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USGS2016

Spatiotemporal patterns of mercury accumulation in lake sediments of western North America

For the Western North America Mercury Synthesis, we compiled mercury records from 165 dated sediment cores from 138 natural lakes across western North America. Lake sediments are accepted as faithful recorders of historical mercury accumulation rates, and regional and sub-regional temporal and spatial trends were analyzed with descriptive and inferential statistics. Mercury accumulation rates in sediments have increased, on average, four times (4×) from 1850 to 2000 and continue to increase by approximately 0.2 μg/m 2 per year. Lakes with the greatest increases were influenced by the Flin Flon smelter, followed by lakes directly affected by mining and wastewater discharges. Of lakes not directly affected by point sources, there is a clear separation in mercury accumulation rates between lakes with no/little watershed development and lakes with extensive watershed development for agricultural and/or residential purposes. Lakes in the latter group exhibited a sharp increase in mercury accumulation rates with human settlement, stabilizing after 1950 at five times (5×) 1850 rates. Mercury accumulation rates in lakes with no/little watershed development were controlled primarily by relative watershed size prior to 1850, and since have exhibited modest increases (in absolute terms and compared to that described above) associated with (regional and global) industrialization. A sub-regional analysis highlighted that in the ecoregion Northwestern Forest Mountains, <1% of mercury deposited to watersheds is delivered to lakes. Research is warranted to understand whether mountainous watersheds act as permanent sinks for mercury or if export of “legacy” mercury (deposited in years past) will delay recovery when/if emissions reductions are achieved.

Alaska, Alberta, Arizona, British Columbia, Califo↗

USGS2023

Inland water greenhouse gas budgets for RECCAP2: 1. State-of-the-art of global scale assessments

Inland waters are important sources of the greenhouse gasses (GHGs) carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) to the atmosphere. In the framework of the 2 nd phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2) initiative, we review the state of the art in estimating inland water GHG budgets at global scale, which has substantially advanced since the first phase of RECCAP nearly ten years ago. The development of increasingly sophisticated upscaling techniques, including statistical prediction and process based models, allows for spatially explicit estimates which are needed for regionalized assessments of continental GHG budgets such as those established for RECCAP. A few recent estimates also resolve the seasonal and/or interannual variability in inland water GHG emissions. Nonetheless, the global-scale assessment of inland water emissions remains challenging because of limited spatial and temporal coverage of observations and persisting uncertainties in the abundance and distribution of inland water surface areas. To decrease these uncertainties, more empirical work on the contributions of hot-spots and hot-moments to overall inland water GHG emissions is particularly needed.

Global Biogeochemical Cycles↗

USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗

USGS2024

Composite estimation to combine spatially overlapping environmental monitoring surveys

Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015–18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming’s Greater Sage-Grouse ( Centrocercus urophasianus ) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ ( p <0.05) between the conservation areas compared to only six and seven indicators for the individual surveys. Overall, we found composite estimation to be an efficient and useful option for improving environmental monitoring information where two surveys entirely overlap and suggest how this estimation method could be beneficial where environmental surveys partially overlap and in small area applications.

Wyoming↗

USGS2014

Characterizing riverbed sediment using high-frequency acoustics 2: scattering signatures of Colorado River bed sediment in Marble and Grand Canyons

In this, the second of a pair of papers on the statistical signatures of riverbed sediment in high-frequency acoustic backscatter, spatially explicit maps of the stochastic geometries (length- and amplitude-scales) of backscatter are related to patches of riverbed surfaces composed of known sediment types, as determined by geo-referenced underwater video observations. Statistics of backscatter magnitudes alone are found to be poor discriminators between sediment types. However, the variance of the power spectrum, and the intercept and slope from a power-law spectral form (termed the spectral strength and exponent, respectively) successfully discriminate between sediment types. A decision-tree approach was able to classify spatially heterogeneous patches of homogeneous sands, gravels (and sand-gravel mixtures), and cobbles/boulders with 95, 88, and 91% accuracy, respectively. Application to sites outside the calibration, and surveys made at calibration sites at different times, were plausible based on observations from underwater video. Analysis of decision trees built with different training data sets suggested that the spectral exponent was consistently the most important variable in the classification. In the absence of theory concerning how spatially variable sediment surfaces scatter high-frequency sound, the primary advantage of this data-driven approach to classify bed sediment over alternatives is that spectral methods have well understood properties and make no assumptions about the distributional form of the fluctuating component of backscatter over small spatial scales.

Arizona↗

USGS2012

Hydrological information products for the Off-Project Water Program of the Klamath Basin Restoration Agreement

The Klamath Basin Restoration Agreement (KBRA) was developed by a diverse group of stakeholders, Federal and State resource management agencies, Tribal representatives, and interest groups to provide a comprehensive solution to ecological and water-supply issues in the Klamath Basin. The Off-Project Water Program (OPWP), one component of the KBRA, has as one of its purposes to permanently provide an additional 30,000 acre-feet of water per year on an average annual basis to Upper Klamath Lake through "voluntary retirement of water rights or water uses or other means as agreed to by the Klamath Tribes, to improve fisheries habitat and also provide for stability of irrigation water deliveries." The geographic area where the water rights could be retired encompasses approximately 1,900 square miles. The OPWP area is defined as including the Sprague River drainage, the Sycan River drainage downstream of Sycan Marsh, the Wood River drainage, and the Williamson River drainage from Kirk Reef at the southern end of Klamath Marsh downstream to the confluence with the Sprague River. Extensive, broad, flat, poorly drained uplands, valleys, and wetlands characterize much of the study area. Irrigation is almost entirely used for pasture. To assist parties involved with decisionmaking and implementation of the OPWP, the U.S. Geological Survey (USGS), in cooperation with the Klamath Tribes and other stakeholders, created five hydrological information products. These products include GIS digital maps and datasets containing spatial information on evapotranspiration, subirrigation indicators, water rights, subbasin streamflow statistics, and return-flow indicators. The evapotranspiration (ET) datasets were created under contract for this study by Evapotranspiration, Plus, LLC, of Twin Falls, Idaho. A high-resolution remote sensing technique known as Mapping Evapotranspiration at High Resolution and Internalized Calibration (METRIC) was used to create estimates of the spatial distribution of ET. The METRIC technique uses thermal infrared Landsat imagery to quantify actual evapotranspiration at a 30-meter resolution that can be related to individual irrigated fields. Because evaporation uses heat energy, ground surfaces with large ET rates are left cooler as a result of ET than ground surfaces that have less ET. As a consequence, irrigated fields appear in the Landsat images as cooler than nonirrigated fields. Products produced from this study include total seasonal and total monthly (April-October) actual evapotranspiration maps for 2004 (a dry year) and 2006 (a wet year). Maps showing indicators of natural subirrigation were also provided by this study. "Subirrigation" as used here is the evapotranspiration of shallow groundwater by plants with roots that penetrate to or near the water table. Subirrigation often occurs at locations where the water table is at or above the plant rooting depth. Natural consumptive use by plants diminishes the benefit of retiring water rights in subirrigated areas. Some agricultural production may be possible, however, on subirrigated lands for which water rights are retired. Because of the difficulty in precisely mapping and quantifying subirrigation, this study presents several sources of spatially mapped data that can be used as indicators of higher subirrigation probability. These include the floodplain boundaries defined by stream geomorphology, water-table depth defined in Natural Resources Conservation Service (NRCS) soil surveys, and soil rooting depth defined in NRCS soil surveys. The two water-rights mapping products created in the study were "points of diversion" (POD) and "place of use" (POU) for surface-water irrigation rights. To create these maps, all surface-water rights data, decrees, certificates, permits, and unadjudicated claims within the entire 1,900 square mile study area were aggregated into a common GIS geodatabase. Surface-water irrigation rights within a 5-mile buffer of the study area were then selected and identified. The POU area was then totaled by water right for primary and supplemental water rights. The maximum annual volume (acre-feet) allowed under each water right also was calculated using the POU area and duty (allowable annual irrigation application in feet). In cases where a water right has more than one designated POD, the total volume for the water right was equally distributed to each POD listed for the water right. Because of this, mapped distribution of diversion rates for some rights may differ from actual practice. Water-right information in the map products was from digital datasets obtained from the Oregon Water Resources Department and was, at the time acquired, the best available compilation of water-right information available. Because the completeness and accuracy of the water-right data could not be verified, users are encouraged to check directly with the Oregon Water Resources Department where specific information on individual rights or locations is essential. A dataset containing streamflow statistics for 72 subbasins in the study area was created for the study area. The statistics include annual flow durations (5-, 10-, 25-, 50-, and 95-percent exceedances) and 7-day, 10-year (7Q10) and 7-day, 2-year (7Q2) low flows, and were computed using regional regression equations based on measured streamflow records in the region. Daily streamflow records used were adjusted as needed for crop consumptive use; therefore the statistics represent streamflow under more natural conditions as though irrigation diversions did not exist. Statistics are provided for flow rates resulting from streamflow originating from within the entire drainage area upstream of the subbasin pour point (referring to the outlet of the contributing drainage basin). The statistics were computed for the purpose of providing decision makers with the ability to estimate streamflow that would be expected after water conservation techniques have been implemented or a water right has been retired. A final product from the study are datasets of indicators of the potential for subsurface return flow of irrigation water from agricultural areas to nearby streams. The datasets contain information on factors such as proximity to surface-water features, geomorphic floodplain characteristics, and depth to water. The digital data, metadata, and example illustrations for the datasets described in this report are available on-line from the USGS Water Resources National Spatial Data Infrastructure (NSDI) Node Website http://water.usgs.gov/lookup/getgislist or from the U.S. Government website DATA.gov at http://www.data.gov with links provided in a Microsoft® Excel® workbook in appendix A.

California;Oregon↗

USGS1997

Analysis of habitat selection studies with multiple patches within cover types

Current statistical methods are inadequate for evaluation of the relation between spatial pattern of the landscape and observed patterns of habitat use by individuals or populations. For example, traditional habitat selection analysis methods do not use information about the size and distribution of the several patches of each cover type that may exist within the study area. Statistical tests are presented for hypotheses about disproportional use of cover types and patches within cover types. These tests require that use of individual patches is recorded, as well as the size of individual patches. Different designs are considered in which there are (1) single or multiple samples of use, and (2) equal or unequal habitat availability. Formulas for calculating Type II statistical errors of the tests are presented and Monte Carlo simulation is used to assess the accuracy of the formulas and to check the Type I error rates of the proposed test statistics. With adequate sample sizes, Type II error formulas can be a useful tool for planning of habitat selection studies. An example analysis is presented of a hypothetical study of habitat selection by ring-necked pheasants ( Phasianus colchicus ) in a Midwestern landscape. The proposed tests also represent a contribution toward bringing together concepts of landscape ecology and wildlife habitat selection.

Journal of Wildlife Management↗

USGS2012

Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds

Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters ( Puffinus mauretanicus ) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.

Biological Conservation↗

USGS2010

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

Remote Sensing↗

USGS2021

Experimental evaluation of spatial capture–recapture study design

A principal challenge impeding strong inference in analyses of wild populations is the lack of robust and long-term data sets. Recent advancements in analytical tools used in wildlife science may increase our ability to integrate smaller data sets and enhance the statistical power of population estimates. One such advancement, the development of spatial capture–recapture (SCR) methods, explicitly accounts for differences in spatial study designs, making it possible to equate multiple study designs in one analysis. SCR has been shown to be robust to variation in design as long as minimal sampling guidance is adhered to. However, these expectations are based on simulation and have yet to be evaluated in wild populations. Here we conduct a rigorously designed field experiment by manipulating the arrangement of artificial cover objects (ACOs) used to collect data on red-backed salamanders ( Plethodon cinereus ) to empirically evaluate the effects of design configuration on inference made using SCR. Our results suggest that, using SCR, estimates of space use and detectability are sensitive to study design configuration, namely the spacing and extent of the array, and that caution is warranted when assigning biological interpretation to these parameters. However, estimates of population density remain robust to design except when the configuration of detectors grossly violates existing recommendations.

Massachusetts↗

USGS2019

Using scenarios to evaluate vulnerability of grassland communities to climate change in the Southern Great Plains of the United States

Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay). Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD? Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP. ScienceBase data release files that support this report are available at https://doi.org/10.5066/P9DGJHEP (Manier and others, 2019).

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗

USGS2013

Variability and trends in irrigated and non-irrigated croplands in the central U.S

Over 23 million hectares (233 thousand km 2 ) of U.S. croplands are irrigated and there was an overall net expansion of 522 thousand hectares nationally from 2002 to 2007. Most of this expansion occurred across the High Plains Aquifer (HPA) in the central Great Plains. Until recently, there has been a lack of geospatially-detailed irrigation data that are consistent, timely, geographically extensive, and periodic to support studies linking agricultural land use change to crop yields, aquifer water use, and other factors. We employed a modeling approach implemented at two time intervals (2002 and 2007) to map irrigated agriculture across the conterminous U.S. at a sub-county spatial detail (250 m 2 spatial resolution). The model integrated U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map. The geospatial model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US), was then used to depict detailed spatial patterns of irrigation change across the HPA from 2002 to 2007. Spatial changes in irrigation may result in shifts in local and regional climate, groundwater depletion, and higher crop yields and farm income. A closer investigation of irrigated corn across the HPA from 2000 to 2012 revealed even more variability through time, underscoring the need for more frequent periodic mapping of irrigated agriculture.

Conference Paper↗

USGS2009

Ground-water quality data in the Owens and Indian Wells Valleys study unit, 2006: Results from the California GAMA Program

Ground-water quality in the approximately 1,630 square-mile Owens and Indian Wells Valleys study unit (OWENS) was investigated in September-December 2006 as part of the Priority Basin Project of 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 collaboration with the California State Water Resources Control Board (SWRCB). The Owens and Indian Wells Valleys study was designed to provide a spatially unbiased assessment of raw ground-water quality within OWENS study unit, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 74 wells in Inyo, Kern, Mono, and San Bernardino Counties. Fifty-three of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and 21 wells were selected to evaluate changes in water chemistry in areas of interest (understanding wells). The ground-water samples were analyzed for a large number of synthetic organic constituents [volatile organic compounds (VOCs), pesticides and pesticide degradates, pharmaceutical compounds, and potential wastewater- indicator 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], radioactive constituents, and microbial indicators. Naturally occurring isotopes [tritium, and carbon-14, and stable isotopes of hydrogen and oxygen in water], and dissolved noble gases also were measured to help identify the source and age of the sampled ground water. This study evaluated the quality of raw ground water in the aquifer in the OWENS study unit and did not attempt to evaluate the quality of treated water delivered to consumers. Water supplied to consumers typically is treated after withdrawal from the ground, disinfected, and blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to treated 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 regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and non-regulatory thresholds established for aesthetic concerns (secondary maximum contamination levels, SMCL-CA) by CDPH. VOCs and pesticides were detected in samples from less than one-third of the grid wells; all detections were below health-based thresholds, and most were less than one-one hundredth of threshold values. All detections of perchlorate and nutrients in samples from OWENS were below health-based thresholds. Most detections of trace elements in ground-water samples from OWENS wells were below health-based thresholds. In samples from the 53 grid wells, three constituents were detected at concentrations above USEPA maximum contaminant levels: arsenic in 5 samples, uranium in 4 samples, and fluoride in 1 sample. Two constituents were detected at concentrations above CDPH notification levels (boron in 9 samples and vanadium in 1 sample), and two were above USEPA lifetime health advisory levels (molybdenum in 3 samples and strontium in 1 sample). Most of the samples from OWENS wells had concentrations of major elements, TDS, and trace elements below the non-enforceable standards set for aesthetic concerns. Samples from nine grid wells had concentrations of manganese, iron, or TDS above the SMCL-CAs.

California↗

USGS2009

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

Groundwater quality in the approximately 860-square-mile Madera–Chowchilla study unit (MADCHOW) was investigated in April and May 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 MADCHOW, and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 35 wells in Madera, Merced, and Fresno Counties. Thirty of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and five more were selected to provide additional sampling density to aid in understanding processes affecting groundwater quality (flow-path wells). Detection summaries in the text and tables are given for grid wells only, to avoid over-representation of the water quality in areas adjacent to flow-path wells. Groundwater samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOCs], low-level 1,2-dibromo-3-chloropropane [DBCP] and 1,2-dibromoethane [EDB], pesticides and pesticide degradates, polar pesticides and metabolites, and pharmaceutical compounds), constituents of special interest (N-nitrosodimethylamine [NDMA], perchlorate, and low-level 1,2,3-trichloropropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), and radioactive constituents (uranium isotopes, and gross alpha and gross beta particle activities). Naturally occurring isotopes and geochemical tracers (stable isotopes of hydrogen, oxygen, and carbon, and activities of tritium and carbon-14), and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, approximately 300 constituents and field water-quality indicators were investigated. Three types of quality-control samples (blanks, replicates, and samples for matrix spikes) each were collected at approximately 11 percent of the wells sampled for each analysis, and the results obtained from 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 data for the groundwater samples were not compromised by possible contamination during sample collection, handling or analysis. Differences between replicate samples were within acceptable ranges. 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 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 the California Department of Public Health (CDPH), and with aesthetic and technical thresholds established 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 regulatory thresholds. The concentrations of most constituents detected in groundwater samples from MADCHOW wells were below drinking-water thresholds. Organic compounds (VOCs and pesticides) were detected in about 40 percent of the samples from grid wells, and most concentrations were less than 1/100 of regulatory or non-regulatory health-based thresholds, although the concentrations of low-level DBCP in 10 percent and low-level EDB in 3 percent of the samples from grid wells were above the corresponding USEPA maximum contaminant levels (MCL-USs). Perchlorate was detected in 70 percent of the samples from grid wells, and most concentrations were less than one-tenth of the CDPH maximum contaminant level (MCL-CA). Low-level 1,2,3-TCP was detected in 33 percent of the samples from grid wells, and all concentrations were less than 1/1,000 of the USEPA lifetime health advisory level (HAL-US). Most concentrations of trace elements and nutrients in samples were below regulatory and non-regulatory health-based thresholds. Concentrations were above the MCL-US for nitrate in 7 percent of the samples from grid wells, for arsenic and uranium in 13 percent each of the samples from grid wells; and the concentration of vanadium was above the CDPH notification level (NL–CA) in 3 percent of the samples from grid wells. Detections of radioactive constituents were below regulatory and non-regulatory health-based thresholds in most samples. Combined activities of uranium isotopes were detected above the MCL-CA in 20 percent of the subset of 25 grid well samples analyzed, and gross alpha particle activity was detected above the MCL-US in 20 percent of the samples from the 30 total grid wells. Most of the samples from MADCHOW grid wells had concentrations of major and minor ions, total dissolved solids, and trace elements below the CDPH secondary maximum contaminant levels (SMCL-CAs), which are nonenforceable thresholds set for aesthetic and technical concerns. Twenty percent of the samples from grid wells contained specific-conductance values, or concentrations of chloride, total dissolved solids, or manganese above the respective SMCL–CAs.

California↗

USGS2024

Leveraging local wildlife surveys for robust occupancy trend estimation

Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers ( Pekania pennati ) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare ( N 0 = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace ( λ = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.

Idaho, Montana↗

USGS1993

Relationship of geological and geothermal field properties: Midcontinent area, USA, an example

Quantitative approaches to data analysis in the last decade have become important in basin modeling and mineral-resource estimation. The interrelation of geological, geophysical, geochemical, and geohydrological variables is important in adjusting a model to a real-world situation. Revealing the interdependences of variables can contribute in understanding the processes interacting in sedimentary basins. It is reasonably simple to compare spatial data of the same type but more difficult if different properties are involved. Statistical techniques, such as cluster analysis or principal components analysis, or some algebraic approaches can be used to ascertain the relations of standardized spatial data. In this example, structural configuration on five different stratigraphic horizons, one total sediment thickness map, and four maps of geothermal data were copared. As expected, the structural maps are highly related because all had undergone about the same deformation with differing degrees of intensity. The temperature gradients derived (1) from shallow borehole logging measurements under equilibrium conditions with the surrounding rock, and (2) from non-equilibrium bottom-hole temperatures (BHT) from deeper depths are mainly independent of each other. This was expected and confirmed also for the two temperature maps at 1000 ft which were constructed using both types of gradient values. Thus, it is evident that the use of a 2-point (BHT and surface temperature) straightline calculation of a mean temperature gradient gives different information about the geothermal regime than using gradients from temperatures logged under equilibrium conditions. Nevertheless, it is useful to determine to what a degree the larger dataset of nonequilibrium temperatures could reflect quantitative relationships to geologic conditions. Comparing all maps of geothermal information vs. the structural and the sediment thickness maps, it was determined that all correlations are moderately negative or slightly positive. These results are clearly shown by the cluster analysis and the principal components. Considering a close relationship between temperature and thermal conductivity of the sediments as observed for most of the Midcontinent area and relatively homogeneous heat-flow density conditions for the study area these results support the following assumptions: (1) undifferentiated geothermal gradients, computed from temperatures of different depth intervals and differing sediment properties, cannot contribute to an improved understanding of the temperature structure and its controls within the sedimentary cover, and (2) the quantitative approach of revealing such relations needs refined datasets of temperature information valid for the different depth levels or stratigraphic units. ?? 1993 International Association for Mathematical Geology.

Mathematical Geology↗

USGS2009

Groundwater quality data for the northern Sacramento Valley, 2007: Results from the California GAMA Program

Groundwater quality in the approximately 1,180-square-mile Northern Sacramento Valley study unit (REDSAC) was investigated in October 2007 through January 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 REDSAC and to facilitate statistically consistent comparisons of groundwater quality throughout California. Samples were collected from 66 wells in Shasta and Tehama Counties. Forty-three of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and 23 were selected to aid in evaluation of specific water-quality issues (understanding wells). The groundwater samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, and pharmaceutical compounds), constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial constituents. Naturally occurring isotopes (tritium, and carbon-14, and stable isotopes of nitrogen and oxygen in nitrate, stable isotopes of hydrogen and oxygen of water), and dissolved noble gases also were measured to help identify the sources and ages of the sampled ground water. In total, over 275 constituents and field water-quality indicators were investigated. Three types of quality-control samples (blanks, replicates, and sampmatrix spikes) were collected at approximately 8 to 11 percent of the wells, and the results for these samples 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 noticeable source of bias in the data for the groundwater samples. Differences between replicate samples were within acceptable ranges for nearly all compounds, indicating acceptably low variability. 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 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 groundwater were compared with regulatory and nonregulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and with aesthetic and technical thresholds established 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 from REDSAC were below drinking-water thresholds. Volatile organic compounds (VOC) and pesticides were detected in less than one-quarter of the samples and were generally less than a hundredth of any health-based thresholds. NDMA was detected in one grid well above the NL-CA. Concentrations of all nutrients and trace elements in samples from REDSAC wells were below the health-based thresholds except those of arsenic in three samples, which were above the USEPA maximum contaminant level (MCL-US). However, none of these wells were public-supply wells. Concentrations of all radioactive constituents were below health-based thresholds except radon-222, which was detected above the proposed MCL-US of 300 pCi/L in samples from 11 grid wells. Most of the samples from REDSAC wells had concentrations of major elements, total dissolved solids, and trace elements below the non-enforceable thresholds set for aesthetic or technical concerns. A few samples contained iron, manganese, or pH at levels above the SMCL-CA or SMCL-US thresholds.

California↗

USGS2009

Ground-Water Quality Data in the Coachella Valley Study Unit, 2007: Results from the California GAMA Program

Ground-water quality in the approximately 820 square-mile Coachella Valley Study Unit (COA) was investigated during February and March 2007 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 raw ground water used for public-water supplies within the Coachella Valley, and to facilitate statistically consistent comparisons of ground-water quality throughout California. Samples were collected from 35 wells in Riverside County. Nineteen of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells). Sixteen additional wells were sampled to evaluate changes in water chemistry along selected ground-water flow paths, examine land use effects on ground-water quality, and to collect water-quality data in areas where little exists. These wells were referred to as 'understanding wells'. The ground-water samples were analyzed for a large number of organic constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, pharmaceutical compounds, and potential wastewater-indicator compounds), constituents of special interest (perchlorate and 1,2,3-trichloropropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial indicators. Naturally occurring isotopes (uranium, tritium, carbon-14, and stable isotopes of hydrogen, oxygen, and boron), and dissolved noble gases (the last in collaboration with Lawrence Livermore National Laboratory) also were measured to help identify the source and age of the sampled ground water. A quality-control sample (blank, replicate, or matrix spike) was collected at approximately one quarter of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Assessment of the quality-control information resulted in V-coding less than 0.1 percent of the data collected. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, and (or) blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to treated water that is supplied 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 the California Department of Public Health (CDPH) and thresholds established for aesthetic purposes (secondary maximum contaminant levels, SMCL-CA) by CDPH. Most constituents detected in ground-water samples were at concentrations below drinking-water thresholds. Volatile organic compounds, pesticides, and pesticide degradates were detected in less than one-third of the grid well samples collected. All VOC and pesticide concentrations measured were below health-based thresholds. Potential waste-water indicators were detected in less than half of the wells sampled, and no detections were above health-based thresholds. Perchlorate was detected in seven grid wells; concentrations from two wells were above the CDPH maximum contaminant level (MCL-CA). Most detections of trace elements in samples collected from COA Study Unit wells were below water-quality thresholds. Exceptions include five samples of arsenic that were above the USEPA maximum contaminant level (MCL-US), two detections of boron above the CDPH notification level (NL-CA), and two detections of mol

Data Series↗