its health-based benchmark in samples from one trend well in the initial sampling and trend sampling periods, and in an additional trend well sample only in the trend sampling period. Most detections of nutrients, major and minor ions, and trace elements in samples from trend wells were less than health-based benchmarks in both sampling periods. Exceptions included nitrate, fluoride, arsenic, boron, molybdenum, strontium, and uranium; these were all detected at concentrations greater than their health-based benchmarks in at least one well sample in both sampling periods. Lead and vanadium were detected above their health-based benchmarks in one sample each collected in the initial sampling period only. The isotopic ratios of oxygen and hydrogen in water and the activities of tritium and carbon-14 generally changed little between sampling periods.

California↗

USGS2022

Characterization of ambient groundwater quality within a statewide, fixed-station monitoring network in Pennsylvania, 2015–19

Pennsylvania leads the Nation in the number of individuals that use groundwater for private domestic water supply; more than 3 million rural and suburban Pennsylvania residents rely on private domestic supplies for drinking water. These supplies are not regulated nor routinely monitored; thus relevant groundwater-quality information is not widely available. The U.S. Geological Survey (USGS), in cooperation with the Pennsylvania Department of Environmental Protection (PaDEP) Safe Drinking Water Bureau, established a statewide, fixed-station ambient groundwater quality network in 2015. The goals for the Pennsylvania Groundwater Monitoring Network (GWMN) include characterizing ambient groundwater quality conditions in rural areas of the State and documenting potential changes in conditions over time. Seventeen wells were selected for monitoring at 6-month intervals beginning in 2015. Since then, several wells have been added to the GWMN, bringing the total number of wells sampled in the fall of 2019 to 28. Routinely monitored constituents included physical characteristics and chemical concentrations in filtered and unfiltered samples (major and trace elements, nutrients, and organic compounds). Samples for volatile organic compounds (VOCs), radionuclides, and dissolved hydrocarbon gases were collected during the first sampling event at each well. To offer insights on the quality of groundwater used for domestic supply in Pennsylvania, summary statistics for the 221 GWMN samples collected during 2015–19 are compared to U.S. Environmental Protection Agency (EPA) drinking-water standards, which are applicable to public water supplies. Results show that samples across the GWMN generally meet drinking-water standards for inorganic and organic constituents; however, a percentage of samples had concentrations that exceeded maximum contaminant level (MCL) thresholds for nitrate (3 percent) and secondary maximum contaminant level (SMCL) thresholds for iron (32 percent), manganese (36 percent), and aluminum (5 percent). Radon-222 activities, which were sampled only during the initial visit to a well, exceeded the lower proposed drinking water standard of 300 picocuries per liter (pCi/L) in 64 percent of wells in the GWMN; additionally, 7 percent of wells exceeded the higher proposed standard of 4,000 pCi/L. There were no exceedances for VOCs, but one well had a tribromomethane detection. Three wells had detectable concentrations of methane, with one sample exceeding the Pennsylvania action level of 7 milligrams per liter (mg/L). The pH and dissolved oxygen concentrations varied widely across the GWMN and were correlated with dissolved metal concentrations and other chemical characteristics of groundwater samples. Considering all samples collected for the study, the pH ranged from 4.2 to 8.3; 42 percent of pH values were either above or below the SMCL range of 6.5–8.5. The highest pH values resulted from contamination of loose grout used in the construction of one well and decreased to levels consistent with other wells in the vicinity after repeated sampling rounds. Dissolved oxygen (DO), which ranged from 0 to 13.9 mg/L, influences the mobility and prevalence of constituents with variable oxidation state, including iron, manganese, and nitrogen species. Samples with acidic pH (less than 6.5) and (or) low DO had the highest concentrations of manganese and iron, whereas those with neutral to alkaline pH values had the highest concentrations of calcium, magnesium, sodium, and other major ions. Analysis of major ions indicates that calcium/bicarbonate water types are the most common, with a few characterized as calcium/chloride or sodium/chloride, and most others as mixed water types including calcium-magnesium/bicarbonate, sodium-magnesium/bicarbonate, and sodium/bicarbonate-chloride. Nonparametric statistical methods were used to evaluate the data for spatial and temporal trends. A principal components analysis (PCA) model developed with ranked data values for the entire network resulted in three components, (1) dissolved solids, (2) redox, and (3) sodium-chloride, which explained 74.5 percent of variance in the dataset. On the basis of individual contributions to the PCA, certain wells were identified through hierarchical cluster analysis that shared relevant water-quality characteristics. The spatial distribution of sampling locations and the temporal trends of constituent concentrations indicate that hydrogeologic setting and topographic position as defined in the PCA model are important factors affecting the spatial and temporal patterns of groundwater quality in the GWMN.

Pennsylvania↗

USGS2023

Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables

The Mississippi Alluvial Plain, located in the south-central United States, is undergoing long-term groundwater-level declines within the surficial Mississippi River Valley alluvial aquifer (hereinafter referred to as “alluvial aquifer”), which has raised concerns about future groundwater availability. In some parts of the alluvial aquifer, groundwater availability for common uses such as irrigation, public supply, and domestic use is limited by quality (for example, high salinity) rather than quantity of water stored in the aquifer. The Mississippi Alluvial Plain region has an abundance of water-quality measurements in the alluvial aquifer and deeper aquifers; however, large areas lack direct measurements of salinity to evaluate regional groundwater availability. Statistical models can interpolate between wells to fill in spatial data gaps. In 2021, the U.S. Geological Survey trained two boosted regression tree (BRT) machine-learning models on specific conductance data available between 1942 and 2020 to predict spatially continuous surfaces of groundwater salinity at multiple depths for the alluvial aquifer and deeper aquifers. Well construction information, water levels, and surficial variables such as geomorphology and soils were included as explanatory variables in this baseline model. Additionally, subsurface electrical resistivity data from the first aquifer-wide aerial electromagnetic (AEM) survey for the region were incorporated to create a geophysical model. This work expands on prior BRT salinity predictions of the alluvial aquifer and extends predictions south to the Gulf of Mexico, where groundwater salinity is high. AEM survey data were not available for the southern extent of the alluvial aquifer at the time of modeling. A BRT model was trained without (baseline) and with (geophysical) AEM variables to test the ability of the models to predict salinity where explanatory data are missing and response data are sparse. Additionally, model sensitivity to AEM survey data was evaluated to better understand how AEM variables influence specific conductance predictions. Model performance was improved with the addition of geophysical data, which added three-dimensional information, thereby improving salinity predictions at depth. Groundwater specific conductance predictions can help inform other geophysical investigations in the southern extent of the study area, where high groundwater specific conductance can obfuscate changes in aquifer sediment resistivity and could limit groundwater resources for agricultural, public supply, and domestic uses.

Scientific Investigations Report↗

USGS2001

Summary of water-quality data, October 1987 through September 1997, for Fountain and Monument Creeks, El Paso and Pueblo Counties, Colorado

Fountain and Monument Creeks, which drain parts of El Paso and Pueblo Counties in Colorado, have been sampled systematically by the U.S. Geological Survey for many years to obtain records of water-quality properties and constituents; the data are stored in the National Water Inventory System. Statistical summaries of these data indicate that they have spatial and temporal trends. Comparison of water-quality data to in-stream regulatory standards, some of which were calculated in this report, indicate that some exceedances are widespread in the system and that some occur locally. Nonparametric tests to quantitatively detect monotonic trends in water-quality data indicate that many water-quality properties and constituents do not have significant monotonic trends; detected trends were mostly downward.

Water-Resources Investigations Report↗

USGS2020

Good practices for species distribution modeling of deep-sea corals and sponges for resource management: Data collection, analysis, validation, and communication

Resource managers in the United States and worldwide are tasked with identifying and mitigating trade-offs between human activities in the deep sea (e.g., fishing, energy development, and mining) and their impacts on habitat-forming invertebrates, including deep-sea corals and sponges (DSCS). Related management decisions require information about where DSCS occur and in what densities. Species distribution modeling (SDM) provides a cost-effective means of identifying potential DSCS habitat over large areas to inform these management decisions and data collection. Here we describe good practices for DSCS SDM, especially in the context of data collection and management applications. Managers typically need information regarding DSCS encounter probabilities, densities, and sizes, defined at sub-regional to basin-wide scales and validated using subsequent, targeted data collections. To realistically achieve these goals, we suggest analysts: 1) integrate available data sources in SDMs including fine-scale visual sampling and broad-scale resource surveys (e.g., fisheries trawl surveys); and 2) include environmental predictor variables representing multiple spatial scales, model residual spatial autocorrelation, and quantify prediction uncertainty. When possible, models fitted to presence-absence and density data are preferred over models fitted only to presence data, which are difficult to validate and can confound estimated probability of occurrence or density with sampling effort. Ensembles of models can provide robust predictions, while multi-species models leverage information across taxa and facilitate community inference. To facilitate the use of models by managers, predictions should be expressed in units that are widely understood and validated at an appropriate spatial scale using a sampling design that provides strong statistical inference. We present three case studies for the Pacific Ocean that illustrate good practices with respect to data collection, modeling, and validation; these case studies demonstrate it is possible to implement our good practices in real-world settings.

Frontiers in Marine Science↗

USGS1991

Application of the FINDER system to the search for epithermal vein gold-silver deposits : Kushikino, Japan, a case study

The FINDER system employs geometric probability, Bayesian statistics, and the normal probability density function to integrate spatial and frequency information to produce a map of probabilities of target centers. Target centers can be mineral deposits, alteration associated with mineral deposits, or any other target that can be represented by a regular shape on a two dimensional map. The size, shape, mean, and standard deviation for each variable are characterized in a control area and the results applied by means of FINDER to the study area. The Kushikino deposit consists of groups of quartz-calcite-adularia veins that produced 55 tonnes of gold and 456 tonnes of silver since 1660. Part of a 6 by 10 km area near Kushikino served as a control area. Within the control area, data plotting, contouring, and cluster analysis were used to identify the barren and mineralized populations. Sodium was found to be depleted in an elliptically shaped area 3.1 by 1.6 km, potassium was both depleted and enriched locally in an elliptically shaped area 3.0 by 1.3 km, and sulfur was enriched in an elliptically shaped area 5.8 by 1.6 km. The potassium, sodium, and sulfur content from 233 surface rock samples were each used in FINDER to produce probability maps for the 12 by 30 km study area which includes Kushikino. High probability areas for each of the individual variables are over and offset up to 4 km eastward from the main Kushikino veins. In general, high probability areas identified by FINDER are displaced from the main veins and cover not only the host andesite and the dacite-andesite that is about the same age as the Kushikino mineralization, but also younger sedimentary rocks, andesite, and tuff units east and northeast of Kushikino. The maps also display the same patterns observed near Kushikino, but with somewhat lower probabilities, about 1.5 km east of the old gold prospect, Hajima, and in a broad zone 2.5 km east-west and 1 km north-south, centered 2 km west of the old gold prospect, Yaeyama.

Geoinformatics↗

USGS2022

The occupancy-abundance relationship and sampling designs using occupancy to monitor populations of Asian bears

Designing a population monitoring program for Asian bears presents challenges associated with their low densities and detectability, generally large home ranges, and logistical or resource constraints. The use of an occupancy-based method to monitor bear populations can be appropriate under certain conditions given the mechanistic relationship between occupancy and abundance. The form of the occupancy–abundance relationship is dependent on species-specific characteristics such as home range size and population density, as well as study area size. To assess the statistical power of tests to detect population change of Asian bears, we conducted a study using a range of scenarios by simulating spatially explicit individual-based capture-recapture data from a demographically open model. Simulations assessed the power to detect changes in population density via changes in site-level occupancy or abundance through time, estimated using a standard occupancy model or a Royle-Nichols model, both with point detectors (representing camera traps). We used IUCN Red List criteria as a guide in selection of two population decline scenarios (20% and 50%), but we chose a shorter time horizon (10 years = 1 bear generation), meaning that declines were steeper than used for IUCN criteria (3 generations). Our simulations detected population declines of 50% with high power (>0.80) and low false positive rates (FPR: incorrectly detecting a decline) (<0.10) when detectors were spaced at > 0.67 times the home range diameter (home-range spacing ratio: HRSR, a measure of spatial correlation), such that bears would tend to overlap no more than two detectors. There was high (0.85) correlation between realized occupancy and N in these scenarios. The FPR increased as the HRSR decreased because of spatial correlation in the occupancy process induced when individual home ranges overlap multiple detectors. The mean statistical power to detect more gradual population declines (20% in 10 years) with HRSR > 0.67 was low for occupancy models 0.22 (maximum power 0.67) and Royle-Nichols models (0.24; maximum power 0.67), suggesting that declines of this magnitude may not be described reliably with 10 years of monitoring. Our results demonstrated that under many realistic scenarios that we explored, false positive rates were unacceptably high. We highlight that when designing occupancy studies, the spacing between point detectors be at least 0.67 times the diameter of the home range size of the larger sex (e.g., males) when the assumptions of the spatial capture-recapture model used for simulation are met.

Global Ecology and Conservation↗

USGS2009

Groundwater quality data in the Mojave study unit, 2008: Results from the California GAMA Program

Groundwater quality in the approximately 1,500 square-mile Mojave (MOJO) study unit was investigated from February to April 2008, as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Project was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). MOJO was the 23rd of 37 study units to be sampled as part of the GAMA Priority Basin Project. The MOJO study was designed to provide a spatially unbiased assessment of the quality of untreated ground water used for public water supplies within MOJO, and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 59 wells in San Bernardino and Los Angeles Counties. Fifty-two of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and seven were selected to aid in evaluation of specific water-quality issues (understanding wells). The groundwater samples were analyzed for a large number of organic constituents [volatile organic compounds (VOCs), pesticides and pesticide degradates, and pharmaceutical compounds], constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]) naturally occurring inorganic constituents (nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and trace elements), and radioactive constituents (gross alpha and gross beta radioactivity, radium isotopes, and radon-222). Naturally occurring isotopes (stable isotopes of hydrogen, oxygen, and carbon, stable isotopes of nitrogen and oxygen in nitrate, and activities of tritium and carbon-14), and dissolved noble gases also were measured to help identify the sources and ages of the sampled ground water. In total, over 230 constituents and water-quality indicators (field parameters) were investigated. Three types of quality-control samples (blanks, replicates, and matrix spikes) each were collected at approximately 5–8 percent of the wells, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a significant source of bias in the data for the groundwater samples. Differences between replicate samples generally were within acceptable ranges, indicating acceptable analytical reproducibility. Matrix spike recoveries were within acceptable ranges for most compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to untreated ground water. However, to provide some context for the results, concentrations of constituents measured in the untreated ground water were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and thresholds established for aesthetic and technical concerns by CDPH. Comparisons between data collected for this study and thresholds for drinking-water are for illustrative purposes only, and are not indicative of compliance or non-compliance with those thresholds. Most constituents that were detected in groundwater samples in the 59 wells in MOJO were found at concentrations below drinking-water thresholds. In MOJO’s 52 grid wells, volatile organic compounds (VOCs) were detected in 40 percent of the wells, and pesticides and pesticide degradates were detected in 23 percent of the grid wells. Results for health-based thresholds in MOJO grid wells showed that all of the detections of organic compounds in samples from MOJO grid wells were below health-based thresholds, with the exception of a single detection of NDMA above the California Department of Public Health notification level (NL-CA). Trace elements and radioactive constituents were sampled for at 19 MOJO grid wells and most detections were below health-based thresholds. Exceptions include: six detections of arsenic above the USEPA maximum contaminant level (MCL-US), two detections of boron and one detection of vanadium above the NL-CA, one detection each of molybdenum and strontium that were above the USEPA lifetime health advisory level (HAL-US), and one detection of fluoride just above the MCL-CA of 2 µg/L. Most detections of radioactive constituents in the MOJO grid wells were below health-based thresholds, with the exception of one detection of gross alpha radioactivity (72-hour count and 30-day count) above the MCL-CA, and 17 grid wells (of 19 sampled) that had activities of radon-222 above the proposed MCL-US of 300 pCi/L, but all were below the proposed alternative MCL-US of 4,000 pCi/L. All of the samples collected from the 19 MOJO grid wells for trace elements, and most of the samples for major ions and total dissolved solids (TDS), had measured concentrations below the non-enforceable thresholds set for aesthetic concerns. Four grid wells had TDS concentrations above the California Department of Public Health secondary maximum contaminant level (SMCL-CA) recommended threshold of 500 mg/L, and three of these wells were also above the SMCL-CA upper threshold of 1,000 mg/L. Four grid wells (of 19 sampled) had sulfate measured at concentrations above the recommended SMCL-CA threshold of 250 mg/L, and one of these detections was also above the upper SMCL-CA threshold of 500 mg/L. One grid well had chloride levels at a concentration above the upper SMCL-CA threshold of 500 mg/L. Eleven grid wells (of 52 sampled) had pH values outside of the SMCL-US range for pH.

California↗

USGS2008

Ground-water quality data in the Central Sierra study unit, 2006— Results from the California GAMA Program

Ground-water quality in the approximately 950 square kilometer (370 square mile) Central Sierra study unit (CENSIE) was investigated in May 2006 as part of the Priority Basin Assessment project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Assessment project was developed in response to the Ground-Water Quality Monitoring Act of 2001, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). This study was designed to provide a spatially unbiased assessment of the quality of raw ground water used for drinking-water supplies within CENSIE, and to facilitate statistically consistent comparisons of ground-water quality throughout California. Samples were collected from thirty wells in Madera County. Twenty-seven of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and three were selected to aid in evaluation of specific water-quality issues (understanding wells). Ground-water samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOCs], gasoline oxygenates and degradates, pesticides and pesticide degradates), constituents of special interest (N-nitrosodimethylamine, perchlorate, and 1,2,3-trichloropropane), naturally occurring inorganic constituents [nutrients, major and minor ions, and trace elements], radioactive constituents, and microbial indicators. Naturally occurring isotopes [tritium, and carbon-14, and stable isotopes of hydrogen, oxygen, nitrogen, and carbon], and dissolved noble gases also were measured to help identify the sources and ages of the sampled ground water. In total, over 250 constituents and water-quality indicators were investigated. Quality-control samples (blanks, replicates, and samples for matrix spikes) were collected at approximately one-sixth of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Results from field blanks indicated contamination was not a noticeable source of bias in the data for ground-water samples. Differences between replicate samples were within acceptable ranges, indicating acceptably low variability. Matrix spike recoveries were within acceptable ranges for most constituents. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH), and thresholds established for aesthetic concerns (Secondary Maximum Contaminant Levels, SMCL-CA) by CDPH. Therefore, any comparisons of the results of this study to drinking-water standards only is for illustrative purposes and is not indicative of compliance or non-compliance to those standards. Most constituents that were detected in ground-water samples were found at concentrations below drinking-water standards or thresholds. Six constituents? fluoride, arsenic, molybdenum, uranium, gross-alpha radioactivity, and radon-222?were detected at concentrations higher than thresholds set for health-based regulatory purposes. Three additional constituents?pH, iron and manganese?were detected at concentrations above thresholds set for aesthetic concerns. Volatile organic compounds (VOCs) and pesticides, were detected in less than one-third of the samples and generally at less than one one-hundredth of a health-based threshold.

California↗