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This child item provides a snapshot of the watershed boundary dataset which consists of a shapefile with 87,020 12-digit hydrologic unit codes (HUC12) for the conterminous United States retrieved 10/26/2020. The National Watershed Boundary Dataset (WBD) is a comprehensive set of digital spatial data that represents the surface drainages areas of the United States. Although versions of the WBD are published as part of U.S. Geological Survey National Hydrography Products, the version used to produce the water-use reanalysis was not archived and is provided here. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Public-supply...
Nitrate removal by hydrogen-coupled denitrification was examined using flow-through, packed-bed bioreactors to develop a small-scale, cost effective system for treating nitrate-contaminated drinking-water supplies. Nitrate removal was accomplished using a Rhodocyclus sp., strain HOD 5, isolated from a sole-source drinking-water aquifer. The autotrophic capacity of the purple non-sulfur photosynthetic bacterium made it particularly adept for this purpose. Initial tests used a commercial bioreactor filled with glass beads and countercurrent, non-sterile flow of an autotrophic, air-saturated, growth medium and hydrogen gas. Complete removal of 2 mM nitrate was achieved for more than 300 days of operation at a 2-h retention...
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These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This data set represents the percent of orchards/vineyards land cover in the conterminous United States. The data set was used as an input data layer for a national model to predict nitrate concentration in ground water used for drinking. Nolan and Hitt (2006) developed two national models to predict contamination of ground water by nonpoint sources of nitrate. The nonlinear approach to national-scale Ground-WAter Vulnerability Assessment...
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This data release contains concentration and quality-assurance results for inorganic, organic analytes and microbiological pathogens collected from 30 different commercial bottled water sources. Samples were processed on July 20 and August 17, 2020 at the New Jersey Water Science Center and analyzed at various U.S. Geological Survey laboratories. Samples were analyzed for nutrients, cations and anions, trace elements and rare earth elements (REE) at the Redox Chemistry Laboratory and Analytical Trace Element Chemistry Laboratory in Boulder, Colorado; pharmaceutical, pesticide, per- and polyfluoroalkyl substances and volatile organic compounds at the National Water Quality Laboratory, Denver, Colorado; disinfection...
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This child item describes a machine learning model that was developed to estimate public-supply water use by service area boundary and 12-digit hydrologic unit code (HUC12) for the conterminous United States. This model was used to develop an annual and monthly public supply reanalysis of withdrawals for the period 2000-2020. This data release contains model input feature datasets, python codes used to develop and train the water use machine learning model, and output water use predictions by HUC12. This page includes the following files: PS_HUC12_Tot_2000_2020.csv - a csv file with monthly public supply reanalysis of withdrawals from 2000-2020 by HUC12 PS_HUC12_GW_2000_2020.csv - a csv file with estimated monthly...


map background search result map search result map Target-Chemical Concentrations and Microbiological Results for Assessment of Mixed Contaminant and Biological Exposures in Bottled Water, 2020 Vulnerability of shallow ground water and drinking-water wells to nitrate in the United States: Model of predicted nitrate concentration in U.S. ground water used for drinking (simulation depth 50 meters) -- Input data set for orchards/vineyards (gwava-dw_orvi) Machine learning model that estimates total monthly and annual per capita public-supply withdrawals National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020 Machine learning model that estimates total monthly and annual per capita public-supply withdrawals National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020 Vulnerability of shallow ground water and drinking-water wells to nitrate in the United States: Model of predicted nitrate concentration in U.S. ground water used for drinking (simulation depth 50 meters) -- Input data set for orchards/vineyards (gwava-dw_orvi) Target-Chemical Concentrations and Microbiological Results for Assessment of Mixed Contaminant and Biological Exposures in Bottled Water, 2020